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Clinical analysis of DNA methylation in the diagnosis of cervical lesions

  • Qin Tian,
  • Huaxin Shi,
  • Lihua Yang,
  • Ting Guo,
  • Hui Yang,
  • Luying Zhu,
  • Xuan long,
  • Weina Wu,
  • Jie Ren

摘要

Background

Currently, cervical cancer screening is primarily conducted through liquid-based thin-layer cytology (TCT) and HPV testing. However, TCT has low sensitivity, leading to a high false-negative rate. Although HPV testing improves the sensitivity of detecting CIN2+ or higher lesions, the specificity of this method remains low. Due to its objective results in detecting CIN3 and cervical cancer and high sensitivity and specificity, DNA methylation analysis is considered a promising alternative to cytological classification.

Objective

To explore the differences in multigene methylation status among cervical lesions at different levels and their clinical value and to analyze the diagnostic efficacy of DNA methylation for cervical cancer (CC) and high-grade cervical intraepithelial neoplasia (CIN3). We investigated whether DNA methylation status can be used as a prognostic indicator in cervical cancer patients.

Results

The positive rates of HPV, TCT, and GynTect tests in the cervical lesion group were all higher than those in the healthy control group, with statistically significant differences (P < 0.001). Additionally, as the severity of cervical lesions increased, the detection rate of GynTect also increased. There was no significant difference in the detection rate of HPV in CIN3 and cervical cancer lesion groups (P > 0.05). The expression differences of TCT and GynTect in CIN3 and cervical cancer were statistically significant, with positive expression rates of 18.8% and 42.9%, respectively (P = 0.04, P = 0.001). Receiver-operating characteristic curve analysis showed that compared to HPV and TCT tests, GynTect had the best diagnostic performance for CIN3 and cervical cancer lesions, with the largest area under the curve of 0.89, sensitivity of 85.7%, and specificity of 91.4%.

Conclusion

Multiple gene (ASTN1, DLX1, ITGA4, RXFP3, SOX17, and ZNF671) methylation detection has high diagnostic efficiency for CIN3 and CC and has potential clinical application value.