A large free-of-charge quadrivalent HPV (qHPV) vaccination program, covering four cohorts annually , has been implemented in Basilicata since 2007. This study evaluated vaccine and non-vaccine HPV prevalence 5-7 years post-vaccination program implementation in vaccinated and unvaccinated women.This population-based, cross-sectional study was conducted in the public screening centers of the Local Health Unit in Matera between 2012 and 2014. Cervical samples were obtained for Pap and HPV testing  and participants completed a sociodemographic and behavioral questionnaire. Detailed HPV vaccination status was retrieved from the official HPV vaccine registry. HPV prevalence was described overall, by type and vaccination status. The association between HPV type-detection and risk/protective factors was studied. Direct vaccine protection (qHPV vaccine effectiveness [VE]), cross-protection, and type-replacement were evaluated in cohorts eligible for vaccination, by analyzing HPV prevalence of vaccine and non-vaccine types according to vaccination status.P <0.001); adjusted VE against vaccine type infections was 90% (95% CI: 73%-96%) for all fully vaccinated women and 100%  in women vaccinated before sexual debut. No statistically significant difference in overall high-risk HPV, high-risk non-vaccine HPV, or any single non-vaccine type prevalence was observed between vaccinated and unvaccinated women.Overall, 2793 women (18-50 years) were included, 1314 of them having been in birth cohorts eligible for the HPV vaccination program (18- to 30-year-old women at enrolment). Among the latter, qHPV vaccine uptake was 59% (at least one dose), with 94% completing the schedule; standardized qHPV type prevalence was 0.6% in vaccinated versus 5.5% in unvaccinated women  contains supplementary material, which is available to authorized users. Genital human papillomavirus (HPV) infection is the most common sexually transmitted viral infection worldwide, with approximately 75% of sexually active men and women exposed to HPV during their lives .HPV types that can infect the genital tract can be categorized as high risk (HR) or low risk (LR) according to the degree of risk associated with the development of cervical cancer. Infection with HR-HPV is found in virtually all cases of cervical cancer and is considered a necessary cause of invasive cervical cancer . Among tIn Italy, cervical cancer is the 15th most frequent cancer overall, and the third most frequent among women aged 15-44 years . Every yLarge randomized controlled trials (RCTs) have shown HPV vaccines to be well tolerated and highly efficacious against vaccine-type persistent HPV infection and precancerous cervical lesions (vaccine efficacy 93% to 100%) , 8. HPV In Basilicata, a region in southern Italy, an organized vaccination program was launched in 2007 with the prophylactic quadrivalent HPV (qHPV) vaccine Gardasil® . A unique multiple-cohort vaccine implementation strategy was used, inviting yearly four birth cohorts  to be vaccinated free of charge in the Local Health Unit (LHU) of Matera. The first cohorts were born in 1996, 1993, 1990, and 1983, respectively. In addition, HPV vaccinations given through this organized program are systematically reported into a computerized vaccination registry. Cervical screening targeting women aged between 25 and 64 years is also well organized in Basilicata, and the adherence rate was on average 57% for 2013 to 2014 .This cross-sectional population-based study aimed to assess vaccine and non-vaccine HPV prevalence 5-7 years post-vaccination program implementation in vaccinated and unvaccinated women.All 15 public screening centers managed by the LHU of Matera took part in the study. These centers used computerized HPV vaccine and screening registries. Between 21 May 2012 and 14 February 2014, all women aged 25-50 years participating in the Basilicata cervical cancer screening program were asked to take part in the study. Women aged 18-24 years, who were not age-eligible for the screening program, were identified from municipality registries and all were also invited by individual letters to participate in the study. Those not yet sexually active, hysterectomized women, and women who had undergone colposcopy in the 24 months prior to the enrolment visit were not eligible for enrolment. Eligible women were enrolled after signing an informed consent form.At the enrolment visit, two