mark rubinstein phd

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Mark P. Rubinstein, Ph.D.

There are three broad research focuses: 

Immune checkpoint inhibitors

Administration of immune checkpoint inhibitors have demonstrated unprecedented efficacy in the treatment of select cancers.  Immune checkpoint inhibitors act by removing tumor inhibitory signals that would otherwise prevent immune cells from killing tumor cells. While some patients can achieve long-term tumor regression, a major hurdle in the field is understanding why some cancers, and why some patients, do not respond to checkpoint therapy.  The Rubinstein laboratory is focused on 1) developing methods to improve checkpoint therapy, 2) identifying biomarkers to predict which patients will respond, and 3) uncovering mechanisms by which patients achieve clinical responses after checkpoint therapy.

Adoptive cellular therapy

The transfer of tumor-killing immune cells has shown great promise in certain cancers refractory to other therapies.   The Rubinstein laboratory is developing novel techniques for improving these adoptive cell therapy strategies. For example, many clinical strategies use chemotherapy or radiation prior to adoptive cell therapy with the goal of making room for the donor cells. The Rubinstein laboratory is developing methodology to avoid the need for these harsh and toxic therapies while retaining the ability to mediate durable tumor regression.  The development of these adoptive cellular therapy strategies is being done in collaboration with the Center for Cellular Therapy.

Understanding tumor-induced immune suppression

One problem in applying immune-based approaches for the treatment of cancer is that the tumor cells often suppress immune responses. Thus, inducing an effective immune response may require either reversing suppression or making immune cells resistant to suppression. To study these suppressive pathways, the Rubinstein laboratory is assaying tumor biopsies from patients.  Understanding these immune suppressive pathways will facilitate the development of new therapeutic strategies.

Selected recent publications:

ALT-803, an IL-15 superagonist, in combination withnivolumab in patients with metastatic non-small cell lung cancer: anon-randomised, open-label, phase 1b trial. (Lancet Oncology, 2018)

IL-2 and Beyond in Cancer Immunotherapy (Journal ofInterferon and Cytokine Research, 2018)

Enhanced Lymphodepletion Is Insufficient to ReplaceExogenous IL2 or IL15 Therapy in Augmenting the Efficacy of AdoptivelyTransferred Effector CD8+ T Cells. (Cancer Research, 2018)

IL-2Rα mediates temporal regulation of IL-2 signaling andenhances immunotherapy (Science Translational Medicine, 2015)

View Scopus Profile

Mark Rubinstein

Associate Professor

• Comprehensive Cancer Center
• Comprehensive Cancer Center - Experimental Therapeutics
• Internal Medicine
• Internal Medicine - Medical Oncology
• 4663 Citations

Research activity per year

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• 1 Similar Profiles
• T-Lymphocytes Medicine & Life Sciences 100%
• Interleukin-15 Medicine & Life Sciences 94%
• Neoplasms Medicine & Life Sciences 46%
• Immunotherapy Medicine & Life Sciences 43%
• Interleukin-2 Medicine & Life Sciences 38%
• Interleukin-12 Medicine & Life Sciences 31%
• ALT-803 Medicine & Life Sciences 27%
• Immunity Medicine & Life Sciences 25%

Collaborations and top research areas from the last five years

Dive into details.

Select a country/territory to view shared publications and projects

Projects per year

Defining the role of tumoral MHC Class I Expression in Mediating Colorectal Cancer Racial Disparities

Rubinstein, M. & Camp, E. R.

National Cancer Institute

08/1/23 → 07/31/24

Project : Research

• Colorectal Neoplasms 100%
• African Continental Ancestry Group 84%
• African Americans 81%
• T-Lymphocytes 48%
• European Continental Ancestry Group 33%

Lymphocyte and inflammatory cytokine markers of response in the first-in-human combination of anti-PD-1 mAb and IL-15/IL-15Ra complexes and investigation of mediators of anti-tumor immune responses

Wrangle, J. & Rubinstein, M.

04/1/19 → 03/31/24

• Interleukin-15 100%
• Mediator Complex 89%
• ALT-803 70%
• Lymphocytes 47%
• Cytokines 44%

Maximizing Memory T Cell Responses by Matured Post Chemotherapy Dendritic Cells

Rubinstein, M.

03/1/10 → 02/28/13

• Dendritic Cells 100%
• T-Lymphocytes 76%
• Drug Therapy 64%
• Neoplasms 46%
• Poly I-C 36%

Research output

• 10 Review article
• 6 Short survey
• 2 Comment/debate
• 1 Editorial

Research output per year

Brief research report: impact of vaccination on antibody responses and mortality from severe COVID-19

Research output : Contribution to journal › Article › peer-review

• Antibody Formation 100%
• Vaccination 89%
• Mortality 56%
• Severe Acute Respiratory Syndrome 42%
• Coronavirus 32%

mRNA vaccines against SARS-CoV-2 induce divergent antigen-specific T-cell responses in patients with lung cancer

• Severe Acute Respiratory Syndrome 100%
• Coronavirus 97%
• Lung Neoplasms 61%
• Vaccines 58%
• Antigens 49%

Emerging Trends in Immunotherapy for Adult Sarcomas

Research output : Contribution to journal › Review article › peer-review

• Sarcoma 100%
• Immunotherapy 93%
• Tumor Microenvironment 27%
• Cell- and Tissue-Based Therapy 12%
• Therapeutics 10%

Increased COVID-19 Mortality and Deficient SARS-CoV-2 Immune Response Are Not Associated with Higher Levels of Endemic Coronavirus Antibodies

• Common Cold 56%
• Antibodies 42%
• Mortality 39%

PD-1-Targeted Immunotherapy: The Ligand Matters

Research output : Contribution to journal › Comment/debate

Watch Now : CRI’s Patient Immunotherapy Summit

Mark P. Rubinstein, PhD, CLIP Investigator

Medical University of South Carolina

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Dr. Zihai Li’s lifelong mission: To unlock the promise of immunotherapy for cancer patients

Zihai Li, MD, PhD, has witnessed cancer “melting away” thanks to the promise of an unfolding therapy that harnesses the body’s own defenses to target and kill cancer cells.

Contributing Writer Ohio State Wexner Medical Center

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As he consulted bedside with his patient, a young and active man with a passion for cycling, Zihai Li, MD, PhD , knew there was little he could do.

The year was 1999, and the patient was fighting stage 4 melanoma. The only medicine that Li and his team were able to offer was for pain; they could not attack the deadly skin cancer.

Fast-forward 10 years. Another young patient with advanced melanoma was in Li’s care. But this time, an emerging treatment known as immunotherapy — a biological therapy that boosts the body’s natural defenses — was identified as a viable option.

The results weren’t just effective, they were transformative.

“Her cancer melted away,” Li says.

Ten years later, incredible outcomes following immunotherapy are happening far more frequently for cancer patients. These discoveries are the inspiration for the newly formed Pelotonia Institute for Immuno-Oncology (PIIO) , a progressive effort dedicated to collaborative cancer research focused on promoting immunotherapy discovery, at The Ohio State University Comprehensive Cancer Center – Arthur G. James Cancer Hospital and Richard J. Solove Research Institute ( OSUCCC – James ).

