Ubiquitin-specific-processing proteases (USPs), the largest deubiquitinating enzyme (DUB) subfamily, play critical roles in cancer. However, clinical utility of USPs is hindered by limited knowledge about their varied and substrate-dependent actions. Here, we performed a comprehensive investigation on pan-cancer impacts of USPs by integrating multi-omics data and annotated data resources, especially a deubiquitination network. Meaningful insights into the roles of 54 USPs in 29 types of cancers were generated. Although rare mutations were observed, a majority of USPs exhibited significant expressional alterations, prognostic impacts and strong correlations with cancer hallmark pathways. Notably, from our DUB-substrate interaction prediction model, additional USP-substrate interactions (USIs) were recognized to complement knowledge gap about cancer-relevant USIs. Intriguingly, expression signatures of the USIs revealed clinically meaningful cancer subtypes, where key USPs and substrates cooperatively contributed to significant prognosis differences among subtypes. Overall, this investigation provides a valuable resource to assist mechanism research and clinical utility about USPs.
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Scheffner M, Nuber U, Huibregtse JM. PRotein Ubiquitination Involving an E1-E2-E3 enzyme ubiquitin thioester cascade. Nature. 1995;373:81–3.
Nijman SMB, Luna-Vargas MPA, Velds A, Brummelkamp TR, Dirac AMG, Sixma TK, et al. A Genomic and functional inventory of deubiquitinating enzymes. Cell. 2005;123:773–86.
Li M, Chen D, Shiloh A, Luo J, Nikolaev AY, Qin J, et al. Deubiquitination of p53 by HAUSP is an important pathway for p53 stabilization. Nature. 2002;416:648–53.
Cummins JM, Rago C, Kohli M, Kinzler KW, Lengauer C, Vogelstein B. Tumour suppression: disruption of HAUSP gene stabilizes p53. Nature. 2004;428:486.
Li M, Brooks CL, Kon N, Gu W. A dynamic role of HAUSP in the p53-Mdm2 pathway. Mol Cell. 2004;13:879–86.
Zhu C, Ji X, Zhang H, Zhou Q, Cao X, Tang M, et al. Deubiquitylase USP9X suppresses tumorigenesis by stabilizing large tumor suppressor kinase 2 (LATS2) in the Hippo pathway. J Biol Chem. 2018;293:1178–91.
Toloczko A, Guo F, Yuen HF, Wen Q, Wood SA, Ong YS, et al. Deubiquitinating enzyme USP9X suppresses tumor growth via LATS kinase and core components of the hippo pathway. Cancer Res. 2017;77:4921–33.
Yang B, Zhang S, Wang Z, Yang C, Ouyang W, Zhou F, et al. Deubiquitinase USP9X deubiquitinates beta-catenin and promotes high grade glioma cell growth. Oncotarget. 2016;7:79515–25.
Weisberg EL, Schauer NJ, Yang J, Lamberto I, Doherty L, Bhatt S, et al. Inhibition of USP10 induces degradation of oncogenic FLT3. Nat Chem Biol. 2017;13:1207–15.
Sun J, Li T, Zhao Y, Huang L, Sun H, Wu H, et al. USP10 inhibits lung cancer cell growth and invasion by upregulating PTEN. Mol Cell Biochem. 2018;441:1–7.
Lu C, Ning Z, Wang A, Chen D, Liu X, Xia T, et al. USP10 suppresses tumor progression by inhibiting mTOR activation in hepatocellular carcinoma. Cancer Lett. 2018;436:139–48.
D’Arcy P, Brnjic S, Olofsson MH, Fryknas M, Lindsten K, De Cesare M, et al. Inhibition of proteasome deubiquitinating activity as a new cancer therapy. Nat Med. 2011;17:1636–40.
Huang X, Dixit VM. Drugging the undruggables: exploring the ubiquitin system for drug development. Cell Res. 2016;26:484–98.
Chauhan D, Tian Z, Nicholson B, Kumar KG, Zhou B, Carrasco R, et al. A small molecule inhibitor of ubiquitin-specific protease-7 induces apoptosis in multiple myeloma cells and overcomes bortezomib resistance. Cancer Cell. 2012;22:345–58.
Turnbull AP, Ioannidis S, Krajewski WW, Pinto-Fernandez A, Heride C, Martin ACL, et al. Molecular basis of USP7 inhibition by selective small-molecule inhibitors. Nature. 2017;550:481–6.
