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A New HPV score System Predicts the Survival of Patients With Cervical Cancers
Persistent high-risk human papillomavirus (hrHPV) infection is confirmed as the major cause of cervical cancer. According to the HPV infection status, cervical cancer could be generalized as following three subgroups: HPV-negative, pure HPV-infection, and HPV-integration. Currently, the impact of HP...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8672055/ https://www.ncbi.nlm.nih.gov/pubmed/34925445 http://dx.doi.org/10.3389/fgene.2021.747090 |
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author | Hu, Qunchao Wang, Yani Zhang, Yuchen Ge, Yanjun Yin, Yihua Zhu, Haiyan |
author_facet | Hu, Qunchao Wang, Yani Zhang, Yuchen Ge, Yanjun Yin, Yihua Zhu, Haiyan |
author_sort | Hu, Qunchao |
collection | PubMed |
description | Persistent high-risk human papillomavirus (hrHPV) infection is confirmed as the major cause of cervical cancer. According to the HPV infection status, cervical cancer could be generalized as following three subgroups: HPV-negative, pure HPV-infection, and HPV-integration. Currently, the impact of HPV status on cervical cancer prognosis remains under dispute. Therefore, we explored the potential correlation between HPV status and the clinical outcome of cervical cancer, by establishing a robust prognostic predicting model based on a cervical cancer cohort using The Cancer Genome Atlas (TCGA) database. We performed an iCluster algorithm incorporating DNA copy number variation, SNP, DNA methylation, mRNA expression, and miRNA expression profile together and classified the cohort into three clusters. According to defined clusters, we established an HPV score system by weighing resultant gene alterations through random forest and COX models. This prediction tool could help to identify cervical cancer prognosis through evaluating individual HPV infection status and subsequent genetic modification, which might provide insights into HPV-related gene driven cervical cancer treatment strategies, yet its predictive power and robustness need to be further verified with independent cohorts. |
format | Online Article Text |
id | pubmed-8672055 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-86720552021-12-16 A New HPV score System Predicts the Survival of Patients With Cervical Cancers Hu, Qunchao Wang, Yani Zhang, Yuchen Ge, Yanjun Yin, Yihua Zhu, Haiyan Front Genet Genetics Persistent high-risk human papillomavirus (hrHPV) infection is confirmed as the major cause of cervical cancer. According to the HPV infection status, cervical cancer could be generalized as following three subgroups: HPV-negative, pure HPV-infection, and HPV-integration. Currently, the impact of HPV status on cervical cancer prognosis remains under dispute. Therefore, we explored the potential correlation between HPV status and the clinical outcome of cervical cancer, by establishing a robust prognostic predicting model based on a cervical cancer cohort using The Cancer Genome Atlas (TCGA) database. We performed an iCluster algorithm incorporating DNA copy number variation, SNP, DNA methylation, mRNA expression, and miRNA expression profile together and classified the cohort into three clusters. According to defined clusters, we established an HPV score system by weighing resultant gene alterations through random forest and COX models. This prediction tool could help to identify cervical cancer prognosis through evaluating individual HPV infection status and subsequent genetic modification, which might provide insights into HPV-related gene driven cervical cancer treatment strategies, yet its predictive power and robustness need to be further verified with independent cohorts. Frontiers Media S.A. 2021-12-01 /pmc/articles/PMC8672055/ /pubmed/34925445 http://dx.doi.org/10.3389/fgene.2021.747090 Text en Copyright © 2021 Hu, Wang, Zhang, Ge, Yin and Zhu. 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 Hu, Qunchao Wang, Yani Zhang, Yuchen Ge, Yanjun Yin, Yihua Zhu, Haiyan A New HPV score System Predicts the Survival of Patients With Cervical Cancers |
title | A New HPV score System Predicts the Survival of Patients With Cervical Cancers |
title_full | A New HPV score System Predicts the Survival of Patients With Cervical Cancers |
title_fullStr | A New HPV score System Predicts the Survival of Patients With Cervical Cancers |
title_full_unstemmed | A New HPV score System Predicts the Survival of Patients With Cervical Cancers |
title_short | A New HPV score System Predicts the Survival of Patients With Cervical Cancers |
title_sort | new hpv score system predicts the survival of patients with cervical cancers |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8672055/ https://www.ncbi.nlm.nih.gov/pubmed/34925445 http://dx.doi.org/10.3389/fgene.2021.747090 |
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