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  • Published: 13 February 2023

Immunotherapy in breast cancer: an overview of current strategies and perspectives

  • Véronique Debien 1 ,
  • Alex De Caluwé   ORCID: orcid.org/0000-0001-5989-7017 2 ,
  • Xiaoxiao Wang 3 ,
  • Martine Piccart-Gebhart   ORCID: orcid.org/0000-0001-9068-8504 4 ,
  • Vincent K. Tuohy 5 ,
  • Emanuela Romano   ORCID: orcid.org/0000-0002-1574-5545 6 &
  • Laurence Buisseret   ORCID: orcid.org/0000-0002-3751-0819 3 , 7  

npj Breast Cancer volume  9 , Article number:  7 ( 2023 ) Cite this article

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  • Breast cancer

Recent progress in immunobiology has led the way to successful host immunity enhancement against breast cancer. In triple-negative breast cancer, the combination of cancer immunotherapy based on PD-1/PD-L1 immune checkpoint inhibitors with chemotherapy was effective both in advanced and early setting phase 3 clinical trials. These encouraging results lead to the first approvals of immune checkpoint inhibitors in triple-negative breast cancer and thus offer new therapeutic possibilities in aggressive tumors and hard-to-treat populations. Furthermore, several ongoing trials are investigating combining immunotherapies involving immune checkpoint inhibitors with conventional therapies and as well as with other immunotherapeutic strategies such as cancer vaccines, CAR-T cells, bispecific antibodies, and oncolytic viruses in all breast cancer subtypes. This review provides an overview of immunotherapies currently under clinical development and updated key results from clinical trials. Finally, we discuss the challenges to the successful implementation of immune treatment in managing breast cancer and their implications for the design of future clinical trials.

Introduction

Cancer immunotherapy represents one of the most significant advances in oncology in recent years. It has demonstrated impressive anti-tumor activity and a durable clinical benefit in diverse malignancies with recent success in triple-negative breast cancer (TNBC). Historically considered poorly immunogenic, breast cancer (BC) was initially not extensively investigated for its susceptibility to immunotherapy. However, recent breakthroughs with immune checkpoint inhibitors (ICI) in other cancers coupled with increasing evidence of the influence of the immune system in cancer behavior, have led to the development of clinical trials evaluating different types of immune therapeutic strategies for BC patients. The presence of tumor-infiltrating lymphocytes (TILs) in the tumor microenvironment (TME) reflects a pre-existing anti-tumor immune response and is associated with a better prognosis and response to chemotherapy 1 . The immune response captured through immune-related tumor gene expression in microarray-based analyses also demonstrated that immune gene signatures were associated with a favorable clinical outcome, particularly in TNBC and Human Epidermal Growth factor Receptor 2 (HER2)-positive BC 2 , 3 . In using immunophenotyping analyses or transcriptomic approaches, different immune cell subsets were identified in the TME and their participation in a pro- or anti-tumor immune response has been demonstrated given their influence on BC clinical outcomes 4 . Among CD8+ T cells, the cytotoxic subpopulation is able to kill cancer cells and is associated with improved survival in patients, whereas the presence of immunosuppressive regulatory CD4+ T cells (Tregs) or macrophages is associated with a worse prognosis 4 .

The extent and composition of immune infiltrates are highly variable between BC subtypes and within each subtype 5 , 6 . Therefore, it is expected that not all BC patients would benefit from the same immunotherapeutic strategy to restore or elicit an anti-tumor immune response 5 . Predictive biomarkers are required to select patients and tailor therapies beyond the established BC subtypes. Programmed death-ligand 1 (PD-L1) immunohistochemistry (IHC) expression is the most widely used biomarker, but not sufficient, as it only appears to have predictive value in metastatic TNBC (mTNBC). Tumor mutational burden (TMB) is a marker of tumor foreignness and immunogenicity, as mutated antigens are recognized by T cells to initiate a cytotoxic response. Mutational load is highly variable in BC, and tumors that present high TMB may respond more favorably to ICI 7 . Tumor antigens have also been investigated in vaccination strategies, as demonstrated by the increasing number of clinical trials evaluating the preventive and therapeutic effects of cancer vaccines. Emerging modalities such as bispecific antibodies (BsAbs) or adoptive cell therapies involving TILs or chimeric antigen receptor T (CAR-T) cells are an area of current research.

This review describes recent advances in immunotherapy to treat BC and summarizes the challenges of implementing such treatments in a heterogeneous disease. We also present a comprehensive overview of the immunotherapeutic combinations currently investigated in clinical trials.

Clinical landscape and update of early results

The clinical development of immunotherapy in BC started more than 20 years ago, but it is only with the discovery of ICI that number of clinical trials testing immunotherapeutic strategies increased (Fig. 1A ) 8 . In January 2022, 745 immunotherapy-based trials enrolling patients with solid tumors, including BC, were identified on clinicaltrials.gov , with 450 (60.4%) exclusively dedicated to BC. Interestingly, our analysis shows a constant increase in the development of vaccines in the last 20 years, whereas more recent immunotherapeutic approaches increased exponentially since 2015 (Fig. 1A ).

figure 1

Panels A – C show the number of clinical trials in breast cancer since early 2000, by immunotherapeutic approach ( A ), by trial setting ( B ), and by trial phase ( C ). Panel D shows the major immune targets. Only targets present in two or more trials are represented. The complete list of targets is available in online Supplementary Table 1 . Panel E shows the histogram of combination trials with PD-1/PD-L1 ICI backbone. ADC antibody-drug conjugates, ICI immune checkpoint inhibitors, mAbs monoclonal antibodies, Neo-adj neoadjuvant.

The number of trials is increasing both in the advanced setting and in early BC. In 2018, the number of neoadjuvant trials exceeded the number of adjuvant trials (Fig. 1B ), and a shift of phase 1 trials towards phase 2 and 3 trials is clearly observed (Fig. 1C ). Of note, the large phase 3 trials are sponsored by pharmaceutical companies, whereas the observed rise of phase 2 investigator-initiated studies indicates an enhanced global effort to investigate novel immunotherapy strategies.

The most studied co-inhibitory receptor is programmed death-1 (PD-1). Multiple monoclonal antibodies (mAbs) targeting PD-1 or its ligand PD-L1 have been developed (Fig. 1D ). Other molecules targeting immune checkpoints to prevent the inhibition of T cells (e.g., CTLA-4, LAG3, and TIGIT) or to stimulate T cells and increase their cytotoxic activity (e.g., OX-40 and 4-1BB) are being tested. HER2 represents the most studied target for vaccines but is also used by BsAbs and other directed therapies (Fig. 1D ). Recently, new combination strategies beyond ICI aiming to increase response rates (RR) and clinical benefit have been initiated with the hope of improving survival outcomes (Fig. 1E ).

Immune checkpoint combinations

Metastatic breast cancer.

In early phase trials, PD-1/PD-L1 ICI was primarily evaluated in monotherapy, enrolling heavily pretreated metastatic patients 9 . The response rates (RR) were only 5–20%, with increased efficacy in patients with PD-L1-positive TNBC, lower tumor burden, and non-visceral disease 10 . Nevertheless, few responders achieved long-lasting responses with survival benefit 11 , 12 . However, the KEYNOTE-119 trial, in which pembrolizumab monotherapy was compared to chemotherapy, failed to improve overall survival (OS) beyond the first line in mTNBC (Table 1 ) 13 .

Higher RR were observed with ICI combined with chemotherapy as first-line therapy in advanced TNBC, leading to randomized phase 3 trials in this setting 10 , 14 . The IMpassion130 trial demonstrated a gain of 2.5 months in progression-free survival (PFS) for patients treated with atezolizumab plus nab-paclitaxel whose tumors have PD-L1 ≥1% immune cells with the VENTANA SP142 immunohistochemistry (IHC) assay 15 . Based on these results, atezolizumab received accelerated approval from the United States Food and Drug Administration (FDA) in March 2019. However, FDA approval for atezolizumab was later withdrawn due to a lack of clinical benefit, because the final PFS and first OS interim analyses in the intention-to-treat (ITT) population did not cross the boundary for statistical significance 16 . The initially planned testing procedure was hierarchical, meaning that the analysis in the PD-L1 positive subgroup could be tested only if the primary endpoint in the overall cohort was met. Therefore, the OS results suggesting a survival benefit in the PD-L1 positive subgroup results must be interpreted with caution. Furthermore, the IMpassion131 trial enrolled a similar population but evaluated the combination of atezolizumab with paclitaxel (instead of nab-paclitaxel), and it also failed to demonstrate an improved outcome (neither PFS nor OS) even in the PD-L1-positive subgroup (Table 1 ) 17 . The use of immunosuppressive steroids for premedication to prevent hypersensitivity reactions with paclitaxel has been incriminated in these discordant results. In the ongoing IMpassion132 trial enrolling TNBC patients with early relapses (<12 months), the chemotherapy partners are carboplatin and gemcitabine or capecitabine 18 . In the KEYNOTE-355 trial, pembrolizumab was used in combination with paclitaxel, nab-paclitaxel, or gemcitabine plus carboplatin in first-line therapy for patients with mTNBC. The primary PFS results led to the approval of the drug by the FDA in November 2020 for patients with PD-L1-positive tumors 19 . Recently, the OS benefit was confirmed in patients with a PD-L1 combined positive score (CPS) ≥10 assessed by the IHC 22C3 pharmDx test 20 .

In luminal BC, the first attempts to combine ICI and chemotherapy were disappointing. In initial trials, no improved outcomes were reported, such as in a phase 2 study evaluating eribulin with or without pembrolizumab in metastatic luminal BC 21 . Results are expected from ongoing studies investigating the safety and efficiency of ICI in combination with endocrine therapies and Cyclin D Kinase 4/6 inhibitors (CDK4/6i). In preclinical models, CDK4/6i enhanced tumor antigen presentation, decreased Tregs proliferation, and modulated T cell activation by reducing the expression of inhibitory receptors such as PD-1 22 , 23 . The phase 1b trial, evaluating the combination of abemaciclib with pembrolizumab with or without endocrine therapy in ER-positive metastatic BC, with or without anastrozole, were complicated by increased hepatic toxicity, interstitial lung disease, and two toxic death in the triplet arm 24 . In contrast, the triple association of letrozole, palbociclib, and pembrolizumab was well tolerated in a phase 1/2 trial 25 .

In metastatic HER2-positive BC, the combination of trastuzumab with pembrolizumab showed a 15% RR in patients with trastuzumab-resistant PD-L1-positive tumors 26 . In combination with T-DM1, atezolizumab did not improve PFS but increased toxicity 27 .

Poly ADP ribose polymerase (PARP) inhibitors can lead to DNA damage and genomic instability, which could increase cancer cell immunogenicity and enhance the sensitivity to immunotherapies 28 . In BRCA-deficient BC, the combination of ICI with PARP inhibitors is under investigation. The RR (objective RR or disease control rate) was promising in two phases 2 trials evaluating the combination of durvalumab and olaparib or pembrolizumab and niraparib in first-line or pretreated patients with germline BRCA1 or BRCA2 mutations (Table 1 ) 29 , 30 .

Early breast cancer

Although many questions remain unanswered in the metastatic setting, several trials examined the use of immunotherapy in early BC. In theory, the early setting could be more appropriate for immunotherapy as the tumor burden is more limited, the biological background is more homogeneous, and the TME is less immunosuppressive and unimpacted by previous systemic treatments 31 . The majority of trials in early BC are now conducted in a neoadjuvant rather than in an adjuvant setting (Fig. 1B ) because it offers the advantage of evaluating the clinical and imaging response before surgery and the pathological response after surgery, the latter being a possible surrogate endpoint for the long-term clinical benefit 32 . Moreover, the presence of the primary tumor could serve as a source of neoantigens. Notably, in preclinical models, the neoadjuvant immunotherapeutic approach demonstrated enhanced efficacy compared with the adjuvant setting 33 .

Similarly, as with metastatic disease, the majority of neoadjuvant trials were conducted in the TNBC subtype. In the landmark phase 3 KEYNOTE-522 trial, stage II and III patients received neoadjuvant chemotherapy (NACT) associated with pembrolizumab or placebo concomitant with NACT and then continued in the adjuvant setting 34 . The pathological complete response (pCR) rates were superior in the experimental arm (64.8 vs. 51.2%), and the overall pCR benefit was more significant for patients with node-positive disease (∆ pCR rate of 20.6 vs. 6.3%) (Table 1 ). The estimated event-free survival (EFS) rate at 36 months favored the pembrolizumab-chemotherapy combination (HR = 0.63, 95% CI 0.48–0.82, absolute gain 7.7%) 34 . The combination of neoadjuvant pembrolizumab plus chemotherapy, followed by adjuvant pembrolizumab, is an FDA-approved regimen for early TNBC as of July 2021.

While the KEYNOTE-522 trial used paclitaxel with carboplatin followed by anthracycline with cyclophosphamide every 3 weeks, combined with an anti-PD-1, the neoadjuvant trials IMpassion031 and GeparNUEVO combined nab-paclitaxel with an anti-PD-L1 (atezolizumab or durvalumab) 35 , 36 , 37 . The NeoTRIPaPDL1 trial combined nab-paclitaxel with carboplatin without anthracyclines in the neoadjuvant setting 37 . In IMpassion031, the addition of atezolizumab to nab-paclitaxel followed by dose-dense anthracycline-based chemotherapy resulted in a significant increase in pCR rate: 41 vs. 58%, (∆ pCR rate 17%, 95% CI 6–27, one-side p  = 0.0044) (Table 1 ) 35 . However, NeoTRIPaPDL1 and GeparNUEVO trials could not demonstrate a substantial increase in pCR rates, highlighting the complexity of comparing different trials 37 , 38 . Even if there had been no difference in pCR rates in the GeparNUEVO trial, the addition of durvalumab to NACT significantly improved 3-year disease-free survival (DFS) and OS, questioning the validity of pCR as a surrogate endpoint in neoadjuvant immunotherapy trials (Table 1 ) 38 . Interestingly, pCR was only improved in patients treated in the window-of-opportunity part, in which durvalumab was given for 2 weeks before starting chemotherapy. Contrarily to the metastatic setting, PD-L1 IHC expression was not predictive of pCR, while TIL levels and dynamic TILs increase were associated with a better response in the retrospective analyses of KEYNOTE-173, GeparNuevo, and NeoTRIPaPDL1 trials 7 , 37 , 39 .

Less data were available for luminal and HER2-positive BC 40 , 41 , 42 . In phase 2 adaptively randomized I-SPY2 trial, adding pembrolizumab to NACT (weekly paclitaxel followed by doxorubicin-cyclophosphamide) was shown to be beneficial amongst patients with HER2-negative BC 40 . Pembrolizumab increased the pCR rate from 13 to 30% in luminal BC, which is a notable result given that in the metastatic setting, no benefit of ICI was found in this subtype. Nevertheless, compared to TNBC, the chemotherapy-ICI combination seems to generate lower pCR rates in luminal cancer, as expected, given its ‘colder’ immune phenotype. The ongoing phase 3 KEYNOTE-756 trial will shed light on the possible benefit of adding ICI to chemotherapy in grade III luminal BC 42 . The use of priming agents to elicit an immune response might be necessary to turn cold luminal BC into hot tumors 43 . For example, radiation therapy, which is a DNA-damaging agent, can be used to induce T cell priming via antigenic release and MHC-I upregulation. In addition, radiation activates innate immunity through several mechanisms, such as dendritic cells (DCs) activation 44 . This strategy is under evaluation in the Neo-CheckRay trial in luminal B MammaPrint high-risk BC 45 . The neoadjuvant chemotherapy-free strategy with ICI combined with endocrine therapy and CDK4/6i for luminal early BC resulted in increased hepatic toxicity 46 .

In HER2-positive BC, the randomized placebo-controlled phase 3 study IMpassion050 that evaluated the addition of atezolizumab to NACT and dual anti-HER2 blockade did not induce a significant increase in pCR rate in ITT nor PD-L1 positive population 47 . In addition, the median EFS, a secondary endpoint, was not reached in both arms 48 .

Fewer studies are being conducted in the adjuvant and post-neoadjuvant settings (Fig. 1B ). Indeed, larger sample sizes are required as well as a longer follow-up, therefore exposing more patients with potentially curable BC to a hypothetically effective and potentially toxic experimental treatment. Of note, the continuation of ICI after neoadjuvant chemotherapy is still unclear in the context of post-neoadjuvant therapies with capecitabine in TNBC and olaparib for patients with germline BRCA1 or BRCA2 mutations 49 , 50 .

Longer follow-up will help to better delineate the benefit versus harm ratio of ICI, which will ultimately dictate the optimal use of immunotherapeutic approaches in early BC. Although the safety profiles with ICI in BC clinical trials were comparable to clinical trials in other tumor types, the risk of long-term side effects in patients treated with curative intent should be taken into consideration as some immune-related adverse events (irAE) could be responsible for chronic diseases 51 , 52 . Moreover, some irAE should be carefully assessed in the perioperative period, particularly endocrine toxicity such as hypopituitarism with the potential risk of adrenal crisis during or after surgical intervention 51 , 53 .

Breast cancer vaccines

When the FDA approved trastuzumab in 1998 as the first monoclonal antibody for cancer treatment, the entire approach to cancer therapy changed. Ever since, there has been a relentless focus on HER2 as a predominant therapeutic target for HER2-positive cancers. However, despite the effectiveness of HER2 as a target for antibody-mediated receptor antagonism, it has met with conflicting and often perplexing results as a cancer vaccine target.

HER2 is a large molecule; therefore, most of the human HER2 cancer vaccines target one or more of the following three HER2-derived peptides: (1) E75 (Nelipepimut-S, NP-S, HER2 369–377, or NeuVax), an HLA-A2-restricted non-peptide derived from the extracellular domain of HER2 and designed to activate CD8+ T cells; (2) GP2 (HER2 654–662), another HLA-A2-restricted nonapeptide derived from the transmembrane domain of HER2 and also designed to activate CD8+ T cells in an HLA-A2-restricted manner; and (3) AE37 (HER2 776–790) an MHC class-II restricted 12-mer peptide derived from the intracellular domain of HER2 but modified by the addition of the four amino acids long Ii-Key peptide LRMK for enhancing the activation of CD4+ T cells 54 .

The results of phase 1/2 trials involving vaccination of BC patients with one or more of these HER2 peptides showed no significant clinical benefit, but exploratory subgroup analyses surprisingly indicated that patients with HER2-low-expressing tumors, including TNBC patients, may have derived a clinical benefit 55 , 56 . However, a subsequent phase 3 clinical trial involving E75 vaccination of patients, including TNBC patients, with node-positive HER2-low expressing breast tumors was stopped early when an interim analysis of the trial data showed that there was no significant difference in the primary endpoint of DFS between E75 vaccinated and placebo vaccinated subjects 57 .

Despite the confounding use of a HER2 vaccine in patients with HER2-low and HER2-negative BC, treatment of mTNBC with AE37 peptide vaccination has continued (NSABP FB-14). Moreover, a dendritic cell vaccine targeting HER2 and HER3, has been used to treat TNBC patients with brain metastases 58 . Further confusing the area, a recent meta-analysis of 24 clinical studies involving a total of 1704 vaccinated patients and 1248 control subjects found that E75 vaccination caused significant improvement in disease recurrence rate and DFS but no significant difference in OS 59 . One can only speculate how a vaccine targeting HER2 could possibly be effective in treating patients with HER2-negative tumors but not HER2-positive tumors, yet the confounding saga of HER2 vaccination continues.

The HER2 vaccine story certainly reveals the frustration that clinical investigators have had in finding a targeted treatment for TNBC, a BC subtype that expresses none of the traditional targets for BC therapy, including estrogen and progesterone receptors, and HER2. Moreover, TNBCs overexpress several non-HER2 tumor-associated antigens (TAAs), many of which have been the focus of numerous cancer vaccine clinical trials.

Perhaps the most commonly targeted non-HER2 TAAs for cancer vaccination have been the cancer-testis antigens (CTAs). These proteins are normally expressed in embryonic stem cells and testicular germ cells, minimally expressed in most other normal tissues but often expressed at high levels in many different tumors 60 . Several hundred CTAs have been identified, and many have served as targets in vaccination involving patients with TNBC 61 . Perhaps the most notable is cancer/testis antigen 1B (NY-ESO-1) 62 . Several other CTAs have been targeted in the vaccination of TNBC patients, including Wilms’ tumor protein (WT1) 63 , 64 the melanoma antigen gene protein-12 (MAGE-12), the folate receptor alpha (FRα), the T-box transcription factor brachyury 65 and the tumor suppressor transcription factor p53 66 .

One of the more interesting TAAs for targeting TNBC is Mucin 1 (MUC1), a hyperglycosylated, immunologically unavailable protein in many normal epithelial cells but a hypoglycosylated, immunologically available protein in several malignant tumors, including TNBC 67 . Several MUC1 vaccines have been tested in TNBC clinical trials. A number of cancer vaccines that target multiple TAAs have been developed for therapy against TNBC, including the PVX-410 vaccine that consists of peptides derived from the transcription factor X-box binding protein 1 (XBP1), the plasma cell marker syndecan-1 (CD138), and the NK cell receptor CD319 (CS1), as well as STEMVAC, a DNA vaccine encoding multiple peptides of CD105 (Endoglin), Y-box binding protein 1 (Yb-1), SRY-box 2 (SOX2), cadherin 3 (CDH3), and murine double minute 2 (MDM2) proteins. In addition, the vaccine-based immunotherapy regimen-2 (VBIR-2) has been used to treat patients with non-small cell lung cancer (NSCLC) and patients with TNBC, and apparently consists of several immunomodulators as well as multiple vaccinations against prostate-specific antigen (PSA), prostate-specific membrane antigen (PSMA), and prostate stem cell antigen (PSCA). Vaccination against PSMA and the preferentially expressed antigen in melanoma (PRAME) has also been used to treat TNBC patients 68 .

It is important to note that not all TNBC vaccines target TAA proteins. Indeed, tumor-associated carbohydrate (TAC) antigens that are frequently poor immunogens can be targeted using molecular mimic peptides or mimotopes that induce antibodies that cross-react with the human TAC antigen 69 . Such a mimotope vaccine called P10s-PADRE is currently being tested in clinical stage I-III TNBC patients. In addition, a vaccine that targets a non-protein hexasaccharide with a ceramide attached to its terminal glucose ring, the Globo H glycosphingolipid antigen, has reached phase 3 clinical trial status in patients with Globo H+ TNBC tumors 70 .

Despite decades of intense efforts using therapeutic cancer vaccines, the results have been modest or confounding at best. However, much has been learned about immunology in the past several decades, and recent cancer vaccine strategies may prove to be more effective than prior generations of cancer vaccines. Individual tumors have their own set of distinct mutations, many of which have the potential to be highly immunogenic for each individual patient. Such mutated proteins are called neoantigens, and recent clinical trials have focused on isolating these neoantigens and vaccinating individual TNBC test subjects with personalized neoantigen vaccines that include traditional vaccine/adjuvant combinations, vaccination with DNA-based vaccines, vaccination involving autologous dendritic cells, and even mRNA vaccination.

Finally, in light of the very successful prophylactic childhood vaccination program against infectious diseases, one may wonder why TNBC cancer vaccines have long been exclusively treatment vehicles 71 . Even when vaccines are used to prevent the recurrence of pre-existing tumors, they are still treatment vehicles. However, it has recently been proposed that vaccination against the human lactation protein, α-lactalbumin, may provide safe and effective primary prevention of TNBC because α-lactalbumin is a “retired” self-protein that is expressed exclusively in the breast only during late pregnancy and lactation but is expressed in >70% of TNBCs 72 . Thus, preemptive α-lactalbumin immunity provided to women at high risk for developing TNBC due to carrying mutations in their BRCA1 genes 73 may provide safe and effective primary prevention of TNBC as long as lactation is avoided. A phase 1 clinical trial to start this clinical testing process has very recently been initiated, with the first patient vaccinated in 2021. Thus, perhaps the focus of cancer vaccinations in the future may be to provide therapeutic immunity in a personalized manner to multiple neoantigens or to provide neoantigen or ‘retired’ self-protein immunity preemptively for the greatest effectiveness.

Other immunotherapeutic strategies under development

Adoptive cell therapies (ACTs) consist of identifying and isolating peripheral blood or tumor-resident T cells in order to modify, activate and expand these cells ex vivo before transferring them back into the patient 74 . ACTs can be classified into TIL-based therapies, T cell receptor (TCR) gene therapy, and CAR-T cells. The latter technology has already provided prolonged responses and remissions for patients with advanced hematological malignancies 75 .

First attempts to reintroduce autologous lymphokine-activated lymphocytes to treat patients with advanced solid tumors were undertaken years ago without relevant results in BC patients 76 . Of note, clinical trials evaluating ACTs were conducted in early phase trials enrolling a small number of patients, including very few with BC 77 . Recently, infusion of autologous activated lymphocytes against specific tumor antigens was demonstrated able to induce a long-lasting response in a patient with chemotherapy-refractory luminal metastatic BC treated with mutant-protein-specific TILs in conjunction with IL-2 and pembrolizumab 78 . In a study evaluating the feasibility of c-MET CAR-T cells, the best response was a stable disease for only one patient with ER-positive HER2-negative disease among the six patients with metastatic BC 79 . In solid tumors, the development of ACTs has been hampered by the heterogeneity of the antigenic landscape, the hostile TME conditions, and the lack of T cell infiltration in the tumor nests. Several strategies are under development to overcome these issues. Thus, promising CAR-T cell targets like HER2, MUC1, or Mesothelin have been identified for the treatment of BC patients 80 . The identification of neoantigens and the use of other immune cell types, such as NK cells or DCs offer new opportunities for ACTs.

Another challenge to develop ACTs is the toxicities related to lymphodepletion and to immune-mediated side effects such as neurotoxicity and cytokine release syndrome, two potentially lethal conditions. Cytokine release syndrome is a systemic inflammatory response with organ dysfunction that can be reversible if promptly diagnosed and managed 81 . In addition to the management of these toxicities, the complexity of manufacturing ACTs limits the development of cellular therapy programs in specialized cancer centers 82 .

