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Comparative Bioinformatics Characteristic of Bladder Cancer Stage 2 from Stage 4 Expression Profile: A Network-Based Study

Mona Zamanian Azodi, Mostafa Rezaei-Tavirani, Mohammad Rostami-Nejad, Majid Rezaei-Tavirani

Background: Bladder cancer (BC) has remained as one of the most challenging issues in medicine. The aim of this study was to investigate the differential network analysis of stages 2 and 4 of BC to better understand the molecular pathology of these states. Materials and Methods: We chose gene expression data of GSE52519 from Gene Expression Omnibus (GEO) database analyzed by the GEO2R online tool. Cytoscape version 3.6.1 and its algorithms are the methods applied for the network construction and investigation of differentially expressed genes (DEG) in these states. Result: Our result revealed that the analysis DEGs provides useful information about a common molecular feature of stages 2 and 4 of BC. Conclusion: Consequently, the network finding revealed that more investigation about stage 2 is required to achieve an effective therapeutic protocol to block the transition from stage 2 to stage 4.[GMJ.2018;7:e1279]

 

Bladder Neoplasm; Transcriptome; Protein Interaction Maps; Biomarkers

Antoni S, Ferlay J, Soerjomataram I, Znaor A, Jemal A, Bray F. Bladder cancer incidence and mortality: a global overview and recent trends. Eur Urol. 2017; 71(1):96-108.

https://doi.org/10.1016/j.eururo.2016.06.010

PMid:27370177

Lezhnina K, Kovalchuk O, Zhavoronkov AA, et al. Novel robust biomarkers for human bladder cancer based on activation of intracellular signaling pathways. Oncotarget. 2014;5(19):9022-33.

https://doi.org/10.18632/oncotarget.2493

PMid:25296972 PMCid:PMC4253415

Grossman HB, Soloway M, Messing E, et al. Surveillance for recurrent bladder cancer using a point-of-care proteomic assay. JAMA. 2006;295(3):299-305.

https://doi.org/10.1001/jama.295.3.299

PMid:16418465

D'Costa JJ, Goldsmith JC, Wilson JS, Bryan RT, Ward DG. A systematic review of the diagnostic and prognostic value of urinary protein biomarkers in urothelial bladder cancer. Bladder Cancer. 2016;2(3):301-17.

https://doi.org/10.3233/BLC-160054

PMid:27500198 PMCid:PMC4969711

Rezaei-Tavirani M, Rezaei-Tavirani S, Mansouri M, Rostami-Nejad M, Rezaei-Tavirani M. Protein-protein interaction network analysis for a biomarker panel related to human esophageal adenocarcinoma. Asian Pac J Cancer Prev. 2017;18(12):3357-63.

PMid:29286604 PMCid:PMC5980895

Tyanova S, Albrechtsen R, Kronqvist P, Cox J, Mann M, Geiger T. Proteomic maps of breast cancer subtypes. Nat Commun. 2016;10259(7):1-11.

https://doi.org/10.1038/ncomms10259

Bell DA, Taylor JA, Paulson DF, Robertson CN, Mohler JL, Lucier GW. Genetic risk and carcinogen exposure: a common inherited defect of the carcinogen-metabolism gene glutathione S-transferase M1 (GSTM1) that increases susceptibility to bladder cancer. J Natl Cancer Inst. 1993;85(14):1159-64.

https://doi.org/10.1093/jnci/85.14.1159

PMid:8320745

Richter J, Wagner U, Kononen J, et al. High-throughput tissue microarray analysis of cyclin E gene amplification and overexpression in urinary bladder cancer. Am J Pathol. 2000;157(3):787-94.

https://doi.org/10.1016/S0002-9440(10)64592-0

Fujimoto K, Yamada Y, Okajima E, et al. Frequent association of p53 gene mutation in invasive bladder cancer. Cancer Res. 1992;52(6):1393-8.

PMid:1540947

Andersen JB, Aaboe M, Borden EC, Goloubeva OG, Hassel BA, Orntoft TF. Stage-associated overexpression of the ubiquitin-like protein, ISG15, in bladder cancer. Br J Cancer. 2006;94(10):1465-71.

https://doi.org/10.1038/sj.bjc.6603099

PMid:16641915 PMCid:PMC2361278

Khal J, Hine AV, Fearon KC, Dejong CH, Tisdale MJ. Increased expression of proteasome subunits in skeletal muscle of cancer patients with weight loss. Int J Biochem Cell Biol. 2005;37(10):2196-206.

https://doi.org/10.1016/j.biocel.2004.10.017

PMid:16125116

Mansouri V, Vafaee R, Abaszadeh H, Heidari M. Protein-protein interaction network analysis of obesity. Arvand J Health Medical Sci. 2016;1(3):157-62.

https://doi.org/10.22631/ajhms.2016.43203

Valizadeh R, Bahadorimonfared A, Rezaei-Tavirani M, Norouzinia M, Ehsani Ardakani MI. Evaluation of involved proteins in colon adenocarcinoma: an interactome analysis. Gastroenterol Hepatol Bed Bench. 2017;10(Suppl1):S129-38.

PMid:29511483 PMCid:PMC5838192

Abdolahi H, Azodi MZ, Hatami B. Protein interaction mapping interpretation of none alcoholic fatty liver disease model of rats after fat diet feeding. Gastroenterol Hepatol Bed Bench. 2017;10(Suppl1):S146-53.

