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Identification of Hub Genes Related to Carcinogenesis and Prognosis in Colorectal Cancer Based on Integrated Bioinformatics.

ABSTRACT: The high mortality of colorectal cancer (CRC) patients and the limitations of conventional tumor-node-metastasis (TNM) stage emphasized the necessity of exploring hub genes closely related to carcinogenesis and prognosis in CRC. The study is aimed at identifying hub genes associated with carcinogenesis and prognosis for CRC. We identified and validated 212 differentially expressed genes (DEGs) from six Gene Expression Omnibus (GEO) datasets and the Cancer Genome Atlas (TCGA) database. We investigated functional enrichment analysis for DEGs. The protein-protein interaction (PPI) network was constructed, and hub modules and genes in CRC carcinogenesis were extracted. A prognostic signature was developed and validated based on Cox proportional hazards regression analysis. The DEGs mainly regulated biological processes covering response to stimulus, metabolic process, and affected molecular functions containing protein binding and catalytic activity. The DEGs played important roles in CRC-related pathways involving in preneoplastic lesions, carcinogenesis, metastasis, and poor prognosis. Hub genes closely related to CRC carcinogenesis were extracted including six genes in model 1 (CXCL1, CXCL3, CXCL8, CXCL11, NMU, and PPBP) and two genes and Metallothioneins (MTs) in model 2 (SLC26A3 and SLC30A10). Among them, CXCL8 was also related to prognosis. An eight-gene signature was proposed comprising AMH, WBSCR28, SFTA2, MYH2, POU4F1, SIX4, PGPEP1L, and PAX5. The study identified hub genes in CRC carcinogenesis and proposed an eight-gene signature with good reproducibility and robustness at the molecular level for CRC, which might provide directive significance for treatment selection and survival prediction.

SUBMITTER: Gong B

PROVIDER: S-EPMC7171686 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identification of Hub Genes Related to Carcinogenesis and Prognosis in Colorectal Cancer Based on Integrated Bioinformatics.

Gong Benjiao B Kao Yanlei Y Zhang Chenglin C Sun Fudong F Gong Zhaohua Z Chen Jian J

Mediators of inflammation 20200409

The high mortality of colorectal cancer (CRC) patients and the limitations of conventional tumor-node-metastasis (TNM) stage emphasized the necessity of exploring hub genes closely related to carcinogenesis and prognosis in CRC. The study is aimed at identifying hub genes associated with carcinogenesis and prognosis for CRC. We identified and validated 212 differentially expressed genes (DEGs) from six Gene Expression Omnibus (GEO) datasets and the Cancer Genome Atlas (TCGA) database. We investi ...[more]

PMID: 32351322

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Project description:Hepatocellular carcinoma (HCC) is a common malignant cancer with poor survival outcomes, and hepatitis B virus (HBV) infection is most likely to contribute to HCC. But the molecular mechanism remains obscure. Our study intended to identify the candidate potential hub genes associated with the carcinogenesis of HBV-related HCC (HBV-HCC), which may be helpful in developing novel tumor biomarkers for potential targeted therapies. Four transcriptome datasets (GSE84402, GSE25097, GSE94660, and GSE121248) were used to screen the 309 overlapping differentially expressed genes (DEGs), including 100 upregulated genes and 209 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were used to explore the biological function of DEGs. A PPI network based on the STRING database was constructed and visualized by the Cytoscape software, consisting of 209 nodes and 1676 edges. Then, we recognized 17 hub genes by CytoHubba plugin, which were further validated on additional three datasets (GSE14520, TCGA-LIHC, and ICGC-LIRI-JP). The diagnostic effectiveness of hub genes was assessed with receiver operating characteristic (ROC) analysis, and all hub genes displayed good performance in discriminating TNM stage I patient samples and normal tissue ones. For prognostic analysis, two prognostic key genes (TOP2A and KIF11) out of the 17 hub genes were screened and used to develop a prognostic signature, which showed good potential for overall survival (OS) stratification of HBV-HCC patients. Gene Set Enrichment Analysis (GSEA) was performed in order to better understand the function of this prognostic gene signature. Finally, the miRNA-mRNA regulatory relationships of all hub genes in human liver were predicted using miRNet. In conclusion, the current study gives further insight on the pathogenesis and carcinogenesis of HBV-HCC, and the identified DEGs provide a promising direction for improving the diagnostic, prognostic, and therapeutic outcomes of HBV-HCC.

