Center for Computational Biology Seminar: Dr. Christina Curtis, Assistant Professor, School of Medicine, Stanford University

Seminar | March 7 | 4:30-5:30 p.m. | 125 Li Ka Shing Center

 Center for Computational Biology

Title: Quantifying the evolutionary dynamics of tumor progression and metastasis

Abstract: Cancer results from the acquisition of somatic alterations in an evolutionary process that typically occurs over many years, much of which is occult. Understanding the evolutionary dynamics that are operative at different stages of progression in individual tumors might inform the earlier detection, diagnosis, and treatment of cancer. Although these processes cannot be directly observed, the resultant spatiotemporal patterns of genetic variation amongst tumor cells encode their evolutionary histories. Whereas it has traditionally been assumed that tumor progression results from ongoing sequential selection for driver mutations that confer a stringent fitness advantage, recently, we described a Big Bang model of tumor evolution, wherein after transformation, the tumor grows as a terminal expansion populated by numerous heterogeneous and effectively equally fit subclones. This new model is compatible with effectively neutral tumor evolution and explains the origins of intra-tumor heterogeneity and the dynamics of tumor growth with implications for earlier detection, treatment resistance and metastasis. Building on these findings, I will discuss the importance of accounting for tumor spatial structure when inferring clonal dynamics and describe an extensible framework to simulate spatial tumor growth under varied levels of selection with implications for defining the mode of evolution in diverse solid tumors. Lastly, I will describe a quantitative framework to infer the timing of metastatic dissemination, revealing fundamentally new insights into this lethal process.

Bio:
Christina Curtis, PhD, MSc is an Assistant Professor of Medicine and Genetics in the School of Medicine at Stanford University and Co-Director of the MolecularTumor Board at the Stanford Cancer Institute. Trained in molecular and computational biology, Dr. Curtis obtained her PhD from USC with Simon Tavaré and completed postdoctoral training at the University of Cambridge. Her laboratory leverages genome-scale data, coupled with computational modeling
and iterative experimentation in order to define the molecular determinants and evolutionary dynamics of tumor progression towards the development of robust biomarkers. For example, through spatial computational modeling of tumor growth and inference of patient-specific parameters, she and her team have
described a Big Bang model of colorectal tumor growth that challenges the defacto model of sequential clonal evolution with attendant clinical implications. Her research also aims to develop a systematic interpretation of genotype/phenotype associations in cancer and has helped to redefine the molecular map of breast
cancer, revealing novel subgroups with distinct clinical outcomes.

 Light refreshments will be provided at reception from 4:00pm - 4:30pm, 125 LKS foyer.

 ccbadmin@berkeley.edu