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Identification of prognostic biomarkers for patients withhepatocellular carcinoma after hepatectomy

Hepatocellular carcinoma (HCC) is a lethal malignancy with high morbidity and mortality rates worldwide. The identification of prognosis-associated biomarkers is crucial to improve HCC patient survival. The present study aimed to explore potential predictive biomarkers for HCC. Differentially expres...

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Autores principales: Wang, Xiangkun, Liao, Xiwen, Yang, Chengkun, Huang, Ketuan, Yu, Tingdong, Yu, Long, Han, Chuangye, Zhu, Guangzhi, Zeng, Xianmin, Liu, Zhengqian, Zhou, Xin, Qin, Wei, Su, Hao, Ye, Xinping, Peng, Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6365689/
https://www.ncbi.nlm.nih.gov/pubmed/30628708
http://dx.doi.org/10.3892/or.2019.6953
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author Wang, Xiangkun
Liao, Xiwen
Yang, Chengkun
Huang, Ketuan
Yu, Tingdong
Yu, Long
Han, Chuangye
Zhu, Guangzhi
Zeng, Xianmin
Liu, Zhengqian
Zhou, Xin
Qin, Wei
Su, Hao
Ye, Xinping
Peng, Tao
author_facet Wang, Xiangkun
Liao, Xiwen
Yang, Chengkun
Huang, Ketuan
Yu, Tingdong
Yu, Long
Han, Chuangye
Zhu, Guangzhi
Zeng, Xianmin
Liu, Zhengqian
Zhou, Xin
Qin, Wei
Su, Hao
Ye, Xinping
Peng, Tao
author_sort Wang, Xiangkun
collection PubMed
description Hepatocellular carcinoma (HCC) is a lethal malignancy with high morbidity and mortality rates worldwide. The identification of prognosis-associated biomarkers is crucial to improve HCC patient survival. The present study aimed to explore potential predictive biomarkers for HCC. Differentially expressed genes (DEGs) were analyzed in the GSE36376 dataset using GEO2R. Hub genes were identified and further investigated for prognostic value in HCC patients. A risk score model and nomogram were constructed to predict HCC prognosis using the prognosis-associated genes and clinical factors. Pearson's correlation was employed to show interactions among hub genes. Gene enrichment analysis was performed to identify detailed biological processes and pathways. A total of 71 DEGs were obtained and seven (ADH4, CYP2C8, CYP2C9, CYP8B1, SLC22A1, TAT and HSD17B13, all adjusted P≤0.05) of the 10 hub genes were identified as prognosis-related genes for survival analysis in HCC patients, including alcohol dehydrogenase 4 (class II), pi polypeptide (ADH4), cytochrome p450 family 2 subfamily C member 8 (CYP2C8), cytochrome P450 family 2 subfamily C member 9 (CYP2C9), cytochrome P450 family 8 subfamily B member 1 (CYP8B1), solute carrier family 22 member 1 (SLC22A1), tyrosine aminotransferase (TAT) and hydroxysteroid 17-β dehydrogenase 13 (HSD17B13). The risk score model could predict HCC prognosis and the nomogram visualized gene expression and clinical factors of probability for HCC prognosis. The majority of genes showed significant Pearson's correlations with others (41 Pearson correlations P≤0.01, four Pearson correlations P>0.05). GO analysis revealed that terms such as ‘chemical carcinogenesis’ and ‘drug metabolism-cytochrome P450’ were enriched and may prove helpful to elucidate the mechanisms of hepatocarcinogenesis. Hub genes ADH4, CYP2C8, CYP2C9, CYP8B1, SLC22A1, TAT and HSD17B13 may be useful as predictive biomarkers for HCC prognosis.
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spelling pubmed-63656892019-02-19 Identification of prognostic biomarkers for patients withhepatocellular carcinoma after hepatectomy Wang, Xiangkun Liao, Xiwen Yang, Chengkun Huang, Ketuan Yu, Tingdong Yu, Long Han, Chuangye Zhu, Guangzhi Zeng, Xianmin Liu, Zhengqian Zhou, Xin Qin, Wei Su, Hao Ye, Xinping Peng, Tao Oncol Rep Articles Hepatocellular carcinoma (HCC) is a lethal malignancy with high morbidity and mortality rates worldwide. The identification of prognosis-associated biomarkers is crucial to improve HCC patient survival. The present study aimed to explore potential predictive biomarkers for HCC. Differentially expressed genes (DEGs) were analyzed in the GSE36376 dataset using GEO2R. Hub genes were identified and further investigated for prognostic value in HCC patients. A risk score model and nomogram were constructed to predict HCC prognosis using the prognosis-associated genes and clinical factors. Pearson's correlation was employed to show interactions among hub genes. Gene enrichment analysis was performed to identify detailed biological processes and pathways. A total of 71 DEGs were obtained and seven (ADH4, CYP2C8, CYP2C9, CYP8B1, SLC22A1, TAT and HSD17B13, all adjusted P≤0.05) of the 10 hub genes were identified as prognosis-related genes for survival analysis in HCC patients, including alcohol dehydrogenase 4 (class II), pi polypeptide (ADH4), cytochrome p450 family 2 subfamily C member 8 (CYP2C8), cytochrome P450 family 2 subfamily C member 9 (CYP2C9), cytochrome P450 family 8 subfamily B member 1 (CYP8B1), solute carrier family 22 member 1 (SLC22A1), tyrosine aminotransferase (TAT) and hydroxysteroid 17-β dehydrogenase 13 (HSD17B13). The risk score model could predict HCC prognosis and the nomogram visualized gene expression and clinical factors of probability for HCC prognosis. The majority of genes showed significant Pearson's correlations with others (41 Pearson correlations P≤0.01, four Pearson correlations P>0.05). GO analysis revealed that terms such as ‘chemical carcinogenesis’ and ‘drug metabolism-cytochrome P450’ were enriched and may prove helpful to elucidate the mechanisms of hepatocarcinogenesis. Hub genes ADH4, CYP2C8, CYP2C9, CYP8B1, SLC22A1, TAT and HSD17B13 may be useful as predictive biomarkers for HCC prognosis. D.A. Spandidos 2019-03 2019-01-03 /pmc/articles/PMC6365689/ /pubmed/30628708 http://dx.doi.org/10.3892/or.2019.6953 Text en Copyright: © Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Wang, Xiangkun
Liao, Xiwen
Yang, Chengkun
Huang, Ketuan
Yu, Tingdong
Yu, Long
Han, Chuangye
Zhu, Guangzhi
Zeng, Xianmin
Liu, Zhengqian
Zhou, Xin
Qin, Wei
Su, Hao
Ye, Xinping
Peng, Tao
Identification of prognostic biomarkers for patients withhepatocellular carcinoma after hepatectomy
title Identification of prognostic biomarkers for patients withhepatocellular carcinoma after hepatectomy
title_full Identification of prognostic biomarkers for patients withhepatocellular carcinoma after hepatectomy
title_fullStr Identification of prognostic biomarkers for patients withhepatocellular carcinoma after hepatectomy
title_full_unstemmed Identification of prognostic biomarkers for patients withhepatocellular carcinoma after hepatectomy
title_short Identification of prognostic biomarkers for patients withhepatocellular carcinoma after hepatectomy
title_sort identification of prognostic biomarkers for patients withhepatocellular carcinoma after hepatectomy
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6365689/
https://www.ncbi.nlm.nih.gov/pubmed/30628708
http://dx.doi.org/10.3892/or.2019.6953
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