cervical samples (one each for Pap and HPV testing) were obtained, and participants completed self-administered sociodemographic and behavioral questionnaires. HPV vaccination history, HPV and cytological data, sociodemographic and behavioral data, including sexual habits and age at first sexual intercourse, were recorded. Detailed individual HPV vaccination status (including date of each vaccination and number of doses received) was also retrieved from the official computerized HPV vaccine registry of the LHU of Matera. This information was used for the statistical analysis. HPV analyses and genotyping were centralized in an accredited laboratory at the Cancer Prevention and Research Institute (ISPO). Quality control of HPV testing, cytology, genotyping, and data input procedures were implemented throughout the study, which was conducted in accordance with the Good Epidemiological Practice guidelines and the principles of the Declaration of Helsinki, and was approved by the Matera LHU ethics committee.HPV detection was performed by Hybrid Capture® 2  using HR-HC2  and LR-HC2  probes with a semi-automated procedure . As recommended by the manufacturer, samples with a relative light units (RLU) to cutoff value (CO) ratio ≥1.0 were classified as HPV positive.Genotyping was performed for all HC2 positive samples , all “borderline” samples (RLU/CO ratio <1 and ≥0.5), and 10% of HC2 negative samples (RLU/CO ratio <0.5) chosen randomly. After DNA extraction , samples were amplified by INNO-LiPA® HPV Genotyping Extra Amp  followed by detection by reverse hybridization with HPV type-specific probes for 28 different HPV types: HPV 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59 ; HPV 26, 53, 66, 68, 70, 73, 82 (classified as “possibly carcinogenic to humans”) and HPV 6, 11, 40, 43, 44, 54, 69, 71, 74 (not classifiable as to its carcinogenicity to humans). Results were interpreted using LiRAS® for LiPA HPV software  followed by manual verification. When the INNO-LiPA test did not exclude the presence of HPV 39, 52, 68, or 56 co-infection, an additional type-specific polymerase chain reaction (PCR) was performed. PCR with specific HPV42 primers was performed on LR-HC2 positive or borderline samples  that were INNO-LiPA negative, as HC2 may detect HPV42 that cannot be detected by INNO-LiPA.www.demo.istat.it) to assess whether the study population was representative of the general female population of Basilicata [Sociodemographic characteristics  collected in the self-administered questionnaire were compared with data from the Italian National Institute of Statistics  were estimated overall, as well as for HR types, HR non-vaccine types, HR vaccine types, LR types, LR non-vaccine types, LR vaccine types, all vaccine types, and all non-vaccine types, as well as by HPV type. The female Italian National Population (1 January 2012 census) was used as the standard population. For women born in cohorts eligible for the HPV vaccination program , overall and type-specific data were stratified by vaccination status.Information on vaccination status, derived from the official computerized Matera LHU vaccine registry, was defined at the date of informed consent. Women who received the first vaccine dose before the date of informed consent were considered as vaccinated (women who received the first vaccine dose at the time of informed consent were considered as unvaccinated). A sensitivity analysis was performed considering as vaccinated only women with a complete vaccination schedule with all three doses administered before the consent date. Age at first sexual intercourse was self-reported and used to identify women who had been vaccinated before sexual debut.P ≤0.1) were included in the multivariate analysis. In the final multivariate logistic regression model, vaccine effectiveness (VE) of a full vaccination schedule was evaluated for the prevention of qHPV vaccine type detection as the complement of the adjusted odds ratio (aOR) of the vaccination status (VE = (1 – aOR)*100), in cohorts eligible to the vaccination program (18- to 30-year-old women). Similar analyses compared HPV prevalence in women vaccinated before sexual debut and unvaccinated women. Due to the low number of women vaccinated before sexual debut in the 25- to 30-year group, these comparisons were restricted to those aged 18-24 years. Statistical analyses were performed using STATA® (version 11 or 