Sohrab Shah received a PhD in computer science from UBC in 2008 and was appointed as a Principal Investigator to The BC Cancer Agency and the University of British Columbia in 2010. As well, Dr. Shah was appointed to MSK in April 2018 as the inaugural Chief of the Computational Oncology Service and is the incumbent of the Nicholls-Biondi Chair. He holds the Canada Research Chair in Computational Cancer Genomics, and is the recipient of both a Michael Smith Foundation for Health Research Career Investigator Award and a Terry Fox Research Institute New Investigator Award. His research focuses on understanding how tumours evolve over time through integrative approaches involving genomics and computational modeling. Dr. Shah has pioneered computational methods and software for inference of mutations in cancer genomes as well as deciphering patterns of cancer evolution which have been widely disseminated internationally. He has a track record of developing novel, innovative Bayesian statistical models, algorithms, and computational approaches to analyze large, high dimensional genomics and transcriptomic data sets, from both patient tumours and model systems (a list of published tools can be found here). This includes advancing molecular profiling of cancer cells at single cell resolution. Dr. Shah has been at the forefront of studying tumor evolution in breast, ovary and lymphoid malignancies. His work has been published in Nature, Nature Genetics, Nature Methods, NEJM, Genome Research, Genome Biology, amongst others. Dr. Shah oversees an annual budget of >$1M in competitively awarded funding from philanthropic, government and international bodies.

Dr. Shah has trained several highly productive PhD graduates whom have gone on to positions at Harvard Medical School, Oxford University Statistics and the Broad Institute of MIT. His trainees include 2 Vanier scholars and 1 Michael Smith Foundation for Heath Research postdoctoral fellow.  He was recently honoured with the

Distinguished Achievement Award for Overall Excellence – Early Career. Fac. of Med UBC (2013), and was named a Killam Laureate recognizing outstanding research and scholarly contributions at University of British Columbia (2016).

Credentials

Chief Of Computational Oncology, Memorial Sloan Kettering Cancer Center 

Canada Research Chair in Computational Cancer Genomics

Associate Professor, University of British Columbia – Department of Pathology and Laboratory Medicine

Associate Member, Genome Sciences Center

Faculty Member, University of British Columbia – Genome Sciences and Technology Graduate Program 

Associate Member, University of British Columbia – Department of Computer Science

Faculty Member, CIHR/MSFHR Bioinformatics Program

PhD, Computer Science (Bioinformatics), University of British Columbia 2008

MSc, Computer Science (Bioinformatics), University of British Columbia 2005

Projects

Selection and drug response

"Making predictions is hard, especially about the future" - Nils Bohr We have a keen interest in learning fitness trajectories from timeseries study of cancer populations within controlled interventions such as CRISPR or pharmacologic methods as a means to predict response to drugs. Using extensions of population genetics theory, we are interested in predicting how cell populations will respond in the presence of a perturbation. This is indeed ‘hard’ and entails the need to decipher stochastic drift, clonal interaction and positive selection.

Mutational signatures in DNA repair deficient cancers

We recently published a landmark study showing how the genomes of ovarian cancer histotypes reflect the DNA repair abnormalities they harbour. We are interested in how to optimize the computational discovery of genome-wide structural and point mutational signatures and how signatures can identify treatment opportunities for ovarian and breast cancers. This work is being carried out at bulk and single cell resolution. In addition, we are working in translation capacity to develop a robust genome-wide test to stratify ovarian cancers in the clinic.

Single cell genomics of cancer

The unit of evolutionary selection in cancer is the cell. Extraordinary progress in measurement technologies has made it possible to reliably and accurately sequence the genomes of individual cancer cells at scale. We have recently optimized biophysical techniques and hidden Markov model approaches to ascertain highly accurate copy number profiles of thousands of cancer cells. As such, studying the ‘population genetics’ of cancer cells is a tractable goal.

