Memorial Hospital Research Laboratories
The Sohrab Shah Lab
The Shah lab focuses on the major topics of cancer evolution, single cell genomics and transcriptomics, mutational processes and prediction of drug response. We are interested in the major questions which underpin the cellular dynamics of cancer. Why do some cancer patients respond to treatment, while others succumb to their disease? Why are some treatments effective initially, but fail over time? How do cancer cells acquire the ability to spread from one part of the body to another? These are the fundamental yet unresolved questions which limit our understanding of cancer progression. Viewing cancer progression through the lens of evolution, our approach centers on studying cancer cells as fundamental units of information encoding biological properties that evolve in different contexts. At Memorial Sloan Kettering we are leveraging single cell technologies and cellular imaging combined with development and deployment of state of the art machine learning tools to study the cellular dynamics of cancer in patients before, during and after treatment. Our work cross cuts basic and translational science including technology and computational methods development with application to biological and clinical problems in ovarian and breast cancer.
Wang YK, Bashashati A, Anglesio MS, Cochrane DR, Grewal D, Ha G, McPherson A, Horlings HM, Senz J, Prentice LM, Karnezis, Anthony N, Lai D, Aniba MR, Zhang AW, Shumansky K, Siu C, Wan A, McConechy MK, Li-Chang H, Tone A, Provencher D, de Ladurantaye M, Fleury H, Okamoto A, Yanagida S, Yanaihara N, Saito M, Mungall AJ, Moore R, Marra MA, Gilks CB, Mes-Masson A, McAlpine JN, Aparicio S, Huntsman DG and Shah SP. Genomic consequences of aberrant DNA repair mechanisms stratify ovarian cancer histotypes. Nature Genetics. 2017 Jun;49(6):856-865. doi: 10.1038/ng.3849.
Zhang A, McPherson A, Milne K, Kroeger DR, Hamilton PT, Miranda A, Funnell T, Litlle N, De Souza CPE, Laan S, LeDoux S, Cochrane DR, Lim J, Yang W, Roth A, Smith MA, Ho J, Tse K, Zeng T, Shlafman I, Mayo MR, Moore R, Failmezger H, Heindl A, Wang Y, Bashashati A, Grewal D, Brown SD, Lai D, Wan A, Nielsen C, Anglesio M, Bouchard-Cote A, Yuan Y, Wasserman W, Gilks B, Karnezis AN, Aparicio S, McAlpine J, Huntsman DG, Holt RA, Nelson BH, Shah SP. Interfaces of malignant and immunologic clonal dynamics in ovarian cancer. Cell. 2018 May 7. Pii: S0092-8674(18)30445-8.doi:10.1016/j.cell.2018.03.073.[Epub ahead of print] PubMed
Sohrab Shah, PhD
- The Shah Lab studies cancer evolution and response to treatment through high density genomics coupled with advanced computational methods such as machine learning and Bayesian statistical models.
- PhD, University of British Columbia (Canada)
- Susan B Komen Scholar (2018)
- Clarivate Analytics Highly Cited Researchers (2018)
Faculty Positions in Computational Oncology
The Computational Oncology Program at Memorial Sloan Kettering Cancer Center (MSK) is inviting applications for tenure track faculty positions at the level of Assistant and Associate Member.
Doctors and faculty members often work with pharmaceutical, device, biotechnology, and life sciences companies, and other organizations outside of MSK, to find safe and effective cancer treatments, to improve patient care, and to educate the health care community.
MSK requires doctors and faculty members to report (“disclose”) the relationships and financial interests they have with external entities. As a commitment to transparency with our community, we make that information available to the public.
Sohrab Shah discloses the following relationships and financial interests:
The information published here is for a specific annual disclosure period. There may be differences between information on this and other public sites as a result of different reporting periods and/or the various ways relationships and financial interests are categorized by organizations that publish such data.
This page and data include information for a specific MSK annual disclosure period (January 1, 2019 through disclosure submission in spring 2020). This data reflects interests that may or may not still exist. This data is updated annually.