Li, a medical oncologist and immunologist who holds the the Klotz Chair in Cancer Research at The Ohio State College of Medicine , became the institute’s founding director in July 2019. There is continued progress in this field, Li says, and it’s a message he’s taking on the road.

As a rider in Pelotonia , the annual grassroots cycling event that funds cancer research at Ohio State and serves as the namesake of the PIIO, Li still recalls the excitement among participants and roadside spectators about immunotherapy during the 2019 event that announced his arrival at Ohio State. It’s a job with big implications for cancer care, and one he doesn’t take lightly.

“You can accomplish more through collaboration than you can through individual efforts,” Li says.

By providing a collaborative environment for over 100 Ohio State University scientists who work in immuno-oncology, Li and the PIIO share a critical mission: to accelerate the development of innovative and effective immunotherapeutics to fight, prevent and reduce the devastating effects of cancer.

Unlocking the codes of cancer

Just as the human body can be trained to endure the physical demands of a long bike ride, it can also “learn” how to engage in cancer-fighting capabilities by leveraging the existing power of the immune system — a concept known as immunotherapy.

“Our bodies are hardwired to deal with infections,” Li says. “Using immunotherapy, we can ‘turn on’ the immune system to fight cancer.”

Flipping that “switch” comes in several forms, including immune checkpoint blockers that take away the brakes of the immune system (such as PD-1 or PD-L1, and CTLA-4), to re-energize the immune system to attack only cancerous cells. Think of it like applying weed killer to a garden; the flowers aren’t affected.

Also promising are cellular adoptive immunotherapies that involve re-engineering a patient’s own blood and infusing it back into the body to target and kill cancer cells. (The OSUCCC – James was one of the first hospitals in the United States to administer this futuristic treatment, which is called CAR T-cell therapy .)

Other efforts include preventive vaccines against diseases that can cause cancer (such as HPV and hepatitis B) and ongoing research to develop effective vaccines that might be administered after a cancer diagnosis.

Advancing these and other immunotherapy breakthroughs are a priority for Li and his team, who represent a spectrum of scientific disciplines.

“It’s daunting and exciting,” Li says. “We have the support, the passion and the conviction to make a difference.”

Personalized treatment, shared progress

Immunotherapy can be more precise and more effective than other treatments for some people diagnosed with melanoma, kidney, liver, lung and other cancers, Li says, and it may prompt fewer side effects.

“But we have not won the war yet,” he adds.

No two people are alike, after all, so a growing body of research and complex patient data is helping doctors and researchers determine the ideal approach for each individual — and to identify how immunotherapy can combat more types of cancer.

By analyzing data from clinical trials and electronic medical records, among other sources, the PIIO and other centers are developing new and stronger models to put findings into real-life practice.

Li is encouraged by the progress, but he says immunotherapy’s current overall success rate is far too low.

Nevertheless, “that gives us hope,” he says. “That means it’s possible.”

This hope underscores the efforts by Li and other PIIO researchers to study the effectiveness of combining different immunotherapies with cancer-centric strategies such as surgery, chemotherapy and radiation. (This field of study, as seen in the institute’s namesake, is known as immuno-oncology [IO]).

To further move the needle in the IO field, the PIIO aims to open 130 or more clinical trials over the next five years to create a strong pipeline of cancer therapeutics rooted in Ohio State research that could one day guide widespread clinical application.

“Identifying how the immune system can go wrong can help us develop therapies that correct those errors and deliver effective immunotherapy to more patients,” Li says.

Dr. Zihai Li answers your immuno-oncology and immunotherapy questions

A lifelong passion for healing

Li was raised in a rural area of central China during a time when health care infrastructure “wasn’t good,” he says. As a teenager, Li was a voracious reader with an interest in science and medicine, and was fascinated by the transformative power of vaccines.

“It became very clear to me that prevention was the key, an economic path toward a healthy population,” Li says. “Seeing the massive vaccination effort in China in the 1960s and ’70s, it was amazing to me that we could eliminate diseases like measles and smallpox. It was always my dream to do something like that.”

By the time Li entered medical school at Zengzhou University in 1979, researchers were broadening their outlook about vaccines.

“People began to wonder: If we can use vaccination to eradicate some infectious diseases, can we do this for cancer?” Li says.

During his medical training, Li focused special effort on understanding the complexity and nuance of the immune system, later pursuing graduate studies in immunology in China, and then in the United States for a doctorate in cancer immunology. Robust clinical and laboratory experience gave Li deep insights into how cancer breakthroughs are developed and how these can transform the lives of patients who receive them.

During his tenure as leader of the Cancer Immunology Program at the Hollings Cancer Center at the Medical University of South Carolina, Li saw the evolution firsthand — both in the field of immunology and among his own patients.

His leadership and passion forged strong collaborative relationships, including with Mark Rubinstein, PhD, who was a colleague of Li and a member of the Cancer Immunology Program in South Carolina. Li recruited Rubinstein to Ohio State in 2021 as an associate professor in the Division of Medical Oncology and as the leader of the Priority Research Program in the PIIO.

Rubinstein says his decision to come to Ohio State was inspired by his relationship with Li, whom he describes as a natural leader who approaches challenges from all angles.

“Not only does Zihai run a laboratory doing amazing and transformative cancer research, he also leads cutting-edge clinical trials that translate findings from the laboratory into the clinic,” Rubinstein says. “Furthermore, he is leading an effort to identify and recruit a diverse group of cancer immunotherapy scientists from all over the world to create a leading institute studying IO.

“By creating an environment where researchers can interact and thrive intellectually, Zihai is building an immuno-oncology program that will lead to extraordinary discoveries and advances that will fundamentally improve treatment for cancer patients everywhere.” 

Attacking cancer from all angles

The PIIO’s ultimate goal is curing cancer with immunotherapy. To accomplish this goal, the institute focuses on two interconnected research centers:

• Systems IO , which seeks a holistic understanding of cellular and molecular circuitry of the immune system to create more efficient and effective immunological tools to fight cancer and better understand the relationship between cancer genomics and immune evasion.
• Translational IO , which works to turn discoveries into new or improved cancer treatments and broaden the indications and patient populations that can be treated with cell therapy, immune checkpoint blockers and other combination strategies.

Read how Ohio State researcher, Yiping Yang, MD, PhD, is turning cancer patients’ own blood into a cancer-fighting weapon

These centers are supported by the PIIO’s Immune Monitoring and Discovery Platform (IMDP), which provides a 360-degree view of the immune system response during treatment with IO agents. The centers are also supported by the PIIO’s Immuno-Informatics Group, which uses big data and quantitative science to improve IO research.

“We’re building an amazing IO database to bring everything together, including clinical data, molecular data and patient outcomes,” Li says, citing the work of Ohio State engineers and computer scientists as another example of strong collaboration within the PIIO.

“It’s cutting edge and I’m very proud,” Li says.

