Sohrab Shah, PhD

Chief of Computational Oncology

Sohrab Shah

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Sohrab Shah is the Chief of Computational Oncology in the Department of Epidemiology and Biostatistics.

Sohrab 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 received a PhD in computer science from the University of British Columbia in 2008 and was appointed as a Principal Investigator to The British Columbia Cancer Agency and the University of British Columbia in 2010 where he developed the roots of his research program. He is a University of British Columbia Killam laureate and a Susan G. Komen Foundation Scholar. His research focuses on cancer evolution, where he uses integrative approaches involving genomics and computational modeling. He has led major projects including the analysis team of the METABRIC consortium, and has published major works in breast and ovarian cancer genomics, including the first description of mutational evolution in a breast cancer patient (Shah et al. Nature 2009), the first mutational landscape of triple negative breast cancers (Shah et al. Nature 2012) and single cell resolution demonstration of clonal evolution in breast cancer xenografts (Eirew et al. Nature 2015).  More recently, he has made seminal contributions to understanding clonal evolution in ovarian cancer and discovered that specific mutational patterns related to foldback inversions in the genomes of ovarian cancers are prognostic in terms of treatment outcomes. Dr. Shah’s recent focus is in deciphering clonal evolution and mutational processes at single cell resolution. His work has been published in Nature, Nature Genetics, Nature Methods, Cell, NEJM, Genome Research, Genome Biology, amongst others.



  1. Campbell KR, …, Shah SP. clonealign: statistical integration of independent single-cell RNA and DNA sequencing data from human cancers. Genome Biol. 2019 Mar 12;20(1):54. doi: 10.1186/s13059-019-1645-z. PubMed PMID: 30866997; PubMed Central PMCID: PMC6417140.

  2. Zhang AW, …, Shah SP. Interfaces of Malignant and Immunologic Clonal Dynamics in Ovarian Cancer. Cell. 2018 Jun 14;173(7):1755-1769.e22. doi: 10.1016/j.cell.2018.03.073. Epub 2018 May 10. PubMed PMID: 29754820.

  3. Wang YK, …, Shah SP. Genomic consequences of aberrant DNA repair mechanisms stratify ovarian cancer histotypes. Nat Genet. 2017 Jun;49(6):856-865. doi: 10.1038/ng.3849. Epub 2017 Apr 24. PubMed PMID: 28436987.

  4. Zahn H, …, Shah SP, et al. Scalable whole-genome single-cell library preparation without preamplification. Nat Methods. 2017 Feb;14(2):167-173. doi: 10.1038/nmeth.4140. Epub 2017 Jan 9. PubMed PMID: 28068316.

  5. Roth A, …, Shah SP. Clonal genotype and population structure inference from single-cell tumor sequencing. Nat Methods. 2016 Jul;13(7):573-6. doi: 10.1038/nmeth.3867. Epub 2016 May 16. PubMed PMID: 27183439.

  6. McPherson A, …, Shah SP. Divergent modes of clonal spread and intraperitoneal mixing in high-grade serous ovarian cancer. Nat Genet. 2016 Jul;48(7):758-67. doi: 10.1038/ng.3573. Epub 2016 May 16. PubMed PMID: 27182968.

  7. Eirew P, …, Shah SP, et al. Dynamics of genomic clones in breast cancer patient xenografts at single-cell resolution. Nature. 2015 Feb 19;518(7539):422-6. doi: 10.1038/nature13952. Epub 2014 Nov 26. PubMed PMID: 25470049; PubMed Central PMCID: PMC4864027.

  8. Roth A, …, Shah SP. PyClone: statistical inference of clonal population structure in cancer. Nat Methods. 2014 Apr;11(4):396-8. doi: 10.1038/nmeth.2883. Epub 2014 Mar 16. PubMed PMID: 24633410; PubMed Central PMCID: PMC4864026.

  9. Shah SP, et al. The clonal and mutational evolution spectrum of primary triple-negative breast cancers. Nature.  2012 Apr 4;486(7403):395-9. doi: 10.1038/nature10933. PubMed PMID: 22495314; PubMed Central PMCID: PMC3863681.


View a complete listing of Sohrab Shah’s publications