Dataset Information

Screening and Identification of Differentially Expressed Genes Expressed among Left and Right Colon Adenocarcinoma.

ABSTRACT: Purpose:Colon adenocarcinoma (COAD) is the third most common malignancy globally and is further categorized as left colon adenocarcinoma (LCOAD) or right colon adenocarcinoma (RCOAD) depending on the location of the primary tumor. The therapeutic outcome and long-term prognosis for patients with COAD are less than satisfactory, and this may be associated with tumor location. Therefore, it is important to investigate the genetic differences in COAD at different sites. Patients and Methods. Public data associated with COAD were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using R software (version 3.5.3), and functional annotation of DEGs was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. A protein-protein interaction network was constructed, hub genes were identified and analyzed, and data mining using Gene Expression Profiling Interactive Analysis (GEPIA) was conducted. Results:A total of 286 DEGs were identified between LCOAD and RCOAD. Additionally, 10 hub genes associated with COAD at different locations were screened, namely, CDKN2A, IGF1R, MDM2, SMAD3, SLC2A1, GRM5, PLCB4, FGFR1, UBE2V2, and TNFRSF10B. The expression of cyclin-dependent kinase inhibitor 2A (CDKN2A) and solute carrier family 2 member 1 (SLC2A1) was significantly associated with pathological stage (P < 0.05). COAD patients with high expression levels of CDKN2A exhibited poorer overall survival (OS) times than those with low expression levels (P < 0.05). Conclusion:CDKN2A expression was significantly different between LCOAD and RCOAD and was closely related to the prognosis of COAD. It is of great value for further understanding of the pathogenesis of LCOAD and RCOAD.

SUBMITTER: Han J

PROVIDER: S-EPMC7201700 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Screening and Identification of Differentially Expressed Genes Expressed among Left and Right Colon Adenocarcinoma.

Han Jing J Zhang Xue X Yang Yang Y Feng Li L Wang Gui-Ying GY Zhang Nan N

BioMed research international 20200121

<h4>Purpose</h4>Colon adenocarcinoma (COAD) is the third most common malignancy globally and is further categorized as left colon adenocarcinoma (LCOAD) or right colon adenocarcinoma (RCOAD) depending on the location of the primary tumor. The therapeutic outcome and long-term prognosis for patients with COAD are less than satisfactory, and this may be associated with tumor location. Therefore, it is important to investigate the genetic differences in COAD at different sites. <i>Patients and Meth ...[more]

PMID: 32420374

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Project description:BackgroundColon adenocarcinoma (COAD) can be divided into left-sided and right-sided COAD (LCCs and RCCs, respectively). They have unique characteristics in various biological aspects, particularly immune invasion and prognosis. The purpose of our study was to develop a prognostic risk scoring model (PRSM) based on differentially expressed immune-related genes (IRGs) between LCCs and RCCs, therefore the prognostic key IRGs could be identified.MethodsThe gene sets and clinical information of COAD patients were derived from TCGA and GEO databases. The comparison of differentially expressed genes (DEGs) of LCCs and RCCs were conducted with appliance of "Limma" analysis. The establishment about co-expression modules of DEGs related with immune score was conducted by weighted gene co-expression network analysis (WGCNA). Furthermore, we screened the module genes and completed construction of gene pairs. The analysis of the prognosis and the establishment of PRSM were performed with univariate- and lasso-Cox regression. We employed the PRSM in the model group and verification group for the purpose of risk group assignment and PRSM accuracy verification. Finally, the identification of the prognostic key IRGs was guaranteed by the adoption of functional enrichment, "DisNor" and protein-protein interaction (PPI).ResultsA total of 215 genes were screened out by differential expression analysis and WGCNA. A PRSM with 16 immune-related gene pairs (IRGPs) was established upon the genes pairing. Furthermore, we confirmed that the risk score was an independent factor for survival by univariate- and multivariate-Cox regression. The prognosis of high-risk group in model group (P < 0.001) and validation group (P = 0.014) was significantly worse than that in low-risk group. Treg cells (P < 0.001) and macrophage M0 (P = 0.015) were highly expressed in the high-risk group. The functional analysis indicated that there was significant up-regulation with regard of lymphocyte and cytokine related terms in low-risk group. Finally, we identified five prognostic key IRGs associated with better prognosis through PPI and prognostic analysis, including IL2RB, TRIM22, CIITA, CXCL13, and CXCR6.ConclusionThrough the analysis and screening of the DEGs between LCCs and RCCs, we constructed a PRSM which could predicate prognosis of LCCs and RCCs, and five prognostic key IRGs were identified as well. Therefore, the basis for identifying the benefits of immunotherapy and immunomodulatory was built.