Another type of engineered molecule are BsAbs designed to recognize two different epitopes or antigens on tumor cells and immune cells allowing immune recognition of these cancer cells 83 . A variety of BsAbs relevant to BC are in development 84 . Zanidatamab, BsAb, targets two different HER2 epitopes, in combination with chemotherapy, was well-tolerated, and has shown anti-tumor activity in heavily pretreated HER2-amplified metastatic BC patients 85 . In TNBC, BsAbs from a large panel of tissue agnostic targets such as CD3, CEACAM5, epithelial cell adhesion molecule (EpCAM), epithelial growth factor receptor (EGFR), mesothelin including Trop2 are under investigation 83 .

Conclusions and perspectives

Although the development of cancer immunotherapy in BC began more than 20 years ago, its integration into patient care was slower than in other tumor types. The current extensive clinical research landscape will hopefully change this situation and expand the use of ICI and other immunotherapies in BC beyond the TNBC subtype. As reviewed herein, the number of clinical trials evaluating multiple immunotherapeutic strategies is increasing across all BC subtypes. The FDA approval of ICI plus chemotherapy in TNBC will provide real-world data that will help to better evaluate the benefit of this therapeutic strategy in underrepresented in landmark clinical trials populations, specifically Black patients. Comprehensive translational research and the use of biomarkers will help avoid the development of “add-on designs” which adds a new immune drug to a clinically established modality without leading to the development of adequate strategies for each individual patient. Indeed, the first results from biomarker analyses in immunotherapy TNBC trials highlight the heterogeneity of this disease and the urgent need to better characterize the TME to tailor immunotherapeutic approaches 37 , 86 . The predictive value of several biomarkers, including TIL levels, presence of tertiary lymphoid structures, or expression of immune gene signatures, is under investigation and has already been retrospectively evaluated in some clinical trials 7 , 37 , 87 . Only PD-L1 IHC expression is currently used to select TNBC patients for ICI in the metastatic setting. Moreover, its use in clinical practice remains controversial and complicated by the availability of several mAb and scoring systems and by the limited inter-observer agreement of PD-L1 scoring 88 . Blood-based biomarker research is ongoing, and liquid biopsies may become a noninvasive alternative to tissue biopsies in predicting and monitoring treatment responses.

Immunotherapy is associated with unique and sometimes severe irAEs that will require multidisciplinary collaborative efforts to offer adequate management of the increasing number of patients treated with ICI and to treat emerging toxicity from new immune-modulating agents and ACTs 82 . Another challenge for developing immunotherapy is to define an adequate response assessment, as the pattern of responses to ICI is different from that due to chemotherapeutic agents. Immune Response Evaluation Criteria in Solid Tumors (iRECIST) to better capture the benefit of immunotherapy have been developed, but most trials are still using the conventional RECIST 89 . In BC, pCR after NACT is a surrogate endpoint for a long-term clinical outcome, which might be less appropriate to capture long-term immune memory responses that could sustain therapeutic effects and prevent relapses, as recently suggested by the results of the GeparNUEVO study 32 , 38 . The development of adequate endpoints and new imaging techniques to measure the immune response could refine our approach to tumor response assessment and our criteria predictive of benefit from a given therapy.

Future clinical investigations will also need to address the question of de-escalation strategies for patients with long-term benefits. The excellent outcome observed in the absence of chemotherapy in patients with high TILs, and early-stage TNBC has led to the design of neoadjuvant immunotherapy trials omitting chemotherapy (e.g., NCT04427293) 90 . For non-responders, the improved understanding of tumor-immune interactions and the contribution of the TME, notably with the help of the latest technologies such as single-cell analyses and spatial transcriptomics, may provide new drug targets and strategies to overcome resistance 91 , 92 .

In summary, the clinical research landscape of immunotherapy in BC is expanding with novel investigational therapies aimed at initiating, restoring, or triggering patients’ immune responses against tumor cells. Innovative drugs combinations have already demonstrated an improved outcome for some BC patients, and these new therapeutic strategies will gradually be integrated into clinical treatments.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

The data used for the Fig. 1 design are available in supplementary table 1 . Data extracted from https://clinicaltrials.gov/ with research terms “breast”, “nivolumab”, “pembrolizumab”, “avelumab”, “atezolizumab”, “durvalumab”, “ipilimumab”, “tremelimumab”, “CAR-T”, “Bispecific”, “Vaccine”, “immunotherapy”, “4-1BB”, “OX-40”, “LAG”, “TIGIT”, “PD-1”, “PD-L1”, and “NK cells”. Data extracted on January 14, 2022.

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Acknowledgements

The authors thank Prof. Christos Sotiriou for the helpful discussions. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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V.D.: Conceptualization, formal analysis, investigation, resources, writing—original draft, visualization, writing—review and editing, and validation. A.D.C.: Formal analysis, investigation, resources, writing—original draft, data research, writing— review and editing, and validation. X.W.: Formal analysis, investigation, resources, writing—original draft, writing—review and editing, and validation. M.P.-G.: Writing—review and editing and validation. V.K.T.: Investigation, writing—original draft, writing—review and editing, and validation. E.R.: Writing—original draft, writing—review and editing, and validation. L.B.: Conceptualization, writing—original draft, visualization, writing—original draft, and validation. All co-authors, after proofreading, approved the final version of the manuscript.

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V.D. and X.W. declare no competing financial or non-financial interests. The following authors declare no competing non-financial interests but the following competing financial interests: A.d.C.: Investigator-initiated trial (funds paid to institution): AstraZeneca. M.P.-G.: Board Member (Scientific Board): Oncolytics; Consultant (honoraria): AstraZeneca, Camel-IDS, Crescendo Biologics, G1 Therapeutics, Genentech, Huya, Immunomedics, Lilly, Menarini, MSD, Novartis, Odonate, Oncolytics, Periphagen, Pfizer, Roche, Seattle Genetics, Immutep, NBE Therapeutics, SeaGen; Research grants to her Institute: AstraZeneca, Lilly, MSD, Novartis, Pfizer, Radius, Roche-Genentech, Servier, Synthon (outside the submitted work). V.K.T.: Funding from the Department of Defense Breakthrough Award, Level 3 Clinical Trial for Primary Immunoprevention of Triple-Negative Breast Cancer, Anixa Biosciences, Inc. V.K.T. holds personal equity in Anixa Biosciences, Inc. ER: Investigator-initiated trial (funds paid to institution): AstraZeneca, BMS, Roche, Replimmune. Consultancy/advisory board: AstraZeneca, Merck, Roche, Pierre Fabre. L.B.: Investigator-initiated trial (funds paid to institution): AstraZeneca. L.B. is supported by the Belgian “Fondation Contre le Cancer”.

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Debien, V., De Caluwé, A., Wang, X. et al. Immunotherapy in breast cancer: an overview of current strategies and perspectives. npj Breast Cancer 9 , 7 (2023). https://doi.org/10.1038/s41523-023-00508-3

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  • Breast cancer

Woman undergoing mammography exam

Receiving a mammogram

During a mammogram, you stand in front of an X-ray machine designed for mammography. A technician places your breast on a platform and positions the platform to match your height. The technician helps you position your head, arms and torso to allow an unobstructed view of your breast.

Breast MRI

Getting a breast MRI involves lying face down on a padded scanning table. The breasts fit into a hollow space in the table. The hollow has coils that get signals from the MRI . The table slides into the large opening of the MRI machine.

Core needle biopsy

Core needle biopsy

A core needle biopsy uses a long, hollow tube to obtain a sample of tissue. Here, a biopsy of a suspicious breast lump is being done. The sample is sent to a lab for testing and evaluation by doctors, called pathologists. They specialize in analyzing blood and body tissue.

Breast cancer diagnosis often begins with an exam and a discussion of your symptoms. Imaging tests can look at the breast tissue for anything that's not typical. To confirm whether there is cancer or not, a sample of tissue is removed from the breast for testing.

Breast exam

During a clinical breast exam, a healthcare professional looks at the breasts for anything that's not typical. This might include changes in the skin or to the nipple. Then the health professional feels the breasts for lumps. The health professional also feels along the collarbones and around the armpits for lumps.

A mammogram is an X-ray of the breast tissue. Mammograms are commonly used to screen for breast cancer. If a screening mammogram finds something concerning, you might have another mammogram to look at the area more closely. This more-detailed mammogram is called a diagnostic mammogram. It's often used to look closely at both breasts.

Breast ultrasound

Ultrasound uses sound waves to make pictures of structures inside the body. A breast ultrasound may give your healthcare team more information about a breast lump. For example, an ultrasound might show whether the lump is a solid mass or a fluid-filled cyst. The healthcare team uses this information to decide what tests you might need next.

MRI machines use a magnetic field and radio waves to create pictures of the inside of the body. A breast MRI can make more-detailed pictures of the breast. Sometimes this method is used to look closely for any other areas of cancer in the affected breast. It also might be used to look for cancer in the other breast. Before a breast MRI , you usually receive an injection of dye. The dye helps the tissue show up better in the images.

Removing a sample of breast cells for testing

A biopsy is a procedure to remove a sample of tissue for testing in a lab. To get the sample, a healthcare professional puts a needle through the skin and into the breast tissue. The health professional guides the needle using images created with X-rays, ultrasound or another type of imaging. Once the needle reaches the right place, the health professional uses the needle to draw out tissue from the breast. Often, a marker is placed in the spot where the tissue sample was removed. The small metal marker will show up on imaging tests. The marker helps your healthcare team monitor the area of concern.

Testing cells in the lab

The tissue sample from a biopsy goes to a lab for testing. Tests can show whether the cells in the sample are cancerous. Other tests give information about the type of cancer and how quickly it's growing. Special tests give more details about the cancer cells. For example, tests might look for hormone receptors on the surface of the cells. Your healthcare team uses the results from these tests to make a treatment plan.

Staging breast cancer

Once your healthcare team diagnoses your breast cancer, you may have other tests to figure out the extent of the cancer. This is called the cancer's stage. Your healthcare team uses your cancer's stage to understand your prognosis.

Complete information about your cancer's stage may not be available until after you undergo breast cancer surgery.

Tests and procedures used to stage breast cancer may include:

  • Blood tests, such as a complete blood count and tests to show how well the kidneys and liver are working.
  • Positron emission tomography scan, also called a PET scan.

Not everyone needs all of these tests. Your healthcare team picks the right tests based on your specific situation.

Breast cancer stages range from 0 to 4. A lower number means the cancer is less advanced and more likely to be cured. Stage 0 breast cancer is cancer that is contained within a breast duct. It hasn't broken out to invade the breast tissue yet. As the cancer grows into the breast tissue and gets more advanced, the stages get higher. A stage 4 breast cancer means that the cancer has spread to other parts of the body.

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Our caring team of Mayo Clinic experts can help you with your breast cancer-related health concerns Start Here

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Breast cancer care at Mayo Clinic

  • Breast cancer staging
  • Breast cancer types
  • 3D mammogram
  • BRCA gene test
  • Breast cancer risk assessment
  • Breast self-exam for breast awareness
  • Chest X-rays
  • Complete blood count (CBC)
  • Molecular breast imaging
  • Positron emission tomography scan
  • Sentinel node biopsy

Breast cancer treatment often starts with surgery to remove the cancer. Most people with breast cancer will have other treatments after surgery, such as radiation, chemotherapy and hormone therapy. Some people may have chemotherapy or hormone therapy before surgery. These medicines can help shrink the cancer and make it easier to remove.

Your treatment plan will depend on your particular breast cancer. Your healthcare team considers the stage of the cancer, how quickly it's growing and whether the cancer cells are sensitive to hormones. Your care team also considers your overall health and what you prefer.

There are many options for breast cancer treatment. It can feel overwhelming to consider all the options and make complex decisions about your care. Consider seeking a second opinion from a breast specialist in a breast center or clinic. Talk to breast cancer survivors who have faced the same decision.

  • Breast cancer surgery

Lumpectomy

A lumpectomy involves removing the cancer and some of the healthy tissue that surrounds it. This illustration shows one possible incision that can be used for this procedure, though your surgeon will determine the approach that's best for your particular situation.

A person who has undergone a total (simple) mastectomy without breast reconstruction

During a total mastectomy, the surgeon removes the breast tissue, nipple, areola and skin. This procedure also is known as a simple mastectomy. Other mastectomy procedures may leave some parts of the breast, such as the skin or the nipple. Surgery to create a new breast is optional. It can be done at the same time as mastectomy surgery or it can be done later.

Sentinel node biopsy

Sentinel node biopsy identifies the first few lymph nodes into which a tumor drains. The surgeon uses a harmless dye and a weak radioactive solution to locate the sentinel nodes. The nodes are removed and tested for signs of cancer.

Breast cancer surgery typically involves a procedure to remove the breast cancer and a procedure to remove some nearby lymph nodes. Operations used to treat breast cancer include:

Removing the breast cancer. A lumpectomy is surgery to remove the breast cancer and some of the healthy tissue around it. The rest of the breast tissue isn't removed. Other names for this surgery are breast-conserving surgery and wide local excision. Most people who have a lumpectomy also have radiation therapy.

Lumpectomy might be used to remove a small cancer. Sometimes you can have chemotherapy before surgery to shrink the cancer so that lumpectomy is possible.

Removing all of the breast tissue. A mastectomy is surgery to remove all breast tissue from a breast. The most common mastectomy procedure is total mastectomy, also called simple mastectomy. This procedure removes all of the breast, including the lobules, ducts, fatty tissue and some skin, including the nipple and areola.

Mastectomy might be used to remove a large cancer. It also might be needed when there are multiple areas of cancer within one breast. You might have a mastectomy if you can't have or don't want radiation therapy after surgery.

Some newer types of mastectomy procedures might not remove the skin or nipple. For instance, a skin-sparing mastectomy leaves some skin. A nipple-sparing mastectomy leaves the nipple and the skin around it, called the areola. These newer operations can improve the look of the breast after surgery, but they aren't options for everyone.

  • Removing a few lymph nodes. A sentinel node biopsy is an operation to take out some lymph nodes for testing. When breast cancer spreads, it often goes to the nearby lymph nodes first. To see if the cancer has spread, a surgeon removes some of the lymph nodes near the cancer. If no cancer is found in those lymph nodes, the chance of finding cancer in any of the other lymph nodes is small. No other lymph nodes need to be removed.
  • Removing several lymph nodes. Axillary lymph node dissection is an operation to remove many lymph nodes from the armpit. Your breast cancer surgery might include this operation if imaging tests show the cancer has spread to the lymph nodes. It also might be used if cancer is found in a sentinel node biopsy.
  • Removing both breasts. Some people who have cancer in one breast may choose to have their other breast removed, even if it doesn't have cancer. This procedure is called a contralateral prophylactic mastectomy. It might be an option if you have a high risk of getting cancer in the other breast. The risk might be high if you have a strong family history of cancer or have DNA changes that increase the risk of cancer. Most people with breast cancer in one breast will never get cancer in the other breast.

Complications of breast cancer surgery depend on the procedures you choose. All operations have a risk of pain, bleeding and infection. Removing lymph nodes in the armpit carries a risk of arm swelling, called lymphedema.

You may choose to have breast reconstruction after mastectomy surgery. Breast reconstruction is surgery to restore shape to the breast. Options might include reconstruction with a breast implant or reconstruction using your own tissue. Consider asking your healthcare team for a referral to a plastic surgeon before your breast cancer surgery.

  • Radiation therapy

Radiation therapy for breast cancer

External beam radiation uses high-powered beams of energy to kill cancer cells. Beams of radiation are precisely aimed at the cancer using a machine that moves around your body.

Radiation therapy treats cancer with powerful energy beams. The energy can come from X-rays, protons or other sources.

For breast cancer treatment, the radiation is often external beam radiation. During this type of radiation therapy, you lie on a table while a machine moves around you. The machine directs radiation to precise points on your body. Less often, the radiation can be placed inside the body. This type of radiation is called brachytherapy.

Radiation therapy is often used after surgery. It can kill any cancer cells that might be left after surgery. The radiation lowers the risk of the cancer coming back.

Side effects of radiation therapy include feeling very tired and having a sunburn-like rash where the radiation is aimed. Breast tissue also may look swollen or feel more firm. Rarely, more-serious problems can happen. These include damage to the heart or lungs. Very rarely, a new cancer can grow in the treated area.

  • Chemotherapy

Chemotherapy treats cancer with strong medicines. Many chemotherapy medicines exist. Treatment often involves a combination of chemotherapy medicines. Most are given through a vein. Some are available in pill form.

Chemotherapy for breast cancer is often used after surgery. It can kill any cancer cells that might remain and lower the risk of the cancer coming back.

Sometimes chemotherapy is given before surgery. The chemotherapy might shrink the breast cancer so that it's easier to remove. Chemotherapy before surgery also might control cancer that spreads to the lymph nodes. If the lymph nodes no longer show signs of cancer after chemotherapy, surgery to remove many lymph nodes might not be needed. How the cancer responds to chemotherapy before surgery helps the healthcare team make decisions about what treatments might be needed after surgery.

When the cancer spreads to other parts of the body, chemotherapy can help control it. Chemotherapy may relieve symptoms of an advanced cancer, such as pain.

Chemotherapy side effects depend on which medicines you receive. Common side effects include hair loss, nausea, vomiting, feeling very tired and having an increased risk of getting an infection. Rare side effects can include premature menopause and nerve damage. Very rarely, certain chemotherapy medicines can cause blood cell cancer.

Hormone therapy

Hormone therapy uses medicines to block certain hormones in the body. It's a treatment for breast cancers that are sensitive to the hormones estrogen and progesterone. Healthcare professionals call these cancers estrogen receptor positive and progesterone receptor positive. Cancers that are sensitive to hormones use the hormones as fuel for their growth. Blocking the hormones can cause the cancer cells to shrink or die.

Hormone therapy is often used after surgery and other treatments. It can lower the risk that the cancer will come back.

If the cancer spreads to other parts of the body, hormone therapy can help control it.

Treatments that can be used in hormone therapy include:

  • Medicines that block hormones from attaching to cancer cells. These medicines are called selective estrogen receptor modulators.
  • Medicines that stop the body from making estrogen after menopause. These medicines are called aromatase inhibitors.
  • Surgery or medicines to stop the ovaries from making hormones.

Hormone therapy side effects depend on the treatment you receive. The side effects can include hot flashes, night sweats and vaginal dryness. More-serious side effects include a risk of bone thinning and blood clots.

Targeted therapy

Targeted therapy uses medicines that attack specific chemicals in the cancer cells. By blocking these chemicals, targeted treatments can cause cancer cells to die.

The most common targeted therapy medicines for breast cancer target the protein HER2 . Some breast cancer cells make extra HER2 . This protein helps the cancer cells grow and survive. Targeted therapy medicine attacks the cells that are making extra HER2 and doesn't hurt healthy cells.

Many other targeted therapy medicines exist for treating breast cancer. Your cancer cells may be tested to see whether these medicines might help you.

Targeted therapy medicines can be used before surgery to shrink a breast cancer and make it easier to remove. Some are used after surgery to lower the risk that the cancer will come back. Others are used only when the cancer has spread to other parts of the body.

Immunotherapy

Immunotherapy is a treatment with medicine that helps the body's immune system to kill cancer cells. The immune system fights off diseases by attacking germs and other cells that shouldn't be in the body. Cancer cells survive by hiding from the immune system. Immunotherapy helps the immune system cells find and kill the cancer cells.

Immunotherapy might be an option for treating triple-negative breast cancer. Triple-negative breast cancer means that the cancer cells don't have receptors for estrogen, progesterone or HER2 .

Palliative care

Palliative care is a special type of healthcare that helps you feel better when you have a serious illness. If you have cancer, palliative care can help relieve pain and other symptoms. A team of healthcare professionals provides palliative care. The team can include doctors, nurses and other specially trained professionals. Their goal is to improve quality of life for you and your family.

Palliative care specialists work with you, your family and your care team to help you feel better. They provide an extra layer of support while you have cancer treatment. You can have palliative care at the same time as strong cancer treatments, such as surgery, chemotherapy or radiation therapy.

When palliative care is used along with all of the other appropriate treatments, people with cancer may feel better and live longer.

  • Brachytherapy
  • Breast cancer supportive therapy and survivorship
  • Chemotherapy for breast cancer
  • Hormone therapy for breast cancer
  • Precision medicine for breast cancer
  • Radiation therapy for breast cancer
  • Common questions about breast cancer treatment
  • Paulas story A team approach to battling breast cancer

Clinical trials

Explore Mayo Clinic studies testing new treatments, interventions and tests as a means to prevent, detect, treat or manage this condition.

Alternative medicine

No alternative medicine treatments have been found to cure breast cancer. But complementary and alternative medicine therapies may help you cope with side effects of treatment.

Alternative medicine for fatigue

Many people with breast cancer have fatigue during and after treatment. This feeling of being very tired and worn down can continue for years. When combined with care from your healthcare team, complementary and alternative medicine therapies may help relieve fatigue.

Talk with your healthcare team about:

  • Expressing your feelings. Find an activity that allows you to write about or discuss your emotions. Examples include writing in a journal, participating in a support group or talking to a counselor.
  • Gentle exercise. If you get the OK from your healthcare team, start with gentle exercise a few times a week. Add more exercise, as you feel up to it. Consider walking, swimming, yoga and tai chi.
  • Managing stress. Take control of the stress in your daily life. Try stress-reduction techniques such as muscle relaxation, visualization, and spending time with friends and family.

Coping and support

Some breast cancer survivors say their diagnosis felt overwhelming at first. It can be stressful to feel overwhelmed at the same time you need to make important decisions about your treatment. In time, you'll find ways to cope with your feelings. Until you find what works for you, it might help to:

Learn enough about your breast cancer to make decisions about your care

If you'd like to know more about your breast cancer, ask your healthcare team for the details of your cancer. Write down the type, stage and hormone receptor status. Ask for good sources of information where you can learn more about your treatment options.

Knowing more about your cancer and your options may help you feel more confident when making treatment decisions. Still, some people don't want to know the details of their cancer. If this is how you feel, let your care team know that too.

Talk with other breast cancer survivors

You may find it helpful and encouraging to talk to others who have been diagnosed with breast cancer. Contact a cancer support organization in your area to find out about support groups near you or online. In the United States, you might start with the American Cancer Society.

Find someone to talk with about your feelings

Find a friend or family member who is a good listener. Or talk with a clergy member or counselor. Ask your healthcare team for a referral to a counselor or other professional who works with people who have cancer.

Keep your friends and family close

Your friends and family can provide a crucial support network for you during your cancer treatment.

As you begin telling people about your breast cancer diagnosis, you'll likely get many offers for help. Think ahead about things you may want help with. Examples include listening when you want to talk or helping you with preparing meals.

Preparing for your appointment

Make an appointment with a doctor or other healthcare professional if you have any symptoms that worry you. If an exam or imaging test shows you might have breast cancer, your healthcare team will likely refer you to a specialist.

Specialists who care for people with breast cancer include:

  • Breast health specialists.
  • Breast surgeons.
  • Doctors who specialize in diagnostic tests, such as mammograms, called radiologists.
  • Doctors who specialize in treating cancer, called oncologists.
  • Doctors who treat cancer with radiation, called radiation oncologists.
  • Genetic counselors.
  • Plastic surgeons.

What you can do to prepare

  • Write down any symptoms you're experiencing, including any that may seem unrelated to the reason for which you scheduled the appointment.
  • Write down key personal information, including any major stresses or recent life changes.
  • Write down your family history of cancer. Note any family members who have had cancer. Note how each member is related to you, the type of cancer, the age at diagnosis and whether each person survived.
  • Make a list of all medicines, vitamins or supplements that you're taking.
  • Keep all of your records that relate to your cancer diagnosis and treatment. Organize your records in a binder or folder that you can take to your appointments.
  • Consider taking a family member or friend along. Sometimes it can be difficult to absorb all the information provided during an appointment. Someone who accompanies you may remember something that you missed or forgot.
  • Write down questions to ask your healthcare professional.

Questions to ask your doctor

Your time with your healthcare professional is limited. Prepare a list of questions so that you can make the most of your time together. List your questions from most important to least important in case time runs out. For breast cancer, some basic questions to ask include:

  • What type of breast cancer do I have?
  • What is the stage of my cancer?
  • Can you explain my pathology report to me? Can I have a copy for my records?
  • Do I need any more tests?
  • What treatment options are available for me?
  • What are the benefits from each treatment you recommend?
  • What are the side effects of each treatment option?
  • Will treatment cause menopause?
  • How will each treatment affect my daily life? Can I continue working?
  • Is there one treatment you recommend over the others?
  • How do you know that these treatments will benefit me?
  • What would you recommend to a friend or family member in my situation?
  • How quickly do I need to make a decision about cancer treatment?
  • What happens if I don't want cancer treatment?
  • What will cancer treatment cost?
  • Does my insurance plan cover the tests and treatment you're recommending?
  • Should I seek a second opinion? Will my insurance cover it?
  • Are there any brochures or other printed material that I can take with me? What websites or books do you recommend?
  • Are there any clinical trials or newer treatments that I should consider?

In addition to the questions that you've prepared, don't hesitate to ask other questions you think of during your appointment.

What to expect from your doctor

Be prepared to answer some questions about your symptoms and your health, such as:

  • When did you first begin experiencing symptoms?
  • Have your symptoms been continuous or occasional?
  • How severe are your symptoms?
  • What, if anything, seems to improve your symptoms?
  • What, if anything, appears to worsen your symptoms?

Living with breast cancer?

Connect with others like you for support and answers to your questions in the Breast Cancer support group on Mayo Clinic Connect, a patient community.

