Identification of hub genes in colon cancer via bioinformatics analysis

Abstract

Objectives This study aimed to investigate hub genes and their prognostic value in colon cancer via bioinformatics analysis. Methods Differentially expressed genes (DEGs) of expression profiles (GSE33113, GSE20916, and GSE37364) obtained from Gene Expression Omnibus (GEO) were identified using the GEO2R tool and Venn diagram software. Function and pathway enrichment analyses were performed, and a protein–protein interaction (PPI) network was constructed. Hub genes were verified based on The Cancer Genome Atlas (TCGA) and Human Protein Atlas (HPA) databases. Results We identified 207 DEGs, 62 upregulated and 145 downregulated genes, enriched in Gene Ontology terms “organic anion transport,” “extracellular matrix,” and “receptor ligand activity”, and in the Kyoto Encyclopedia of Genes and Genomes pathway “cytokine-cytokine receptor interaction.” The PPI network was constructed and nine hub genes were selected by survival analysis and expression validation. We verified these genes in the TCGA database and selected three potential predictors ( ZG16, TIMP1, and BGN) that met the independent predictive criteria. TIMP1 and BGN were upregulated in patients with a high cancer risk, whereas ZG16 was downregulated. The immunostaining results from HPA supported these findings. Conclusion This study indicates that these hub genes may be promising prognostic indicators or therapeutic targets for colon cancer.

Colon Cancer Progression Is Reflected to Monotonic Differentiation in Gene Expression and Pathway Deregulation Facilitating Stage–specific Drug Repurposing

“…A recent publication has also proposed the significant role of syntrophin beta 1-SNTB1 as prognostic marker for colon cancer metastasis (26). Moreover, it has been found that integrin betalike 1 -ITGBL1 is involved in the colon cancer development and metastasis (27) whileTACSTD2 and LEMD1 belong to the significant up-regulated genes of colon cancer (28,29). For the case of under-expressed MEGs found in our analysis, it has been indicated that the lower levels of PPARGC1A and SLC26A2 could increase colon cancer risk, proliferation and propagation and they have been proposed as possible candidate targets for cancer therapy (30,31).…”

Identification of Prognostic Biomarkers for Suppressing Tumorigenesis and Metastasis of Hepatocellular Carcinoma through Transcriptome Analysis

“…In this study, amplification was found as genetic alterations in 0.57% of the patients. In GBM, CCNB2 acted as a potential biomarker and played a vital role in Cellular Senescence and cell cycle [68]. These have missense mutation at location P80S having phosphorylation PTM site and amplification in 0.57% of the patients and shallow deletion copy number alterations.…”

Identification of prognostic biomarkers for suppressing tumorigenesis and metastasis of Hepatocellular carcinoma through transcriptome analysis

“…CCNB2 also found to promote cell cycle progression resulting in tumorigenesis in case of triple negative breast cancer (Wu et al, 2021). It was also identified in the cell cycle progression leading to poor prognosis of HCC (Liu et al, 2020). In this study, amplification was found as genetic alterations in 0.57% of the patients.…”