References
- Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424. doi:https://doi.org/10.3322/caac.21492.
- Kamisawa T, Wood LD, Itoi T, Takaori K. Pancreatic cancer. Lancet. 2016;388(10039):73–85. doi:https://doi.org/10.1016/S0140-6736(16)00141-0.
- Gillen S, Schuster T, Meyer Zum Büschenfelde C, Friess H, Kleeff J. Preoperative/neoadjuvant therapy in pancreatic cancer: a systematic review and meta-analysis of response and resection percentages. PLoS Med. 2010;7(4):e1000267. doi:https://doi.org/10.1371/journal.pmed.1000267.
- Siegel R, Desantis C, Jemal A. Colorectal cancer statistics, 2014. CA Cancer J Clin. 2014;64(2):104–117. doi:https://doi.org/10.3322/caac.21220.
- Hidalgo M, Cascinu S, Kleeff J, et al. Addressing the challenges of pancreatic cancer: future directions for improving outcomes. Pancreatology. 2015;15(1):8–18. doi:https://doi.org/10.1016/j.pan.2014.10.001.
- Siegel RL, Miller KD, Jemal A. Cancer statistics, 2017. CA Cancer J Clin. 2017;67(1):7–30. doi:https://doi.org/10.3322/caac.21387.
- Singhi AD, Koay EJ, Chari ST, Maitra A. Early detection of pancreatic cancer: opportunities and challenges. Gastroenterology. 2019;156(7):2024–2040. doi:https://doi.org/10.1053/j.gastro.2019.01.259.
- Kleeff J, Korc M, Apte M, et al. Pancreatic cancer. Nat Rev Dis Primers. 2016;2:16022. doi:https://doi.org/10.1038/nrdp.2016.22.
- Birnbaum DJ, Bertucci F, Finetti P, Birnbaum D, Mamessier E. Molecular classification as prognostic factor and guide for treatment decision of pancreatic cancer. Biochim Biophys Acta Rev Cancer. 2018;1869(2):248–255. doi:https://doi.org/10.1016/j.bbcan.2018.02.001.
- Kimura H, Yamamoto H, Harada T, et al. CKAP4, a DKK1 receptor, is a biomarker in exosomes derived from pancreatic cancer and a molecular target for therapy. Clin Cancer Res. 2019;25(6):1936–1947. doi:https://doi.org/10.1158/1078-0432.CCR-18-2124.
- Zhao J, Zhai B, Gygi SP, Goldberg AL. mTOR inhibition activates overall protein degradation by the ubiquitin proteasome system as well as by autophagy. Proc Natl Acad Sci USA. 2015;112(52):15790–15797. doi:https://doi.org/10.1073/pnas.1521919112.
- Glickman MH, Ciechanover A. The ubiquitin–proteasome proteolytic pathway: destruction for the sake of construction. Physiol Rev. 2002;82(2):373–428. doi:https://doi.org/10.1152/physrev.00027.2001.
- Collins GA, Goldberg AL. The logic of the 26S proteasome. Cell. 2017;169(5):792–806. doi:https://doi.org/10.1016/j.cell.2017.04.023.
- Clague MJ, Urbé S. Ubiquitin: same molecule, different degradation pathways. Cell. 2010;143(5):682–685. doi:https://doi.org/10.1016/j.cell.2010.11.012.
- Goldberg AL. Functions of the proteasome: from protein degradation and immune surveillance to cancer therapy. Biochem Soc Trans. 2007;35(Pt 1):12–17. doi:https://doi.org/10.1042/BST0350012.
- Sawada MT, Morinaga C, Izumi K, Sawada H. The 26S proteasome assembly is regulated by a maturation-inducing hormone in starfish oocytes. Biochem Biophys Res Commun. 1999;254(2):338–344. doi:https://doi.org/10.1006/bbrc.1998.9948.