Breast Cancer Discussions

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  • Mukwende M, et al. Erythema. In: Mind the Gap: A Handbook of Clinical Signs in Black and Brown Skin. St. George's University of London; 2020. https://www.blackandbrownskin.co.uk/mindthegap. Accessed Aug. 10, 2023.
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  • Palliative care. National Comprehensive Cancer Network. https://www.nccn.org/guidelines/guidelines-detail?category=3&id=1454. Accessed Aug. 2, 2023.
  • Cancer-related fatigue. National Comprehensive Cancer Network. https://www.nccn.org/guidelines/guidelines-detail?category=3&id=1424. Accessed Aug. 2, 2023.
  • Breast SPOREs. National Cancer Institute. https://trp.cancer.gov/spores/breast.htm. Accessed Aug. 9, 2023.
  • Ami TR. Allscripts EPSi. Mayo Clinic. Jan. 31, 2023.
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  • Member institutions. Alliance for Clinical Trials in Oncology. https://www.allianceforclinicaltrialsinoncology.org/main/public/standard.xhtml?path=%2FPublic%2FInstitutions. Accessed Aug. 9, 2023.
  • Giridhar KV (expert opinion). Mayo Clinic. Oct. 18, 2023.
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Breast Cancer Treatments: Updates and New Challenges

Anna burguin.

1 Department of Molecular Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1T 1C2, Canada; [email protected]

2 Cancer Research Center, CHU de Québec-Université Laval, Quebec City, QC G1V 4G2, Canada; [email protected]

Caroline Diorio

3 Department of Preventive and Social Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1T 1C2, Canada

Francine Durocher

Associated data.

The study did not report any data.

Breast cancer (BC) is the most frequent cancer diagnosed in women worldwide. This heterogeneous disease can be classified into four molecular subtypes (luminal A, luminal B, HER2 and triple-negative breast cancer (TNBC)) according to the expression of the estrogen receptor (ER) and the progesterone receptor (PR), and the overexpression of the human epidermal growth factor receptor 2 (HER2). Current BC treatments target these receptors (endocrine and anti-HER2 therapies) as a personalized treatment. Along with chemotherapy and radiotherapy, these therapies can have severe adverse effects and patients can develop resistance to these agents. Moreover, TNBC do not have standardized treatments. Hence, a deeper understanding of the development of new treatments that are more specific and effective in treating each BC subgroup is key. New approaches have recently emerged such as immunotherapy, conjugated antibodies, and targeting other metabolic pathways. This review summarizes current BC treatments and explores the new treatment strategies from a personalized therapy perspective and the resulting challenges.

1. Introduction

Breast cancer (BC) is the most frequent cancer and the second cause of death by cancer in women worldwide. According to Cancer Statistics 2020, BC represents 30% of female cancers with 276,480 estimated new cases and more than 42,000 estimated deaths in 2020 [ 1 ].

Invasive BC can be divided into four principal molecular subtypes by immunohistological technique based on the expression of the estrogen receptor (ER), the progesterone receptor (PR), and the human epidermal growth factor receptor 2 (HER2) [ 2 ]. Luminal A BC (ER+ and/or PR+, and HER2-) represents around 60% of BC and is associated with a good prognosis [ 3 ]. Luminal B BC (ER+ and/or PR+, and HER2+) represents 30% of BC and is associated with high ki67 (>14%), a proliferation marker, and a poor prognosis [ 4 ]. HER2 BC (ER-, PR-, and HER2+) represents 10% of BC and is also associated with a poor prognosis [ 5 ]. Lastly, triple-negative BC (TNBC) (ER-, PR-, and HER2-) represents 15–20% of BC and is associated with more aggressivity and worse prognosis compared to other BC molecular subtypes and often occurs in younger women [ 6 ]. Characteristics of BC by molecular subtypes are described in Figure 1 .

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Object name is jpm-11-00808-g001.jpg

Characteristics of breast cancer molecular subtypes. ER: estrogen receptor; PR: progesterone receptor; HER2: human epidermal growth factor receptor 2; TNBC: triple-negative breast cancer. a . Frequency derived from Al-thoubaity et al. [ 12 ] and Hergueta-Redondo et al. [ 13 ]. b . Grade derived from Engstrom et al. [ 14 ]. c . Prognosis derived from Hennigs et al. [ 15 ] and Fragomeni et al. [ 16 ]. d . The 5–year survival rate derived from the latest survival statistics of SEER [ 7 ].

The 5-year relative BC-specific survival rate of BC is encouraging with 90.3% for all subtypes and stages. However, for metastatic BC the 5-year relative cancer-specific survival rate is still low: 29% regardless of subtype and can drop to 12% for metastatic TNBC [ 7 ]. This clearly indicates that strategies of treatment for metastatic BC patients are not effective enough to ensure a good survival rate. Thus, it is crucial to find new solutions for the treatment of metastatic BC and especially TNBC.

Treatment choice is based on the grade, stage, and BC molecular subtype to have the most personalized, safe, and efficient therapy. The grade describes the appearance of tumor cells compared to normal cells. It includes tubule differentiation, nuclear pleomorphism, and the mitotic count [ 8 ]. The stage is used to classify the extent of cancer in the body and is defined using the TNM system comprising tumor size, lymph node status, and the presence of metastases [ 9 ]. For non-metastatic BC, the strategic therapy involves removing the tumor by complete or breast-conserving surgery with preoperative (neoadjuvant) or postoperative (adjuvant) radiotherapy and systemic therapy including chemotherapy, and targeted therapy. Targeted therapy comprises endocrine therapy for hormone receptor-positive (HR+) BC and anti-HER2 therapy for HER2+ BC. Unfortunately, there is no available targeted therapy for the TNBC subtype. For metastatic BC the priority is to contain tumor spread as this type of BC remains incurable. The same systemic therapies are used to treat metastatic BC [ 10 ].

Challenges in the treatment of BC including dealing with treatment resistance and recurrence. Indeed, 30% of early-stage BC have recurrent disease, mostly metastases [ 11 ]. Thus, it is crucial to develop new strategic therapies to treat each BC subgroup effectively.

This review will summarize current treatments for invasive BC, the underlying resistance mechanisms and explore new treatment strategies focusing on personalized therapy and the resulting challenges.

2. Common Treatments for All Breast Cancer Subtypes

In addition to surgery, radiotherapy and chemotherapy are used routinely to treat all BC subtypes [ 17 ].

2.1. Surgery

The most standard breast surgery approaches are either total excision of the breast (mastectomy), usually followed by breast reconstruction, or breast-conserving surgery (lumpectomy). Lumpectomy entails the excision of the breast tumor with a margin of surrounding normal tissue. The recommended margins status is defined as “no ink on tumor”, meaning no remaining tumor cells at the tissue edge [ 18 ]. Studies show that total mastectomy and lumpectomy plus irradiation are equivalent regarding relapse-free and overall survival (OS) [ 19 ]. Contraindications for breast-conserving surgery include the presence of diffuse microcalcifications (suspicious or malignant-appearing), disease that cannot be incorporated by local excision with satisfactory cosmetic result, and ATM (ataxia-telangiesctasia mutated) mutation (biallelic inactivation) [ 18 ].

The surgery to remove axillary lymph nodes is useful to determine cancerous cell spread and for therapeutic purposes. For instance, axillary lymph node dissection (ALND) can improve survival rated by removing remaining tumor cells. ALND used to be the goal standard for removing positive lymph nodes. However, clinical trials showed that sentinel lymph node biopsy (SLNB) had the same effect as ALND regarding disease-free survival (DFS) and OS [ 20 ]. Other clinical trials demonstrated that ALND was not necessary for all patients with positive lymph nodes. Moreover, most patients who receive radiation and systemic treatment after SLNB have negative lymph nodes as these treatments are sufficient in eliminating residual tumor cells [ 21 ].

2.2. Radiotherapy

Radiation therapy has been used to treat cancer since Röngten discovered the X-ray in 1895 [ 22 ]. High-energy radiations are applied to the whole breast or a portion of the breast (after breast-conservative surgery), chest wall (after mastectomy), and regional lymph nodes [ 23 ]. A meta-analysis showed that radiation following conservative surgery offered more benefits to patients with higher-risk BC while patients with small, low-grade tumors could forego radiation therapy [ 24 ]. Postmastectomy radiation to the chest wall in patients with positive lymph nodes is associated with decreased recurrence risk and BC mortality compared to patients with negative lymph nodes [ 25 ]. A radiation boost to the regional node radiation treatment can be incorporated after mastectomy for patients at higher risk for recurrence [ 26 ]. This additional radiation boost to regional nodes following mastectomy is associated with improved (DFS) but is also associated with an increase in radiation toxicities such as pneumonitis and lymphedema [ 27 ]. Radiotherapy can be administered concurrently with personalized therapy (anti-HER2 therapy or endocrine therapy).

As one of the major side effects of radiotherapy is cardiotoxicity, it is critical to minimize exposure to the heart and lungs [ 28 ]. Additional techniques can be used to reduce the radiation exposure to the heart, lungs, and normal tissue such as prone positioning, respiratory control, or intensity-modulated radiotherapy [ 29 ].

Advanced invasive BC can exhibit radiation therapy resistance [ 30 ]. The hypoxic tumor microenvironment, which lacks oxygen, leads to increased cell proliferation, apoptosis resistance, and radiotherapy resistance [ 31 ]. The major player of this resistance is the HIF-1α (hypoxia-inducible factor 1 alpha) protein [ 32 ]. Indeed, HIF-1α overexpression is caused by low oxygen levels within the microenvironment and promotes the maintenance of hypoxia by allowing tumoral cells to survive in a hypoxic microenvironment [ 33 , 34 , 35 ]. Cancer stem cells (CSC) could also have a role in radiation therapy resistance [ 36 ]. CSC can self-renew and initiate subpopulations of differential progeny, and a hypoxic microenvironment is ideal for CSC survival and proliferation [ 37 , 38 ].

Radiation therapy is used to treat all BC subtypes, but its implication is more important for TNBC, as there is no personalized therapy for this subtype. It has been shown that radiotherapy benefits TNBC patients both after conserving surgery and mastectomy [ 39 ].

2.3. Chemotherapy

BC chemotherapy comprises several families of cytotoxic drugs, including alkylating agents, antimetabolites and tubulin inhibitors [ 40 ]. Cyclophosphamide is a nitrogen mustard alkylating agent causing breakage of the DNA strands [ 41 ]. The mechanism of action for anthracyclines (doxorubicin, daunorubicin, epirubicin, and idarubicin) includes DNA intercalation, thereby inhibiting macromolecular biosynthesis [ 42 ]. Taxanes, including docetaxel and paclitaxel, bind to microtubules and prevent their disassembly, leading to cell cycle arrest and apoptosis [ 43 ].

Chemotherapy can be administered in the neoadjuvant or adjuvant setting and for metastatic BC treatment.

2.3.1. Neoadjuvant Chemotherapy (NAC)

Neoadjuvant chemotherapy was initially administered for non-metastatic but inoperable BC, defined as unreachable tumors [ 44 ]. Then, chemotherapy was used before the surgery for operable tumors to facilitate breast conservation [ 45 ].

Studies demonstrated that chemotherapy administered before surgery is as effective as administered after surgery [ 46 , 47 , 48 ]. The NSABP-B-18 trial compared the effects of doxorubicin and cyclophosphamide administered either postoperatively or preoperatively. This trial showed that NAC reduces the rate of axillary metastases in node-negative BC patients [ 48 ].

Some patients fail to achieve pathologic complete response after a full course of NAC. Unfortunately, there is no consensus regarding the treatment strategy to follow for patients with residual disease after surgery [ 49 , 50 ]. The BC subtype plays an important role in the response to NAC. Indeed, TNBC and HER2+ BC are more likely to be sensitive to chemotherapy. Hence, NAC is a good strategy to maximize pathologic complete response in these BC subtypes [ 45 ].

2.3.2. Adjuvant Chemotherapy

Adjuvant chemotherapy is administered to BC patients with lymph nodes metastases or a high risk of recurrence [ 51 ]. The standard chemotherapy treatment comprises an anthracycline and a taxane. The two most common regimens are cyclophosphamide and doxorubicin for four cycles followed by paclitaxel for four cycles. Then patients are given the previous combination of therapies followed by either weekly paclitaxel for 12 weeks, or docetaxel every 3 weeks for four cycles [ 52 , 53 ].

Like neoadjuvant therapy, patients with HR-negative BC receive more benefits from adjuvant therapy (i.e., reduction of BC recurrence and mortality) than HR+ BC patients [ 54 ]. However, for patients with HR+, node-negative BC associated with a high Oncotype recurrence score (≥31), calculated from the expression of 16 BC-related genes and 5 reference genes, adjuvant chemotherapy reduces the risk of recurrence [ 55 ]. The TAILORx clinical trial showed that HR+ BC patients with a low Oncotype recurrence score do not benefit from chemotherapy alone [ 56 ].

According to the molecular BC subtype, chemotherapy can be administered with targeted therapies. Patients with HR+ BC should receive endocrine therapy after chemotherapy is completed, and HER2+ BC patients should receive trastuzumab combined with chemotherapy [ 57 ]. For TNBC patients, front-line therapy includes a combination of taxane and anthracycline [ 58 ].

One of the major drawbacks of chemotherapy is its side effects. The early side effects (0–6 months of treatment) involve fatigue, alopecia, cytopenia (reduction in the number of normal blood cells), muscle pain, neurocognitive dysfunction, and chemo-induced peripheral neuropathy. The chronic or late side effects (after 6 months of treatment) include cardiomyopathy, second cancers, early menopause, sterility, and psychosocial impacts [ 59 ].

As mentioned previously in this review, chemotherapy is composed of taxanes, anthracyclines and cyclophosphamide. Each of these molecules can lead to resistance in BC patients [ 60 ].

One mechanism of resistance is by overexpressing p-glycoprotein, an ATP-binding cassette (ABC) family member, which confers resistance to anthracycline and taxanes [ 61 ]. Breast cancer resistance protein (BCRP), another ABC family member, induces resistance to anthracycline but not taxanes when overexpressed [ 62 ]. Microtubule alterations can also lead to taxane resistance. The overexpression of β-tubulin III induces paclitaxel resistance [ 63 ]. Moreover, mutations in microtubule-associated proteins (MAPs) affect microtubule dynamics and improve taxane resistance [ 64 ]. Multiple enzymes are known to be involved in the cyclophosphamide detoxification, leading to its resistance. For example, aldehyde dehydrogenase upregulation detoxifies aldophosphamide a type of cyclophosphamide, and mutations in glutathione S-transferases, enzymes involved in drug-metabolizing conjugation reactions, can also affect cyclophosphamide detoxification [ 65 , 66 ].

Surgery, radiotherapy, and chemotherapy are complementary strategies in the treatment of BC patients. However, they are not sufficient to effectively treat all BC molecular subtypes, as they do not have the same response to radiotherapy or chemotherapy. Thus, personalized therapies are essential in the process for BC treatment.

3. Current Personalized Treatments for Breast Cancer: Strengths and Weaknesses

The current strategies of treatment are principally based on the tumor progression and BC molecular subtypes in order to offer the most personalized treatment for BC patients. The algorithm of BC treatment is represented in Figure 2 .

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Breast cancer treatment flow diagram. ( A ). Early-stage breast cancer. ( B ). Metastatic/advanced breast cancer. a Neoadjuvant chemotherapy for HR+ BC patients is not systematic. It is mainly administered to luminal B BC patients and/or elder BC patients. HR+: hormone receptors positive; HER2+: human epidermal growth factor receptor 2 positive; TNBC: triple-negative breast cancer; AIs: aromatase inhibitors; T-DM1: trastuzumab-emtansine.

3.1. Endocrine Therapy

Endocrine therapy is the main strategy to treat HR positive invasive BC. The purpose of this therapy is to target the ER directly (selective estrogen receptors modulators and degraders) or the estrogen synthesis (aromatase inhibitors) [ 67 ]. The most common types of endocrine therapy are selective estrogen receptor modulators (SERMs), selective modulators estrogen receptor degraders (SERDs), and aromatase inhibitors (AIs) [ 68 ]. Endocrine therapy mechanism of action and resistance are described in Figure 3 .

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Endocrine therapy mechanisms of action and resistance. The left part of the figure shows the mechanism of endocrine therapy through aromatase inhibitors, tamoxifen, and fulvestrant. The right part of the figure describes the mechanisms of resistance to endocrine therapy through the epigenetic modifications, the increase of coactivators and cell cycle actors, and the activation of other signaling pathways. Estrogens can go through the plasma membrane by a. diffusion as they are small non-polar lipid soluble molecules; b. binding to membrane ER initiating the activation of Ras/Raf/MAPK and PI3K/Akt signaling pathways which are blocked by tamoxifen. 1: inhibition of ER dimerization; 2: blockage of nucleus access; 3: ER degradation. ER: estrogen receptor; AIB1: amplified in breast cancer 1; IGF-1R: insulin growth factor receptor 1; IGF: insulin growth factor; HER: human epidermal receptors; EGF: epidermal growth factor; HB-EGF: heparin-binding EGF-like growth factor; TGF-α: transforming growth factor alpha; MEK/MAPK: mitogen activated protein kinase; PI3K: phosphoinositide 3-kinase; mTOR: mammalian target of rapamycin; Me: methylation; Ac: acetylation.

3.1.1. Selective Estrogen Receptor Modulators (SERMs)

SERMs, such as tamoxifen, toremifene, bazedoxifene, and raloxifene, are antiestrogens that compete with estrogen by binding to the ER. This binding changes the conformation of the ER ligand-binding domain, and once ER is translocated to the nucleus, it blocks co-factor recruitment and subsequent genes transcription involved in cell cycle progression (cyclin D1), cell proliferation (like IGF-1), or cell migration (collagenase) [ 69 , 70 ].

The most used SERMs is tamoxifen, approved by the US Food and Drugs Administration (FDA) in 1977. It is an adjuvant therapy orally administered for 5 to 10 years according to tumor aggressivity. Tamoxifen adjuvant treatment reduces recurrence risk by 50% for the first 5 years and 30% for the next 5 years [ 71 ]. Tamoxifen is given to either premenopausal or postmenopausal patients. However, for high-risk premenopausal patients, adding ovarian suppression is more effective than tamoxifen alone [ 72 ]. Tamoxifen can also be administered as neoadjuvant treatment, especially for elderly BC patients [ 73 ]. However, studies have demonstrated no difference in OS for ER+ BC patients when neoadjuvant tamoxifen is compared to surgery [ 74 , 75 ].

Other SERMs have since been developed, such as toremifene approved by the FDA in 1997 [ 76 ]. Studies comparing the effect of toremifene and tamoxifen in premenopausal patients with ER+ advanced BC have shown that toremifene efficacy and safety are similar to tamoxifen [ 77 , 78 ]. Bazedoxifene and raloxifene are administered as prevention treatment to postmenopausal patients at high risk of developing invasive BC and for preventing osteoporosis [ 79 , 80 , 81 ].

The most frequent adverse events of SERMs are hot flushes, nausea, vomiting, vaginal bleeding/discharges, and increased risk of thromboembolic events [ 82 ]. Of note, about 40% of HR+ BC patients will develop resistance to SERMs [ 83 ]. SERMs resistance can occur by the loss of ER expression or functions. Epigenetic modifications such as hypermethylation of CpG islands or histone deacetylation can lead to transcriptional repression of ER [ 84 ]. Another potential mechanism for ER expression loss is the overpopulation of ER-negative cells in heterogenous ER+ tumors [ 85 ]. Mutations in the ligand-binding domain of ER gene ( ESR1 ) inhibit the binding of estrogen to the ER leading to the abolition of downstream signaling. Moreover, abnormal splicing can lead to truncated, nonfunctional ER protein [ 86 , 87 ]. Another explanation for SERMs resistance is the abnormal expression of ER coregulators [ 88 ]. Coregulators are very important in the ER pathway as they can increase or decrease ER activity depending on incoming signals [ 89 ]. The most studied coregulator involved in SERMs resistance is the AIB1 (Amplified in breast cancer 1) coactivator protein, often overexpressed in resistant breast tumors [ 90 ]. In particular, in ER+ cells that overexpress HER2, there is a crosstalk between HER2 and AIB1. HER2 induces phosphorylation of AIB1 leading to evasion and subsequent activation of the ER signaling pathway even though it is inhibited by SERMs [ 91 ]

3.1.2. Selective Estrogen Receptor Degraders (SERDs)

To counteract the large proportion of tamoxifen-resistant tumors, a new type of therapeutic agents with a different mechanism of action has been developed: SERDs. In contrast to SERMs, SERDs completely block the ER signaling pathway.

Fulvestrant is the main SERD administered. It was discovered by Wakeling and collaborators in 1987 and demonstrated pure anti-estrogen activity [ 92 ]. Fulvestrant binds to ER with a higher affinity than tamoxifen. Once it binds to the ER, it inhibits receptor dimerization and then blocks ER translocation to the nucleus leading to its degradation [ 93 , 94 , 95 ].

Fulvestrant is administered by intramuscular injections, and common adverse effects are nausea, pain, and headaches [ 96 ]. Fulvestrant is approved to treat postmenopausal and premenopausal patients with ovarian function suppression, with ER+ advanced or metastatic BC on prior endocrine therapy [ 97 ]. More recently (in 2017), fulvestrant was approved as first-line monotherapy for advanced ER+ breast cancer [ 98 ]. According to the 2021 NCCN guidelines, fulvestrant combined with endocrine therapy or CDK4/6 inhibitors is one of the preferred regimens for second-line therapy in ER+ advanced or metastatic BC [ 99 ]. The combination of fulvestrant with other endocrine therapies has not shown any advantages over fulvestrant used in monotherapy [ 100 , 101 ]. Clinical studies have shown benefits from fulvestrant when administered in higher doses to patients with ESR1 -mutated advanced BC [ 102 , 103 ]. Indeed, ESR1 mutations occur in nearly 20% of cases of ER+ BC [ 86 ].

However, fulvestrant can lead to resistance by different mechanisms. For example, by upregulating the PI3K (phosphatidylinositol 3-kinase), mTOR (mammalian target of rapamycin) and Ras-ERK (extracellular signal-regulated kinase) signaling pathways. PI3K/Akt/mTOR is a downstream signaling pathway of ER activation and plays an important role in antiestrogen therapy resistance [ 104 ]. PI3K pathway activation can occur independently of ER by binding to the epidermal growth factor (EGF) [ 105 ]. Moreover, it has been shown that Akt overexpression leads to fulvestrant resistance [ 106 ]. IGF-1R activation (insulin-like growth factor 1 receptor) may be another mechanism of resistance to fulvestrant. IGF-1R expression is involved in cell survival and promotes metastatic cell proliferation. The interaction between IGF-1R and ER initiates the activation of IGF-1R/MAPK (mitogen-activated protein kinase) and IGF-1R/PI3K signaling leading to antiestrogen resistance [ 107 ].

3.1.3. Aromatase Inhibitors (AIs)

Aromatase is a cytochrome P50 enzyme involved in the synthesis of androgens and estrogens [ 108 ]. Aromatase is found in the breast, uterus, and other estrogen-sensitive tissues in specific levels depending on menopausal status [ 109 , 110 ]. Aromatase expression is increased in breast tumors and associated with high estrogen levels. Therefore, high expression of aromatase promotes ER+ tumor proliferation [ 111 ].

Aromatase inhibitors (AIs) block aromatase enzyme activity, leading to the inhibition of estrogen synthesis. Current AIs can be classified into two categories: steroidal AIs and non-steroidal AIs [ 112 ]. Exemestane, a steroidal AI, has a steroid-like structure similar to androstenedione, which is the aromatase substrate. Exemestane irreversibly binds to the aromatase substrate-binding site leading to its inactivation [ 113 ]. Non-steroidal AIs include letrozole and anastrozole. They both bind non-covalently and competitively to the aromatase substrate-binding site and prevent the binding of androgens by saturating the binding site [ 112 ].

AIs are an oral treatment administered only to postmenopausal women (including patients that become postmenopausal following ovarian suppression). It is administered alone or in combination with tamoxifen as adjuvant therapy for HR+ BC patients [ 114 , 115 , 116 , 117 ]. AIs can be administered for 5 years or 2–3 years if followed by tamoxifen and up to 5 years after previous tamoxifen or AI treatment. For advanced or metastatic HR+ BC, AIs can be delivered as first-line and second-line therapy. Patients who become postmenopausal after or during the 5 years of tamoxifen treatment can receive AIs, such as letrozole, as an extended treatment strategy [ 118 , 119 ].

Estrogens have protective effects on the cardiovascular system by regulating serum lipids concentrations and increasing vasodilatation [ 120 ]. Hence, AIs might increase the risk of developing cardiovascular diseases by reducing estrogen levels in the blood [ 121 ]. Other adverse effects of AIs include hot flushes, vaginal dryness, fatigue, and osteoporosis [ 122 ]. ER+ tumors can acquire AI resistance. Some mechanisms of AI resistance are similar to those conferring SERM or SERD resistance, such as ESR1 mutations, epigenetic modifications, and PI3K pathway upregulation [ 123 ]. However, other mechanisms of action are involved in AI resistance. For example, the upregulation of cyclin-dependent kinase 4 (CDK4) or cyclin-dependent kinase 6-retinoblastoma (CDK6-RB) pathways can lead to an estrogen-dependent cell progression [ 124 ]. Clinical studies have shown better benefits from CDK4-CDK6 inhibitors in combination with AIs compared to AIs alone [ 125 , 126 ].

Endocrine therapy is a well-established treatment strategy for HR+ tumors. Over the last decades, SERMs, SERDs and AIs have been proven as safe and effective personalized therapy for HR+ BC patients, and these therapeutic strategies have shown continued improvements. However, the main drawback of endocrine therapy is acquired or de novo resistance [ 127 ]. Hence, it is essential to develop new therapeutic agents that use different modes of action to treat HR+ BC more efficiently.

3.2. Anti-HER2 Therapy

The overexpression of HER2 is associated with worse survival outcome compared to HR-positive/HER2-negative BC [ 128 , 129 ]. Hence, therapies targeting HER2 are essential to treat HER2-positive BC. The current anti-HER2 therapies comprise antibodies that target specific HER2 epitopes, tyrosine kinase inhibitors (TKIs) and, more recently, antibody-drug conjugates (ADCs) [ 130 ]. Anti-HER2 mechanisms of action and resistance are described in Figure 4 .

