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: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.Gastric 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.

Project description:OBJECTIVE:To analyze the differentially expressed genes (DEGs) between lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) with bioinformatics analysis and search for potential biomarkers for clinical diagnosis of nonsmall cell lung cancer (NSCLC). METHODS:The gene expression profiling datasets of LUAD and LUSC were acquired. The transcriptome differences between LUAD and LUSC were identified using R language processing and t-test analysis. The differential expressions of the genes were shown by Venn diagram. The DEGs identified by GEO2R were analyzed with DAVID and Ingenuity Pathway Analysis (IPA) to identify the signaling pathways and biomarkers that could be used for differential diagnosis of LUAD and LUSC. The TCGA data and the biomarker expression data from clinical lung cancer samples were used to verify the differential expressions of the Osteoarthritis pathway and LXR/RXR between LUAD and LUSC. We further examined the differential expressions of miR-181 and its two target genes, WNT5A and MBD2, in 23 clinical specimens of lung squamous cell carcinoma and the paired adjacent tissues. RESULTS:GEO data analysis identified 851 DEGs (including 276 up-regulated and 575 down-regulated genes) in LUAD and 885 DEGs (including 406 up-regulated and 479 down-regulated genes) in LUSC. DAVID and IPA analysis revealed that leukocyte migration and inflammatory responses were more abundant in LUAD than in LUSC. Osteoarthritis pathway was inhibited in LUAD and activated in LUSC. IPA analysis showed that transcription factors (GATA4, RELA, YBX1, TP63 and MBD2), cytokines (WNT5A and IL1A) and microRNAs (miR-34a, miR-181b and miR-15a) differed significantly between LUAD and LUSC. miR-34a with IL-1A, miR-15a with YBX1, and miR-181b with WNT5A and MBD2 could serve as the paired microRNA and mRNA targets for differential diagnosis of NSCLC subtypes. Analysis of the clinical samples showed an increased expression of miR-181b-5p and the down-regulation of WNT5A, which could be used as molecular markers for the diagnosis of LUSC. CONCLUSIONS:Through transcriptome analysis, we identified candidate genes, paired microRNAs and pathways for differentiating LUAD and LUSC, and they can provide novel differential diagnosis and therapeutic strategies for LUAD and LUSC.

Dataset Information

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

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

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