Publication:
Comprehensive bioinformatic analysis reveals a cancer-associated fibroblast gene signature as a poor prognostic factor and potential therapeutic target in gastric cancer

dc.contributor.kuauthorMetin, Cemre Uçaryılmaz
dc.contributor.kuauthorÖzcan, Gülnihal
dc.contributor.kuprofileFaculty Member
dc.contributor.schoolcollegeinstituteGraduate School of Health Sciences
dc.contributor.schoolcollegeinstituteSchool of Medicine
dc.contributor.yokidN/A
dc.contributor.yokid185014
dc.date.accessioned2024-11-09T12:12:10Z
dc.date.issued2022
dc.description.abstractBackground: gastric cancer is one of the deadliest cancers, currently available therapies have limited success. Cancer-associated fibroblasts (CAFs) are pivotal cells in the stroma of gastric tumors posing a great risk for progression and chemoresistance. The poor prognostic signature for CAFs is not clear in gastric cancer, and drugs that target CAFs are lacking in the clinic. In this study, we aim to identify a poor prognostic gene signature for CAFs, targeting which may increase the therapeutic success in gastric cancer. Methods: we analyzed four GEO datasets with a network-based approach and validated key CAF markers in The Cancer Genome Atlas (TCGA) and The Asian Cancer Research Group (ACRG) cohorts. We implemented stepwise multivariate Cox regression guided by a pan-cancer analysis in TCGA to identify a poor prognostic gene signature for CAF infiltration in gastric cancer. Lastly, we conducted a database search for drugs targeting the signature genes. Results: our study revealed the COL1A1, COL1A2, COL3A1, COL5A1, FN1, and SPARC as the key CAF markers in gastric cancer. Analysis of the TCGA and ACRG cohorts validated their upregulation and poor prognostic significance. The stepwise multivariate Cox regression elucidated COL1A1 and COL5A1, together with ITGA4, Emilin1, and TSPAN9 as poor prognostic signature genes for CAF infiltration. The search on drug databases revealed collagenase clostridium histolyticum, ocriplasmin, halofuginone, natalizumab, firategrast, and BIO-1211 as the potential drugs for further investigation. Conclusions: our study demonstrated the central role of extracellular matrix components secreted and remodeled by CAFs in gastric cancer. The gene signature we identified in this study carries high potential as a predictive tool for poor prognosis in gastric cancer patients. Elucidating the mechanisms by which the signature genes contribute to poor patient outcomes can lead to the discovery of more potent molecular-targeted agents and increase the therapeutic success in gastric cancer.
dc.description.fulltextYES
dc.description.indexedbyWoS
dc.description.indexedbyScopus
dc.description.indexedbyPubMed
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.sponsorshipN/A
dc.description.versionPublisher version
dc.description.volume22
dc.formatpdf
dc.identifier.doi10.1186/s12885-022-09736-5
dc.identifier.embargoNO
dc.identifier.filenameinventorynoIR03766
dc.identifier.issn1471-2407
dc.identifier.linkhttps://doi.org/10.1186/s12885-022-09736-5
dc.identifier.quartileQ2
dc.identifier.scopus2-s2.0-85132549475
dc.identifier.urihttps://hdl.handle.net/20.500.14288/1139
dc.identifier.wos815096500001
dc.keywordsBioinformatics
dc.keywordsCancer-associated fibroblasts
dc.keywordsExtracellular matrix
dc.keywordsGastric cancer
dc.keywordsPrognostic biomarkers
dc.keywordsTherapeutic targets
dc.keywordsTumor microenvironment
dc.languageEnglish
dc.publisherBioMed Central
dc.relation.grantnoNA
dc.relation.urihttp://cdm21054.contentdm.oclc.org/cdm/ref/collection/IR/id/10628
dc.sourceBMC Cancer
dc.subjectOncology
dc.titleComprehensive bioinformatic analysis reveals a cancer-associated fibroblast gene signature as a poor prognostic factor and potential therapeutic target in gastric cancer
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.authoridN/A
local.contributor.authorid0000-0001-5354-0148
local.contributor.kuauthorMetin, Cemre Uçaryılmaz
local.contributor.kuauthorÖzcan, Gülnihal

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