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Anti-HER2 therapy mechanisms of action and resistance. The left part of the figure describes the mechanism of action of anti-HER2 therapy through anti-HER2 antibody (trastuzumab and pertuzumab), tyrosine kinase inhibitors (lapatinib and nerotinib), and trastuzumab-emtansine (T-DM1). The right part of the figure describes the mechanism of resistance to anti-HER2 therapy through constitutive active p95 HER2 fragment, activation of other signaling pathways, and rapid recycling of HER2-T-DM1. ADCC: antibody-dependent cellular cytotoxicity; HER2: human epidermal growth factor receptor 2; EGF: epidermal growth factor, HB-EGF: heparin-binding EGF-like growth factor; TGF-α: transforming growth factor alpha; T-DM1: trastuzumab-emtansine; IGF-1R: insulin growth factor receptor 1; IGF: insulin growth factor; HGF: hepatocyte growth factor; MEK/MAPK: mitogen activated protein kinase; PI3K: phosphoinositide 3-kinase; mTOR: mammalian target of rapamycin; PTEN: phosphatase and tensin homolog.

3.2.1. Antibodies Targeting HER2

The first developed HER2-targeted antibody, trastuzumab (Herceptin), was approved by the FDA in 1998 [ 131 , 132 ]. Trastuzumab targets subdomain IV of the HER2 extracellular domain. However, the mechanism underlying trastuzumab’s therapeutic effect is not well understood. Multiple studies have reported hypotheses to explain trastuzumab’s mechanism of action. For instance, trastuzumab may inhibit the formation of the HER2-HER3 heterodimer, known to be the most oncogenic pair in the HER family [ 133 ]. It could also inhibit the formation of the active p95 HER2 fragment by preventing cleavage of the HER2 extracellular domain [ 134 ]. An indirect antitumor effect could be activating antibody-dependent cellular cytotoxicity (ADCC) by engaging with Fc receptors on immune effector cells [ 135 ].

Initially, trastuzumab was approved for administration in metastatic HER2+ BC, increasing the clinical benefits of first-line chemotherapy [ 132 ]. Trastuzumab has also demonstrated its efficacy and safety in early-stage HER2+ BC. It is given as neoadjuvant or adjuvant therapy in combination with other anti-HER2 treatments and/or with chemotherapy [ 136 , 137 , 138 ]. The recommended dose for intravenous trastuzumab is 4 mg/kg followed by 2 mg/kg weekly for 1 year in the adjuvant setting for early-stage HER2+ BC and until disease-free progression for metastatic HER2+ BC [ 139 ].

Pertuzumab (Perjeta) is another antibody that targets the HER2 extracellular domain but binds to subdomain II. Once it binds to HER2, pertuzumab prevents HER2 heterodimerization with other HER family members, leading to inhibition of downstream signaling pathways [ 140 ]. Like trastuzumab, one of pertuzumab’s indirect antitumor effects is activating the ADCC pathway [ 141 ]. Multiple clinical trials have shown that pertuzumab, combined with trastuzumab and chemotherapy, improved OS in metastatic HER2+ BC patients compared to trastuzumab and chemotherapy alone [ 142 , 143 , 144 , 145 ]. The benefits of pertuzumab have also been shown in early-stage HER2+ BC, as pertuzumab can be used in the neoadjuvant or adjuvant setting combined with trastuzumab and chemotherapy [ 146 , 147 , 148 , 149 ]. Pertuzumab is administered in fixed doses of 840 mg followed by 420 mg every three weeks [ 150 ].

Despite the major positive impacts of trastuzumab and pertuzumab in HER2+ BC treatment, only one-third of BC patients with HER2+ tumors benefit from anti-HER2 antibodies [ 151 ]. One of the hypotheses explaining this resistance concerns structural modifications of HER2, which hinder antibody binding. Alternative splicing can lead to a truncated isoform lacking the extracellular domain, thus forming a constitutive active p95 HER2 fragment [ 152 ]. The overexpression of other tyrosine kinases can bypass the signaling pathways mediated by HER2. It has been shown that cells overexpressing IGF-1R overcome cell cycle arrest by increasing CDK2 kinase activity [ 153 ]. Moreover, the overexpression of c-Met (a hepatic growth factor receptor) synergizes with HER2 signaling to confer resistance to anti-HER2 antibodies. Indeed, c-Met physically interacts with HER2, and c-Met depletion renders cells more sensitive to trastuzumab [ 154 , 155 ]. Another hypothesis for anti-HER2 antibody resistance is intracellular alterations in HER2 downstream signaling pathways. HER2 activates PI3K/Akt signaling, and PTEN (phosphatase and tensin homolog) is a well-known inhibitor of this pathway [ 156 ]. Tumors with a loss of PTEN function and/or constitutive activation of PI3K due to alteration mutations achieve worse therapeutic outcomes with trastuzumab [ 157 , 158 ].

3.2.2. Tyrosine Kinase Inhibitors (TKIs)

Since tumors may be resistant to anti-HER2 antibodies, new approaches have been developed. TKIs such as lapatinib, neratinib, or pyrotinib are small molecules that compete with ATP at the catalytic domain of the receptor to prevent tyrosine phosphorylation and HER2 downstream signaling [ 159 ].

Lapatinib is a dual EGFR/HER2 TKI blocking both HER1 and HER2 activation [ 160 ]. In metastatic BC, clinical trials have shown that lapatinib offers more benefits than chemotherapy alone [ 161 , 162 , 163 ]. The effects of lapatinib in the neoadjuvant/adjuvant setting have also been evaluated. As a neoadjuvant treatment, lapatinib plus trastuzumab combined with chemotherapy were more efficient than chemotherapy combined with lapatinib or trastuzumab alone [ 164 ]. Lapatinib as adjuvant treatment showed modest antitumor efficacy compared to placebo in a randomized, controlled, and multicenter phase III trial (TEACH) [ 165 ]. For luminal B (ER/PR+; HER2+) advanced or metastatic BC, lapatinib can be administered in combination with AIs.

Neratinib is an irreversible TKI targeting HER1, HER2, and HER4 [ 166 ]. The FDA approved Neratinib in 2017 as an extended adjuvant treatment for patients with HER2+ early-stage BC and combination with trastuzumab in the adjuvant setting [ 167 , 168 ]. Neratinib can be delivered in combination with capecitabine as a third-line and beyond therapy for HER2+ advanced or metastatic BC.

More recently, pyrotinib, a new generation TKI targeting HER1, HER2 and HER4, has been developed [ 169 ]. Pyrotinib is still under clinical trials to prove its efficacy and safety [ 170 ]. However, in 2018, the Chinese State Drug Administration approved pyrotinib in combination with or after chemotherapy treatment for patients with HER2+ advanced or metastatic BC [ 171 ].

Despite the recent development of TKI treatments, patients can still exhibit intrinsic or acquired resistance to these agents. Three mechanisms of action have been hypothesized: (1) activation of compensatory pathways, (2) HER2 tyrosine kinase domain mutation, and (3) other gene amplification [ 172 ]. For instance, activation of the PI3K/Akt pathway and FOXO3A (Forkhead transcription factor) by the upregulation of HER3 can lead to lapatinib resistance [ 173 ]. Other tyrosine kinases can be involved, such as c-Met, also known to be implicated in trastuzumab resistance. C-Met induces the activation of PI3K/Akt signaling in lapatinib-resistant BC [ 174 ]. Mutations in the HER2 tyrosine kinase domain lead to the constitutive activation of HER2 by substituting individual amino acids [ 175 ]. Lastly, it has been shown that the amplification of the NIBP (TRAPPC9, Trafficking Protein Particle Complex 9) gene occurs in HER2+ lapatinib-resistant tumors. The inhibition of NIBP makes resistant cells sensitive to lapatinib [ 176 ].

3.2.3. Trastuzumab-Emtansine (T-DM1)

Trastuzumab-emtansine (T-DM1) is an antibody-drug conjugate (ADC), which is a conjugate of trastuzumab and a cytotoxic molecule, DM1, a derivative of maytansine [ 177 ]. T-DM1 binds to HER2 with the trastuzumab part. The formed complex is then internalized for degradation, releasing DM1 metabolites into the cytoplasm. DM1 then inhibits microtubule assembly causing cell death [ 178 , 179 ]. Thus, T-DM1 consists of the antitumor effects of trastuzumab and those associated with DM1 metabolites [ 180 ].

Three phase III clinical trials have evaluated the safety and efficacy of T-DM1 for HER2+ metastatic BC [ 181 , 182 , 183 ]. They have shown that T-DM1 improves OS and DFS of HER2+ metastatic BC patients compared to lapatinib in combination with trastuzumab or chemotherapy [ 181 , 182 , 183 ]. T-DM1 as neoadjuvant treatment has less efficacy compared with trastuzumab or pertuzumab with chemotherapy [ 146 ]. This suggests that T-DM1 should not be administered as a neoadjuvant treatment but as a first-line or second-line therapy for HER2+ metastatic BC. The 2021 NCCN guidelines recommend using T-DM1 as second-line therapy for HER2+ advanced or metastatic BC [ 99 ].

The mechanism of action of T-DM1 involves those related to trastuzumab and DM1, so the observed resistance to T-DM1 could come from interference in one or both constituents [ 184 ]. The mechanism of T-DM1 resistance has been hypothesized to involve (1) the loss of trastuzumab mediated activity, (2) the dysfunctional intracellular trafficking of T-DM1, and (3) the impairment of DM1 mediated cytotoxicity [ 185 ].

As previously described in this review, the reduction of trastuzumab effects can occur by reduced HER2 expression, dysregulation of PI3K signaling, or the activation of alternative tyrosine kinase receptors [ 153 , 154 , 156 , 186 ]. The alteration of HER2-T-DM1 complex internalization can go through a rapid recycling of HER2 to the plasma membrane leading to the inhibition of DM1 metabolism released into the cytoplasm [ 187 ]. The internalization of the HER2-T-DM1 complex occurs through the formation of lysosomes. These vesicles enclose lysosomal enzymes involved in HER2-T-DM1 complex degradation. In T-DM1-resistant tumors, the level of lysosomal enzymes is inhibited [ 188 , 189 ]. T-DM1 also disrupts microtubule assembly causing incomplete spindle formation resulting in mitotic catastrophe and apoptosis [ 190 ]. Cells resistant to T-DM1 can avoid this process by reducing the induction of Cyclin-B1, an enzyme essential for cell cycle progression [ 191 ].

HER2+ BC are aggressive and associated with poor prognosis and metastasis, and recurrences. Anti-HER2 therapy has greatly improved the management of HER2+ BC. However, 25% of early-stage HER2+ BC patients will have a recurrence after the initial anti-HER2 treatment [ 192 ]. The emergence of new therapeutic agents specific for HER2+ BC provides new hope to treat this particularly aggressive BC subtype.

3.3. PARP Inhibitors

The prevalence of BRCA (Breast Cancer genes) mutations in TNBC patients is approximately 20% [ 193 ]. BRCA1 and BRCA2 are proteins involved in the DNA damage response to repair DNA lesions [ 194 ]. Mutations in BRCA 1/2 genes are associated with an increased risk of breast and ovarian cancers [ 195 ].

PARP (poly-(ADP-ribose) polymerase protein) proteins are also involved in the DNA damage response as they recruit DNA repair proteins, such as BRCA1 and BRCA2, to the damage site [ 196 ]. PARP inhibitors (PARPi) were developed to inhibit DNA repair in BRCA-mutated BC since cells defective in BRCA functions cannot repair DNA damage when PARP is inhibited [ 197 ]. The principal PARPis currently in clinical development are olaparib, talazoparib, veliparib, and rucaparib [ 198 ]. PARP inhibitors mechanisms of action and resistance are described in Figure 5 .

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PARP inhibitors mechanisms of action and resistance. The left part of the figure describes the mechanism of PARP inhibitors in the context of BRCA mutated breast cancer. The right part of the figure describes the mechanism of resistance to PARP inhibitors through secondary intragenic mutations restoring BRCA proteins functions and the decrease of the recruitment of nucleases (MUS81 or MRE11) to protect the replication fork. PARP: poly-(ADP-ribose) polymerase protein; PARPi: PARP inhibitors; BRCA: breast cancer protein; MUS81: methyl methanesulfonate ultraviolet sensitive gene clone 81; MRE11: meiotic recombination 11.

3.3.1. Olaparib

Olaparib is the first FDA-approved PARPi for the treatment of BRCA -mutated BC [ 199 ]. Phase I and phase II trials evaluating the effects of olaparib monotherapy in germline BRCA-mutated (gBRCAm) BC proved its clinical benefits by improving progression-free survival (PFS) [ 200 , 201 , 202 , 203 ]. The phase III, randomized, open-label, OlympiAD trial compared olaparib monotherapy vs. standard chemotherapy in patients with BRCA mutated HER2-negative BC. This trial showed that olaparib has better efficacy and tolerability than standard chemotherapy for this group of patients [ 204 ]. Olaparib has also been tested in combination with chemotherapy. A phase I study evaluated the effects of olaparib in combination with paclitaxel in unselected TNBC patients [ 205 ]. The overall response rate (ORR) for these patients was 37%. Two phase I studies evaluating the combination of olaparib with cisplatin or carboplatin in gBRCAm BC patients showed improved ORR [ 206 , 207 ].

3.3.2. Talazoparib

Talazoparib has the highest PARP-DNA trapping efficiency among the PARPis [ 208 ]. A phase II trial testing the effects of talazoparib on gBRCAm early-stage BC showed decreased tumor size in all patients included [ 209 ]. Other phase I and II trials with gBRCAm BC patients receiving talazoparib confirmed the efficiency of this PARPi [ 210 , 211 ]. The EMBRACA study, an open-label phase III trial, compared talazoparib monotherapy to chemotherapy in gBRCAm, HER2-negative BC patients [ 212 ]. PFS and ORR were improved with talazoparib compared to chemotherapy alone.

3.3.3. Veliparib

Veliparib has been mostly evaluated in combination with chemotherapy. For example, the phase II multicenter I-SPY2 trial tested the combination of veliparib and neoadjuvant chemotherapy in unselected TNBC patients [ 213 ]. The predicted complete response rate (pCR) was 51% with veliparib and chemotherapy vs. 26% in the control arm (chemotherapy alone). The phase II BROCADE study evaluated the combination of veliparib with carboplatin and paclitaxel in gBRCAm BC patients [ 214 ]. The ORR was improved with the combination of veliparib and chemotherapy compared to chemotherapy alone. Lastly, the phase III BRIGHTNESS study evaluated the addition of veliparib to carboplatin in the standard neoadjuvant chemotherapy setting [ 211 ]. The addition of veliparib showed no further benefit to chemotherapy.

3.3.4. Rucaparib

Rucaparib is the second PARPi that has been FDA approved for gBRCAm BC patients [ 215 ]. Intravenous rucaparib was tested in a phase II trial of gBRCAm BC patients [ 216 ]. Stable disease, meaning no tumor development, was reported in 44% of patients. Rucaparib was also tested in combination with chemotherapy in unselected TNBC patients [ 217 ]. This phase I study showed that rucaparib could be safely used in combination with chemotherapy. The phase II, a randomized BRE09-146 trial, evaluated rucaparib in combination with cisplatin vs. cisplatin alone in gBRCAm patients with residual disease following neoadjuvant therapy [ 218 ]. DFS was similar in the two arms, as low-dose rucaparib did not affect cisplatin toxicity. However, the rucaparib dose may not have been sufficient to inhibit PARP activity.

Tumor cells can become resistant to PARPi by different mechanisms [ 219 ].

First, secondary intragenic mutations that restore BRCA proteins functions can lead to PARPi resistance [ 220 ]. These genetic events can lead to the expression of nearly full-length proteins or full-length wild-type proteins with complete restored functions [ 221 ]. This has been reported mostly in ovarian cancer patients, and it has also been demonstrated in BC cell line models [ 222 ]. Tumor cells with missense mutations conserving the N-terminal and C-terminal domains of BRCA proteins also lead to poor PARPi response [ 223 ]. Another mechanism of action leading to PARPi resistance is decreased expression of PARP enzymes. Indeed, tumor cells with low PARP1 expression acquire resistance to veliparib [ 224 ].

In addition, tumor cells can find alternative mechanisms to protect the replication fork. It has been shown that PARPi-resistant cells can reduce the recruitment of the MRE11 (meiotic recombination 11) nuclease to the damage site, leading to the protection of the fork by blocking its access [ 225 ]. Another study has shown that BRCA2 -mutated tumors acquired PARPi resistance by reducing the recruitment of the MUS81 (methyl methanesulfonate ultraviolet sensitive gene clone 81) nuclease to protect the replication fork [ 226 ].

Chemotherapy has been the pioneer treatment strategy for TNBC for decades. The development of PARPis has been a major improvement in the treatment of TNBC and, more specifically, gBRCAm TNBC, as they have shown more benefits over chemotherapy [ 227 ]. However, TNBC is a heterogenous BC subtype, and PARPis cannot treat all TNBCs as it is administered only for gBRCAm TNBC [ 228 ]. Therefore, it is necessary to develop specific targeted therapies to treat each TNBC subtype.

4. New Strategies and Challenges for Breast Cancer Treatment

4.1. emerging therapies for hr-positive breast cancer.

As mentioned in Section 3.1 , the major mechanisms of action of current endocrine therapy resistance occur via (1) the mTOR/PI3K/Akt signaling pathway and (2) the actors of the cell cycle progression CDK4/6. Therefore, emerging therapies for HR+ BC mainly target these pathways to bypass estrogen-independent cell survival [ 229 ]. The most recent completed clinical trials on emerging therapies for HR+ BC are presented in Table 1 .

Most recent completed clinical trial on emerging therapies for HR-positive breast cancer.

HR+: hormone receptors positive; HER2-: human epidermal growth factor receptor 2 negative; MBC: metastatic breast cancer; BC: breast cancer; PFS: progression free survival; CBR: clinical benefit rate; ORR: objective response rate; pCR: pathologic complete response; HR: hazard ratio.

4.1.1. mTOR/PI3K/AKT Pathway Inhibitors

The mTOR/PI3K/Akt pathway inhibitors can be divided into different categories according to the target in the pathway. Specific inhibitors have been developed to target all or specific isoforms of PI3K, mTORC1 and Akt [ 251 ].

Pan-Pi3K Inhibitors

Pan-PI3K inhibitors target all PI3K isoforms resulting in significant off-target effects. The main pan-PI3K inhibitors are buparlisib and pictilisib [ 252 ]. Multiple clinical trials have tested the effects of pan-PI3K inhibitors in luminal BC.

The phase III randomized double-blinded BELLE-2 trial compared buparlisib combined with fulvestrant, to fulvestrant monotherapy in luminal A advanced or metastatic BC patients [ 230 ]. The results of this trial showed a modest improvement in PFS when buparlisib was added to fulvestrant. Another phase III clinical trial (BELLE-3) studied the effects of buparlisib plus fulvestrant in luminal A advanced or metastatic BC patients with no benefits from endocrine therapy [ 231 ]. Though PFS was significantly improved with buparlisib, there were severe adverse effects such as hyperglycemia, dyspnea, or pleural effusion. Lastly, the phase II/III BELLE-4 clinical trial evaluated buparlisib plus paclitaxel in HER2-negative locally advanced or metastatic BC patients [ 232 ]. The addition of buparlisib to paclitaxel did not improve PFS in these patients. Thus, further studies on buparlisib in HR+ BC were not conducted. The phase II randomized, double-blinded FERGI clinical trial analyzed the effects of pictilisib plus fulvestrant in luminal A BC patients resistant to AI [ 233 ]. The addition of pictilisib to fulvestrant did not improve PFS. Moreover, severe adverse effects occurred when the dose of pictilisib was increased. These results were confirmed for pictilisib plus paclitaxel, as the phase II PEGGY study showed no benefit from pictilisib in PI3K-mutated HER2-negative BC patients [ 234 ].

Hence, pan-PI3K inhibitors are not optimal to treat HR+ BC due to their toxicity and lack of efficacy.

Isoform-Specific PI3K Inhibitors

To sort out issues related to off-target effects and toxicities with pan-PI3K inhibitors, isoform-specific PI3K inhibitors have been developed. These isoform-specific PI3K inhibitors can specifically target the PI3K p110α, p110β, p110δ, and p110γ isoforms [ 252 ]. Multiple clinical trials have tested the effects of isoform-specific PI3K inhibitors.

PI3K p110α is the most commonly mutated isoform in BC [ 253 ]. Alpelisib is the first FDA-approved PI3K p110α isoform inhibitor. A phase Ib clinical trial tested the effects of alpelisib and letrozole in patients with ER+ metastatic BC refractory to endocrine therapy [ 235 ]. The clinical benefit of the alpselisib and letrozole combination was higher for patients with PI3K-mutated BC, but clinical activity was still observed in patients with non-mutated tumors. The phase III randomized SOLAR-1 clinical trial compared the effects of alpelisib plus fulvestrant to fulvestrant alone in luminal A advanced BC patients who received no benefits from prior endocrine therapy [ 236 ]. The addition of alpelisib improved PFS for patients with PI3K-mutated BC.

Taselisib targets the PI3K p110α, p110γ and p110δ isoforms [ 254 ]. Taselisib was tested in the SANDPIPER study, a phase III randomized clinical trial, in combination with fulvestrant in patients with ER+ metastatic BC resistant to AIs [ 238 ]. Although the addition of taselisib slightly improved PFS, further clinical trials with taselisib were interrupted since high rates of severe adverse events were detected.

mTORC1 Inhibitors

mTORC1 inhibitors, such as everolimus, block the mTORC1 dependent phosphorylation of s6k1 [ 255 ]. The BOLERO-2 phase III randomized clinical trial investigated the effects of exemestane with or without everolimus in AI-resistant ER+ metastatic BC patients [ 240 ]. The combination of everolimus and exemestane improved PFS. The TAMRAD phase II randomized open-label study compared the effects of tamoxifen with or without everolimus in AI-resistant luminal A BC patients [ 241 ]. This study showed an improvement in overall survival (OS) when everolimus was given in combination with tamoxifen. The findings of these two clinical trials led to FDA approval of everolimus. More recently, the PrE0102 phase II randomized clinical trial showed that the addition of everolimus to fulvestrant improved PFS of patients with AI-resistant ER+ BC compared to fulvestrant alone [ 242 ].

Akt Inhibitors

Akt inhibitors target all Akt isoforms as Akt 1, 2, and 3 isoforms share very similar structures [ 256 ]. Capivasertib is the principal Akt inhibitor under investigation in different clinical trials. The FAKTION phase II multi-centered randomized clinical trial compared the effects of capivasertib plus fulvestrant to fulvestrant plus placebo in AI-resistant luminal A advanced BC patients [ 243 ]. PFS was significantly improved with the combination of capivasertib and fulvestrant in comparison with the placebo arm.

The AKT1 E17K activating mutation is the most common in Akt and occurs in approximately 7% of ER+ metastatic BC. This mutation in the Akt lipid-binding pocket leads to constitutive Akt activation by modifying its localization to the membrane [ 257 ]. A phase I study analyzed the effects of capivasertib alone or in combination with fulvestrant in a cohort of patients with AKT1 E17K mutation ER+ metastatic BC [ 244 ]. Capivasertib, in combination with fulvestrant, demonstrated clinically meaningful activity and better tolerability compared to capivasertib alone.

4.1.2. CDK4/6 Inhibitors

There are currently three CDK4/6 inhibitors approved to treat HR+/HER2- metastatic BC: palbociclib, ribociclib, and abemaciclib. They can be administered as first-line treatment combined with AIs or as second-line treatment combined with fulvestrant [ 258 ].

First-Line Treatment

Palbociclib, a highly selective CDK4/6 inhibitor, is the first FDA-approved CDK4/6 inhibitor as first-line treatment combined with AIs for metastatic or advanced HR+ BC patients [ 259 ].

PALOMA-1 is an open-label, randomized phase II study that evaluated the effects of palbociclib in combination with letrozole vs. letrozole alone as first-line treatment for HR+ advanced BC patients [ 126 ]. The addition of palbociclib to letrozole significantly improved PFS in HR+ BC patients. A phase III study was performed (PALOMA-2) to confirm these findings and expand the efficacy and safety of palbociclib, [ 245 ]. This double-blinded clinical trial tested the combination of palbociclib and letrozole in postmenopausal BC patients without prior systemic therapy for advanced BC. The addition of palbociclib to letrozole significantly improved PFS and ORR.

Ribociclib is the second FDA-approved CDK4/6 inhibitor for first-line treatment in postmenopausal advanced BC patients in combination with AIs [ 260 ]. The phase III MONALEESA-2 clinical trial results showed improved PFS and ORR with the combination of ribociclib and letrozole in HR+ metastatic BC patients. The clinical benefits and manageable tolerability observed with ribociclib and letrozole are maintained with longer follow-up compared to letrozole alone [ 247 ].

Abemaciclib has been tested in the phase III randomized double-blinded MONARCH-3 study [ 250 ]. HR+ advanced BC patients with no prior systemic therapy received abemaciclib plus anastrozole or letrozole or AIs plus placebo in the control arm. PFS and ORR were significantly improved with the combination of abemaciclib and AIs.

Second-Line Treatment

As second-line treatment, palbociclib can be given in combination with fulvestrant in advanced or metastatic BC patients with disease progression after endocrine therapy [ 261 ]. This was confirmed in the phase III multi-centered randomized double-blinded PALOMA-3 trial [ 246 ]. BC patients who received palbociclib plus fulvestrant had significantly longer PFS compared to fulvestrant plus placebo.

The phase III MONALEESA-3 study tested the effects of ribociclib plus fulvestrant in patients with HR+ advanced BC who received prior endocrine therapy in the advanced setting [ 248 ]. The PFS and ORR were significantly improved when ribociclib was added to fulvestrant. Thus, ribociclib plus fulvestrant can be considered as second-line treatment for these BC patients.

Abemaciclib has been recently approved in combination with fulvestrant for HR+ advanced or metastatic BC patients with disease progression after endocrine therapy. This was based on the results of the phase III, double-blinded MONARCH 2 study [ 249 ]. The combination of abemaciclib and fulvestrant demonstrated a significant improvement of PFS and ORR compared to fulvestrant plus placebo in HR+ metastatic BC patients who experienced relapse or progression after prior endocrine therapy.

mTOR/PI3K/Akt inhibitors and CDK4/6 inhibitors show great promise for advanced HR+ BC resistant to endocrine therapy. To leverage the potential of these two types of therapies, some preclinical studies have evaluated a triple therapy combination including PI3K inhibitors, CDK4/6 inhibitors, and endocrine therapy (see the summarized table at the end of the manuscript) [ 262 ].

