Human papillomavirus (HPV) genotypes in women with cervical precancer and cancer at Kaiser Permanente Northern California

Improved detection of low-frequency within-host variants from deep sequencing: A case study with human papillomavirus

High-coverage sequencing allows the study of variants occurring at low frequencies within samples, but is susceptible to false-positives caused by sequencing error. Ion Torrent has a very low single nucleotide variant (SNV) error rate and has been employed for the majority of human papillomavirus (HPV) whole genome sequences. However, benchmarking of intrahost SNVs (iSNVs) has been challenging, partly due to limitations imposed by the HPV life cycle. We address this problem by deep sequencing three replicates for each of 31 samples of HPV type 18 (HPV18). Errors, defined as iSNVs observed in only one of three replicates, are dominated by C→T (G→A) changes, independently of trinucleotide context. True iSNVs, defined as those observed in all three replicates, instead show a more diverse SNV type distribution, with particularly elevated C→T rates in CCG context (CCG→CTG; CGG→CAG) and C→A rates in ACG context (ACG→AAG; CGT→CTT). Characterization of true iSNVs allowed us to develop two methods for detecting true variants: (1) VCFgenie, a dynamic binomial filtering tool which uses each variant's allele count and coverage instead of fixed frequency cut-offs; and (2) a machine learning binary classifier which trains eXtreme Gradient Boosting models on variant features such as quality and trinucleotide context. Each approach outperforms fixed-cut-off filtering of iSNVs, and performance is enhanced when both are used together. Our results provide improved methods for identifying true iSNVs in within-host applications across sequencing platforms, specifically using HPV18 as a case study.

A novel human papillomavirus and host DNA methylation score and detection of cervical adenocarcinoma

BACKGROUND

The widespread introduction of Pap testing in the 1960s was followed by substantial reductions in the incidence of cervical squamous cell cancer (SCC). However, the incidence of cervical adenocarcinoma (ADC) did not decrease, likely because of low Pap test sensitivity for ADC and adenocarcinoma in situ (AIS). This study assessed a novel human papillomavirus (HPV) and host DNA Methylation Score for AIS and ADC screening.

METHODS

We measured methylation levels at CpG sites in the L2/L1 open reading frames of HPV16, HPV18, and HPV45-as well as 2 human loci, DCC and HS3ST2. Specifically, we tested exfoliated cervicovaginal cells from women in the HPV Persistence and Progression (PaP) cohort who were positive for 1 of HPV16, 18, or 45, including: 1) 176 with AIS/ADC, 2) 353 with cervical intraepithelial neoplasia-3 (CIN3) or SCC, and 3) controls who either cleared (HPV-Clearers; n = 579) or had persistent HPV16, 18, or 45 infection (HPV-Persisters; n = 292). CpG site-specific methylation percentages were measured using our reported next-generation methods. The Methylation Score was the average methylation percentage across all 35 CpG sites tested.

RESULTS

Each individual CpG site had higher methylation percentages in exfoliated cervicovaginal cells collected from patients with AIS/ADC, and as well as those with CIN3/SCC, relative to either control group (weakest P  = .004). The Methylation Score for AIS/ADC had a sensitivity of 74% and specificity of 89%. The multivariate odds ratio (OR) between the Methylation Score (4th vs 1st quartile) for AIS/ADC was ORq4-q1 = 49.01 (PBenjamini-Hochberg = 4.64E-12), using HPV-Clearers as controls. CIN3/SCC had similar, albeit weaker, associations with the Methylation Score.

CONCLUSIONS

HPV16/18/45-infected women with Methylation Scores in the highest quartile had very high odds of AIS/ADC, suggesting they may warrant careful histologic evaluation of the cervical transition zone (eg, conization or loop electrosurgical excision procedure [LEEP]).

Contribution of Etiologic Cofactors to CIN3+ Risk Among Women With Human Papillomavirus-Positive Screening Test Results

OBJECTIVE

The US screening and management guidelines for cervical cancer are based on the absolute risk of precancer estimated from large clinical cohorts and trials. Given the widespread transition toward screening with human papillomavirus (HPV) testing, it is important to assess which additional factors to include in clinical risk assessment to optimize management of HPV-infected women.

MATERIALS AND METHODS

We analyzed data from HPV-infected women, ages 30-65 years, in the National Cancer Institute-Kaiser Permanente Northern California Persistence and Progression study. We estimated the influence of HPV risk group, cytology result, and selected cofactors on immediate risk of cervical intraepithelial neoplasia grade 3 or higher (CIN 3+) among 16,094 HPV-positive women. Cofactors considered included, age, race/ethnicity, income, smoking, and hormonal contraceptive use.

RESULTS

Human papillomavirus risk group and cytology test result were strongly correlated with CIN 3+ risk. After considering cytology and HPV risk group, other cofactors (age, race/ethnicity, income, smoking, and hormonal contraceptive use) had minimal impact on CIN 3+ risk and did not change recommended management based on accepted risk thresholds. We had insufficient data to assess the impact of long-duration heavy smoking, parity, history of sexually transmitted infection, or immunosuppression.

CONCLUSIONS

In our study at the Kaiser Permanente Northern California, the risk of CIN 3+ was determined mainly by HPV risk group and cytology results, with other cofactors having limited impact in adjusted analyses. This supports the use of HPV and cytology results in risk-based management guidelines.

Phylogenomic Analysis of Human Papillomavirus Type 31 and Cervical Carcinogenesis: A Study of 2093 Viral Genomes

Human papillomavirus (HPV) type 31 (HPV31) is closely related to the most carcinogenic type, HPV16, but only accounts for 4% of cervical cancer cases worldwide. Viral genetic and epigenetic variations have been associated with carcinogenesis for other high-risk HPV types, but little is known about HPV31. We sequenced 2093 HPV31 viral whole genomes from two large studies, one from the U.S. and one international. In addition, we investigated CpG methylation in a subset of 175 samples. We evaluated the association of HPV31 lineages/sublineages, single nucleotide polymorphisms (SNPs) and viral methylation with cervical carcinogenesis. HPV31 A/B clade was >1.8-fold more associated with cervical intraepithelial neoplasia grade 3 and cancer (CIN3+) compared to the most common C lineage. Lineage/sublineage distribution varied by race/ethnicity and geographic region. A viral genome-wide association analysis identified SNPs within the A/B clade associated with CIN3+, including H23Y (C626T) (odds ratio = 1.60, confidence intervals = 1.17-2.19) located in the pRb CR2 binding-site within the E7 oncogene. Viral CpG methylation was higher in lineage B, compared to the other lineages, and was most elevated in CIN3+. In conclusion, these data support the increased oncogenicity of the A/B lineages and suggest variation of E7 as a contributing risk factor.

Genetic and Epigenetic Variations of HPV52 in Cervical Precancer

The goal of this study was to identify human papillomavirus (HPV) type 52 genetic and epigenetic changes associated with high-grade cervical precancer and cancer. Patients were selected from the HPV Persistence and Progression (PaP) cohort, a cervical cancer screening program at Kaiser Permanente Northern California (KPNC). We performed a nested case-control study of 89 HPV52-positive women, including 50 cases with predominantly cervical intraepithelial neoplasia grade 3 (CIN3) and 39 controls without evidence of abnormalities. We conducted methylation analyses using Illumina sequencing and viral whole genome Sanger sequencing. Of the 24 CpG sites examined, increased methylation at CpG site 5615 in HPV52 L1 region was the most significantly associated with CIN3, with a difference in median methylation of 17.9% (odds ratio (OR) = 4.8, 95% confidence interval (CI) = 1.9–11.8) and an area under the curve of 0.73 (AUC; 95% CI = 0.62–0.83). Complete genomic sequencing of HPV52 isolates revealed associations between SNPs present in sublineage C2 and a higher risk of CIN3, with ORs ranging from 2.8 to 3.3. This study identified genetic and epigenetic HPV52 variants associated with high risk for cervical precancer, improving the potential for early diagnosis of cervical neoplasia caused by HPV52.

Age-related distribution of uncommon HPV genotypes in cervical intraepithelial neoplasia grade 3

AIM

Cervical cancer prevention guidelines include Human Papillomavirus (HPV) test, cytology, and HPV-16/18 typing for triage to determine the risk of cervical intraepithelial neoplasia (CIN) grade 3 as the best proxy of cervical cancer risk. In doing that, they do not consider how age can modify the type-specific risk of CIN3. The present study aimed to evaluate the age-related distribution of HPV genotypes affecting the risk-assessment in cervical cancer screening programs: non-screening-type-HPV and non-HPV-16/18 in unvaccinated women with CIN3.

METHODS

Retrospective multi-institutional study, including HPV genotyped women with CIN3 on cone histology treated between 2014 and 2019. The sample was divided into three categories of age: <30, 30-44, ≥45. HPV genotypes were grouped in non-screening-type-HPV (not-including genotypes 16/18/31/33/35/39/45/51/52/56/58/59/66/68) and non-HPV-16/18. Associations and trends between different age-groups and HPV genotypes were measured.

RESULTS

1332 women were analyzed. Non-screening-type-HPV CIN3 were 73 (5.5%). Non-HPV-16/18 were found in 417 participants (31.3%). Women over 45 associated with non-screening-type HPV [odds ratio (OR) = 1.87, 95% confidence interval (CI) 1.07-3.25; p = 0.027]. Non-screening-type-HPV prevalence increased significantly with age (3.9% vs 5.1% vs 9.0%, p = 0.016). Women under 30 showed a lower rate of non-HPV-16/18 (OR = 0.65, 95% CI 0.47-0.89; p = 0.007). There was a positive trend with age of non-HPV-16/18 CIN3 (23.6% vs 32.1% vs 38.0%, p = 0.0004).

CONCLUSION

The proportion of CIN3 lesions unrelated to genotypes detected by primary screening tests increased with age. This implies that age probably modifies the risk of CIN3 and possibly of cancer associated with HPV types. The risk-based recommendation should take into consideration age to define the management of HPV positive women.

