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Identification of special key genes for alcohol-related hepatocellular carcinoma through bioinformatic analysis

BACKGROUND: Alcohol-related hepatocellular carcinoma (HCC) was reported to be diagnosed at a later stage, but the mechanism was unknown. This study aimed to identify special key genes (SKGs) during alcohol-related HCC development and progression. METHODS: The mRNA data of 369 HCC patients and the cl...

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Autores principales: Zhang, Xiuzhi, Kang, Chunyan, Li, Ningning, Liu, Xiaoli, Zhang, Jinzhong, Gao, Fenglan, Dai, Liping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6368834/
https://www.ncbi.nlm.nih.gov/pubmed/30755830
http://dx.doi.org/10.7717/peerj.6375
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author Zhang, Xiuzhi
Kang, Chunyan
Li, Ningning
Liu, Xiaoli
Zhang, Jinzhong
Gao, Fenglan
Dai, Liping
author_facet Zhang, Xiuzhi
Kang, Chunyan
Li, Ningning
Liu, Xiaoli
Zhang, Jinzhong
Gao, Fenglan
Dai, Liping
author_sort Zhang, Xiuzhi
collection PubMed
description BACKGROUND: Alcohol-related hepatocellular carcinoma (HCC) was reported to be diagnosed at a later stage, but the mechanism was unknown. This study aimed to identify special key genes (SKGs) during alcohol-related HCC development and progression. METHODS: The mRNA data of 369 HCC patients and the clinical information were downloaded from the Cancer Genome Atlas project (TCGA). The 310 patients with certain HCC-related risk factors were included for analysis and divided into seven groups according to the risk factors. Survival analyses were applied for the HCC patients of different groups. The patients with hepatitis B virus or hepatitis C virus infection only were combined into the HCC-V group for further analysis. The differentially expressed genes (DEGs) between the HCCs with alcohol consumption only (HCC-A) and HCC-V tumors were identified through limma package in R with cutoff criteria│log2 fold change (logFC)|>1.0 and p < 0.05. The DEGs between eight alcohol-related HCCs and their paired normal livers of GSE59259 from the Gene Expression Omnibus (GEO) were identified through GEO2R (a built-in tool in GEO database) with cutoff criteria |logFC|> 2.0 and adj.p < 0.05. The intersection of the two sets of DEGs was considered SKGs which were then investigated for their specificity through comparisons between HCC-A and other four HCC groups. The SKGs were analyzed for their correlations with HCC-A stage and grade and their prognostic power for HCC-A patients. The expressional differences of the SKGs in the HCCs in whole were also investigated through Gene Expression Profiling Interactive Analysis (GEPIA). The SKGs in HCC were validated through Oncomine database analysis. RESULTS: Pathological stage is an independent prognostic factor for HCC patients. HCC-A patients were diagnosed later than HCC patients with other risk factors. Ten SKGs were identified and nine of them were confirmed for their differences in paired samples of HCC-A patients. Three (SLC22A10, CD5L, and UROC1) and four (SLC22A10, UROC1, CSAG3, and CSMD1) confirmed genes were correlated with HCC-A stage and grade, respectively. SPP2 had a lower trend in HCC-A tumors and was negatively correlated with HCC-A stage and grade. The SKGs each was differentially expressed between HCC-A and at least one of other HCC groups. CD5L was identified to be favorable prognostic factor for overall survival while CSMD1 unfavorable prognostic factor for disease-free survival for HCC-A patients and HCC patients in whole. Through Oncomine database, the dysregulations of the SKGs in HCC and their clinical significance were confirmed. CONCLUSION: The poor prognosis of HCC-A patients might be due to their later diagnosis. The SKGs, especially the four stage-correlated genes (CD5L, SLC22A10, UROC1, and SPP2) might play important roles in HCC development, especially alcohol-related HCC development and progression. CD5L might be useful for overall survival and CSMD1 for disease-free survival predication in HCC, especially alcohol-related HCC.