4.2. New Strategic Therapies for HER2-Positive Breast Cancer

As mentioned in Section 3.2 , HER2+ BC is currently treated with specific HER2 targeting antibodies or tyrosine kinase inhibitors (TKIs), and more recently, with TDM-1, an antibody-drug conjugate. These treatments have greatly improved HER2+ BC survival. However, 25% of HER2+ BC patients will still develop resistance to anti-HER2 treatment. Hence, new therapeutic strategies are emerging, such as new antibodies targeting HER2, new TKIs, vaccines, and PI3K/mTOR and CDK4/6 inhibitors [ 263 ]. The most recent completed clinical trials on new strategies for HER2+ BC treatment are gathered in Table 2 .

Most recent completed clinical trials on emerging therapies for HER2+ breast cancer.

HER2+: human epidermal growth factor receptor 2 positive; ER+: estrogen receptor positive; HLA2/3: human leucocyte antigen 2/3; MBC: metastatic breast cancer; BC: breast cancer; PFS: progression free survival; CBR: clinical benefit rate; ORR: objective response rate; DFS: disease-free survival OS: overall survival GM-CSF: granulocyte macrophage colony-stimulated factor; HR: hazard ratio.

4.2.1. New Antibodies

Novel types of antibodies have been developed to target HER2+ BC more efficiently. They can be divided into three categories: antibody-drug conjugates (ADC), modified antibodies, and bispecific antibodies.

Antibody-Drug Conjugates (ADC)

ADCs are the combination of a specific monoclonal antibody and a cytotoxic drug that is released in the antigen-expressing cells [ 280 ]. The most common ADC is TDM-1, and the promising results with TDM-1 have led to the development of new ADCs.

Trastuzumab-deruxtecan (DS-8201a) is a HER2-targeting antibody (trastuzumab) linked to a DNA topoisomerase I inhibitor (deruxtecan) [ 281 ]. A phase I study demonstrated that DS-8201a had antitumor activity even with HER2 low-expressing tumors [ 282 ]. These results led to phase II and phase III clinical trials. The DESTINY-Breast01 clinical trial is an open-labeled, single-group, multicentered phase II study [ 264 ] was evaluated in HER2+ metastatic BC patients who received prior TDM-1 treatment. DS-8201a showed durable antitumor activity for these patients. Two phase III clinical trials are currently evaluating DS-8201a. DESTINY-Breast02 (ClinicalTrials.gov identifier: {"type":"clinical-trial","attrs":{"text":"NCT03523585","term_id":"NCT03523585"}} NCT03523585 ) is comparing DS-8201a to standard treatment (lapatinib or trastuzumab) in HER2+ metastatic BC patients previously treated with TDM-1. The DESTINY-Breast03 (ClinicalTrials.gov identifier: {"type":"clinical-trial","attrs":{"text":"NCT03529110","term_id":"NCT03529110"}} NCT03529110 ) trial is evaluating the effects of DS-8201a vs. TDM-1 in HER2+ metastatic BC patients with prior trastuzumab and taxane treatment.

Trastuzumab-duocarmycin (SYD985) is a HER-2 targeting antibody (trastuzumab) conjugate with a cleavable linker-duocarmycin payload that causes irreversible alkylation of the DNA in tumor cells leading to cell death [ 283 ]. A dose-escalation phase I study evaluated the effects of SYD85 in BC patients with variable HER2 status and refractory to standard cancer treatment [ 284 ]. Trastuzumab-duocarmycin showed clinical activity in heavily pretreated HER2+ metastatic BC patients, including TDM-1 resistant and HER2-low BC patients. After these promising results, a phase I expansion cohort study was performed on the same type of patients (heavily pretreated HER2+ or HER2-low BC patients) [ 265 ]. This study confirmed previous results on the efficacy of STD985. A phase III clinical trial (TULIP-ClinicalTrials.gov identifier: {"type":"clinical-trial","attrs":{"text":"NCT03262935","term_id":"NCT03262935"}} NCT03262935 ) is ongoing to compare SYD985 to the treatment chosen by the physician in HER2+ metastatic BC patients. Other ADCs are under clinical trials to test their safety and activity for HER2+ advanced BC patients. RC48 is an anti-HER2 antibody conjugated with monomethyl auristatin E that demonstrated promising efficacy and a manageable safety profile in an open-labeled, multicentered phase II study (ClinicalTrials.gov identifier: {"type":"clinical-trial","attrs":{"text":"NCT02881138","term_id":"NCT02881138"}} NCT02881138 ) [ 248 ]. PF06804103 conjugates an anti-HER2 monoclonal antibody and the cytotoxic agent, Aur0101. In a phase I study (ClinicalTrials.gov identifier: {"type":"clinical-trial","attrs":{"text":"NCT03284723","term_id":"NCT03284723"}} NCT03284723 ), PF06804103 showed manageable toxicity and promising antitumor activity [ 249 ]. XMT1522 showed encouraging results in a dose-escalation phase I study (ClinicalTrials.gov identifier: {"type":"clinical-trial","attrs":{"text":"NCT02952729","term_id":"NCT02952729"}} NCT02952729 ) [ 250 ]. MEDI4276, which targets two different HER2 epitopes and is linked to a microtubule inhibitor, showed promising clinical activity in a phase I study (ClinicalTrials.gov identifier: {"type":"clinical-trial","attrs":{"text":"NCT02576548","term_id":"NCT02576548"}} NCT02576548 ) [ 254 ] (see the summarized table at the end of the manuscript).

Chimeric Antibody

Margetuxumab (MGAH22) is a human/mouse chimeric IgG1 targeting HER2 monoclonal antibody. It is based on trastuzumab as it binds to the same epitope (subdomain IV or HER2 extracellular domain) but with an enhanced Fcγ domain. The substitution of five amino acids into the IgG1 Fc domain increases CD16A affinity, a receptor found on macrophages and natural-killer cells, and decreases CD32B affinity, leading to increased antibody-dependent cell-mediated cytotoxicity (ADCC) [ 285 ]. A phase I study evaluated margetuximab toxicity and tumor activity on HER2+ BC patients for whom no standard treatment was available [ 266 ]. This study showed promising single-agent activity of margetuximab as well as good tolerability. The phase III randomized open-labeled SOPHIA clinical trial (ClinicalTrials.gov Identifier: {"type":"clinical-trial","attrs":{"text":"NCT02492711","term_id":"NCT02492711"}} NCT02492711 ) compared margetuximab plus chemotherapy vs. trastuzumab plus chemotherapy in pretreated HER2+ advanced BC patients [ 286 ]. The combination of margetuximab and chemotherapy significantly improved the PFS of patients compared to trastuzumab plus chemotherapy. This study is still under investigation to collect data on OS (see the summarized table at the end of the manuscript).

Bispecific Antibodies

Bispecific antibodies (BsAbs) can target two different epitopes in the same or different receptors by combining the functionality of two monoclonal antibodies [ 287 ]. MCLA-128 targets both HER2 and HER3 and have an enhanced ADCC activity [ 288 ]. A phase I/II study evaluated the safety, tolerability, and antitumor activity of MCLA-128 in patients with pretreated HER2+ metastatic BC.

Preliminary results showed encouraging clinical benefits of MCLA-128. An open-labeled, multicentered phase II study (ClinicalTrials.gov identifier: {"type":"clinical-trial","attrs":{"text":"NCT03321981","term_id":"NCT03321981"}} NCT03321981 ) is ongoing to evaluate the effects of MCLA-128 in combination with trastuzumab and chemotherapy in HER2+ metastatic BC patients.

ZW25 is a BsAb biparatopic that binds the IV and II subdomains of the HER2 extracellular domain, the binding epitopes of trastuzumab and pertuzumab, respectively [ 289 ]. The efficacy of ZW25 was evaluated in a phase I study given alone or in combination with chemotherapy in patients with advanced or metastatic HER2+ BC. The results of this study showed promising antitumor activity, and no-dose limiting was observed.

T-cell bispecific antibodies (TCBs) are another type of BsAbs recently developed. TCBs target the CD3-chain of the T-cell receptor and tumor-specific antigens, resulting in lymphocyte activation and tumor cell death [ 290 ].

GBR1302 targets both HER2 and CD3 receptors and directs T-cells to HER2+ tumor cells. A phase II study (ClinicalTrials.gov identifier: {"type":"clinical-trial","attrs":{"text":"NCT03983395","term_id":"NCT03983395"}} NCT03983395 ) is ongoing to determine the safety profile of the GBR1302 single agent in previously treated HER2+ metastatic BC. PRS-343 targets HER2 and the immune receptor CD137, a member of the tumor necrosis factor receptor family. Two clinical trials are investigating the effects of PRS-343 monotherapy (ClinicalTrials.gov identifier: {"type":"clinical-trial","attrs":{"text":"NCT03330561","term_id":"NCT03330561"}} NCT03330561 ) or in combination with other treatments (ClinicalTrials.gov identifier: {"type":"clinical-trial","attrs":{"text":"NCT03650348","term_id":"NCT03650348"}} NCT03650348 ) (see the summarized table at the end of the manuscript).

4.2.2. HER2-Derived Peptide Vaccines

One of the strategies of immunotherapy is activating the patient’s immune system to kill cancer cells. Vaccination is an emerging approach to induce a tumor-specific immune response by targeting tumor-associated antigens, such as HER2 [ 291 ]. HER2-derived peptide vaccines comprise different parts of the HER2 molecule, such as E75 (extracellular domain), GP2 (transmembrane domain), and AE37 (intracellular domain) [ 292 ].

E75 (HER2/neu 369–377: KIFGSLAFL) has high affinity for HLA2 and HLA3 (human leucocyte antigen) that can stimulate T-cells against HER2 overexpressing tumor cells [ 293 ]. The efficacy of the E75 vaccine to prevent BC recurrence has been evaluated in a phase I/II study, in which high-risk HER2+ HLA2/3+ BC patients received the E75 vaccine [ 269 ]. The results demonstrated the safety and clinical efficacy of the vaccine as PFS was improved in the E75-vaccinated group compared to the unvaccinated group. Other clinical trials are currently investigating the efficacy of the E75 vaccine on HER2+ BC (see he summarized table at the end of the manuscript).

GP2 (654-662: IISAVVGIL) is a subdominant epitope with poor affinity for HLA2 [ 294 ]. A phase I trial evaluating the effects of a GP2 vaccine in disease-free BC patients showed that it was safe and tolerable with HER2-specific immune response [ 295 ]. The GP2 vaccine has been tested in a randomized, open-labeled phase II study to prevent BC recurrence. The patients that received the GP2 vaccine had HER2+ and HLA2+ BC and were disease-free with a high risk of recurrence at the time of the study [ 270 ]. The results demonstrated that the GP2 vaccine was safe and clinically beneficial for patients with HER2+ BC who received the full vaccine series.

AE37 (Ii-key hybrid of MHC II peptide AE36 (HER2/neu 776–790)) can stimulate CD8+ and CD4+ cells. A randomized, single-blinded phase II study evaluated the effects of an AE37 vaccine to prevent BC recurrence. Patients with a high risk of recurrence and HER2+ BC received the AE37 vaccine [ 271 ]. The vaccination demonstrated no benefit in the overall intention-to-treat analysis, a method that considers the randomized treatment to avoid bias happening after the randomization [ 296 ]. However, the study showed that the AE37 vaccine was safe, and results suggested that it could be effective for HER2-low BC, such as TNBC.

4.2.3. New Tyrosine Kinase Inhibitors (TKIs)

As previously described in this review (see Section 3.2.2 Tyrosine kinase inhibitors (TKIs)), TKIs are small molecules targeting the HER2 intracellular catalytic domain [ 159 ]. New TKIs have been developed with better efficacy and less toxicity in the treatment of HER2+ metastatic BC, such as tucatinib and poziotinib.

Tucatinib is a TKI with high selectivity for HER2, leading to less EGFR-related toxicities, common with other HER TKIs [ 297 ]. A phase I dose-escalation trial evaluated the combination of tucatinib and trastuzumab in BC patients with progressive HER2+ brain metastases [ 298 ]. This study showed preliminary evidence of tucatinib efficacy and tolerability in these patients. Tucatinib was also tested in combination with TDM-1 in a phase Ib trial in HER2+ metastatic BC patients with heavy pre-treatment [ 299 ]. The combination of tucatinib and TDM-1 showed acceptable toxicity and antitumor activity in these patients. Tucatinib was FDA approved in combination with trastuzumab and capecitabine for patients with advanced or metastatic HER2+ BC who received prior anti-HER2 in the metastatic setting [ 300 ]. This was based on the results of the phase II HER2CLIMB clinical trial, where HER2+ metastatic BC patients received tucatinib or placebo in combination with trastuzumab and capecitabine [ 267 ]. The addition of tucatinib to trastuzumab and capecitabine improved PFS and OS of heavily pretreated HER2+ metastatic BC patients.

Poziotinib is a pan-HER kinase inhibitor that irreversibly inhibits the HER family members’ kinase activity [ 301 ]. A phase I study evaluated the efficacy and tolerability of poziotinib in advanced solid tumors. The results showed encouraging antitumor activity against different types of HER2+ cancers as poziotinib was safe and well-tolerated by the patients [ 302 ]. The phase II NOV120101-203 study evaluated the safety and efficacy of poziotinib monotherapy in heavily pretreated HER2+ metastatic BC patients [ 268 ]. Poziotinib showed meaningful activity in these patients with no severe toxicities.

4.2.4. mTOR/PI3K Inhibitors and CDK4/6 Inhibitors

As mentioned in the previous Section 4.1 , mTOR/PI3K inhibitors and CDK4/6 inhibitors have been evaluated as potential new strategic therapies for HR+ BC resistant to endocrine therapy. The mTOR/PI3K signaling pathway and CDK4/6 also play a role in the mechanisms leading to treatment resistance in HER2+ BC [ 303 ]. Thus, targeting them with mTOR/PI3K and CDK4/6 inhibitors is also being investigated in HER2+ BC subtype.

mTOR/PI3K Inhibitors

Alpelisib and taselisib are PI3K isoform-specific inhibitors that were also evaluated in HR+ BC [ 235 , 236 , 238 , 253 , 254 ]. A phase I study evaluated alpelisib in combination with trastuzumab and LJM716 (a HER3-targeted antibody) in patients with PI3KCA mutant HER2+ metastatic BC [ 272 ]. Unfortunately, the results of this study were limited by high gastrointestinal toxicity. Another phase I study tested alpelisib in combination with TDM-1 in HER2+ metastatic BC patients pretreated with trastuzumab [ 273 ]. The combination of alpelisib and TDM-1 demonstrated tolerability and antitumor activity in trastuzumab-resistant HER2+ metastatic BC patients. Taselisib is being tested in an ongoing phase Ib dose-escalation trial in combination with anti-HER2 therapies (trastuzumab, pertuzumab and TDM-1) in HER2+ advanced BC patients (ClinicalTrials.gov identifier: {"type":"clinical-trial","attrs":{"text":"NCT02390427","term_id":"NCT02390427"}} NCT02390427 ).

Copanlisib is a highly selective and potent pan-class I PI3K inhibitor [ 304 ]. A phase Ib (PantHER) study evaluated the tolerability and activity of copanlisib in combination with trastuzumab in heavily pretreated HER2+ metastatic BC patients [ 274 ]. The combination of copanlisib and trastuzumab was safe and tolerable. Preliminary evidence of tumor stability was observed in these patients.

Everolimus is a mTORC1 inhibitor also tested in HR+ BC [ 240 , 241 , 242 ]. Everolimus was tested in phase III clinical trials, in combination with trastuzumab and docetaxel (BOLERO-1), or in combination with trastuzumab and vinorelbine (BOLERO-3) in trastuzumab-resistant advanced HER2+ BC [ 275 , 276 ]. Unfortunately, results showed an increase of adverse effects with everolimus. Moreover, the BOLERO-1 clinical trial showed no improvement in PFS with the combination of trastuzumab and everolimus. By contrast, PFS was significantly longer when everolimus was added to vinorelbine in BOLERO-3. A study analyzing the molecular alterations found in patients in the BOLERO-1 and BOLERO-3 clinical trials demonstrated that HER2+ BC patients could derive more benefit from everolimus if the tumors had PI3KCA mutations, PTEN loss or a hyperactive PI3K pathway [ 305 ].

CDK4/6 Inhibitors

Palbociclib, ribociclib and abemaciclib are CDK4/6 inhibitors that have been FDA approved to treat HR+ BC as first-line treatments [ 247 , 250 , 259 ]. They have also been evaluated in multiple clinical trials for advanced HER2+ BC. Palbociclib has been tested in combination with trastuzumab in the phase II SOLTI-1303 PATRICIA clinical trial in heavily pretreated advanced HER2+ BC patients [ 277 ]. Palbociclib combined with trastuzumab demonstrated safety and encouraging survival outcomes in these patients. Palbociclib has also been evaluated in combination with TDM-1 in HER2+ advanced BC patients pretreated with trastuzumab and taxane therapy [ 306 ]. The results of this phase I/Ib study showed safety, tolerability, and antitumor activity in these patients.

Ribociclib was evaluated in a phase Ib/II trial in combination with trastuzumab to treat advanced HER2+ BC patients previously treated with multiple anti-HER2 therapies [ 278 ]. The combination of ribociclib and trastuzumab was safe, but there was limited activity in heavily pretreated patients. The conclusions of this study suggest that CDK4/6 inhibitor/anti-HER2 combination should be administered in patients with few previous therapies.

Abemaciclib has been tested in the phase II randomized open-labeled MonarcHER trial in combination with trastuzumab with or without fulvestrant vs. trastuzumab with standard chemotherapy in HR+/HER2+ BC patients [ 279 ]. The combination of abemaciclib, trastuzumab, and fulvestrant significantly improved PFS in these patients, with a tolerable safety profile.

There are multiple ongoing clinical trials for advanced HER2+ BC testing the combination of palbociclib, trastuzumab, pertuzumab, and anastrozole (ClinicalTrials.gov identifier: {"type":"clinical-trial","attrs":{"text":"NCT03304080","term_id":"NCT03304080"}} NCT03304080 ); or palbociclib and trastuzumab plus letrozole (ClinicalTrials.gov identifier: {"type":"clinical-trial","attrs":{"text":"NCT03054363","term_id":"NCT03054363"}} NCT03054363 ). Preliminary results are expected around July 2021 and March 2022, respectively (see he summarized table at the end of the manuscript).

A great proportion of HER2+ BC patients develop resistance to traditional anti-HER2 therapies, and 40–50% of patients with advanced HER2+ BC develop brain metastases [ 307 ]. Thus, developing new therapies to overcome resistance is essential. The therapeutic strategies that have been described in this section provide new hope for HER2+ BC patients, especially for advanced or metastatic HER2+ BC patients.

4.3. Emerging Therapies for Triple Negative Breast Cancer (TNBC)

TNBC is the most aggressive BC subtype. The fact that TNBC lacks ER and PR expression and does not overexpress HER2, combined with its high heterogeneity, has contributed to the difficulties in developing efficient therapies [ 308 ]. Thus, multiple strategic therapies have been developed to treat all TNBC subtypes. These include conjugated antibodies, targeted therapy, and immunotherapy. An overview of the most recent and completed clinical trials on emerging therapies for TNBC is presented in Table 3 .

Most recent completed clinical trials on emerging therapies for TNBC.

TNBC: triple negative breast cancer; HER2: human epidermal growth factor receptor; HR: hormonal receptor; MBC: metastatic breast cancer; BC: breast cancer; AR: androgen receptor; PPV: personalized peptide vaccine; PFS: progression free survival; CBR: clinical benefit rate; ORR: objective response rate; IDFS: invasive disease-free survival; OS: overall survival; TTP: time to progression; pCR: pathologic complete response; HR: hazard ratio.

4.3.1. Antibodies-Drug Conjugates (ADC)

Antibody drug conjugates (ADCs) deliver a cytotoxic drug into the tumor cell by the specific binding of an antibody to a surface molecule [ 280 ]. Multiple ADCs have been investigated in TNBC such as sacituzumab govitecan, ladiratuzumab vedotin, or trastuzumab deruxtecan.

Sacituzumab govitecan combines an antibody targeting trophoblast antigen 2 (Trop-2) and a topoisomerase I inhibitor SN-38 [ 334 ]. Trop-2, a CA 2+ signal transducer, is expressed in 90% of TNBCs and is associated with poor prognosis [ 335 , 336 ]. A single-arm, multicentered phase I/II study evaluated sacituzumab govitecan in heavily pretreated metastatic TNBC patients [ 336 , 337 ]. The efficacy and safety of scituzumab govitecan was shown in these patients, as it was associated with durable objective response. Based on these results, a randomized phase III trial (ASCENT) tested sacituzumab govitecan compared to single-agent chemotherapy chosen by the physician in patients with relapsed or refractory metastatic TNBC [ 309 ]. Sacituzumab govitecan significantly improved PFS and OS of metastatic TNBC patients compared to chemotherapy.

Ladiratuzumab vedotin is composed of a monoclonal antibody targeting the zinc transporter LIV-1 and a potent microtubule disrupting agent, monoethyl auristatin E (MMAE) [ 338 ]. LIV-1 is a transmembrane protein with potent zinc transporter and metalloproteinase activity, expressed in more than 70% of metastatic TNBC tumors [ 339 ]. All clinical trials investigating ladiratuzumab vedotin are still ongoing. A dose-escalation phase I study is evaluating the safety and efficacy of ladiratuzumab vedotin in heavily pretreated metastatic TNBC patients (ClinicalTrials.gov identifier: {"type":"clinical-trial","attrs":{"text":"NCT01969643","term_id":"NCT01969643"}} NCT01969643 ). Preliminary results showed encouraging antitumor activity and tolerability of ladiratuzumab vedotin with an objective response rate of 32% [ 340 ]. The estimated study completion date is June 2023. Two phase Ib/II trials are testing ladiratuzumab vedotin in combination with immunotherapy agents in metastatic TNBC patients, such as pembrolizumab (ClinicalTrials.gov Identifier: {"type":"clinical-trial","attrs":{"text":"NCT03310957","term_id":"NCT03310957"}} NCT03310957 ) with expected preliminary results in February 2022, or in combination with multiple immunotherapy-based treatments (ClinicalTrials.gov Identifier: {"type":"clinical-trial","attrs":{"text":"NCT03424005","term_id":"NCT03424005"}} NCT03424005 ) with expected preliminary results in January 2023.

Trastuzumab deruxtecan is an ADC developed as a treatment for metastatic HER2+ BC patients. Its mechanism of action is described in Section 3.2 . Even though trastuzumab deruxtecan was developed to treat HER2+ BC, it showed antitumor activity in HER2-low tumors in a phase I study [ 282 ]. Based on these results, an ongoing open-labeled, multicentered phase III study (ClinicalTrials.gov Identifier: {"type":"clinical-trial","attrs":{"text":"NCT03734029","term_id":"NCT03734029"}} NCT03734029 ) is recruiting patients with HER2-low metastatic BC to test trastuzumab deruxtecan vs. standard treatment chosen by the physician. Preliminary results are expected in January 2023 (see Table 4 ).

Ongoing clinical trials on emerging therapies for BC treatment for all BC molecular subtypes.

TNBC: triple negative breast cancer; HER2: human epidermal growth factor receptor 2; ER: estrogen receptor; MBC: metastatic breast cancer; BC: breast cancer; HR: hormonal receptor; PFS: progression free survival; CBR: clinical benefit rate; ORR: objective response rate; DFS: disease-free survival; OS: overall survival; TTP: time to progression. pCR: pathologic complete response; GM-CSF: granulocyte macrophage colony-stimulated factor; DLT: dose-limiting toxicities; MTD: maximum tolerated dose; TTF: time to treatment failure; TTR: time to treatment response; iDFS: invasive disease-free survival; RFS: recurrence free survival; DDFS: distant disease-free survival; iEFS: invasive events-free survival; CR: clinical response; DoCB: duration of clinical benefit; SD: stable disease; DoR: duration of response; IAEs: incidence of adverse events; TDR: treatment discontinuation rate; PR: partial response; DCR: disease control rate; HR: hazard ratio.

4.3.2. Targeted Therapies

Targeted therapy is the current standard of care to treat HR+ and HER2+ BC, but it cannot be administered to patients with TNBC as these tumors lack the expression of these biomarkers. Hence, the next logical step is to identify biomarkers associated with TNBC to develop specific targeted therapies. Several emerging targeted therapies are being clinically trialed with limited or mixed results.

VEGF and EGFR Inhibitors

Vascular endothelial growth factor (VEGF) and epidermal growth factor receptor (EGFR) are overexpressed in most TNBC patients [ 341 , 342 ]. Bevacizumab and cetuximab are antibodies developed to specifically target VEGF and EGFR, respectively. Unfortunately, clinical trials studying the effects of these antibodies in TNBC patients demonstrated limited results. The phase III, randomized BEATRICE study evaluating adjuvant bevacizumab-continuing therapy in TNBC demonstrated no significant benefit in OS [ 310 ]. A phase II trial evaluating the impact of adding bevacizumab or cisplatin to neoadjuvant chemotherapy to stage II to III TNBC concluded that further investigation of bevacizumab in this setting was unlikely [ 311 ].

The phase II randomized TBCRC 001 trial testing the combination of cetuximab and carboplatin in stage IV TNBC showed a response in fewer than 20% of patients [ 312 ]. Another randomized phase II study compared the effects of cetuximab plus cisplatin to cisplatin alone in metastatic TNBC patients. Adding cetuximab to cisplatin prolonged PFS and OS, warranting further investigation of cetuximab in TNBC [ 313 ]. Based on these results, bevacizumab is not recommended for the treatment of TNBC.

mTOR/PI3K/AKT Inhibitors

mTOR/PI3K/Akt signaling pathway is an important target involving all BC subtypes. Inhibitors of mTOR, PI3K, and Akt have been tested in HR+ and HER2+ BC patients and have also been tested in TNBC patients. The mTOR inhibitor everolimus has been tested in a randomized phase II trial in combination with chemotherapy vs. chemotherapy alone in stage II/III TNBC patients [ 314 ]. Unfortunately, the addition of everolimus was associated with more adverse effects, without improving pCR or clinical response. A phase I study testing the combination of everolimus and eribulin in metastatic TNBC patients showed that this combination was safe, but the efficacy was modest [ 343 ].

