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TNFRSF12A and a new prognostic model identified from methylation combined with expression profiles to predict overall survival in hepatocellular carcinoma

BACKGROUND: It has been proved that DNA methylation, as an epigenetic regulatory mode, plays a crucial role in the initiation, progression and invasion of hepatocellular carcinoma (HCC). However, there still are some pathways and factors that regulates the carcinogenesis of HCC remains unclear. METH...

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Autores principales: Fang, Yu, Xiang, Lin, Chen, La-Mei, Sun, Wei-Juan, Zhai, Yu-Jia, Fan, Yu-Chen, Wang, Kai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8797803/
https://www.ncbi.nlm.nih.gov/pubmed/35117914
http://dx.doi.org/10.21037/tcr-20-1342
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author Fang, Yu
Xiang, Lin
Chen, La-Mei
Sun, Wei-Juan
Zhai, Yu-Jia
Fan, Yu-Chen
Wang, Kai
author_facet Fang, Yu
Xiang, Lin
Chen, La-Mei
Sun, Wei-Juan
Zhai, Yu-Jia
Fan, Yu-Chen
Wang, Kai
author_sort Fang, Yu
collection PubMed
description BACKGROUND: It has been proved that DNA methylation, as an epigenetic regulatory mode, plays a crucial role in the initiation, progression and invasion of hepatocellular carcinoma (HCC). However, there still are some pathways and factors that regulates the carcinogenesis of HCC remains unclear. METHODS: The original datasets comparing DNA methylation, clinical information and transcriptome profiling between HCC and normal controls were downloaded from The Cancer Genome Atlas (TCGA) database. R software was used to screen for methylation-differential genes (MDGs) and methylation-driven genes. Gene-functional enrichment analysis, ConsensusPathDB pathway analysis, protein-protein interaction (PPI) network construction and survival analysis were performed; methylation-specific polymerase chain reaction (MSP) and real-time quantitative polymerase chain reaction (RT-qPCR) were used for validation. RESULTS: One hundred and sixty-seven MDGs and 285 methylation-driven genes were identified. Function and pathway enrichment analysis revealed that they are associated with sequence-specific DNA binding, nuclear nucleosome, regulation of insulin-like growth factor transport, etc. An eight-gene (HIST1H1D, RP11-476B1.1, OR2AK2, TNFRSF12A, CTD-2313N18.8, AC133644.2, RP11-467L13.4 and LINC00989) prognostic model was identified from the MDGs; its methylation degree can strongly predict the overall survival of HCC. Among them, TNFRSF12A being the only one belongs to both MDGs and methylation-driver genes, shows a significant independent correlation with the prognosis of HCC. That was validated in further details. CONCLUSIONS: Our research has identified a registry of novel genes and pathways that’s important for regulating the carcinogenesis of HCC. In addition, we identified a strong molecular model for prognostic prediction. These findings will not only provide guidance for clinical individualized treatment, but also to set us targets for further research on the molecular mechanism of HCC.
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spelling pubmed-87978032022-02-02 TNFRSF12A and a new prognostic model identified from methylation combined with expression profiles to predict overall survival in hepatocellular carcinoma Fang, Yu Xiang, Lin Chen, La-Mei Sun, Wei-Juan Zhai, Yu-Jia Fan, Yu-Chen Wang, Kai Transl Cancer Res Original Article BACKGROUND: It has been proved that DNA methylation, as an epigenetic regulatory mode, plays a crucial role in the initiation, progression and invasion of hepatocellular carcinoma (HCC). However, there still are some pathways and factors that regulates the carcinogenesis of HCC remains unclear. METHODS: The original datasets comparing DNA methylation, clinical information and transcriptome profiling between HCC and normal controls were downloaded from The Cancer Genome Atlas (TCGA) database. R software was used to screen for methylation-differential genes (MDGs) and methylation-driven genes. Gene-functional enrichment analysis, ConsensusPathDB pathway analysis, protein-protein interaction (PPI) network construction and survival analysis were performed; methylation-specific polymerase chain reaction (MSP) and real-time quantitative polymerase chain reaction (RT-qPCR) were used for validation. RESULTS: One hundred and sixty-seven MDGs and 285 methylation-driven genes were identified. Function and pathway enrichment analysis revealed that they are associated with sequence-specific DNA binding, nuclear nucleosome, regulation of insulin-like growth factor transport, etc. An eight-gene (HIST1H1D, RP11-476B1.1, OR2AK2, TNFRSF12A, CTD-2313N18.8, AC133644.2, RP11-467L13.4 and LINC00989) prognostic model was identified from the MDGs; its methylation degree can strongly predict the overall survival of HCC. Among them, TNFRSF12A being the only one belongs to both MDGs and methylation-driver genes, shows a significant independent correlation with the prognosis of HCC. That was validated in further details. CONCLUSIONS: Our research has identified a registry of novel genes and pathways that’s important for regulating the carcinogenesis of HCC. In addition, we identified a strong molecular model for prognostic prediction. These findings will not only provide guidance for clinical individualized treatment, but also to set us targets for further research on the molecular mechanism of HCC. AME Publishing Company 2020-09 /pmc/articles/PMC8797803/ /pubmed/35117914 http://dx.doi.org/10.21037/tcr-20-1342 Text en 2020 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
spellingShingle Original Article
Fang, Yu
Xiang, Lin
Chen, La-Mei
Sun, Wei-Juan
Zhai, Yu-Jia
Fan, Yu-Chen
Wang, Kai
TNFRSF12A and a new prognostic model identified from methylation combined with expression profiles to predict overall survival in hepatocellular carcinoma
title TNFRSF12A and a new prognostic model identified from methylation combined with expression profiles to predict overall survival in hepatocellular carcinoma
title_full TNFRSF12A and a new prognostic model identified from methylation combined with expression profiles to predict overall survival in hepatocellular carcinoma
title_fullStr TNFRSF12A and a new prognostic model identified from methylation combined with expression profiles to predict overall survival in hepatocellular carcinoma
title_full_unstemmed TNFRSF12A and a new prognostic model identified from methylation combined with expression profiles to predict overall survival in hepatocellular carcinoma
title_short TNFRSF12A and a new prognostic model identified from methylation combined with expression profiles to predict overall survival in hepatocellular carcinoma
title_sort tnfrsf12a and a new prognostic model identified from methylation combined with expression profiles to predict overall survival in hepatocellular carcinoma
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8797803/
https://www.ncbi.nlm.nih.gov/pubmed/35117914
http://dx.doi.org/10.21037/tcr-20-1342
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