Breast Cancer Interaction Network Concept from Mostly Related Components
DOI:
https://doi.org/10.31661/gmj.v8i.1298Abstract
Background: Management of breast cancer (BC) as a heterogeneous disease is very challenging. Biomarker discovery has been shown promising for this aim. Protein interaction mapping could provide further knowledge of the vital roles of these markers. Materials and Methods: Cytoscape and its plug-ins are used for network construction and evaluation. The plug-ins used in this study are STRING, Network Analyzer, GeneMANIA, and CluePedia. Results: The central proteins are enriched in transcription regulatory region DNA binding, regulatory region nucleic acid binding, regulatory region DNA binding, Fc receptor signaling pathway, cell cycle arrest, and immune response-regulating cell surface receptor signaling pathway. Conclusion: The introduced biomarkers and their related biological processes may show useful for the breast cancer diagnosis and monitoring; however, has to encounter more validation studies to be clinically applicable. [GMJ.2019;8:e1298]
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References
Porto-Mascarenhas EC, Assad DX, Chardin H, Gozal D, Canto GDL, Acevedo AC et al. Salivary biomarkers in the diagnosis of breast cancer: A review. Critical reviews in oncology/hematology. Crit Rev Oncol Hematol. 2017;110:62-73. https://doi.org/10.1016/j.critrevonc.2016.12.009PMid:28109406 Halakou F, Gursoy A, Kilic ES, Keskin O, editors. Topological, functional, and structural analyses of protein-protein interaction networks of breast cancer lung and brain metastases. Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2017 IEEE Conference on. 2017. https://doi.org/10.1109/CIBCB.2017.8058539 Aslebagh R, Channaveerappa D, Arcaro KF, Darie CC. Proteomics analysis of human breast milk to assess breast cancer risk. Electrophoresis. 20187;. 39(4):653-665. https://doi.org/10.1002/elps.201700123PMid:29193311 Rezaei-Tavirani M, Rezaei-Tavirani S, Mansouri V, Rostami-Nejad M, Rezaei-Tavirani M. Protein-Protein Interaction Network Analysis for a Biomarker Panel Related to Human Esophageal Adenocarcinoma. Asian Pacific Journal of Cancer Prevention Asian Pac J Cancer Prev. 2017;18(12):3357-63. Tyanova S, Albrechtsen R, Kronqvist P, Cox J, Mann M, Geiger T. Proteomic maps of breast cancer subtypes. Nature communications Nat Commun. 2016;10259 (7):1-11. https://doi.org/10.1038/ncomms10259PMid:26725330 PMCid:PMC4725767 Valizadeh R, Monfared AB, Rezaei-Tavirani M, Mansouri V. Evaluation of involved proteins in colon adenocarcinoma: an interactome analysis. Gastroenterology and Hepatology from bed to bench Gastroenterol Hepatol Bed Bench. 2017;10(1) 129-138. Barabasi A-L, Oltvai ZN. Network biology: understanding the cell's functional organization. Nature reviews genetics Nat Rev Genet. 2004;5(2):101-113. https://doi.org/10.1038/nrg1272PMid:14735121 Dashatan NA, Tavirani MR, Zali H, Koushki M, Ahmadi N. Prediction of Leishmania Major Key Proteins via Topological Analysis of Protein-Protein Interaction Network. Galen Medical Journal Galen. 2018;7:1-11. Abdolahi H, Azodi MZ. Protein interaction mapping interpretation of none alcoholic fatty liver disease model of rats after fat diet feeding. Gastroenterology and Hepatology from bed to bench Gastroenterol Hepatol Bed Bench. 2017;10(1):146-153. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome researchGenome Res. 2003;13(11):2498-504. https://doi.org/10.1101/gr.1239303PMid:14597658 PMCid:PMC403769 Szklarczyk D, Morris JH, Cook H, Kuhn M, Wyder S, Simonovic M et al. The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic acids research Nucleic Acids Res. 2016; 45:362-368. https://doi.org/10.1093/nar/gkw937PMid:27924014 PMCid:PMC5210637 Montojo J, Zuberi K, Rodriguez H, Kazi F, Wright G, Donaldson SL et al. GeneMANIA Cytoscape plugin: fast gene function predictions on the desktop. Bioinformatics. 2010;26(22):2927-8. https://doi.org/10.1093/bioinformatics/btq562PMid:20926419 PMCid:PMC2971582 Bindea G, Galon J, Mlecnik B. CluePedia Cytoscape plugin: pathway insights using integrated experimental and in silico data. Bioinformatics. 2013;29(5):661-3. https://doi.org/10.1093/bioinformatics/btt019PMid:23325622 PMCid:PMC3582273 Giunti G, Giunta D, Guisado-Fernandez E, Bender J, Fernandez-Luque L. A biopsy of Breast Cancer mobile applications: state of the practice review. International journal of medical informatics Int J Med Inform. 