A proposed new generation of evidence-based microsimulation models to inform global control of cervical cancer

Health decision models are the only available tools designed to consider the lifetime natural history of human papillomavirus (HPV) infection and pathogenesis of cervical cancer, and the estimated long-term impact of preventive interventions. Yet health decision modeling results are often considered a lesser form of scientific evidence due to the inherent needs to rely on imperfect data and make numerous assumptions and extrapolations regarding complex processes. We propose a new health decision modeling framework that de-emphasizes cytologic-colposcopic-histologic diagnoses due to their subjectivity and lack of reproducibility, relying instead on HPV type and duration of infection as the major determinants of subsequent transition probabilities. We posit that the new model health states (normal, carcinogenic HPV infection, precancer, cancer) and corollary transitions are universal, but that the probabilities of transitioning between states may vary by population. Evidence for this variability in host response to HPV infections can be inferred from HPV prevalence patterns in different regions across the lifespan, and might be linked to different average population levels of immunologic control of HPV infections. By prioritizing direct estimation of model transition probabilities from longitudinal data (and limiting reliance on model-fitting techniques that may propagate error when applied to multiple transitions), we aim to reduce the number of assumptions for greater transparency and reliability. We propose this new microsimulation model for critique and discussion, hoping to contribute to models that maximally inform efficient strategies towards global cervical cancer elimination.

High grade cervical intraepithelial neoplasia positive biopsy: the importance of accurate pre-operative workup

BACKGROUND

In cervical cancer screening programs, women with abnormal cytology and confirmation by biopsy are referred for colposcopy for histological evaluation.

METHODS

We characterized the presence and the genotype of HPV by Linear Array HPV genotyping assay in cytological samples collected from about 400 women undergoing conization, with reported high CIN grade after biopsy.

RESULTS

The most prevalent genotype was HPV 16, with an increasing presence depending on the severity of the CIN and with the highest incidence in the 26-35 age range. In the group of younger women (<25) we found the highest percentage of CIN3 (39.3%) and the lowest of CIN1 (17.9%). An increase of CIN1 with increasing age was observed. A different distribution of HPV presence was observed depending on CIN grade (P<0.001): CIN1 HPV negative samples were 46.3%, CIN2: 5.8% and CIN3: 1.4%. Interesting, in the analyzed cohort, we observed the presence of 30% of CIN1. Moreover, within CIN1, 85% of them were associated to negative HPV detection, this observation suggested that the detection of HPV presence may be useful to identify low CIN grade that should be reconsidered for surgical treatment.

CONCLUSIONS

These findings suggest implementing the protocol for the management of women with high risk precancer lesions, with a further HPV test before surgical treatment. The evaluation of HPV presence and genotype before conization might represent a useful tool in reducing or postpone the conization treatment.

A Study of Partial Human Papillomavirus Genotyping in Support of the 2019 ASCCP Risk-Based Management Consensus Guidelines

INTRODUCTION

The 2019 ASCCP Risk-Based Management Consensus Guidelines include recommendations for partial human papillomavirus (HPV) genotyping in management of abnormal cervical cancer screening results. The guidelines are based on matching estimates of cervical intraepithelial neoplasia (CIN) 3+ risk to consensus clinical action thresholds. In support of the guidelines, this analysis addresses the risks predicted by individual identification of HPV 16 and HPV 18.

METHODS

Risk estimates were drawn from a subset of women in the Kaiser Permanente Northern California screening program, whose residual cervical specimens were HPV typed as part of the HPV Persistence and Progression study. We calculated risk of CIN 3+ to assess how identification of HPV 16, HPV 18, or 12 other "high-risk" HPV types would influence recommended clinical management of new abnormal screening results, taking into account current cytologic results and recent screening history. Immediate and/or 5-year risks of CIN 3+ were matched to clinical actions identified in the guidelines.

RESULTS

Identification of HPV 16 at the first visit including HPV testing elevated immediate risk of diagnosing CIN 3+ sufficiently to mandate colposcopic referral even when cytology was Negative for Intraepithelial Lesions or Malignancy and to support a preference for treatment of cytologic high-grade squamous intraepithelial lesion. HPV 18 less clearly elevated CIN 3+ risk.

CONCLUSIONS

Identification of HPV 16 clearly mandated consideration in clinical management of new abnormal screening results. HPV 18 positivity must be considered as a special situation because of established disproportionate risk of invasive cancer. More detailed genotyping and use beyond initial management will be considered in guideline updates.

2019 ASCCP Risk-Based Management Consensus Guidelines: Methods for Risk Estimation, Recommended Management, and Validation

Supplemental digital content is available in the text.

Objective

To manage cervical screening abnormalities, the 2019 ASCCP management consensus guidelines will recommend clinical action on the basis of risk of cervical precancer and cancer. This article details the methods used to estimate risk, to determine the risk-based management, and to validate that the risk-based recommendations are of general use in different settings.

Methods

Based on 1.5 million patients undergoing triennial cervical screening by cotesting at the Kaiser Permanente Northern California from 2003 to 2017, we estimated risk profiles for different clinical scenarios and combinations of past and current human papillomavirus and cytology test results. We validated the recommended management by comparing with the estimated risks in several external data sources.

Results

Risk and management tables are presented separately by Egemen et al.¹ and Demarco et al.² Risk-based management derived from the Kaiser Permanente Northern California largely agreed with the management implied from the estimated risks of the other data sources.

Conclusions

The new risk-based guidelines present management of abnormal cervical screening results. By describing the steps used to develop these guidelines, the methods presented in this article can provide a basis for future extensions of the risk-based guidelines.

A study of type-specific HPV natural history and implications for contemporary cervical cancer screening programs

BACKGROUND

HPV testing is replacing cytology for cervical cancer screening because of greater sensitivity and superior reassurance following negative tests for the dozen HPV genotypes that cause cervical cancer. Management of women testing positive is unresolved. The need for identification of individual HPV genotypes for clinical use is debated. Also, it is unclear how long to observe persistent infections when precancer is not initially found.

METHODS

In the longitudinal NCI-Kaiser Permanente Northern California Persistence and Progression (PaP) Study, we observed the clinical outcomes (clearance, progression to CIN3+, or persistence without progression) of 11,573 HPV-positive women aged 30-65 yielding 14,158 type-specific infections.

FINDINGS

Risks of CIN3+ progression differed substantially by type, with HPV16 conveying uniquely elevated risk (26% of infections with seven-year CIN3+ risk of 22%). The other carcinogenic HPV types fell into 3 distinct seven-year CIN3+ risk groups: HPV18, 45 (13% of infections, risks >5%, with known elevated cancer risk); HPV31, 33, 35, 52, 58 (39%, risks >5%); and HPV39, 51, 56, 59, 68 (23%, risks <5%). In the absence of progression, HPV clearance rates were similar by type, with 80% of infections no longer detected within three years; persistence to seven years without progression was uncommon. The predictive value of abnormal cytology was most evident for prevalent CIN3+, but less evident in follow-up. A woman's age did not modify risk; rather it was the duration of persistence that was important.

INTERPRETATION

HPV type and persistence are the major predictors of progression to CIN3+; at a minimum, distinguishing HPV16 is clinically important. Dividing the other HPV types into three risk-groups is worth considering.

Mutations in the HPV16 genome induced by APOBEC3 are associated with viral clearance

HPV16 causes half of cervical cancers worldwide; for unknown reasons, most infections resolve within two years. Here, we analyze the viral genomes of 5,328 HPV16-positive case-control samples to investigate mutational signatures and the role of human APOBEC3-induced mutations in viral clearance and cervical carcinogenesis. We identify four de novo mutational signatures, one of which matches the COSMIC APOBEC-associated signature 2. The viral genomes of the precancer/cancer cases are less likely to contain within-host somatic HPV16 APOBEC3-induced mutations (Fisher's exact test, P = 6.2 x 10-14), and have a 30% lower nonsynonymous APOBEC3 mutation burden compared to controls. We replicate the low prevalence of HPV16 APOBEC3-induced mutations in 1,749 additional cases. APOBEC3 mutations also historically contribute to the evolution of HPV16 lineages. We demonstrate that cervical infections with a greater burden of somatic HPV16 APOBEC3-induced mutations are more likely to be benign or subsequently clear, suggesting they may reduce persistence, and thus progression, within the host.

Age-Related Changes in the Fraction of Cervical Intraepithelial Neoplasia Grade 3 Related to HPV Genotypes Included in the Nonavalent Vaccine

Objective

The prevalence of some human papillomavirus (HPV) genotypes has been shown to change with age. So, also the distribution of HPV genotypes included in the nonavalent vaccine may not be the same at all ages, and this could mean that vaccine protection against cervical cancer may be affected by age. The present study aimed to evaluate whether there are age-related changes in the fraction of high-grade cervical intraepithelial neoplasia (CIN) attributable to HPV genotypes included in the nonavalent vaccine.

Methods

Two hundred four consecutive women undergoing conization with a histological diagnosis of CIN3 were retrospectively analyzed. All included women had a preconization HPV genotyping (HPV Sign® Genotyping Test). The women were divided into three groups according to age: <35, 35–44, and ≥45 years of age. Based on HPV genotypes detected in cervical lesions, the age-related changes in the expected vaccine protection were evaluated by the Cochran–Armitage test for trend.

Results

The fraction of CIN3 attributable to HPV genotypes included in the nonavalent vaccine showed a significant negative trend with increasing age, with potential vaccine protection of 82% after the age of 45 (p=0.006). The rate of HPV-16 and HPV-33, included in the vaccine, showed a negative trend with age (p=0.047 and p=0.044, respectively). Among HPV genotypes not covered by the vaccine, the rate of non-high-risk HPVs (genotypes: 53-54-70-73-82-85-87) showed a significant positive trend with increasing age (p=0.018).

