Bioinformatic analysis of RNA-seq data unveiled critical genes in rectal adenocarcinoma.

OBJECTIVE

RNA-seq data of rectal adenocarcinoma (READ) were analyzed with bioinformatics tools to unveil potential biomarkers in the disease.

MATERIALS AND METHODS

RNA-seq data of READ were downloaded from The Cancer Genome Atlas (TCGA) database. Differential analysis was performed with package edgeR. False discovery rate (FDR) < 0.05 and |log2 (fold change)|>1 were set as cut-off values to screen out differentially expressed genes (DEGs). Gene coexpression network was constructed with package Ebcoexpress. Gene Ontology enrichment analysis was performed for the DEGs in the gene coexpression network with DAVID online tool. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was also performed for the genes with KOBASS 2.0.

RESULTS

A total of 620 DEGs, 389 up-regulated genes, and 231 down-regulated genes, were identified from 163 READ samples and 9 normal controls. A gene coexpression network consisting of 71 DEGs and 253 edges were constructed. Genes were associated with ribosome and focal adhesion functions. Three modules were identified, in which genes were involved in muscle contraction, negative regulation of glial cell proliferation and extracellular matrix organization functions, respectively. Several critical hub genes were disclosed, such as RPS2, MMP1, MMP11 and FAM83H. Thirteen relevant small molecule drugs were identified, such as scriptaid and spaglumic acid. A total of 8 TFs and 5 miRNAs were acquired, such as MYC, NFY, STAT5A, miR-29, miR-200 and miR-19.

CONCLUSIONS

Several critical genes and relevant drugs, TFs and miRNAs were revealed in READ. These findings could advance the understanding about the disease and benefit therapy development.