Hypermethylated PCDHGB7 as a Biomarker for Early Detection of Endometrial Cancer in Endometrial Brush Samples and Cervical Scrapings

高甲基化的 PCDHGB7 作为子宫内膜刷样本和宫颈刮片中子宫内膜癌早期检测的生物标志物

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作者:Jiangjing Yuan, Zhanrui Mao, Qi Lu, Peng Xu, Chengyang Wang, Xiaona Xu, Zhaowei Zhou, Tongsheng Zhang, Wenqiang Yu, Shihua Dong, Yudong Wang, Weiwei Cheng

Abstract

Endometrial cancer (EC) is one of the most common gynecologic cancers in developed countries. Presently, it is imperative to develop a reliable, noninvasive, or minimally invasive detection method for EC. We explored the possibility of using DNA methylation marker from endometrial brush samples (with a "Tao brush") and cervical scrapes (with a "Pap brush") for early detection of EC. We analyzed the methylation data of EC and normal endometrial tissues from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data sets. An optimized methylation-sensitive restriction enzyme combined with real-time fluorescent quantitative PCR (MSRE-qPCR) was used for methylation detection. Included in the training set were 143 endometrial tissues, 103 Tao, and 109 Pap brush samples. The validation set included 110 Tao and 112 Pap brush samples. PCDHGB7 was significantly hypermethylated in EC compared with normal endometrial tissues in the TCGA and GEO data sets (AUC >0.95), which was verified in clinical samples. In the Pap brush samples, the AUC was 0.86 with 80.65% sensitivity and 82.81% specificity, whereas the Tao brush samples exhibited higher specificity (95.31%). The combination of Tao and Pap brush samples significantly increased the sensitivity to 90.32%. In the validation set, the final model yielded a sensitivity of 98.61%, specificity of 60.53%, positive predictive value of 82.56%, and negative predictive value of 95.83%. These results demonstrate the potential application of the novel methylation marker, hypermethylated PCDHGB7, in cervical scrapings and endometrial brush, which provides a viable, noninvasive, or minimally invasive method for early endometrial cancer detection across different clinical features and histologies to supplement current hysteroscopy diagnosis.

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