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spelling pubmed-63688342019-02-12 Identification of special key genes for alcohol-related hepatocellular carcinoma through bioinformatic analysis Zhang, Xiuzhi Kang, Chunyan Li, Ningning Liu, Xiaoli Zhang, Jinzhong Gao, Fenglan Dai, Liping PeerJ Bioinformatics BACKGROUND: Alcohol-related hepatocellular carcinoma (HCC) was reported to be diagnosed at a later stage, but the mechanism was unknown. This study aimed to identify special key genes (SKGs) during alcohol-related HCC development and progression. METHODS: The mRNA data of 369 HCC patients and the clinical information were downloaded from the Cancer Genome Atlas project (TCGA). The 310 patients with certain HCC-related risk factors were included for analysis and divided into seven groups according to the risk factors. Survival analyses were applied for the HCC patients of different groups. The patients with hepatitis B virus or hepatitis C virus infection only were combined into the HCC-V group for further analysis. The differentially expressed genes (DEGs) between the HCCs with alcohol consumption only (HCC-A) and HCC-V tumors were identified through limma package in R with cutoff criteria│log2 fold change (logFC)|>1.0 and p < 0.05. The DEGs between eight alcohol-related HCCs and their paired normal livers of GSE59259 from the Gene Expression Omnibus (GEO) were identified through GEO2R (a built-in tool in GEO database) with cutoff criteria |logFC|> 2.0 and adj.p < 0.05. The intersection of the two sets of DEGs was considered SKGs which were then investigated for their specificity through comparisons between HCC-A and other four HCC groups. The SKGs were analyzed for their correlations with HCC-A stage and grade and their prognostic power for HCC-A patients. The expressional differences of the SKGs in the HCCs in whole were also investigated through Gene Expression Profiling Interactive Analysis (GEPIA). The SKGs in HCC were validated through Oncomine database analysis. RESULTS: Pathological stage is an independent prognostic factor for HCC patients. HCC-A patients were diagnosed later than HCC patients with other risk factors. Ten SKGs were identified and nine of them were confirmed for their differences in paired samples of HCC-A patients. Three (SLC22A10, CD5L, and UROC1) and four (SLC22A10, UROC1, CSAG3, and CSMD1) confirmed genes were correlated with HCC-A stage and grade, respectively. SPP2 had a lower trend in HCC-A tumors and was negatively correlated with HCC-A stage and grade. The SKGs each was differentially expressed between HCC-A and at least one of other HCC groups. CD5L was identified to be favorable prognostic factor for overall survival while CSMD1 unfavorable prognostic factor for disease-free survival for HCC-A patients and HCC patients in whole. Through Oncomine database, the dysregulations of the SKGs in HCC and their clinical significance were confirmed. CONCLUSION: The poor prognosis of HCC-A patients might be due to their later diagnosis. The SKGs, especially the four stage-correlated genes (CD5L, SLC22A10, UROC1, and SPP2) might play important roles in HCC development, especially alcohol-related HCC development and progression. CD5L might be useful for overall survival and CSMD1 for disease-free survival predication in HCC, especially alcohol-related HCC. PeerJ Inc. 2019-02-06 /pmc/articles/PMC6368834/ /pubmed/30755830 http://dx.doi.org/10.7717/peerj.6375 Text en © 2019 Zhang et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Zhang, Xiuzhi
Kang, Chunyan
Li, Ningning
Liu, Xiaoli
Zhang, Jinzhong
Gao, Fenglan
Dai, Liping
Identification of special key genes for alcohol-related hepatocellular carcinoma through bioinformatic analysis
title Identification of special key genes for alcohol-related hepatocellular carcinoma through bioinformatic analysis
title_full Identification of special key genes for alcohol-related hepatocellular carcinoma through bioinformatic analysis
title_fullStr Identification of special key genes for alcohol-related hepatocellular carcinoma through bioinformatic analysis
title_full_unstemmed Identification of special key genes for alcohol-related hepatocellular carcinoma through bioinformatic analysis
title_short Identification of special key genes for alcohol-related hepatocellular carcinoma through bioinformatic analysis
title_sort identification of special key genes for alcohol-related hepatocellular carcinoma through bioinformatic analysis
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6368834/
https://www.ncbi.nlm.nih.gov/pubmed/30755830
http://dx.doi.org/10.7717/peerj.6375
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