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
Large-scale dependency and drug screens characterize the therapeutic vulnerabilities of Multiple Myeloma with 1q
Sklavenitis-Pistofidis R, Lightbody ED, Reidy M et al. Blood 2025
Published 12 Mar 2025
Single-cell RNA sequencing defines distinct disease subtypes and reveals hypo-responsiveness to interferon in asymptomatic Waldenstrom's Macroglobulinemia
Sklavenitis-Pistofidis R, Konishi Y et al. Nat Commun 2025
Published 10 Feb 2025
DLBclass: A Probabilistic Molecular Classifier to Guide Clinical Investigation and Practice in DLBCL
Chapuy B, Wood TR, Stewart C et al. Blood 2024
Published 22 Dec 2024
Deeper evaluation of a single-cell foundation model
Boiarsky R et al. Nat Mach Intell 2024
Published 12 Dec 2024
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
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