Still, the momentum following Li’s summer 2019 arrival at Ohio State — and his inaugural Pelotonia ride — was soon countered by an unforeseen challenge: the COVID-19 pandemic.

Li doesn’t view the public health emergency as a deterrent to his mission. In fact, he felt it underscored the importance of discovery in the field of IO.

“It provided a sense of urgency, more than anything else,” he says, noting that PIIO staff took protective measures to safely continue their on-site research, which expanded in scope to examine how COVID-19 impacts the immune system of cancer patients.

This study was particularly valuable due to the lack of peer-reviewed data on how cancer therapy affects the efficacy of the COVID-19 mRNA vaccine in cancer patients. (Cancer patients on active therapy are often excluded from vaccine trials.) It’s also a prime example of how quickly and adeptly the PIIO can pivot and leverage its expertise and resources in unforeseen circumstances.

“COVID-19 actually highlighted the importance of our immune system and the knowledge of how it works — how we can turn things off for the benefit of human health,” Li says. 

Navigating the road ahead

Groundbreaking research coupled with Li’s leadership have already made the institute a strong player in cancer care.

“The PIIO has become an integral part of the James,” says David Carbone, MD, PhD, director of the Thoracic Oncology Center at the OSUCCC – James. “Zihai has a ton of energy and enthusiasm for what he’s doing. I think he’s a terrific leader for this initiative.”

Read more about Dr. Carbone’s work with immunotherapy in lung cancers

Li is modest about his influence. He prefers to use his platform to educate and excite scientists and the community about the clinical potential of immunotherapy — and to champion the need for more funding, collaboration and accessibility in this space.

Development of cell therapies, he says, is “exceptionally expensive,” and the infrastructure to develop and deploy these treatments affordably remains a significant challenge for universities, governments and the pharmaceutical industry. Combined with the many missing pieces still present in the field, IO researchers will face many hurdles.

However, Li and his colleagues in the PIIO see these hurdles as motivation. And just as he witnessed while pedaling across central Ohio, the race has implications for everyone.

“We recognize our obligation to do something as important as immunotherapy because many of us believe it really holds the key to curing cancer,” Li says. “This requires everyone to work together to tackle this disease in a fundamentally different way.”

Learn more about how the Pelotonia Institute for Immuno-Oncology is transforming cancer care from prevention through treatment and survivorship.

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Prof. Emeritus Mark Rubinstein

Mark Rubinstein , a finance professor emeritus whose work had a profound impact on Wall Street by forever changing how financial assets are created and priced, died May 9 in Tiburon, California. He was 74.

Rubinstein was best known for his contributions in options pricing as well as the development of the first exchange-traded fund. A quintessential Renaissance man, his intellectual curiosity led him to acquire an impressive knowledge of Shakespeare as well as ancient Greek and Roman history.

After earning a bachelor’s degree at Harvard, an MBA at Stanford, and a PhD at UCLA, Rubinstein joined the Haas faculty in 1972.

His research efforts focused on options markets, which had just begun trading in Chicago. In 1979, working with John Cox and Stephen Ross of MIT, he developed the Cox-Ross-Rubinstein Model for valuing a wide range of complex options. The model contributed to the growth of derivatives around the world and remains one of the most important valuation tools on Wall Street. A subsequent book, Options Markets (with John Cox), made option-pricing theory accessible to a broad audience.

In 1981, Rubinstein joined with Haas Prof. Emeritus Hayne Leland and Haas Adjunct Prof. John O’Brien to form Leland O’Brien Rubinstein (LOR). The firm grew rapidly, and in 1987 the three founders were named among Fortune’s Businessmen of the Year. LOR developed a risk-hedging algorithm called “portfolio insurance,” the strategies of which are still used by traders today.

LOR then pioneered the SuperTrust, an S&P 500-based fund that traded as a single security—which in 1992 became the first exchange-traded fund (ETF) in the U.S. ETFs helped form the regulatory framework for what has become arguably the most important financial innovation in the last quarter century. In the years since, ETF assets have grown to more than $5 trillion globally.

In 2001, Rubinstein helped to found the Berkeley Haas Master of Financial Engineering Program, which was the first such program in a U.S. business school and is consistently ranked #1. After his retirement, he wrote about classical Greece, Rome, and the early history of Christianity.

IN MEMORIAM LIST

Jessie Shew, BS 40 Harold Jow, BS 41 Jane Galvan, BS 46 Donald McNary, BS 46 Kenneth Booth, BS 47 Kenneth Ashcraft, BS 48 John Daniels, BS 48 Leslie Foppiano, BS 48 Floyd Pickett, BS 49 Tetsushi Uratsu, BS 49 George Armstrong, BS 50 Allan Buchanan, BS 50 Yutaka Kobori, BS 50 Kenneth Murray, BS 50 Augie Ong, BS 50 Allen Blanc, BS 51 Arnold Brown, BS 51 Don Deming, BS 51 Sydney Hammill, BS 51, MBA 54 John Vohs, BS 51 Savino Cavaliere, BS 52 George Spence, BS 52 Theodore Mah, MBA 52 Ronald Britting, BS 54 Henry Angerbauer, BS 55 Donn Bearden, BS 55 Alan Ghidossi, BS 55 Stanley Loeb, BS 55 Marian Vantress, BS 56 Robert Bishop, BS 57 James Johnson, BS 57 John Vanderveen, BS 57 Donald Hill, MBA 57 William Awbrey, BS 58 Robert Beatty, BS 58, MBA 59 Alan Holloway, BS 58 Whitney Newton, BS 58 Joseph Ryan, BS 58 Paul Cooper, BS 59 Joseph Innis, BS 59 Daniel Moore, BS 59 Glenn Quick, BS 59 Robert Brodie, BS 60, MBA 62 Robert Ehrhart, BS 60 Ernest Lee, BS 60 David Peterson, BS 60 Lawrence Broeren, MBA 60 Robert Mayer, BS 61 Wilmer Post, MBA 62 Johann Koo, MBA 64 Arthur Stonehill, PhD 65 Ury Beary, BS 66 John Fox, BS 66 Erle Winkler, BS 66 Robert Crandall, vMBA 66, PhD 68 William Balamuth, BS 67 John Kjellman, MBA 67 James Pellissier, BS 69, MBA 70 Garth Johnson, MBA 70 Stephen Yee, BS 71 Douglas Wholey, MBA 79, PhD 84 Gregory Martin, BS 82 Helen Andritsakis, BS 84 Kristi Kali Berquist, MBA 95 Carolyn Carlson, Friend William Cole, Friend Dennes Coombs, Friend Charles Goldberg, Friend James Love, Friend Denny McLeod, Friend Earle Pendarvis, Friend Dorothy Sanderson, Friend James Williams, Friend

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Mark Rubinstein, who forever changed Wall Street, dies at 74

Mark Rubinstein, a finance professor emeritus whose work had a profound impact on Wall Street by forever changing how financial assets are created and priced, died May 9 in Tiburon, California. He was 74.