The Akt inhibitor ipatasertib has been tested in combination with paclitaxel (vs. placebo) for metastatic TNBC patients in the phase II multicentered double-blinded randomized LOTUS trial [ 315 ]. The results showed improved PFS when patients received ipatasertib. Another phase II double-blinded randomized trial, FAIRLANE, testing neoadjuvant ipatasertib plus paclitaxel for early TNBC, showed no clinically or statistically significant improvement in the pCR rate, but ipatasertib’s antitumor effect was more pronounced in patients with PI3K/AKT1/PTEN-altered tumors [ 316 ]. Capivasertib, another Akt inhibitor, has been tested in combination with paclitaxel (vs. placebo), first-line therapy for metastatic TNBC patients in the phase II double-blinded randomized PAKT trial [ 317 ]. The addition of capivasertib to paclitaxel significantly improved PFS and OS, with better benefits for patients with PI3K/AKT1/PTEN-altered tumors.

Androgen Receptor Inhibitors

The androgen receptor (AR) is a steroidal hormonal receptor that belongs to the nuclear receptor family and is expressed in 10% to 50% of TNBC tumors [ 344 ]. Tumors expressing AR have better prognosis but are less responsive to chemotherapy [ 345 ]. Multiple clinical trials have tested AR inhibitors in TNBC [ 318 , 319 , 320 ].

Bicalutamide, an AR agonist, was tested in a phase II study in patients with AR+, HR- metastatic BC [ 318 ]. The results showed promising efficacy and safety for these patients.

Enzalutamide, a nonsteroidal antiandrogen, has been tested in a phase II study in patients with locally advanced or metastatic AR+ TNBC [ 319 ]. Enzalutamide demonstrated significant clinical activity and tolerability, warranting further investigation.

Abiraterone, a selective inhibitor of CYP17, has been evaluated in combination with prednisone in AR+ locally advanced or metastatic TNBC patients [ 320 ]. This combination was beneficial for 20% of the patients.

Several clinical trials are currently testing AR inhibitors alone or combined with other treatments for TNBC patients; expecting results between 2022 and 2027 (see Table 4 ).

4.3.3. Immunotherapy

Targeted antibodies.

The immune system plays a crucial role in BC development and progression. Tumor cells can escape the immune system by regulating T-cell activity leading to the inhibition of immune response [ 346 , 347 ]. Two principal biomarkers found in TNBC are associated with this bypass: the programmed cell death protein receptor (PD-1) and its ligand PDL-1, and the cytotoxic T lymphocyte-associated protein 4 (CTLA-4) [ 348 ].

PD-1 is an immune checkpoint receptor expressed on the surface of activated T-cells. PDL-1, its ligand, is expressed on the surface of dendritic cells or macrophages. The interaction of PD-1 and PDL-1 inhibits T-cell response [ 349 ]. CTLA-4 is expressed on T-cells and inhibits T-cell activation by binding to CD80/CD86, leading to decreased immune response [ 350 ].

Atezolizumab, an anti-PDL-1 antibody, has demonstrated safety and efficacy in a phase I study for metastatic TNBC patients [ 351 ]. Based on these results, atezolizumab was tested in combination with nab-paclitaxel for unresectable locally advanced or metastatic TNBC in the phase III double-blinded placebo-controlled randomized Impassion130 study [ 321 ]. Atezolizumab plus nab-paclitaxel prolonged PFS and OS in both the intention-to-treat population and PDL1+ subgroup. Another double-blinded, randomized phase III study (Impassion031) compared atezolizumab in combination with nab-paclitaxel and anthracycline-based chemotherapy vs. placebo for early-stage TNBC [ 322 ]. This combination significantly improved pCR with an acceptable safety profile.

Durvalumab, another anti-PDL-1 antibody, has been tested in combination with an anthracycline taxane-based neoadjuvant therapy for early TNBC in the randomized phase II GeparNuevo study [ 323 ]. This combination increased pCR rate, particularly in patients pretreated with durvalumab monotherapy before chemotherapy. Another randomized phase II study, SAFIRO BREAST-IMMUNO, compared durvalumab to maintenance chemotherapy in a cohort including TNBC patients [ 324 ]. Results showed that durvalumab, as a single agent therapy, could improve outcomes in TNBC patients. A phase I study tested durvalumab in combination with multiple TNBC therapies: PARP inhibitor olaparib and VEGFR1-3 inhibitor cediranib for patients with recurrent cancers including TNBC [ 325 ]. This combination was well tolerated and showed preliminary antitumor activity in all of these patients.

The safety and efficacy of avelumab, another anti-PDL-1 antibody, was evaluated in the phase Ib JAVELIN study in patients with locally advanced or metastatic BC, including TNBC [ 326 ]. Avelumab showed an acceptable safety profile and clinical activity, particularly in tumors expressing PDL-1.

Pembrolizumab is an anti-PD-1 antibody that has been tested in multiple clinical trials. The phase Ib KEYNOTE-012 study demonstrated the safety and efficacy of pembrolizumab on advanced TNBC patients [ 352 ]. Based on these results, the phase II KEYNOTE-086 study evaluated pembrolizumab monotherapy for pretreated or non-pretreated metastatic TNBC patients [ 327 , 353 ]. Pembrolizumab monotherapy showed a manageable safety profile and durable antitumor activity for both pretreated and non-pretreated subgroups. The randomized open-labeled phase III KEYNOTE-119 trial compared pembrolizumab monotherapy to standard chemotherapy in metastatic TNBC [ 354 ]. Pembrolizumab monotherapy did not significantly improve OS compared to chemotherapy in these patients. These findings suggest that pembrolizumab should be investigated in a combinational approach rather than in monotherapy. Based on these results, pembrolizumab was tested in combination with chemotherapy (vs. placebo) for pretreated locally recurrent or metastatic TNBC patients in the phase III double-blinded randomized KEYNOTE-355 trial [ 328 ]. The combination of pembrolizumab plus chemotherapy significantly and clinically improved PFS compared to chemotherapy plus placebo. Pembrolizumab has also been evaluated for early TNBC as neoadjuvant therapy in combination with chemotherapy (vs. placebo) in the phase III KEYNOTE-522 trial [ 329 ]. The combination of pembrolizumab plus chemotherapy significantly improved pCR rate in these patients compared to placebo plus chemotherapy.

Tremelimumab is an anti-CTLA-4 antibody. A dose-escalation phase I study evaluating the safety and efficacy of tremelimumab in patients with metastatic BC showed good tolerability [ 330 ].

Vaccination is an emerging approach to prevent recurrence in high-risk BC patients. As mentioned earlier, TNBC is the most aggressive BC subtype with a higher risk of distant recurrence [ 331 ]. Thus, developing vaccines to prevent recurrence in TNBC patients is of great interest.

Takahashi et al. have developed a novel regimen of personalized peptide vaccination (PPV) based on the patient’s immune system to select vaccine antigens from a pool of peptide candidates [ 332 ]. They performed a phase II study where metastatic recurrent BC patients with prior chemotherapy and/or hormonal therapies received a series of personalized vaccines. This vaccination demonstrated safety, possible clinical benefit, and immune response, especially for TNBC patients [ 332 ]. A multicentered, randomized, double-blinded phase III study analyzed the effects of sialyl-TN keyhole limpet hemocyanin (STn-KLH) on metastatic BC patients [ 333 ]. STn-KLH consists of a synthetic STn, an epitope expressed in BC and associated with aggressive and metastatic tumors, and a high molecular weight protein carrier KLH [ 355 ]. Stn-KLH demonstrated good tolerability, but no benefits in time to progression (TTP) or survival were found. Thus, this vaccination is not recommended for metastatic BC patients [ 333 ].

PVX-410 is a multiple peptide vaccine that activates T-cell to target tumor cells and was developed to treat myeloma. A phase Ib/II study demonstrated the safety and immunogenicity in myeloma patients [ 356 ]. Based on these results, a PVX-410 vaccine is currently being tested to treat TNBC in multiple clinical trials (see Table 4 ).

Finding new treatments for TNBC is an ongoing challenge. The therapeutic strategies that have been described in this section offer great hope to treat TNBC patients. However, because TNBC is highly heterogeneous, it is difficult to find a single treatment efficient for all TNBC subtypes [ 228 ].

5. Conclusions

This review clearly demonstrates that the treatment of BC is complex and is constantly evolving with a large number of ongoing clinical trials on emerging therapies. Indeed, the BC molecular subtype will determine the personalized therapeutic approach, such as targeted treatments like endocrine therapy for HR+ BC or anti-HER2 therapy for HER2+ BC. These therapies have demonstrated their safety and efficacy in treating BC over the years. However, it is essential to go beyond these conventional treatments as BC is a complex disease and not all patients can benefit from personalized treatment. One of the major challenges in BC treatment is finding effective therapies to treat TNBC patients since conventional targeted therapies cannot be administered for this specific BC subtype, which has the worst survival outcomes.

Another important issue in BC treatment is the acquisition of treatment resistance. This is a common phenomenon for either endocrine therapy, anti-HER2 therapy, and chemotherapy.

Hence, understanding the mechanisms underlying drug resistance is a good strategy to develop novel treatments for BC. For example, the mTOR/PI3K/Akt pathway is involved in the mechanism of resistance in all BC molecular subtypes, and thus developing specific inhibitors targeting this pathway is a promising BC treatment approach.

Acknowledgments

The authors would also like to thank team members from the C.D. and F.D. research groups for their valuable assistance.

Abbreviation

Author contributions.

A.B. conceptualized and drafted the manuscript. F.D. and C.D. supervised the project. All authors did critical revision of the manuscript. All authors have read and agreed to the published version of the manuscript.

This work was supported by the “Fond de recherche du Québec–Santé (FRQS)” associated with the Canadian Tumor Repository Network (CTRNet). Caroline Diorio is a senior Research Scholar from the FRSQ. Anna Burguin holds a Bourse d’excellence en recherche sur le cancer du sein—Faculté de médecine-Université Laval.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Data availability statement, conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Advances in Breast Cancer

Screening and Treatment Get Personal

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Breast cancer is the second most common cancer among American women. Breast cancer death rates have been falling over the past 30 years. But nearly 13% of women are still diagnosed in their lifetime. Men can get breast cancer too, although it’s rare.

Cancer is caused by changes to genes Stretches of DNA you inherit from your parents that defines features, like your risk for certain diseases. that control the way our cells function. These changes affect how cells grow and divide. Cancer results when cells divide uncontrollably. In breast cancer, this happens in the breast tissue.

Researchers are studying the risk factors for different types of breast cancer. They’re also searching for more personalized treatments.

Unraveling The Risks

“Breast cancer is caused by a combination of factors,” says Dr. Montserrat García-Closas, a cancer researcher at NIH. Your genes, lifestyle, and environment all contribute to your risk. Researchers are trying to better understand how each plays a role.

People with a family history of breast cancer are at increased risk for the disease. Some are born with rare versions of certain genes that put them at high risk. These include the genes BRCA1 and BRCA2 .

“But the vast majority of patients have no known family history and no known gene that causes cancer,” explains Dr. Margaret Gatti-Mays, a breast cancer treatment specialist at The Ohio State University.

So researchers are also searching for combinations of genes that may lead to breast cancer. “Women can inherit hundreds or thousands of common versions of genes that each have tiny effects, but in combination can put them at substantial risk for developing breast cancer,” García-Closas says. An NIH study called the Confluence Project is trying to unravel these combinations.

Other factors can increase your risk for breast cancer, too. These include your age, whether you’ve had children, alcohol use, and obesity.

Studies are examining how all these factors—genes, medical history, and lifestyle—interact to affect cancer risk. One is called Connect for Cancer Prevention. “It’s recruiting 200,000 people in the U.S. and following them for years to see who develops different types of cancers,” says García-Closas.

Staying Ahead of Breast Cancer

Another study, called the Wisdom Study, is exploring how to best personalize breast cancer screening. Screening tests look for signs of a disease before symptoms appear. Finding cancer early may increase the chance that it can be treated and cured.

If you’re at high risk for breast cancer, your doctor may advise you to get screenings at an earlier age than most, or more often.

“Women from 40 to 50 should talk with their doctor about when they should start screening. And that should be based on their personal risks,” says Dr. Brandy Heckman-Stoddard, an NIH expert on breast cancer.

Mammograms are the most common way to screen for breast cancer. These are X-ray pictures of the breast. An NIH study called TMIST is comparing whether 2D or 3D mammograms are better for screening. 2D mammograms are taken from two sides of the breast. 3D mammograms are taken from different angles around the breast. Then, a computer builds a 3D-like image.

Magnetic resonance imaging (MRI) is sometimes used to screen women at high risk of breast cancer. MRIs can create a clearer image of the breast and don’t use radiation.

Researchers are looking for other ways to detect breast cancer, too. García-Closas’ team is trying to detect cancer using blood samples. These “liquid biopsies” detect DNA from cancer cells, which travel around the body in the bloodstream.

“Liquid biopsies should reflect what’s going on in your whole body,” García-Closas says, “versus when you look at a tissue biopsy, you’re taking a tiny sample of tissue in a particular location.”

Liquid biopsies may one day be able to detect cancer before other clinical tests, she says. “And, they might be able to better monitor what’s happening in your body after cancer has been diagnosed.”

Fighting Back

When breast cancer is found, treatment depends on the type of tumor. Surgery and radiation are common. Chemotherapy may also be used. Doctors might recommend other treatments as well, depending on the type of breast cancer.

“There are three main types of breast cancer,” Gatti-Mays says. “The subtype is determined by the presence or absence of three receptors Molecules that receive and respond to signals, such as hormones. .” These receptors respond to the hormones Substances made in the body’s glands that signal another part of the body to react a certain way. estrogen or progesterone or a protein called HER2.

“If your tumor has estrogen and progesterone receptors, then you can be treated with hormone therapies,” says Heckman-Stoddard. These block the action of hormones that can cause certain cancers to grow.

Hormone treatments can also be used to prevent or lower the risk of cancer for certain women. One such drug is called tamoxifen. But it has side effects that make it unappealing for prevention. Heckman-Stoddard’s team is studying whether using the drug as a gel lessens the side effects.

There are newer treatment options called targeted treatments. These block specific proteins that control how cancer cells grow, divide, and spread. Targeted treatments for HER2-positive cancer have improved survival over the last decade.

The most recent type of cancer treatment is called immunotherapy. It trains your body to fight cancer using your own immune system The system that protects your body from invading viruses, bacteria, and other microscopic threats. .

“Immunotherapy is very promising, but the benefits are still limited to only some patients with triple negative breast cancer,” says Gatti-Mays. These cancers lack all three receptors. But researchers are trying to expand this treatment to more patients with breast cancer. They’re also testing whether using it in combination with other treatments will work better.

Scientists continue to look for ways to improve screening, prevention, and treatment. “In the next five to 10 years, there should be better ways for women to determine their risk of breast cancer,” says García-Closas. “That should help them have a conversation with their physicians on what will be the best tailored prevention strategies.”

No matter what your personal risk of cancer, a healthy lifestyle is the best way to prevent it. Eat a heart-healthy diet, reduce alcohol intake, don’t smoke, and get regular exercise. See the Wise Choices box and talk with your health care provider about ways to lower your risk.

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Targeted immunotherapy could lead to pioneering treatment for breast cancer

by Institute of Cancer Research

Targeted immunotherapy could lead to pioneering treatment for breast cancer

A new type of immunotherapy that targets non-cancer cells could help prevent the growth and spread of breast cancer tumors, according to new research.

The discovery, published 28 February in the Journal for ImmunoTherapy of Cancer , has found that an immunotherapy approach targeting a protein called endosialin disrupts the tumor's blood supply and, as a result, can hinder its growth and spread.

A new approach to attack cancer

Unlike most cancer treatments, this innovative treatment doesn't target cancer cells directly but attacks the cells that support the disease instead.

Immunotherapy is a type of cancer treatment that works by helping the body's own immune system to recognize and kill cancer cells.

Researchers at The Institute of Cancer Research, London, used a type of immunotherapy called CAR-T therapy, which involves removing a patient's healthy immune cells and genetically modifying them to attack specific targets.

Cutting off the blood supply to tumors

CAR-T therapies are already being used to treat some blood cancers, and scientists are trying to find ways to make them effective for other types of cancer, including breast cancer . However, CAR-T cell therapy doesn't always work on tumors because their environment suppresses the immune response , and it can also be challenging to find specific features on the breast cancer cells to target.

To work around these challenges, the team directed the CAR-T cells to cells surrounding the tumor's blood supply that make the endosialin protein, rather than actual cancer cells. In experiments in mice, targeting endosialin successfully reduced the breast cancer's growth and spread.

The team, based at the Breast Cancer Now Toby Robins Research Center at The Institute of Cancer Research (ICR), also tested the treatment on lung cancer tumors in mice and saw similarly successful results, suggesting patients with other types of cancer could benefit from this new treatment too.

In addition, researchers found that the CAR-T therapy didn't affect cells without endosialin, indicating this could work as a cancer-specific treatment with potentially fewer side effects for patients.

The researchers are now developing this treatment further so that it can be tested in clinical trials.

Improving the success of immunotherapy

Dr. Frances Turrell, study co-leader and postdoctoral training fellow in the Division of Breast Cancer Research at The Institute of Cancer Research, London, said, "This is the very first study that demonstrates the effectiveness of using endosialin-directed CAR-T cells to reduce breast cancer tumor growth and spread.

"Immunotherapy has had limited success in treating breast cancer but by targeting the cells that support the tumor and help it to survive, rather than the cancer cells directly, we've found a promising way to overcome the challenges posed by the tumor environment and develop a more effective and targeted treatment for breast cancer.

"We could not have done this project without funding to the Molecular Cell Biology group from Breast Cancer Now and we hope that further research will help translate these findings into targeted therapies for breast cancer patients."

Dr. Simon Vincent, director of research, support and influencing at Breast Cancer Now, said, "This exciting research could lead to much-needed targeted treatments for people with breast cancer, and with one person dying from breast cancer every 45 minutes in the U.K., new treatments like these are urgently needed.

"Now we know that the treatment works in principle in mice, Breast Cancer Now researchers can continue to develop this immunotherapy to make it suitable for people, as well as to understand the full effect it could have and who it may benefit the most."

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Book cover

  • © 2023

Breast Cancer Research and Treatment

Innovative Concepts

  • Ouissam Al Jarroudi 0 ,
  • Khalid El Bairi 1 ,
  • Giuseppe Curigliano 2

Department of Medical Oncology, Mohammed VI University Hospital, Oujda, Morocco

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Division of New Drugs and Early Drug Development, European Institute of Oncology IRCCS, Milan, Italy

Focuses on treatment options for breast cancer, such as radiotherapy, systemic therapy and immunotherapy

Addresses ongoing research in screening, diagnosis and management for all subtypes of breast cancer

Edited and authored by leading experts in the field

Part of the book series: Cancer Treatment and Research (CTAR, volume 188)

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  • Table of contents

About this book

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Table of contents (14 chapters)

Front matter, antibody–drug conjugates: a new therapeutic approach for triple-negative breast cancer.

  • Ouissam Al Jarroudi, Khalid El Bairi, Giuseppe Curigliano, Said Afqir

Immune-Checkpoint Inhibitors: A New Line of Attack in Triple-Negative Breast Cancer

Screening programs for breast cancer: toward individualized, risk-adapted strategies of early detection.

  • Dario Trapani, Josè Sandoval, Pamela Trillo Aliaga, Liliana Ascione, Pier Paolo Maria Berton Giachetti, Giuseppe Curigliano et al.

Transversal Perspectives of Integrative Oncology Care in Gastric and Lobular Breast Cancer

  • Emilio Francesco Giunta, Gianluca Arrichiello, Annalisa Pappalardo, Piera Federico, Angelica Petrillo

Assessment and Response to Neoadjuvant Treatments in Breast Cancer: Current Practice, Response Monitoring, Future Approaches and Perspectives

  • Vincenzo Sabatino, Alma Pignata, Marvi Valentini, Carmen Fantò, Irene Leonardi, Michela Campora

Estimating the Benefit of Preoperative Systemic Therapy to Reduce the Extent of Breast Cancer Surgery: Current Standard and Future Directions

  • Giacomo Montagna

A Precise Approach for Radiotherapy of Breast Cancer

  • Samantha Sigurdson, Stephane Thibodeau, Martin Korzeniowski, Fabio Ynoe Moraes

Fast Mimicking Diets and Other Innovative Nutritional Interventions to Treat Patients with Breast Cancer

  • Federica Giugliano, Laura Boldrini, Jacopo Uliano, Edoardo Crimini, Ida Minchella, Giuseppe Curigliano

Mechanisms of Endocrine Resistance in Hormone Receptor-Positive Breast Cancer

  • Antonio Marra, Dario Trapani, Emanuela Ferraro, Giuseppe Curigliano

Innovative Therapeutic Approaches for Patients with HER2-Positive Breast Cancer

  • Beatrice Taurelli Salimbeni, Emanuela Ferraro, Luca Boscolo Bielo, Giuseppe Curigliano

Breast Cancer Brain Metastases: Achilles’ Heel in Breast Cancer Patients’ Care

  • Emanuela Ferraro, Andrew D. Seidman

New Concepts in Cardio-Oncology

  • Paola Zagami, Eleonora Nicolò, Chiara Corti, Carmine Valenza, Giuseppe Curigliano

Next-Generation Sequencing for Advanced Breast Cancer: What the Way to Go?

  • Dario Trapani, Edoardo Crimini, José Sandoval, Giuseppe Curigliano

The Global Landscape on the Access to Cancer Medicines for Breast Cancer: The ONCOLLEGE Experience

  • Csongor György Lengyel, Baker Shalal Habeeb, Sara Cecilia Altuna, Dario Trapani, Shah Zeb Khan, Sadaqat Hussain
  • Breast Cancer Treatment
  • Triple-negative Breast Cancer
  • Tumor-infiltrating Lymphocytes
  • Immune Checkpoint Inhibitors
  • Screening programs for breast cancer
  • Precision surgery for the treatment of breast cancer
  • HER2- positive breast cancer
  • Biomarkers in Breast Cancer
  • Luminal B breast cancer
  • Onco-immunology of breast cancer

Ouissam Al Jarroudi, Khalid El Bairi

Giuseppe Curigliano

Dr. Ouissam Al Jarroudi, MD, is a distinguished medical oncologist practicing in the medical oncology department at Mohammed VI University Hospital in Oujda, Morocco. She holds a position as a professor at the Faculty of Medicine and Pharmacy, affiliated with Mohammed Ist University. Dr. Al Jarroudi has pursued various fellowships at renowned institutions such as the Department of Medical Oncology at Paul Brousse Hospital, Assistance Publique - Hopitaux de Paris, and Léon Bérard Center in France.

Dr. Al Jarroudi's research is primarily focused on prognostic and predictive biomarkers in breast cancer and she is currently a member of the European Society for Medical Oncology (ESMO) and the American Society of Clinical Oncology (ASCO).

Khalid El Bairi is a clinical research fellow and an investigator in OVANORDEST studies. He is currently pursuing clinical and translational research in medical oncology. He has published many peer-reviewed articles in the field of predictive and prognostic cancer biomarkers to improve survival outcomes in several WoS and Medline-indexed journals. His research focuses particularly on biomarkers for digestive and gynecological cancers such as ovarian and colorectal malignancies. He is currently a member of various international scientific societies such as the European Society for Medical Oncology (ESMO), the American Society of Clinical Oncology (ASCO), the European Society of Gynaecological Oncology (ESGO), and the American Association for Cancer Research (AACR). He is also an editor and reviewer for various journals and a guest editor for several special issues on emerging topics in gynecological cancers such as platinum-resistant ovarian cancer. He is also highly interested in teaching evidence-based medicine, clinical research methods, and publishing ethics to medical and PhD students and was selected for the 70th Lindau Nobel Laureate Meeting as a young scientist. He is also involved in “global oncology” initiatives through providing free training to young researchers across LMICs. He joined the ASCO Trainee & Early Career Advisory Group as a member for the 2022-2024 term and NCODA (National Community Oncology Dispensing Association, Inc.) as an advisory member of its International Executive Council in 2023.

Giuseppe Curigliano, MD PhD, is Associate Professor of Medical Oncology at the University of Milano and the Head of the Division of Early Drug Development at the European Institute of Oncology, IRCCS, Italy. He is a clinician and researcher specializing in early drug development for patients with solid tumors with a special commitment to breast cancer. He has been a member of the Italian National Health Council since 2018 and, in 2019, he served as Chair of the Scientific Committee of The Lega Nazionale Lotta ai Tumori. He has served as a Member of the ESMO Breast Cancer Faculty since 2001 and he is currently the Faculty Coordinator. He has also served on the Scientific Committee for the St Gallen Conference since 2011 and was the Scientific Co-Chair in St Gallen 2017 and 2019. He has been an Editorial Board Member for Annals of Oncology since 2014, and serves as Co-Editor in Chief of The Breast, Co-Editor in Chief of Cancer Treatment Reviews, Associate Editor of the European Journal of Cancer, Editor of the Journal of Clinical Oncology. He also serves on the European School of Oncology (ESO) faculty committee.  

