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CEWG Past Seminar Series


Past CEWG seminar recordings may be accessed by logging into myAACR, clicking under the “Events” section and searching for Cancer Evolution Working Group, which will provide all past seminars. You may also click on the image below that corresponds directly to that monthly seminar. If you are not an AACR member, you can create a myAACR non-member account to access the recordings. 


Thursday, October 5, 2023

Theme: Overcoming Therapeutic Resistance


Carlo C. Maley, PhD
Professor, Biodesign Institute, School of Life Sciences; Director, Arizona Cancer Evolution Center, Arizona State University, Tempe, AZ


Joel Brown, PhD
Cancer Biology and Evolution Program and Department of Integrated Mathematical Oncology, Moffitt
Cancer Center, Tampa, FL

Title: Extinction Therapy: How to go from billions to none

Adam Palmer, PhD
Assistant Professor, Department of Pharmacology, UNC School of Medicine, University of North Carolina, Chapel Hill, NC

Title: How Combination Therapies Overcome Cancer Heterogeneity


Thursday, September 7, 2023

Theme: Leveraging Mathematical and Computational Biology Approaches to Better Understand and Treat Cancer


Jason Somarelli, PhD
Assistant Professor, Department of Medicine; Director of Research, Duke Comparative Oncology Group, Duke Cancer Institute, Durham, NC


Mohit K. Jolly, PhD
Assistant Professor, Centre for Biosystems Science and Engineering, Indian Insitute of Science, Bangalore, India

Title: Dynamical modeling of non-genetic heterogeneity and multi-dimensional phenotypic plasticity in cancer

Summary: Phenotypic plasticity enables cancer cells to adapt to various stresses during metastasis and therapeutic attack. It can be manifested along many interconnected axes, such as stemness and differentiation, drug-sensitive and drug-resistant states, and between epithelial and mesenchymal cell-states. Despite growing acceptance for phenotypic plasticity as a hallmark of cancer, the dynamics of this process remains poorly understood. This talk will discuss how mechanism-based dynamical models of underlying gene regulatory networks, in close collaboration with high-throughput omics and clinical data, can unravel the systems-level dynamics of how cell-states transition among each other along multiple dimensions of plasticity, and how can this dynamical understanding lead to rational design of more effective combinatorial therapies. Understanding the dynamics of phenotypic plasticity may be a key component in shifting the paradigm of cancer treatment from reactionary to a more predictive, proactive approach. 

Yijun Sun, PhD
Professor, Department of Microbiology and Immunology; Department of Computer Science and Engineering, New York State Center of Excellence in Bioinformatics and Life Sciences, University of Buffalo, The State University of New York, Buffalo, NY

Title: Cancer Progression Modeling Using Massive Static Sample Data 

Summary: Cancer evolution has been studied for >50 years. However, due to the difficulty in obtaining time-series data, there is currently no established cancer progression model. The lack of time-series data has been recognized by the field as the central problem. We recently developed a novel computational strategy that overcomes the existing sampling limitations and enables the construction of cancer progression models by using massive static sample data. The application of the developed computational pipeline to the TCGA and METABRIC datasets (n = 3,420) resulted in one of the first working models of breast cancer progression that covers the entire disease process. To demonstrate the validity of the constructed model, we performed a series of internal and external validations. The replication of the bifurcating structure in additional 25 independent datasets (n = 5,831) and the post-construction association analysis of genetic and clinical variables and matched primary and metastatic tumor samples provided substantial support for the model. Our study shed light on some longstanding issues regarding the origins of molecular subtypes and their possible progression relationships. Built upon our progression modeling analysis, we also developed a novel strategy to detect cancer driver genes and pathways directly based on their definitions derived from cancer evolution theory and visualize identified changes in a cancer development roadmap. A computational approach that can overcome the existing sampling limitations and thereby enables the leveraging of accumulating data represents a major advance with respect to the application of bioinformatics methodology to the study of progressive human diseases. In the talk, I will also discuss briefly how to use single-cell sequencing and spatial omics techniques for cancer progression modeling analysis.   

