Publication:
Investigation of putative roles of smoking-associated salivary microbiome alterations on carcinogenesis by integrative in silico analysis

dc.contributor.buuauthorDOĞAN, BERKCAN
dc.contributor.buuauthorPirim, Dilek
dc.contributor.buuauthorPİRİM, DİLEK
dc.contributor.buuauthorAyar, Berna
dc.contributor.departmentSağlık Bilimleri Enstitüsü Fakültesi
dc.contributor.departmentMoleküler Biyoloji ve Genetik Ana Bilim Dalı
dc.contributor.orcid0000-0001-8061-8131
dc.contributor.researcheridHTP-6233-2023
dc.contributor.researcheridAAD-5249-2020
dc.date.accessioned2024-11-20T12:40:30Z
dc.date.available2024-11-20T12:40:30Z
dc.date.issued2022-12-30
dc.description.abstractGrowing evidence suggests that cigarette smoking alters the salivary microbiome composition and affects the risk of various complex diseases including cancer. However, the potential role of the smoking-associated microbiome in cancer development remains unexplained. Here, the putative roles of smoking-related microbiome alterations in carcinogenesis were investigated by in silico analysis and suggested evidence can be further explored by experimental methodologies. The Disbiome database was used to extract smoking-associated microbial taxa in saliva and taxon set enrichment analysis (TSEA) was conducted to identify the gene sets associated with extracted microbial taxa. We further analyzed the expression profiles of identified genes by using RNA-sequencing data from TCGA and GTEx projects. Associations of the genes with smoking-related phenotypes in cancer datasets were analyzed to prioritize genes for their interplay between smoking-related microbiome and carcinogenesis. Thirty-eight microbial taxa associated with smoking were included in the TSEA and this revealed sixteen genes that were significantly associated with smoking-associated microbial taxa. All genes were found to be differentially expressed in at least one cancer dataset, yet the ELF3 and CTSH were the most common differentially expressed genes giving significant results for several cancer types. Moreover, C2CD3, CTSH, DSC3, ELF3, RHOT2, and WSB2 showed statistically significant associations with smoking-related phenotypes in cancer datasets. This study provides in silico evidence for the potential roles of the salivary microbiome on carcino-genesis. The results shed light on the importance of smoking cessation strategies for cancer management and interventions to stratify smokers for their risk of smoking-induced carcinogenesis.
dc.identifier.doi10.1016/j.compbiolchem.2022.107805
dc.identifier.issn1476-9271
dc.identifier.urihttps://doi.org/10.1016/j.compbiolchem.2022.107805
dc.identifier.urihttps://hdl.handle.net/11452/48238
dc.identifier.volume102
dc.identifier.wos000918732100001
dc.indexed.wosWOS.SCI
dc.language.isoen
dc.publisherElsevier Sci Ltd
dc.relation.journalComputational Biology And Chemistry
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectCathepsin-h
dc.subjectGut microbiota
dc.subjectOral microbiota
dc.subjectCancer
dc.subjectIdentification
dc.subjectExpression
dc.subjectPathways
dc.subjectPatterns
dc.subjectInvasion
dc.subjectDisease
dc.subjectCigarette smoking
dc.subjectSalivary microbiome
dc.subjectCarcinogenesis
dc.subjectFunctional enrichment analysis
dc.subjectBioinformatics
dc.subjectScience & technology
dc.subjectLife sciences & biomedicine
dc.subjectTechnology
dc.subjectBiology
dc.subjectComputer science, interdisciplinary applications
dc.subjectLife sciences & biomedicine - other topics
dc.subjectComputer science
dc.titleInvestigation of putative roles of smoking-associated salivary microbiome alterations on carcinogenesis by integrative in silico analysis
dc.typeArticle
dspace.entity.typePublication
local.contributor.departmentFen Edebiyat Fakültesi Fakültesi/Moleküler Biyoloji ve Genetik Ana Bilim Dalı
local.contributor.departmentSağlık Bilimleri Enstitüsü Fakültesi
relation.isAuthorOfPublication2619712d-96a4-43ce-a680-666e68d6560f
relation.isAuthorOfPublication4fe8e2a8-6667-4c54-9c39-a4059fcb6657
relation.isAuthorOfPublication.latestForDiscovery2619712d-96a4-43ce-a680-666e68d6560f

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