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Doherty LM, Mills CE, Boswell SA, Liu X, Hoyt CT, Gyori B, Buhrlage SJ, Sorger PK. Integrating multi-omics data reveals function and therapeutic potential of deubiquitinating enzymes. eLife 2022; 11:72879. [PMID: 35737447 PMCID: PMC9225015 DOI: 10.7554/elife.72879] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 05/26/2022] [Indexed: 12/11/2022] Open
Abstract
Deubiquitinating enzymes (DUBs), ~100 of which are found in human cells, are proteases that remove ubiquitin conjugates from proteins, thereby regulating protein turnover. They are involved in a wide range of cellular activities and are emerging therapeutic targets for cancer and other diseases. Drugs targeting USP1 and USP30 are in clinical development for cancer and kidney disease respectively. However, the majority of substrates and pathways regulated by DUBs remain unknown, impeding efforts to prioritize specific enzymes for research and drug development. To assemble a knowledgebase of DUB activities, co-dependent genes, and substrates, we combined targeted experiments using CRISPR libraries and inhibitors with systematic mining of functional genomic databases. Analysis of the Dependency Map, Connectivity Map, Cancer Cell Line Encyclopedia, and multiple protein-protein interaction databases yielded specific hypotheses about DUB function, a subset of which were confirmed in follow-on experiments. The data in this paper are browsable online in a newly developed DUB Portal and promise to improve understanding of DUBs as a family as well as the activities of incompletely characterized DUBs (e.g. USPL1 and USP32) and those already targeted with investigational cancer therapeutics (e.g. USP14, UCHL5, and USP7).
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Affiliation(s)
- Laura M Doherty
- Harvard Medical School (HMS) Library of Integrated Network-based Cellular Signatures (LINCS) Center, Cambridge, United States.,Department of Cancer Biology and the Linde Program in Cancer Chemical Biology, Dana-Farber Cancer Institute, Boston, United States.,Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, United States.,Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Program in Therapeutic Science, Harvard Medical School, Boston, United States
| | - Caitlin E Mills
- Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Program in Therapeutic Science, Harvard Medical School, Boston, United States
| | - Sarah A Boswell
- Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Program in Therapeutic Science, Harvard Medical School, Boston, United States
| | - Xiaoxi Liu
- Department of Cancer Biology and the Linde Program in Cancer Chemical Biology, Dana-Farber Cancer Institute, Boston, United States.,Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, United States
| | - Charles Tapley Hoyt
- Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Program in Therapeutic Science, Harvard Medical School, Boston, United States
| | - Benjamin Gyori
- Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Program in Therapeutic Science, Harvard Medical School, Boston, United States
| | - Sara J Buhrlage
- Department of Cancer Biology and the Linde Program in Cancer Chemical Biology, Dana-Farber Cancer Institute, Boston, United States.,Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, United States
| | - Peter K Sorger
- Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Program in Therapeutic Science, Harvard Medical School, Boston, United States
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Zhou W, Li J, Lu X, Liu F, An T, Xiao X, Kuo ZC, Wu W, He Y. Derivation and Validation of a Prognostic Model for Cancer Dependency Genes Based on CRISPR-Cas9 in Gastric Adenocarcinoma. Front Oncol 2021; 11:617289. [PMID: 33732644 PMCID: PMC7959733 DOI: 10.3389/fonc.2021.617289] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2020] [Accepted: 01/06/2021] [Indexed: 12/12/2022] Open
Abstract
As a CRISPR-Cas9-based tool to help scientists to investigate gene functions, Cancer Dependency Map genes (CDMs) include an enormous series of loss-of-function screens based on genome-scale RNAi. These genes participate in regulating survival and growth of tumor cells, which suggests their potential as novel therapeutic targets for malignant tumors. By far, studies on the roles of CDMs in gastric adenocarcinoma (GA) are scarce and only a small fraction of CDMs have been investigated. In the present study, datasets of the differentially expressed genes (DEGs) were extracted from the TCGA-based (The Cancer Genome Atlas) GEPIA database, from which differentially expressed CDMs were determined. Functions and prognostic significance of these verified CDMs were evaluated using a series of bioinformatics methods. In all, 246 differentially expressed CDMs were determined, with 147 upregulated and 99 downregulated. Ten CDMs (ALG8, ATRIP, CCT6A, CFDP1, CINP, MED18, METTL1, ORC1, TANGO6, and PWP2) were identified to be prognosis-related and subsequently a prognosis model based on these ten CDMs was constructed. In comparison with that of patients with low risk in TCGA training, testing and GSE84437 cohort, overall survival (OS) of patients with high risk was significantly worse. It was then subsequently demonstrated that for this prognostic model, area under the ROC (receiver operating characteristic) curve was 0.771 and 0.697 for TCGA training and testing cohort respectively, justifying its reliability in predicting survival of GA patients. With the ten identified CDMs, we then constructed a nomogram to generate a clinically practical model. The regulatory networks and functions of the ten CDMs were then explored, the results of which demonstrated that as the gene significantly associated with survival of GA patients and Hazard ratio (HR), PWP2 promoted in-vitro invasion and migration of GA cell lines through the EMT signaling pathway. Therefore, in conclusion, the present study might help understand the prognostic significance and molecular functions of CDMs in GA.
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Affiliation(s)
- Wenjie Zhou
- Digestive Disease Center, Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.,Department of Gastrointestinal Surgery, First Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Junqing Li
- Digestive Disease Center, Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.,Department of Gastrointestinal Surgery, First Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Xiaofang Lu
- Department of Pathology, Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Fangjie Liu
- Department of Hematology, Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Tailai An
- Digestive Disease Center, Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Xing Xiao
- Scientific Research Centre, Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Zi Chong Kuo
- Digestive Disease Center, Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Wenhui Wu
- Digestive Disease Center, Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Yulong He
- Digestive Disease Center, Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.,Department of Gastrointestinal Surgery, First Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
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