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Forecasting pancreatic carcinogenesis from spatial multi-omics

Frontiers in Biostatistics Seminar

Tuesday September 26, 2023 @ 10am ET
Center for Life Sciences Building, Room 11081

Elana Fertig, PhD
Division Director of Oncology Quantitative Sciences, Professor of Oncology
Johns Hopkins University

Join the Zoom.

Combining genomics with mathematical modeling provides a forecast system that can yield computational predictions to anticipate cancer progression and therapeutic response. High-throughput profiling technologies can indicate the molecular and cellular pathways of malignancies, but not the effect of targeting those pathways with therapy. Precision interception requires relating therapies to the cellular phenotypes underlying pancreatic carcinogenesis. This talk presents a hybrid computational and experimental strategy to uncover interactions between neoplastic cells and the microenvironment during pancreatic carcinogenesis. As pancreatic cancer develops, it forms a complex microenvironment of multiple interacting cells. The microenvironment of advanced pancreatic cancer includes a heterogeneous and dense population of cells, such as macrophages and fibroblasts, that are associated with immunosuppression. New single-cell and spatial molecular profiling technologies enable unprecedented characterization of the cellular and molecular composition of the microenvironment. These technologies provide the potential to identify candidate therapeutics to intercept immunosuppression in pancreatic cancer. State-of-the-art mathematical approaches in computational biology are essential to uncover mechanistic insights for high-throughput data for these precision interception strategies.

 

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Heng Li, PhD Named International Society of Computational Biology Fellow

The International Society of Computational Biology (ISCB) welcomes Heng Li, PhD to the prestigious 2023 ISCB Fellows cohort. Dr. Li is Assistant Professor of Biomedical informatics, Dana-Farber Cancer Institute and Harvard Medical School.

Per ISCB’s release: The Fellows program was created to honor members who have distinguished themselves through outstanding contributions to the fields of computational biology and bioinformatics. Begun in 2009, 2023 marks the 14th anniversary of the program. Each year, ISCB seeks Fellows’ nominations from our members who meet the eligibility criteria for significant scientific and leadership contributions to the field of computational biology and bioinformatics.

Dr. Li is recognized for his influential tools for the processing of sequence data and his dedication to open-source software, including the detailed documentation which has permitted numerous researchers to learn and build from his work.

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BioC2023: the Bioconductor Annual Conference

We are incredibly excited that Bioc2023 the annual Bioconductor meeting will be in Boston at the Dana-Farber Cancer Institute from August 2-4. It is a hybrid meeting to enable maximum outreach to our global community. Registration is now open and scholarships are available. 

Contact us for sponsorship opportunities. 

Speakers include:

  • JJ Allaire (Founder and CEO of RStudio, Posit PBC)
  • Heng Li (Associate Professor, Dana-Farber Cancer Institute, Harvard Medical School)
  • Beth Cimini (Senior Group Leader, Broad Institute of MIT & Harvard)
  • Jeffrey Moffitt (Assistant Professor, Harvard Medical School and Boston Children’s Hospital) 
  • Sam Lent (Senior Computational Biologist at Freenome)

Connect with talented R/Bioconductor users & developers, data scientists, biostatisticians, and bioinformaticians at #Bioc2023

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David Harrington, PhD Receives 2023 Marvin Zelen Award

Article courtesy of Harvard T.H. Chan School of Public Health, Department of Biostatistics:

We are pleased to announce Dr. David Harrington, Emeritus Professor of Statistics Professor of Biostatistics, Harvard T.H. Chan School of Public Health and former Chair of the Department of Data Science at DFCI, will be the recipient of the 2023 Marvin Zelen Leadership Award in Statistical Science.

We will host Dave for a lecture on “The special relationship between survival analysis and cancer research — successes and persistent problems.” on Wednesday, April 26th in FXB G11 at 4pm, followed by a reception in the FXB Atrium.

Over the course of his exceptional 45-year career, Dave has served as both a scholar and a leader in the theory and practice of statistics in medical research. In addition to being on the forefront of the development of the new field of biostatistics, he played a crucial role in preparing a new generation of statisticians and physicians, leading the field of medicine towards a more rational use of data. The breadth of his contributions in both research and pedagogy reflect the fundamental vision of Marvin Zelen, making Dave a natural recipient for this prestigious award.

Dave received his PhD in 1976 from the University of Maryland with a focus on statistical theory and methods and spent nearly all of his 45-year career in the development of statistical methods and their application in medical and public health research, as reflected in his extensive CV. He joined the faculty at the Harvard School of Public Health and the Dana-Farber Cancer Institute (DFCI) in 1984 and worked as a professor of Biostatistics from 1990-2018. He chaired the Department of Biostatistics and Computational Biology (now the Department of Data Science) of the Dana-Farber Cancer Institute from 1998–2009, and the Department of Statistics at Harvard from 2012–2014. While at Harvard he developed and taught a course attended by hundreds of students each year providing a data-driven introduction to biostatistics. He also co-wrote a text on the subject and introduced it online as an open-source resource. During the 11 years he was Chair of the Biostatistical Department at DFCI, Dave led the expansion of membership as well as the scope of research, embracing the new field of computational biology.