Cancer Evolution

Our lab is motivated by studying cancer through the lens of evolution. We are engaged in several studies that span both temporal and spatial multi-sample studies of our cancers of interest. Observing the dynamics of genomically-defined clones reflected in timeseries biopsies of patient tumours, patient-derived xenografts, or through spreading of clones across anatomical sites is a key area of interest for our lab.

Selected Publications

Interfaces of Malignant and Immunologic Clonal Dynamics in Ovarian Cancer.

Cell, 2018
Zhang, Allen W, McPherson, Andrew, Milne, Katy, Kroeger, David R, Hamilton, Phineas T, Miranda, Alex, Funnell, Tyler, Little, Nicole, de Souza, Camila P E, Laan, Sonya, LeDoux, Stacey, Cochrane, Dawn R, Lim, Jamie L P, Yang, Winnie, Roth, Andrew, Smith, Maia A, Ho, Julie, Tse, Kane, Zeng, Thomas, Shlafman, Inna, Mayo, Michael R, Moore, Richard, Failmezger, Henrik, Heindl, Andreas, Wang, Yi Kan, Bashashati, Ali, Grewal, Diljot S, Brown, Scott D, Lai, Daniel, Wan, Adrian N C, Nielsen, Cydney B, Huebner, Curtis, Tessier-Cloutier, Basile, Anglesio, Michael S, Bouchard-Côté, Alexandre, Yuan, Yinyin, Wasserman, Wyeth W, Gilks, C Blake, Karnezis, Anthony N, Aparicio, Samuel, McAlpine, Jessica N, Huntsman, David G, Holt, Robert A, Nelson, Brad H, Shah, Sohrab P

Genomic consequences of aberrant DNA repair mechanisms stratify ovarian cancer histotypes.

Nature genetics, 2017
Wang, Yi Kan, Bashashati, Ali, Anglesio, Michael S, Cochrane, Dawn R, Grewal, Diljot S, Ha, Gavin, McPherson, Andrew, Horlings, Hugo M, Senz, Janine, Prentice, Leah M, Karnezis, Anthony N, Lai, Daniel, Aniba, Mohamed R, Zhang, Allen W, Shumansky, Karey, Siu, Celia, Wan, Adrian, McConechy, Melissa K, Li-Chang, Hector, Tone, Alicia, Provencher, Diane, de Ladurantaye, Manon, Fleury, Hubert, Okamoto, Aikou, Yanagida, Satoshi, Yanaihara, Nozomu, Saito, Misato, Mungall, Andrew J, Moore, Richard, Marra, Marco A, Gilks, C Blake, Mes-Masson, Anne-Marie, McAlpine, Jessica N, Aparicio, Samuel, Huntsman, David G, Shah, Sohrab P

Dynamics of genomic clones in breast cancer patient xenografts at single-cell resolution.

Nature, 2015
Eirew, Peter, Steif, Adi, Khattra, Jaswinder, Ha, Gavin, Yap, Damian, Farahani, Hossein, Gelmon, Karen, Chia, Stephen, Mar, Colin, Wan, Adrian, Laks, Emma, Biele, Justina, Shumansky, Karey, Rosner, Jamie, McPherson, Andrew, Nielsen, Cydney, Roth, Andrew J L, Lefebvre, Calvin, Bashashati, Ali, de Souza, Camila, Siu, Celia, Aniba, Radhouane, Brimhall, Jazmine, Oloumi, Arusha, Osako, Tomo, Bruna, Alejandra, Sandoval, Jose L, Algara, Teresa, Greenwood, Wendy, Leung, Kaston, Cheng, Hongwei, Xue, Hui, Wang, Yuzhuo, Lin, Dong, Mungall, Andrew J, Moore, Richard, Zhao, Yongjun, Lorette, Julie, Nguyen, Long, Huntsman, David, Eaves, Connie J, Hansen, Carl, Marra, Marco A, Caldas, Carlos, Shah, Sohrab P, Aparicio, Samuel
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