Multi-omic data interpretation to repurpose subtype specific drug candidates for breast cancer

dc.contributor.authorTuranli, Beste
dc.contributor.authorKaragoz, Kubra
dc.contributor.authorBidkhori, Gholamreza
dc.contributor.authorSinha, Raghu
dc.contributor.authorGatza, Michael L.
dc.contributor.authorUhlen, Mathias
dc.contributor.authorMardinoglu, Adil
dc.date.accessioned2025-05-10T15:22:07Z
dc.date.issued2019
dc.departmentİstanbul Medeniyet Üniversitesi
dc.description.abstractTriple-negative breast cancer (TNBC), which is largely synonymous with the basal-like molecular subtype, is the 5th leading cause of cancer deaths for women in the United States. The overall prognosis for TNBC patients remains poor given that few treatment options exist; including targeted therapies (not FDA approved), and multi-agent chemotherapy as standard-of-care treatment. TNBC like other complex diseases is governed by the perturbations of the complex interaction networks thereby elucidating the underlying molecular mechanisms of this disease in the context of network principles, which have the potential to identify targets for drug development. Here, we present an integrated “omics” approach based on the use of transcriptome and interactome data to identify dynamic/active protein-protein interaction networks (PPINs) in TNBC patients. We have identified three highly connected modules, EED, DHX9, and AURKA, which are extremely activated in TNBC tumors compared to both normal tissues and other breast cancer subtypes. Based on the functional analyses, we propose that these modules are potential drivers of proliferation and, as such, should be considered candidate molecular targets for drug development or drug repositioning in TNBC. Consistent with this argument, we repurposed steroids, anti-inflammatory agents, anti-infective agents, cardiovascular agents for patients with basal-like breast cancer. Finally, we have performed essential metabolite analysis on personalized genome-scale metabolic models and found that metabolites such as sphingosine-1phosphate and cholesterol-sulfate have utmost importance in TNBC tumor growth. Copyright © 2019 Turanli, Karagoz, Bidkhori, Sinha, Gatza, Uhlen, Mardinoglu and Arga. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
dc.description.sponsorshipTUBITAK; National Institutes of Health, NIH, (V2016-013); V Foundation for Cancer Research, (DHFS-18PPC-024); New Jersey Commission on Spinal Cord Research, NJSCR; Knut och Alice Wallenbergs Stiftelse, (FEN-C-DRP-250816-0417); Marmara Üniversitesi
dc.identifier.doi10.3389/fgene.2019.00420
dc.identifier.issn1664-8021
dc.identifier.issueMAY
dc.identifier.scopus2-s2.0-85067884608
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.3389/fgene.2019.00420
dc.identifier.urihttps://hdl.handle.net/20.500.14730/6323
dc.identifier.volume10
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherFrontiers Media S.A.
dc.relation.ispartofFrontiers in Genetics
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_Scopus_20250302
dc.subjectBasal subtype; Breast cancer; Drug repositioning; Non-cancer therapeutics; Personalized metabolic models; Repurposing
dc.titleMulti-omic data interpretation to repurpose subtype specific drug candidates for breast cancer
dc.typeArticle

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