12) software .Direct vaccine protection (effect on qHPV vaccine types), cross-protection , and potential type-replacement , HR non-vaccine non-cross-protective types , and each single HR non-vaccine HPV types (provided N >10) were evaluated in cohorts eligible for vaccination, by analyzing HPV prevalence of vaccine and non-vaccine types according to vaccination status. Comparison of standardized HPV prevalence in vaccinated and unvaccinated participants was obtained using a Poisson regression model adjusted for 5-year age groups. The difference between HPV prevalence by 5-year age groups was tested using the chi-squared test. Logistic regression was used to evaluate the relationship between cervical HPV infection and potential risk or protective factors, including vaccination. A univariate analysis was used to identify associations between HPV infection and each potential risk/protective factor. Factors for which an association with HPV infection was found . The proportion of women aged 25-50 years attending for cervical cancer screening who agreed to participate in the study was >98% (1909/1941). Overall, 2793 women were included in the statistical analysis (11 enrolled women were excluded either because sample dates were inconsistent or because samples had not been sent for testing), 894 and 1899 in the 18-24 years and 25- to 50-year groups, respectively.Study population characteristics are described in Additional file P <0.001): 67% in the 18- to 24-year group, and 42% in the 25- to 30-year group , whereas it was near zero among women older than 30 years.Table Among vaccinated women, 38.4% (301/783) had received their first dose before sexual debut. This value reached to ≈50% in the 18- to 24-year group (296/597) and then dropped sharply in the older age group (2.8% for those 25-30 years and 0% for those 31-55 years).Almost all women (94%) who had received at least one dose had gone on to complete the full vaccination schedule of three doses. Schedule completion was higher in women who had been vaccinated before sexual debut, with 97% receiving all three doses.P =0.268) , single 92% vs 71%), with a higher educational level (84% vs 72%), and more frequently unemployed  was 9.5% for all types, 7.6% for HR-HPV types, and 3.2% for LR-HPV types .The overall standardized prevalence of non-vaccine HPV types was 8.0% (4.9% for HR non-vaccine types) and 2.4% for the four qHPV vaccine types combined  (2.3% for HR-qHPV vaccine types) , HR-HPV type prevalence , and LR-HPV type prevalence  (Table P =0.01 in the 18- to 24-year old group) (Table P =0.09)  Table . HR-HPV P <0.001) (Table P <0.001) and LR-qHPV vaccine types . The corresponding adjusted VE against vaccine type infections was 90% (95% CI: 73%-96%). No qHPV vaccine type infections were detected among women vaccinated before sexual debut  was significantly higher in unvaccinated than in vaccinated women  Table . This waP =0.58, and 2.7% vs 1.5%, P =0.30, respectively; Table Even though we observed a higher prevalence point estimate for HPV 31, and HPV 31, 33, and 45 combined in unvaccinated versus vaccinated women, these differences were not statistically significant . Due to this large sample size, the wide age range of women targeted by the vaccination program in Basilicata (11- to 24-year-old women each year), as well as the very good overall adherence to the vaccination program , this region provides a unique setting to evaluate the real-life effect of a well-implemented vaccination program on viral HPV circulation, particularly on HPV types under the selective pressure of qHPV vaccine introduction.This is also the first study analyzing overall HPV and type-specific prevalence in a post-vaccine era in Italy. By performing a comprehensive genotyping assay for surveillance, rather than focusing on HPV 16/18 only, we aimed to gain insights into cross-protection and type-replacement, in addition to vaccine effectiveness, as well as to provide a good baseline to monitor the impact of the possible future introduction of a nonavalent HPV vaccine.A strength of this study was the high quality of the information gathered on individual vaccination status, which was issued from the official computerized vaccine registry of the LHU of Matera ensuring differentiation between vaccinated and unvaccinated individuals and allowing for a robust vaccine effectiveness evaluation. The collection of sociodemographic and behavioral