About Gad A. Getz, PhD

Professor of Pathology, Harvard Medical School
Associate Investigator, Massachusetts General Hospital
Director of Bioinformatics, Massachusetts General Hospital Cancer Center and Department of Pathology
Paul C. Zamecnik Chair of Oncology, Massachusetts General Hospital Cancer Center 
Director, Cancer Genome Computational Analysis and Institute Member, Broad Institute
Contact email: ggetz1@mgh.harvard.edu

Affiliations 

Overview

Characterizing the cancer genome

Cancer is a disease of the genome that is driven by a combination of possible germline risk-alleles together with a set of “driver” somatic mutations that are acquired during the

clonal expansion of increasingly fitter clones. In order to generate a comprehensive list of all germline and somatic events that occurred during life and the development of the cancer, we are developing and applying highly sensitive and specific tools for detecting different types of mutations in massively-parallel sequencing data. The volume, noise and complexity of these data require developing computational tools using state-of-the-art statistical and machine learning approaches to extract the signal from the noise (e.g., MuTect, CapSeg, dRanger, BreakPointer, MSMuTect, etc.).

Detecting cancer-associated genes

Next, we analyze the detected events across a cohort of samples searching for genes/ pathways, as well as non-coding variants, that show significant signals of positive selection. To that end, we construct a statistical model of the background mutational processes and then detect genes that deviate from it. As part of constructing the models, we study and infer the mutational processes (using SignatureAnalyzer) that affected the samples (carcinogens, defects in repair mechanisms, etc.) and their timing.

We have developed tools for detecting significantly gained or lost genes in cancer (GISTIC) and genes with increased density or irregular patterns of mutations (MutSig suite, CLUMPS/ EMPRINT, MSMutSig, NetSig). Our work demonstrated the importance of modeling the heterogeneity of these models across patients, sequence contexts and the genome, when searching for cancer genes.

Heterogeneity and clonal evolution of cancer

Cancer samples are heterogeneous, containing a mixture of normal cells and cancer cells that often represents multiple subclones. We developed and continue to develop tools (ABSOLUTE, Phylogic, PhylogicNDT) for characterizing the heterogeneity of cancer samples using copy-number and mutation data measured on bulk samples and now also using single cells. Using these tools, we can infer which mutations are clonal or sub-clonal, as well as estimate the number of subclones and their distribution over space and time. We are now working to introduce these concepts to clinical trials and eventually clinical care.

Read more about the Getz Lab from the Center for Cancer Research Annual Report and the Pathology Basic Science Research Brochure.

Group Members

  • Francois Aguet, PhD 
  • Maryam Alsalah
  • Eila Arich-Landkof 
  • Rotem Ben-Hamo Deutsh, PhD
  • Chet Birger, PhD
  • Timothy Defreitas
  • Andrew Dunford
  • Samuel Freeman 
  • Gad Getz, PhD 
  • Manaswi Gupta
  • Kane Hadley
  • Megan Hanna
  • Nicholas Haradhvala 
  • David Heiman
  • Julian Hess 
  • Atanas Kamburov, PhD 
  • Jaegil Kim, PhD 
  • Kirsten Kubler, MD, PhD
  • Ignat Leshchiner, PhD 
  • Dimitri Livitz 
  • Sam Meier
  • Yosef Maruvka, PhD 
  • Michael Noble
  • Prasanna Parasuraman, PhD 
  • Paz Polak, PhD 
  • Esther Rheinbay, PhD 
  • Daniel Rosebrock 
  • Gordon Saksena
  • Eddie Salinas
  • Ayellet Segre, PhD 
  • Chip Stewart, PhD 
  • Timothy Sullivan 
  • Grace Tiao
  • Keren Yizhak, PhD
  • Hailei Zhang, PhD

Selected Publications

Bibliography of Gad Getz via PubMed

Rheinbay E, Parasuraman P, et al, Ellisen LW, Iafrate AJ, Boehm JS, Gabriel SB, Meyerson M, Golub TR, Baselga J, Hidalgo-Miranda A, Shioda T, Bernards A, Lander ES, Getz G. Recurrent and functional regulatory mutations in breast cancer. Nature. 2017; 547(7661):55-60.

Somatic ERCC2 mutations are associated with a distinct genomic signature in urothelial tumors. Kim J, Mouw KW, Polak P, Braunstein LZ, Kamburov A, Tiao G, Kwiatkowski DJ, Rosenberg JE, Van Allen EM, D'Andrea AD, Getz G. Nat Genet. 2016 Jun;48(6):600-6.

Mutational Strand Asymmetries in Cancer Genomes Reveal Mechanisms of DNA Damage and Repair.Haradhvala NJ, Polak P, Stojanov P, Covington KR, Shinbrot E, Hess JM, Rheinbay E, Kim J, Maruvka YE, Braunstein LZ, Kamburov A, Hanawalt PC, Wheeler DA, Koren A, Lawrence MS, Getz G. Cell. 2016 Jan 28;164(3):538-49.

Discovery and saturation analysis of cancer genes across 21 tumour types. Lawrence MS, Stojanov P, Mermel CH, Robinson JT, Garraway LA, Golub TR, Meyerson M, Gabriel SB, Lander ES, Getz G. Nature. 2014 Jan 23;505(7484):495-501.

Mutational heterogeneity in cancer and the search for new cancer-associated genes. Lawrence MS, Stojanov P, Polak P, Kryukov GV, Cibulskis K, Sivachenko A, Carter SL, Stewart C, Mermel CH, Roberts SA, Kiezun A, Hammerman PS, McKenna A, Drier Y, Zou L, Ramos AH, Pugh TJ, Stransky N, Helman E, Kim J, Sougnez C, Ambrogio L, Nickerson E, Shefler E, Cortés ML, Auclair D, Saksena G, Voet D, Noble M, DiCara D, Lin P, Lichtenstein L, Heiman DI, Fennell T, Imielinski M, Hernandez B, Hodis E, Baca S, Dulak AM, Lohr J, Landau DA, Wu CJ, Melendez-Zajgla J, Hidalgo-Miranda A, Koren A, McCarroll SA, Mora J, Lee RS, Crompton B, Onofrio R, Parkin M, Winckler W, Ardlie K, Gabriel SB, Roberts CW, Biegel JA, Stegmaier K, Bass AJ, Garraway LA, Meyerson M, Golub TR, Gordenin DA, Sunyaev S, Lander ES, Getz G. Nature. 2013 Jul 11;499(7457):214-8.

Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Cibulskis K, Lawrence MS, Carter SL, Sivachenko A, Jaffe D, Sougnez C, Gabriel S, Meyerson M, Lander ES, Getz G. Nat Biotechnol. 2013 Mar;31(3):213-9.