The Getz Lab
Lab Overview

The Getz lab is focused on cancer genome analysis, which includes (i) somatic events that cause cancer or lead to development of resistance, (ii) germline events that increase the risk for getting cancer, and (iii) using these events to identify subtypes of the disease and their relationship to clinical parameters and/or treatment outcomes. The team is building tools that are part of a robust analytical pipeline to analyze data coming from various national/international collaborative cancer genome projects, and these tools are revolutionizing how we analyze cancer genomes and use them in clinical settings.

Cancer genome analysis in the Getz lab includes two major steps: (i) Characterization – cataloging of all genomic events and the mechanisms that created them during the clonal evolution of the cancer, comparing events at the DNA, RNA and protein levels between tumor and normal samples from an individual patient; and (ii) Interpretation – analysis of the characterization data across a cohort of patients with the aim of identifying the alterations in genes and pathways that cause cancer or increase its risk as well as identifying molecular subtypes of the disease, their markers, and relationship to clinical variables.

Recent Papers
Developmental mosaicism underlying EGFR-mutant lung cancer presenting with multiple primary tumors
Burr R, Leshchiner I, Costantino CL et al. Nat Cancer 2024
Published 25 Oct 2024
AnnoMate: Exploring and annotating integrated molecular data through custom interactive visualizations
Chu C, Messer C et al. Patterns 2024
Published 16 Sep 2024
Systematic identification of minor histocompatibility antigens predicts outcomes of allogeneic hematopoietic cell transplantation
Cieri N et al. Nat Biotechnol 2024
Published 21 Aug 2024
Clinical Outcomes and Evolution of Clonal Hematopoiesis in Patients with Newly Diagnosed Multiple Myeloma
Mouhieddine TH, Nzerem C et al. Cancer Res Commun 2023
Published 18 Dec 2023
Pan-cancer proteogenomocs connects oncogenic drivers to functional states
Li Y, Porta-Pardo E, Tokheim C, Bailey MH, Yaron TM et al. Cell 2023
Published 31 Aug 2023
Pan-cancer analysis of post-translational modifications reveals shared patterns of protein regulation
Geffen Y, Anand S, Akiyama Y, Yaron TM, Song Y et al. Cell 2023
Published 14 Aug 2023
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