Identification of key genes and pathways for cholangiocarcinoma using an integrated bioinformatics analysis

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dc.authoridEngin Ulukaya / 0000-0003-4875-5472en_US
dc.authoridAslı Kutlu / 0000-0002-9169-388Xen_US
dc.authoridMerve Arda / 0000-0001-6826-0704en_US
dc.authorscopusidAslı Kutlu / 57716458200en_US
dc.authorscopusidEngin Ulukaya / 6602927353en_US
dc.authorscopusidMerve Arda / 57979115100
dc.authorwosidEngin Ulukaya / K-5792-2018en_US
dc.authorwosidAslı Kutlu / DYB-1368-2022en_US
dc.contributor.authorKutlu, Aslı
dc.contributor.authorArda, Merve
dc.contributor.authorAtak, Evren
dc.contributor.authorUlukaya, Engin
dc.date.accessioned2023-01-19T08:29:26Z
dc.date.available2023-01-19T08:29:26Z
dc.date.issued2022en_US
dc.departmentİstinye Üniversitesi, Tıp Fakültesi, Dahili Tıp Bilimleri Bölümüen_US
dc.description.abstractObjectives: The scope of this study was to identify potential genes as a promising biomarker in diagnosing cholangio-carcinoma (CCA) or differentiating the subtypes of CCA. In this study, we used Gene Expression Omnibus (GEO)-NCBI data sets as promising open sources to perform integrative analysis. Methods: The gene expression data sets of intrahepatic CCA (iCCA) and extrahepatic CCA (eCCA) were retrieved from GEO, and the statistical analysis of GSE45001 (iCCA), GSE76311 (iCCA), and GSE132305 (eCCA) was performed to identify significantly expressed genes. The association of listed genes with CCA was checked via text-mining approaches. For CCA, the details were provided by discussing its relations with our results. Then, the pathway analysis was performed to identify common pathways both in iCCA and eCCA. Results: The pathway analysis reveals that although there are common pathways between iCCA and eCCA, the associated genes within these pathways are different from one another. According to the results of upregulated gene sets, integrin cell surface interaction (R-HSA-216083), MET activates PTK2 signaling (R-HSA-8874081), degradation of the extracellular matrix (ECM) (R-HSA-1474228), nonintegrin membrane–ECM interaction (R-HSA-3000171), and assembly of collagen fibrils and other multimeric structures (R-HSA-2022090) are found as common pathways among these data sets, yet there is no reported common pathway within downregulated gene sets. A detailed study of common pathway analysis shows that COL1A1 and COL1A2 genes, whose associations with CCA have not been reported, seem promising to differentiate iCCA from eCCA. The pathway analysis also reveals that although there are common pathways between iCCA and eCCA, the associated genes within these pathways are different from one another. Conclusion: Focusing on pathways rather than genes is more promising for revealing the potential biomarkers to-gether with providing a deeper understanding by highlighting significant pathways. © 2022, Kare Publishing. All rights reserved.en_US
dc.identifier.citationKutlu, A., Arda, M., Atak, E., & Ulukaya, E. (2022). Identification of key genes and pathways for cholangiocarcinoma using an integrated bioinformatics analysis. International Journal of Medical Biochemistry, 5(3), 137-151.en_US
dc.identifier.doi10.14744/ijmb.2022.18199en_US
dc.identifier.endpage151en_US
dc.identifier.issn2587-2362en_US
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-85142541573en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage137en_US
dc.identifier.trdizinid1132209en_US
dc.identifier.urihttp://doi.org/10.14744/ijmb.2022.18199
dc.identifier.urihttps://hdl.handle.net/20.500.12713/3824
dc.identifier.volume5en_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakTR-Dizinen_US
dc.institutionauthorKutlu, Aslı
dc.institutionauthorArda, Merve
dc.institutionauthorUlukaya, Engin
dc.language.isoenen_US
dc.publisherKare Publishingen_US
dc.relation.ispartofInternational journal of medical biochemistryen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectCOL1A1en_US
dc.subjectCOL1A2;en_US
dc.subjecteCCAen_US
dc.subjectGene Expression Studyen_US
dc.subjectGEO Data Setsen_US
dc.subjectiCCAen_US
dc.titleIdentification of key genes and pathways for cholangiocarcinoma using an integrated bioinformatics analysisen_US
dc.typeArticleen_US

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