Gene Fusions Create Partner and Collateral Dependencies Essential to Cancer Cell Survival

Abstract

Gene fusions frequently result from rearrangements in cancer genomes. In many instances, gene fusions play an important role in oncogenesis; in other instances, they are thought to be passenger events. Although regulatory element rearrangements and copy number alterations resulting from these structural variants are known to lead to transcriptional dysregulation across cancers, the extent to which these events result in functional dependencies with an impact on cancer cell survival is variable. Here we used CRISPR-Cas9 dependency screens to evaluate the fitness impact of 3,277 fusions across 645 cell lines from the Cancer Dependency Map. We found that 35% of cell lines harbored either a fusion partner dependency or a collateral dependency on a gene within the same topologically associating domain as a fusion partner. Fusion-associated dependencies revealed numerous novel oncogenic drivers and clinically translatable alterations. Broadly, fusions can result in partner and collateral dependencies that have biological and clinical relevance across cancer types.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jun 07, 2021
Source ID
10.1158/0008-5472.can-21-0791

Entities

People

  • Alexander Gusev
  • Alma Imamovic
  • Bo Kyung A. Seong
  • Brian J. Haas
  • Clement Ma
  • David Liu
  • Eliezer M. Van Allen
  • Felix Dietlein
  • Francisca Vazquez
  • Jake R. Conway
  • James M McFarland
  • Jesse S Boehm
  • Jett Crowdis
  • Jihye Park
  • Katherine A. Janeway
  • Kimberly Stegmaier
  • Kyuho Han
  • Meng Xiao He
  • Michael C Bassik
  • Neekesh Dharia
  • Riaz Gillani
  • Saif Alimohamed

Organizations

  • Dana–Farber Cancer Institute
  • Harvard Medical School
  • Harvard University
  • National Institutes of Health
  • St. Baldrick's Foundation
  • Stanford University
  • United States Department of Defense

Tags

Fields of Study

  • Biology

Readers

  • Geospatial Intelligence and Artificial Intelligence Analytics
  • Molecular Biology and Genetics
  • Molecular and Cellular Biology

Technology Areas

  • Biotechnology