Dataset Information

Clinical and Survival Impact of Sex-Determining Region Y-Box 2 in Colorectal Cancer: An Integrated Analysis of the Immunohistochemical Study and Bioinformatics Analysis.

ABSTRACT: Transcription factor sex-determining region Y-box 2 (SOX2) involves in the maintenance of cancer stem cells. However, the role of SOX2 in colorectal cancer (CRC) remains unclear. This study was conducted to investigate the effect of SOX2 on CRC. Studies were searched using electronic databases. The combined odds ratios (ORs) or hazard ratios (HRs: multivariate Cox survival analysis) with their 95% confidence intervals (CIs) were calculated. The Cancer Genome Atlas (TCGA) and GEO datasets were further applied to validate the survival effect. The functional analysis of SOX2 was investigated. In this work, 13 studies including 2337 patients were identified, and validation data were enrolled from TCGA and GEO datasets. SOX2 expression was not significantly related to age, gender, microsatellite instability (MSI) status, clinical stage, histological grade, tumor size, pT-stage, lymph node metastasis, distal metastasis, and cancer-specific survival (CSS) but was correlated with worse overall survival (OS: n?=?536 patients) (P < 0.05). Furthermore, TCGA data demonstrated similar results, with no significant correlation between SOX2 and pathological characteristics. Further validation data (OS: n?=?1408 and disease-free survival (DFS): n?=?1367) showed that SOX2 expression was correlated with worse OS (HR?=?1.35, 95% CI: 1.11-1.65, P=0.004) and DFS (HR?=?1.30, 95% CI: 1.04-1.62, P=0.02). The functional analyses showed that SOX2 involved in cell-cell junction, focal adhesion, extracellular matrix- (ECM-) receptor interaction, and MAP kinase activity. Our findings suggest that SOX2 expression may be correlated with the worse prognosis of CRC.

SUBMITTER: Song K

PROVIDER: S-EPMC7040407 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Clinical and Survival Impact of Sex-Determining Region Y-Box 2 in Colorectal Cancer: An Integrated Analysis of the Immunohistochemical Study and Bioinformatics Analysis.

Song Kun K Hao Jingduo J Ge Zuyin Z Chen Pushi P

Journal of oncology 20200213

Transcription factor sex-determining region Y-box 2 (SOX2) involves in the maintenance of cancer stem cells. However, the role of SOX2 in colorectal cancer (CRC) remains unclear. This study was conducted to investigate the effect of SOX2 on CRC. Studies were searched using electronic databases. The combined odds ratios (ORs) or hazard ratios (HRs: multivariate Cox survival analysis) with their 95% confidence intervals (CIs) were calculated. The Cancer Genome Atlas (TCGA) and GEO datasets were fu ...[more]

