Dataset Information

Identification of key lncRNAs in colorectal cancer progression based on associated protein-protein interaction analysis.

ABSTRACT: Colorectal cancer (CRC) was one of the most commonly diagnosed malignancies. The molecular mechanisms involved in the progression of CRC remain unclear. Accumulating evidences showed that long noncoding RNAs (lncRNAs) played key roles in tumorigenesis, cancer progression, and metastasis. Therefore, we aimed to explore the roles of lncRNAs in the progression of CRC.In this study, we aimed to identify differentially expressed lncRNAs and messenger RNAs (mRNAs) in CRC by analyzing a cohort of previously published datasets: GSE64857. GO and KEGG pathway analyses were applied to give us insight in the functions of those lncRNAs and mRNAs in CRC.Totally, 46 lncRNAs were identified as differentially expressed between stage II and stage III CRC for the first time screening by microarray. GO and KEGG pathway analyses showed that differentially expressed lncRNAs were involved in regulating signal transduction, cell adhesion, cell differentiation, focal adhesion, and cell adhesion molecules.We found three lncRNAs (LOC100129973, PGM5-AS1, and TTTY10) widely co-expressed with differentially expressed mRNAs. We also constructed lncRNA-associated PPI in CRC and found that these lncRNAs may be associated with CRC progression. Moreover, we found that high PGM5-AS1 expression levels were associated with worse overall survival in CRC cancer. We believe that this study would provide novel potential therapeutic and prognostic targets for CRC.

SUBMITTER: Zhu H

PROVIDER: S-EPMC5553992 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Identification of key lncRNAs in colorectal cancer progression based on associated protein-protein interaction analysis.

Zhu Haishan H Yu Jiajing J Zhu Haifeng H Guo Yusheng Y Feng Shengjie S

World journal of surgical oncology 20170810 1

<h4>Background</h4>Colorectal cancer (CRC) was one of the most commonly diagnosed malignancies. The molecular mechanisms involved in the progression of CRC remain unclear. Accumulating evidences showed that long noncoding RNAs (lncRNAs) played key roles in tumorigenesis, cancer progression, and metastasis. Therefore, we aimed to explore the roles of lncRNAs in the progression of CRC.<h4>Methods</h4>In this study, we aimed to identify differentially expressed lncRNAs and messenger RNAs (mRNAs) in ...[more]

PMID: 28797257

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Project description:Colorectal cancer (CRC) is known to display a high risk of metastasis and recurrence. The main objective of our investigation was to shed more light on CRC pathogenesis by screening CRC datasets for the identification of key genes and signaling pathways, possibly leading to new approaches for the diagnosis and treatment of CRC. We downloaded the colorectal cancer datasets from the Gene Expression Omnibus (GEO) database site. We used GEO2R to screen for differentially expressed genes (DEGs) of which those with a fold change >1 were considered as up-regulated and those with a fold change <-1 were considered as down-regulated on the basis of a P < .05. "Gene ontology (GO)" and "Kyoto Encyclopedia of Genes and Genomes (KEGG)" data were analyzed by the "DAVID" software. The online search tool "STRING" was used to search for interacting genes or proteins and we used Cytoscape (v3.8.0) to generate a PPI network map and to identify key genes. Finally, survival analysis and stage mapping of key genes were performed using "GEPIA" with the aim of elucidating their potential impact on CRC. Our study revealed 120 intersecting genes of which 55 were up- and 65 were downregulated, respectively. GO analysis revealed that these genes were involved in cell proliferation, exosome secretion, G2/M transition, cytosol, protein binding, and protein kinase activity. KEGG pathway analysis showed that these genes were involved in cell cycle and mineral absorption. The Cytoscape PPI map showed 17 nodes and 262 edges, and 10 hub genes were identified by top 10 degrees. Survival analysis demonstrated that the AURKA, CCNB1, and CCNA2 genes were strongly associated with the survival rate of CRC patients. In addition, CCNB1, CCNA2, CDK1, CKS2, MAD2L1, and DLGAP5 could be correlated to pathological CRC staging. In this research, we identified key genes that may explain the molecular mechanism of occurrence and progression of CRC but may also contribute to an improvement in the clinical staging and prognosis of CRC patients.

Dataset Information

Identification of key lncRNAs in colorectal cancer progression based on associated protein-protein interaction analysis.

Publications

Identification of key lncRNAs in colorectal cancer progression based on associated protein-protein interaction analysis.

Similar Datasets

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