Conclusions

Although the fraction of CIN3 attributable to genotypes included in the nonavalent HPV vaccine was high even after age 45, older women appeared to be more at risk of high-grade CIN related to HPV genotypes not included in the vaccine. Interestingly, older women showed a higher rate of precancerous cervical lesions associated with non-high-risk HPV. The present findings seem to raise the question about the management of cervical pathology at a later age in a future postvaccination era.

Bayesian analysis of baseline risk of CIN2 and ≥CIN3 by HPV genotype in a European referral cohort

Whereas HPV16 and HPV18 have been the focus in current risk-based cervical cancer screening algorithms using HPV genotype information, mounting evidence suggests that oncogenic HPV types such as HPV31, 33, 52 and 58 pose a ≥CIN3 risk equivalent to or greater than that of HPV18, and the combined risk of HPV31 and HPV33 rivals even HPV16 in women above 30 years of age. Here, we evaluate the baseline risk of CIN2 and CIN3 by genotype in a colposcopy referral population from Denmark and Italy. In total, 655 women were enrolled upon a referral to colposcopy after a positive screening sample. All samples were HPV analyzed using Onclarity HPV assay with extended genotyping and combined with the histology outcomes, a Bayesian probability modeling was used to determine the risk per genotype assessed. The combined data for this referral population showed that the ≥CIN2 risk of HPV16 was 69.1%, HPV31 at 63.3%, HPV33/58 at 52.7%, HPV18 at 46.6% and HPV52 at 40.8%. For ≥CIN3, the risks were 44.3%, 38.5%, 36.8%, 30.9% and 16.8% for HPV16, HPV31, HPV18, HPV33/58 and HPV52, respectively, indicating that the baseline risk of disease arising from HPV16 is, not surprisingly, the highest among the oncogenic HPV genotypes. We find that the HPV genotype-specific ≥CIN2 and ≥CIN3 risk-patterns are so distinct that, for example, 35/39/68 and 56/59/66 should be considered only for low intensive follow-up, thereby proposing active use of this information in triage strategies for screening HPV-positive women.

Human papillomavirus types in cervical high-grade lesions or cancer among Nordic women-Potential for prevention

It is valuable to establish a population‐based prevaccination baseline distribution of human papillomavirus (HPV) types among women with high‐grade cervical intraepithelial neoplasia (CIN) grade 2 or 3 and cervical cancer in order to assess the potential impact of HPV vaccination. In four countries (Denmark, Norway, Sweden, and Iceland), we collected consecutive series of cervical cancers (n = 639) and high‐grade precancerous cervical lesions (n = 1240) during 2004‐2006 before implementation of HPV vaccination and subjected the specimens to standardized HPV genotyping. The HPV prevalence was 82.7% (95% confidence interval [CI] 79.0‐86.4) in CIN2, 91.6% (95% CI 89.7‐93.5) in CIN3, and 86.4% (95% CI 83.7‐89.1) in cervical cancer. The most common HPV types in CIN2/3 were HPV16 (CIN2: 35.9%, 95% CI 31.2‐40.6; CIN3: 50.2%, 95% CI 46.8‐53.6) and HPV31 (CIN2: 10.9%, 95% CI 7.8‐13.9; CIN3: 12.1%, 95% CI 9.9‐14.3), while HPV16 and HPV18 were the most frequent types in cervical cancer (48.8%, 95% CI 44.9‐52.7 and 15.3%, 95% CI 12.5‐18.1, respectively). The prevalence of HPV16/18 decreased with increasing age at diagnosis in both CIN2/3 and cervical cancer (P < 0.0001). Elimination of HPV16/18 by vaccination is predicted to prevent 42% (95% CI 37.0‐46.7) of CIN2, 57% (95% CI 53.8‐60.5) of CIN3 and 64% (95% CI 60.3‐67.7) of cervical cancer. Prevention of the five additional HPV types HPV31/33/45/52/58 would increase the protection to 68% (95% CI 63.0‐72.2) in CIN2, 85% (95% CI 82.4‐87.2) in CIN3 and 80% (95% CI 77.0‐83.2) in cervical cancer. This study provides large‐scale and representative baselines for assessing and evaluating the population‐based preventive impact of HPV vaccination.

Niche adaptation and viral transmission of human papillomaviruses from archaic hominins to modern humans

Recent discoveries on the origins of modern humans from multiple archaic hominin populations and the diversity of human papillomaviruses (HPVs) suggest a complex scenario of virus-host evolution. To evaluate the origin of HPV pathogenesis, we estimated the phylogeny, timing, and dispersal of HPV16 variants using a Bayesian Markov Chain Monte Carlo framework. To increase precision, we identified and characterized non-human primate papillomaviruses from New and Old World monkeys to set molecular clock models. We demonstrate specific host niche adaptation of primate papillomaviruses with subsequent coevolution with their primate hosts for at least 40 million years. Analyses of 212 HPV16 complete genomes and 3582 partial sequences estimated ancient divergence of HPV16 variants (between A and BCD lineages) from their most recent common ancestors around half a million years ago, roughly coinciding with the timing of the split between archaic Neanderthals and modern Homo sapiens, and nearly three times longer than divergence times of modern Homo sapiens. HPV16 A lineage variants were significantly underrepresented in present African populations, whereas the A sublineages were highly prevalent in European (A1-3) and Asian (A4) populations, indicative of viral sexual transmission from Neanderthals to modern non-African humans through multiple interbreeding events in the past 80 thousand years. Remarkably, the human leukocyte antigen B*07:02 and C*07:02 alleles associated with increased risk in cervix cancer represent introgressed regions from Neanderthals in present-day Eurasians. The archaic hominin-host-switch model was also supported by other HPV variants. Niche adaptation and virus-host codivergence appear to influence the pathogenesis of papillomaviruses.

Low Risk of Cervical Cancer/Precancer Among Most Women Under Surveillance Postcolposcopy

Objective

To inform impending postcolposcopy guidelines, this analysis examined the subsequent risk of CIN 3+ among women with a grade lower than CIN 2 (< CIN 2) colposcopy results, taking into account the referring results that brought them to colposcopy and cotest results postcolposcopy.

Methods

We analyzed 107,005 women from 25 to 65 years old, recommended for colposcopy at Kaiser Permanente Northern California. We estimated absolute risks of CIN 3+ among women: (1) recommended for colposcopy (precolposcopy), (2) following colposcopy and with histology results < CIN 2 (postcolposcopy), and (3) with cotest results 12 months after a < CIN 2 colposcopy (return cotest).

Results

After colposcopy showing < CIN 2 (n = 69,790; 87% of the women at colposcopy), the 1-year risk of CIN 3+ was 1.2%, compared with 6.3% at the time of colposcopy recommendation. Negative cotest results 1 year after colposcopy identified a large group (37.1%) of women whose risk of CIN 3+ (i.e., <0.2% at 3 years after postcolposcopy cotest) was comparable with women with normal cytology in the screening population. These risks are consistent with current guidelines recommending repeat cotesting 12 months after colposcopy < CIN 2 and a 3-year return for women with a negative postcolposcopy cotest.

Conclusions

Most women are at low risk of subsequent CIN 3+ after a colposcopy showing < CIN 2, especially those who are human papillomavirus–negative postcolposcopy, consistent with current management guidelines for repeat testing intervals. Before the finalizing the upcoming guidelines, we will consider additional rounds of postcolposcopy cotesting.

Validation of a Human Papillomavirus (HPV) DNA Cervical Screening Test That Provides Expanded HPV Typing

As cervical cancer screening shifts from cytology to human papillomavirus (HPV) testing, a major question is the clinical value of identifying individual HPV types. We aimed to validate Onclarity (Becton Dickinson Diagnostics, Sparks, MD), a nine-channel HPV test recently approved by the FDA, by assessing (i) the association of Onclarity types/channels with precancer/cancer; (ii) HPV type/channel agreement between the results of Onclarity and cobas (Roche Molecular Systems, Pleasanton, CA), another FDA-approved test; and (iii) Onclarity typing for all types/channels compared to typing results from a research assay (linear array [LA]; Roche). We compared Onclarity to histopathology, cobas, and LA. We tested a stratified random sample (n = 9,701) of discarded routine clinical specimens that had tested positive by Hybrid Capture 2 (HC2; Qiagen, Germantown, MD). A subset had already been tested by cobas and LA (n = 1,965). Cervical histopathology was ascertained from electronic health records. Hierarchical Onclarity channels showed a significant linear association with histological severity. Onclarity and cobas had excellent agreement on partial typing of HPV16, HPV18, and the other 12 types as a pool (sample-weighted kappa value of 0.83); cobas was slightly more sensitive for HPV18 and slightly less sensitive for the pooled high-risk types. Typing by Onclarity showed excellent agreement with types and groups of types identified by LA (kappa values from 0.80 for HPV39/68/35 to 0.97 for HPV16). Onclarity typing results corresponded well to histopathology and to an already validated HPV DNA test and could provide additional clinical typing if such discrimination is determined to be clinically desirable.

Human Papillomavirus DNA Methylation as a Biomarker for Cervical Precancer: Consistency across 12 Genotypes and Potential Impact on Management of HPV-Positive Women

Purpose: Human papillomavirus (HPV) DNA methylation testing is a promising triage option for women testing HPV positive during cervical cancer screening. However, the extent to which methylation indicates precancer for all 12 carcinogenic HPV types has not been evaluated.Experimental Design: In this nested case-control study, we tested up to 30 cases of precancer [cervical intraepithelial neoplasia grade 3 (CIN3)/adenocarcinoma in situ (AIS)] and 30 normal controls for each carcinogenic type (single infections with 16/18/31/33/35/39/45/51/52/56/58/59). Next-generation bisulfite sequencing was performed on CpG sites within the L1 and L2 genes. We calculated differences in methylation, ORs, and AUC. Using a fixed sensitivity of 80%, we evaluated the specificity and the risk of CIN3/AIS for best performing CpG sites, and compared the performance of an explorative multi-type methylation assay with current triage strategies.Results: Methylation was positively associated with CIN3/AIS across all 12 types. AUCs for the top sites ranged from 0.71 (HPV51 and HPV56) to 0.86 (HPV18). A combined 12-type methylation assay had the highest Youden index (0.46), compared with cytology (0.31) and a 5-type methylation assay, including only previously described types (0.26). The 12-type methylation assay had higher sensitivity (80% vs. 76.6%) and lower test positivity compared with cytology (38.5% vs. 48.7%). The risk of CIN3/AIS was highest for methylation positives and lowest for cytology or HPV16/18 positives.Conclusions: HPV DNA methylation is a general phenomenon marking the transition from HPV infection to precancer for all 12 carcinogenic types. Development of a combined multitype methylation assay may serve as a triage test for HPV-positive women. Clin Cancer Res; 24(9); 2194-202. ©2018 AACR.