Rubinstein, who retired in 2012 after nearly 40 years on the University of California, Berkeley’s Haas School of Business faculty, was a pioneer in applying mathematical tools to financial markets. He was best known for his contributions in options pricing, as well as the development of the first Exchange Traded Fund (ETF).

Prof. Mark Rubinstein surrounded by his beloved Shakespeare in his home library in 2002 (Berkeley Haas photo)

Rubinstein was intellectually fearless and known by his students as a sincere mentor who had extraordinary passion. He was also a quintessential Renaissance man whose curiosity and love of learning led him to acquire an impressive knowledge of Shakespeare, Ancient Greek, and Roman history.

"Mark was unusually honest and open-minded,” said Prof. Terry Odean, a colleague in the Haas Finance Group. "He was one of the few people I’ve known who would actually change his opinion when confronted with new facts or a better argument."

Simplified options pricing

Rubinstein grew up in Seattle, the son of Sam and Gladys Rubinstein. After earning a bachelor’s degree at Harvard, an MBA at Stanford, and a PhD at UCLA, Rubinstein joined the Haas faculty in 1972.

His research efforts soon focused on options markets, which had just begun trading in Chicago. In 1979, working with John Cox and Stephen Ross of MIT, he developed the Cox-Ross-Rubinstein (CRR) Model, a "binomial" model for valuing a wide range of complex options. The model contributed to the growth of derivatives around the world and remains one of the most important valuation tools on Wall Street. A subsequent book, Options Markets (with John Cox), made option pricing theory accessible to a broad audience.

"His most famous contribution was in simplifying the option pricing model not only to a level that everyone could understand, but also to a point where everyone could use it effectively in the real world," said Prof. Emeritus Hayne Leland, a finance colleague who worked closely with Rubinstein.

Leland O’Brien Rubinstein’s (LOR) influence

In 1981, Rubinstein joined with Leland and Haas Adjunct Prof. John O’Brien to form Leland O’Brien Rubinstein (LOR). The firm grew rapidly, and in 1987 the three founders were named among Fortune ’s "Businessmen of the Year." LOR developed a risk-hedging algorithm called "portfolio insurance." To stem losses, the algorithm required selling when markets declined, and portfolio insurance was accused of being a major accelerant of the October 1987 crash, when the stock market fell more than 20% in a day. These events and the role of LOR are recounted in Diana Henriques’ A First-Class Catastrophe: The Road to Black Monday, the Worst Day in Wall Street History .

The market eventually recovered, and the crash may have warded off a real recession by bringing stock prices back down to reality, according a later analysis. Traders today still use strategies that are roughly equivalent to portfolio insurance.

First Exchange Traded Fund

In an effort to protect investors without dynamic selling, LOR then pioneered the SuperTrust, an S&P 500-based fund that traded as a single security-which in 1992 became the first Exchange Traded Fund (ETF) in the United States. Rubinstein and Leland provided the economic arguments that convinced the SEC to give the first exemption to rules in the 1940 Investment Act that had prevented ETFs. These exemptions later became standard, and helped form the regulatory framework for what has arguably become the most important financial innovation in the last quarter century. In the years since, ETF funds’ assets have grown to more than $5 trillion globally.

Founded the Master of Financial Engineering Program

Rubinstein was elected President of the American Finance Association in 1992, and was named as the IAQF Financial Engineer of the Year in 1995. In 2001, he helped to found the Berkeley Haas Master of Financial Engineering (MFE) Program, which was the first such program in a U.S. business school and is consistently ranked #1.

MFE Program Executive Director Linda Kreitzman called Rubinstein a giant in his field. "He had a huge impact on our students’ lives and also our alumni. He was a brilliant, kind person and he’ll be deeply missed."

An avid student of history, Rubinstein examined the development of modern theories of investment in his 2006 book,  A History of the Theory of Investments:  My Annotated Bibliography . He continued his academic research and mentoring of doctoral students at Berkeley throughout his career, and after his retirement, continued to nurture his intellectual curiosity with research and writing on classical Greece, Rome, and the early history of Christianity.

Rubinstein is survived and dearly missed by his wife Diane, and his children Judd and Maisie.

A memorial service will be held at 1:30 p.m. on Sunday, June 9 at Fernwood Mortuary, 301 Tennessee Valley Rd., Mill Valley.

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Mark P. Rubinstein, Ph.D.

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Ph.D. awarded from the Medical University of South Carolina - 2002 Postdoctoral Fellowships - Scripps Research Institute and University of California, San Diego - 2003-2008

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Immunotherapy: Programming Your Immune System to Target Cancer Cells

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Data analyses, e-cigarette use behaviors, presence and comparison of vocs, associations between vocs and e-cigarette use, type of product, conclusions, acknowledgments, adolescent exposure to toxic volatile organic chemicals from e-cigarettes.

POTENTIAL CONFLICT OF INTEREST: Dr Benowitz is a consultant to several pharmaceutical companies that market medications to aid smoking cessation and has served as a paid expert witness in litigation against tobacco companies. Drs Ramo and Rubinstein have consulted for Carrot Inc, which makes a tobacco cessation device; and Dr Delucchi has indicated he has no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURE: Dr Benowitz is a consultant to several pharmaceutical companies that market medications to aid smoking cessation and has served as a paid expert witness in litigation against tobacco companies. Drs Ramo and Rubinstein have consulted for Carrot Inc, which makes a tobacco cessation device; and Dr Delucchi has indicated he has no financial relationships relevant to this article to disclose.

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Mark L. Rubinstein , Kevin Delucchi , Neal L. Benowitz , Danielle E. Ramo; Adolescent Exposure to Toxic Volatile Organic Chemicals From E-Cigarettes. Pediatrics April 2018; 141 (4): e20173557. 10.1542/peds.2017-3557

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There is an urgent need to understand the safety of e-cigarettes with adolescents. We sought to identify the presence of chemical toxicants associated with e-cigarette use among adolescents.

Adolescent e-cigarette users (≥1 use within the past 30 days, ≥10 lifetime e-cigarette use episodes) were divided into e-cigarette–only users (no cigarettes in the past 30 days, urine 4-[methylnitrosamino]-1-[3-pyridyl]-1-butanol [NNAL] level <1 pg/mL of creatinine; n = 67), dual users (use of cigarettes in the past 30 days in addition to e-cigarettes, NNAL level >30 pg/mL; n = 16), and never-using controls ( N = 20). Saliva was collected within 24 hours of the last e-cigarette use for analysis of cotinine and urine for analysis of NNAL and levels of 8 volatile organic chemical compounds. Bivariate analyses compared e-cigarette–only users with dual users, and regression analyses compared e-cigarette–only users with dual users and controls on levels of toxicants.

The participants were 16.4 years old on average. Urine excretion of metabolites of benzene, ethylene oxide, acrylonitrile, acrolein, and acrylamide was significantly higher in dual users versus e-cigarette–only users (all P < .05). Excretion of metabolites of acrylonitrile, acrolein, propylene oxide, acrylamide, and crotonaldehyde were significantly higher in e-cigarette–only users compared with controls (all P < .05).