Tavirani MR, Okhovatian F, Rostami-Nejad M, Tavirani SR. Protein-protein interaction network analysis revealed a new prospective of posttraumatic stress disorder. GMJ. 2018;7:e1137

Montojo J, Zuberi K, Rodriguez H, et al. GeneMANIA Cytoscape plugin: fast gene function predictions on the desktop. Bioinformatics. 2010;26(22):2927-8.

https://doi.org/10.1093/bioinformatics/btq562

PMid:20926419 PMCid:PMC2971582

Barrett T, Wilhite SE, Ledoux P, et al. NCBI GEO: archive for functional genomics data sets--update. Nucleic Acids Res. 2013;41(Database issue):D991-5.

PMid:23193258

Shannon P, Markiel A, Ozier O, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498-504.

https://doi.org/10.1101/gr.1239303

PMid:14597658 PMCid:PMC403769

Szklarczyk D, Morris JH, Cook H, et al. The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible. Nucleic Acids Res. 2017;45(Database issue):D362-8.

https://doi.org/10.1093/nar/gkw937

PMid:27924014 PMCid:PMC5210637

Assenov Y, Ramírez F, Schelhorn SE, Lengauer T, Albrecht M. Computing topological parameters of biological networks. Bioinformatics. 2007;24(2):282-4.

https://doi.org/10.1093/bioinformatics/btm554

PMid:18006545

Peyvandi H, Peyvandi AA, Safaei A, Azodi MZ, Rezaei-Tavirani M. Introducing potential key proteins and pathways in human laryngeal cancer: a system biology approach. Iran J Pharm Res. 2018;17(1):415-25.

PMid:29755572 PMCid:PMC5937111

Rezaei-Tavirani M, Hasanzadeh H, Seyyedi S, Ghoujeghi F, Semnani V, Zali H. Proteomic analysis of Extremely Low-Frequency ElectroMagnetic Field (ELF-EMF) with different intensities in rats hippocampus. Arch Neurosci. 2018; 5(1):e62954.

https://doi.org/10.5812/archneurosci.62954

Williamson DF, Parker RA, Kendrick JS. The box plot: a simple visual method to interpret data. Ann Intern Med. 1989;110(11):916-21.

https://doi.org/10.7326/0003-4819-110-11-916

PMid:2719423

Edwards YH, Putt W, Fox M, Ives JH. A novel human phosphoglucomutase (PGM5) maps to the centromeric region of chromosome 9. Genomics. 1995;30(2):350-3.

https://doi.org/10.1006/geno.1995.9866

PMid:8586438

Noetzel E, Rose M, Sevinc E, et al. Intermediate filament dynamics and breast cancer: aberrant promoter methylation of the Synemin gene is associated with early tumor relapse. Oncogene. 2010;29(34):4814.

https://doi.org/10.1038/onc.2010.229

PMid:20543860

Winder SJ, Walsh MP. Smooth muscle calponin. Inhibition of actomyosin MgATPase and regulation by phosphorylation. J Biol Chem. 1990;265(17):10148-55.

PMid:2161834

Hazell GG, Peachey AM, Teasdale JE, et al. PI16 is a shear stress and inflammation-regulated inhibitor of MMP2. Sci Rep. 2016; 6: 39553

https://doi.org/10.1038/srep39553

PMid:27996045 PMCid:PMC5171773

Jiang HK, Qiu GR, Li-Ling J, Xin N, Sun KL. Reduced ACTC1 expression might play a role in the onset of congenital heart disease by inducing cardiomyocyte apoptosis. Circ J. 2010;74(11):2410-8.

https://doi.org/10.1253/circj.CJ-10-0234

PMid:20962418

Milner DJ, Mavroidis M, Weisleder N, Capetanaki Y. Desmin cytoskeleton linked to muscle mitochondrial distribution and respiratory function. J Cell Biol. 2000;150(6):1283-98.

https://doi.org/10.1083/jcb.150.6.1283

PMid:10995435 PMCid:PMC2150713

Rezaei–Tavirani M, Bashash D, Rostami FT, et al. Celiac disease microarray analysis based on system biology approach. Gastroenterol Hepatol Bed Bench. 2018;11(3):216-24.

PMid:30013745 PMCid:PMC6040039

Lucena-Araujo AR, de Oliveira FM, Leite-Cueva SD, dos Santos GA, Falcao RP, Rego EM. High expression of AURKA and AURKB is associated with unfavorable cytogenetic abnormalities and high white blood cell count in patients with acute myeloid leukemia. Leuk Res. 2011;35(2):260-4.

https://doi.org/10.1016/j.leukres.2010.07.034

PMid:20732714

Zamanian-Azodi M, Rezaei-Tavirani M, Rostami-Nejad M, Tajik-Rostami F. New molecular aspects of cardiac arrest; promoting cardiopulmonary resuscitation approaches. Emerg. 2018;6(1):1-6.

Gandhi N, Krishna S, Booth CM, et al. Diagnostic accuracy of magnetic resonance imaging for tumour staging of bladder cancer: systematic review and meta-analysis. BJU Int. 2018.

https://doi.org/10.1111/bju.14366

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