- Cohen-Kaplan V, Livneh I, Avni N, et al. p62- and ubiquitin-dependent stress-induced autophagy of the mammalian 26S proteasome. Proc Natl Acad Sci USA. 2016;113(47):E7490–E7499. doi:https://doi.org/10.1073/pnas.1615455113.
- Lin P-L, Chang JT, Wu D-W, Huang C-C, Lee H. Cytoplasmic localization of Nrf2 promotes colorectal cancer with more aggressive tumors via upregulation of PSMD4. Free Radic Biol Med. 2016;95:121–132. doi:https://doi.org/10.1016/j.freeradbiomed.2016.03.014.
- Fejzo MS, Anderson L, Chen H-W, et al. Proteasome ubiquitin receptor PSMD4 is an amplification target in breast cancer and may predict sensitivity to PARPi. Genes Chromosomes Cancer. 2017;56(8):589–597. doi:https://doi.org/10.1002/gcc.22459.
- Midorikawa Y, Tsutsumi S, Taniguchi H, et al. Identification of genes associated with dedifferentiation of hepatocellular carcinoma with expression profiling analysis. Jpn J Cancer Res. 2002;93(6):636–643. doi:https://doi.org/10.1111/j.1349-7006.2002.tb01301.x.
- Fararjeh AS, Chen L-C, Ho Y-S, et al. Proteasome 26S subunit, non-ATPase 3 (PSMD3) regulates breast cancer by stabilizing HER2 from degradation. Cancers (Basel). 2019;11(4):527. doi:https://doi.org/10.3390/cancers11040527.
- Zhi T, Jiang K, Xu X, et al. ECT2/PSMD14/PTTG1 axis promotes the proliferation of glioma through stabilizing E2F1. Neuro Oncol. 2019;21(4):462–473. doi:https://doi.org/10.1093/neuonc/noy207.
- Hutter C, Zenklusen JC. The cancer genome atlas: creating lasting value beyond its data. Cell. 2018;173(2):283–285. doi:https://doi.org/10.1016/j.cell.2018.03.042.
- Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biol. 2010;11(10):R106. doi:https://doi.org/10.1186/gb-2010-11-10-r106.
- Yip SH, Wang P, Kocher J-PA, Sham PC, Wang J. Linnorm: improved statistical analysis for single cell RNA-seq expression data. Nucleic Acids Res. 2017;45(22):e179. doi:https://doi.org/10.1093/nar/gkx828.
- Yip SH, Wang P, Kocher J-PA, Sham PC, Wang J. Corrigendum: Linnorm: improved statistical analysis for single cell RNA-seq expression data. Nucleic Acids Res. 2017;45(22):13097. doi:https://doi.org/10.1093/nar/gkx1189.
- McIntyre CA, Winter JM. Diagnostic evaluation and staging of pancreatic ductal adenocarcinoma. Semin Oncol. 2015;42(1):19–27. doi:https://doi.org/10.1053/j.seminoncol.2014.12.003.
- Liao X, Huang K, Huang R, et al. Genome-scale analysis to identify prognostic markers in patients with early-stage pancreatic ductal adenocarcinoma after pancreaticoduodenectomy. Onco Targets Ther. 2017;10:4493–4506. doi:https://doi.org/10.2147/OTT.S142557.
- Yang C, Yu T, Liu Z, et al. Cystatin F as a key family 2 cystatin subunit and prognostic biomarker for early‑stage pancreatic ductal adenocarcinoma. Oncol Rep. 2019;42(1):79–90.
- Andersson T, Alfredsson L, Källberg H, Zdravkovic S, Ahlbom A. Calculating measures of biological interaction. Eur J Epidemiol. 2005;20(7):575–579. doi:https://doi.org/10.1007/s10654-005-7835-x.
- Wolbers M, Koller MT, Witteman JCM, Steyerberg EW. Prognostic models with competing risks: methods and application to coronary risk prediction. Epidemiology. 2009;20(4):555–561. doi:https://doi.org/10.1097/EDE.0b013e3181a39056.