HPV16 E7 Genetic Conservation Is Critical to Carcinogenesis

Although most cervical human papillomavirus type 16 (HPV16) infections become undetectable within 1-2 years, persistent HPV16 causes half of all cervical cancers. We used a novel HPV whole-genome sequencing technique to evaluate an exceptionally large collection of 5,570 HPV16-infected case-control samples to determine whether viral genetic variation influences risk of cervical precancer and cancer. We observed thousands of unique HPV16 genomes; very few women shared the identical HPV16 sequence, which should stimulate a careful re-evaluation of the clinical implications of HPV mutation rates, transmission, clearance, and persistence. In case-control analyses, HPV16 in the controls had significantly more amino acid changing variants throughout the genome. Strikingly, E7 was devoid of variants in precancers/cancers compared to higher levels in the controls; we confirmed this in cancers from around the world. Strict conservation of the 98 amino acids of E7, which disrupts Rb function, is critical for HPV16 carcinogenesis, presenting a highly specific target for etiologic and therapeutic research.

[Pap Smear after 65 years]

The French recommendations (in favor of stopping cervical cancer screening by cervico-uterine smear from 65 years of age) are logical in the context of organized screening; however, it is not yet generalized in France. The proportion of invasive cervical cancer in the oldest patients is high and these cancers are more evolved and have a more pejorative prognosis. The prevalent infection with high-risk HPV virus remains important in elderly patients: if the HPV infection does not appear to be more risky in the elderly, HPV-induced lesions appear to be more evolving. Unfortunately, pap smear coverage rates are low in the most advanced age groups. Patients without adequate follow-up are exposed to invasive cancer after age 65: all studies insist on the protective effect of two or more normal pap smears between 50 and 65 years that would allow to stop screening. Recent publications in Europe insist, however, on the value of continuing screening beyond the age of 65 in populations that live longer. For the clinician, in France, patients who could benefit from systematic FCU after age 65 could be those: (1) who request it, (2) who have an HPV history, (3) who have not had more than 3 consecutive normal pap smears or (4) who have an associated pathogenic condition. The place of the HPV test deserves to be considered: because of its very high negative predictive value, it could be performed as an exit test or as an alternative test to the pap smear.

Age-related changes in pre- and post-conization HPV genotype distribution among women with high-grade cervical intraepithelial neoplasia

OBJECTIVE

To assess the effect of age on pre- and post-conization HPV genotype distribution.

METHODS

The present retrospective observational study included consecutive women with high-grade cervical intraepithelial neoplasia who underwent conization at the Cervical Cancer Screening Centre of Reggio Emilia, Italy, and University Hospital of Modena, Italy, between February 1, 2012, and October 31, 2014. Pre-conization and 6-month post-conization HPV genotyping results were compared between four age groups (<30, 30-39, 40-49, and ≥50 years) and age-related changes in the HPV genotypes present were evaluated.

RESULTS

There were 162 patients included. The lowest occurrence of pre-conization high-risk and probable high-risk HPV genotypes was observed among patients aged at least 50 years when compared with younger patients (P=0.017). Conversely, women aged at least 50 years exhibited the highest level of post-conization high-risk and probable high-risk HPV genotypes (P=0.043). Additionally, an increasing incidence of recording identical pre- and post-conization HPV genotypes was associated with increasing age (P=0.024), as was increasing post-treatment recurrence of cervical intraepithelial neoplasia grade 2+ (P=0.030).

CONCLUSION

The presence of high-risk and probable high-risk HPV genotypes was lowest among older patients before conization and was highest among these patients post-conization; post-treatment HPV clearance decreased with age and increasing age could be a risk factor for post-conization recurrence.

HPV16 Sublineage Associations With Histology-Specific Cancer Risk Using HPV Whole-Genome Sequences in 3200 Women

BACKGROUND

HPV16 is a common sexually transmitted infection although few infections lead to cervical precancer/cancer; we cannot distinguish nor mechanistically explain why only certain infections progress. HPV16 can be classified into four main evolutionary-derived variant lineages (A, B, C, D) that have been previously suggested to have varying disease risks.

METHODS

We used a high-throughput HPV16 whole-genome sequencing assay to investigate variant lineage risk among 3215 HPV16-infected women. Using sublineages A1/A2 as the reference, we assessed all variant lineage associations with infection outcome over three or more years of follow-up: 1107 control subjects (

RESULTS

A4 sublineage was associated with an increased risk of cancer, specifically adenocarcinoma (OR = 9.81, 95% CI = 2.02 to 47.69, P = 4.7x10(-03)). Lineage B had a lower risk of CIN3 (OR = 0.51, 95% CI = 0. 28 to 0.91, P = 02) while lineage C showed increased risk (OR = 2.06, 95% CI = 1.09 to 3.89, P = 03). D2/D3 sublineages were strongly associated with an increased risk of CIN3 and cancer, particularly D2 (OR for cancer = 28.48, 95% CI = 9.27 to 87.55, P = 5.0x10(-09)). D2 had the strongest increased risk of glandular lesions, AIS (OR = 29.22, 95% CI = 8.94 to 95.51, P = 2.3x10(-08)), and adenocarcinomas (OR = 137.34, 95% CI = 37.21 to 506.88, P = 1.5x10(-13)). Moreover, the risk of precancer and cancer for specific variant lineages varied by a women's race/ethnicity; those women whose race/ethnicity matched that of the infecting HPV16 variant had an increased risk of CIN3 + (P < 001).

CONCLUSIONS

Specific HPV16 variant sublineages strongly influence risk of histologic types of precancer and cancer, and viral genetic variation may help explain its unique carcinogenic properties.

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Key Words Collapse

MESH Headings

• Adenocarcinoma/ethnology
• Adenocarcinoma/virology
• Adenocarcinoma in Situ/ethnology
• Adenocarcinoma in Situ/virology
• Adult
• Aftercare
• California/epidemiology
• Carcinoma/ethnology
• Carcinoma/virology
• Carcinoma, Squamous Cell/ethnology
• Carcinoma, Squamous Cell/virology
• Female
• Genome
• High-Throughput Nucleotide Sequencing
• Human papillomavirus 16/classification
• Human papillomavirus 16/genetics
• Human papillomavirus 16/pathogenicity
• Humans
• Middle Aged
• Papillomavirus Infections/ethnology
• Papillomavirus Infections/virology
• Phylogeny
• Precancerous Conditions/ethnology
• Precancerous Conditions/virology
• Risk Factors
• Uterine Cervical Neoplasms/ethnology
• Uterine Cervical Neoplasms/virology
• Young Adult
• Uterine Cervical Dysplasia/ethnology
• Uterine Cervical Dysplasia/virology

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Grants

• U01 CA078527 NCI NIH HHS

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Affiliation(s)