June 1, 2023

Thursday, June 1, 2023
11:00am-12:30pm ET

Webinar Theme: Cellular Cognition in Cancer Evolution

Moderator: Perry S. Marshall


Eric Kuelker, PhD, R. Psych.

William B. Miller, MD

May 4, 2023

Thursday, May 4, 2023
11:00 am – 12:30 pm ET

Webinar Theme: Tumor Heterogeneity and Evolvability


James DeGregori, PhD

Courtenay C. and Lucy Patten Davis Endowed Chair in Lung Cancer Research, Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical Campus, School of Medicine, Aurora, CO

James DeGregori is a Professor in the Department of Biochemistry and Molecular Genetics (faculty since 1997) and Deputy Director of the University of Colorado Cancer Center. He has degrees from the University of Texas at Austin (B.A. Microbiology) and the Massachusetts Institute of Technology (PhD Biology), and received postdoctoral training at Duke University. He holds the Courtenay and Lucy Patten Davis Endowed Chair in Lung Cancer Research, and is Editor-in-Chief of the journal Aging And Cancer.

His lab studies the evolution of cancer, in the context of their Adaptive Oncogenesis model, with a focus on how aging, smoking, Down Syndrome, and other insults influence cancer initiation and responses to therapy. In this model, mutations face fitness landscapes that vary with age, genetics, or following carcinogen exposure. These fitness landscapes are highly dependent on the state of the tissue microenvironment in which stem cells reside.


Sheng Li, PhD
Associate Professor, Department of Computational Biology, The Jackson Laboratory for Genomic Medicine & The Jackson Laboratory Cancer Center Farmington, CT

Biography: The Li lab harnesses technological and algorithmic advancements to quantify the influence of somatic mutations and the aged ecosystem on epigenome dynamics and transcriptional dysregulation during cancer initiation and evolution. The long-term goal is to establish a foundation for developing future therapeutic and preventative strategies to extend the health span and life span of the rapidly growing aging population. The Li lab emphasizes algorithm development and integrative analysis of high-throughput data derived from single-cell, long-read, and spatial multi-omics technology. This approach aims to effectively translate the wealth of information embedded in advanced multi-omics data into meaningful biological discoveries in cancer evolution while promoting interdisciplinary collaborations and partnerships to achieve bold, impactful, and challenging goals.

Title: Deciphering Cellular Epigenome Heterogeneity and Evolution in Cancer within an Aged Ecosystem

Abstract: Cancer is an age-related disease, with its evolution resulting from selection acting on cell-to-cell genetic and epigenetic heterogeneity over time. Epigenetic reprogramming is a shared hallmark of both cancer and aging. Our research, along with others’, demonstrates that increased epigenetic heterogeneity correlates with poor clinical outcomes in hematopoietic and solid tumors, including acute myeloid leukemia (AML). This confers an additional layer of fitness to malignant cells beyond genetic heterogeneity. We have also shown that somatic mutations in DNA methylation regulator genes drive epigenetic heterogeneity, preceding leukemic transformation. Importantly, epigenetic heterogeneity can be pharmacologically reversed in vivo, suggesting clonal reduction as a novel therapeutic target for AML. We are currently investigating the influence of aging and clonal hematopoiesis on epigenetic heterogeneity, evolvability, and leukemogenesis through in vivo parallel capture of clonal history and cell identity. Our goal is to identify novel leukemia onset targets to develop preventative interventions as part of the NIH NCI-NIA jointly funded OncoAging Consortium. Furthermore, we are uncovering the aged tissue ecosystem through spatial multi-omics as part of the NIH Common Fund SenNet Consortium.

