宫颈上皮内瘤变
阴道镜检查
医学
前瞻性队列研究
细胞学
宫颈癌
队列
生物标志物
尿
活检
宫颈筛查
内科学
胃肠病学
肿瘤科
癌症
病理
生物
生物化学
作者
Rafael Guerrero‐Preston,Blanca L. Valle,Anne Jedlicka,Nitesh Turaga,Oluwasina Folawiyo,Francesca Pirini,Fahcina Lawson,Angelo Vergura,Maartje Noordhuis,Amanda Dziedzic,Gabriela Pérez,Marisa Renehan,Carolina Guerrero-Díaz,Edgar De Jesus Rodríguez,Teresa Díaz-Montes,José Rodríguez Orengo,Keimari Méndez,Josefina Romaguera,Bruce J. Trock,Liliana Florea
标识
DOI:10.1158/1940-6207.capr-16-0138
摘要
Clinically useful molecular tools to triage women for a biopsy upon referral to colposcopy are not available. We aimed to develop a molecular panel to detect cervical intraepithelial neoplasia (CIN) grade 2 or higher lesions (CIN2+) in women with abnormal cervical cytology and high-risk HPV (HPV+). We tested a biomarker panel in cervical epithelium DNA obtained from 211 women evaluated in a cervical cancer clinic in Chile from 2006 to 2008. Results were verified in a prospective cohort of 107 women evaluated in a high-risk clinic in Puerto Rico from 2013 to 2015. Promoter methylation of ZNF516, FKBP6, and INTS1 discriminated cervical brush samples with CIN2+ lesions from samples with no intraepithelial lesions or malignancy (NILM) with 90% sensitivity, 88.9% specificity, 0.94 area under the curve (AUC), 93.1% positive predictive value (PPV), and 84.2% negative predictive value (NPV). The panel results were verified in liquid-based cervical cytology samples from an independent cohort with 90.9% sensitivity, 60.9% specificity, 0.90 AUC, 52.6% PPV, and 93.3% NPV, after adding HPV16-L1 methylation to the panel. Next-generation sequencing results in HPV+ cultured cells, and urine circulating cell-free DNA (ccfDNA) were used to design assays that show clinical feasibility in a subset (n = 40) of paired plasma (AUC = 0.81) and urine (AUC = 0.86) ccfDNA samples obtained from the prospective cohort. Viral and host DNA methylation panels can be tested in liquid cytology and urine ccfDNA from women referred to colposcopy, to triage CIN2+ lesions for biopsy and inform personalized screening algorithms. Cancer Prev Res; 9(12); 915-24. ©2016 AACR.
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