Although e-cigarette vapor may be less hazardous than tobacco smoke, our findings can be used to challenge the idea that e-cigarette vapor is safe, because many of the volatile organic compounds we identified are carcinogenic. Messaging to teenagers should include warnings about the potential risk from toxic exposure to carcinogenic compounds generated by these products.

The presence of harmful ingredients in electronic cigarette vapor has been established.

We have demonstrated that at least 5 potentially harmful toxicants are found in the body of human adolescents who use electronic cigarettes.

Electronic cigarettes (e-cigarettes) are marketed to promote smoking cessation or reduced cigarette smoking in adults. 1 However, social influence and marketing strategies for these products have clearly had an effect on children as well, because more teenagers now use e-cigarettes than traditional cigarettes. 2 In 2016, e-cigarette use in the past 30 days among 10th-graders was more than twice that of cigarette use (11.0% vs 4.9%). 3 Reasons for the dramatic increase in adolescent e-cigarette use include peer influence, enticing flavors, 4 and extensive marketing presenting e-cigarettes as safer. 5 , 6 Common messages found on product Web sites are that e-cigarettes do not produce the same cancer-causing agents as traditional cigarettes. 1  

Despite advertising claims, there is uncertainty about the safety of e-cigarettes. By using aerosolized nicotine rather than combusting tobacco, e-cigarettes do produce fewer toxins than smoking cigarettes. 7 However, e-cigarettes contain additives and solvents, including propylene glycol and/or glycerol, which can form carcinogenic compounds when heated. 8 , – 11 These and other toxic chemicals 12 may be inhaled through the vapor produced. Although there is some controversy on how use patterns may affect exposure, some data from adults reveal that these toxicants can be detected in the urine of e-cigarette users. 13 , 14 Importantly, these studies did not exclude participants with a possible exposure to secondhand smoke.

To our knowledge, there are no data on toxicant exposure in adolescent e-cigarette users. However, there is great concern because exposure to toxicants during adolescence may result in greater harm than exposure in adulthood, given vulnerability to the acute and chronic effects of toxicants in general and from their cumulative exposure if started early. 15  

Given the rapid uptake of e-cigarettes among teenagers, there is an urgent need to understand the safety of these products in adolescents, including how use contributes to toxicant exposure. In this study, we sought to assess in adolescents the presence of certain carcinogenic toxicants linked to e-cigarette use and examine how specific behavioral patterns of use may influence exposure to toxicants.

As part of an ongoing longitudinal study of the effects of e-cigarettes on adolescents, adolescent (aged 13–18 years) e-cigarette users (used an e-cigarette product on ≥1 day in the past 30 days and had at least 10 lifetime use episodes) were recruited from the San Francisco Bay area by using fliers and online advertising. The research design and procedures were reviewed and approved by the University of California Institutional Review Board.

To capture nicotine exposure and investigate the presence of toxicants, participants were instructed to schedule their baseline appointments in temporal proximity (ie, past 24 hours) to use of their e-cigarettes. Adolescents were never pressured or instructed to use e-cigarettes, and in the cases in which no use occurred, appointments were rescheduled. After signing consents, participants completed a baseline survey including questions about demographics and e-cigarette use behaviors. Participants then provided saliva samples for cotinine measurement and urine for the measurement of the tobacco-specific nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) and levels of metabolites of 8 volatile organic compounds (VOCs). Participants received $30.

Specimens were also collected from 20 age-matched control adolescents attending pediatric clinics at a Bay area public hospital with undetectable cotinine and NNAL, confirming no e-cigarette or nicotine use. These adolescents were part of another study on secondhand smoke exposure for which urine was collected and analyzed for NNAL and cotinine.

Saliva and urine samples were analyzed at the Clinical Pharmacology Laboratory at the University of California, San Francisco. Salivary specimens were analyzed for cotinine, the main proximate metabolite of nicotine, by using liquid chromatography–tandem mass spectrometry. 16 , 17 Urine was analyzed for NNAL, a metabolite of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone, a tobacco-specific nitrosamine that is a potent carcinogen, 13 , 18 by liquid chromatography–tandem mass spectrometry. 18 This was done as an adjunct to self-reported tobacco smoking and to rule out significant secondhand tobacco smoke exposure (or exposure from marijuana blunts), because NNAL is detectable in urine for 6 to 12 weeks after exposure. 19 Urine was analyzed for metabolites of a panel of 8 VOCs that are toxic environmental or tobacco smoke constituents, including benzene (phenylmercapturic acid [PMA]), 1,3-butadiene (4-hydroxy-2-buten-1-yl-mercapturic acid), ethylene oxide (2-hydroxyethylmercapturic acid [HEMA]), acrylonitrile (2-cyanoethylmercapturic acid [CNEMA]), acrolein (3-hydroxypropylmercapturic acid [3-HPMA]), propylene oxide (2-hydroxypropylmercapturic acid [2-HPMA]), acrylamide (2-carbamoylethylmercapturic acid [AAMA]), and crotonaldehyde (3-hydroxy-1-methyl-propylmercapturic acid [HMPMA]). 20 Both NNAL and VOC concentrations were normalized for creatinine. 21  

Demographic, E-Cigarette, and Smoking Characteristics

Demographic variables included race and/or ethnicity, sex, and age. Individuals who identified as Hispanic were classified as such, regardless of race. A measure of e-cigarette use was designed for this study that included the time of last use (used to calculate hours since last use), frequency of use (days used in the past month), quantity of use (average sessions per day on using days, calculated by asking how many times they used their devices on each weekday and weekend day and then dividing by 7), usual number of puffs per session in 4 categories (1–4, 5–10, 10–15, or >15), length of each session in 4 categories (1–2, 3–5, 6–10, or >10 minutes), main type of e-cigarette used in 4 categories (vape pen, modified, Juul, other), whether e-cigarettes contained nicotine (always, sometimes, unsure, or never), and the flavors consumed in the past month (fruit, candy, menthol, or tobacco; yes or no). Tobacco use was assessed by asking if participants smoked a cigarette in the past 30 days (yes or no).

Three categories were developed on the basis of the combination of reported e-cigarette and cigarette use and urine NNAL levels. E-cigarette–only users had used no traditional combustion cigarettes in the past 30 days and had levels of urine NNAL <1 pg/mL of creatinine. We used 1 pg per milliliter of creatinine to exclude smokers on the basis of our data to distinguish adolescents who were smokers from those who were nonsmokers in San Francisco. 22 Values between 0 and 1 pg/mg indicate no recent active smoking and either past smoking or light secondhand smoke exposure, neither of which would be expected to substantially increase VOC exposure. Dual users reported use of traditional cigarettes in the past 30 days in addition to e-cigarettes and had to have NNAL levels >30 pg/mL of creatinine. We chose a cutoff of 30 pg/mL of creatinine to ensure primary exposure to combusted tobacco. To ensure no exposure to combusted tobacco or nicotine from other sources (including e-cigarettes), controls had to have levels of NNAL and cotinine below the limit of quantitation (ie, 0.25 and 1 ng/mL respectively). We excluded from analyses participants who did not use an e-cigarette in the previous 24 hours because most VOCs in smokers, including those tested here, decline to baseline levels within 24 hours. 23 Finally, for the purposes of creating well-differentiated comparison groups, we also set an a priori exclusion from analyses for those participants who had intermediate levels of NNAL (ie, 1–29 pg/mL of creatinine), because the true source of exposure would be unclear. Conservative criteria for group definitions meant that the e-cigarette–only group was clearly differentiated from the dual user group, and any VOCs found in the e-cigarette–only group could be clearly attributed to e-cigarette use.

