American Association for Cancer Research
can-21-0791_supplementary_table_11_suppst11.xlsx (1.35 MB)

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

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posted on 2023-03-31, 04:41 authored by Riaz Gillani, Bo Kyung A. Seong, Jett Crowdis, Jake R. Conway, Neekesh V. Dharia, Saif Alimohamed, Brian J. Haas, Kyuho Han, Jihye Park, Felix Dietlein, Meng Xiao He, Alma Imamovic, Clement Ma, Michael C. Bassik, Jesse S. Boehm, Francisca Vazquez, Alexander Gusev, David Liu, Katherine A. Janeway, James M. McFarland, Kimberly Stegmaier, Eliezer M. Van Allen
Supplementary Data from Gene Fusions Create Partner and Collateral Dependencies Essential to Cancer Cell Survival


National Institutes of Health (NIH)

Innovation in Cancer Informatics Award

U.S. Department of Defense (DOD)

St. Baldrick's Foundation (SBF)



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. This study provides insights into how fusions contribute to fitness in different cancer contexts beyond partner-gene activation events, identifying partner and collateral dependencies that may have direct implications for clinical care.

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