data, using an anonymous questionnaire, is another strength of this study, as well as facilitated adjusted comparisons between vaccinated and unvaccinated women with several confounding factors for HPV infection in multivariate analysis. In particular, the self-declared age at first sexual intercourse allowed differentiation between women vaccinated before sexual debut, who had the potential to fully benefit from the vaccination, and those who were likely to have been exposed to HPV before vaccination.One limitation of the study is the low participation rate (10.8%) of women not age-eligible for the organized screening program (aged 18-24 years). This participation rate, lower than that expected based on previous studies in Italy , 13, wasAnother limitation is that our study was conducted in a post-vaccine era only. In absence of HPV prevalence data collected in a similar manner in a pre-vaccine era , we cannot fully assess the impact of the vaccine program introduction. Nevertheless, our data seem overall consistent with HPV prevalence data observed in pre-vaccine eras elsewhere in Italy. For example, the HPV prevalences observed in 2007 in a screened population aged 25-65 years living in central and southern Italy  were verOur population had a high prevalence of HPV42. It is important to note that most prevalence studies in Italy did not genotype LR types or the genotype systems used did not detect HPV 42. In the present study, all genotyping analyses were performed by INNO-LiPA Genotyping Extra, which is not able to detect HPV 42, one of the LR-HPV HC2 target types. Consequently, we evaluated HPV 42 prevalence by type-specific PCR, for all LR-HC2 positive samples that were negative for specific HPV genotypes as detected by INNO-LiPA. This may explain why the prevalence of HPV 42 is so high in our study.The high prevalence of HPV infection in the youngest age groups and decreasing HPV prevalence with increasing age was expected from HPV natural history –18. StilIn our study, VE against qHPV vaccine types was 90% considering all vaccinated women (18-30 years), regardless of sexual exposure at the time of vaccination. These figures are close to those observed by Tabrizi , with a Although not statistically significant, lower HPV prevalence point estimates of HPV 31, 33, and 45 were observed in vaccinated versus unvaccinated women, suggesting that the qHPV vaccine might provide some degree of cross-protection against non-vaccine HPV types. This seems in line with evidence from other clinical –26 and oP =0.03) [Vaccination is expected to reduce the prevalence of HPV vaccine types, but there is a theoretical concern that vaccine introduction may affect the distribution of other oncogenic types and induce type-replacement . SimilarP =0.03) . A recenP =0.03)  shows a P =0.03) . This fi“Unmasking,” a potential diagnostic artifact of broad-spectrum assays, may give rise to an apparent increase in non-vaccine types following vaccination , 32, and“Unmasking” should be differentiated from type-replacement. It is equally important to evaluate the test used and ensure that it performs adequately. The World Health Organization HPV LabNet provides blinded “proficiency panels” designed to evaluate whether assays can detect a monoinfection equally well in the presence of other HPV types. Comparison of results from more than 100 laboratories worldwide that have used a variety of HPV assays has shown that underestimation of some HPV types, when other types are present in the same sample, is a problem for some assays , 34. In The results of our study will be an important basis for the evaluation of future changes in the epidemiology of HPV infection in Italy, particularly in view of the upcoming 9-valent HPV vaccine that protects against five additional oncogenic HPV types . OngoingThe results of this study, conducted shortly after the implementation of the qHPV vaccination program in Basilicata, provide insight into the real-life population effect of HPV vaccination programs in those 18-50 years. They show a high VE of the qHPV vaccine on vaccine type prevalence, and found no evidence of type-replacement. This effectiveness is expected to be even more important in young girls who are HPV naive at vaccination, and will be examined in the routine cohort of 12-/13-year-olds, in whom vaccine uptake is higher and who will attend their first cervical screening visit in 2021.


