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Predicting MicroRNA Target Genes and Identifying Hub Genes in IIA Stage Colon Cancer Patients Using Bioinformatics Analysis

BACKGROUND: Colon cancer is a heterogeneous disease, differing in clinical symptoms, epigenetics, and prognosis for each individual patient. Identifying the core genes is important for early diagnoses and it provides a more precise method for treating colon cancer. MATERIALS AND METHODS: In this stu...

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Autores principales: Dong, Zhiyong, Lin, Wei, Kujawa, Stacy A., Wu, Shike, Wang, Cunchuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6383401/
https://www.ncbi.nlm.nih.gov/pubmed/30881993
http://dx.doi.org/10.1155/2019/6341967
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author Dong, Zhiyong
Lin, Wei
Kujawa, Stacy A.
Wu, Shike
Wang, Cunchuan
author_facet Dong, Zhiyong
Lin, Wei
Kujawa, Stacy A.
Wu, Shike
Wang, Cunchuan
author_sort Dong, Zhiyong
collection PubMed
description BACKGROUND: Colon cancer is a heterogeneous disease, differing in clinical symptoms, epigenetics, and prognosis for each individual patient. Identifying the core genes is important for early diagnoses and it provides a more precise method for treating colon cancer. MATERIALS AND METHODS: In this study, we wanted to pinpoint these core genes so we obtained GSE101502 microRNA profiles from the GEO database, which resulted in 17 differential expressed microRNAs that were identified by GEO2R analysis. Then, 875 upregulated and 2920 downregulated target genes were predicted by FunRich. GO and KEGG pathway were used to do enrich analysis. RESULTS: GO analysis indicated that upregulated genes were significantly enriched in the regulation of cell communication and signaling and in nervous system development, while the downregulated genes were significantly enriched in nervous system development and regulation of transcription from the RNA polymerase II promoter. KEGG pathway analysis suggested that the upregulated genes were enriched in axon guidance, MAPK signaling pathway, and endocytosis, while the downregulated genes existed in pathways in cancer, focal adhesion, and PI3K-Akt signaling pathway. The top four molecules including 82 hub genes were identified from the PPI network and involved in endocytosis, spliceosome, TGF-beta signaling pathway, and lysosome. Finally, NUDT21, GNB1, CLINT1, and COL1A2 core gene were selected due to their correlation with the prognosis of IIA stage colon cancer. CONCLUSION: this study suggested that NUDT21, GNB1, CLINT1, and COL1A2 might be the core genes for colon cancer that play an important role in the development and prognosis of IIA stage colon cancer.
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spelling pubmed-63834012019-03-17 Predicting MicroRNA Target Genes and Identifying Hub Genes in IIA Stage Colon Cancer Patients Using Bioinformatics Analysis Dong, Zhiyong Lin, Wei Kujawa, Stacy A. Wu, Shike Wang, Cunchuan Biomed Res Int Research Article BACKGROUND: Colon cancer is a heterogeneous disease, differing in clinical symptoms, epigenetics, and prognosis for each individual patient. Identifying the core genes is important for early diagnoses and it provides a more precise method for treating colon cancer. MATERIALS AND METHODS: In this study, we wanted to pinpoint these core genes so we obtained GSE101502 microRNA profiles from the GEO database, which resulted in 17 differential expressed microRNAs that were identified by GEO2R analysis. Then, 875 upregulated and 2920 downregulated target genes were predicted by FunRich. GO and KEGG pathway were used to do enrich analysis. RESULTS: GO analysis indicated that upregulated genes were significantly enriched in the regulation of cell communication and signaling and in nervous system development, while the downregulated genes were significantly enriched in nervous system development and regulation of transcription from the RNA polymerase II promoter. KEGG pathway analysis suggested that the upregulated genes were enriched in axon guidance, MAPK signaling pathway, and endocytosis, while the downregulated genes existed in pathways in cancer, focal adhesion, and PI3K-Akt signaling pathway. The top four molecules including 82 hub genes were identified from the PPI network and involved in endocytosis, spliceosome, TGF-beta signaling pathway, and lysosome. Finally, NUDT21, GNB1, CLINT1, and COL1A2 core gene were selected due to their correlation with the prognosis of IIA stage colon cancer. CONCLUSION: this study suggested that NUDT21, GNB1, CLINT1, and COL1A2 might be the core genes for colon cancer that play an important role in the development and prognosis of IIA stage colon cancer. Hindawi 2019-02-07 /pmc/articles/PMC6383401/ /pubmed/30881993 http://dx.doi.org/10.1155/2019/6341967 Text en Copyright © 2019 Zhiyong Dong et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Dong, Zhiyong
Lin, Wei
Kujawa, Stacy A.
Wu, Shike
Wang, Cunchuan
Predicting MicroRNA Target Genes and Identifying Hub Genes in IIA Stage Colon Cancer Patients Using Bioinformatics Analysis
title Predicting MicroRNA Target Genes and Identifying Hub Genes in IIA Stage Colon Cancer Patients Using Bioinformatics Analysis
title_full Predicting MicroRNA Target Genes and Identifying Hub Genes in IIA Stage Colon Cancer Patients Using Bioinformatics Analysis
title_fullStr Predicting MicroRNA Target Genes and Identifying Hub Genes in IIA Stage Colon Cancer Patients Using Bioinformatics Analysis
title_full_unstemmed Predicting MicroRNA Target Genes and Identifying Hub Genes in IIA Stage Colon Cancer Patients Using Bioinformatics Analysis
title_short Predicting MicroRNA Target Genes and Identifying Hub Genes in IIA Stage Colon Cancer Patients Using Bioinformatics Analysis
title_sort predicting microrna target genes and identifying hub genes in iia stage colon cancer patients using bioinformatics analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6383401/
https://www.ncbi.nlm.nih.gov/pubmed/30881993
http://dx.doi.org/10.1155/2019/6341967
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