Lisa Mirabello Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (LM, MY, MC, JFB, NW, XZ, KY, QY, JM, DR, SB, LB, YX, MS); Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD (MY, MC, JFB, XZ, QY, JM, DR, SB, LB); Department of Microbiology, The Chinese University of Hong Kong, Hong Kong (ZC); Women's Health Research Institute, Division of Research, Kaiser Permanente Northern California, Oakland CA (TRB); Regional Laboratory, Kaiser Permanente Northern California, Oakland, CA (TL); Department of Epidemiology and Population Health, at Albert Einstein College of Medicine, Bronx, NY (PEC, RDB); Departments of Pediatrics; Microbiology & Immunology; and, Obstetrics, Gynecology and Women's Health, at Albert Einstein College of Medicine, Bronx, NY (RDB)
Meredith Yeager Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (LM, MY, MC, JFB, NW, XZ, KY, QY, JM, DR, SB, LB, YX, MS); Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD (MY, MC, JFB, XZ, QY, JM, DR, SB, LB); Department of Microbiology, The Chinese University of Hong Kong, Hong Kong (ZC); Women's Health Research Institute, Division of Research, Kaiser Permanente Northern California, Oakland CA (TRB); Regional Laboratory, Kaiser Permanente Northern California, Oakland, CA (TL); Department of Epidemiology and Population Health, at Albert Einstein College of Medicine, Bronx, NY (PEC, RDB); Departments of Pediatrics; Microbiology & Immunology; and, Obstetrics, Gynecology and Women's Health, at Albert Einstein College of Medicine, Bronx, NY (RDB)
Michael Cullen Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (LM, MY, MC, JFB, NW, XZ, KY, QY, JM, DR, SB, LB, YX, MS); Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD (MY, MC, JFB, XZ, QY, JM, DR, SB, LB); Department of Microbiology, The Chinese University of Hong Kong, Hong Kong (ZC); Women's Health Research Institute, Division of Research, Kaiser Permanente Northern California, Oakland CA (TRB); Regional Laboratory, Kaiser Permanente Northern California, Oakland, CA (TL); Department of Epidemiology and Population Health, at Albert Einstein College of Medicine, Bronx, NY (PEC, RDB); Departments of Pediatrics; Microbiology & Immunology; and, Obstetrics, Gynecology and Women's Health, at Albert Einstein College of Medicine, Bronx, NY (RDB)
Joseph F Boland Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (LM, MY, MC, JFB, NW, XZ, KY, QY, JM, DR, SB, LB, YX, MS); Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD (MY, MC, JFB, XZ, QY, JM, DR, SB, LB); Department of Microbiology, The Chinese University of Hong Kong, Hong Kong (ZC); Women's Health Research Institute, Division of Research, Kaiser Permanente Northern California, Oakland CA (TRB); Regional Laboratory, Kaiser Permanente Northern California, Oakland, CA (TL); Department of Epidemiology and Population Health, at Albert Einstein College of Medicine, Bronx, NY (PEC, RDB); Departments of Pediatrics; Microbiology & Immunology; and, Obstetrics, Gynecology and Women's Health, at Albert Einstein College of Medicine, Bronx, NY (RDB)
Zigui Chen Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (LM, MY, MC, JFB, NW, XZ, KY, QY, JM, DR, SB, LB, YX, MS); Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD (MY, MC, JFB, XZ, QY, JM, DR, SB, LB); Department of Microbiology, The Chinese University of Hong Kong, Hong Kong (ZC); Women's Health Research Institute, Division of Research, Kaiser Permanente Northern California, Oakland CA (TRB); Regional Laboratory, Kaiser Permanente Northern California, Oakland, CA (TL); Department of Epidemiology and Population Health, at Albert Einstein College of Medicine, Bronx, NY (PEC, RDB); Departments of Pediatrics; Microbiology & Immunology; and, Obstetrics, Gynecology and Women's Health, at Albert Einstein College of Medicine, Bronx, NY (RDB)
Nicolas Wentzensen Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (LM, MY, MC, JFB, NW, XZ, KY, QY, JM, DR, SB, LB, YX, MS); Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD (MY, MC, JFB, XZ, QY, JM, DR, SB, LB); Department of Microbiology, The Chinese University of Hong Kong, Hong Kong (ZC); Women's Health Research Institute, Division of Research, Kaiser Permanente Northern California, Oakland CA (TRB); Regional Laboratory, Kaiser Permanente Northern California, Oakland, CA (TL); Department of Epidemiology and Population Health, at Albert Einstein College of Medicine, Bronx, NY (PEC, RDB); Departments of Pediatrics; Microbiology & Immunology; and, Obstetrics, Gynecology and Women's Health, at Albert Einstein College of Medicine, Bronx, NY (RDB)
Xijun Zhang Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (LM, MY, MC, JFB, NW, XZ, KY, QY, JM, DR, SB, LB, YX, MS); Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD (MY, MC, JFB, XZ, QY, JM, DR, SB, LB); Department of Microbiology, The Chinese University of Hong Kong, Hong Kong (ZC); Women's Health Research Institute, Division of Research, Kaiser Permanente Northern California, Oakland CA (TRB); Regional Laboratory, Kaiser Permanente Northern California, Oakland, CA (TL); Department of Epidemiology and Population Health, at Albert Einstein College of Medicine, Bronx, NY (PEC, RDB); Departments of Pediatrics; Microbiology & Immunology; and, Obstetrics, Gynecology and Women's Health, at Albert Einstein College of Medicine, Bronx, NY (RDB)
Kai Yu Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (LM, MY, MC, JFB, NW, XZ, KY, QY, JM, DR, SB, LB, YX, MS); Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD (MY, MC, JFB, XZ, QY, JM, DR, SB, LB); Department of Microbiology, The Chinese University of Hong Kong, Hong Kong (ZC); Women's Health Research Institute, Division of Research, Kaiser Permanente Northern California, Oakland CA (TRB); Regional Laboratory, Kaiser Permanente Northern California, Oakland, CA (TL); Department of Epidemiology and Population Health, at Albert Einstein College of Medicine, Bronx, NY (PEC, RDB); Departments of Pediatrics; Microbiology & Immunology; and, Obstetrics, Gynecology and Women's Health, at Albert Einstein College of Medicine, Bronx, NY (RDB)
Qi Yang Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (LM, MY, MC, JFB, NW, XZ, KY, QY, JM, DR, SB, LB, YX, MS); Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD (MY, MC, JFB, XZ, QY, JM, DR, SB, LB); Department of Microbiology, The Chinese University of Hong Kong, Hong Kong (ZC); Women's Health Research Institute, Division of Research, Kaiser Permanente Northern California, Oakland CA (TRB); Regional Laboratory, Kaiser Permanente Northern California, Oakland, CA (TL); Department of Epidemiology and Population Health, at Albert Einstein College of Medicine, Bronx, NY (PEC, RDB); Departments of Pediatrics; Microbiology & Immunology; and, Obstetrics, Gynecology and Women's Health, at Albert Einstein College of Medicine, Bronx, NY (RDB)
Jason Mitchell Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (LM, MY, MC, JFB, NW, XZ, KY, QY, JM, DR, SB, LB, YX, MS); Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD (MY, MC, JFB, XZ, QY, JM, DR, SB, LB); Department of Microbiology, The Chinese University of Hong Kong, Hong Kong (ZC); Women's Health Research Institute, Division of Research, Kaiser Permanente Northern California, Oakland CA (TRB); Regional Laboratory, Kaiser Permanente Northern California, Oakland, CA (TL); Department of Epidemiology and Population Health, at Albert Einstein College of Medicine, Bronx, NY (PEC, RDB); Departments of Pediatrics; Microbiology & Immunology; and, Obstetrics, Gynecology and Women's Health, at Albert Einstein College of Medicine, Bronx, NY (RDB)
David Roberson Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (LM, MY, MC, JFB, NW, XZ, KY, QY, JM, DR, SB, LB, YX, MS); Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD (MY, MC, JFB, XZ, QY, JM, DR, SB, LB); Department of Microbiology, The Chinese University of Hong Kong, Hong Kong (ZC); Women's Health Research Institute, Division of Research, Kaiser Permanente Northern California, Oakland CA (TRB); Regional Laboratory, Kaiser Permanente Northern California, Oakland, CA (TL); Department of Epidemiology and Population Health, at Albert Einstein College of Medicine, Bronx, NY (PEC, RDB); Departments of Pediatrics; Microbiology & Immunology; and, Obstetrics, Gynecology and Women's Health, at Albert Einstein College of Medicine, Bronx, NY (RDB)
Sara Bass Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (LM, MY, MC, JFB, NW, XZ, KY, QY, JM, DR, SB, LB, YX, MS); Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD (MY, MC, JFB, XZ, QY, JM, DR, SB, LB); Department of Microbiology, The Chinese University of Hong Kong, Hong Kong (ZC); Women's Health Research Institute, Division of Research, Kaiser Permanente Northern California, Oakland CA (TRB); Regional Laboratory, Kaiser Permanente Northern California, Oakland, CA (TL); Department of Epidemiology and Population Health, at Albert Einstein College of Medicine, Bronx, NY (PEC, RDB); Departments of Pediatrics; Microbiology & Immunology; and, Obstetrics, Gynecology and Women's Health, at Albert Einstein College of Medicine, Bronx, NY (RDB)
Yanzi Xiao Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (LM, MY, MC, JFB, NW, XZ, KY, QY, JM, DR, SB, LB, YX, MS); Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD (MY, MC, JFB, XZ, QY, JM, DR, SB, LB); Department of Microbiology, The Chinese University of Hong Kong, Hong Kong (ZC); Women's Health Research Institute, Division of Research, Kaiser Permanente Northern California, Oakland CA (TRB); Regional Laboratory, Kaiser Permanente Northern California, Oakland, CA (TL); Department of Epidemiology and Population Health, at Albert Einstein College of Medicine, Bronx, NY (PEC, RDB); Departments of Pediatrics; Microbiology & Immunology; and, Obstetrics, Gynecology and Women's Health, at Albert Einstein College of Medicine, Bronx, NY (RDB)
Laurie Burdett Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (LM, MY, MC, JFB, NW, XZ, KY, QY, JM, DR, SB, LB, YX, MS); Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD (MY, MC, JFB, XZ, QY, JM, DR, SB, LB); Department of Microbiology, The Chinese University of Hong Kong, Hong Kong (ZC); Women's Health Research Institute, Division of Research, Kaiser Permanente Northern California, Oakland CA (TRB); Regional Laboratory, Kaiser Permanente Northern California, Oakland, CA (TL); Department of Epidemiology and Population Health, at Albert Einstein College of Medicine, Bronx, NY (PEC, RDB); Departments of Pediatrics; Microbiology & Immunology; and, Obstetrics, Gynecology and Women's Health, at Albert Einstein College of Medicine, Bronx, NY (RDB)
Tina Raine-Bennett Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (LM, MY, MC, JFB, NW, XZ, KY, QY, JM, DR, SB, LB, YX, MS); Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD (MY, MC, JFB, XZ, QY, JM, DR, SB, LB); Department of Microbiology, The Chinese University of Hong Kong, Hong Kong (ZC); Women's Health Research Institute, Division of Research, Kaiser Permanente Northern California, Oakland CA (TRB); Regional Laboratory, Kaiser Permanente Northern California, Oakland, CA (TL); Department of Epidemiology and Population Health, at Albert Einstein College of Medicine, Bronx, NY (PEC, RDB); Departments of Pediatrics; Microbiology & Immunology; and, Obstetrics, Gynecology and Women's Health, at Albert Einstein College of Medicine, Bronx, NY (RDB)
Thomas Lorey Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (LM, MY, MC, JFB, NW, XZ, KY, QY, JM, DR, SB, LB, YX, MS); Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD (MY, MC, JFB, XZ, QY, JM, DR, SB, LB); Department of Microbiology, The Chinese University of Hong Kong, Hong Kong (ZC); Women's Health Research Institute, Division of Research, Kaiser Permanente Northern California, Oakland CA (TRB); Regional Laboratory, Kaiser Permanente Northern California, Oakland, CA (TL); Department of Epidemiology and Population Health, at Albert Einstein College of Medicine, Bronx, NY (PEC, RDB); Departments of Pediatrics; Microbiology & Immunology; and, Obstetrics, Gynecology and Women's Health, at Albert Einstein College of Medicine, Bronx, NY (RDB)
Philip E Castle Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (LM, MY, MC, JFB, NW, XZ, KY, QY, JM, DR, SB, LB, YX, MS); Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD (MY, MC, JFB, XZ, QY, JM, DR, SB, LB); Department of Microbiology, The Chinese University of Hong Kong, Hong Kong (ZC); Women's Health Research Institute, Division of Research, Kaiser Permanente Northern California, Oakland CA (TRB); Regional Laboratory, Kaiser Permanente Northern California, Oakland, CA (TL); Department of Epidemiology and Population Health, at Albert Einstein College of Medicine, Bronx, NY (PEC, RDB); Departments of Pediatrics; Microbiology & Immunology; and, Obstetrics, Gynecology and Women's Health, at Albert Einstein College of Medicine, Bronx, NY (RDB)
Robert D Burk Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (LM, MY, MC, JFB, NW, XZ, KY, QY, JM, DR, SB, LB, YX, MS); Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD (MY, MC, JFB, XZ, QY, JM, DR, SB, LB); Department of Microbiology, The Chinese University of Hong Kong, Hong Kong (ZC); Women's Health Research Institute, Division of Research, Kaiser Permanente Northern California, Oakland CA (TRB); Regional Laboratory, Kaiser Permanente Northern California, Oakland, CA (TL); Department of Epidemiology and Population Health, at Albert Einstein College of Medicine, Bronx, NY (PEC, RDB); Departments of Pediatrics; Microbiology & Immunology; and, Obstetrics, Gynecology and Women's Health, at Albert Einstein College of Medicine, Bronx, NY (RDB)
Mark Schiffman Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (LM, MY, MC, JFB, NW, XZ, KY, QY, JM, DR, SB, LB, YX, MS); Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick, MD (MY, MC, JFB, XZ, QY, JM, DR, SB, LB); Department of Microbiology, The Chinese University of Hong Kong, Hong Kong (ZC); Women's Health Research Institute, Division of Research, Kaiser Permanente Northern California, Oakland CA (TRB); Regional Laboratory, Kaiser Permanente Northern California, Oakland, CA (TL); Department of Epidemiology and Population Health, at Albert Einstein College of Medicine, Bronx, NY (PEC, RDB); Departments of Pediatrics; Microbiology & Immunology; and, Obstetrics, Gynecology and Women's Health, at Albert Einstein College of Medicine, Bronx, NY (RDB)