2018;110:1-9. https://doi.org/10.1016/j.ijmedinf.2017.10.022PMid:29331247 Beretov J, Wasinger VC, Millar EK, Schwartz P, Graham PH, Li Y. Proteomic analysis of urine to identify breast cancer biomarker candidates using a label-free LC-MS/MS approach. PloS one PLoS One. 2015;10(11): 1-20. https://doi.org/10.1371/journal.pone.0141876PMid:26544852 PMCid:PMC4636393 Tomas A, Futter CE, Eden ER. EGF receptor trafficking: consequences for signaling and cancer. Trends in cell biology Trends Cell Biol. 2014;24(1):26-34. https://doi.org/10.1016/j.tcb.2013.11.002PMid:24295852 PMCid:PMC3884125 Petitjean A, Achatz M, Borresen-Dale A, Hainaut P, Olivier M. TP53 mutations in human cancers: functional selection and impact on cancer prognosis and outcomes. Oncogene. 2007;26(15): 2157-65. https://doi.org/10.1038/sj.onc.1210302PMid:17401424 Stahl P, Seeschaaf C, Lebok P, Kutup A, Bockhorn M, Izbicki JR et al. Heterogeneity of amplification of HER2, EGFR, CCND1 and MYC in gastric cancer. BMC Gastroenterol BMC Gastroenterol. 2015;15(7). 231-4. https://doi.org/10.1186/s12876-015-0231-4PMid:25649416 PMCid:PMC4324419 Therkildsen C, Bergmann TK, Henrichsen-Schnack T, Ladelund S, Nilbert M. The predictive value of KRAS, NRAS, BRAF, PIK3CA and PTEN for anti-EGFR treatment in metastatic colorectal cancer: A systematic review and meta-analysis. Acta oncologica Acta Oncol. 2014;53(7):852-64. https://doi.org/10.3109/0284186X.2014.895036PMid:24666267 Shachaf CM, Kopelman AM, Arvanitis C, Karlsson Å, Beer S, Mandl S et al. MYC inactivation uncovers pluripotent differentiation and tumour dormancy in hepatocellular cancer. Nature. 2004;431(7012): 1112-7. https://doi.org/10.1038/nature03043PMid:15475948 Campbell IG, Russell SE, Choong DY, Montgomery KG, Ciavarella ML, Hooi CS et al. Mutation of the PIK3CA gene in ovarian and breast cancer. Cancer research. 2004;64(21):7678-81. https://doi.org/10.1158/0008-5472.CAN-04-2933PMid:15520168 Soleimani Z, Kheirkhah D, Sharif MR, Sharif A, Karimian M, Aftabi Y. Association of CCND1 Gene c. 870G> A polymorphism with breast cancer risk: A case-controlstudy and a meta-analysis. Pathology & Oncology Research Pathol Oncol Res. 2017;23(3):621-31. https://doi.org/10.1007/s12253-016-0165-3PMid:28004353 Garcia R, Franklin RA, McCubrey JA. EGF induces cell motility and multi-drug resistance gene expression in breast cancer cells. Cell Cycle. 2006;5(23):2820-6. https://doi.org/10.4161/cc.5.23.3535PMid:17172846 Kleer CG, Cao Q, Varambally S, Shen R, Ota I, Tomlins SA et al. EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proceedings of the National Academy of Sciences. Proc Natl Acad Sci U S A2003;100(20):11606-11. https://doi.org/10.1073/pnas.1933744100PMid:14500907 PMCid:PMC208805 Perou CM, Jeffrey SS, Van De Rijn M, Rees CA, Eisen MB, Ross DT et al. Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. Proceedings of the National Academy of Sciences Proc Natl Acad Sci U S A. 1999;96(16):9212-7. https://doi.org/10.1073/pnas.96.16.9212PMid:10430922 PMCid:PMC17759 Gu Y, Zhang S, Wu Q, Xu S, Cui Y, Yang Z et al. Differential expression of decorin, EGFR and cyclin D1 during mammary gland carcinogenesis in TA2 mice with spontaneous breast cancer. Journal of Experimental & Clinical Cancer Research. J Exp Clin Cancer Res. 2010;29(6):1-10. https://doi.org/10.1186/1756-9966-29-6PMid:20092659 PMCid:PMC2845556 Brooks D, Ravetch JV. Fc receptor signaling. Mechanisms of Lymphocyte Activation and Immune Regulation V. Springer. 1994; 365:185-95. https://doi.org/10.1007/978-1-4899-0987-9_19PMid:7887303 Schmidt M, Böhm D, Von Törne C, Steiner E, Puhl A, Pilch H et al. The humoral immune system has a key prognostic impact in node-negative breast cancer. Cancer research. 2008;68(13):5405-13. https://doi.org/10.1158/0008-5472.CAN-07-5206PMid:18593943 Janes PW, Daly RJ, Sutherland R. Activation of the Ras signalling pathway in human breast cancer cells overexpressing erbB-2. Oncogene. 1994;9(12):3601-8. De Boer C, Kluin-Nelemans J, Dreef E, Kester M, Kluin P, Schuuring E et al. Involvement of the CCND1 gene in hairy cell leukemia. Annals of Oncology Ann Oncol. 1996;7(3):251-5. https://doi.org/10.1093/oxfordjournals.annonc.a010568PMid:8740788 Bièche I, Laurendeau I, Tozlu S, Olivi M, Vidaud D, Lidereau R et al. Quantitation of MYC gene expression in sporadic breast tumors with a real-time reverse transcription-PCR assay. Cancer research. 1999;59(12):2759-65. Allred DC, Clark GM, Elledge R, Fuqua SA, Brown RW, Chamness GC et al. Association of p53 protein expression with tumor cell proliferation rate and clinical outcome in node-negative breast cancer. JNCI: Journal of the National Cancer Institute J Natl Cancer Inst. 1993;85(3):200-6. https://doi.org/10.1093/jnci/85.3.200PMid:8423624 Samuels Y, Wang Z, Bardelli A, Silliman N, Ptak J, Szabo S et al. High frequency of mutations of the PIK3CA gene in human cancers. Science. 2004;304(5670):554. https://doi.org/10.1126/science.1096502PMid:15016963
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