Davis MI, Pragani R, Fox JT, Shen M, Parmar K, Gaudiano EF, et al. Small molecule inhibition of the ubiquitin-specific protease USP2 accelerates cyclin D1 degradation and leads to cell cycle arrest in colorectal cancer and mantle cell lymphoma models. J Biol Chem. 2016;291:24628–40.
Yuan T, Yan FJ, Ying MD, Cao J, He QJ, Zhu H, et al. Inhibition of ubiquitin-specific proteases as a novel anticancer therapeutic strategy. Front Pharmacol. 2018;9:1080.
Chen D, Liu X, Xia T, Tekcham DS, Wang W, Chen H. et al. A Multidimensional Characterization of E3 Ubiquitin Ligase and Substrate Interaction Network. iScience. 2019;16:177–91.
Li Y, Xie P, Lu L, Wang J, Diao LH, Liu ZY, et al. An integrated bioinformatics platform for investigating the human E3 ubiquitin ligase-substrate interaction network. Nat Commun. 2017;8:347.
Cancer Genome Atlas Research N, Weinstein JN, Collisson EA, Mills GB, Shaw KR, Ozenberger BA, et al. The cancer genome atlas pan-cancer analysis project. Nat Genet. 2013;45:1113–20.
Wang Y, Xu X, Maglic D, Dill MT, Mojumdar K, Ng PK, et al. Comprehensive molecular characterization of the hippo signaling pathway in cancer. Cell Rep. 2018;25:1304–.e5.
Bailey MH, Tokheim C, Porta-Pardo E, Sengupta S, Bertrand D, Weerasinghe A, et al. Comprehensive characterization of cancer driver genes and mutations. Cell. 2018;174:1034–5.
Ge Z, Leighton JS, Wang Y, Peng X, Chen Z, Chen H, et al. Integrated genomic analysis of the ubiquitin pathway across cancer types. Cell Rep. 2018;23:213–26 e3.
Forbes SA, Beare D, Boutselakis H, Bamford S, Bindal N, Tate J, et al. COSMIC: somatic cancer genetics at high-resolution. Nucl Acids Res. 2017;45:D777–83.
Edwards NJ, Oberti M, Thangudu RR, Cai S, McGarvey PB, Jacob S, et al. The CPTAC data portal: a resource for cancer proteomics research. J Proteome Res. 2015;14:2707–13.
Trompouki E, Hatzivassiliou E, Tsichritzis T, Farmer H, Ashworth A, Mosialos G. CYLD is a deubiquitinating enzyme that negatively regulates NF-kappa B activation by TNFR family members. Nature. 2003;424:793–6.
Meuwissen ME, Schot R, Buta S, Oudesluijs G, Tinschert S, Speer SD, et al. Human USP18 deficiency underlies type 1 interferonopathy leading to severe pseudo-TORCH syndrome. J Exp Med. 2016;213:1163–74.
Nijman SM, Huang TT, Dirac AM, Brummelkamp TR, Kerkhoven RM, D’Andrea AD, et al. The deubiquitinating enzyme USP1 regulates the Fanconi anemia pathway. Mol cell. 2005;17:331–9.
Barabasi AL. Scale-free networks: a decade and beyond. Science. 2009;325:412–3.
Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000;25:25–9.
Yu DH, Hung MC. Overexpression of ErbB2 in cancer and ErbB2-targeting strategies. Oncogene. 2000;19:6115–21.
Kapoor A, Yao W, Ying H, Hua S, Liewen A, Wang Q, et al. Yap1 activation enables bypass of oncogenic Kras addiction in pancreatic cancer. Cell. 2014;158:185–97.
Landi S, Moreno V, Gioia-Patricola L, Guino E, Navarro M, de Oca J, et al. Association of common polymorphisms in inflammatory genes interleukin (IL)6, IL8, tumor necrosis factor alpha, NFKB1, and peroxisome proliferator-activated receptor gamma with colorectal cancer. Cancer Res. 2003;63:3560–6.
Wade M, Li YC, Wahl GM. MDM2, MDMX and p53 in oncogenesis and cancer therapy. Nat Rev Cancer. 2013;13:83–96.
Ishizawar R, Parsons SJ. c-Src and cooperating partners in human cancer. Cancer Cell. 2004;6:209–14.
Chan GKT, Jablonski SA, Sudakin V, Hittle JC, Yen TJ. Human BUBR1 is a mitotic checkpoint kinase that monitors CENP-E functions at kinetochores and binds the cyclosome/APC. J Cell Biol. 1999;146:941–54.
