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

Nat Cancer. 2023 May;4(5):754-773. doi: 10.1038/s43018-023-00550-x.

Ricardo de Matos Simoes ^# ¹ ² ³ ⁴, Ryosuke Shirasaki ^# ¹ ² ³ ⁴, Sondra L Downey-Kopyscinski ^# ¹ ² ³, Geoffrey M Matthews ^# ¹ ² ³, Benjamin G Barwick ^# ⁵, Vikas A Gupta ⁵, Daphné Dupéré-Richer ⁶, Shizuka Yamano ¹ ², Yiguo Hu ¹ ², Michal Sheffer ¹ ² ³ ⁴, Eugen Dhimolea ¹ ² ³ ⁴, Olga Dashevsky ¹ ² ³ ⁴, Sara Gandolfi ¹ ² ³ ⁴, Kazuya Ishiguro ¹ ², Robin M Meyers ³, Jordan G Bryan ³, Neekesh V Dharia ² ³ ⁷, Paul J Hengeveld ¹ ², Johanna B Brüggenthies ¹ ² ³, Huihui Tang ¹ ² ³ ⁴, Andrew J Aguirre ¹ ² ³, Quinlan L Sievers ¹ ² ³, Benjamin L Ebert ¹ ² ³, Brian J Glassner ¹ ² ³, Christopher J Ott ¹ ² ³ ⁸, James E Bradner ¹ ² ³, Nicholas P Kwiatkowski ² ⁹, Daniel Auclair ¹⁰, Joan Levy ¹⁰, Jonathan J Keats ¹¹, Richard W J Groen ¹ ¹², Nathanael S Gray ¹ ² ⁹, Aedin C Culhane ¹³ ¹⁴, James M McFarland ³, Joshua M Dempster ³, Jonathan D Licht ⁶, Lawrence H Boise ⁵, William C Hahn ¹ ² ³, Francisca Vazquez ¹⁵, Aviad Tsherniak ¹⁶, Constantine S Mitsiades ¹⁷ ¹⁸ ¹⁹ ²⁰

Affiliations

1 Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
2 Harvard Medical School, Boston, MA, USA.
3 Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
4 Ludwig Center at Harvard, Boston, MA, USA.
5 Department of Hematology and Medical Oncology and the Winship Cancer Institute, Emory University, Atlanta, GA, USA.
6 University of Florida Health Cancer Center, Gainesville, FL, USA.
7 Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
8 Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
9 Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA.
10 Multiple Myeloma Research Foundation, Norwalk, CT, USA.
11 Translational Genomics Research Institute, Phoenix, AZ, USA.
12 Department of Hematology, Amsterdam UMC, VU University Medical Center, Cancer Center Amsterdam, Amsterdam, the Netherlands.
13 Department of Data Sciences, Dana-Farber Cancer Institute & Harvard School of Public Health, Boston, MA, USA.
14 Limerick Digital Cancer Research Center, Health Research Institute, School of Medicine, University of Limerick, Limerick, Ireland.
15 Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA. vazquez@broadinstitute.org.
16 Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA. aviad@broadinstitute.org.
17 Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. constantine_mitsiades@dfci.harvard.edu.
18 Harvard Medical School, Boston, MA, USA. constantine_mitsiades@dfci.harvard.edu.
19 Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA. constantine_mitsiades@dfci.harvard.edu.
20 Ludwig Center at Harvard, Boston, MA, USA. constantine_mitsiades@dfci.harvard.edu.
# Contributed equally.

PMID: 37237081 DOI: 10.1038/s43018-023-00550-x

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.

Products

Cat. No.

Product Name

Description

Target

Research Area
HY-15776

HG-9-91-01

99.77%, SIK 抑制剂

Salt-inducible Kinase (SIK)

Inflammation/Immunology

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