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
Inferring early genetic progression in cancers with unobtainable premalignant disease
Leshchiner I, Mroz EA, Cha J et al. Nature Cancer 2023
Published 24 Apr 2023
Genomic and transcriptomic analysis of checkpoint blockade response in advanced non-small cell lung cancer
Ravi A, Hellmann MD, Arniella MB et al. Nature Genetics 2023
Published 06 Apr 2023
Evolutionary history of transformation from chronic lymphocytic leukemia to Richter syndrome
Parry EM, Leshchiner I, Guièze R et al. Nature Medicine 2023
Published 19 Jan 2023
MinimuMM-seq: Genome sequencing of circulating tumor cells for minimally invasive molecular characterization of multiple myeloma pathology
Dutta AK, Alberge JB et al. Cancer Discovery 2022
Published 07 Dec 2022
Single Cell Characterization of Myeloma and its Precursor Conditions Reveals Transcriptional Signatures of Early Tumorigenesis
Boiarsky R et al. Nature Communicatiopns 2022
Published 17 Nov 2022
Immune biomarkers of response to immunotherapy in patients with high-risk smoldering myeloma
Sklavenitis-Pistofidis R et al. Cancer Cell 2022
Published 14 Nov 2022