Pseudomonas stutzeri, Bacteroides fragilis, Lactobacillus delbrueckii, Atopobium vaginae, and Streptococcus agalactiae mediated by HPV infection on CIN status were observed. The directions of the direct and the indirect associations between CIN status and Ps. stutzeri were opposite. The directions of the direct and the indirect associations between CIN status and A. vaginae were the same. B. fragilis, L. delbrueckii, and S. agalactiae only had indirect association with CIN status. In summary, our study provided suggestive evidence that some microbial populations could have direct or indirect effects mediated by affecting HPV infection on CIN progression. Besides HPV infection, microbial community composition possibly plays a role in cervical carcinogenesis.Cervical microbiota composition is associated with cervical HPV infection and CIN severity. Previous studies only assessed the total association between cervical microbiota and HPV infections or CINs, and yet no study reported the direct and indirect associations between cervical microbiota and CINs mediated by HPV infection, respectively. The aim of this study was to investigate the direct and indirect associations between microbiotas and CIN severity. Cervical microbiota of 126 women with CIN 1−  and 40 with CIN 2+ (CIN 2 and CIN 3) were analyzed using Illumina sequencing based on the 16S rRNA gene. HPV was detected using a highly sensitive PCR primer set (SPF1/GP6+). Indirect effects of  Human papillomavirus (HPV) infection has been recognized as an important cause of cervical precancerous lesions or cancer, and yet is necessary but not sufficient for cervical carcinogenesis process Some studies have demonstrated that cervical microbiota composition was associated with the acquisition, reactivation, or delayed clearance of cervical HPV infection and even CIN severity In this study, we enrolled participants with CIN and normal cervical epithelium in order to investigate the direct and indirect associations between microbiotas and CIN severity.n = 64], CIN 1 [n = 62]) and CIN 2+ (including CIN 2 [n = 19] and CIN 3 [n = 21]) from Beijing Cancer Hospital, Beijing, China, between 2014 and 2015. All biopsy specimens were reviewed by two experienced pathologists who confirmed the diagnosis of CIN. Individual informed consents had been collected from all participants. This study received ethical approval from the Institutional Review Board of the Peking University School of Oncology, China, and the study was carried out in accordance with approved guidelines.A total of 166 cervical biopsy specimens were collected and diagnosed with CIN 1−  following the manufacturer's instructions. All 166 specimens were used to determine microbiota composition and the 36 HPV‐positive specimens were used to identify HPV integrations.HPV DNA was detected using a highly sensitive PCR primer set (SPF1/GP6+) amplifying a 184‐bp fragment of the L1 open reading frame PCR was used with unique barcoded primers to amplify the variable region V3–V4 of the 16S rRNA gene to create an amplicon library from cervical samples The amplicon library was sequenced on an Illumina HiSeq 2500 platform  and 250 bp paired‐end reads were generated. The raw sequences were sorted using their unique barcodes, truncated by cutting off the barcode and primer sequence, and low‐quality reads were removed α = 0.05 and LDA = 2.0 Alpha diversity metrics  according to CIN status were evaluated by Wilcoxon rank sum test. Principal coordinates analysis (PCoA) of weighted UniFrac metrics (beta diversity metrics) were used to visualize difference in microbial community according to CIN status. Hierarchical clustering  was performed based on the 18 most abundant species. Linear discriminate analysis effect size (LEfSe) was used to detect the differences in the 18 most abundant species according to the HPV infection and CIN status using the default values of P values reported were two‐sided and considered significant if they were <0.05. Statistical analyses were conducted using Stata 11.0 .Raw sequencing data were submitted to the Sequence Read Archive (study accession number PRJNA319915).n = 8), HPV18 (n = 2), and HPV58 (n = 3); two samples harbored two types of HPV . Of the 21 HPV‐positive CIN 2+ samples, we detected HPV16 (n = 15), HPV33 (n = 2), and HPV58 (n = 2); two samples harbored two types of HPV .As shown in Table Firmicutes, Actinobacteria, and Proteobacteria were the three dominant phyla . L. crispatus, S. agalactiae, B. fragilis, and Campylobacter ureolyticus were more abundant in samples obtained from CIN 2+ cases. Higher abundance of Photobacterium