Literature DB >> 33361419

Identification and Complete Validation of Prognostic Gene Signatures for Human Papillomavirus-Associated Cancers: Integrated Approach Covering Different Anatomical Locations.

Eun Jung Kwon1, Mihyang Ha1, Jeon Yeob Jang2,3, Yun Hak Kim4,5.   

Abstract

Human papillomavirus (HPV) infects squamous epithelium and is a major cause of cervical cancer (CC) and a subset of head and neck cancers (HNC). Virus-induced tumorigenesis, molecular alterations, and related prognostic markers are expected to be similar between the two cancers, but they remain poorly understood. We present integrated molecular analysis of HPV-associated tumors from TCGA and GEO databases and identify prognostic biomarkers. Analysis of gene expression profiles identified common upregulated genes and pathways of DNA replication and repair in the HPV-associated tumors. We established 34 prognostic gene signatures with a universal cutoff value in TCGA-CC using Elastic Net Cox regression analysis. We were able to externally validate our results in the TCGA-HNC and several GEO data sets, and demonstrated prognostic power in HPV-associated HNC, but not in HPV-negative cancers. The HPV-related prognostic and predictive indicator did not discriminate other cancers, except bladder urothelial carcinoma. These results identify and completely validate a highly selective prognostic system and its cross-usefulness in HPV-associated cancers, regardless of the tumor's anatomical subsite.IMPORTANCE Persistent infection with high-risk HPV interferes with cell function regulation and causes cell mutations, which accumulate over the long term and eventually develop into cancer. Results of pathway enrichment analysis presumably showed this accumulation of intracellular damage during the chronic HPV-infected state. We used highly advanced statistical methods to identify the most appropriate genes and coefficients and developed the HPV-related prognostic and predictive indicator (HPPI) risk scoring system. We applied the same cutoff value to training and validation sets and demonstrated good prognostic performance in both data sets, and confirmed a consistent trend in external validation. Moreover, HPPI presented significant validation results for bladder cancer suspected to be related to HPV. This suggested that our risk scoring system based on the prognostic gene signature could play an important role in the development of treatment strategies for patients with HPV-related cancer.
Copyright © 2021 American Society for Microbiology.

Entities:  

Keywords:  cervical cancer; gene signature; head and neck cancer; human papillomavirus; prognostic biomarker

Year:  2021        PMID: 33361419     DOI: 10.1128/JVI.02354-20

Source DB:  PubMed          Journal:  J Virol        ISSN: 0022-538X            Impact factor:   5.103


  2 in total

1.  Novel deep learning-based survival prediction for oral cancer by analyzing tumor-infiltrating lymphocyte profiles through CIBERSORT.

Authors:  Yeongjoo Kim; Ji Wan Kang; Junho Kang; Eun Jung Kwon; Mihyang Ha; Yoon Kyeong Kim; Hansong Lee; Je-Keun Rhee; Yun Hak Kim
Journal:  Oncoimmunology       Date:  2021-03-29       Impact factor: 8.110

2.  Immunogenomic Identification for Predicting the Prognosis of Cervical Cancer Patients.

Authors:  Qun Wang; Aurelia Vattai; Theresa Vilsmaier; Till Kaltofen; Alexander Steger; Doris Mayr; Sven Mahner; Udo Jeschke; Helene Hildegard Heidegger
Journal:  Int J Mol Sci       Date:  2021-02-28       Impact factor: 5.923

  2 in total

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