Dave’s contributions in academia were paralleled by his outstanding contributions to the field of cancer research. From 2001 to 2014, Dave served as principal investigator of the NCI sponsored Statistical Coordinating Center for the Cancer Care Outcomes Research and Surveillance (CanCORS) Consortium, a study of access to and outcomes from cancer care in a cohort of 10,000 patients with colorectal or lung cancer. Dave led nation-wide clinical trial statistical coordinating centers and was instrumental in establishing the DF/HCC Biostatistics research program. He also served on the Scientific Advisory Board for St. Jude’s Children’s Hospital for five years and on the standing Data Safety Monitoring Committees for NIAID HIV studies in Sub-Saharan Africa (2001-17, Chair from 2015), as well as cancer trials at Memorial Sloan Kettering for 20 years. From 2000-2008 he served on the US FDA Oncologic Advisory committee with continued service as an Ad hoc member.

The importance of Dave’s contributions is reflected in the many teaching awards and accolades he earned over his career. These included the Nichols Award for Teaching Excellence, the Levenson Memorial Teaching Prize, and the Hoopes Prize for Senior Thesis Mentoring from Harvard, as well as the Herman Callert Leadership Award from Hasselt University, Belgium. Dave is also an elected fellow of the International Statistical Institute, the Institute of Mathematical Sciences, and the American Statistical Association. Throughout his career, he also contributed his expertise to major medical publications, serving as the lead statistical editor for the New England Journal of Medicine.

Marvin Zelen had a vision for the future of the field of Biostatistics, recognizing the importance of faculty and students meaningfully expanding its applications in classroom and hospital settings. Dr. Zelen’s vision was exemplified by his recruitment of David Harrington to join his department nearly four decades ago. Though he followed in Martin’s footsteps, Dave’s pathways were innovative, and his style was thoughtful. His career and accomplishments exceeded Marvin’s high expectations and he stewarded the development of a foundation for the study of Biostatistics at Harvard that continues to be fertile ground for the growth and expansion of the field.

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Simona Cristea, PhD Joins Data Science Faculty

The Department of Data Science is delighted to announce the faculty promotion of Simona Cristea, PhD. 

Dr. Cristea’s research focuses on developing computational and mathematical models to understand the evolutionary forces driving cancer initiation, progression and invasion. Her particular interest is to connect deep learning frameworks with mechanistic descriptions of tumor evolution and immune system involvement. Dr. Cristea joined Dana-Farber Cancer Institute in 2016 as Postdoctoral Fellow in Franziska Michor’s lab. Since 2020, she has served as Harvard Medical School Faculty with an appointment as Instructor in Medicine.

Currently, Dr. Cristea is Head of Data Science at the Hale Family Center for Pancreatic Cancer Research. She is leading a team of data scientists and mathematical modelers to develop algorithms and data analysis frameworks to model tumor progression by combining evolutionary thinking with statistical methods and deep learning.

Dr. Cristea holds Bachelor’s degrees in Mathematics and Cybernetics from the University of Bucharest and the Academy for Economic Studies in Romania, a Master’s in Computational Biology and a PhD in Computational Cancer Genomics from ETH Zurich, Switzerland. Throughout her career, Dr. Cristea has received multiple awards and fellowships, including the ETH Excellence Scholarship, several Swiss National Science Foundation fellowships, and the Helen Gurley Women in Science Award.

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Dana-Farber Researchers Lead Study Providing Hope for Younger Breast Cancer Patients Looking To Pursue Pregnancy

There is good news for young women with breast cancer who would like to have a baby. A landmark international study, POSITIVE, led by a team that included Dana-Farber researchers, and presented at the recent San Antonio Breast Cancer Symposium, found that young women with early-stage hormone receptor-positive breast cancer could safely interrupt their endocrine therapy to pursue a pregnancy.

Young women with hormone receptor-positive breast cancer are often treated with endocrine therapy which seeks to impede tumor growth by blocking the production of certain hormones or preventing them from reaching tumor cells. Examples include ovarian function suppression, aromatase inhibitors, and selective estrogen receptor modulators. Endocrine therapy can last for 5-10 years, during which time young women are counselled by their physicians to forgo having a child until the completion of therapy, a reality that may prohibit many young women from starting a family or expanded their existing one.

