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Identifying Potential Prognostic Markers for Muscle-Invasive Bladder Urothelial Carcinoma by Weighted Gene Co-Expression Network Analysis

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Pathology & Oncology Research

Abstract

Muscle-invasive bladder urothelial carcinoma (MIBC) is characterized as a genetic heterogeneous cancer with a high percentage of recurrence and worse prognosis. Identify the prognostic potentials of novel genes for muscle-invasive urothelial bladder cancer could at least provide important information for early detection and clinical treatment. Weighted gene co-expression network analysis (WGCNA) algorithm, a powerful systems biology approach, was utilized to extract co-expressed gene networks from mRNA expression dataset to construct transcriptional modules in MIBC samples, which was associated with demographic and clinical traits of MIBC patients. The potential prognostic markers of MIBC were screened out in the discovery dataset and verified in an independent external validation dataset. A total of 8 co-expression modules were detected through the WGCNA algorithm in the discovery datasets based on 401 MIBC samples. One transcriptional module enriched in cell development was observed to be correlated with the MIBC prognosis in the discovery datasets (HR = 1.48, 95%CI = 1.04–2.11) and independently verified in an external dataset (HR = 3.59, 95%CI = 1.09–11.79). High expression of hub genes including discoidin domain receptor tyrosine kinase 2 (DDR2), PDZ and LIM domain 3 (PDLIM3), zinc finger protein 521 (ZNF521), methionine sulfoxide reductase B3 (MSRB3) were significantly associated with the unfavorable survival of MIBC patients. We identified and validated four novel potential biomarkers associated with prognosis of MIBC patients by constructing genes co-expression networks. The discovery of these genetic markers may provide a new target for the development of MIBC chemotherapeutic drugs.

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References

  1. Antoni S, Ferlay J, Soerjomataram I, Znaor A, Jemal A, Bray F (2017) Bladder Cancer incidence and mortality: a global overview and recent trends. Eur Urol 71(1):96–108. https://doi.org/10.1016/j.eururo.2016.06.010

    Article  PubMed  Google Scholar 

  2. Kamat AM, Hahn NM, Efstathiou JA, Lerner SP, Malmström P-U, Choi W, Guo CC, Lotan Y, Kassouf W (2016) Bladder cancer. Lancet 388(10061):2796–2810. https://doi.org/10.1016/s0140-6736(16)30512-8

    Article  PubMed  Google Scholar 

  3. Migita T, Ueda A, Ohishi T, Hatano M, Seimiya H, Horiguchi SI, Koga F, Shibasaki F (2017) Epithelial-mesenchymal transition promotes SOX2 and NANOG expression in bladder cancer. Lab Invest 97:567–576. https://doi.org/10.1038/labinvest.2017.17

    Article  CAS  Google Scholar 

  4. Baumgart E, Cohen MS, Silva Neto B, Jacobs MA, Wotkowicz C, Rieger-Christ KM, Biolo A, Zeheb R, Loda M, Libertino JA, Summerhayes IC (2007) Identification and prognostic significance of an epithelial-mesenchymal transition expression profile in human bladder tumors. Clinical cancer research : an official journal of the American association for. Cancer Res 13(6):1685–1694. https://doi.org/10.1158/1078-0432.CCR-06-2330

    Article  CAS  Google Scholar 

  5. Grossman HB, Natale RB, Tangen CM, Speights VO, Vogelzang NJ, Trump DL, deVere White RW, Sarosdy MF, Wood DP Jr, Raghavan D, Crawford ED (2003) Neoadjuvant chemotherapy plus cystectomy compared with cystectomy alone for locally advanced bladder cancer. N Engl J Med 349(9):859–866. https://doi.org/10.1056/NEJMoa022148

    Article  CAS  PubMed  Google Scholar 

  6. Amir S, Mabjeesh NJ (2017) microRNA expression profiles as decision-making biomarkers in the management of bladder cancer. Histol Histopathol 32(2):107–119. https://doi.org/10.14670/HH-11-814

    Article  CAS  PubMed  Google Scholar 

  7. Dudek AM, van Kampen JGM, Witjes JA, Kiemeney L, Verhaegh GW (2018) LINC00857 expression predicts and mediates the response to platinum-based chemotherapy in muscle-invasive bladder cancer. Cancer Med 7:3342–3350. https://doi.org/10.1002/cam4.1570