Jeffrey West, PhD
Assistant Member, Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL

Biography: Jeffrey West is an Assistant Member of the Integrated Mathematical Oncology department within the Moffitt Cancer Center in Tampa, Florida. The broad research goal of his group is to aid in targeting treatment resistance by constructing mathematical models of 1) tumor evolution and heterogeneity and 2) evolutionary-minded treatment strategies, employing techniques such as agent-based modeling, dose response convexity analysis and evolutionary game theory. He is also the founding editor of “This Week in MathOnco,” a weekly newsletter (250 issues) that consolidates the important updates in the field of mathematical oncology, and co-editor of The Mathematical Oncology Blog, which facilitates robust discussion on the role of mathematics in oncology (

Title: Mathematical modeling informs our understanding of tumor heterogeneity and the evolution of treatment resistance

Abstract: We begin by discussing the role of mathematics in investigating tumor heterogeneity and evolvability, specifically highlighting agent-based modeling as a key tool for exploration of cell–cell and cell–environment interactions that drive cancer progression and therapeutic resistance. We then illustrate the model exploration process with a case study describing the impact of tissue architecture on the emergent mode of tumor evolution: Darwinian or neutral. Finally, we review the impact of mathematics in treatment scheduling, with an emphasis on evolution-based therapies that account for cancer as an evolutionary and ecological process when designing treatment protocols.

February 9, 2023

Thursday, February 9, 2023
11:00 am – 12:30 pm EST


Frank H. Laukien, PhD
Bruker Corporation, Harvard University, Boston, MA

Title: Active Vertical and Horizontal Multiomics Cancer Evolution at Different Timescales

Jeffrey P. Townsend, PhD

Elihu Professor of Biostatistics, Professor of Ecology and Evolutionary Biology, Yale School of Public Health, New Haven, CT

Title: “Why Me?”: The Mutagenic Origins of Cancer for Individual Tumors and Tumor Types

Abstract: It is natural for patients to want to understand the causes behind their calamities. To date, risk factors are nearly the only answer that science or medicine has been able to give patients who ask “why me?” or to public health officials that ask “why us?”. Recent research has revealed signatures of these mutational processes in the genomes of tumors, which has been an extraordinary contribution to our scientific understanding of tumorigenesis. However, knowledge of the mutational processes acting on our DNA does not on its own convey the cellular causation of cancer: many mutations are “passenger” mutations that do not affect progression. One must know which mutations are causative, which are not, and to what degree. In recent years we quantified the effect sizes of somatic nucleotide changes on cancer, i.e., the degree to which each nucleotide change contributes to the survival and proliferation of cancer cells in humans. In current research, we have described how the quantifications of mutation and selection in the evolution of cancer can be brought together to ascribe the causation of cancer to specific mutational processes. We are now able to quantify the contribution of each mutational process to cancer in individual patients (a far finer scale of discovery than corresponding epidemiological findings) via the selected protein site variants that those processes engender. Our results provide molecular validation of well-known correlative findings from the epidemiological literature—such as providing an explanation for the increased odds of KRAS mutation in tumor tissue of ever smokers compared to never smokers, as well as the increased odds of EGFR mutation in never smokers compared to ever smokers. We demonstrate that melanomas and lung cancers are largely attributable to the preventable, exogenous mutational processes of ultraviolet light and tobacco exposure, whereas gliomas and prostate adenocarcinoma tumors are largely attributable to endogenous processes associated with aging. Other potentially preventable mutational processes, such as mutations associated with pathogen exposure and APOBEC activity, account for a large proportion of the cancer effect within head and neck, bladder, cervical, and breast cancers.Furthermore, our results quantify the balance of endogenous processes (such as cytosine deamination associated with aging) and exogenous processes (such as smoking, ultraviolet light, or exposure to haloalkanes) contributing to 23 major cancer types—a balance that both validates the dangers of exogenous mutations and conveys our prospects for public health efforts toward the prevention of their carcinogenic effects.