Descriptive statistics were used to characterize sociodemographic and e-cigarette use, t tests were used for continuous variables, and Pearson’s χ 2 tests were used for categorical variables. Because of skew, the nonparametric Mann–Whitney U test was used to compare the distributions on hours since last use between e-cigarette–only and dual users.

Medians were reported for cotinine, NNAL, and all 8 VOCs because of non-normal distribution. Regression models including planned covariates (sex, race and/or ethnicity) compared e-cigarette–only users (reference group) with dual users and controls on log-transformed levels of VOCs (8 models). Among e-cigarette–only users, Pearson’s r was used to calculate associations between levels of VOCs and e-cigarette use characteristics. For any models revealing significant differences in levels of VOCs between e-cigarette–only users and controls, analysis of variance was used to examine VOCs by type of product used, and t tests were used to compare VOCs by the presence or absence of flavors used in the past month.

Although we tried to eliminate exposure to blunts (tobacco mixed with marijuana) using NNAL, we could not exclude the potential contribution of VOC exposure from marijuana smoking on the day of the study. 24 Consequently, we estimated and tested regression models of log-transformed VOC values that were significant in the first set of analyses, including planned covariates (sex, race and/or ethnicity), with the additional covariate of self-reported frequency of marijuana use.

Three hundred eighty-six adolescents were screened, 229 were found to be eligible, and 180 agreed to participate. After verbally reporting use within 24 hours, 29 participants admitted on their surveys to not using an e-cigarette product in the previous 24 hours and thus were excluded from analyses. An additional 48 adolescents had levels of NNAL that might be consistent with substantial secondhand exposure or occasional cigarette smoking (ie, 1–29 pg per milligram of creatinine) and, as per our a priori criteria described above, were excluded from analyses. The final sample consisted of 67 e-cigarette–only users, 16 dual users, and 20 controls.

E-cigarette–only users reported using their e-cigarettes a mean of 12.8 days (SD = 8.9) a month compared with 25.5 days (SD = 6.6) for dual users ( P < .001) ( Table 1 ). There was no difference in time since the last use of e-cigarettes between e-cigarette–only (mean: 2:02 hours) and dual users (mean: 1:58 hours; P > .91). Among e-cigarette–only users, the level of salivary cotinine was significantly associated with both the number of days using an e-cigarette in the past 30 days ( r = 0.34; P < .01) and the mean number of use sessions a day ( r = 0.75; P < .001).

E-Cigarette Use Characteristics

N/A, not applicable.

Used an e-cigarette product in the past 24 h and had NNAL levels <1 ppm of creatinine.

Used an e-cigarette product in the past 24 h, smoked a cigarette in the past 30 d, and had NNAL levels ≥30 ppm of creatinine.

P values are the result of comparing 3 groups on age (analysis of variance), sex, and ethnicity (χ 2 ); all e-cigarette characteristics are the result of comparing e-cigarette–only use to dual-use groups ( t tests for continuous variables and χ 2 analyses for categorical variables).

The median was reported because of non-normal distribution.

Participants could select >1.

E-cigarette–only participants who reported using nicotine containing products “all” or “some” of the time had significantly higher levels of saliva cotinine compared with those who “never” used or were “unsure” if there was nicotine in their e-cigarettes (31 ng/mL [SD = 130.8] versus 0.08 ng/mL [SD = 0.38]; P < .001). E-cigarette–only participants who used nicotine in their e-cigarettes also reported using their e-cigarettes more frequently, with an average use of 15.1 (SD = 9.2) days per month compared with 7.6 (SD = 5.6) days ( P < .001) and an average of 2.5 (SD = 4.0) sessions per day on days they used versus 0.65 (SD = 0.61) sessions ( P < .01).

Urine excretion of metabolites of benzene (PMA), ethylene oxide (HEMA), acrylonitrile (CNEMA), acrolein (3-HPMA), and acrylamide (AAMA) was significantly higher in dual users versus e-cigarette–only users and controls (all P < .05; see Table 2 ; Fig 1 ). Excretion of metabolites of 5 VOCs was significantly higher in e-cigarette–only users compared with controls (all P < .05): acrylonitrile (341% higher than in controls but 327% lower than in dual users), acrolein (20% higher than in controls but 11% lower than in dual users), propylene oxide (51% higher than in controls but 8% lower than in dual users; 2-HPMA), acrylamide (30% higher than in controls but 23% lower than in dual users), and crotonaldehyde (20% higher than in controls but 7% lower than in dual users; HMPMA).

Biomarkers of Nicotine, Tobacco-Specific Nitrosamine, and Volatile Organic Toxicants in Exclusive E-Cigarette–Only Users Versus Dual Users and Controls

All comparisons were made with e-cigarette–only users as a comparison group. IQR, interquartile range; MHBMA, 4-hydroxy-2-buten-1-yl-mercapturic acid.

Used an e-cigarette product in the past 24 h and had NNAL levels <1 pg/mL of creatinine.

Used an e-cigarette product in the past 24 h, smoked a cigarette in the past 30 d, and had NNAL levels ≥30 pg/mL of creatinine.

No use of tobacco or e-cigarette in the past 30 d, with NNAL levels <1 pg/mL of creatinine and cotinine levels <1 ng/mL.

The median (IQR) was reported for cotinine, NNAL (pg/mL of creatinine), and VOCs (ng/mg of creatinine) because of non-normal distribution.

Tests were based on regression models of log-transformed values, including planned covariates (sex and race and/or ethnicity) with contrasts for e-cigarette–only users versus controls and for e-cigarette–only users versus dual users.

P < .05; ** P < .001.

Significant VOC exposure in e-cigarette–only users versus controls and e-cigarette–only users versus dual users. A, Acrolein. B, Acrylonitrile. C, Propylene oxide. D, Acrylamide. E, Crotonaldehyde. Tests were based on regression models of shifted log-transformed values, including planned covariates (sex, race and/or ethnicity), with contrasts for e-cigarette–only users versus controls and e-cigarette–only users versus dual users. All comparisons are made with e-cigarette–only users as the comparison group. * P < .05; ** P < .001.

We reran the 5 regression models used to predict the 5 log-transformed VOC values that were significant in the first set of analyses, including predictors of planned covariates (sex, race and/or ethnicity) and contrasts between e-cigarette–only users and dual users, with the additional covariate of self-reported frequency of marijuana use. In all models, group membership remained a statically significant predictor of VOC value (dual users > e-cigarette–only users), accounting for variance independent of marijuana use frequency.

