Li Ya, Zhang Rui, Zhang Jin, Gao Ying, Bian Yawen, Bai Wenpei
The Department of Gynecology and Obstetrics, Beijing Shijitan Hospital, Capital Medical University, Haidian, 100038, Beijing, China.
The Department of Pathology, Beijing Shijitan Hospital, Capital Medical University, Haidian, 100038, Beijing, China.
Cell Biochem Biophys. 2025 Mar;83(1):1151-1158. doi: 10.1007/s12013-024-01548-7. Epub 2024 Oct 9.
Cervical high-grade squamous intraepithelial lesions (HSIL) are one of the common types of cervical cancer precancerous changes, and HPV16/18 positivity is a risk factor for HSIL recurrence. By detecting the expression of relevant markers in the lesion tissue of recurrent patients, it is helpful for the diagnosis of HPV16/18 positivity and can provide a basis for disease recurrence risk assessment. Therefore, this study analyzed the relationship between p16, C-myc, PIK3CA proteins and HPV16/18 positivity in recurrent cervical HSIL patients. By examining the p16, C-myc, and PIK3CA proteins in the cervical lesion tissue of 180 HSIL recurrent patients who underwent examination in the hospital from January 2020 to December 2022, this study analyzed the relationship between p16, C-myc, and PIK3CA proteins and HPV16/18 positivity. PIK3CA expression detection found that the proportion of positive expression of p16, C-myc, and PIK3CA in HPV16/18 (+) patients was significantly higher than that in HPV16/18 (-), and the expression of HPV16/18 in HSIL patients was significantly positively correlated with p16, C-myc, and PIK3CA. Meanwhile, a prediction model F was constructed based on binary logistic regression analysis data with good fit, and through ROC curve analysis. It was found that p16, C-myc, PIK3CA, and logistic model F can effectively predict HPV16/18 (+), with model F having the best diagnostic performance.
宫颈高级别鳞状上皮内病变(HSIL)是宫颈癌癌前病变的常见类型之一,HPV16/18阳性是HSIL复发的危险因素。通过检测复发患者病变组织中相关标志物的表达,有助于诊断HPV16/18阳性,并可为疾病复发风险评估提供依据。因此,本研究分析了复发性宫颈HSIL患者中p16、C-myc、PIK3CA蛋白与HPV16/18阳性之间的关系。通过检测2020年1月至2022年12月在本院接受检查的180例HSIL复发患者宫颈病变组织中的p16、C-myc和PIK3CA蛋白,分析p16、C-myc和PIK3CA蛋白与HPV16/18阳性之间的关系。PIK3CA表达检测发现,HPV16/18(+)患者中p16、C-myc和PIK3CA阳性表达比例显著高于HPV16/18(-)患者,HSIL患者中HPV16/18表达与p16、C-myc和PIK3CA显著正相关。同时,基于二元逻辑回归分析数据构建了拟合良好的预测模型F,并通过ROC曲线分析。发现p16、C-myc、PIK3CA和逻辑模型F可有效预测HPV16/18(+),模型F诊断性能最佳。