    Article  CAS  PubMed Central  Google Scholar 

  8. Siegel RL, Miller KD, Jemal A (2018) Cancer statistics, 2018. CA Cancer J Clin 68(1):7–30. https://doi.org/10.3322/caac.21442

    Article  PubMed  Google Scholar 

  9. Kiselyov A, Bunimovich-Mendrazitsky S, Startsev V (2016) Key signaling pathways in the muscle-invasive bladder carcinoma: clinical markers for disease modeling and optimized treatment. Int J Cancer 138(11):2562–2569. https://doi.org/10.1002/ijc.29918

    Article  CAS  PubMed  Google Scholar 

  10. Masson-Lecomte A, Rava M, Real FX, Hartmann A, Allory Y, Malats N (2014) Inflammatory biomarkers and bladder cancer prognosis: a systematic review. Eur Urol 66(6):1078–1091. https://doi.org/10.1016/j.eururo.2014.07.033

    Article  CAS  PubMed  Google Scholar 

  11. Clarke C, Madden SF, Doolan P, Aherne ST, Joyce H, O'Driscoll L, Gallagher WM, Hennessy BT, Moriarty M, Crown J, Kennedy S, Clynes M (2013) Correlating transcriptional networks to breast cancer survival: a large-scale coexpression analysis. Carcinogenesis 34(10):2300–2308. https://doi.org/10.1093/carcin/bgt208

    Article  CAS  PubMed  Google Scholar 

  12. Oros Klein K, Oualkacha K, Lafond MH, Bhatnagar S, Tonin PN, Greenwood CM (2016) Gene Coexpression analyses differentiate networks associated with diverse cancers harboring TP53 missense or null mutations. Front Genet 7:137. https://doi.org/10.3389/fgene.2016.00137

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Guo L, Zhang K, Bing Z (2017) Application of a coexpression network for the analysis of aggressive and nonaggressive breast cancer cell lines to predict the clinical outcome of patients. Mol Med Rep 16(6):7967–7978. https://doi.org/10.3892/mmr.2017.7608

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Robertson AG, Kim J, Al-Ahmadie H, Bellmunt J, Guo G, Cherniack AD, Hinoue T, Laird PW, Hoadley KA, Akbani R, Castro MAA, Gibb EA, Kanchi RS, Gordenin DA, Shukla SA, Sanchez-Vega F, Hansel DE, Czerniak BA, Reuter VE, Su X, de Sa Carvalho B, Chagas VS, Mungall KL, Sadeghi S, Pedamallu CS, Lu Y, Klimczak LJ, Zhang J, Choo C, Ojesina AI, Bullman S, Leraas KM, Lichtenberg TM, Wu CJ, Schultz N, Getz G, Meyerson M, Mills GB, McConkey DJ, Network TR, Weinstein JN, Kwiatkowski DJ, Lerner SP (2017) Comprehensive molecular characterization of muscle-invasive bladder Cancer. Cell 171(3):540–556 e525. https://doi.org/10.1016/j.cell.2017.09.007

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Rebouissou S, Bernard-Pierrot I, de Reynies A, Lepage ML, Krucker C, Chapeaublanc E, Herault A, Kamoun A, Caillault A, Letouze E, Elarouci N, Neuzillet Y, Denoux Y, Molinie V, Vordos D, Laplanche A, Maille P, Soyeux P, Ofualuka K, Reyal F, Biton A, Sibony M, Paoletti X, Southgate J, Benhamou S, Lebret T, Allory Y, Radvanyi F (2014) EGFR as a potential therapeutic target for a subset of muscle-invasive bladder cancers presenting a basal-like phenotype. Sci Transl Med 6(244):244ra291. https://doi.org/10.1126/scitranslmed.3008970

    Article  CAS  Google Scholar 

  16. Mak MP, Tong P, Diao L, Cardnell RJ, Gibbons DL, William WN, Skoulidis F, Parra ER, Rodriguez-Canales J, Wistuba II, Heymach JV, Weinstein JN, Coombes KR, Wang J, Byers LA (2016) A patient-derived, pan-Cancer EMT signature identifies global molecular alterations and immune target enrichment following epithelial-to-mesenchymal transition. Clin Cancer Res 22(3):609–620. https://doi.org/10.1158/1078-0432.CCR-15-0876

