Workshop on Emerging Topics in Cancer Evolution

Motivation and Workshop Goals

Cancer results from an evolutionary process that yields a heterogeneous tumor with distinct subpopulations and varying sets of somatic mutations. Viewing cancer through the lens of evolution is critical to improve our understanding of tumorigenesis and ultimately treatment of cancer. The workshop will focus on algorithms and models of evolutionary processes in cancer. Specifically, we aim to bring together the algorithmically-focused side of the cancer evolution community with the biologically-focused side. Topics could include:

• Reconstruction of the cancer phylogenies based on both bulk and single cell genomic, transcriptomic and epigenomic sequencing data;
• Identification of common evolutionary patterns and trajectories in cancers;
• Inference and deconvolution of mutational signatures of cancers and the associated therapeutic opportunities;
• Inferring selection, patterns of migration, and the impact of neutral evolution on cancer progression and malignancy;
• Adaptive therapies for treating cancer based on evolutionary models; and
• Other topics related to cancer evolution.

Workshop Organizers

• Mohammed El-Kebir is an Assistant Professor of Computer Science at the University of Illinois at Urbana-Champaign. Dr. El-Kebir received his Ph.D. in computer science from CWI / VU University Amsterdam. Dr. El-Kebir is also the recipient of NSF CRII and CAREER Awards. His lab focuses on the development of theory, models and methods for cancer phylogenetics.
• Quaid Morris is a Full Member in the Computational and System Biology program at Memorial Sloan Kettering Cancer Centre and he holds a CCAI chair through the Vector Institute for Artificial Intelligence. He still holds a status-only full professorship in Molecular Genetics and Computer Science at the University of Toronto. Dr Morris received his Ph.D. in Computational Neuroscience from MIT. His lab uses machine learning and artificial intelligence to do biomedical research, focusing on cancer evolution, post-transcriptional regulation, automated phenotyping and electronic medical records.
• Layla Oesper is an Assistant Professor of Computer Science at Carleton College. Dr. Oesper received her B.A. in mathematics from Pomona College and her Sc.M and Ph.D. in Computer Science from Brown University. Dr. Oesper is also the recipient of NSF CRII and CAREER Awards. Her lab focuses on the design of computational methods related to inference and analysis of cancer evolution.
• Cenk Sahinalp is a Senior Investigator at the Cancer Data Science Laboratory in National Cancer Institute, Bethesda, MD. His lab focuses on algorithmic problems in computational cancer biology, including those related to tumor evolution and intratumor heterogeneity.