Dataset Information

Bioinformatics Analysis and Validation of the Expressed Sequences Tag in Human Colorectal Adenocarcinoma.

ABSTRACT: BACKGROUND:This study was to investigate some new pathological genes in colorectal adenocarcinoma of human. METHODS:Human colorectal adenocarcinoma tissues and normal colorectal tissues were taken and suppression subtractive hybridization (SSH) and cDNA microarray techniques were employed. From differentially expressed 86 expressed sequence tags (EST), 10 EST of the SSH were selected as seed sequence for bioinformatics analyses, semi-quantitative RT-PCR and PCR-sequencing. Each lane of semi-quantitative RT-PCR was analyzed by Q1 software. RESULTS:Among these 10 EST, it has been found that ES274070, ES274071, ES274076 and ES274081 may play role in the onset of colorectal adenocarcinoma in human. CONCLUSIONS:The ES274070, ES274071, ES274076 and ES274081 are related to the onset of human colorectal adenocarcinoma.

SUBMITTER: Chen Y

PROVIDER: S-EPMC5139827 | biostudies-literature | 2009 Apr

REPOSITORIES: biostudies-literature

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Bioinformatics Analysis and Validation of the Expressed Sequences Tag in Human Colorectal Adenocarcinoma.

Chen Yao Y Zhang Chun Le CL Shen Yong Qiang YQ Wang Li Cheng LC

Gastroenterology research 20090320 2

<h4>Background</h4>This study was to investigate some new pathological genes in colorectal adenocarcinoma of human.<h4>Methods</h4>Human colorectal adenocarcinoma tissues and normal colorectal tissues were taken and suppression subtractive hybridization (SSH) and cDNA microarray techniques were employed. From differentially expressed 86 expressed sequence tags (EST), 10 EST of the SSH were selected as seed sequence for bioinformatics analyses, semi-quantitative RT-PCR and PCR-sequencing. Each la ...[more]

PMID: 27956963

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Project description:Osteoarthritis (OA), also known as degenerative arthritis, affects millions of people all over the world. OA occurs when the cartilage wears down over time, which is a worldwide complaint. The aim of this study was to screen and verify hub genes involved in developmental chondrogenesis as well as to explore potential molecular mechanisms.The expression profiles of GSE51812 were downloaded from the Gene Expression Omnibus (GEO) database, which contained 9 samples, including 6-week pre-chondrocytes (PC, 6 independent specimens) and 17-week fetal periarticular resting chondrocytes (RC, 3 independent specimens). The raw data were integrated to obtain differentially expressed genes (DEGs) and were further analyzed with bioinformatics analysis. The Gene Ontology (GO) and pathway enrichment of DEGs were conducted via Database for Annotation, Visualization, and Integrated Discovery (DAVID). The protein-protein interaction (PPI) networks of the DEGs were constructed based on data from the search tool for the retrieval of interacting genes (STRING) database. An intersection figure was provided to show the relationship between the DEGs identified in this study and genes from any existed related studies.A total of 9486 DEGs, including 4821 upregulated genes and 4665 downregulated genes were observed. The top 30 developmental chondrogenesis associated genes were identified, including matrix metalloproteinase (MMP)1, MMP3, MMP13, prostaglandin-endoperoxide synthase 2 (PTGS2), and so on. The majority of DEGs, including PTGS2, CCL20, CHI3L1, LIF, CXCL8, and CXCL12 were intensively enriched in immune-associated biological process terms, including inflammatory, and immune responses. Additionally, the majority of DEGs were mainly enriched in NF-kappa β (NF-kβ) signaling pathway and tumor necrosis factor (TNF) signaling pathway. The hub genes identified in STRING and Cytoscape databases included MMP1, MMP3, MMP13, PTGS2 and so on. Among the top 30 upregulated and downregulated DEGs, there were 15 genes have been reported to be associated with OA or developmental chondrogenesis.This large scale gene expression study observed genes associated with human developmental chondrogenesis and their relative GO function, which may offer opportunities for the research for cartilage tissue engineering and novel insights into the prevention of OA in the near future.

Project description:BackgroundLung adenocarcinoma is the main pathological type of non-small cell lung cancer (NSCLC). In this study, we analyzed the gene expression profile of lung adenocarcinoma tumor and paracancerous tissues by bioinformatics to assess the genes and signal pathways related to lung adenocarcinoma.MethodsThe expression data of GSE7670, GSE27262, and GSE32863 were downloaded from the Gene Expression Omnibus (GEO) database. The three microarray data sets were integrated to obtain common differential expression genes of lung adenocarcinoma tumor and adjacent tissues. The STRING database was used to construct the protein-protein interaction (PPI) network of lung adenocarcinoma and mine the gene modules and core genes in the network, and the online tools, GEPIA and Kaplan-Meier plotter were used to further verify and analyze the core genes.ResultsThere were 109 pairs of lung adenocarcinoma tissues and matched paracancerous normal lung tissues in the three data sets. Eighty-three differentially expressed genes were identified, including 16 up-regulated and 67 down-regulated genes, and 60 differentially expressed genes were successfully incorporated into the PPI network complex. Eleven core genes were identified in the PPI network complex, including three up-regulated (COMP, SPP1, COL1A1) and eight down-regulated genes (CDH5, CAV1, CLDN5, LYVE1, IL6, VWF, TEK, PECAM1). These core genes were verified by the GEPIA tumor database. Survival analysis showed that expression of the core genes was significantly related to the prognosis of lung adenocarcinoma. KEGG pathway analysis of core genes showed six genes (COMP, SPP1, COL1A1, IL6, VWF, TEK) were significantly enriched in the PI3K-Akt signaling-pathway (P=1.62E-06).ConclusionsBy analyzing the differential expression genes of lung adenocarcinoma and paracancerous normal tissues with bioinformatics, 11 genes with significant differential expression and significant influence on prognosis were identified. The findings may provide new concepts for developing diagnosis and treatment targets and prognosis markers for lung adenocarcinoma.

Dataset Information

Bioinformatics Analysis and Validation of the Expressed Sequences Tag in Human Colorectal Adenocarcinoma.

Publications

Bioinformatics Analysis and Validation of the Expressed Sequences Tag in Human Colorectal Adenocarcinoma.

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