January 12, 2023

Thursday, January 12, 2023
11:00 am – 12:30 pm EST


Jason Somarelli, PhD
Assistant Professor of Medicine, Director of Research, Duke Comparative Oncology Group, Duke University, Durham, NC


Antonia Chroni, PhD 

Post-doctoral Research Fellow, Applied Bioinformatics Laboratories, Department of Pathology, Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY

Title: Tumor Island Biogeography: From Theory to Clinic

Abstract: The formation of tumors is nothing like walking along a straight line but rather like dwelling at the center of the Minotaur’s labyrinth. Cancer cells are equipped with a complex architecture of unique features that allow them to survive and engineer their own microenvironment, but also to escape their initial tumor of growth, migrate, colonize other anatomical sites and form metastasis. Tumor Island Biogeography (TIB) is an exciting and promising framework that conceptualizes tumors as island-like ecosystems that undergo evolutionary and spatiotemporal dynamic processes. Tumor insularity considers tumor size and carrying capacity and physical distance and connectivity between anatomical sites to provide insights into tumor heterogeneity and metastatic potential. We pose that tumor insularity will affect tumor heterogeneity and its associated microenvironment over time and across space, and shape metastatic migrations of cancer cells. Integration of single-cell sequencing data across different modalities (e.g., genomes and transcriptomes) holds promise for investigating tumor heterogeneity and its associated microenvironment under the TIB framework. I will discuss how tumor spatial and longitudinal variation patterns in patients are relevant to tumor insularity, and how TIB can facilitate the translation of evolutionary and ecological elements into clinical applications to inform patient stratification, and clinical trials and improve treatment strategies.

Sarah Amend, PhD

Assistant Professor, Department of Urology and Oncology, Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, MD

Title: Optimal Foraging Theory to Understand the Adaptive Strategies that Drive Lethal Cancer

Abstract: Metastasis, the cause of nearly all cancer-related deaths, is lethal and remains incurable. The process of metastasis requires that a cancer cell leave the primary tumor, travel throughout the body, and invade and colonize a distant site.  We apply fundamental ecological principles to better understand each of these steps of the metastatic process, includ

DeCember 2022

Thursday, December 1, 2022

Frank H. Laukien, PhD, Bruker Corporation, Harvard University, Boston, MA

Laurie H. Glimcher, MD, Dana-Faber Cancer Institute, Boston, MA


Benjamin L. Ebert, MD, PhD, Dana-Faber Cancer Institute, Boston, MA

Title: Clonal Hematopoiesis and the Origins of Blood Cancers

Abstract: Clonal hematopoiesis of indeterminate potential (CHIP) is a common, age-associated condition in individuals who do not have a hematologic malignancy or altered blood counts.  CHIP is defined by the presence of clonal, somatic mutations that are found in hematologic malignancies such as myelodysplastic syndrome, myeloproliferative neoplasms, acute myeloid leukemia.  Indeed, the mutations identified in CHIP, including mutations in DNMT3A, TET2, and ASXL1, are lesions that are commonly acquired early in the genetic ontogeny of hematologic malignancies, prior to the development of overt disease.   Consistent with the concept that CHIP is a pre-malignant state, CHIP is associated with a striking increased risk of hematologic malignancy.  In recent studies, we have identified somatic genetic abnormalities in the peripheral blood of healthy individuals that are recurrently mutated in lymphoid malignancies as well as the previously defined myeloid mutations.  The somatic mutations or copy number changes detected in the blood can be parsed into lesions that increase the risk of either lymphoid or myeloid malignancies.  In addition to the risk of malignancy, individuals with myeloid CHIP mutations have increased risk of cardiovascular disease.  In murine models, Tet2 inactivation in blood cells, transplanted into Ldl receptor knockout mice, leads to accelerated atherosclerosis.  CHIP is also associated with the development of chronic obstructive pulmonary disease (COPD), and Tet2 inactivation in blood cells accelerates emphysematous changes in a murine model of COPD.  More broadly, CHIP is associated with a range of inflammatory disorders.  CHIP is therefore a common condition, and clonal mutations in blood cells can contribute to diverse pathologic processes.

