Role of Methylation Test Triage in HPV Positive Women

Clinical validation of p16/Ki‐67 dual‐stained cytology triage of HPV‐positive women: Results from the IMPACT trial

AbstractTriage strategies are needed for primary human papillomavirus (HPV)‐based cervical cancer screening to identify women requiring colposcopy/biopsy. We assessed the performance of p16/Ki‐67 dual‐stained (DS) immunocytochemistry to triage HPV‐positive women and compared it to cytology, with or without HPV16/18 genotyping. A prospective observational screening study enrolled 35 263 women aged 25 to 65 years at 32 U.S. sites. Cervical samples had HPV and cytology testing, with colposcopy/biopsy for women with positive tests. Women without cervical intraepithelial neoplasia Grade 2 or worse (≥CIN2) at baseline (n = 3876) were retested after 1 year. In all, 4927 HPV‐positive women with valid DS results were included in this analysis. DS sensitivity for ≥CIN2 and ≥CIN3 at baseline was 91.2% (95% confidence interval [CI]: 86.8%‐94.2%) and 91.9% (95% CI: 86.1%‐95.4%), respectively, in HPV16/18‐positive women and 83.0% (95% CI: 78.4%‐86.8%) and 86.0% (95% CI: 77.5%‐91.6%) in women with 12 “other” genotypes. Using DS alone to triage HPV‐positive women showed significantly higher sensitivity and specificity than HPV16/18 genotyping with cytology triage of 12 “other” genotypes, and substantially higher sensitivity but lower specificity than using cytology alone. The risk of ≥CIN2 was significantly lower in HPV‐positive, DS‐negative women (3.6%; 95% CI: 2.9%‐4.4%), compared to triage‐negative women using HPV16/18 genotyping with cytology for 12 “other” genotypes (7.4%; 95% CI: 6.4%‐8.5%; P < .0001) or cytology alone (7.5%; 95% CI: 6.7%‐8.4%; P < .0001). DS showed better risk stratification than cytology‐based strategies and provided high reassurance against pre‐cancers both at baseline and at 1‐year follow‐up, irrespective of the HPV genotype. DS allows for the safe triage of primary screening HPV‐positive women.

HPV‐related methylation‐based reclassification and risk stratification of cervical cancer

Human papillomavirus (HPV) is a clear etiology of cervical cancer (CC). However, the associations between HPV infection and DNA methylation have not been thoroughly investigated. Additionally, it remains unknown whether HPV‐related methylation signatures can identify subtypes of CC and stratify the prognosis of CC patients. DNA methylation profiles were obtained from The Cancer Genome Atlas to identify HPV‐related methylation sites. Unsupervised clustering analysis of HPV‐related methylation sites was performed to determine the different CC subtypes. CC patients were categorized into cluster 1 (Methylation‐H), cluster 2 (Methylation‐M), and cluster 3 (Methylation‐L). Compared to Methylation‐M and Methylation‐L, Methylation‐H exhibited a significantly improved overall survival (OS). Gene set enrichment analysis (GSEA) was conducted to investigate the functions that correlated with different CC subtypes. GSEA indicated that the hallmarks of tumors, including KRAS signaling, TNFα signaling via NF‐κB, inflammatory response, epithelial–mesenchymal transition, and interferon‐gamma response, were enriched in Methylation‐M and Methylation‐L. Based on mutation and copy number variation analyses, we found that aberrant mutations, amplifications, and deletions among the MYC, Notch, PI3K‐AKT, and RTK‐RAS pathways were most frequently detected in Methylation‐H. Additionally, mutations, amplifications, and deletions within the Hippo, PI3K‐AKT, and TGF‐β pathways were presented in Methylation‐M. Genes within the cell cycle, Notch, and Hippo pathways possessed aberrant mutations, amplifications, and deletions in Methylation‐L. Moreover, the analysis of tumor microenvironments revealed that Methylation‐H was characterized by a relatively low degree of immune cell infiltration. Finally, a prognostic signature based on six HPV‐related methylation sites was developed and validated. Our study revealed that CC patients could be classified into three heterogeneous clusters based on HPV‐related methylation signatures. Additionally, we derived a prognostic signature using six HPV‐related methylation sites that stratified the OS of patients with CC into high‐ and low‐risk groups.

