Shen-Gunther Jane, Xia Qingqing, Stacey Winfred, Asusta Heisy B
Gynecologic Oncology & Clinical Investigation, Department of Clinical Investigation, Brooke Army Medical Center, Fort Sam Houston, TX, United States.
Department of Molecular Medicine, Cancer Therapy and Research Center, University of Texas Health Science Center at San Antonio, San Antonio, TX, United States.
Front Microbiol. 2020 Oct 15;11:595902. doi: 10.3389/fmicb.2020.595902. eCollection 2020.
Primary high-risk Human Papillomavirus (hrHPV) screening has recently become an accepted standalone or co-test with conventional cytology. Unfortunately, hrHPV singularly lacks specificity for cytopathological grade. However, mechanisms and markers of evolving virus-host interactions at the epigenome level may be harnessed as a better predictor of carcinogenesis. This study aimed to validate and expand the clinical performance of a multiparametric biomarker panel, referred to as the "Molecular Pap smear" based, on HPV genotype and , and CpG-methylation as a predictive classifier of cervical cytology. This prospective, cross-sectional study used an independent cohort of residual liquid-based cytology for HPV genotyping and epigenetic analysis. Extracted DNA underwent parallel PCR using 3 primer sets for HPV DNA amplification. HPV-infected samples were genotyped by Sanger sequencing. Promoter methylation levels of 3 tumor suppressor genes were quantified by bisulfite-pyrosequencing of genomic DNA on the newest high-resolution PyroMark Q48 platform. Logistic model performance was compared, and model parameters were used to predict and classify binary cytological outcomes. A total of 883 samples were analyzed. HPV DNA positivity correlated with worsening grade: 125/237 (53%) NILM; 136/235 (58%) ASCUS; 222/229 (97%) LSIL; and 157/182 (86%) HSIL samples. The proportion of carcinogenic HPV-types in PCR-positive sequenceable samples correlated with worsening grade: NILM 34/98 (35%); ASCUS 50/113 (44%); LSIL 92/214 (43%); HSIL 129/152 (85%). Additionally, , , and methylation levels increased in direct correlation with worsening grade. Overall, the multi-marker modeling parameters predicted binarized cytological outcomes better than HPV-type alone with significantly higher area under the receiver operator curve (AUC)s, respectively: NILM vs. > NILM (AUC 0.728 vs. 0.709); NILM/ASCUS vs. LSIL/HSIL (AUC 0.805 vs. 0.776); and <HSIL vs. HSIL (AUC 0.830 vs. 0.761). Our expanded findings validated the multivariable prediction model developed for cytological classification. The sequencing-based "Molecular Pap smear" outperformed HPV-type alone in predicting four grades of cervical cytology. Additional host epigenetic markers that evolved with disease progression decidedly contributed to the overall classification accuracy.
原发性高危人乳头瘤病毒（hrHPV）筛查最近已成为一种被认可的独立检测方法，或与传统细胞学检查联合使用。遗憾的是，hrHPV单独检测对细胞病理学分级缺乏特异性。然而，在表观基因组水平上不断演变的病毒-宿主相互作用的机制和标志物，可能被用作更好的致癌预测指标。本研究旨在验证并扩展一种多参数生物标志物组合（称为“分子巴氏涂片”）的临床性能，该组合基于HPV基因型以及 和 CpG甲基化，作为宫颈细胞学的预测分类器。这项前瞻性横断面研究使用了一个独立的剩余液基细胞学队列进行HPV基因分型和表观遗传分析。提取的DNA使用3组引物进行平行PCR以扩增HPV DNA。HPV感染的样本通过桑格测序进行基因分型。通过在最新的高分辨率焦磷酸测序PyroMark Q48平台上对基因组DNA进行亚硫酸氢盐焦磷酸测序，定量3个肿瘤抑制基因的启动子甲基化水平。比较逻辑模型性能，并使用模型参数预测和分类二元细胞学结果。共分析了883个样本。HPV DNA阳性与分级恶化相关：237个样本中有125个（53%）为正常细胞学涂片（NILM）；235个样本中有136个（58%）为非典型鳞状细胞不能明确意义（ASCUS）；229个样本中有222个（97%）为低度鳞状上皮内病变（LSIL）；182个样本中有157个（86%）为高度鳞状上皮内病变（HSIL）。PCR阳性且可测序样本中致癌性HPV类型的比例与分级恶化相关：NILM为98个样本中的34个（35%）；ASCUS为113个样本中的50个（44%）；LSIL为214个样本中的92个（43%）；HSIL为152个样本中的129个（85%）。此外， 、 和 甲基化水平与分级恶化直接相关。总体而言，多标志物建模参数预测二元细胞学结果比单独使用HPV类型更好，受试者操作特征曲线（AUC）下面积分别显著更高：NILM与> NILM（AUC 0.728对0.709）；NILM/ASCUS与LSIL/HSIL（AUC 0.805对0.776）；以及<HSIL与HSIL（AUC 0.830对0.761）。我们扩展后的研究结果验证了为细胞学分类开发的多变量预测模型。基于测序的“分子巴氏涂片”在预测宫颈细胞学的四个分级方面优于单独的HPV类型。随着疾病进展而演变的额外宿主表观遗传标志物无疑有助于提高总体分类准确性。
