Dr. Sohrab Shah
Associate Professor
Pathology and Laboratory Medicine
Dr. Sohrab Shah is an Associate Professor in the Departments of Pathology and Computer Science, University of British Columbia and is a Scientist at the BC Cancer Agency. He is the recipient of a Canada Research Chair in Computational Cancer Genomics, a Terry Fox New Investigator Award, and is a Michael Smith Foundation for Health Research Career Investigator.
Current Research Focus
Dr. Shah’s work focuses on characterization of cancer genomes for determination of pathogenic driver mutations in cancer subtypes and measuring and quantifying tumour evolution. His work is in the field of computational cancer genomics and involves development of statistical models and machine learning algorithms to interpret next generation sequence data for defining mutational landscapes and quantifying clonal evolution in ovarian and breast cancers. His recent work describing new cancer genes in ovarian cancer has been published in the New England Journal of Medicine and his work describing mutational evolution in breast cancer has been featured in Nature.
Example Project
“The Clonal Dynamics of Ovarian Cancers: Phylogenetic Models of Chemosensitivity and Resistance”
I aim to understand how high grade serous ovarian cancers evolve. High grade serous cancers are the most lethal histotype of ovarian cancer, where up to 80% of cases suffer relapse after initial response to treatment with many patients succumbing to treatment resistant disease. It is believed that clonal evolution underpins treatment resistance, but we have little understanding about the relative fitness of clones that comprise tumours at diagnosis. More importantly, the dynamic growth trajectories of clones found within peritoneal foci have not been studied systematically when challenged with chemotherapeutic selective pressures. As such, beyond anecdotal evidence of BRCA revertant mutations, most relapses and their underlying mechanisms remain unexplained. I have outlined a multi-disciplinary programmatic approach to addressing these knowledge gaps which will leverage local expertise in ovarian cancer pathology, gynecologic oncologic surgery, patient derived xenografts, next generation sequencing and computational biology. This program will result in an unprecedented view of high grade serous ovarian cancer evolution as it relates to the challenges of microenvironmental and therapeutic selective pressures.
Research Keywords
Clonal Dynamics, Computational Biology, DNA Repair, Genomic Instability, Genomic Signatures, Homologous Recombination, Next-Generation Sequencing, Ovarian Cancer, Tumour Evolution