Book Title : Breast Cancer Research and Treatment

Book Subtitle : Innovative Concepts

Editors : Ouissam Al Jarroudi, Khalid El Bairi, Giuseppe Curigliano

Series Title : Cancer Treatment and Research

DOI : https://doi.org/10.1007/978-3-031-33602-7

Publisher : Springer Cham

eBook Packages : Medicine , Medicine (R0)

Copyright Information : The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023

Hardcover ISBN : 978-3-031-33601-0 Published: 05 January 2024

Softcover ISBN : 978-3-031-33604-1 Due: 19 January 2025

eBook ISBN : 978-3-031-33602-7 Published: 04 January 2024

Series ISSN : 0927-3042

Series E-ISSN : 2509-8497

Edition Number : 1

Number of Pages : VIII, 368

Number of Illustrations : 5 b/w illustrations, 28 illustrations in colour

Topics : Oncology , Gynecology , Cancer Research

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FAM3C in Cancer-Associated Adipocytes Promotes Breast Cancer Cell Survival and Metastasis

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Cancer Res 2024;84:545–59

  • Funder(s):  National Research Foundation of Korea (NRF)
  • Award Id(s): RS-2023-00218616
  • Principal Award Recipient(s): J.   Park
  • Award Id(s): NRF-2018R1A2B6003878
  • Award Id(s): NRF-2021R1A2C2005499
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  • Principal Award Recipient(s): M.   Kim
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  • Accepted Manuscript December 20 2023

Sahee Kim , Jiyoung Oh , Chanho Park , Min Kim , Woobeen Jo , Chu-Sook Kim , Sun Wook Cho , Jiyoung Park; FAM3C in Cancer-Associated Adipocytes Promotes Breast Cancer Cell Survival and Metastasis. Cancer Res 15 February 2024; 84 (4): 545–559. https://doi.org/10.1158/0008-5472.CAN-23-1641

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Adipose tissue within the tumor microenvironment (TME) plays a critical role in supporting breast cancer progression. In this study, we identified FAM3 metabolism-regulating signaling molecule C (FAM3C) produced by cancer-associated adipocytes (CAA) as a key regulator of tumor progression. FAM3C overexpression in cultured adipocytes significantly reduced cell death in both adipocytes and cocultured breast cancer cells while suppressing markers of fibrosis. Conversely, FAM3C depletion in CAAs resulted in adipocyte–mesenchymal transition (AMT) and increased fibrosis within the TME. Adipocyte FAM3C expression was driven by TGFβ signaling from breast cancer cells and was reduced upon treatment with a TGFβ-neutralizing antibody. FAM3C knockdown in CAAs early in tumorigenesis in a genetically engineered mouse model of breast cancer significantly inhibited primary and metastatic tumor growth. Circulating FAM3C levels were elevated in patients with metastatic breast cancer compared with those with nonmetastatic breast cancer. These results suggest that therapeutic inhibition of FAM3C expression levels in CAAs during early tumor development could be a promising approach in the treatment of patients with breast cancer.

High FAM3C levels in cancer-associated adipocytes contribute to tumor-supportive niches and are tightly associated with metastatic growth, indicating that FAM3C inhibition could be beneficial for treating patients with breast cancer.

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breast cancer in research and treatment

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Research reveals potential breakthrough in breast cancer treatment

By Imogen Howse via SWNS

Breast cancer could be treated with a drug that copies the way the hormone testosterone works, according to new research.

Figures show breast cancer is the most common type of cancer in the UK, with around one in seven women diagnosed with the disease during their lifetime.

For decades there has been a focus on treating breast cancer hormonally – by blocking estrogen.

But a new study has discovered a potentially less toxic way to tackle the disease.

Researchers at the University of Adelaide in Australia, the Dana-Farbed Cancer Institute in the US, and the University of Liverpool in the UK have found that the drug enobosarm – which can be taken orally – has antitumor qualities.

It works by stimulating a patient’s androgen receptor (AR), which has previously been shown to suppress estrogen receptor-positive (ER+) breast cancer.

ER+ breast cancer – which is when the hormone estrogen tells a tumor’s cells to grow – constitutes 80 percent of all breast cancer cases.

The research team assessed enobosarm’s safety and efficacy in 136 postmenopausal women with advanced or metastatic ER+, HER2-negative breast cancer.

Results revealed that the drug worked well against tumors, without adversely effecting a patient’s quality of life or causing masculinizing symptoms – as is common in traditional hormone-blocking cancer treatments.

Senior co-author Professor Wayne Tilley, of the University of Adelaide, said: “The effectiveness of enobosarm lies in its ability to activate the AR and trigger a natural defense mechanism in breast tissue, thereby slowing the growth of ER+ breast cancer, which relies on the hormone estrogen to grow and spread.”

He said the research is supported by the University’s previous clinical research, which established that the AR is a tumor suppressor in ER+ breast cancer.

The proposed new hormonal strategy, published in The Lancet Oncology , differs from traditional cancer treatments which involve suppressing estrogen in the body.

While these treatments prove successful initially, they can cause severe side effects – and treatment-resistant progression of the disease is common.

The research team’s discovery offers the hope of a less toxic, less debilitating form of treatment.

Senior co-author and study principal investigator Dr. Beth Overmoyer, of the Dana-Farber Cancer Institute in the US, said: “This is the first time a non-estrogen receptor hormonal treatment approach has been shown to be clinically advantageous in ER+ breast cancer.

“Our study supports further investigation of enobosarm in earlier stages of breast cancer, as well as in combination with targeted therapies such as ribociclib – a CDK 4/6 inhibitor.”

The post Research reveals potential breakthrough in breast cancer treatment appeared first on Talker .

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‘Pioneering’ breakthrough paves way for new breast cancer treatment

New treatment could ‘disrupt’ growth of breast cancer tumours, article bookmarked.

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A breakthrough injection could pave the way for a pioneering new treatment for breast cancer, which kills thousands of women every year.

Scientists have found a way to use a new cancer treatment, which targets the cells that help tumours survive, to prevent the growth and spread of breast cancer for the first time.

At least 55,000 people are diagnosed with breast cancer and 11,500 women die from the disease each year in the UK.

Researchers from the Institute of Cancer Research, through tests on mice, have found a way to adapt a new cutting edge type of immunotherapy treatment, which traditionally has had limited success in treating breast cancer, to make it more “effective and targeted”. Human trials could be the next step.

The news comes amid worsening waiting times for breast cancer treatment within England. Last year, The Independent revealed a shocking warning from oncologists that breast cancer treatment is facing a “crisis” due to a lack of specialist doctors and nurses to deliver new treatments.

While chemotherapy and radiotherapy target cancer cells directly, immunotherapy works by helping the body’s immune system recognise and kill cancer cells.

Scientists at the Institute of Cancer Research have now adapted a method of immunotherapy for breast cancer specifically and tested the treatment on mice.

The treatment, called CAR-T, works by removing a patient’s healthy immune cells and genetically modifying them to attack specific targets.

As part of the treatment, T-cells – blood cells that protect the body from infection and disease – are genetically modified in a lab to make them better at killing cancer and returned to the blood.

It has been used to treat some blood cancers but never for breast cancer- which is the second leading cause of cancer deaths among women in the UK.

Last April NHS England announced it would roll out CAR-T therapies to more patients with two types of blood cancer. Around 215 patients with a blood cancer called “Large B-cell Lymphoma” will now be eligible for this treatment each year.

Researchers said the use of CAR-T therapy on solid cancers “remains a challenge”.

To use CAR-T for breast cancer, researchers modified the treatment to target a protein called endosalin. They found this disrupted the tumour’s blood supply and reduced its growth and spread.

Dr Frances Turrell, study co-leader and postdoctoral training fellow at the Institute of Cancer Research, said: “This is the very first study that demonstrates the effectiveness of using endosialin-directed CAR-T cells to reduce breast cancer tumour growth and spread.

She said immunotherapy has had limited success in treating breast cancer but by targeting the cells that support the tumour and help it to survive the study had found a “promising” new way to develop a more “effective and targeted” treatment for breast cancer.

The team, funded by the charity Breast Cancer Now, also tested the treatment on lung cancer tumours in mice and saw similar successful results, indicating it could be used for other cancers also.

Professor Clare Isacke, professor of molecular cell biology at The Institute of Cancer Research, London, said human trials for the new method would take at least two years from this point as steps need to be taken to make the therapy suitable for human patients.

The findings also suggest that because the therapy does impact cells without the protein endosialin, this could lead to treatment with fewer side effects for patients than traditional immunotherapy.

Dr Simon Vincent, director of research, support and influencing at Breast Cancer Now, said: “This exciting research could lead to much-needed targeted treatments for people with breast cancer, and with one person dying from breast cancer every 45 minutes in the UK, new treatments like these are urgently needed.

“Now we know that the treatment works in principle in mice, Breast Cancer Now researchers can continue to develop this immunotherapy to make it suitable for people, as well as to understand the full effect it could have and who it may benefit the most.”

Research information manager at Cancer Research UK, Dr Nisharnthi Duggan said: “Identifying new targets for immunotherapy could increase the number of cancers that can be treated by this type of therapy.

“While still early-stage, this research suggests that we can target the processes which help certain tumours to thrive, rather than targeting the cancer itself, a strategy that could be applied to a wide range of cancer types.”

Meanwhile , on Monday research from the International Cancer Benchmarking Partnership also warned the UK lags behind other countries in its use of two other cancer treatments chemotherapy and radiotherapy.

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Photo of Dr. Deborah Anderson, wearing a lab coat, in a laboratory at the University of Saskatchewan campus.

USask researchers seek to develop new breast cancer treatments

Improving patient’s cancer treatments and minimizing side effects is the focus of new research at the University of Saskatchewan (USask) which aims to explore an innovative and potentially life-changing treatment targeting the most aggressive form of breast cancer.

Feb 29, 2024

Dr. Deborah Anderson (PhD), the director of research for the Saskatchewan Cancer Agency and a professor in USask’s College of Medicine, is working with other scientists at USask and across Canada to develop a new drug treatment for metastatic breast cancer.   

Previous work done by Anderson and other cancer researchers identified a different marker, the CLIC3 protein, as a new area target for pharmaceuticals to target and battle triple-negative breast cancer.  

The research conducted by Anderson and her team is working towards developing the first-ever drugs to target CLIC3. By focusing on the CLIC3 protein, Anderson said the hope is the new drug will prevent the cancer from growing and spreading.   

“We have a lead compound and will work to modify it so that it binds tighter, is more effective at inhibiting the CLIC3 target ... and to make sure that not only is it a compound that inhibits the metastatic cell properties, but it’s also a good and safe drug for patients to take,” Anderson said.   

Anderson said there are three major types of breast cancer, and chemotherapy is typically used to battle “triple-negative” breast cancer – one of the most aggressive and difficult to treat, as it does not possess any of the three common receptors targeted for drug or hormone treatments.  

If Anderson and her team continue to have success developing this new treatment drug, they could give patients an option for fighting breast cancer that has far fewer side effects than chemotherapy.  

“(Chemotherapy) is typically quite harsh for patients,” she said. “This would be more targeted, and potentially be given to patients early on to prevent new metastasis from happening. So, once you know you have cancer, it could be given to try to block the cancer cells from forming new metastasis.”  

The goal for this potential new drug would be to provide an additive therapy that can be used alongside other treatment methods. The research is still in the early stages, but the potential for a chemotherapy alternative could be game-changing for breast cancer patients.   

“I’m a fundamental researcher. This is the first time we’ve ventured into something that might make a change in a patient’s life,” she said. “That’s very exciting for anybody, that they think they might actually have a positive impact on healthcare, on the ability of patients to have better quality-of-life.”  

Anderson credited the CIHR for funding this ongoing project, and also thanked the USask College of Medicine for providing support while looking for additional funding to support the project.  

Together, we will undertake the research the world needs. We invite you to join by  supporting critical research  at USask.

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Augmented interpretation of HER2, ER, and PR in breast cancer by artificial intelligence analyzer: enhancing interobserver agreement through a reader study of 201 cases

  • Minsun Jung 1   na1 ,
  • Seung Geun Song 2 ,
  • Soo Ick Cho 3 ,
  • Sangwon Shin 3 ,
  • Taebum Lee 3 ,
  • Wonkyung Jung 3 ,
  • Hajin Lee 3 ,
  • Jiyoung Park 3 ,
  • Sanghoon Song 3 ,
  • Gahee Park 3 ,
  • Heon Song 3 ,
  • Seonwook Park 3 ,
  • Jinhee Lee 3 ,
  • Mingu Kang 3 ,
  • Jongchan Park 3 ,
  • Sergio Pereira 3 ,
  • Donggeun Yoo 3 ,
  • Keunhyung Chung 3 ,
  • Siraj M. Ali 3 &
  • So-Woon Kim 4  

Breast Cancer Research volume  26 , Article number:  31 ( 2024 ) Cite this article

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Metrics details

Accurate classification of breast cancer molecular subtypes is crucial in determining treatment strategies and predicting clinical outcomes. This classification largely depends on the assessment of human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), and progesterone receptor (PR) status. However, variability in interpretation among pathologists pose challenges to the accuracy of this classification. This study evaluates the role of artificial intelligence (AI) in enhancing the consistency of these evaluations.

AI-powered HER2 and ER/PR analyzers, consisting of cell and tissue models, were developed using 1,259 HER2, 744 ER, and 466 PR-stained immunohistochemistry (IHC) whole-slide images of breast cancer. External validation cohort comprising HER2, ER, and PR IHCs of 201 breast cancer cases were analyzed with these AI-powered analyzers. Three board-certified pathologists independently assessed these cases without AI annotation. Then, cases with differing interpretations between pathologists and the AI analyzer were revisited with AI assistance, focusing on evaluating the influence of AI assistance on the concordance among pathologists during the revised evaluation compared to the initial assessment.

Reevaluation was required in 61 (30.3%), 42 (20.9%), and 80 (39.8%) of HER2, in 15 (7.5%), 17 (8.5%), and 11 (5.5%) of ER, and in 26 (12.9%), 24 (11.9%), and 28 (13.9%) of PR evaluations by the pathologists, respectively. Compared to initial interpretations, the assistance of AI led to a notable increase in the agreement among three pathologists on the status of HER2 (from 49.3 to 74.1%, p  < 0.001), ER (from 93.0 to 96.5%, p  = 0.096), and PR (from 84.6 to 91.5%, p  = 0.006). This improvement was especially evident in cases of HER2 2+ and 1+, where the concordance significantly increased from 46.2 to 68.4% and from 26.5 to 70.7%, respectively. Consequently, a refinement in the classification of breast cancer molecular subtypes (from 58.2 to 78.6%, p  < 0.001) was achieved with AI assistance.

Conclusions

This study underscores the significant role of AI analyzers in improving pathologists' concordance in the classification of breast cancer molecular subtypes.

Breast cancer has typically been classified into molecular intrinsic subtypes based on routine immunohistochemistry (IHC), including human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), and progesterone receptor (PR) [ 1 ]. The classification based on the presence of these receptors and expression level plays a significant role in both prognostic assessment and determining the most appropriate treatment approach [ 1 , 2 ]. For example, the level of HER2 expression is crucial for predicting the therapeutic response to trastuzumab, the canonical HER2-targeted monoclonal antibody and the level of ER expression is essential for forecasting the treatment response to tamoxifen, a selective ER modulator [ 3 , 4 ]. Recently, novel therapeutic agents such as trastuzumab deruxtecan, an antibody–drug conjugate (ADC) of trastuzumab and a ‘tecan,’ have emerged, demonstrating compelling results in particular for the treatment of HER2-low (HER2 1+ or HER2 2+ without in situ hybridization [ISH] amplification) breast cancer [ 5 ]. Consequently, this underscores the importance of a precise evaluation of the expression levels of the protein targets via IHC, as these results play a pivotal role in tailoring and optimizing therapeutic strategies.

However, significant interobserver and interlaboratory variations among pathologists have been noted in the evaluation of HER2, ER, and PR status, particularly for possible HER2-low cases [ 6 , 7 , 8 ]. Such inconsistencies might directly influence patient survival outcomes by affecting the selection of optimal treatment strategies [ 8 , 9 ].

Recently, advancements and increasing deployment of digital pathology systems have paved the way for numerous strategies to analyze and quantify digital whole-slide images (WSIs) [ 10 , 11 ]. Specifically, this permits the application of AI algorithms designed for various fields of oncology, including image analysis [ 12 ]. In early studies, such algorithms have shown significant potential to reduce interobserver variability among pathologists which has correlated with the improved prediction of response to treatment [ 13 , 14 , 15 , 16 , 17 ].

There are several approaches to utilize AI algorithms to assess HER2, ER, and PR status in breast cancer. Previous studies demonstrated the improved consistency and accuracy in the evaluation of HER2 status by pathologists with AI assistance, including HER2-low cases [ 18 , 19 , 20 , 21 ]. AI algorithms have also demonstrated excellent agreement with pathologists' interpretation of ER and PR status [ 22 , 23 ]. Although these studies have reported on the development of individual AI models for the assessment of HER2 or ER/PR, few studies have evaluated the impact of AI-aided analysis on assessing HER2, ER, and PR comprehensively for a single patient cohort.

In this study, we conducted a comprehensive AI-assisted reader study to evaluate HER2, ER, and PR status on the same patients. Our aim was to examine whether AI assistance could ameliorate the interobserver variability associated with the evaluation of HER2, ER, and PR status in breast cancer, and subsequent impact on the determination of molecular subtypes of breast cancer.

Dataset for HER2 and ER/PR analyzer development

An AI-powered HER2 analyzer of breast, Lunit SCOPE HER2 (Lunit, Seoul, Republic of Korea) was developed with 1259 HER2 IHC-stained WSIs of breast cancer, consisting of 880, 253, and 126 for training, tuning, and internal test, in each set. An AI-powered ER/PR analyzer of breast, Lunit SCOPE ER/PR was developed with 1210 ER/PR IHC-stained WSIs of breast cancer, consisting of 782, 287, and 141 WSIs for training, tuning, and internal test, in each set. Further information on the dataset is described in Additional file 1 : Supplementary Methods.

Data preprocessing for model development

Patches of a predefined area (0.04 mm 2 for cell and 2.54 mm 2 for tissue) were extracted from WSIs. Those images had a normalized micron per pixel resolution of 0.19 μm (1024 * 1024 pixels for cell and 8192 * 8192 pixels for tissue) and were used as input for the AI model development. In the patch level, we prevented dataset leakage by following the classification of training, tuning, and internal tests classified by WSIs. Additional file 1 : Table S1 shows the numbers of WSIs and patches assigned to training, tuning, and internal test sets. All patches were annotated by board-certified pathologists, and further information about annotation results is mentioned in Additional file 1 : Supplementary Methods, Additional file 1 : Tables S2 and S3.

Development of AI model—Cell Detection Model

The cell detection models of both HER2 and ER/PR identify all tumor cells. For HER2, the model also identifies other cells (OTs or non-tumor cells). Beyond detecting the location of cells, the model is also proficient in identifying varying intensity levels associated with each cell. Therefore, the HER2 model can detect a total of five cell classes, including four tumor cells (3+, 2+, 1+, and 0), and OTs, while ER/PR model can detect four cell classes of tumor cells (3+, 2+, 1+, and 0). This cell detection task was approached as a dense segmentation challenge, utilizing the DeepLabv3+ segmentation model with a ResNet-34 for feature extraction [ 24 , 25 ]. Additional details of the AI model are described in Additional file 1 : Supplementary Methods.

Development of AI model—Tissue segmentation model

The tissue segmentation model evaluates each pixel of the input to determine if it belongs to specific classes. The HER2 model can segment CA (cancer area; invasive breast cancer), CIS (carcinoma in situ), or BG (background; any tissue area that does not belong to CA or CIS), while the ER/PR model can segment CA or BG (including CIS). The model employs a DeepLabv3, complemented with a ResNet-101 for feature extraction. Additional details of the AI model are described in Additional file 1 : Supplementary Methods.

Scoring algorithms of HER2 and ER/PR analyzer

The HER2 analyzer and ER/PR analyzer evaluated the expression of HER2 and ER/PR at the slide level by merging the results from the cell detection model and the tissue segmentation model from a WSI. The HER2 analyzer counted the HER2-positive tumor cells in the CA area and calculated the proportion of each tumor cell class (3+, 2+, 1+, and 0). The ER/PR analyzer also counted the ER/PR-positive tumor cells in the CA area, but calculated the proportion of any positive tumor cells (regardless of intensity level). The slide-level expression level of HER2, ER, and PR was categorized by the American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAP) guidelines [ 26 , 27 ].

External test dataset and reader study

An external test set was selected from Kyung Hee University Hospital (Seoul, Republic of Korea). The inclusion criteria for this study were cases diagnosed as breast cancer by pathologists between January 2018 and December 2021 and had all of the matched HER2, ER, and PR slides. All slides were stained with Ventana anti-HER2/neu (4B5) (Ventana Medical Systems, Tucson, AZ, USA) for HER2, Novocastra Liquid Mouse Monoclonal Antibody Estrogen Receptor (NCL-L-ER-6F11) (Novocastra Laboratories, Newcastle, UK) for ER, and Novocastra Liquid Mouse Monoclonal Antibody Progesterone Receptor (PGR-312-L-CE, PGR-312-L-CE-S) for PR. All slides were scanned with a P1000 scanner with 40× magnification and were inferred by the AI algorithms mentioned above.

Three board-certified pathologists (M.J., S.-W.K., and S.G.S.), each from different hospitals, independently evaluated the scanned HER2, ER, and PR IHC slides in accordance with the guidelines using a digital visualizer [ 26 , 27 ]. They could zoom in or out of each scanned WSI through the digital visualizer to determine the expression level of HER2/ER/PR at the slide level (Additional file 1 : Figure S1). They annotated WSI-level HER2 expression level as 3+ (positive), 2+ (equivocal), 1+ (negative but low), and 0 (negative), and ER/PR expression level as positive (> 10% of cell staining), low positive (1–10% of cell staining), and negative (< 1% of cell staining) without AI inference results. Per ASCO/CAP guidelines updated in 2020, PR cases were categorized as negative and positive, but in this study, low positives were additionally categorized separately to make comparable results with ER cases.

If a pathologist's evaluation (any of HER2, ER, and PR IHC) did not match the result from AI analyzers, each pathologist revisited the case using AI's inferred results and reevaluated it independently. In this phase, the pathologists used the same digital visualizer as before, with the AI inference results added. The visualizer showed the total numbers of IHC-positive tumor cells (including their intensity) and negative tumor cells, the expression level of HER2/ER/PR, and the coordinate of each cell on the WSIs and segmentation of tissue (Additional file 1 : Figure S1). Figure  1 displays the flow of the reader study.

figure 1

A schematic flow of the reader study (AI: artificial intelligence, ER: estrogen receptor, HER2: human epidermal growth factor receptor 2, PR: progesterone receptor)

Consensus was determined by combining the results of independent evaluations from three pathologists. If all three pathologists agreed to the results, the case was categorized as concordant; if only two agreed, it was categorized as partially concordant, and otherwise as discordant. A consensus result is defined as an evaluation result that at least two out of three people agree on. Therefore, a concordant or partially concordant case can have a consensus result. If a case was altogether discordant, those cases were labeled as no consensus. The degree of agreement between pathologists is measured in both initial (without AI assistance) and revised (revisiting and reevaluating with AI assistance in case of disagreement with AI results) results.

This study was approved by the Institutional Review Board (IRB) of Kyung Hee University Hospital (IRB no. KHUH 2022-01-035). Informed consent was waived by the IRB because of the retrospective design of the study and the anonymized clinical data used in the analysis. The study was performed in accordance with the Declaration of Helsinki.

Statistical analysis

F1 score and intersection over union (IoU) were applied to evaluate the performance of the cell model and the tissue model, respectively. Agreement rate or quadratic weighted kappa value between raters or AI analyzers was evaluated as overall agreement. Categorical variables were compared using the Chi-square test/Fisher’s exact test or McNemar test. All statistical analyses were performed using Python 3.7 and R version 4.0.3 software (R Foundation for Statistical Computing, Vienna, Austria).

Performance of cell detection and tissue segmentation models—HER2 and ER/PR

In the HER2 model, the cell detection showed the best performance for OT, but had the lowest performance for 2+ tumor cells. For the ER/PR model, the highest cell detection performance was observed in 3+ tumor cells, while the performance was lowest in 1+ tumor cells. The tissue segmentation model in the HER2 model achieved better performance on CA than on CIS, while those in the ER/PR model achieved performances of CA comparable to the HER2 model. Further detail of cell detection and tissue segmentation model performance is described in Additional file 1 : Supplementary Results and Additional file 1 : Tables S4–S7.

Clinical information of the reader study set

We retrospectively collected data and found a total of 201 breast cancer patients with all three IHC types of HER2, ER, and PR slides. Of these, 199 (99.0%) were female and 2 (1.0%) were male. The median age at the time of specimen collection was 57 years, with ages ranging from a minimum of 28 to a maximum of 84 years. The majority of cases were surgical excision specimens ( N  = 189, 94.0%), and American Joint Committee on Cancer (AJCC) stage 1A cases were the most common ( N  = 87, 43.3%). Table 1 summarizes the clinical information of the cases.

WSI-level assessment of HER2/ER/PR by pathologists in the reader study set

For the HER2 WSI, there were 99 (49.3%) concordant cases, 99 (49.3%) partially concordant cases, and three (1.5%) discordant cases (Fig.  2 A). In the consensus results of the pathologists, there were 49 (24.4%) cases of HER2 3+, 91 (45.3%) cases of HER2 2+, 34 (16.9%) cases of HER2 1+, 24 (11.9%) cases of HER2 0, and 3 (1.5%) cases with no consensus. Consensus-classified HER2 3+ had the highest concordance rate (73.5%) and HER2 1+ had the lowest (26.5%). Agreement rates and quadratic weighted kappa values between the two pathologists were 66.2%/0.803 (pathologist 1 [P1] and pathologist 2 [P2]), 77.6%/0.843 (P1 and pathologist 3 [P3]), and 53.2%/0.709 (P2 and P3), respectively (Additional file 1 : Figure S2A–C).

figure 2

Concordance among pathologists in HER2 (human epidermal growth factor receptor 2) dataset ( A ), ER (estrogen receptor) dataset ( B ), and PR (progesterone receptor) dataset ( C ). Concordance between the consensus of pathologists and the AI (artificial intelligence) analyzer in HER2 dataset ( D ), ER dataset ( E ), and PR dataset ( F )

For the ER WSI, there were 187 (93.0%) concordant cases and 14 (7.0%) partially concordant cases (Fig.  2 B). In the pathologists’ consensus results, there were 153 (76.1%) cases of ER-positive, 10 (5.0%) cases of ER-low positive, and 38 (18.9%) cases of ER-negative. Consensus-classified ER-positive had the highest concordance rate (98.0%) and ER-low positive had the lowest (30.0%). Agreement rates and quadratic weighted kappa values between the two pathologists were 95.5%/0.940 (P1 and P2), 95.5%/0.952 (P1 and P3), and 95.0%/0.949 (P2 and P3), respectively (Additional file 1 : Figure S3A–C).