- Iasonos A, Schrag D, Raj GV, Panageas KS. How to build and interpret a nomogram for cancer prognosis. J Clin Oncol. 2008;26(8):1364–1370. doi:https://doi.org/10.1200/JCO.2007.12.9791.
- Liao X, Yu T, Yang C, et al. Comprehensive investigation of key biomarkers and pathways in hepatitis B virus-related hepatocellular carcinoma. J Cancer. 2019;10(23):5689–5704. doi:https://doi.org/10.7150/jca.31287.
- Liao X, Wang X, Huang K, et al. Integrated analysis of competing endogenous RNA network revealing potential prognostic biomarkers of hepatocellular carcinoma. J Cancer. 2019;10(14):3267–3283. doi:https://doi.org/10.7150/jca.29986.
- Ryan CJ, Smith MR, de Bono JS, Molina A, et al. Abiraterone in metastatic prostate cancer without previous chemotherapy. N Engl J Med. 2013;368(2):138–148. doi:https://doi.org/10.1056/NEJMoa1209096.
- Tang Z, Li C, Kang B, Gao G, Li C, Zhang Z. GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res. 2017;45(W1):W98-W102. doi: https://doi.org/10.1093/nar/gkx247.
- Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics. 2008;9:559. doi:https://doi.org/10.1186/1471-2105-9-559.
- Xia J, Benner MJ, Hancock REW. NetworkAnalyst-integrative approaches for protein–protein interaction network analysis and visual exploration. Nucleic Acids Res. 2014;42(Web Server issue):W167–W174. doi:https://doi.org/10.1093/nar/gku443.
- Szklarczyk D, Franceschini A, Wyder S, et al. STRING v10: protein–protein interaction networks, integrated over the tree of life. Nucleic Acids Res. 2015;43(Database issue):D447–D452. doi:https://doi.org/10.1093/nar/gku1003.
- Mostafavi S, Morris Q. Combining many interaction networks to predict gene function and analyze gene lists. Proteomics. 2012;12(10):1687–1696. doi:https://doi.org/10.1002/pmic.201100607.
- Szklarczyk D, Gable AL, Lyon D, et al. STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47(D1):D607–D613. doi:https://doi.org/10.1093/nar/gky1131.
- Subramanian A, Tamayo P, Mootha VK, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA. 2005;102(43):15545–15550. doi:https://doi.org/10.1073/pnas.0506580102.
- Wang J, Vasaikar S, Shi Z, Greer M, Zhang B. WebGestalt 2017: a more comprehensive, powerful, flexible and interactive gene set enrichment analysis toolkit. Nucleic Acids Res. 2017;45(W1):W130–W137. doi:https://doi.org/10.1093/nar/gkx356.
- Liberzon A, Birger C, Thorvaldsdóttir H, Ghandi M, Mesirov JP, Tamayo P. The molecular signatures database (MSigDB) hallmark gene set collection. Cell Syst. 2015;1(6):417–425. doi:https://doi.org/10.1016/j.cels.2015.12.004.
- Glickman ME, Rao SR, Schultz MR. False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies . J Clin Epidemiol. 2014;67(8):850–857. doi:https://doi.org/10.1016/j.jclinepi.2014.03.012.
- Benjamini Y, Drai D, Elmer G, Kafkafi N, Golani I. Controlling the false discovery rate in behavior genetics research. Behav Brain Res. 2001;125(1–2):279–284. doi:https://doi.org/10.1016/S0166-4328(01)00297-2.
- Li J-T, Yin M, Wang D, et al. BCAT2-mediated BCAA catabolism is critical for development of pancreatic ductal adenocarcinoma. Nat Cell Biol. 2020;22(2):167–174. doi:https://doi.org/10.1038/s41556-019-0455-6.
- Weng C-C, Lin Y-C, Cheng K-H. The use of genetically engineered mouse models for studying the function of mutated driver genes in pancreatic cancer. J Clin Med. 2019;8(9):1369. doi: https://doi.org/10.3390/jcm8091369.