Approaches to triage optimization in HPV primary screening: Extended genotyping and p16/Ki‐67 dual‐stained cytology—Retrospective insights from ATHENA

The objective of our study was to assess the performance of different triage strategies for high‐risk human papillomavirus (hrHPV)‐positive results utilizing either extended genotyping or a p16/Ki‐67 dual‐stained cytology (DS) approach, with or without partial genotyping. A subset of women with hrHPV infections participating in the Addressing the Need for Advanced HPV Diagnostics (ATHENA) study were analyzed to determine the number of cervical intraepithelial neoplasia grade 3 or worse (≥CIN3) cases detected, and the absolute risk for ≥CIN3 of each genotype. A clinical utility table was constructed to compare the impact of different triage strategies. In all, 2,339 women with single‐genotype hrHPV infections were identified. Among these were 171 ≥CIN3 cases. The U.S. Food and Drug Administration (FDA)‐approved algorithm (HPV16/18 positive, or 12‐other hrHPV positive and Pap positive, i.e., ≥ atypical squamous cells of undetermined significance) for primary HPV screening detected 132/171 (77.2%) ≥CIN3 cases and required 964 colposcopies (colposcopies per ≥CIN3 ratio: 7.3). An approach that uses DS instead of cytology in the FDA‐approved algorithm detected 147/171 (86.0%) ≥CIN3 cases, requiring 1,012 colposcopies (ratio: 6.9). Utilizing DS for triage of all hrHPV‐positive women identified 126/171 (73.7%) ≥CIN3 cases, requiring 640 colposcopies (ratio: 5.1). A strategy that detected HPV16/18/31/33/35+ captured 130/171 (76.0%) ≥CIN3 cases, requiring 1,025 colposcopies (ratio: 7.9). Inclusion of additional genotypes resulted in greater disease detection at the expense of higher colposcopy ratios. Substituting cytology with a DS triage approach improved disease detection and the colposcopy detection rate. Further reduction of colposcopy rates can be achieved by using DS without partial genotyping. Extended genotyping strategies can identify a comparable number of cases but requires an increased number of colposcopies.

HPV and DNA Methylation Testing in Urine for Cervical Intraepithelial Neoplasia and Cervical Cancer Detection

Abstract Purpose: Biomarker detection in urine offers a potential solution to increase effectiveness of cervical cancer screening programs by attracting nonresponders. In this prospective study, the presence of high-risk human papillomavirus (hrHPV) DNA and the performance of DNA methylation analysis was determined for the detection of cervical cancer and high-grade cervical intraepithelial neoplasia (CIN2/3) in urine, and compared with paired cervicovaginal self-samples and clinician-taken cervical scrapes. Experimental Design: A total of 587 samples were included from 113 women with cervical cancer, 92 women with CIN2/3, and 64 controls. Samples were tested for hrHPV DNA and five methylation markers. Univariate and multivariate logistic regression and leave-one-out cross-validation were used to determine the methylation marker performance for CIN3 and cervical cancer (CIN3+) detection in urine. Agreement between samples was determined using Cohen kappa statistics and the Spearman correlation coefficients. Results: HrHPV presence was high in all sample types, 79% to 92%. Methylation levels of all markers in urine significantly increased with increasing severity of disease. The optimal marker panel (ASCL1/LHX8) resulted in an AUC of 0.84 for CIN3+ detection in urine, corresponding to an 86% sensitivity at a 70% predefined specificity. At this threshold 96% (109/113) of cervical cancers, 68% (46/64) of CIN3, and 58% (14/24) of CIN2 were detected. Between paired samples, a strong agreement for HPV16/18 genotyping and a fair to strong correlation for methylation was found. Conclusions: HrHPV DNA and DNA methylation testing in urine offers a promising solution to detect cervical cancer and CIN2/3 lesions, especially for women currently unreached by conventional screening methods.

Constantijne H. Mom

Irene A.M. van der Avoort

Ivonne Martin

Mark H Stoler

Nienke E van Trommel

Renske DM Steenbergen

Rianne van den Helder

Thomas C. Wright

Zhijun Dai

Dr. Dai is a Professor of Department of Oncology, the Second Affiliated Hospital, Xi'an Jiaotong University. His research has been focused on anticancer and pharmacological properties of natural compounds. He obtained a PhD and Master’s degree from Xi'an Jiaotong University, China. Dr. Dai has published more than 100 peer-reviewed articles. He also has been on the editorial board of many international journals.