Among e-cigarette–only users, levels of the 5 VOCs (ie, CNEMA, 3-HPMA, 2-HPMA, AAMA, HMPMA) that were significantly greater than the levels found in controls were not associated with time since last e-cigarette use ( P values ranged from .53 to .92). Compared with those who never used nicotine in their e-cigarettes or were unsure, participants who reported using nicotine in their e-cigarettes all or some of the time had significantly higher median levels of urinary CNEMA (1.50 vs 0.88 ng/mL creatinine; P = .05) and AAMA (71.5 vs 60.4 ng/mL creatinine, P = .05). The average number of sessions of e-cigarette use per day was associated with increased levels of CNEMA ( r = 0.36, P = .003). Days of use in the past month was not associated with any increases in urinary VOC levels ( P values raged from .21 to .72) among e-cigarette–only users.

There were no differences in levels of the 5 significant VOCs that were based on that type of product used (F test scores ranged from 0.51 to 2.3; P values ranged from .09 [for 2-HPMA] to .67). Participants who reported using fruit flavors in the past month had higher CNEMA levels than those who did not (yes: mean = 10.4 ng/mL creatinine [SD = 21.7]; no: mean 2.1 ng/mL creatinine [SD = 3.4]; P = .03). There were no differences in VOC levels among those who favored candy ( P values ranged from .33 to .87), tobacco ( P values ranged from .42 to .87), or menthol flavors ( P values ranged from .09 [for 2-HPMA] to .95) compared with those who did not.

To the best of our knowledge, this is the first study to report on the presence of VOC toxicants in adolescent e-cigarette users. Overall results reveal significantly greater toxicant exposure in adolescent e-cigarette users compared with their nonusing peers. Adolescent e-cigarette–only users had levels of 5 VOC toxicants detected in their urine in quantities up to 3 times greater than in matched controls, including metabolites of acrylonitrile, acrolein, propylene oxide, acrylamide, and crotonaldehyde. Levels of toxicant exposure in dual users were up to 3 times higher than in those who used only e-cigarettes. Post hoc analyses revealed that, among dual users, levels of VOCs were not associated with NNAL ( P values ranged from .17 to .81), suggesting that the higher VOCs were not only due to exposure to traditional cigarettes.

The presence of harmful ingredients in e-cigarette vapor has been established 25 ; we can now say that these chemicals are found in the body of human adolescents who use these products. A risk analysis of lifelong exposure to even low-level VOCs, derived using data from secondhand tobacco smoke exposure, indicated an increased cancer risk, which could be applicable to exposure in the current study. 26 Of course, this assumes that the exposures will be ongoing, which has not yet been established. It is worth noting that although e-cigarette–only users had significantly higher exposure to 5 VOCs, controls also had detectable levels of these chemicals. In fact, human exposure to VOCs from environmental sources is ubiquitous. 27 It is also worth noting that levels of VOCs detected in e-cigarette–only users were on average lower than has been reported among adults. 13 , 14 , 28 For example, using a similar methodology, Pulvers et al 14 reported the following median levels among exclusive e-cigarette users: CNEMA of 20.3 ng/mg of creatinine (versus 1.3 ng/mg in our sample), 3-HPMA of 370.3 ng/mg (versus 254.3 ng/mg), 2-HPMA of 38.0 ng/mg (versus 28.8 ng/mg), AAMA of 96.5 ng/mg (versus 67.3 ng/mg), and HMPMA of 251.6 ng/mg (versus 148.7 ng/mg). However, participants reported more frequent use of e-cigarettes in that study (ie, 24.7 days in the past 30 days and an average of 11.8 times per day on use days), and exclusive use of e-cigarettes was based on self-report only, because this was a switching study in which NNAL levels would not have had time to decline to nonexposed levels. Thus, the increase in VOCs among adults might be reflective of greater exposure to e-cigarettes and/or combustion products. Moreover, unlike our study, none of the authors of these studies employed a control group to account for baseline levels of environmental VOCs.

Not surprisingly, e-cigarette–only participants who reported using nicotine-containing products all or some of the time had significantly higher levels of cotinine compared with those who never used or were unsure if there was nicotine in their e-cigarettes. To the best of our knowledge, this is the first study to report cotinine levels in adolescent e-cigarette–only users. Among e-cigarette–only users, only the VOCs CNEMA and AAMA were higher in users of nicotine containing e-cigarettes. Levels of the 3 other significant and likely toxic VOCs were just as high in users of nonnicotine products as in those using nicotine. This is particularly important because many teenagers initiate e-cigarette use with nicotine-free products, 4 in part because they feel that they are safer. 29  

There were no significant differences found in levels of toxicants by type of product used. Despite a small number of subjects using each type of product, there was great variability among the 3 main types of e-cigarette products used by our participants. Given the results of studies of emissions among adult users of e-cigarettes, which revealed significant differences by brand and type of product, 25 , 30 , – 32 the small numbers of users and variable use patterns among products may have limited our ability to detect small exposure-related differences among products.

There are researchers who suggests that certain flavorings may generate higher levels of toxic chemicals than others. 32 , – 35 Among our e-cigarette–only participants, the use of fruit-flavored products produced significantly higher levels of the metabolites of acrylonitrile. This is of particular interest to adolescent e-cigarette use, because 1 of the main reasons teenagers report using e-cigarettes is the appealing flavors. 4 Moreover, for various reasons, including the stigma associated with tobacco, some may also feel that the fruit-flavored products are safer than tobacco-flavored products. In fact, fruit flavors were the most popular choice among our e-cigarette users with roughly 55% of e-cigarette–only users and 67% of dual users reporting using fruit flavors most often.

In addition to being the first to report toxicant levels in the urine of adolescent e-cigarette users, we used strict criteria based on objective biomarkers to avoid secondary sources of VOCs by excluding participants with any evidence of exposure to combustion products from tobacco from our e-cigarette–only group. Another strength of this study is the use of age-matched controls to account for the underlying rate of environmental exposures to 8 toxicants. We did not specifically test for marijuana exposure, a task which is fraught with difficulty, given the limitations of the testing itself, which are due to the long half-life of δ-9-tetrahydrocannabinol. 36 , 37 Despite this, our analyses revealed that it is unlikely that the variance in VOCs explained by our e-cigarette use group was accounted for by marijuana use instead of e-cigarette use.

Other limitations of this study include the fact that a wide range of e-cigarette products were used among participants, and thus, it may be difficult to pinpoint variability in toxicant exposure on the basis of the self-reported product used. However, this strengthens the external validity of the study because it gives a more real-world view of the toxicants found from the e-cigarette products commonly used by adolescents. We also only tested 8 likely toxic VOCs, but there may be other significant toxicants, including formaldehyde, which can be produced by e-cigarettes and which could pose a threat to adolescent users of these products; however, formaldehyde exposure is difficult to assess in vivo. 25 Although the focus of this study was on e-cigarette–only users, we also had a relatively small number of confirmed (ie, using NNAL) dual users. Lastly, controls were on average more likely to be female and Hispanic compared with e-cigarette–only and dual users. However, we do not feel that this played a role in our VOC findings because the analyses accounted for both sex and race and/or ethnicity. There may be other factors that could have influenced VOC levels, but given the sample size, we limited the number of covariates we included in any analysis. Larger prospective studies are needed to confirm the findings reported here to test for recent marijuana use and examine changes over time, perhaps with more complex matching.