damselae, L. jensenii, and A. vaginae was detected in CIN 1− samples.LEfSe analyses evaluating microbial species discriminating on HPV infection or CIN status are shown in Figure Ps. stutzeri, B. fragilis, L. delbrueckii, A. vaginae, and S. agalactiae mediated by HPV infection on CIN status were observed. The directions of the direct and the indirect associations between CIN status and Ps. stutzeri were opposite. The directions of the direct and the indirect associations between CIN status and A. vaginae were the same. B. fragilis, L. delbrueckii, and S. agalactiae only had indirect association with CIN status.To further evaluate the direct and indirect effect of cervical microbiota on CIN status, we categorized each microbiota into three groups  according to the p25 and p75 quartiles of each microbiota. Table L. iners and L. crispatus were the predominant cervical microbiota in most participating women. Some cervical microbiota not only had the direct associations with CIN severity, but also had indirect effect on CIN severity mediated by affecting HPV infection status. The directions of the direct and indirect associations between CIN status and cervical microbiota could be the same or opposite.Our study found that Lactobacillus iners and Lactobacillus crispatus were the predominant cervical microbiotas in most of the participating women. These two species were also dominant in previous studies in Asian women and yet their relative abundance in our study was lower than those reported previously L. jensenii and L. crispatus were found in CIN 2+ and CIN 1− samples, respectively; while we did not observe the association between L. iners and CIN severity. Although cervical Lactobacillus spp. are dominant and maintain a low pH by producing lactic acid in most women, different species could play distinctive roles in cervical carcinogenesis process Lactobacillus spp., we also found some other microbes with high abundance in CIN 1− and CIN 2+ groups, respectively. More importantly, we found indirect associations between cervical microbiotas and CINs mediated by affecting HPV infection status and moreover directions of the direct and indirect associations could be the same or opposite in different microbes, indicating that the variation of microbiota composition could directly affect cervical carcinogenesis process and with indirect effect mediated by HPV infection. Although many studies have elucidated the host‐commensal microbiota interaction in gastrointestinal tract and to some extent in pelvic inflammatory diseases and pregnancy complications In this study, high abundance of However, there are some limitations in our study. First, the associations between CIN severity and the microbial community were not adjusted for other risk factors due to unavailability of demographic characteristics. Second, the cross‐sectional study did not investigate the temporal relationship between cervical microbiotas and CINs. Third, we did not clarify the mechanism of interplay between cervical microbiotas and HPV infection for cervical carcinogenesis in this study. Fourth, as sample size was small and moreover site of sampling is at the location of CIN but not entire cervix, the proportion of HPV infection in our individuals could be underestimated. Fifth, as the HPV‐positive sample size is small, we would enroll more individuals to validate our study findings in the near future. Sixth, although HPV DNA was detected using a highly sensitive PCR primer set (SPF1/GP6+) amplifying a 184‐bp fragment of the L1 open reading frame, this assay might also underestimate the proportion of some type HPV infection.In summary, our study provided suggestive evidence that some microbial populations could have direct or indirect effects mediated by affecting HPV infection on CIN progression. Besides HPV infection, microbial community composition possibly plays a role in cervical carcinogenesis.The authors have no conflict of interest.Figure S1. Distribution of cervical microbiota community types at the phylum level among the 166 participants.Click here for additional data file.Figure S2. Distribution of cervical microbiota community types at the genus level among the 166 participants.Click here for additional data file.Figure S3. Differences in the 18 most abundant species according to the four community types.Click here for additional data file.Table S1. HPV dristibution in CIN1− and CIN2+ casesa.Table S2. The associations between cervical mucosa community type and CIN or HPV status among 166 women in China.Click here for additional data file. Click here for additional data file.