    Article  CAS  PubMed  Google Scholar 

  17. Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15(12):550. https://doi.org/10.1186/s13059-014-0550-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Langfelder P, Horvath S (2008) WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 9:559. https://doi.org/10.1186/1471-2105-9-559

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Zhang B, Horvath S (2005) A general framework for weighted gene co-expression network analysis. Stat Appl Genet Mol Biol 4:Article17. https://doi.org/10.2202/1544-6115.1128

    Article  PubMed  Google Scholar 

  20. Yuan L, Chen L, Qian K, Qian G, Wu CL, Wang X, Xiao Y (2017) Co-expression network analysis identified six hub genes in association with progression and prognosis in human clear cell renal cell carcinoma (ccRCC). Genom Data 14:132–140. https://doi.org/10.1016/j.gdata.2017.10.006

    Article  PubMed  PubMed Central  Google Scholar 

  21. Yu G, Wang LG, Han Y, He QY (2012) clusterProfiler: an R package for comparing biological themes among gene clusters. Omics : a Journal Of Integrative Biology 16(5):284–287. https://doi.org/10.1089/omi.2011.0118

    Article  CAS  PubMed  Google Scholar 

  22. Achkar T, Parikh RA (2018) Adjuvant therapy in muscle-invasive bladder Cancer and upper tract urothelial carcinoma. Urol Clin N Am 45(2):257–266. https://doi.org/10.1016/j.ucl.2017.12.010

    Article  Google Scholar 

  23. Hermans TJN, Voskuilen CS, van der Heijden MS, Schmitz-Drager BJ, Kassouf W, Seiler R, Kamat AM, Grivas P, Kiltie AE, Black PC, van Rhijn BWG (2017) Neoadjuvant treatment for muscle-invasive bladder cancer: the past, the present, and the future. Urol Oncol 36:413–422. https://doi.org/10.1016/j.urolonc.2017.10.014

    Article  CAS  PubMed  Google Scholar 

  24. Tsai MC, Li WM, Huang CN, Ke HL, Li CC, Yeh HC, Chan TC, Liang PI, Yeh BW, Wu WJ, Lim SW, Li CF (2016) DDR2 overexpression in urothelial carcinoma indicates an unfavorable prognosis: a large cohort study. Oncotarget 7(48):78918–78931. https://doi.org/10.18632/oncotarget.12912

    Article  PubMed  PubMed Central  Google Scholar 

  25. Corsa CA, Brenot A, Grither WR, Van Hove S, Loza AJ, Zhang K, Ponik SM, Liu Y, DeNardo DG, Eliceiri KW, Keely PJ, Longmore GD (2016) The action of Discoidin domain receptor 2 in basal tumor cells and stromal Cancer-associated fibroblasts is critical for breast Cancer metastasis. Cell Rep 15(11):2510–2523. https://doi.org/10.1016/j.celrep.2016.05.033

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Grither WR, Divine LM, Meller EH, Wilke DJ, Desai RA, Loza AJ, Zhao P, Lohrey A, Longmore GD, Fuh KC (2018) TWIST1 induces expression of discoidin domain receptor 2 to promote ovarian cancer metastasis. Oncogene 37(13):1714–1729. https://doi.org/10.1038/s41388-017-0043-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Kim D, Ko P, You E, Rhee S (2014) The intracellular juxtamembrane domain of discoidin domain receptor 2 (DDR2) is essential for receptor activation and DDR2-mediated cancer progression. Int J Cancer 135(11):2547–2557. https://doi.org/10.1002/ijc.28901

    Article  CAS  PubMed  Google Scholar 

  28. Sasaki S, Ueda M, Iguchi T, Kaneko M, Nakayama H, Watanabe T, Sakamoto A, Mimori K (2017) DDR2 expression is associated with a high frequency of peritoneal dissemination and poor prognosis in colorectal Cancer. Anticancer Res 37(5):2587–2591. https://doi.org/10.21873/anticanres.11603

    Article  CAS  PubMed  Google Scholar 

  29. Bagnall RD, Yeates L, Semsarian C (2010) Analysis of the Z-disc genes PDLIM3 and MYPN in patients with hypertrophic cardiomyopathy. Int J Cardiol 145(3):601–602. https://doi.org/10.1016/j.ijcard.2010.08.004