Project description:BackgroundDNA methylation, acknowledged as a key modification in the field of epigenetics, regulates gene expression at the transcriptional level. Aberrant methylation in DNA regulatory regions could upregulate oncogenes and downregulate tumor suppressor genes without changing the sequences. However, studies of methylation in the control of gene expression are still inadequate. In the present research, we performed bioinformatics analysis to clarify the function of methylation and supply candidate methylation-related biomarkers and drivers for colon cancer.AimTo identify and analyze methylation-regulated differentially expressed genes (MeDEGs) in colon cancer by bioinformatics analysis.MethodsWe downloaded RNA expression profiles, Illumina Human Methylation 450K BeadChip data, and clinical data of colon cancer from The Cancer Genome Atlas project. MeDEGs were identified by analyzing the gene expression and methylation levels using the edgeR and limma package in R software. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed in the DAVID database and KEGG Orthology-Based Annotation System 3.0, respectively. We then conducted Kaplan-Meier survival analysis to explore the relationship between methylation and expression and prognosis. Gene set enrichment analysis (GSEA) and investigation of protein-protein interactions (PPI) were performed to clarify the function of prognosis-related genes.ResultsA total of 5 up-regulated and 81 down-regulated genes were identified as MeDEGs. GO and KEGG pathway analyses indicated that MeDEGs were enriched in multiple cancer-related terms. Furthermore, Kaplan-Meier survival analysis showed that the prognosis was negatively associated with the methylation status of glial cell-derived neurotrophic factor (GDNF) and reelin (RELN). In PPI networks, GDNF and RELN interact with neural cell adhesion molecule 1. Besides, GDNF can interact with GDNF family receptor alpha (GFRA1), GFRA2, GFRA3, and RET. RELN can interact with RAFAH1B1, disabled homolog 1, very low-density lipoprotein receptor, lipoprotein receptor-related protein 8, and NMDA 2B. Based on GSEA, hypermethylation of GDNF and RELN were both significantly associated with pathways including "RNA degradation," "ribosome," "mismatch repair," "cell cycle" and "base excision repair."ConclusionAberrant DNA methylation plays an important role in colon cancer progression. MeDEGs that are associated with the overall survival of patients may be potential targets in tumor diagnosis and treatment.

Project description:Gastric adenocarcinoma is an aggressive cancer with poor prognosis. Blood based biomarkers of gastric cancer have the potential to improve diagnosis and monitoring of these tumors. Proteins that show altered levels in the circulation of gastric cancer patients could prove useful as putative biomarkers. We used an iTRAQ-based quantitative proteomic approach to identify proteins that show altered levels in the sera of patients with gastric cancer. Our study resulted in identification of 643 proteins, of which 48 proteins showed increased levels and 11 proteins showed decreased levels in serum from gastric cancer patients compared to age and sex matched healthy controls. Proteins that showed increased expression in gastric cancer included inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4), Mannose-binding protein C (MBL2), sex hormone-binding globulin (SHBG), insulin-like growth factor-binding protein 2 (IGFBP2), serum amyloid A protein (SAA1), Orosomucoid 1 (ORM1) and extracellular superoxide dismutase [Cu-Zn] (SOD3). We used multiple reaction monitoring assays and validated elevated levels of ITIH4 and SAA1 proteins in serum from gastric cancer patients.Biological significanceGastric cancer is a highly aggressive cancer associated with high mortality. Serum-based biomarkers are of considerable interest in diagnosis and monitoring of various diseases including cancers. Gastric cancer is often diagnosed at advanced stages resulting in poor prognosis and high mortality. Pathological diagnosis using biopsy specimens remains the gold standard for diagnosis of gastric cancer. Serum-based biomarkers are of considerable importance as they are minimally invasive. In this study, we carried out quantitative proteomic profiling of serum from gastric cancer patients to identify proteins that show altered levels in gastric cancer patients. We identified more than 50 proteins that showed altered levels in gastric cancer patient sera. Validation in a large cohort of well classified patient samples would prove useful in identifying novel blood based biomarkers for gastric cancers. This article is part of a Special Issue entitled: Proteomics in India.

Dataset Information

Screening and Identification of Differentially Expressed Genes Expressed among Left and Right Colon Adenocarcinoma.

Publications

Screening and Identification of Differentially Expressed Genes Expressed among Left and Right Colon Adenocarcinoma.

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