Investigation of putative roles of smoking-associated salivary microbiome alterations on carcinogenesis by integrative in silico analysis. (February 2023)

• Record Type: Journal Article
• Authors: Doğan, Berkcan; Ayar, Berna; Pirim, Dilek
• Is Part Of: Computational biology and chemistry. Volume 102(2023)
• Publication Date: 2023-02
• Subjects: Cigarette smoking -- Salivary microbiome -- Carcinogenesis -- Functional enrichment analysis -- Bioinformatics; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2022.107805
• Languages: English
• ISSNs: 1476-9271

Abstract

Abstract: Growing 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 carcinogenesis. 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. Graphical Abstract: ga1 Highlights: The saliva of cigarette smokers is enriched with specific microbiome compositions. Enrichment Analysis reveals key genes associated with salivary microbiome profiles. In silico analyses identified key genes associated with smoking-related phenotypes. Smoking-associated salivary microbiome may have potential roles in carcinogenesis.