- Brown ZJ, Heinrich B, Greten TF. Mouse models of hepatocellular carcinoma: an overview and highlights for immunotherapy research. Nat Rev Gastroenterol Hepatol. 2018;15(9):536–554. doi:https://doi.org/10.1038/s41575-018-0033-6.
- Iñarrairaegui M, Melero I, Sangro B. Immunotherapy of hepatocellular carcinoma: facts and hopes. Clin Cancer Res. 2018;24(7):1518–1524. doi:https://doi.org/10.1158/1078-0432.CCR-17-0289.
- Prieto J, Melero I, Sangro B. Immunological landscape and immunotherapy of hepatocellular carcinoma. Nat Rev Gastroenterol Hepatol. 2015;12(12):681–700. doi:https://doi.org/10.1038/nrgastro.2015.173.
- Herbst RS, Morgensztern D, Boshoff C. The biology and management of non-small cell lung cancer. Nature. 2018;553(7689):446–454. doi:https://doi.org/10.1038/nature25183.
- Rizvi NA, Peters S. Immunotherapy for unresectable stage iii non-small-cell lung cancer. N Engl J Med. 2017;377(20):1986–1988. doi:https://doi.org/10.1056/NEJMe1711430.
- Young K, Hughes DJ, Cunningham D, Starling N. Immunotherapy and pancreatic cancer: unique challenges and potential opportunities. Ther Adv Med Oncol. 2018;10:1758835918816281. doi:https://doi.org/10.1177/1758835918816281.
- Menon S, Shin S, Dy G. Advances in cancer immunotherapy in solid tumors. Cancers (Basel). 2016;8(12):106. doi:https://doi.org/10.3390/cancers8120106.
- Balachandran VP, Beatty GL, Dougan SK. Broadening the impact of immunotherapy to pancreatic cancer: challenges and opportunities. Gastroenterology. 2019;156(7):2056–2072. doi:https://doi.org/10.1053/j.gastro.2018.12.038.
- Van Cutsem E, Vervenne WL, Bennouna J, et al. Phase III trial of bevacizumab in combination with gemcitabine and erlotinib in patients with metastatic pancreatic cancer. J Clin Oncol. 2009;27(13):2231–2237. doi:https://doi.org/10.1200/JCO.2008.20.0238.
- Torres C, Grippo PJ. Pancreatic cancer subtypes: a roadmap for precision medicine. Ann Med. 2018;50(4):277–287. doi:https://doi.org/10.1080/07853890.2018.1453168.
- Willett WC. Diet and cancer. Oncologist. 2000;5(5):393–404. doi:https://doi.org/10.1634/theoncologist.5-5-393.
- Bosetti C, Bertuccio P, Negri E, La Vecchia C, Zeegers MP, Boffetta P. Pancreatic cancer: overview of descriptive epidemiology. Mol Carcinog. 2012;51(1):3–13. doi:https://doi.org/10.1002/mc.20785.
- Moore A, Donahue T. Pancreatic cancer. JAMA. 2019;322(14):1426 doi:https://doi.org/10.1001/jama.2019.14699.
- Sakamoto K, Sato Y, Shinka T, et al. Proteasome subunits mRNA expressions correlate with male BMI: implications for a role in obesity. Obesity (Silver Spring). 2009;17(5):1044–1049. doi:https://doi.org/10.1038/oby.2008.612.
- Sakamoto K, Sato Y, Sei M, Ewis AA, Nakahori Y. Proteasome activity correlates with male BMI and contributes to the differentiation of adipocyte in hADSC. Endocrine. 2010;37(2):274–279. doi:https://doi.org/10.1007/s12020-009-9298-4.
- Cho YS, Chen C-H, Hu C, MuTHER Consortium, et al. Meta-analysis of genome-wide association studies identifies eight new loci for type 2 diabetes in east Asians. Nat Genet. 2011;44(1):67–72. doi:https://doi.org/10.1038/ng.1019.