    Article  PubMed  Google Scholar 

  30. Fagerberg L, Hallstrom BM, Oksvold P, Kampf C, Djureinovic D, Odeberg J, Habuka M, Tahmasebpoor S, Danielsson A, Edlund K, Asplund A, Sjostedt E, Lundberg E, Szigyarto CA, Skogs M, Takanen JO, Berling H, Tegel H, Mulder J, Nilsson P, Schwenk JM, Lindskog C, Danielsson F, Mardinoglu A, Sivertsson A, von Feilitzen K, Forsberg M, Zwahlen M, Olsson I, Navani S, Huss M, Nielsen J, Ponten F, Uhlen M (2014) Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics. Mol Cell Proteomics 13(2):397–406. https://doi.org/10.1074/mcp.M113.035600

    Article  CAS  PubMed  Google Scholar 

  31. Germano G, Morello G, Aveic S, Pinazza M, Minuzzo S, Frasson C, Persano L, Bonvini P, Viola G, Bresolin S, Tregnago C, Paganin M, Pigazzi M, Indraccolo S, Basso G (2017) ZNF521 sustains the differentiation block in MLL-rearranged acute myeloid leukemia. Oncotarget 8(16):26129–26141. https://doi.org/10.18632/oncotarget.15387

    Article  PubMed  PubMed Central  Google Scholar 

  32. Spina R, Filocamo G, Iaccino E, Scicchitano S, Lupia M, Chiarella E, Mega T, Bernaudo F, Pelaggi D, Mesuraca M, Pazzaglia S, Semenkow S, Bar EE, Kool M, Pfister S, Bond HM, Eberhart CG, Steinkuhler C, Morrone G (2013) Critical role of zinc finger protein 521 in the control of growth, clonogenicity and tumorigenic potential of medulloblastoma cells. Oncotarget 4(8):1280–1292. https://doi.org/10.18632/oncotarget.1176

    Article  PubMed  PubMed Central  Google Scholar 

  33. Harder L, Eschenburg G, Zech A, Kriebitzsch N, Otto B, Streichert T, Behlich AS, Dierck K, Klingler B, Hansen A, Stanulla M, Zimmermann M, Kremmer E, Stocking C, Horstmann MA (2013) Aberrant ZNF423 impedes B cell differentiation and is linked to adverse outcome of ETV6-RUNX1 negative B precursor acute lymphoblastic leukemia. J Exp Med 210(11):2289–2304. https://doi.org/10.1084/jem.20130497

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Mega T, Lupia M, Amodio N, Horton SJ, Mesuraca M, Pelaggi D, Agosti V, Grieco M, Chiarella E, Spina R, Moore MA, Schuringa JJ, Bond HM, Morrone G (2011) Zinc finger protein 521 antagonizes early B-cell factor 1 and modulates the B-lymphoid differentiation of primary hematopoietic progenitors. Cell Cycle 10(13):2129–2139. https://doi.org/10.4161/cc.10.13.16045

    Article  CAS  PubMed  Google Scholar 

  35. Brot N, Weissbach L, Werth J, Weissbach H (1981) Enzymatic reduction of protein-bound methionine sulfoxide. Proc Natl Acad Sci U S A 78(4):2155–2158

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Kim HY, Gladyshev VN (2004) Methionine sulfoxide reduction in mammals: characterization of methionine-R-sulfoxide reductases. Mol Biol Cell 15(3):1055–1064. https://doi.org/10.1091/mbc.E03-08-0629

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Kwak GH, Kim HY (2017) MsrB3 deficiency induces cancer cell apoptosis through p53-independent and ER stress-dependent pathways. Arch Biochem Biophys 621:1–5. https://doi.org/10.1016/j.abb.2017.04.001

    Article  CAS  PubMed  Google Scholar 

  38. Kwak GH, Kim TH, Kim HY (2017) Down-regulation of MsrB3 induces cancer cell apoptosis through reactive oxygen species production and intrinsic mitochondrial pathway activation. Biochem Biophys Res Commun 483(1):468–474. https://doi.org/10.1016/j.bbrc.2016.12.120

    Article  CAS  PubMed  Google Scholar 

  39. Lee E, Kwak GH, Kamble K, Kim HY (2014) Methionine sulfoxide reductase B3 deficiency inhibits cell growth through the activation of p53-p21 and p27 pathways. Arch Biochem Biophys 547:1–5. https://doi.org/10.1016/j.abb.2014.02.008

