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CEWG Seminar Series

upcoming seminar series

General Attendee Webinar Zoom Link:

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.

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