- Chen M, Hu C, Zhang R, et al. A variant of PSMD6 is associated with the therapeutic efficacy of oral antidiabetic drugs in Chinese type 2 diabetes patients. Sci Rep. 2015;5:10701. doi:https://doi.org/10.1038/srep10701.
- Keaton JM, Cooke Bailey JN, Palmer ND, et al. A comparison of type 2 diabetes risk allele load between African Americans and European Americans. Hum Genet. 2014;133(12):1487–1495. doi:https://doi.org/10.1007/s00439-014-1486-5.
- Zhang L, Sanagapalli S, Stoita A. Challenges in diagnosis of pancreatic cancer. World J Gastroenterol. 2018;24(19):2047–2060. doi:https://doi.org/10.3748/wjg.v24.i19.2047.
- Hayes DF. HER2 and breast cancer: a phenomenal success story. N Engl J Med. 2019;381(13):1284–1286. doi:https://doi.org/10.1056/NEJMcibr1909386.
- Yu G, Li N, Wang W, Niu M, Feng X. p28GANK overexpression is associated with chemotherapy resistance and poor prognosis in ovarian cancer. Oncol Lett. 2020;19(1):505–512.
- Yang F, Zhang L, Wang F, Wang Y, Huo X-S, Yin Y-x, et al. Modulation of the unfolded protein response is the core of microRNA-122-involved sensitivity to chemotherapy in hepatocellular carcinoma. Neoplasia. 2011;13(7):590–600. doi:https://doi.org/10.1593/neo.11422.
- Li J, Tian F, Li D, et al. MiR-605 represses PSMD10/Gankyrin and inhibits intrahepatic cholangiocarcinoma cell progression. FEBS Lett. 2014;588(18):3491–3500. doi:https://doi.org/10.1016/j.febslet.2014.08.008.
- Luo G, Hu N, Xia X, Zhou J, Ye C. RPN11 deubiquitinase promotes proliferation and migration of breast cancer cells. Mol Med Rep. 2017;16(1):331–338. doi:https://doi.org/10.3892/mmr.2017.6587.
- Song Y, Li S, Ray A, et al. Blockade of deubiquitylating enzyme Rpn11 triggers apoptosis in multiple myeloma cells and overcomes bortezomib resistance. Oncogene. 2017;36(40):5631–5638. doi:https://doi.org/10.1038/onc.2017.172.
- Wang B, Ma A, Zhang L, et al. POH1 deubiquitylates and stabilizes E2F1 to promote tumour formation. Nat Commun. 2015;6:8704. doi:https://doi.org/10.1038/ncomms9704.
- Wang C-H, Lu S-X, Liu L-L, et al. POH1 knockdown induces cancer cell apoptosis via p53 and Bim. Neoplasia. 2018;20(5):411–424. doi:https://doi.org/10.1016/j.neo.2018.02.005.
- Lv J, Zhang S, Wu H, et al. Deubiquitinase PSMD14 enhances hepatocellular carcinoma growth and metastasis by stabilizing GRB2. Cancer Lett. 2020;469:22–34. doi:https://doi.org/10.1016/j.canlet.2019.10.025.
- Goldberg AL. Development of proteasome inhibitors as research tools and cancer drugs. J Cell Biol. 2012;199(4):583–588. doi:https://doi.org/10.1083/jcb.201210077.
- Clague MJ, Heride C, Urbé S. The demographics of the ubiquitin system. Trends Cell Biol. 2015;25(7):417–426. doi:https://doi.org/10.1016/j.tcb.2015.03.002.
- Ciechanover A. Intracellular protein degradation: from a vague idea through the lysosome and the ubiquitin–proteasome system and onto human diseases and drug targeting. Bioorg Med Chem. 2013;21(12):3400–3410. doi:https://doi.org/10.1016/j.bmc.2013.01.056.
