Methylation sites of human papillomavirus 16 as potential biomarkers for cervical cancer progression

Methylation of specific CpG sites in the HPV16 L1 gene holds promise as a biomarker for cervical cancer progression. The gene locus at position 6367 has important features in the methylation pattern of cervical cancer, and high accuracy shown in diagnosis make it a potential biomarker for early diagnosis of cervical cancer.

Authors

Institutions

Publication Details

Journal
Frontiers in Oncology
Published
2025-01-27
DOI
https://doi.org/10.3389/fonc.2025.1481621
Primary Topic
Cervical Cancer and HPV Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Methylation sites of human papillomavirus 16 as potential biomarkers for cervical cancer progression

Sha Ji, Nannan Ji
Frontiers in Oncology
Cervical Cancer and HPV Research
article

Methylation sites of human papillomavirus 16 as potential biomarkers for cervical cancer progression

Sha Ji, Nannan Ji
article en

Abstract

Methylation of specific CpG sites in the HPV16 L1 gene holds promise as a biomarker for cervical cancer progression. The gene locus at position 6367 has important features in the methylation pattern of cervical cancer, and high accuracy shown in diagnosis make it a potential biomarker for early diagnosis of cervical cancer.

Frontiers in OncologyVol. 15
Shihezi University (CN), People's Hospital of Xinjiang Uygur Autonomous Region (CN)
Good health and well-being
Openalex Percentile: Top 98%
Cervical Cancer and HPV Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.