Contribution of MicroRNA Biogenesis Pathway toCarcinogenesis: A Comprehensive S tudy Based on GeneExpression Profiles from TCGA Database

Objective: Cancer cells exhibit numerous deregulations invarious genes, including those involved in the microRNA biogenesispathway. Although cumulative evidence highlights theroles of microRNAs in cancer, the importance of the micro-RNA biogenesis machinery and consequently the significanceof global microRNA activity has not yet been completely surveyed.Here, we aim to explore the expression alterations ofmicroRNA biogenesis components in the deadlies t and mos tprevalent cancers.Materials and Methods: Raw counts of RNA-sequencing profilesof ۱۳ cancer types were downloaded from The Cancer GenomeAtlas (TCGA). The obtained data were normalized usingthe DESeq۲ package (R programming). The normalized countsfor ۱۶ genes of microRNA biogenesis machinery were subjectedto several analyses including principal component analysis(PCA), Volcano plotting, heatmap analysis, and differential expressionanalysis. Genes with an adjus ted P value<۰.۰۵ wereconsidered differentially expressed.Results: Our results indicated all ۱۶ genes were differentiallyexpressed across different tumor types. The auxiliary componentsof the microRNA biogenesis pathway (e.g. GEMIN۴ andTNRC۶A) displayed lower variations in expression comparedto the main, canonical components. The key components (i.e.DICER, DROSHA, TRBP, AGO۲, and XPO۵) were the mos tdifferentially expressed (all except DICER were upregulated)and exhibited consis tent expression patterns in different cancertypes. Interes tingly, upregulation of the shuttling components,XPO۱ and XPO۵, sugges ted an increased rate of microRNAprocessing in cancer.Conclusion: The canonical components of the microRNA biogenesispathway were the mos t differentially expressed genesfrom the microRNA machinery and showed reproducible expressiondynamics across various cancer types. All componentsbut DICER were upregulated across various tumor types.

کلیدواژه ها:

Noncoding RNA ، Tumorigenesis ، In Silico Analysis ، Gene Regulation