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The molecular basis of the associations between non-alcoholic fatty liver disease and colorectal cancer
Background: Given the ongoing research on non-alcoholic fatty liver disease (NAFLD) and colorectal cancer (CRC), the number of studies suggesting a strong link between NAFLD and CRC is on the rise, while its underlying pathological mechanisms remain uncertain. This study aims to explore the shared g...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9780501/ https://www.ncbi.nlm.nih.gov/pubmed/36568397 http://dx.doi.org/10.3389/fgene.2022.1007337 |
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author | Qiu, Ting Hu, Weitao Rao, Zilan Fang, Taiyong |
author_facet | Qiu, Ting Hu, Weitao Rao, Zilan Fang, Taiyong |
author_sort | Qiu, Ting |
collection | PubMed |
description | Background: Given the ongoing research on non-alcoholic fatty liver disease (NAFLD) and colorectal cancer (CRC), the number of studies suggesting a strong link between NAFLD and CRC is on the rise, while its underlying pathological mechanisms remain uncertain. This study aims to explore the shared genes and mechanisms and to reveal the molecular basis of the association between CRC and NAFLD through bioinformatics approaches. Methods: The Gene Expression Omnibus (GEO) dataset GSE89632 is downloaded for NAFLD cases and healthy controls. Additionally, the GSE4107 and GSE9348 datasets are obtained for CRC cases and healthy controls. Differentially expressed genes (DEGs) are obtained for NAFLD and CRC datasets, as well as shared genes between the two disorders. GO and KEGG enrichment analyses are further conducted. Subsequently, the STRING database and Cytoscape software are utilized to establish the PPI network and identify the hub genes. Then, co-expression analysis is performed using GeneMANIA. Subsequently, ROC curves and external datasets validation were applied to further screen the candidate markers. Finally, NetworkAnalyst is available as a means to construct a miRNA-gene regulatory network. Results: Under the threshold of FDR ≤ 0.01, 147 common genes are obtained in NAFLD and CRC. Categorization of GO functions shows that DEGs are predominantly enriched in “response to organic substance”, “cellular response to chemical stimulus”, and “response to external stimulus”. The predominant KEGG pathways in DEGs are the “IL-17 signaling pathway”, the “TNF signaling pathway”, “Viral protein interaction with cytokine and cytokine receptor”, “Cytokine-cytokine receptor interaction”, and the “Toll-like receptor signaling pathway”. Additionally, MYC, IL1B, FOS, CXCL8, PTGS2, MMP9, JUN, and IL6 are identified as hub genes by the evaluation of 7 algorithms. With the construction of miRNA-gene networks, 2 miRNAs, including miR-106a-5p, and miR-204-5p are predicted to be potential key miRNAs. Conclusion: This study identifies possible hub genes acting in the co-morbidity of NAFLD and CRC and discovers the interaction of miRNAs and hub genes, providing a novel understanding of the molecular basis for the relevance of CRC and NAFLD, thus contributing to the development of new therapeutic strategies to combat NAFLD and CRC. |
format | Online Article Text |
id | pubmed-9780501 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97805012022-12-24 The molecular basis of the associations between non-alcoholic fatty liver disease and colorectal cancer Qiu, Ting Hu, Weitao Rao, Zilan Fang, Taiyong Front Genet Genetics Background: Given the ongoing research on non-alcoholic fatty liver disease (NAFLD) and colorectal cancer (CRC), the number of studies suggesting a strong link between NAFLD and CRC is on the rise, while its underlying pathological mechanisms remain uncertain. This study aims to explore the shared genes and mechanisms and to reveal the molecular basis of the association between CRC and NAFLD through bioinformatics approaches. Methods: The Gene Expression Omnibus (GEO) dataset GSE89632 is downloaded for NAFLD cases and healthy controls. Additionally, the GSE4107 and GSE9348 datasets are obtained for CRC cases and healthy controls. Differentially expressed genes (DEGs) are obtained for NAFLD and CRC datasets, as well as shared genes between the two disorders. GO and KEGG enrichment analyses are further conducted. Subsequently, the STRING database and Cytoscape software are utilized to establish the PPI network and identify the hub genes. Then, co-expression analysis is performed using GeneMANIA. Subsequently, ROC curves and external datasets validation were applied to further screen the candidate markers. Finally, NetworkAnalyst is available as a means to construct a miRNA-gene regulatory network. Results: Under the threshold of FDR ≤ 0.01, 147 common genes are obtained in NAFLD and CRC. Categorization of GO functions shows that DEGs are predominantly enriched in “response to organic substance”, “cellular response to chemical stimulus”, and “response to external stimulus”. The predominant KEGG pathways in DEGs are the “IL-17 signaling pathway”, the “TNF signaling pathway”, “Viral protein interaction with cytokine and cytokine receptor”, “Cytokine-cytokine receptor interaction”, and the “Toll-like receptor signaling pathway”. Additionally, MYC, IL1B, FOS, CXCL8, PTGS2, MMP9, JUN, and IL6 are identified as hub genes by the evaluation of 7 algorithms. With the construction of miRNA-gene networks, 2 miRNAs, including miR-106a-5p, and miR-204-5p are predicted to be potential key miRNAs. Conclusion: This study identifies possible hub genes acting in the co-morbidity of NAFLD and CRC and discovers the interaction of miRNAs and hub genes, providing a novel understanding of the molecular basis for the relevance of CRC and NAFLD, thus contributing to the development of new therapeutic strategies to combat NAFLD and CRC. Frontiers Media S.A. 2022-12-09 /pmc/articles/PMC9780501/ /pubmed/36568397 http://dx.doi.org/10.3389/fgene.2022.1007337 Text en Copyright © 2022 Qiu, Hu, Rao and Fang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Qiu, Ting Hu, Weitao Rao, Zilan Fang, Taiyong The molecular basis of the associations between non-alcoholic fatty liver disease and colorectal cancer |
title | The molecular basis of the associations between non-alcoholic fatty liver disease and colorectal cancer |
title_full | The molecular basis of the associations between non-alcoholic fatty liver disease and colorectal cancer |
title_fullStr | The molecular basis of the associations between non-alcoholic fatty liver disease and colorectal cancer |
title_full_unstemmed | The molecular basis of the associations between non-alcoholic fatty liver disease and colorectal cancer |
title_short | The molecular basis of the associations between non-alcoholic fatty liver disease and colorectal cancer |
title_sort | molecular basis of the associations between non-alcoholic fatty liver disease and colorectal cancer |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9780501/ https://www.ncbi.nlm.nih.gov/pubmed/36568397 http://dx.doi.org/10.3389/fgene.2022.1007337 |
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