- Grabbe C, Husnjak K, Dikic I. The spatial and temporal organization of ubiquitin networks. Nat Rev Mol Cell Biol. 2011;12(5):295–307. doi:https://doi.org/10.1038/nrm3099.
- Mocciaro A, Rape M. Emerging regulatory mechanisms in ubiquitin-dependent cell cycle control. J Cell Sci. 2012;125(Pt 2):255–263. doi:https://doi.org/10.1242/jcs.091199.
- Hyer ML, Milhollen MA, Ciavarri J, et al. A small-molecule inhibitor of the ubiquitin activating enzyme for cancer treatment. Nat Med. 2018;24(2):186–193. doi:https://doi.org/10.1038/nm.4474.
- Deshaies RJ. Proteotoxic crisis, the ubiquitin-proteasome system, and cancer therapy. BMC Biol. 2014;12:94. doi:https://doi.org/10.1186/s12915-014-0094-0.
- Wang L, Zhao L, Wei G, et al. Homoharringtonine could induce quick protein synthesis of PSMD11 through activating MEK1/ERK1/2 signaling pathway in pancreatic cancer cells. J Cell Biochem. 2018;119(8):6644–6656. doi:https://doi.org/10.1002/jcb.26847.
- Burki TK. Molecular subgroups of pancreatic cancer. Lancet Oncol. 2016;17(4):e139. doi:https://doi.org/10.1016/S1470-2045(16)00153-4.
- Waddell N, Pajic M, Patch AM, Australian Pancreatic Cancer Genome Initiative, et al. Whole genomes redefine the mutational landscape of pancreatic cancer. Nature. 2015;518(7540):495–501. doi:https://doi.org/10.1038/nature14169.
- Jones S, Zhang X, Parsons DW, et al. Core signaling pathways in human pancreatic cancers revealed by global genomic analyses. Science. 2008;321(5897):1801–1806. doi:https://doi.org/10.1126/science.1164368.
- Wang L, Tsutsumi S, Kawaguchi T, et al. Whole-exome sequencing of human pancreatic cancers and characterization of genomic instability caused by MLH1 haploinsufficiency and complete deficiency. Genome Res. 2012;22(2):208–219. doi:https://doi.org/10.1101/gr.123109.111.
- Furuyama T, Tanaka S, Shimada S, et al. Proteasome activity is required for the initiation of precancerous pancreatic lesions. Sci Rep. 2016;6:27044. doi:https://doi.org/10.1038/srep27044.
- Waters AM, Der CJ. KRAS: the critical driver and therapeutic target for pancreatic cancer. Cold Spring Harb Perspect Med. 2018;8(9):a031435. doi:https://doi.org/10.1101/cshperspect.a031435.
- Vaseva AV, Blake DR, Gilbert TSK, et al. KRAS suppression-induced degradation of MYC is antagonized by a MEK5-ERK5 compensatory mechanism. Cancer Cell. 2018;34(5):807–822.e807. doi:https://doi.org/10.1016/j.ccell.2018.10.001.
- George G, Singh S, Lokappa SB, Varkey J. Gene co-expression network analysis for identifying genetic markers in Parkinson's disease: a three-way comparative approach. Genomics. 2019;111(4):819–830. doi:https://doi.org/10.1016/j.ygeno.2018.05.005.
- Lando M, Fjeldbo CS, Wilting SM, C Snoek B, et al. Interplay between promoter methylation and chromosomal loss in gene silencing at 3p11–p14 in cervical cancer. Epigenetics. 2015;10(10):970–980. doi:https://doi.org/10.1080/15592294.2015.1085140.
- Lando M, Wilting SM, Snipstad K, et al. Identification of eight candidate target genes of the recurrent 3p12–p14 loss in cervical cancer by integrative genomic profiling. J Pathol. 2013;230(1):59–69. doi:https://doi.org/10.1002/path.4168.