Brown NR, Lowe ED, Petri E, Skamnaki V, Antrobus R, Johnson LN. Cyclin B and cyclin A confer different substrate recognition properties on CDK2. Cell Cycle. 2007;6:1350–9.
Ronnstrand L. Signal transduction via the stem cell factor receptor/c-Kit. Cell Mol life Sci: CMLS. 2004;61:2535–48.
Sorrentino A, Thakur N, Grimsby S, Marcusson A, von Bulow V, Schuster N, et al. The type I TGF-beta receptor engages TRAF6 to activate TAK1 in a receptor kinase-independent manner. Nat Cell Biol. 2008;10:1199–207.
Barretina J, Caponigro G, Stransky N, Venkatesan K, Margolin AA, Kim S, et al. The cancer cell line encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature. 2012;483:603–7.
Srinivas NR. Clinical pharmacokinetics of panobinostat, a novel histone deacetylase (HDAC) inhibitor: review and perspectives. Xenobiotica. 2017;47:354–68.
Luise C, Capra M, Donzelli M, Mazzarol G, Jodice MG, Nuciforo P, et al. An atlas of altered expression of deubiquitinating enzymes in human cancer. PLoS ONE. 2011;6:e15891.
Chen M, Gutierrez GJ, Ronai ZA. Ubiquitin-recognition protein Ufd1 couples the endoplasmic reticulum (ER) stress response to cell cycle control. Proc Natl Acad Sci. 2011;108:9119–24.
Cotto-Rios XM, Jones MJK, Huang TT. Insights into phosphorylation-dependent mechanisms regulating USP1 protein stability during the cell cycle. Cell Cycle. 2011;10:4009–16.
Colaprico A, Silva TC, Olsen C, Garofano L, Cava C, Garolini D, et al. TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data. Nucl Acids Res. 2016;44:e71.
Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinf. 2008;9:559.
Tarca AL, Draghici S, Khatri P, Hassan SS, Mittal P, Kim JS, et al. A novel signaling pathway impact analysis. Bioinformatics. 2009;25:75–82.
Rani J, Shah AR, Ramachandran S. pubmed.mineR: an R package with text-mining algorithms to analyse PubMed abstracts. J Biosci. 2015;40:671–82.
Hanpude P, Bhattacharya S, Dey AK, Maiti TK. Deubiquitinating enzymes in cellular signaling and disease regulation. IUBMB life. 2015;67:544–55.
Kim MS, Pinto SM, Getnet D, Nirujogi RS, Manda SS, Chaerkady R, et al. A draft map of the human proteome. Nature. 2014;509:575–81.
Matsumoto M, Nishimura T. Mersenne Twister: a 623-dimensionally equidistributed uniform pseudo-random number generator. ACM Trans Model Comput Simul. 1998;8:28.
Chawla NV, Bowyer KW, Hall LO, Kegelmeyer WP. SMOTE: synthetic minority over-sampling technique. J Artif Intell Res. 2002;16:321–57.
Torgo L. Data Mining with R, learning with case studies. Chapman and Hall/CRC, Boca Raton, 2010.
Zhang JD, Wiemann S. KEGGgraph: a graph approach to KEGG PATHWAY in R and bioconductor. Bioinformatics. 2009;25:1470–1.
Wilkerson MD, Hayes DN. ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking. Bioinformatics. 2010;26:1572–3.
Li J, Zhao W, Akbani R, Liu W, Ju Z, Ling S, et al. Characterization of human cancer cell lines by reverse-phase protein arrays. Cancer Cell. 2017;31:225–39.
Breiman L. Random forests. Mach Learn. 2001;45:5–32.
Liaw AWM. Classification and regression by randomForest. R News. 2002;2:18–22.
Dedicated to the 70th anniversary of Dalian Institute of Chemical Physics, CAS. We thank Guowang Xu, Tongming Li, and all members of the Dr. Piao laboratory for helpful discussions and suggestions. This study is supported by the National Natural Science Foundation of China (Grant Nos. 81672440, 31701156, 81502024, and 81572881), Project funded by China Postdoctoral Science Foundation (No. 2017M611281), Innovation program of science and research from the DICP, CAS (DICP TMSR201601, DICP ZZBS201803).
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Chen, D., Ning, Z., Chen, H. et al. An integrative pan-cancer analysis of biological and clinical impacts underlying ubiquitin-specific-processing proteases. Oncogene 39, 587–602 (2020). https://doi.org/10.1038/s41388-019-1002-4