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N7-Methylguanosine Genes Related Prognostic Biomarker in Hepatocellular Carcinoma

Background: About 90% of liver cancer-related deaths are caused by hepatocellular carcinoma (HCC). N7-methylguanosine (m7G) modification is associated with the biological process and regulation of various diseases. To the best of our knowledge, its role in the pathogenesis and prognosis of HCC has n...

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Autores principales: Regmi, Parbatraj, He, Zhi-Qiang, Lia, Thongher, Paudyal, Aliza, Li, Fu-Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9207530/
https://www.ncbi.nlm.nih.gov/pubmed/35734429
http://dx.doi.org/10.3389/fgene.2022.918983
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author Regmi, Parbatraj
He, Zhi-Qiang
Lia, Thongher
Paudyal, Aliza
Li, Fu-Yu
author_facet Regmi, Parbatraj
He, Zhi-Qiang
Lia, Thongher
Paudyal, Aliza
Li, Fu-Yu
author_sort Regmi, Parbatraj
collection PubMed
description Background: About 90% of liver cancer-related deaths are caused by hepatocellular carcinoma (HCC). N7-methylguanosine (m7G) modification is associated with the biological process and regulation of various diseases. To the best of our knowledge, its role in the pathogenesis and prognosis of HCC has not been thoroughly investigated. Aim: To identify N7-methylguanosine (m7G) related prognostic biomarkers in HCC. Furthermore, we also studied the association of m7G–related prognostic gene signature with immune infiltration in HCC. Methods: The TCGA datasets were used as a training and GEO dataset “GSE76427” for validation of the results. Statistical analyses were performed using the R statistical software version 4.1.2. Results: Functional enrichment analysis identified some pathogenesis related to HCC. We identified 3 m7G-related genes (CDK1, ANO1, and PDGFRA) as prognostic biomarkers for HCC. A risk score was calculated from these 3 prognostic m7G-related genes which showed the high-risk group had a significantly poorer prognosis than the low-risk group in both training and validation datasets. The 3- and 5-years overall survival was predicted better with the risk score than the ideal model in the entire cohort in the predictive nomogram. Furthermore, immune checkpoint genes like CTLA4, HAVCR2, LAG3, and TIGT were expressed significantly higher in the high-risk group and the chemotherapy sensitivity analysis showed that the high-risk groups were responsive to sorafenib treatment. Conclusion: These 3 m7G genes related signature model can be used as prognostic biomarkers in HCC and a guide for immunotherapy and chemotherapy response. Future clinical study on this biomarker model is required to verify its clinical implications.
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spelling pubmed-92075302022-06-21 N7-Methylguanosine Genes Related Prognostic Biomarker in Hepatocellular Carcinoma Regmi, Parbatraj He, Zhi-Qiang Lia, Thongher Paudyal, Aliza Li, Fu-Yu Front Genet Genetics Background: About 90% of liver cancer-related deaths are caused by hepatocellular carcinoma (HCC). N7-methylguanosine (m7G) modification is associated with the biological process and regulation of various diseases. To the best of our knowledge, its role in the pathogenesis and prognosis of HCC has not been thoroughly investigated. Aim: To identify N7-methylguanosine (m7G) related prognostic biomarkers in HCC. Furthermore, we also studied the association of m7G–related prognostic gene signature with immune infiltration in HCC. Methods: The TCGA datasets were used as a training and GEO dataset “GSE76427” for validation of the results. Statistical analyses were performed using the R statistical software version 4.1.2. Results: Functional enrichment analysis identified some pathogenesis related to HCC. We identified 3 m7G-related genes (CDK1, ANO1, and PDGFRA) as prognostic biomarkers for HCC. A risk score was calculated from these 3 prognostic m7G-related genes which showed the high-risk group had a significantly poorer prognosis than the low-risk group in both training and validation datasets. The 3- and 5-years overall survival was predicted better with the risk score than the ideal model in the entire cohort in the predictive nomogram. Furthermore, immune checkpoint genes like CTLA4, HAVCR2, LAG3, and TIGT were expressed significantly higher in the high-risk group and the chemotherapy sensitivity analysis showed that the high-risk groups were responsive to sorafenib treatment. Conclusion: These 3 m7G genes related signature model can be used as prognostic biomarkers in HCC and a guide for immunotherapy and chemotherapy response. Future clinical study on this biomarker model is required to verify its clinical implications. Frontiers Media S.A. 2022-06-06 /pmc/articles/PMC9207530/ /pubmed/35734429 http://dx.doi.org/10.3389/fgene.2022.918983 Text en Copyright © 2022 Regmi, He, Lia, Paudyal and Li. 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
Regmi, Parbatraj
He, Zhi-Qiang
Lia, Thongher
Paudyal, Aliza
Li, Fu-Yu
N7-Methylguanosine Genes Related Prognostic Biomarker in Hepatocellular Carcinoma
title N7-Methylguanosine Genes Related Prognostic Biomarker in Hepatocellular Carcinoma
title_full N7-Methylguanosine Genes Related Prognostic Biomarker in Hepatocellular Carcinoma
title_fullStr N7-Methylguanosine Genes Related Prognostic Biomarker in Hepatocellular Carcinoma
title_full_unstemmed N7-Methylguanosine Genes Related Prognostic Biomarker in Hepatocellular Carcinoma
title_short N7-Methylguanosine Genes Related Prognostic Biomarker in Hepatocellular Carcinoma
title_sort n7-methylguanosine genes related prognostic biomarker in hepatocellular carcinoma
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9207530/
https://www.ncbi.nlm.nih.gov/pubmed/35734429
http://dx.doi.org/10.3389/fgene.2022.918983
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