“Fortunately, the vast majority of women with early-stage breast cancer are going to be cured of their disease,” says Ann Partridge, MD, MPH, vice chair of medical oncology and founder and director of the Institute’s Program for Young Adults with Breast Cancer who co-chaired the POSITIVE study. “Among the many unique survivorship challenges faced by young women with breast cancer though, is future fertility. We wanted to evaluate the safety of women pausing their endocrine therapy to pursue pregnancy.”

Dana-Farber researchers Richard Gelber, PhD, Sam Niman, MS, and Meredith Regan, ScD, of Data Science designed and led the statistical collaboration for the POSITIVE study (Pregnancy Outcome and Safety of Interrupting Therapy for Women with Endocrine Responsive Breast Cancer), a clinical trial to evaluate if a pause in endocrine therapy leads to an increased risk of breast cancer recurrence.

The trial, which enrolled participants from December 2014 through December 2019, involved 518 women between the ages of 18 and 42 who had previously been treated for breast cancer and desired to become pregnant. In enrolling in the study, participants opted to pause endocrine therapy for approximately two years to try to get pregnant. Before pausing their treatment, women had completed between 18 and 30 months of post-surgical endocrine therapy.

After a median follow-up of 41 months, 44 participants had experienced a recurrence of breast cancer. The three-year rate of recurrence was 8.9%, similar to the 9.2% rate in an external control cohort.

Of 497 women followed for pregnancy status, 368 (74%) had at least one pregnancy, and 317 (63.8%) had at least one live birth, with a total of 365 babies born. These rates of conception and childbirth were on par with or higher than rates in the general public.

These results from the POSTIVE study provide encouraging guidance to younger women diagnosed with breast cancer who hope to have children, the study authors said. Previous research had suggested that pregnancy after breast cancer would not increase a woman’s risk of developing a recurrence of the cancer. However, these data were collected retrospectively, from trials conducted for other purposes. A controlled prospective study like POSITIVE was needed to conclusively answer these questions. This academic trial was made possible through an international collaboration involving 116 centers and 20 countries on 4 continents, sponsored and conducted globally by International Breast Cancer Study Group (IBCSG), Alliance for Clinical Trials in Oncology and Breast International Group (BIG) with support from research foundations and donors.

Since 1977, Dana-Farber has been home of the International Breast Cancer Study Group (IBCSG) Statistical Center, led by Regan. As members of the Institute’s Department of Data Science, the IBCSG statisticians have collaborated with clinical colleagues world-wide to design, analyze, and report practice-changing clinical trial results, which have improved outcomes for patients with early breast cancer.

“One of the challenges with a trial like POSITIVE is that, ethically, it cannot randomly assign participants to either attempt or not attempt pregnancy,” explains Regan. “IBCSG statisticians worked with colleagues to design the POSITIVE trial – balancing the challenge to both provide anti-cancer care and improve patients’ survivorship experience by permitting family plans to proceed.”

The statistical design included stringent stopping criteria and frequent reviews by the IBCSG’s Independent Data Monitoring Committee to monitor safety, and its analysis used an external control group from other IBCSG clinical trials that enrolled similar patients who didn’t interrupt their endocrine therapy. The researchers are continuing to follow the POSITIVE study participants to assess recurrence risk over time.

“It is extremely gratifying to see to the POSITIVE trial results, and we are forever indebted to the bravery of the women who chose to participate,” says Niman. “Due to the unique trial design and research questions, the analyses at times were challenging, but it gave us the opportunity to stretch our imaginations and put together a thoughtful and robust final product that will hopefully impact the lives young breast survivors across the globe.”

Trial participants were strongly recommended to resume endocrine therapy after a pregnancy attempt or success.

“These data stress the need to incorporate patient-centered reproductive healthcare, treatments, and choices in working with and following up on our young women with breast cancer so that they can not only survive, but thrive in their survivorship,” says Partridge.

– Dana-Farber Cancer Institute, 2023

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Genomics Expert Jeremy Simon, PhD Joins Data Science

The Department of Data Science welcomed Jeremy M. Simon, PhD on May 1, 2023.

Dr. Simon’s research focuses on the genetic and environmental effects on gene expression and gene regulation in human disease. He is currently Associate Professor, Genetics at University of North Carolina (UNC) Chapel Hill, where he directs the UNC Neuroscience Center Bioinformatics Core and serves as co-Principal of the UNC School of Medicine Bioinformatics and Analytics Research Collaborative (BARC).

“We are delighted that Dr. Simon is joining the Department of Data Science,” said Department Chair Rafa A. Irizarry, PhD. “He is an expert in genomics and a superb collaborator.”

Team science is central to Dr. Simon’s research approach. He has collaborated with dozens of investigators and laboratories on the design, execution, analysis, and biological interpretation of high-throughput sequencing-based studies. Using integrative high-throughput sequencing-based approaches (ATAC-seq, ChIP-seq, RNA-seq, and others in bulk and single cells), Dr. Simon has studied chromatin and gene expression dysregulation in numerous disease contexts including Renal Cell Carcinoma, Ewing Sarcoma, breast cancer, autism, and Crohn’s disease. Through this work, he and his collaborators have uncovered novel disease mechanisms, as well as molecular and genetic disease subtypes.