Franziska Michor, PhD, Dana-Faber Cancer Institute, Boston, MA

Title: Somatic Evolution of Human Cancer

Abstract: The last decades have brought about a revolution in cancer biology and clinical care. The advent of large scale, cost-efficient and high-throughput genomics approaches such as whole genome, exome and RNA sequencing, epigenetic, metabolomic, proteomic and other data types at the bulk and single cell levels for tens of thousands of cancer samples and millions of single cells has enabled researchers to understand cancer progression and treatment response at an unprecedented level. Additionally, phenotypic data of tumor and microenvironmental cells such as growth and death rates, migration, invasion, and interaction kinetics with other cell types are obtained for multiple tumor types, treatment conditions, and in vivo models. This revolution has enabled a precise understanding of the somatic evolution of human cancer, its continued genetic and epigenetic diversification during tumor progression, and the bottleneck effects of treatments. It has also heralded the era of precision medicine where patients’ tumors are now profiled at the molecular level and individually matched to best treatment options – may that be immunotherapy, targeted agents, radiation, chemotherapy or a combination thereof. We will discuss recent contributions to a data-driven, quantitative understanding of the somatic evolution of human cancer.  

November 2022

Thursday, November 3, 2022

Theme: Spatial Biology Insights into Cancer Evolution


Franziska Michor, PhD Professor of Computational Biology, Departments of Data Sciences, Biostatistics, and Stem Cell and Regenerative Biology, Dana-Farber Cancer Institute; Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA


Michael Angelo, MD PhD
Assistant Professor, Department of Pathology, Stanford University School of Medicine, Palo Alto, CA

Title: Coevolution of immune and stromal function in cancer, pregnancy, and tuberculosis

Abstract: The focus of our work is to understand how normative tolerogenic processes like pregnancy and wound healing are aberrantly recruited to drive persistence of tumor cells and foreign antigens in cancer and infectious disease.  These programs are mediated through an evolving spatiotemporal network involving dozens of cell types and multiple organ sites.  Consequently, understanding them requires technical approaches that can identify these cell types and their functions within intact human tissue.  To begin to address this need, we created a new type of ion microscope for high-dimensional subcellular imaging of intact archival human tissue from medical center biobanks (MIBI-TOF). To meet the breadth and complexity of multiplexed images generated by MIBI-TOF, we have developed complimentary deep learning algorithms for automated, scalable annotation of single cells and larger multicellular structures with human-level accuracy. This synergy permitted us in previous work to discover spatial programs present at the time of diagnosis that were predictive of long-term invasive progression in ductal carcinoma in situ (DCIS) and overall survival in triple-negative breast cancer (TNBC).  We are expanding on this work to create a spatial ontology where tissue function is linked to coevolving interactions between immune and stromal cells with foreign antigens. This approach has revealed a shared ontology in pregnancy, tuberculosis granulomas, and metastatic cancer where innate immune suppression, stromal desmoplasia, and regulatory T-cells sustain a tolerogenic niche that deters cytotoxic T-cell infiltration.  Lastly, using complementary techniques for spatial transcriptomics and glycomics, we are expanding these spatial ontologies to identify tissue glycans and underlying regulatory pathways that can be exploited for diagnostic and therapeutic purposes.