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Effectiveness of less than three doses of quadrivalent human papillomavirus vaccine against cervical intraepithelial neoplasia when administered using a standard dose spacing schedule: Observational cohort of young women in Australia

Background

Optimised two-dose human papillomavirus (HPV) vaccine schedules are now endorsed for young adolescents by the World Health Organization. Limited data are available about effectiveness of <3 doses using a standard dose schedule.

Methods

Deterministic data linkage was undertaken between the Victorian Cervical Cytology Registry and National HPV Vaccination Program Register to determine quadrivalent HPV vaccination status and incidence of cervical pathology among vaccine eligible women (aged 26 years or younger in 2007) screened in Victoria, Australia between April 2007 and December 2011. Proportional hazards regression was used to estimate hazard ratios (HR) adjusted for age, socioeconomic status and area of residence. Women were stratified into those vaccinated before or after first screen.

Results

Any number of doses (1, 2 or 3) were associated with lower rates of high grade and low grade cytology diagnoses as long as doses were given before screening commencement (one dose HR high grade 0.44 (95% CI 0.32–0.59), one dose low grade 0.48 (95% CI 0.40–0.58); two doses HR high grade 0.63 (95% CI 0.50–0.80), HR low grade 0.52 (95% CI 0.44–0.61); three doses HR high grade 0.53 (95% CI 0.47–0.60), HR low grade 0.73 (95% CI 0.68–0.78)). Three doses of vaccine, but not fewer, were associated with reduced risk of high grade histologically confirmed abnormality in this cohort, regardless of whether vaccination occurred before or after screening (HR before 0.71 (95% CI 0.64–0.80), HR after 0.87 (95% CI 0.82–0.93)). Secondary analyses censoring end points occurring within 1, 6, 12, or 24 months of final vaccine dose suggested an increasing effect of partial vaccination courses over time.

Conclusion

Our data suggest that less than three doses of quadrivalent HPV vaccine provides some protection against cervical intraepithelial neoplasia, even when measured within 5 years in a population including those who were sexually active at the time of vaccination.

Deep sequencing of HPV16 genomes: A new high-throughput tool for exploring the carcinogenicity and natural history of HPV16 infection

For unknown reasons, there is huge variability in risk conferred by different HPV types and, remarkably, strong differences even between closely related variant lineages within each type. HPV16 is a uniquely powerful carcinogenic type, causing approximately half of cervical cancer and most other HPV-related cancers. To permit the large-scale study of HPV genome variability and precancer/cancer, starting with HPV16 and cervical cancer, we developed a high-throughput next-generation sequencing (NGS) whole-genome method. We designed a custom HPV16 AmpliSeq™ panel that generated 47 overlapping amplicons covering 99% of the genome sequenced on the Ion Torrent Proton platform. After validating with Sanger, the current "gold standard" of sequencing, in 89 specimens with concordance of 99.9%, we used our NGS method and custom annotation pipeline to sequence 796 HPV16-positive exfoliated cervical cell specimens. The median completion rate per sample was 98.0%. Our method enabled us to discover novel SNPs, large contiguous deletions suggestive of viral integration (OR of 27.3, 95% CI 3.3-222, P=0.002), and the sensitive detection of variant lineage coinfections. This method represents an innovative high-throughput, ultra-deep coverage technique for HPV genomic sequencing, which, in turn, enables the investigation of the role of genetic variation in HPV epidemiology and carcinogenesis.

The Role of Human Papillomavirus Genotyping in Cervical Cancer Screening: A Large-Scale Evaluation of the cobas HPV Test

BACKGROUND

The cobas HPV Test ("cobas"; Roche Molecular Systems) detects HPV16 and HPV18 individually, and a pool of 12 other high-risk (HR) HPV types. The test is approved for (i) atypical squamous cells of undetermined significance (ASC-US) triage to determine need for colposcopy, (ii) combined screening with cytology ("cotesting"), and (iii) primary HPV screening.

METHODS

To assess the possible value of HPV16/18 typing, >17,000 specimens from a longitudinal cohort study of initially HPV-positive women (HC2, Qiagen) were retested with cobas. To study accuracy, cobas genotyping results were compared with those of an established method, the Linear Array HPV Genotyping Test (LA, Roche Molecular Systems). Clinical value of the typing strategy was evaluated by linking the cobas results (supplemented by other available typing results) to 3-year cumulative risks of CIN3+.

RESULTS

Grouped hierarchically (HPV16, else HPV18, else other HR types, else negative), the κ statistic for agreement between cobas and LA was 0.86 [95% confidence interval (CI), 0.86-0.87]. In all three scenarios, HPV16-positive women were at much higher 3-year risk of CIN3+ than HPV16-negative women: women ages 21 and older with ASC-US (14.5%; 95% CI, 13.5%-15.5% vs. 3.5%; 95% CI, 3.3-3.6); women ages 30 years and older that were HPV-positive cytology-negative (10.3%; 95% CI, 9.6-11.1 vs. 2.3%; 95% CI, 2.2-2.4); and all women 25 years and older that were HPV-positive (18.5%; 95% CI, 17.8-19.2 vs. 4.3%; 95% CI, 4.2-4.4).

CONCLUSION

The cobas and LA results show excellent agreement. The data support HPV16 typing.

IMPACT

HPV16 typing is useful in the management of HPV-positive/cytology-negative women in cotesting, of all HPV-positive women in primary HPV testing, and perhaps in the management of HPV-positive women with ASC-US. Cancer Epidemiol Biomarkers Prev; 24(9); 1304-10.

Age-related changes in the diagnostic assessment of women with severe cervical lesions

OBJECTIVES

To evaluate the effect of age on the diagnostic assessment of women with severe cervical intraepithelial neoplasia (CIN).

METHODS

This retrospective observational study included 338 consecutive women with a diagnosis of CIN3 on cone specimen. Patients were divided into three groups according to age: < 35 years (Group A), 35-49 years (Group B), and ≥ 50 years (Group C). Clinical and colposcopic variables were compared, and human papillomavirus (HPV) genotype distribution was measured.

RESULTS

The most common HPV genotype was HPV-16 (63.65%), followed by HPV-33 (7%), HPV-18 (6.2%), and HPV-31 (5.4%). The rate of the following high-grade lesion predictors was lower in Group C than in Groups A and B: HPV-16 infections (55.9% vs. 75% vs. 70.9%, respectively, p = 0.022); high-grade colposcopic impression (29.4% vs. 51.8% vs. 51.7%, respectively, p < 0.0001); and high-grade cytological changes (30.9% vs. 56.2% vs. 45.4%, respectively, p = 0.025). An endocervical lesion location was more frequent in Group C than in Groups A and B (55.6% vs. 6.8% vs. 11.8%, respectively, p < 0.0001).

CONCLUSION

Women aged 50 years and older with CIN3 showed a significant reduction of high-grade lesion predictors along with physiological confounding cervical changes (transformation zone type 3 and endocervical lesion location). The diagnostic work-up of cervical lesions in older women should provide their potential consideration as a special population.

HPV16 methyl-haplotypes determined by a novel next-generation sequencing method are associated with cervical precancer

We have developed and evaluated a next-generation bisulfite sequencing (NGS) assay to distinguish HPV16 cervical precancer (CIN2-3; N=59) from HPV16-positive transient infections (N=40). Cervical DNA was isolated and treated with bisulfite and HPV16 methylation was quantified by (i) amplification with barcoded primers and massively parallel single molecule sequencing and (ii) site-specific pyrosequencing. Assays were evaluated for agreement using intraclass correlation coefficients (ICC). Odds ratios (OR) for high methylation vs. low methylation were calculated. Single site pyrosequencing and NGS data were correlated (ICC=0.61) and both indicated hypermethylation was associated with precancer (ORs of 2-37). Concordant NGS and pyrosequencing results yieled ORs that were stronger when compared with using either assay separately. Within the L1 region, the ORs for CIN2-3 were 14.3 and 22.4 using pyrosequencing and NGS assays, respectively; when both methods agreed the OR was 153. NGS assays provide methylation haplotypes, termed methyl-haplotypes from single molecule reads: cases had increased methyl-haplotypes with ≥1 methylated CpG site(s) per fragment compared with controls, particularly in L1 (p=3.0×10(-8)). The maximum discrimination of cases from controls for a L1 methyl-haplotype had an AUC of 0.89 corresponding to a sensitivity of 92.5% and a specificity of 73.1%. The strengthening of the OR when the two assays were concordant suggests the true association of CpG methylation with precancer is stronger than with either assay. As cervical cancer prevention moves to DNA testing methods, DNA based biomarkers, such as HPV methylation could serve as a reflex strategy to identify women at high risk for cervix cancer.