“I am very excited to join Dana-Farber,” said Dr. Simon, who trained under Dana-Farber alumnus Dr. Ian Davis at UNC-Chapel Hill. “I learned so much during my time at UNC. It taught me the ins and outs of genomics, how these data can help us solve big questions in cancer, and how important team science is to basic and translational research. I look forward to diving in and collaborating broadly across the Institute.”

Dr. Simon will be an independent investigator in Data Science with a Senior Research Scientist appointment at the Harvard T.H. Chan School of Public Health. He received a PhD in Bioinformatics and Computational Biology from UNC-Chapel Hill.

meredith_regan_headshot
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Meredith M. Regan, ScD, Promoted to Professor of Medicine

The Department of Data Science is delighted to announce that Meredith M. Regan, ScD, is promoted to Professor of Medicine as of October 1st.  

Dr. Regan is a graduate of Harvard TH Chan School of Public Health and joined our faculty in 2003. In addition to appointments at Dana-Farber and Harvard Medical School, Dr. Regan is Director of the International Breast Cancer Study Group Statistical and Data Management Center, centered at DFCI since 1977. Her research focuses on clinical-translational investigations to inform patient care and treatment selection for breast and genitourinary cancers and on clinical trial endpoints. She co-leads the IBCSG’s SOFT/TEXT trials which have changed care for premenopausal women with hormone receptor-positive early breast cancer. The DFCI-led ICECaP Working Group investigated surrogate endpoints of overall survival for localized prostate cancer trials and received the American Statistical Association’s 2021 SPAIG Award. She and colleagues proposed a treatment-free survival endpoint to measure durable remission arising from immunotherapy.

Dr. Regan is integral to statistical collaboration and faculty development at DFCI. She is a dedicated mentor to our biostatisticians and early career colleagues. She also serves as co-director of the DFCI Methods in Clinical Cancer Research prerequisite for all clinical trial PIs and sits on the Executive Committee for Clinical Research and Committee for Women Faculty (including 4 years as chair).  

Nationally and internationally, Dr. Regan’s leadership in developing and interpreting breast cancer clinical trials to improve patient care includes US NCI Breast Cancer and EBCTCG Steering Committees, ASCO and ESMO clinical guidelines committees, and St. Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer. She is a frequent reviewer for ASCO, grants and clinical oncology journals; associate editor for JNCI Cancer Spectrum; a Breast Cancer Research Foundation (BCRF) sponsored researcher and Fellow of the American Society of Clinical Oncology.

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Research Collaboration Wins 2022 Youden Award at JSM

The American Statistical Association named Roberta DeVito, PhD; Ruggero Bellio, PhD; Lorenzo Trippa, PhD; and Giovanni Parmigiani, PhD  as the recipients of the 2022 W.J. Youden Award. The award honors work developed at the Department of Data Science on multi-study factor analysis.

The authors propose a novel class of factor analysis methodologies for the joint analysis of multiple studies, published in Biometrics. 

The W. J. Youden Award in Interlaboratory Testing was “established in 1985 to recognize the authors of publications that make outstanding contributions to the design and/or analysis of interlaboratory tests or describe ingenious approaches to the planning and evaluation of data from such tests.”  The award is presented annually at the ASA Joint Statistical Meetings.

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Artificial Intelligence Expert Bill Lotter, PhD Joins Data Science Faculty

The Department of Data Science faculty welcomes Bill Lotter, PhD on October 1, 2022.

Dr. Lotter joins Dana-Farber from DeepHealth Inc., a company he co-founded to improve diagnostic tools and outcomes in medical imaging. The company develops artificial intelligence (AI) software to assist radiologists, with a special focus on mammography. It was acquired in 2020 by RadNet Inc., the largest provider of outpatient imaging services in the United States.

As Chief Technology Officer of DeepHealth and Vice President of Machine Learning at RadNet, Dr. Lotter led the development of two FDA-cleared products that are now processing over 1 million mammograms per year. Dr. Lotter’s research has detailed the AI algorithms underlying these products, as well as their ability to aid in earlier breast cancer detection. He will bring his expertise in developing clinically-effective AI to novel applications within Dana-Farber.

“Building high-performing AI algorithms with clinical integration in mind can enable more widespread access to quality care,” said Dr. Lotter. “I’m excited to join the unique Dana-Farber ecosystem and collaborate on new AI applications to improve cancer care for all.”

Dr. Lotter will be Assistant Professor, Pathology Department at Harvard Medical School and an independent faculty member in Data Science. He received his PhD in Biophysics and Computational Science, where he developed computer vision algorithms for computational neuroscience in addition to medical imaging.