Bernd Bodenmiller, PhD Dual Professor University of Zurich and ETH Zurich. Director, Department of Quantitative Biomedicine, Comprehensive Cancer Center Zuerich (CCCZ) University of Zurich, Zurich, Switzerland

Title: The Emerging Role of Spatial Biology to study Cancer Evolution for Precision Medicine

Abstract: Tumors are highly heterogeneous ecosystems within and across patients. Due to cancer evolution processes, tumor heterogeneity is dynamically changing tumor cell composition, cellular communities and ultimately location. This evolving heterogeneity is the main obstacle to treat cancer. Thus to enable an understanding of tumor biology, to define new biomarkers to improve patient care, and to infer for each patient a tailored therapy, approaches are needed that enable to comprehensively study the ever changing cellular and spatial heterogeneity of tumor ecosystems. To support such analyses, we develop mass-tag based highly multiplexed protein imaging approaches of tumor tissue. These approaches currently enable to visualize over 50 and soon 200 antibodies simultaneously in situ with subcellular resolution. The generated multiplexed images reveal which cell types are present in a tumor, their functional state, and which cell-cell interactions are present. We applied highly multiplexed protein tissue imaging to compare single-cell phenotypes of primary breast cancers and their matched lymph-node and distant metastases to understand how the tumor ecosystem evolves from the primary to foreign sites. Our analyses revealed extensive variability in the predominant cellular phenotypes of matched primary tumor and metastatic tissues. However, a tumor’s most abundant disseminated cell phenotype, often with molecular features that deviated from its clinical classification and enriched in triple-negative cellular features, was identified as a subpopulation in the primary tumor in the majority of cases. We also found that the metastatic site does not “select” for defined tumor cell phenotypes. Finally, we identified single-cell phenotypes and spatial organizations of disseminated tumor cells in lymph nodes that were strongly associated with patient survival. These features can be measured using standard clinical methods in lymph node metastasis tissue and provide prognostic information beyond current clinical classifiers. In summary, these results show how the evolutionary trajectory of tumor ecosystem heterogeneity from the primary tumor, to lymph-nodes to distant sites is an untapped source of clinically applicable information.

october 2022

Thursday, October 6, 2022

Theme: Cancer Treatment and Resistance from a Basic and Evolutionary Perspective


Robert H. Gatenby, MD, Senior Member, Chair, Radiology and Co-Director, Center of Excellence for Evolutionary Therapy, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL


Evolutionary Dynamics of Cancer Treatment and Resistance
Joel Brown, PhD, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL

Integration of Mathematical Modeling into Treatment Strategies
Alexander Anderson, PhD, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL

Designing Clinical Trials Based on Mathematically Framed Evolutionary Principles
Damon R. Reed, MD, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL

Evolution Tumor Board
Christine H. Chung, MD and Mark Robertson Tessi, PhD, H. Lee Moffitt Cancer Center and Research Institute

September 2022

Thursday, September 8, 2022

Theme: Cancer and Ecology

Diverse populations of cancer cells exist within the ever-changing ecosystem of the body. Cancer cells must compete for space and resources to maintain their fitness in much the same ways as populations of organisms in any ecosystem. This session will focus on ways in which cancer cell genotypes and phenotypes impact their ecological fitness. 


Jason Somarelli, PhD
Assistant Professor of Medicine, Director of Research, Duke Comparative Oncology Group, Duke University, Durham, NC


Andriy Marusyk, PhD
Associate Professor, University of South Florida; Associate Member, Department of Cancer Physiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL

Title: Impact of Stromal Sheltering on Eco-Evolutionary Dynamics of Acquired Resistance in Targetable Lung Cancers

Frederick R. Adler, PhD
Professor, Department of Mathematics; Director, School of Biological Sciences, College of Science, The University of Utah, Salt Lake City, UT

Title: Cancer Corruption

Strategies for modeling cancer range from describing “one renegade cell” to inclusion of ecology and evolution.  Our approach emphasizes that cancer cells are still cells, and interact not only with each other but with the surrounding healthy tissue that they depend on.  Their success requires corrupting the system of signaling that maintains tissue integrity in the face of uncertainty and disturbance. I conclude with analogies to Ecological Restoration and economics to inspire alternative approaches to cancer control.

August 2022

Please note that the AACR Cancer Evolution Working Group Seminar Series will be taking a summer break and resume in September.

