Genome-scale functional genomics identify genes preferentially essential for multiple myeloma cells compared to other neoplasias

Ricardo de Matos Simoes, Ryosuke Shirasaki, Sondra L. Downey-Kopyscinski, Geoffrey M. Matthews, Benjamin G. Barwick, Vikas A. Gupta, Daphné Dupéré-Richer, Shizuka Yamano, Yiguo Hu, Michal Sheffer, Eugen Dhimolea, Olga Dashevsky, Sara Gandolfi, Kazuya Ishiguro, Robin M. Meyers, Jordan G. Bryan, Neekesh V. Dharia, Paul J. Hengeveld, Johanna B. Brüggenthies, Huihui TangAndrew J. Aguirre, Quinlan L. Sievers, Benjamin L. Ebert, Brian J. Glassner, Christopher J. Ott, James E. Bradner, Nicholas P. Kwiatkowski, Daniel Auclair, Joan Levy, Jonathan J. Keats, Richard W. J. Groen, Nathanael S. Gray, Aedin C. Culhane, James M. McFarland, Joshua M. Dempster, Jonathan D. Licht, Lawrence H. Boise, William C. Hahn, Francisca Vazquez, Aviad Tsherniak, Constantine S. Mitsiades

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)

Abstract

Clinical progress in multiple myeloma (MM), an incurable plasma cell (PC) neoplasia, has been driven by therapies that have limited applications beyond MM/PC neoplasias and do not target specific oncogenic mutations in MM. Instead, these agents target pathways critical for PC biology yet largely dispensable for malignant or normal cells of most other lineages. Here we systematically characterized the lineage-preferential molecular dependencies of MM through genome-scale clustered regularly interspaced short palindromic repeats (CRISPR) studies in 19 MM versus hundreds of non-MM lines and identified 116 genes whose disruption more significantly affects MM cell fitness compared with other malignancies. These genes, some known, others not previously linked to MM, encode transcription factors, chromatin modifiers, endoplasmic reticulum components, metabolic regulators or signaling molecules. Most of these genes are not among the top amplified, overexpressed or mutated in MM. Functional genomics approaches thus define new therapeutic targets in MM not readily identifiable by standard genomic, transcriptional or epigenetic profiling analyses.
Original languageEnglish
Pages (from-to)754-773
Number of pages20
JournalNature Cancer
Volume4
Issue number5
DOIs
Publication statusPublished - 1 May 2023

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