HPV type attribution in high-grade cervical lesions: assessing the potential benefits of vaccines in a population-based evaluation in the United States

BACKGROUND

Two currently available vaccines targeting human papillomavirus (HPV) types 16 and 18 could prevent 70% of cervical cancers and 50% of high-grade cervical lesions. Next-generation vaccines against additional types, such as a candidate 9-valent vaccine against HPV6/11/16/18/31/33/45/52/58, could further reduce HPV-associated disease burden.

METHODS

HPV was typed in archived tissues from women ages 21 to 39 years residing in five catchment areas in the United States with cervical intraepithelial neoplasia 2/3 and adenocarcinoma in situ (CIN2+) using L1 consensus PCR and type-specific hybridization. Type attribution was estimated using weights to account for lesions with multiple types detected.

RESULTS

From 2008 to 2011, 5,498 of 6,306 (87.2%) specimens obtained from 8,469 women with CIN2+ had valid typing results; HPV DNA was detected in 97.3%. Overall, 50.1% of lesions were attributable to HPV16/18, ranging from 50.3% to 52.4% among those ages 21 to 34 years, and significantly declined in 35 to 39 year-olds (43.5%). HPV16/18 attribution was higher in non-Hispanic whites (56.4%) versus racial/ethnic minorities (range, 41.8%-45.9%; P < 0.001). HPV31/33/45/52/58 attribution was 25.0% overall and increased with age (P < 0.001). A higher proportion of CIN2+ was attributable to HPV31/33/45/52/58 in non-Hispanic black (29.9%), Hispanic (29.2%), and Asian (33.1%) women compared with non-Hispanic whites (22.8%; P < 0.001).

CONCLUSIONS

Overall, 75% of lesions were attributable to 7 oncogenic HPV types: 50% to HPV16/18 and 25% to HPV31/33/45/52/58. HPV16/18 had the largest attributable fraction in CIN2+ across all subpopulations, although to a lesser extent in older women and racial/ethnic minorities.

IMPACT

Vaccines targeting additional oncogenic HPV types could prevent more high-grade cervical lesions, especially among racial/ethnic minorities.

Prevalence of human papillomavirus types in invasive cervical cancers from 7 US cancer registries before vaccine introduction

OBJECTIVE

We conducted a baseline study of human papillomavirus (HPV) type prevalence in invasive cervical cancers (ICCs) using data from 7 cancer registries (CRs) in the United States. Cases were diagnosed between 1994 and 2005 before the implementation of the HPV vaccines.

MATERIALS AND METHODS

Cancer registries from Florida, Kentucky, Louisiana, Michigan, Hawaii, Iowa, and Los Angeles, California identified eligible ICC cases and obtained sections from representative blocks of archived tumor specimens for DNA extraction. All extracts were assayed by linear array and, if inadequate or HPV negative, retested with INNO-LiPA Genotype test. Clinical and demographic factors were obtained from the CRs and merged with the HPV typing data to analyze factors associated with different types and with HPV negativity.

RESULTS

A total of 777 ICCs were included in this analysis, with broad geographic, age, and race distribution. Overall, HPV was detected in 91% of cases, including 51% HPV-16, 16% HPV-18 (HPV-16-negative), and 24% other oncogenic and rare types. After HPV-16 and -18, the most common types were 45, 33, 31, 35, and 52. Older age and nonsquamous histology were associated with HPV-negative typing.

CONCLUSIONS

This study provides baseline prevaccine HPV types for postvaccine ICC surveillance in the future. HPV-16 and/or -18 were found in 67% of ICCs, indicating the potential for vaccines to prevent a significant number of cervical cancers.

Human papillomavirus genotype-specific prevalence across the continuum of cervical neoplasia and cancer

BACKGROUND

The New Mexico HPV Pap Registry was established to measure the impact of cervical cancer prevention strategies in the United States. Before widespread human papillomavirus (HPV) vaccine implementation, we established the baseline prevalence for a broad spectrum of HPV genotypes across the continuum of cervical intraepithelial neoplasia (CIN) and cancer.

METHODS

A population-based sample of 6,272 tissue specimens was tested for 37 HPV genotypes. The number of specimens tested within each diagnostic category was: 541 negative, 1,411 CIN grade 1 (CIN1), 2,226 CIN grade 2 (CIN2), and 2,094 CIN grade 3 (CIN3) or greater. Age-specific HPV prevalence was estimated within categories for HPV genotypes targeted by HPV vaccines.

RESULTS

The combined prevalence of HPV genotypes included in the quadrivalent and nonavalent vaccines increased from 15.3% and 29.3% in CIN1 to 58.4% and 83.7% in CIN3, respectively. Prevalence of HPV types included in both vaccines tended to decrease with increasing age for CIN1, CIN2, CIN3, and squamous cell carcinoma (SCC), most notably for CIN3 and SCC. The six most common HPV types in descending order of prevalence were HPV-16, -31, -52, -58, -33, and -39 for CIN3 and HPV-16, -18, -31, -45, -52, and -33 for invasive cancers.

CONCLUSIONS

Health economic modeling of HPV vaccine impact should consider age-specific differences in HPV prevalence.

IMPACT

Population-based HPV prevalence in CIN is not well described, but is requisite for longitudinal assessment of vaccine impact and to understand the effectiveness and performance of various cervical screening strategies in vaccinated and unvaccinated women.

A study of genotyping for management of human papillomavirus-positive, cytology-negative cervical screening results

The effective management of women with human papillomavirus (HPV)-positive, cytology-negative results is critical to the introduction of HPV testing into cervical screening. HPV typing has been recommended for colposcopy triage, but it is not clear which combinations of high-risk HPV types provide clinically useful information. This study included 18,810 women with Hybrid Capture 2 (HC2)-positive, cytology-negative results and who were age ≥30 years from Kaiser Permanente Northern California. The median follow-up was 475 days (interquartile range [IQR], 0 to 1,077 days; maximum, 2,217 days). The baseline specimens from 482 cases of cervical intraepithelial neoplasia grade 3 or cancer (CIN3+) and 3,517 random HC2-positive noncases were genotyped using 2 PCR-based methods. Using the case-control sampling fractions, the 3-year cumulative risks of CIN3+ were calculated for each individual high-risk HPV type. The 3-year cumulative risk of CIN3+ among all women with HC2-positive, cytology-negative results was 4.6%. HPV16 status conferred the greatest type-specific risk stratification; women with HC2-positive/HPV16-positive results had a 10.6% risk of CIN3+, while women with HC-2 positive/HPV16-negative results had a much lower risk of 2.4%. The next most informative HPV types and their risks in HPV-positive women were HPV33 (5.9%) and HPV18 (5.9%). With regard to the etiologic fraction, 20 of 71 cases of cervical adenocarcinoma in situ (AIS) and adenocarcinoma in the cohort were positive for HPV18. HPV16 genotyping provides risk stratification useful for guiding clinical management; the risk among HPV16-positive women clearly exceeds the U.S. consensus risk threshold for immediate colposcopy referral. HPV18 is of particular interest because of its association with difficult-to-detect glandular lesions. There is a less clear clinical value of distinguishing the other high-risk HPV types.

The influence of type-specific human papillomavirus infections on the detection of cervical precancer and cancer: A population-based study of opportunistic cervical screening in the United States

There are limited data on the prospective risks of detecting cervical precancer and cancer in United States (US) populations specifically where the delivery of opportunistic cervical screening takes place outside managed care and in the absence of organized national programs. Such data will inform the management of women with positive screening results before and after widespread human papillomavirus (HPV) vaccination and establishes a baseline preceding recent changes in US cervical cancer screening guidelines. Using data reported to the statewide passive surveillance systems of the New Mexico HPV Pap Registry, we measured the 3-year HPV type-specific cumulative incidence of cervical intraepithelial neoplasia grade 2 or more severe (CIN2+) and grade 3 or more severe (CIN3+) detected during real-world health care delivery across a diversity of organizations, payers, clinical settings, providers and patients. A stratified sample of 47,541 cervical cytology specimens from a screening population of 379,000 women underwent HPV genotyping. Three-year risks for different combinations of cytologic interpretation and HPV risk group ranged from <1% (for several combinations) to approximately 70% for CIN2+ and 55% for CIN3+ in women with high-grade (HSIL) cytology and HPV16 infection. A substantial proportion of CIN2+ (35.7%) and CIN3+ (30.9%) were diagnosed following negative cytology, of which 62.3 and 78.2%, respectively, were high-risk HPV positive. HPV16 had the greatest 3-year risks (10.9% for CIN2+,8.0% for CIN3+) followed by HPV33, HPV31, and HPV18. Positive results for high-risk HPV, especially HPV16, the severity of cytologic interpretation, and age contribute independently to the risks of CIN2+ and CIN3+.

Individual detection of 14 high risk human papilloma virus genotypes by the PapType test for the prediction of high grade cervical lesions

Background

HR HPV genotypes when assayed collectively, achieve high sensitivity but low specificity for the prediction of CIN2+. Knowledge of the specific genotypes in an infection may facilitate the use of HR HPV detection in routine clinical practice.

Objectives

To compare the rate of HR HPV detection and the accuracy of CIN2+ prediction between PapType test (Genera Biosystems) and other commercially available HR HPV assays, and to examine the value of full HPV genotyping.

