A stemness and EMT based gene expression signature identifies phenotypic plasticity and is a predictive but not prognostic biomarker for breast cancer

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buir.contributor.authorAkbar, Muhammad Waqas
buir.contributor.authorBelder, Nevin
buir.contributor.authorDemirkol-Canlı, Seçil Demirkol
buir.contributor.authorKüçükkaraduman, Barış
buir.contributor.authorTürk, Can
buir.contributor.authorŞahin, Özgür
buir.contributor.authorGüre, Ali Osmay
dc.citation.epage961en_US
dc.citation.issueNumber1en_US
dc.citation.spage949en_US
dc.citation.volumeNumber11en_US
dc.contributor.authorAkbar, Muhammad Waqas
dc.contributor.authorBelder, Nevin
dc.contributor.authorDemirkol-Canlı, Seçil
dc.contributor.authorKüçükkaraduman, Barış
dc.contributor.authorTürk, Can
dc.contributor.authorŞahin, Özgür
dc.contributor.authorGüre, Ali Osmay
dc.date.accessioned2021-02-17T07:21:51Z
dc.date.available2021-02-17T07:21:51Z
dc.date.issued2020
dc.departmentDepartment of Molecular Biology and Geneticsen_US
dc.description.abstractAims: Molecular heterogeneity of breast cancer results in variation in morphology, metastatic potential and response to therapy. We previously showed that breast cancer cell line sub-groups obtained by a clustering approach using highly variable genes overlapped almost completely with sub-groups generated by a drug cytotoxicity-profile based approach. Two distinct cell populations thus identified were CSC(cancer stem cell)-like and non-CSC-like. In this study we asked whether an mRNA based gene signature identifying these two cell types would explain variation in stemness, EMT, drug sensitivity, and prognosis in silico and in vitro. Main methods: In silico analyses were performed using publicly available cell line and patient tumor datasets. In vitro analyses of phenotypic plasticity and drug responsiveness were obtained using human breast cancer cell lines. Key findings: We find a novel gene list (CNCL) that can generate both categorical and continuous variables corresponding to the stemness/EMT (epithelial to mesenchymal transition) state of tumors. We are presenting a novel robust gene signature that unites previous observations related either to EMT or stemness in breast cancer. We show in silico, that this signature perfectly predicts behavior of tumor cells tested in vitro, and can reflect tumor plasticity. We thus demonstrate for the first time, that breast cancer subtypes are sensitive to either Lapatinib or Midostaurin. The same gene list is not capable of predicting prognosis in most cohorts, except for one that includes patients receiving neo-adjuvant taxene therapy. Significance: CNCL is a robust gene list that can identify both stemness and the EMT state of cell lines and tumors. It can be used to trace tumor cells during the course of phenotypic changes they undergo, that result in altered responses to therapeutic agents. The fact that such a list cannot be used to identify prognosis in most patient cohorts suggests that presence of factors other than stemness and EMT affect mortality.en_US
dc.description.provenanceSubmitted by Onur Emek (onur.emek@bilkent.edu.tr) on 2021-02-17T07:21:51Z No. of bitstreams: 1 A_Stemness_and_EMT_Based_Gene_Expression_Signature_Identifies_Phenotypic_Plasticity_and_is_A_Predictive_but_Not_Prognostic_Biomarker_for_Breast_Cancer.pdf: 1965348 bytes, checksum: c5842098f816085b45caa7ad8b476bd2 (MD5)en
dc.description.provenanceMade available in DSpace on 2021-02-17T07:21:51Z (GMT). No. of bitstreams: 1 A_Stemness_and_EMT_Based_Gene_Expression_Signature_Identifies_Phenotypic_Plasticity_and_is_A_Predictive_but_Not_Prognostic_Biomarker_for_Breast_Cancer.pdf: 1965348 bytes, checksum: c5842098f816085b45caa7ad8b476bd2 (MD5) Previous issue date: 2020en
dc.description.sponsorshipThis work was partially funded by a grant from the Turkish Scientific and Technological Research Council/TUBITAK (117S058) to AOG and one from The Higher Education Commission of Pakistan to MWA.en_US
dc.identifier.doi10.7150/jca.34649en_US
dc.identifier.issn1837-9664
dc.identifier.urihttp://hdl.handle.net/11693/73185
dc.language.isoEnglishen_US
dc.publisherIvyspring International Publisheren_US
dc.relation.isversionofhttps://dx.doi.org/10.7150/jca.34649en_US
dc.source.titleJournal of Canceren_US
dc.subjectBreast canceren_US
dc.subjectPredictive biomarkersen_US
dc.subjectTumor plasticityen_US
dc.subjectTranscriptomicsen_US
dc.titleA stemness and EMT based gene expression signature identifies phenotypic plasticity and is a predictive but not prognostic biomarker for breast canceren_US
dc.typeArticleen_US

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