JuLY 2022

Thursday, July 7, 2022
11 a.m. – 1 p.m. EST

Sarah R. Amend, PhD, John Hopkins University

Claire Edwards, PhD, University of Oxford
Cancer Evolution: The Importance of the Bone Microenvironment

Denis Wirtz, PhD and Ashley Kiemen PhD, John Hopkins University
“Mapping the 3D Microanatomy of Tumors at Single-cell Resolution Using CODA”

June 2022

Thursday, June 2, 2022
11 a.m. – 1 p.m. EST

Perry S. Marshall, BS, Marketing Consultant and Author

Michael Levin, PhD, Tufts University
“Cancer, Cognition, and Biological Causation”

František Baluška, PhD, University of Bonn
“Concept of Sentient Eukaryotic Cell and Cognitive Evolution”

May 2022

Thursday, May 5, 2022
11 a.m. – 1 p.m. EST

Michael Gillette, MD, PhD, The Broad Institute

David Reich PhD, Harvard Medical School
“Insights into Evolutionary Analysis from the Ancient DNA Revolution”

Gad Getz, PhD, Harvard Medical School
“Convergent Evolution as a key signal for discovering mechanisms of resistance to cancer therapy”

March and April 2022

Please note that the AACR Cancer Evolution Working Group Seminar Series will be postponed during the months of March and April due to the 2022 AACR Annual Meeting in New Orleans, LA.

February 2022

Thursday, February 3, 2022
Susan Rosenberg, PhD, Baylor College of Medicine

Carlo C. Maley, PhD, Arizona State University
Daniel Jarosz, PhD, Stanford University School of Medicine
Miroslav Radman, PhD, Mediterranean Institute for Life Sciences

January 2022

Thursday, January 6, 2022
11 a.m. – 1 p.m. EST

Giulia C. Kennedy, PhD, Veracyte, Inc.

Wendy J. Fantl, PhD, Stanford University
Klaus Lindpaintner, MD, MPH, InterVenn Biosciences

December 2021

Thursday, December 2, 2021
11 a.m. – 12:30 p.m .EST

George Poste, DVM, PhD, FMedSci, FRS, Arizona State University

Alissa Weaver, MD, PhD, Vanderbilt University School of Medicine
“The role of exosomes in tumor angiogenesis and metastasis”

David C. Lyden, MD, PhD, Weill Cornell Medical College
“Extracellular Vesicles as Biomarkers for Cancer Detection and Determining Cancer Type”

November 2021

Thursday, November 4, 2021
11 a.m. – 12:30 p.m. EDT

Frank H. Laukien, PhD, Bruker Corporation

Doru M. Paul, MD, PhD, Cornell Medicine

Aurora M. Nedelcu, PhD, University of New Brunswick
“A Systemic View of Cancer: The Unexplored Links Between Cancer and the Organism’s Internal ‘climate'”

Gary Patti, PhD, Washington University in St. Louis
“Oncogenic Mechanisms for Co-Opting Healthy Tissue Metabolism to Drive Tumor Growth”

Susan M. Rosenberg, PhD, Baylor College of Medicine
“Looking upstream of evolution at the DNA Damageome and Cancer, and Stess-induced Mutations”

October 2021

October 7, 2021
11 a.m. – 12:30 p.m. EDT

Jeff Townsend, PhD, Yale School of Public Health

Vincent Cannataro, PhD, Emmanuel College
“Attribution of Cancer Origins to Endogenous, Exogenous, and Preventable Mutational Processes”

David McCandlish, PhD, Cold Spring Harbor Laboratory
“Modeling High-Dimensional Cancer Fitness Landscapes”

September 2021

September 2, 2021
11 a.m. – 12:30 p.m. EDT

Jason Somarelli, PhD, Duke Cancer Institute

Gábor Balázsi, PhD, Stony Brook University
“Mapping the Landscapes of Chemoresistance and Metastasis”

James DeGregori, PhD, University of Colorado Anschutz School of Medicine
“Aging, Somatic Evolution, and Cancer – the Inexorable Link”