Project description:Colorectal cancer (CRC) is a life-threatening disease with a poor prognosis. Therefore, it is crucial to identify molecular prognostic biomarkers for CRC. The present study aimed to identify potential key genes that could be used to predict the prognosis of patients with CRC. Three CRC microarray datasets (GSE20916, GSE73360 and GSE44861) were downloaded from the Gene Expression Omnibus (GEO) database, and one dataset was obtained from The Cancer Genome Atlas (TCGA) database. The three GEO datasets were analyzed to detect differentially expressed genes (DEGs) using the BRB-ArrayTools software. Functional and pathway enrichment analyses of these DEGs were performed using the Database for Annotation, Visualization and Integrated Discovery tool. A protein-protein interaction (PPI) network of DEGs was constructed, hub genes were extracted, and modules of the PPI network were analyzed. To investigate the prognostic values of the hub genes in CRC, data from the CRC datasets of TCGA were used to perform the survival analyses based on the sample splitting method and Cox regression model. Correlation among the hub genes was evaluated using Spearman's correlation analysis. In the three GEO datasets, a total of 105 common DEGs were identified, including 51 down- and 54 up-regulated genes in CRC compared with normal colorectal tissues. A PPI network consisting of 100 DEGs and 551 edges was constructed, and 44 nodes were identified as hub genes. Among these 44 genes, the four hub genes TIMP metallopeptidase inhibitor 1 (TIMP1), solute carrier family 4 member 4 (SLC4A4), aldo-keto reductase family 1 member B10 (AKR1B10) and ATP binding cassette subfamily E member 1 (ABCE1) were associated with overall survival (OS) in patients with CRC. Three significant modules were extracted from the PPI network. The hub gene TIMP1 was present in Module 1, ABCE1 was involved in Module 2 and SLC4A4 was identified in Module 3. Univariate analysis revealed that TIMP1, SLC4A4, AKR1B10 and ABCE1 were associated with the OS of patients with CRC. Multivariate analysis demonstrated that SLC4A4 may be an independent prognostic factor associated with OS. Furthermore, the results from correlation analysis revealed that there was no correlation between TIMP1, SLC4A4 and ABCE1, whereas AKR1B10 was positively correlated with SLC4A4. In conclusion, the four key genes TIMP1, SLC4A4, AKR1B10 and ABCE1 associated with the OS of patients with CRC were identified by integrated bioinformatics analysis. These key genes may be used as prognostic biomarkers to predict the survival of patients with CRC, and may therefore represent novel therapeutic targets for CRC.

Project description:BackgroundAntisense noncoding RNA in the INK4 locus (ANRIL) is located on human chromosome 9p21, and modulation of ANRIL expression mediates susceptibility to some important human disease, including atherosclerosis (AS) and tumors, by affecting the cell cycle circANRIL and linear ANRIL are isoforms of ANRIL. However, it remains unclear whether these isoforms have distinct functions. In our research, we constructed a circANRIL overexpression plasmid, transfected it into HEK-293T cell line, and explored potential core genes and signaling pathways related to the important differential mechanisms between the circANRIL-overexpressing cell line and control cells through bioinformatics analysis.MethodsStable circANRIL-overexpressing (circANRIL-OE) HEK-293T cells and control cells were generated by infection with the circANRIL-OE lentiviral vector or a negative control vector, and successful transfection was confirmed by conventional flurescence microscopy and quantitative real-time PCR (qRT-PCR). Next, differentially expressed genes (DEGs) between circANRIL-OE cells and control cells were detected. Subsequently, Gene Ontology (GO) biological process (BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to explore the principal functions of the significant DEGs. A protein-protein interaction (PPI) network and competing endogenous RNA (ceRNA) network were constructed in Cytoscape to determine circularRNA (circRNA)- microRNA(miRNA)-messenger RNA (mRNA) interactions and hub genes, and qRT-PCR was used to verify changes in the expression of these identified target genes.ResultsThe successful construction of circANRIL-OE cells was confirmed by plasmid sequencing, visualization with fluorescence microscopy and qRT-PCR. A total of 1745 DEGs between the circANRIL-OE group and control were identified, GO BP analysis showed that these genes were mostly related to RNA biosynthesis and processing, regulation of transcription and signal transduction. The KEGG pathway analysis showed that the up regulated DEGs were mainly enriched in the MAPK signaling pathway. Five associated target genes were identified in the ceRNA network and biological function analyses. The mRNA levels of these five genes and ANRIL were detected by qRT-PCR, but only COL5A2 and WDR3 showed significantly different expression in circANRIL-OE cells.

Dataset Information

Identification of Hub Genes Related to Carcinogenesis and Prognosis in Colorectal Cancer Based on Integrated Bioinformatics.

Publications

Identification of Hub Genes Related to Carcinogenesis and Prognosis in Colorectal Cancer Based on Integrated Bioinformatics.

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