125
Views
5
CrossRef citations to date
0
Altmetric
Gynaecology

A 5-gene DNA methylation signature is a promising prognostic biomarker for early-stage cervical cancer

, , , &
Pages 327-332 | Published online: 04 Jun 2021
 

Abstract

The demographic information and overall survival (OS) of patients with cervical cancer (CC) (pathological stage: IA–IIA) were extracted from the TCGA database. A univariate and multivariate Cox proportional hazard model was performed to identify methylation markers significantly associated with the OS of patients in the training dataset. Then such a prognostic classifier was tested on the validation set and all subgroups. The Kaplan–Meier analysis and ROC analysis were performed to detect the ability to discriminate between patients with different risks and different OS. A DNA methylation signature which contained five genes was found to be significantly associated with the OS of CC patients by the Cox regression analysis in the training dataset. Such a signature could efficiently distinguish the patients into two risk groups with significantly different OS in both datasets. The receiver operating characteristic (ROC) analysis showed it had high sensitivity and specificity. Moreover, such a prognostic model also could be effectively applied to different subgroups, including groups of different ages, tumour sizes, histologic types, etc. A 5-DNA methylation signature identified by this study may act as a novel prognostic indicator for early-stage CC, and it may be helpful for the timely diagnosis and intervention of CC at pathological stages IA–IIA.

    Impact Statement

  • What is already known on this subject? Cervical cancer (CC) is one of the most common gynaecological malignant tumours.

  • What the results of this study add? This study constructed a risk model based on a 5-DNA methylation signature for early-stage CC patients’ survival prediction.

  • What the implications are of these findings for clinical practice and/or further research? Methylated markers have the potential to discriminate patients of different risks and different OS. Our results may shed new light on the early diagnosis and intervention, and potential therapeutic targets for CC patients at pathological stages IA–IIA.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work is supported by Health Commission of Hubei Province Scientific Research Project [WJ2019H188] and Special Research Project of Key Discipline of Pharmacy of Hubei University of Science and Technology [2019-20YZ02].

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 65.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.