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
Detection of heterogeneous resistance mechanisms to tyrosine kinase inhibitors from cell-free DNA
Parsons HA, Messer C, Santos K, Weiss J et al. Cell Genom. 2025
Published 10 Dec 2025
Long-term Survival and Molecular Biomarker Evaluation of a Phase II Cetuximab and Nivolumab Clinical Trial in Recurrent/Metastatic Head and Neck Cancer
Chaudhary R, Moorhead G et al. Clin Cancer Res. 2025
Published 21 Oct 2025
Numbat-multiome: inferring copy number variations by combining RNA and chromatin accessibility information from single-cell data.
Li R et al. Briefings in Bioinformatics 2025
Published 31 Aug 2025
Tamoxifen induces PI3K activation in uterine cancer
Kübler K, Nardone A, et al. Nat Genet 2025
Published 22 Aug 2025
SWIFT-seq enables comprehensive single-cell transcriptomic profiling of circulating tumor cells in multiple myeloma and its precursors
Lightbody ED, Sklavenitis-Pistofidis R et al. Nat Cancer 2025
Published 08 Aug 2025
Genomic landscape of multiple myeloma and its precursor conditions
Alberge JB, Dutta AK, Poletti A et al. Nat Genet 2025
Published 21 May 2025
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Broad • 08 Oct 2025