Countless efforts have been made to eradicate cervical cancer worldwide, including improving disease screening and human papillomavirus (HPV) vaccination programs. Nevertheless, cervical cancer still claims the lives of more than 300 000 women every year. Persistent infections with high-risk HPV genotypes 16 and 18 are the main cause of cancer and may result in HPV integration into the host genome. The central dogma is that HPV integration is an important step in oncogenesis, but in fact, it impedes the virus from replicating and spreading. HPV causing cervical cancer can therefore be perceived as a failed evolutionary viral trait. Here we outline the occurrence and mechanisms of HPV integration and how this process results in oncogenic transformation.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.molmed.2024.05.009DOI Listing

Publication Analysis

Top Keywords

hpv integration
16
cervical cancer
16
failed evolutionary
8
evolutionary viral
8
viral trait
8
hpv
7
cancer
5
cervical
4
integration cervical
4
cancer failed
4

Similar Publications

MTIOT: Identifying HPV subtypes from multiple infection data.

Comput Struct Biotechnol J

December 2024

Key Laboratory of Systems Biology, Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai 200031, China.

Persistent infection with high-risk human papillomavirus (hrHPV) is a major cause of cervical cancer. The effectiveness of current HPV-DNA testing, which is crucial for early detection, is limited in several aspects, including low sensitivity, accuracy issues, and the inability to perform comprehensive hrHPV typing. To address these limitations, we introduce MTIOT (Multiple subTypes In One Time), a novel detection method that utilizes machine learning with a new multichannel integration scheme to enhance HPV-DNA analysis.

View Article and Find Full Text PDF

Background: T cells are involved in every stage of tumor development and significantly influence the tumor microenvironment (TME). Our objective was to assess T-cell marker gene expression profiles, develop a predictive risk model for human papilloma virus (HPV)-negative oral squamous cell carcinoma (OSCC) utilizing these genes, and examine the correlation between the risk score and the immunotherapy response.

Methods: We acquired scRNA-seq data for HPV-negative OSCC from the GEO datasets.

View Article and Find Full Text PDF

Purpose: Blood-borne, cell-free DNA has been proposed as a means of individualizing the management of human papillomavirus (HPV)-positive oropharyngeal carcinoma.

Methods And Materials: This study was designed based on the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) statement. A comprehensive literature search of peer-reviewed publications from January 2013 to January 2024 was undertaken to identify prospective studies pertaining to the use of circulating HPV-DNA for oropharyngeal carcinoma.

View Article and Find Full Text PDF

Post hoc analyses of 9-valent human papillomavirus (9vHPV) vaccine immunogenicity were conducted in five Phase 3 studies that enrolled males. Month 7 antibody geometric mean titers (GMTs) after three 9vHPV vaccine doses were analyzed in 10,024 males/females aged 16-26 years from studies 001 (NCT00543543), 002 (NCT00943722), 003 (NCT01651949), and 020 (NCT02114385). Covariates considered were age, gender, sexual orientation, region of residence, and race.

View Article and Find Full Text PDF

Background: Cervical cancer is the fourth most common cancer in women globally, and the main cause of the disease has been found to be ongoing HPV infection. Cervical cancer remains the primary cause of cancer-related death despite major improvements in screening and treatment approaches, especially in low- and middle-income nations. Therefore, it is crucial to investigate the tumor microenvironment in advanced cervical cancer in order to identify possible treatment targets.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!