On the PR slides, there were 170 (84.6%) concordant cases, 29 (14.4%) partially concordant cases, and two (1.0%) discordant cases (Fig.  2 C). In the pathologists’ consensus results, PR-positive, PR-low positive, PR-negative, and no consensus were 132 (65.7%) cases, 17 (8.5%) cases, 50 (24.9%) cases, and 2 (1.0%) cases, in each. Consensus-classified PR-positive had the highest concordance rate (93.2%) and PR-low positive had the lowest (35.3%). Agreement rates and quadratic weighted kappa values between the two pathologists were 90.0%/0.922 (P1 and P2), 90.5%/0.937 (P1 and P3), and 87.6%/0.906 (P2 and P3), respectively (Additional file 1 : Figure S4A–C).

Overall, the pathologists' concordances for HER2/ER/PR IHC results are generally lower for the cases within IHC low positive category (i.e., HER2 2+ or 1+, ER-low positive, PR-low positive).

Standalone performance of the AI analyzer

The AI analyzer had an agreement rate of 72.2% (143 out of 198, excluding three cases of no consensus) and quadratic weighted kappa value of 0.844 compared to the pathologists’ HER2 consensus result (Fig.  2 D). Compared to pathologists, the AI analyzer tended to classify lower HER2 grades than the pathologists’ consensus (Additional file 1 : Figure S5A). In the 99 cases where the three pathologists agreed, the AI results had an 89.9% ( N  = 89) agreement rate and quadratic weighted kappa value of 0.948 with the consensus result.

In the ER dataset, the AI analyzer had an agreement rate of 93.0% ( N  = 187) and quadratic weighted kappa value of 0.916 compared to the pathologists’ ER consensus result (Fig.  2 E). In contrast to the HER2 AI analyzer, compared to pathologists, the AI analyzer tended to classify higher ER grades than the pathologists’ consensus (Additional file 1 : Figure S5B). In the 187 cases where the three pathologists agreed, the AI results had a 96.3% ( N  = 180) agreement rate and quadratic weighted kappa value of 0.938 with the consensus result.

In the PR dataset, the AI analyzer had an agreement rate of 89.4% (178 out of 199, excluding two cases of no consensus) and quadratic weighted kappa value of 0.902 compared to the pathologists’ PR consensus result (Fig.  2 F). Similar to the ER AI analyzer, compared to pathologists, the AI analyzer tended to classify higher PR grades than the pathologists’ consensus (Additional file 1 : Figure S5C). In the 170 cases where the three pathologists agreed, the AI results had a 93.5% ( N  = 159) agreement rate and quadratic weighted kappa value of 0.941 with the consensus result.

Change in HER2/ER/PR interpretation after AI assistance

The cases that were discordant between the pathologists and AI were reevaluated by the pathologists. In the HER2 dataset, the numbers of cases revisited were as follows: 61 cases (30.3%) for P1, 42 cases (20.9%) for P2, and 80 cases (39.8%) for P3 (Fig.  3 A). Among these, the HER2 classification was revised by the pathologists in 46 cases (75.4%) for P1, 19 cases (45.2%) for P2, and 54 cases (67.5%) for P3. After revisiting, pathologists’ consensus results were changed; HER2 3+, HER2 2+, HER2 1+, HER2 0, and no consensus were 38 (18.9%) cases, 76 (37.8%) cases, 58 (28.9%) cases, 28 (13.9%) cases, and 1 (0.5%) cases, in each (Fig.  3 B). In cases ( N  = 112) of revisit, HER2 results tended to change to a lower grade (e.g., HER2 1+ to 0, 2+ to 1 +) (Fig.  3 C, Additional file 1 : Figures S6A-C). After revisiting, the number of cases in which all three pathologists agreed increased significantly from 99 (49.3%) to 149 (74.1%) cases ( p  < 0.001) (Fig.  2 A). Compared to the initial evaluation, the revised evaluation improved concordance at all HER2 expression levels, but especially at HER2 2+ and 1+, with a significant increase in concordance from 46.2 to 68.4% and 26.5 to 70.7%, respectively (Fig.  2 A). Agreement rates and quadratic weighted kappa values between the two pathologists after revision were changed to 84.6%/0.914 (P1 and P2), 84.6%/0.911 (P1 and P3), and 78.6%/0.875 (P2 and P3), respectively (Additional file 1 : Figure S2D–F).

figure 3

A Proportion of revisited and revised cases by artificial intelligence (AI) analyzer in Pathologist 1 (P1), Pathologist 2 (P2), and Pathologist 3 (P3). Initial and revised pathologists’ consensus of HER2 (human epidermal growth factor receptor 2) in All cases ( B ) or revisited cases only ( C ). Initial and revised pathologists’ consensus of ER (estrogen receptor) in All cases ( D ) or revisited cases only ( E ). Initial and revised pathologists’ consensus of PR (progesterone receptor) in All cases ( F ) or revisited cases only ( G )

In ER dataset, there were 15 (7.5%) cases for P1, 17 (8.5%) cases for P2, and 11 (5.5%) cases for P3 that went to revisit (Fig.  3 A). Among them, pathologists revised ER classification in 6 (40.0%), 8 (47.1%), and 7 (63.6%) cases, in each. After revisiting, pathologists’ consensus results were changed; ER-positive, ER-low positive, ER-negative, and no consensus were 156 (77.6%) cases, 6 (3.0%) cases, 37 (18.4%) cases, and 2 (1.0%) cases, in each (Fig.  3 D). In cases ( N  = 21) of revisit, ER results tended to change to a higher grade (e.g., ER-negative to weak positive, weak positive to positive) (Fig.  3 E, Additional file 1 : Figures S6D–F). After revisiting, the number of cases in which all three pathologists agreed increased from 187 (93.0%) to 194 (96.5%) cases, but this increase was not statistically significant ( p  = 0.096) (Fig.  2 B). Compared to the initial pathologist interpretation, the revised evaluation improved concordance among the pathologists at all ER expression levels, but especially at ER-low positive, with a significant increase in concordance from 30.0 to 83.3% (Fig.  2 B), which concurred with the acceptance of the AI’s inference of ER-low positivity (Fig.  2 E). Agreement rates and quadratic weighted kappa values between the two pathologists after revision were changed to 97.5%/0.967 (P1 and P2), 97.5%/0.967 (P1 and P3), and 97.1%/0.975 (P2 and P3), respectively (Additional file 1 : Figure S3D–F).

In PR dataset, there were 26 (12.9%) cases for P1, 24 (11.9%) cases for P2, and 28 (13.9%) cases for P3 that went to revisit (Fig.  3 A). Among them, pathologists revised PR classification in 7 (26.9%), 9 (37.5%), and 16 (57.1%) cases, in each. After revisiting, pathologists’ consensus results were changed; PR-positive, PR-low positive, PR-negative, and no consensus were 131 (65.2%) cases, 19 (9.5%) cases, 50 (24.9%) cases, and 1 (0.5%) cases, in each (Fig.  3 F). In cases ( N  = 42) of revisit, changes in PR results did not skew toward higher or lower (Fig.  3 G, Additional file 1 : Figures S6G–I). After revisiting, the number of cases in which all three pathologists agreed increased significantly from 170 (84.6%) to 184 (91.5%) cases ( p  = 0.006) (Fig.  2 C). Compared to the initial evaluation, the revised evaluation improved concordance among the pathologists especially at PR-low positive, with a significant increase in concordance from 35.3 to 73.7% (Fig.  2 C). The pathologist–AI concordance also increased in PR-low positive cases, from 70.6 to 89.5% (Fig.  2 F). Agreement rates and quadratic weighted kappa values between the two pathologists after revision were changed to 94.5%/0.962 (P1 and P2), 94.5%/0.953 (P1 and P3), and 93.5%/0.955 (P2 and P3), respectively (Additional file 1 : Figure S4D–F).

Molecular Subtypes of breast cancer after AI assistance

In this study, breast cancer molecular subtypes can be divided into the following: (1) HER2-positive: HER2 3+; (2) HER2-equivocal and HR-positive: HER2 2+ with at least one ER/PR-positive (including low positive); (3) HER2-equivocal and HR-negative: HER2 2+ with both ER/PR-negative; (4) HR-positive: HER2 1+ or 0 with at least one ER/PR-positive (including low positive); (5) triple-negative breast cancer (TNBC): HER2 1+ or 0 with both ER/PR-negative. HER2-equivocal and HR-positive subtype had the highest number of cases at initial evaluation ( N  = 82, 40.8%), followed by HER2-positive subtype and HR-positive subtype ( N  = 49, 24.4% in each), TNBC subtype ( N  = 9, 4.5%), HER2-equivocal and HR-negative subtype ( N  = 8, 4.0%), and no consensus ( N  = 4, 2.0%), respectively (Fig.  4 A). The number of cases where subtypes were agreed between all pathologists was 117 (58.2%) cases. Of these, the initial concordance rates of pathologist interpretation were lowest for HER2-equivocal and HR-positive subtype at 45.1% and highest for HER2-positive at 73.5% (Fig.  4 B).

figure 4

A Initial and revised pathologists’ consensus of subtype. B Initial and revised concordance rates of subtype among pathologists (ER: estrogen receptor, HER2: human epidermal growth factor receptor 2, PR: progesterone receptor)

After revisiting by AI analyzers, HR-positive subtype was the most common with 74 (36.8%) cases, followed by HER2-equivocal and HR-positive subtype with 72 (35.8%) cases, HER2-positive subtype with 38 (18.9%) cases, TNBC subtype with 10 (5.0%) cases, HER2-equivocal and HR-negative subtype with 4 (2.0%) cases, and no consensus with 3 (1.5%) cases (Fig.  4 A). Of note, 18.4% (9/49) of HER2-positive cases were reclassified as a HER2-equivocal and HR-positive type, and 28.0% (23/82) of the HER2-equivocal and HR-positive cases were reclassified as an HR-positive type. The number of cases where subtypes were agreed between all pathologists significantly increased from 117 to 158 cases (58.2 to 78.6%, p  < 0.001). The concordance rate increased for all subtypes except for the HER2-equivocal and HR-negative subtype (Fig.  4 B).

Analyze factors that can affect pathologists’ concordance or AI analyzer performance

We further analyzed the interaction between the pathologist and the AI analyzer. First, a total of 304 revisiting requests were made to the three pathologists, of which 166 (54.6%) revised their interpretation according to the AI analyzer’s results. HER2 was most likely to be changed on revisit (62.8%) and PR was least likely (39.7%) (Fig.  5 ). Depending on the number of pathologists who requested to revisit, 67.5% (54/80) of cases where only one pathologist was asked to revisit the case were revised based on the AI analyzer results, but only 29.4% (30/102) of cases where all three pathologists were asked to revisit the case were revised.

figure 5

Rate of revising by pathologists according to the artificial intelligence (AI) analyzer’s results, when one, two, or all three pathologists revisited (ER: estrogen receptor, HER2: human epidermal growth factor receptor 2, PR: progesterone receptor)

Next, we defined a complete failure of the AI analyzer as a case where all three pathologists were requested to revisit and none of them changed their initial interpretations. This occurred in a total of 10 cases. Within these, two cases exhibited specific failures in HER2, without affecting ER/PR evaluations. Four cases demonstrated failures solely in PR, with no impact on HER2 and ER evaluations. The remaining four cases presented concurrent failures in both ER and PR, but not in HER2.

In the case of HER2, the AI analyzer classified cases that were pathologists’ consensus 1+ in both cases as 2+. In those cases, normal ductal or CIS areas containing HER2-stained cells were classified as CA (Fig.  6 A). For the 4 cases with ER/PR overlapped, the pathologists’ consensus was negative, but the AI analyzer classified them as positive or low positive. These were due to the AI analyzer recognizing the inked area at the margin of the tissue as a CA with positive tumor cells (Fig.  6 B). Of the four cases with no ER issues and only PR issues, two were caused by ink, as above. In one case where the tumor cells showed mild atypia and a low density of tumor cell clusters, the AI analyzer made a poor interpretation, barely catching the CA throughout the entire area of a slide (Fig.  6 C). In the last case, the three pathologists concordantly classified it as low positive even after revision because there were clearly visible clusters of positive tumor cells at low magnification on the slide. However, the AI analyzer counted all the tumor cells and read them as negative (Fig.  6 D).

figure 6

A Carcinoma in situ areas containing HER2 (human epidermal growth factor receptor 2)-stained cells were classified as cancer area (CA) by HER2 analyzer (bar: 200 μm). B ER (estrogen receptor)/PR (progesterone receptor) analyzer recognized the inked area at the margin of the tissue as a CA with ER-positive tumor cells (bar left: 5 mm, right: 200 μm). C ER/PR analyzer barely caught the CA through the entire area of PR-stained slide (bar left: 5 mm, right: 100 μm). D In a PR-stained slide, pathologists focused the visible clusters of positive tumor cells at low magnification and classified them as low positive all together even after revision. In contrast, ER/PR analyzer counted all the tumor cells and interpreted them as negative (bar left: 5 mm, right: 100 μm)

In this study, we found that when pathologists assessed the expression of HER2, ER, and PR in breast cancer with the assistance of an AI algorithm, the concordance of their individual readings increased.

The ASCO/CAP guidelines strongly recommend HER2, ER, and PR testing of invasive breast cancers [ 26 , 27 ]. The objective of these guidelines is to enhance the accuracy of these diagnostic assays, which enable clinicians to identify breast cancer patients who will benefit most from endocrine therapy or HER2-targeted therapy. Recent advancements, notably the emergence of HER2-targeted ADC, have demonstrated improved survival outcomes in breast cancer patients with HER2 IHC scores of 1+ or 2+ (HER2-low when combined with knowledge of negative ERBB2 amplification status). This underscores the increasing necessity for a precise interpretation of HER2 testing [ 5 ].

In the evaluation of HER2 status via IHC, pronounced interobserver discrepancies among pathologists have been identified. While there is a high consensus among pathologists for 0 and +3 staining, agreement levels drop significantly for 1+ and 2+ staining [ 6 ]. Consistent with this observation, another study found a 26% agreement between HER2 IHC scores of 0 and 1+ [ 7 ]. As for ER and PR evaluations using IHC, although classifications related to the ER and PR status of tumors generally demonstrate good to excellent agreement, considerable variations both within and between laboratories have been reported [ 8 , 28 ]. Preceding these laboratory and observer variations, preanalytic factors can also affect the determination of IHC interpretations such as anatomic origin of the tissue, storage conditions, and fixation methods. Such discrepancies can lead to variations in the determination of IHC status, and thus subtyping, treatment and clinical outcomes [ 9 , 29 ].

Digital pathology has been rapidly spreading, overcoming issues related to image capacity and lack of standardization. [ 30 , 31 ]. With the spreading of digital pathology, there have been several attempts to introduce AI algorithms in the field of pathology to enhance standardization and compensate for analytic variability [ 10 , 11 ]. Some studies have evidenced that these algorithms not only diminish interobserver variability but can also prognosticate the treatment response to immunotherapy by assessing programmed death ligand 1 (PD-L1) expression or tumor infiltrating lymphocytes [ 13 , 14 , 16 , 17 ].

Previous computational assessments, whether rule-based or utilizing machine learning models, have shown promise in evaluating the IHC status of HER2, ER, and PR, typically reporting a high level of concordance between pathologists’ manual scoring and computational assessment [ 32 , 33 , 34 , 35 , 36 ]. However, most of those algorithms do not address tasks with parameters beyond their specific training set due to a lack of robustness and importantly may require human intervention to extract features, making these less suitable for the scale of clinical workflow. Furthermore, many such early models are circumscribed to analyzing tissue microarray images or require the selection of specific regions of interest (ROI) for analysis instead of WSIs [ 33 , 34 , 35 ].

The advent of large-scale datasets, coupled with the evolution of AI algorithms and drastically increasing computing power, have paved the way for deep learning (DL)-based AI models which mimic algorithmic structures of the human brain that exhibit impressive alignment with pathologists' assessments [ 18 , 19 , 20 , 21 , 22 , 23 ]. An AI model has shown a potential to be included in clinical digital workflow and another model has shown robustness across variable environmental factors such as staining systems or types of scanners [ 22 , 23 ]. However, a common thread of limitation in most studies is their focus on individual AI analyzers assessing HER2, ER, or PR. Even in studies where AI was used for multiple biomarkers, concurrent evaluations on the same patient remained rare [ 23 , 37 ].

The Al analyzer developed in this study was based on the DL algorithm and encompasses models for HER2 and ER/PR which each also contains both a cell detection model and a tissue segmentation model. In a previous report, an AI-powered PD-L1 analyzer based on a cell model alone occasionally misidentified normal epithelial cells as PD-L1 negative tumor cells [ 13 ]. In this study, by combining the results from cell and tissue models, some falsely detected tumor cells in areas outside ROI could be excluded.

In the context of the cell detection model, many discrepancies were observed, mainly in cell classes where the AI analyzer’s assessment differed by a single intensity grade, such as changing from a 2+ tumor cell to a 1+ tumor cell. In contrast, cases where the AI analyzer misjudged the intensity by more than two grades, like from a 3+ tumor cell to a negative (0) tumor cell, were less common. Another study also suggested that AI models might have reduced accuracy for mid-range grades compared to extreme grades [ 38 ].

In our study, the ER/PR analyzer exhibited relatively high agreement with the pathologist's interpretation because it focused solely on the proportion of positive or negative tumor cells, without considering intensity. This meant that even if the cell model misidentified a 2+ tumor cell as a 1+ tumor cell, it did not significantly affect the final result. However, the HER2 analyzer had lower agreement with the pathologist's interpretation because it needed to consider both intensity and proportion. Still, as shown in Additional file 1 : Tables S4 and S6, there were cases where 2+ tumor cells were misclassified as 1+ tumor cells and vice versa. However, since there are typically thousands or more tumor cells in a WSI, unless misclassifications are skewed toward a particular class, the overall impact of misdetection is somewhat mitigated. As a result, the AI analyzers developed in our study demonstrated reliable performance, even when tested on external datasets, as indicated by the high agreement between the AI analyzers and pathologists for HER2/ER/PR grades.

After revising with AI analyzer, concordance in the individual interpretation of each IHC type and for molecular subtypes derived from the combined results of IHC was enhanced. Importantly, these results showed a significant increase in concordance for the classes corresponding to the low-HER2 classification (HER2 IHC 1+ or 2+) and remarkable decrease in HER2-positive class by the AI assistance. Following AI-assisted revisit, pathologists reached a consensus to downgrade the 26 out of 91 (28.6%) initial 2+ cases to 1+ (Fig.  3 B). This downgrading avoids (unnecessary) ISH testing for ERBB2 amplification as indicated for HER2 2+ cases as this would identify HER2-low cases, either 2+ and ISH−, or 1+. This carries immediate implications given the eligibility of HER2-low patients for Enhertu, the HER2 ADC [ 5 ].

When utilizing the AI analyzer as a tool for second opinions, as done in this study, pathologists can maintain their original workflow, requiring reinterpretation in only a select subset of cases (approximately 30% for HER2 and 10% for ER and PR). As a result, with AI assistance, pathologists can achieve a more precise interpretation. When prompted by the AI analyzer to reevaluate in this study, if one or two pathologists revised their initial judgments, corrections were made in two-thirds or more of the original interpretations. This implies the AI analyzer's capacity to aid pathologists as a ‘second-reader’ in harmonizing judgments that may diverge due to over- or underestimations [ 39 ]. However, when all three pathologists were requested to reevaluate by the AI analyzer in 102 cases, the correction rate of their initial assessments decreased to less than one-third (29.4%), compared to the correction rate of 67.5% (54 out of 80 cases) when only one pathologist was revisited. This may indicate situations with inaccurate tissue segmentation (e.g., misclassifying CIS as CA or mistaking a normal duct for CA). Given that this AI analyzer was developed from a training set with specimens consisting predominantly of CA, this issue can be addressed by expanding its training to include samples from other tissue types, especially CIS, which is in progress.

This study has several limitations. First, even with the collection of consecutive cases over years from a university hospital, the potential for selection bias must be acknowledged. Second, the scope of validation of the AI analyzer was primarily confined to enhancing the concordance of pathologist interpretation. A clinical validation, such as gauging the AI analyzer's impact on patients' survival outcomes, has yet to be performed. Third, in actual clinical practice, HER2-equivocal (2+) has a final evaluation of HER2 expression by the fluorescence in situ hybridization (FISH) test, which was not available in this study due to the limited number of cases with test results. Lastly, the external validation of the analyzer relied on a dataset from a single institution and was reviewed by a limited number of pathologists. To ensure effective integration of an AI analyzer in clinical practice, comprehensive validation is essential. This should include testing with diverse external cohorts and conducting ring studies that involve a larger number of cases and pathologists [ 40 ].

Despite the aforementioned limitations, our study has several strengths. First and foremost, the statuses of HER2, ER, and PR were concurrently evaluated within a consecutive cohort of cases. Moreover, concordance arose from the interpretations of multiple pathologists from several institutions, which emulates real-world practice. Notably, the AI analyzer for ER and PR was effective even when the antibodies used differed between model training and validation phases which supports the robustness of the analyzer as it can generalize across different antibodies.

In conclusion, we reported that pathologists' use of AI analyzers to assess HER2, ER, and PR status as an important characterization of breast cancer molecular subtypes improved the agreement of pathologists across IHC stains and thus molecular subtypes of breast cancer. Notably, this AI-assisted increase in concordance was more pronounced for low positive IHC cases with initial relatively low interpathologist agreement. The promise of AI-driven image analysis on precision oncology seen in this study will require further prospective investigation to validate possible real-world clinical impact.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author for academic purposes upon request. The software was developed using Python programming language (version 3.9). The models are implemented using PyTorch v1.7.1 (available at https://github.com/pytorch/pytorch ). The cell detection model and the tissue segmentation model are based on a proprietary implementation of DeepLabv3+ (open-source implementations available online, e.g., at https://github.com/VainF/DeepLabV3Plus-Pytorch ), with a ResNet-34 and ResNet-101 backbone architectures (open-source implementation available at https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py ). The data augmentation transformations and image manipulation routines are implemented using TorchVision v0.8.2 ( https://github.com/pytorch/vision ), Albumentations v1.2.1 ( https://github.com/albumentations-team/albumentations ), OpenCV Python v4.6.0.66 ( https://github.com/opencv/opencv-python ), and Scikit-image v0.19.3 ( https://github.com/scikit-image/scikit-image ). Mathematical and statistical operations are implemented using Numpy v1.23.1 ( https://github.com/numpy/numpy ), Pandas v1.4.3 ( https://github.com/pandas-dev/pandas ), Scipy v1.9.0 ( https://github.com/scipy/scipy ), and Scikit-learn v1.1.1 ( https://github.com/scikit-learn/scikit-learn ). Finally, the WSIs were read and manipulated using OpenSlide v3.4.1 ( https://github.com/openslide/openslide ) and the corresponding Python wrapper v1.2.0 ( https://github.com/openslide/openslide-python ). For any questions regarding the replication of results, the corresponding author can be contacted.

Abbreviations

Antibody–drug conjugate

Artificial intelligence

American Joint Committee on Cancer

The American Society of Clinical Oncology

Cancer area

College of American Pathologists

Carcinoma in situ

Deep learning

Estrogen receptor

Human epidermal growth factor receptor 2

Immunohistochemistry

Intersection over union

In situ hybridization

Pathologist 1

Pathologist 2

Pathologist 3

Programmed death ligand 1

Progesterone receptor

Regions of interest

Triple-negative breast cancer

Whole-slide image

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Acknowledgements

This work was supported by Lunit, which was involved in the study design, data collection, analysis, and interpretation.

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2022R1A2C1010536).

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Minsun Jung and Seung Geun Song contributed equally to this work.

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Department of Pathology, Yonsei University College of Medicine, Seoul, Republic of Korea

Minsun Jung

Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea

Seung Geun Song

Lunit, Seoul, Republic of Korea

Soo Ick Cho, Sangwon Shin, Taebum Lee, Wonkyung Jung, Hajin Lee, Jiyoung Park, Sanghoon Song, Gahee Park, Heon Song, Seonwook Park, Jinhee Lee, Mingu Kang, Jongchan Park, Sergio Pereira, Donggeun Yoo, Keunhyung Chung & Siraj M. Ali

Department of Pathology, Kyung Hee University Hospital, Kyung Hee University College of Medicine, Seoul, Republic of Korea

So-Woon Kim

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MJ, SGS, SIC, and S-WK conceptualized the study. HL, JP, and S-WK contributed to the data acquisition. TL, WJ, and HL contributed to the quality control of data and algorithms. HS, SP, JL, MK, JP, SP, DY, and KC developed algorithms. MJ, SGS, SS, GP, and S-WK performed data analysis and interpretation. SIC and SS performed statistical analyses. SIC, SS, and SA prepared an initial draft of the paper. MJ, SGS, SIC, SS, SMA, and S-WK edited the paper. All authors reviewed the final version of the paper. MJ and SGS contributed equally as co-first authors.

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Soo Ick Cho, Sangwon Shin, Taebum Lee, Wonkyung Jung, Hajin Lee, Jiyoung Park, Sanghoon Song, Gahee Park, Heon Song, Seonwook Park, Jinhee Lee, Mingu Kang, Jongchan Park, Sergio Pereira, Donggeun Yoo, Keunhyung Chung, and Siraj M. Ali are employees of Lunit and/or have stock/stock options in Lunit.

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Jung, M., Song, S.G., Cho, S.I. et al. Augmented interpretation of HER2, ER, and PR in breast cancer by artificial intelligence analyzer: enhancing interobserver agreement through a reader study of 201 cases. Breast Cancer Res 26 , 31 (2024). https://doi.org/10.1186/s13058-024-01784-y

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  • Artificial intelligence (AI)
  • Breast cancer
  • Concordance
  • Digital pathology
  • Estrogen receptor (ER)
  • Human epidermal growth factor receptor 2 (HER2)
  • Progesterone receptor (PR)
  • Whole-slide image (WSI)

Breast Cancer Research

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