PMID: 32104175

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Project description:BackgroundLiver fibrosis and hepatocellular carcinoma (HCC) are common adverse consequences of chronic liver injury. The interaction of various risk factors may cause them to happen. Identification of specific biomarkers is of great significance for understanding the occurrence, development mechanisms, and determining the novel tools for diagnosis and treatment of both liver fibrosis and HCC.AimTo identify liver fibrosis-related core genes, we analyzed the differential expression pattern of core genes in liver fibrosis and HCC.MethodsGene expression profiles of three datasets, GSE14323, GSE36411, and GSE89377, obtained from the Gene Expression Omnibus (GEO) database, were analyzed, and differentially expressed genes (DEGs) between patients with liver cirrhosis and healthy controls were identified by screening via R software packages and online tool for Venn diagrams. The WebGestalt online tool was used to identify DEGs enriched in biological processes, molecular functions, cellular components, and Kyoto Encyclopedia of Genes and Genomes pathways. The protein-protein interactions of DEGs were visualized using Cytoscape with STRING. Next, the expression pattern of core genes was analyzed using Western blot and immunohistochemistry in a carbon tetrachloride (CCl4)-induced liver cirrhosis mouse model and in patient liver samples. Finally, Kaplan-Meier curves were constructed using the Kaplan-Meier plotter online server.ResultsForty-five DEGs (43 upregulated and 2 downregulated genes) associated with liver cirrhosis were identified from three GEO datasets. Ten hub genes were identified, which were upregulated in liver cirrhosis. Western blot and immunohistochemical analyses of the three core genes, decorin (DCN), dermatopontin (DPT), and SRY-box transcription factor 9 (SOX9), revealed that they were highly expressed in the CCl4-induced liver cirrhosis mouse model. The expression levels of DCN and SOX 9 were positively correlated with the degree of fibrosis, and SOX 9 level in HCC patients was significantly higher than that in fibrosis patients. However, high expression of DPT was observed only in patients with liver fibrosis, and its expression in HCC was low. The gene expression profiling interactive analysis server (GEPIA) showed that SOX9 was significantly upregulated whereas DCN and DPT were significantly downregulated in patients with HCC. In addition, the Kaplan-Meier curves showed that HCC patients with higher SOX9 expression had significantly lower 5-year survival rate, while patients with higher expression of DCN or DPT had significantly higher 5-year survival rates.ConclusionThe expression levels of DCN, DPT, and SOX9 were positively correlated with the degree of liver fibrosis but showed different correlations with the 5-year survival rates of HCC patients.

Project description:Ischemic stroke (IS) greatly threatens human health resulting in high mortality and substantial loss of function. Recent studies have shown that the outcome of IS has sex specific, but its mechanism is still unclear. This study is aimed at identifying the sexually dimorphic to peripheral immune response in IS progression, predicting potential prognostic biomarkers that can lead to sex-specific outcome, and revealing potential treatment targets. Gene expression dataset GSE37587, including 68 peripheral whole blood samples which were collected within 24 hours from known onset of symptom and again at 24-48 hours after onset (20 women and 14 men), was downloaded from the Gene Expression Omnibus (GEO) datasets. First, using Bioconductor R package, two kinds of differentially expressed genes (DEGs) (nonsex-specific- and sex-specific-DEGs) were screened by follow-up (24-48 hours) vs. baseline (24 hours). 30 nonsex-specific DEGs (1 upregulated and 29 downregulated), 79 female-specific DEGs (25 upregulated and 54 downregulated), and none of male-specific DEGs were obtained finally. Second, bioinformatics analysis of female-specific DEGs was performed. Gene Ontology (GO) functional annotation analysis shows that DEGs were mainly enriched in translational initiation, cytosolic ribosome, and structural constituent of ribosome. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis shows that the top 6 enrichment pathways are ribosome, nuclear factor--kappa B (NF-kappa B) signaling pathway, apoptosis, mineral absorption, nonalcoholic fatty liver disease, and pertussis. Three functional modules were clustered in the protein-protein interaction (PPI) network of DEGs. The top 10 key genes of the PPI network constructed were selected, including RPS14, RPS15A, RPS24, FAU, RPL27, RPL31, RPL34, RPL35A, RSL24D1, and EEF1B2. Sex difference of ribosome in stroke-induced peripheral immunosuppression may be the potential mechanism of sex disparities in outcome after IS, and women are more likely to have stroke-induced immunosuppression. RPS14, RPS15A, RPS24, FAU, RPL27, RPL31, RPL34, RPL35A, RSL24D1, and EEF1B2 may be novel prognostic biomarkers and potential therapeutic targets for IS.

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Dataset Information

Clinical and Survival Impact of Sex-Determining Region Y-Box 2 in Colorectal Cancer: An Integrated Analysis of the Immunohistochemical Study and Bioinformatics Analysis.

Publications

Clinical and Survival Impact of Sex-Determining Region Y-Box 2 in Colorectal Cancer: An Integrated Analysis of the Immunohistochemical Study and Bioinformatics Analysis.

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