Study design

PreservCyt samples from 1099 women referred for abnormal cervical cytology were used. CIN2+ was chosen as the primary end-point but CIN3+ was also evaluated. A hierarchy of HR HPV genotypes was created using PPV and this was used to create 3 groups of genotypes with potentially different management.

Results

The PapType assay has a specificity of 22.4% and a sensitivity of 94.6% for CIN2+ prediction. Classification into Groups A (HPV33 and HPV16, very highly predictive), B (HPV31, 18, 52, 35, 58, 51 highly predictive) and C (HPV68, 45, 39, 66, 56, 59, intermediate predictive) could double the specificity (44.5%) but only slightly reduce the sensitivity for CIN2+ (91.5%) and CIN3+ (94.0%).

Conclusions

The PapType assay is a simple, reproducible and effective test for HR HPV detection and genotyping. HPV 33 was found to have a very high PPV and should therefore be managed as for HPV16.

Molecular epidemiology of human papillomavirus infections in cervical samples from cuban women older than 30 years

OBJECTIVE

This study aimed to provide information about the molecular epidemiology of human papillomavirus (HPV) in a group of Cuban women.

MATERIALS AND METHODS

DNA from cervical samples was analyzed using a quantitative real-time polymerase chain reaction (PCR), which detects 6 of the clinically most relevant high-risk HPV types. Furthermore, end point PCR and sequencing were performed. Three hundred twenty-two women (211 with positive and 111 with negative cytologic results) aged between 30 and 69 years were enrolled. Risk factors associated with HPV infections and premalignant lesions were also investigated.

RESULTS

HPV DNA was detected in 76.1% (245/322) of the studied population, and 34 different genotypes were found. There was an association between HPV infection and low educational level, history of oral contraceptives, menopausal stage, as well as cigarette and/or alcohol consumption. Besides, in a multivariate analysis, previous positive Pap test result and positive colposcopy finding were both predictor variables for HPV infections and for premalignant lesions. Human papillomavirus infection was found in 94.3% of women (199/211) with positive cytologic result and in 41.4% (46/111) of those with negative results, being more likely that the first group was infected with any HPV (odds ratio = 23.43; 95% CI = 11.70-46.92; p = .000). The most common genotypes were HPV types 16, 18, 31, 58, 33, and 45. All the cases with HPV positive findings had at least 1 high-risk HPV genotype.

CONCLUSIONS

This is the first report of the molecular epidemiology of HPV in Cuban women, based on results from a DNA sequence and quantitative PCR. Most individuals were infected with high-risk HPV types. These findings support the inclusion of HPV vaccine in Cuba.

Comparing human papillomavirus prevalences in women with normal cytology or invasive cervical cancer to rank genotypes according to their oncogenic potential: a meta-analysis of observational studies

BACKGROUND

Mucosal human papillomavirus (HPV) infection is a necessary cause of cervical cancer. Vaccine and non-vaccine genotype prevalences may change after vaccine introduction. Therefore, it appears essential to rank HPV genotypes according to their oncogenic potential for invasive cervical cancer, independently of their respective prevalences.

METHODS

We performed meta-analyses of published observational studies and estimated pooled odds ratios with random-effects models for 32 HPV genotypes, using HPV-16 as the reference.

RESULTS

Twenty-seven studies yielded 9,252 HPV-infected women: 2,902 diagnosed with invasive cervical cancer and 6,350 with normal cytology. Expressed as (odds ratio [95% confidence interval]), HPV-18 (0.63 [0.51, 0.78]) ranked closest to HPV-16, while other genotypes showed continuously decreasing relative oncogenic potentials: HPV-45 (0.35 [0.22, 0.55]), HPV-69 (0.28 [0.09, 0.92]), HPV-58 (0.24 [0.15, 0.38]), HPV-31 (0.22 [0.14, 0.35]), HPV-33 (0.22 [0.12, 0.38]), HPV-34 (0.21 [0.06, 0.80]), HPV-67 (0.21 [0.06, 0.67]), HPV-39 (0.17 [0.09, 0.30]), HPV-59 (0.17 [0.09, 0.31]), HPV-73 (0.16 [0.06, 0.41]), and HPV-52 (0.16 [0.11, 0.23]).

CONCLUSIONS

Our results support the markedly higher oncogenic potentials of HPV-16 and -18, followed by HPV-31, -33, -39, -45, -52, -58 and -59, and highlight the need for further investigation of HPV-34, -67, -69 and -73. Overall, these findings could have important implications for the prevention of cervical cancer.

Human papillomavirus genotype spectrum in studied group of Montenegrin women

The risk of high-grade lesions and carcinoma is known to correlate with specific high-risk HPV genotypes. The distribution of HPV types varies between countries and little is known about HPV distribution in our country. Therefore, the purpose of this study was to determine the range and frequency of HPV genotypes in studied group of women in Montenegro. HPV genotypes were determined using the method of enzyme restriction of PCR products amplified with group-specific primers MY09/MY11 and restricted with seven different restriction endonucleases. Out of the total number of women HPV infection was found in 1/5 of participants (20%). Genotyping performed in HPV DNA positive women shows that the HPV genotype 16 is dominant and present in more than 1/3 of the participants (36.8%). The second most frequent HPV infection is with HPV genotype 58 and it is found in 10.5% of participants. HPV 31 and HPV 6 infections are present in 7.9% of women, while infections with other genotypes were demonstrated individually by 2.6%. Multiple HPV infection was demonstrated in 18.4% and they are dominant in younger women (aged 25 to 30 years).

Methylation of HPV18, HPV31, and HPV45 genomes and cervical intraepithelial neoplasia grade 3

BACKGROUND

Persistent infections with carcinogenic human papillomavirus (HPV) types are the necessary cause of cervical cancer. We recently demonstrated that the HPV16 genome is strongly methylated in cervical precancer compared with transient infections. However, the extent of methylation in other HPV types and its role in progression to cancer is poorly understood.

METHODS

We analyzed whole-genome methylation patterns of the three next most carcinogenic HPV genotypes: HPV31 (closely related to HPV16), and two other closely related types, HPV18 and HPV45. DNA was extracted from cervical cytology specimens from 92 women with precancer and 96 women infected with HPV31, HPV18, or HPV45, but who had no cytological or histological abnormalities. After bisulfite modification, genome-wide pyrosequencing was performed covering 80-106 sites. We calculated differences in median methylation, odds ratios, areas under the curve, and Spearman rank correlation coefficients for methylation levels between different sites. All statistical tests were two-sided.

RESULTS

For all three HPV types, we observed strongly elevated methylation levels at multiple CpG sites in the E2, L2, and L1 regions among women with cervical intraepithelial neoplasia grade 3 compared with women with transient infections. We observed high correlation of methylation patterns between phylogenetically related types. The highest areas under the curve were 0.81 for HPV31, 0.85 for HPV18, and 0.98 for HPV45. Differential methylation patterns in cervical intraepithelial neoplasia grade 3 patients with multiple infections suggest that methylation can clarify which of the infections is causal.

CONCLUSIONS

Carcinogenic HPV DNA methylation indicates transforming HPV infections. Our findings show that methylation of carcinogenic HPV types is a general phenomenon that warrants development of diagnostic assays.

Does HPV type 16 or 18 prevalence in cervical intraepithelial neoplasia grade 3 lesions vary by age? An important issue for postvaccination surveillance

AIM

We used existing data to investigate whether prevalence of HPV16/18 in cervical intraepithelial neoplasia 3 (CIN3) varies by age, in order to determine whether age specific baseline data is required as the prevaccination comparator for type-specific surveillance following HPV vaccination programs.

MATERIALS & METHODS

We analyzed available Australian HPV typing data from 317 cervical smears from women with concurrent CIN3 on biopsy and conducted a review and analysis of the international literature.

RESULTS

Among 317 women with CIN3, HPV16 was detected in 70% of those 16-25 years old, 59% of 26-35-year-olds and 48% of >36-year-olds (p = 0.025). This association took the form of a trend with decreasing HPV16 prevalence with increasing age (p = 0.007). That HPV16 is commoner in younger women with high-grade cervical lesions was consistent with all but one study of 18 identified in the literature.

CONCLUSION

In screened populations, younger women with CIN3 are more likely to have HPV16 detected. To make valid pre- and post-vaccination comparisons, surveillance specimens for HPV typing should be both age stratified and lesion specific.

HPV16 is associated with younger age in women with cervical intraepithelial neoplasia grade 2 and 3

OBJECTIVE

To evaluate if women with HPV16 positive CIN2 and CIN3 are diagnosed at a younger age.

METHODS

We conducted a population-based cohort study including more than 40,000 women having a liquid based cervical cytology sample taken as part of routine screening. HPV analysis was performed using Hybrid Capture 2 and LiPAv2. The study population was linked to the Danish Pathology Data Bank to retrieve information on subsequent cervical histology. We included HR HPV positive CIN2/3 samples, comprising 173 CIN2 and 467 CIN3 lesions. Due to a high number of multiple concurrent HPV infections, the causative HPV type was assigned to a hierarchically group.

RESULTS

In CIN3, the estimated proportion of lesions positive for HPV16 was 68.1% among women aged 20 years and decreased to 38.9% among women aged 50 years. A decrease in HPV16 positivity with increasing age was also observed in CIN2. In a multinomial logistic regression analysis, young age was strongly associated with HPV16 positivity in CIN3 lesions (OR=0.46 per 10 year increase in age, 95% CI: 0.32-0.65). The proportion of HPV16 and/or 18 positive lesions among women diagnosed with CIN2 and CIN3 below 30 years of age was 44% and 75%, respectively.

CONCLUSIONS

HPV16 positivity was significantly associated with younger age at diagnosis of CIN3. In a population vaccinated against HPV16 and 18, we will experience a shift to older ages in cervical precancerous lesions. These findings may imply that cervical cancer screening programs could start at an older age in HPV vaccinated populations.