Exploring molecular markers and drug candidates for colorectal cancer through comprehensive bioinformatics analysis

Abstract

Colorectal cancer (CRC) often has a poor prognosis and identifying useful and novel agents for treating CRC is urgently required. This study aimed to examine molecular markers associated with CRC prognosis and to identify potential drug candidates. The differentially expressed genes (DEGs) of CRC in TCGA were identified. The genes associated with CRC, summarized from NCBI-gene, OMIM, and the DEGs, were used to construct a co-expression network by WGCNA. Moreover, the co-expression genes from modules of interest were used to carry out functional enrichment. A total of 2742 DEGs, including 1674 upregulated and 1068 downregulated genes, were identified. Thirteen co-expression modules were constructed with WGCNA. Brown and blue co-expression modules with significant differences in disease phenotype were found. Functional enrichment analysis showed that genes in the brown module were mainly related to cell cycle, cell proliferation, DNA replication, and RNA transport. The genes in the blue module were mainly associated with fatty acid degradation, sulfur metabolism, PPAR signaling pathway and bile secretion. In addition, both the genes in brown and blue were associated with tumor staging. Some prognostic markers and candidate small molecules drugs for CRC treatment were identified. In conclusion, we revealed molecular biomarker profiles in CRC by systematic bioinformatics analysis, constructed regulatory networks of mRNA, ncRNA and transcriptional regulators (TFs), and identified potential drugs targeting hub proteins and TFs.www.aging-us.com AGINGgenes involved in tumorigenesis and progression in CRC through WGNCA and to identify potential therapeutic drugs. AGING Table 3. Pivot (ncRNA)-module interaction pairs. Module ncRNA Connection P

SLAMF8 can predict prognosis of pan-cancer and the immunotherapy response effectivity of gastric cancer

“…However, up to date, there are no researches that confirmed the expression pattern, prognostic significance, and biological role of SLAMF8 across various cancers. In recent years, bioinformatics analysis has played a crucial role in the molecular classification and identification of biomarkers in cancers [ 9 , 10 ]. In this study, a thorough analysis of SLAMF8 was conducted to investigate its abnormal expression, its relationship with pan-cancer prognosis and the immune microenvironment, and to verify its ability to predict the effectiveness of immunotherapy in gastric.…”