Although e-cigarette vapor may be less dangerous than combustible cigarettes, with lower overall exposure to VOC toxicants, with our findings, we challenge the idea that e-cigarette vapor is safe. Many of the VOCs we identified among e-cigarette users are carcinogenic, including propylene oxide, acrylamide, acrylonitrile, and crotonaldehyde. 13 With few exceptions, these toxicants were present whether the product contained nicotine or flavorings. Consequently, as with traditional cigarettes, messaging to teenagers must include warnings about the potential risk from toxic exposure to carcinogenic compounds generated by these products.

2-carbamoylethylmercapturic acid

2-cyanoethylmercapturic acid

electronic cigarette

2-hydroxyethylmercapturic acid

3-hydroxy-1-methyl-propylmercapturic acid

4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol

phenylmercapturic acid

volatile organic compound

2-hydroxypropylmercapturic acid

3-hydroxypropylmercapturic acid

Drs Rubinstein, Delucchi, Ramo, and Benowitz made substantial contributions to the conception and design of the study and to the analysis and interpretation of data, participated in and made substantial contributions to the drafting of the manuscript for important intellectual content, and are in agreement to be accountable for all aspects of the work, ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved; and all authors approved the final manuscript as submitted.

FUNDING: Funded by National Institutes of Health (NIH) grants R21DA040718, P50 CA180890, P30 DA012393, S10 RR026437, and TRDRP 24XT-0007. Funded by the National Institutes of Health (NIH).

We thank Mr Richard Ceballos III, Mrs Judy Gonzalez-Vargas, Dr Karma McKelvey, Mr Michael Berry, Mr Mark Thomas, and Mr Jerome Andres for their assistance with data collection and participant recruitment. We are also grateful to Lisa Yu and Peyton Jacob III for assistance with biomarker assays. We thank Trisha Mao, Ethan Yip, Lawrence Chan, and Kristina Bello for performing analytical chemistry. We thank Dr Judith Prochaska for feedback on an earlier draft of the manuscript.

Competing Interests

Re: e-cigarettes are safer than cigarettes but not entirely safe.

We appreciate the interest our research has garnered. No single study can resolve all questions of interest, and all findings warrant replication. Our focus for this study was examining toxicants in adolescent e-cigarette only users relative to non-users. Since a number of adolescents who enrolled in our study were found to also have recently smoked combustible cigarettes (dual users), we included them as a comparison group.

As we stated in our article, e-cigarettes do appear to produce lower levels of toxicants than traditional cigarettes, based on the literature and based upon the levels observed among our dual user group. Use of e-cigarettes among adult tobacco smokers was not a focus of our study and we encourage readers interested in that literature to see the references we noted in our article. Again, we chose to focus on adolescents for whom the paradigm is different than the debate that has been characterized as harm reduction among adults. Rather, the focus of interest with adolescents is harm creation. The comparison of interest is not combustibles, but no use of any tobacco product at all. Specifically, adolescents are by and large using e-cigarettes for recreational use, not as a means of switching from traditional cigarettes. This is evidenced by epidemiologic data showing that the number of adolescents using e-cigarettes outnumbers adolescent tobacco smokers (in the U.S.) and use by never smokers is also increasing. Furthermore, studies of adolescents in the U.S. show a reverse trajectory for teens from e-cigarettes to traditional cigarettes. Consequently, for adolescents, the question of interest is: Are these products more dangerous than no use at all (rather than compared to tobacco only smoking)? As such, the most relevant groups for comparison would be those with and without e-cigarette exposure, which was the focus of our study.

The relative toxicity of the products is complex to determine. For this reason, we analyzed exposures in a non-e-cigarette using comparison group. That way, readers can compare baseline environmental exposures, which we point out in the paper were greater than zero. Again, with the perspective that most adolescents are using e-cigarettes for recreational purposes, our findings provide a warning that they are exposing themselves unnecessarily to cancer-causing toxicants. As we point out in the manuscript (and consistent with other exposures such as secondhand tobacco smoke), the harm from these lower levels of VOCs would likely not present for many years and assumes that these adolescents will continue to be exposed over time (something that as yet remains unknown). Assuming adolescents continue using e-cigarettes for many years, there are data available which can provide an estimate of cancer risk for each of the toxicants we examined. A particularly good reference is: Intake of Toxic and Carcinogenic Volatile Organic Compounds from Secondhand Smoke in Motor Vehicles: 10.1158/1055-9965.EPI-14-0548.

Again, we appreciate the interest and hope that our research findings provide the impetus for deeper investigation into the potential harms and benefits of e-cigarettes for both adults and young people.

E-cigarettes are safer than cigarettes but not entirely safe

Studying the safety of E-Cigarettes on teenagers is extremely important. This study describes the presence of certain metabolites in the urine of adolescents who smoke e-cigarettes. It also tells us many of them are carcinogenic. It concludes by advising the public to warn teenagers about "the potential risk from toxic exposure to carcinogenic compounds." However, it fails to adequately frame the message for cigarette smokers:

1. Authors were very careful to select e-cigarette-only users (they even established their elegibility by measuring the levels of urine NNAL). But they did not recruit a comparisson group composed of cigarette-only users. Being able to compare both groups is important because E-Cigarettes are advertised as an alternative to cigarettes--the carcinogenic hazards of cigarette consumption are well established--not as an alternative to dual use. Having measured the levels of volatile organic compounds in cigarette-only users, we would know by how much e-cigarettes reduce the levels of VOC compared with cigarettes in teenagers. The authors cited a study using this design,[1] suggesting they deliberately decided not to have such comparisson group.

2. The study does not tell the reader the levels at which these volatile organic compounds start being toxic. This information is crucial to understand the importance of the findings. While a statistical analysis is useful, toxicity can be better assessed by using a population-level measure of toxicity. If such information is not yet available, it should be mentioned.

Even in the absence of these data, we know that a reduced intake of VOC is associated with a reduction of disease risk [2]. It is likely that cigarette smokers would benefit by becoming e-cigarette-only users and this should be emphasized given how lightly scientific articles can be interpreted and how prevalent smoking-related cancer is.

References [1] Hecht, Stephen S. et al. “Evaluation of Toxicant and Carcinogen Metabolites in the Urine of E-Cigarette Users Versus Cigarette Smokers.” Nicotine & Tobacco Research 17.6 (2015): 704–709. PMC. Web. 11 Mar. 2018. [2] Shahab, Lion et al. “Nicotine, Carcinogen and Toxicant Exposure in Long-Term E-Cigarette and Nicotine Replacement Therapy Users: A Cross-Sectional Study.” Annals of internal medicine 166.6 (2017): 390–400. PMC. Web. 11 Mar. 2018.

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