    Article  CAS  PubMed  Google Scholar 

  40. Morel AP, Ginestier C, Pommier RM, Cabaud O, Ruiz E, Wicinski J, Devouassoux-Shisheboran M, Combaret V, Finetti P, Chassot C, Pinatel C, Fauvet F, Saintigny P, Thomas E, Moyret-Lalle C, Lachuer J, Despras E, Jauffret JL, Bertucci F, Guitton J, Wierinckx A, Wang Q, Radosevic-Robin N, Penault-Llorca F, Cox DG, Hollande F, Ansieau S, Caramel J, Birnbaum D, Vigneron AM, Tissier A, Charafe-Jauffret E, Puisieux A (2017) A stemness-related ZEB1-MSRB3 axis governs cellular pliancy and breast cancer genome stability. Nat Med 23(5):568–578. https://doi.org/10.1038/nm.4323

    Article  CAS  PubMed  Google Scholar 

  41. Mani SA, Guo W, Liao MJ, Eaton EN, Ayyanan A, Zhou AY, Brooks M, Reinhard F, Zhang CC, Shipitsin M, Campbell LL, Polyak K, Brisken C, Yang J, Weinberg RA (2008) The epithelial-mesenchymal transition generates cells with properties of stem cells. Cell 133(4):704–715. https://doi.org/10.1016/j.cell.2008.03.027

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Polyak K, Weinberg RA (2009) Transitions between epithelial and mesenchymal states: acquisition of malignant and stem cell traits. Nat Rev Cancer 9(4):265–273. https://doi.org/10.1038/nrc2620

    Article  CAS  PubMed  Google Scholar 

  43. Manzotti G, Torricelli F, Benedetta D, Lococo F, Sancisi V, Rossi G, Piana S, Ciarrocchi A (2018) An epithelial-to-mesenchymal transcriptional switch triggers evolution of pulmonary Sarcomatoid carcinoma (PSC) and identifies Dasatinib as new therapeutic option. Clinical cancer research : an official journal of the American Association for Cancer Research. https://doi.org/10.1158/1078-0432.CCR-18-2364

    Article  PubMed  Google Scholar 

  44. Xie B, Lin W, Ye J, Wang X, Zhang B, Xiong S, Li H, Tan G (2015) DDR2 facilitates hepatocellular carcinoma invasion and metastasis via activating ERK signaling and stabilizing SNAIL1. J Exp Clin Cancer Res : CR 34:101. https://doi.org/10.1186/s13046-015-0218-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The corresponding author would like to thank all the co-workers for collecting, managing, maintaining and interpreting the data used in this analysis. We also appreciate Soochow University for providing the financial support to conduct the present study.

Funding

This work was supported by Scientific Research Foundation for Talented Scholars in Soochow University, China (Q413900215).

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Authors and Affiliations

  1. Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, 215123, China

    Yueyi Feng & Xiaochen Shu

  2. Department of General Surgery, Harrison International Peace Hospital, Hengshui, 053000, China

    Yiqing Jiang

  3. Medical Research Centre, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, 100020, China

    Tao Wen

  4. Centre of Systems Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, China

    Fang Meng

  5. Suzhou Institute of Systems Medicine, Suzhou, 215123, China

    Fang Meng

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Contributions

Conception and design: Yueyi Feng, Xiaochen Shu.

Financial support: Xiaochen Shu.

Collection and assembly of data: Yueyi Feng.

Data analysis and interpretation: Yueyi Feng, Yiqing Jiang, Tao Wen, Fang Meng, Xiaochen Shu.

Manuscript writing: Yueyi Feng, Xiaochen Shu.

Final approval of manuscript: Yueyi Feng, Yiqing Jiang, Tao Wen, Fang Meng, and Xiaochen Shu.

Xiaochen Shu will be responsible for the overall content as guarantor of this work.

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Correspondence to Fang Meng or Xiaochen Shu.

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Feng, Y., Jiang, Y., Wen, T. et al. Identifying Potential Prognostic Markers for Muscle-Invasive Bladder Urothelial Carcinoma by Weighted Gene Co-Expression Network Analysis. Pathol. Oncol. Res. 26, 1063–1072 (2020). https://doi.org/10.1007/s12253-019-00657-6

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