HR-HPV载量联合细胞免疫指标预测宫颈癌变进程

目的 比较高危型人乳头状瘤病毒载量（HR-HPV DNA）、CD4⁺CD25⁺Foxp3⁺调节性T细胞（Treg）、T细胞亚群在不同宫颈局部微环境的表达差异,探讨它们预测宫颈癌变进程的可能性和意义。 方法 将339例HR-HPV持续感染者分为宫颈上皮内瘤变（CIN）和宫颈癌两大组,采用PCR荧光法检测宫颈分泌物HPV-DNA,应用流式细胞仪CD4⁺CD25⁺Foxp3⁺设门和CD45/SSC设门方法分别对宫颈刷检物中的CD4⁺CD25⁺Treg细胞和CD3⁺、CD4⁺、CD8⁺T细胞相对计数,对数据资料进行单因素方差和多因素Logistic回归统计学分析,筛选宫颈癌预测指标,评估其价值。 结果 单因素方差分析显示,HR-HPV DNA（X₁）、CD4⁺CD25⁺Foxp3⁺Treg（X₂）、CD3⁺（X₃）、CD4⁺（X₄）、CD8⁺（X₅）在CIN和宫颈癌组均存在差异（均P<0.05）,可作为预测宫颈癌变的危险因素,而多因素Logistic回归分析显示,HR-HPV DNA、CD3⁺被回归方程剔除,提示CD4⁺CD25⁺Foxp3⁺Treg、CD4⁺、CD8⁺与宫颈癌发生有关,由此建立回归方程Logit（P）=-16.201 +0.800 X₂+0.687X₄-0.665X₅,依回归系数,预测宫颈癌变的密切程度依次为CD4⁺CD25⁺Foxp3⁺Treg>CD4⁺>CD8⁺。回归模型拟合优度检验Nagelkerke R²= 0.858,对CIN的预判率为94.4%,宫颈癌的预判率为96.0%,总的正判率为95.0%,提示拟合效果好,预测准确度高。 结论 基于预测宫颈癌变的回归模型,HR-HPV DNA不是预测宫颈癌变的良好指标,可能与HPV的感染状态有更密切的关联,从CIN到宫颈癌,持续感染HR-HPV的宫颈局部微环境免疫细胞表达量不同,在宫颈癌变进程中发挥的作用也不相同,局部免疫失衡造成的宫颈免疫抑制微环境是宫颈癌变的关键环节。

Predicting progression of cervical cancer by high risk human papillomavirus load and cellular immunologic indexes

Objective To compare the difference among high risk human papillomavirus load (HR-HPV DNA), CD4⁺CD25⁺Foxp3⁺ regulatory T cells (Treg), and T cell subsets in the local microenvironments of cervix, then to discuss the possibility and significance of their predictions of cervical carcinogenesis. Methods A total of 339 cases with HR-HPV persistent infection were divided into two groups: a cervical intraepithelial neoplasia (CIN) group and a cervical cancer group. HPV-DNA from cervical secretion was detected by PCR fluorescence. The relative cell numbers of Treg and CD3⁺, CD4⁺, CD8⁺ from cervical brush samples were determine by flow cytometry with the CD4⁺CD25⁺Foxp3⁺ and CD45/SSC gating methods respectively. The single factor variance and multivariate logistic regression were used to analyze the data, then the predictors of cervical cancer were screened and their values were evaluated. Results The single factor variance analysis showed that HR-HPV DNA (X₁), CD4⁺CD25⁺Foxp3⁺Treg(X₂), CD3⁺(X₃), CD4⁺(X₄), and CD8⁺(X₅) were significantly different between the CIN group and cervical cancer group (P<0.05), and they could be used as predictors of cervical cancer. However, the logistic regression analysis showed that HR-HPV DNA and CD3⁺ were eliminated by the regression equation, suggesting that CD4⁺CD25⁺Foxp3⁺, CD4⁺ and CD8⁺ were associated with cervical cancer. The regression equation was established: Logit(P)=-16.201+0.800X₂+0.687X₄-0.665X₅. The degree of cervical cancer prediction was CD4⁺CD25⁺Foxp3⁺Treg>CD4⁺>CD8⁺. The goodness of fit test was Nagelkerke R²= 0.858, the prediction rate for CIN was 94.4%, the prediction rate of cervical cancer was 96.0%, and the total positive rate was 95.0%, indicating that the fitting effect was good and the prediction accuracy was high. Conclusions HR-HPV DNA is not a good predictor of cervical cancer based on the regression model for predicting cervical cancer, and it may be more closely related to the infection of HPV. From CIN to cervical cancer, the expression of immune cells in local microenvironment of cervix with persistent infection of HR-HPV is different, and their roles in the process of cervical cancer are not the same. The immunosuppressive microenvironment caused by local immune imbalance is the key link of cervical cancer.