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Key genes associated with non-alcoholic fatty liver disease and hepatocellular carcinoma with metabolic risk factors

Background: Hepatocellular carcinoma (HCC) has become the world’s primary cause of cancer death. Obesity, hyperglycemia, and dyslipidemia are all illnesses that are part of the metabolic syndrome. In recent years, this risk factor has become increasingly recognized as a contributing factor to HCC. A...

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Autores principales: Yang, Fan, Ni, Beibei, Lian, Qinghai, Qiu, Xiusheng, He, Yizhan, Zhang, Qi, Zou, Xiaoguang, He, Fangping, Chen, Wenjie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10025510/
https://www.ncbi.nlm.nih.gov/pubmed/36950134
http://dx.doi.org/10.3389/fgene.2023.1066410
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author Yang, Fan
Ni, Beibei
Lian, Qinghai
Qiu, Xiusheng
He, Yizhan
Zhang, Qi
Zou, Xiaoguang
He, Fangping
Chen, Wenjie
author_facet Yang, Fan
Ni, Beibei
Lian, Qinghai
Qiu, Xiusheng
He, Yizhan
Zhang, Qi
Zou, Xiaoguang
He, Fangping
Chen, Wenjie
author_sort Yang, Fan
collection PubMed
description Background: Hepatocellular carcinoma (HCC) has become the world’s primary cause of cancer death. Obesity, hyperglycemia, and dyslipidemia are all illnesses that are part of the metabolic syndrome. In recent years, this risk factor has become increasingly recognized as a contributing factor to HCC. Around the world, non-alcoholic fatty liver disease (NAFLD) is on the rise, especially in western countries. In the past, the exact pathogenesis of NAFLD that progressed to metabolic risk factors (MFRs)-associated HCC has not been fully understood. Methods: Two groups of the GEO dataset (including normal/NAFLD and HCC with MFRs) were used to analyze differential expression. Differentially expressed genes of HCC were verified by overlapping in TCGA. In addition, functional enrichment analysis, modular analysis, Receiver Operating Characteristic (ROC) analysis, LASSO analysis, and Genes with key survival characteristics were analyzed. Results: We identified six hub genes (FABP5, SCD, CCL20, AGPAT9(GPAT3), PLIN1, and IL1RN) that may be closely related to NAFLD and HCC with MFRs. We constructed survival and prognosis gene markers based on FABP5, CCL20, AGPAT9(GPAT3), PLIN1, and IL1RN.This gene signature has shown good diagnostic accuracy in both NAFLD and HCC and in predicting HCC overall survival rates. Conclusion: As a result of the findings of this study, there is some guiding significance for the diagnosis and treatment of liver disease associated with NAFLD progression.
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spelling pubmed-100255102023-03-21 Key genes associated with non-alcoholic fatty liver disease and hepatocellular carcinoma with metabolic risk factors Yang, Fan Ni, Beibei Lian, Qinghai Qiu, Xiusheng He, Yizhan Zhang, Qi Zou, Xiaoguang He, Fangping Chen, Wenjie Front Genet Genetics Background: Hepatocellular carcinoma (HCC) has become the world’s primary cause of cancer death. Obesity, hyperglycemia, and dyslipidemia are all illnesses that are part of the metabolic syndrome. In recent years, this risk factor has become increasingly recognized as a contributing factor to HCC. Around the world, non-alcoholic fatty liver disease (NAFLD) is on the rise, especially in western countries. In the past, the exact pathogenesis of NAFLD that progressed to metabolic risk factors (MFRs)-associated HCC has not been fully understood. Methods: Two groups of the GEO dataset (including normal/NAFLD and HCC with MFRs) were used to analyze differential expression. Differentially expressed genes of HCC were verified by overlapping in TCGA. In addition, functional enrichment analysis, modular analysis, Receiver Operating Characteristic (ROC) analysis, LASSO analysis, and Genes with key survival characteristics were analyzed. Results: We identified six hub genes (FABP5, SCD, CCL20, AGPAT9(GPAT3), PLIN1, and IL1RN) that may be closely related to NAFLD and HCC with MFRs. We constructed survival and prognosis gene markers based on FABP5, CCL20, AGPAT9(GPAT3), PLIN1, and IL1RN.This gene signature has shown good diagnostic accuracy in both NAFLD and HCC and in predicting HCC overall survival rates. Conclusion: As a result of the findings of this study, there is some guiding significance for the diagnosis and treatment of liver disease associated with NAFLD progression. Frontiers Media S.A. 2023-03-06 /pmc/articles/PMC10025510/ /pubmed/36950134 http://dx.doi.org/10.3389/fgene.2023.1066410 Text en Copyright © 2023 Yang, Ni, Lian, Qiu, He, Zhang, Zou, He and Chen. 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
Yang, Fan
Ni, Beibei
Lian, Qinghai
Qiu, Xiusheng
He, Yizhan
Zhang, Qi
Zou, Xiaoguang
He, Fangping
Chen, Wenjie
Key genes associated with non-alcoholic fatty liver disease and hepatocellular carcinoma with metabolic risk factors
title Key genes associated with non-alcoholic fatty liver disease and hepatocellular carcinoma with metabolic risk factors
title_full Key genes associated with non-alcoholic fatty liver disease and hepatocellular carcinoma with metabolic risk factors
title_fullStr Key genes associated with non-alcoholic fatty liver disease and hepatocellular carcinoma with metabolic risk factors
title_full_unstemmed Key genes associated with non-alcoholic fatty liver disease and hepatocellular carcinoma with metabolic risk factors
title_short Key genes associated with non-alcoholic fatty liver disease and hepatocellular carcinoma with metabolic risk factors
title_sort key genes associated with non-alcoholic fatty liver disease and hepatocellular carcinoma with metabolic risk factors
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10025510/
https://www.ncbi.nlm.nih.gov/pubmed/36950134
http://dx.doi.org/10.3389/fgene.2023.1066410
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