Identification and prediction of novel non-coding and coding RNA-associated competing endogenous RNA networks in colorectal cancer
| Autor: | Cheng Zhang, Ming-Hui Ma, Dong-Qiu Dai, Yu Liang |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Bioinformatics analysis Colorectal cancer Kaplan-Meier Estimate Computational biology Biology 03 medical and health sciences Cell Line Tumor microRNA medicine Overall survival Humans Gene Regulatory Networks RNA Messenger Competing endogenous RNA Gene Expression Profiling Gastroenterology Computational Biology RNA MicroRNA General Medicine Basic Study Prognosis medicine.disease LncRNA Gene Expression Regulation Neoplastic MicroRNAs 030104 developmental biology RNA Long Noncoding Identification (biology) Colorectal Neoplasms Coding (social sciences) |
| Zdroj: | World Journal of Gastroenterology |
| ISSN: | 1007-9327 |
| Popis: | AIM To identify and predict the competing endogenous RNA (ceRNA) networks in colorectal cancer (CRC) by bioinformatics analysis. METHODS In the present study, we obtained CRC tissue and normal tissue gene expression profiles from The Cancer Genome Atlas project. Differentially expressed (DE) genes (DEGs) were identified. Then, upregulated and downregulated miRNA-centered ceRNA networks were constructed by analyzing the DEGs using multiple bioinformatics approaches. DEmRNAs in the ceRNA networks were identified in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways using KEGG Orthology Based Annotation System 3.0. The interactions between proteins were analyzed using the STRING database. Kaplan-Meier survival analysis was conducted for DEGs and real time quantitative polymerase chain reaction (RT-qPCR) was also performed to validate the prognosis-associated lncRNAs in CRC cell lines. RESULTS Eighty-one DElncRNAs, 20 DEmiRNAs, and 54 DEmRNAs were identified to construct the ceRNA networks of CRC. The KEGG pathway analysis indicated that nine out of top ten pathways were related with cancer and the most significant pathway was “colorectal cancer”. Kaplan-Meier survival analysis showed that the overall survival was positively associated with five DEGs (IGF2-AS, POU6F2-AS2, hsa-miR-32, hsa-miR-141, and SERPINE1) and it was negatively related to three DEGs (LINC00488, hsa-miR-375, and PHLPP2). Based on the STRING protein database, it was found that SERPINE1 and PHLPP2 interact with AKT1. Besides, SERPINE1 can interact with VEGFA, VTN, TGFB1, PLAU, PLAUR, PLG, and PLAT. PHLPP2 can interact with AKT2 and AKT3. RT-qPCR revealed that the expression of IGF2-AS, POU6F2-AS2, and LINC00488 in CRC cell lines was consistent with the in silico results. CONCLUSION CeRNA networks play an important role in CRC. Multiple DEGs are related with clinical prognosis, suggesting that they may be potential targets in tumor diagnosis and treatment. |
| Databáze: | OpenAIRE |
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