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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...

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Detalles Bibliográficos
Autores principales: Qiu, Ting, Hu, Weitao, Rao, Zilan, Fang, Taiyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
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
Descripción
Sumario: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.