• Researcher Profile

    Rameen Beroukhim, MD, PhD

     
    Physician

    Assistant Professor of Medicine, Harvard Medical School

    Center/Program

    Neuro-Oncology

    Office phone: 617-632-2166
    Fax: 617-632-4773

    Preferred contact method: appointment phone

    View Physician Profile
     
     

    Research Departments

    Cancer Biology

    Medical Oncology

    Interests

    Glioma, Meningioma, Somatic genetics of cancer

    Area of Research

    Cancer Genomics


    Dana-Farber Cancer Institute
    450 Brookline Avenue
    SM1022C
    Boston, MA 02215

    Recent Awards

    • V Scholar Award, 2009

    Research

    Cancer Genomics

    Our research team focuses on understanding the genetic changes in cancer and how these genetic changes affect cancer behavior.  We have a particular focus on brain cancers, although we study many types of cancer.  All our projects involve collaborations with multiple other groups at the DFCI, Broad Institute, and multiple other institutions.

    We have undertaken a variety of genomic approaches to profiling large numbers of cancers, including the use of SNP arrays, expression arrays, and sequencing.  We have also developed several computational approaches to understand these data.

    For copy-number changes, which are some of the most frequent somatic genetic events in cancer, we developed an approach (GISTIC, for Genomic Identification of Significant Targets In Cancer) that simultaneously identifies those events that are most likely to drive cancer development and profiles individual specimens for the set of events they have undergone. We have used this approach to identify new oncogenes in several cancer types, including lung, esophageal, and colorectal cancers.  We published an analysis of over 3000 cancer copy-number profiles in 2010, which is one of the most-cited publications in cancer from that year.  This study identified two new amplified oncogenes (MCL1 and BCL2L1) and showed both lineage-specific genetic events and events that were shared across many cancer types.  We have also used this approach to identify prognostic indicators in endometrial cancers and predictors of pathway dependency several cancer types, including glioblastoma and renal cancer.

    We have performed integrated genomic analyses across multiple datasets.  For example, we have integrated copy-number data with functional screens to identify novel vulnerabilities associated with genomic losses in cancer.  

    We have performed high-throughput sequencing analyses of several cancer types. For example, we found mutations in SMO and AKT1 in meningiomas, which may serve as therapeutic targets in these diseases.  We have also found rearrangements of MYBL1 in pediatric low-grade gliomas.

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