To identify new personal biomarkers for the improved diagnosis, prognosis and biological follow-up of human papillomavirus (HPV)-associated carcinomas, we developed a generic and comprehensive Capture-HPV method followed by Next Generation Sequencing (NGS). Starting from biopsies or circulating DNA samples, this Capture-NGS approach rapidly identifies the HPV genotype, HPV status , the viral-host DNA junctions and the associated genome rearrangements. This analysis of 72 cervical carcinomas identified five HPV signatures. The first two signatures contain two hybrid chromosomal–HPV junctions whose orientations are co-linear (2J-COL) or non-linear (2J-NL), revealing two modes of viral integration associated with chromosomal deletion or amplification events, respectively. The third and fourth signatures exhibit 3–12 hybrid junctions, either clustered in one locus (MJ-CL) or scattered at distinct loci (MJ-SC) while the fifth signature consists of episomal HPV genomes (EPI). Cross analyses between the HPV signatures and the clinical and virological data reveal unexpected biased representation with respect to the HPV genotype, patient age and disease outcome, suggesting functional relevance(s) of this new classification. Overall, our findings establish a facile and comprehensive rational approach for the molecular detection of any HPV-associated carcinoma and definitive personalised sequence information to develop sensitive and specific biomarkers for each patient. Upon persistent, long-term infections of the cervical mucosa, oncogenic HPVs can cause high-grade cervical intraepithelial neoplasias (CINs), that without ablative treatment, may develop into invasive carcinomas.3 Better understanding of HPV biology has permitted major advances in the development of prophylactic vaccines and in the detection of HPV-associated diseases. However, cervical carcinomas remain frequent worldwide and their prognosis is poor, particularly in advanced stages and in cases of relapse.5 Notably, the efficiency of surgical removal of tumour relapses is related to the tumour size.6 It is thus of major importance to acquire molecular biomarkers that will facilitate the early diagnosis of cervical cancer, the detection of precocious tumour relapses and offer optimal biological follow-ups of the disease, upon and after treatment. Therefore, efforts to facilitate the diagnosis of HPV-associated cancers, elucidate the mechanisms driving HPV oncogenicity and develop cost-efficient and precise monitoring tools to improve clinical oncology, are needed.Each year, >500,000 individuals are diagnosed worldwide with human papillomavirus (HPV) associated cancers.7 among which the HPV16 and HPV18 genotypes are the most prevalent.8–11 Viral oncogenicity is largely related to their encoded E6 and E7 proteins, which have the ability to interact and inhibit the host tumour suppressors, p53 and pRB, as well as many other cellular protein targets.12 In CIN cases, the HPV DNA generally replicates extrachromosomally in the cell nucleus, whereas in most invasive carcinomas, a portion of the viral DNA is stably integrated into a unique site or perhaps within a few sites in the tumour cell genome.13–20 Upon integration, there is often a disruption of the E1/E2 genes, which causes constitutive expression of the E6/E7 oncoproteins. Viral integration may also lead to structural and/or modified expression of cellular genes nearby, as well as genomic amplifications, encompassing the HPV insertion site that may have a role in tumour progression.21–24 Along this line, the viral–cellular host junctions represent highly specific molecular markers of the individual patient tumours.25 However, PCR-based approaches used for junction analysis26 are difficult to implement in clinical oncology, notably due to a high rate of inconclusive and false-negative results.23 Most recently, a few genome-wide studies based on Next-Generation Sequencing (NGS) techniques such as whole genome, exome and targeted capture as well as RNA sequencing27 have been reported. However, these approaches remain limited and/or are difficult to implement in clinical practice, owing to technical complexities, biases towards certain HPV types, thresholds of bioinformatic filtering and/or cost efficiencies.At the molecular level, HPV contains a 7.8-kbp double-stranded DNA circular genome . One majHere we describe a sensitive and exhaustive double-Capture HPV method, followed by NGS, designed to determine any HPV genotype and to detect cellular integration sites in HPV-associated carcinomas. This approach has been validated from a panel of 72 cervical patient cases, using tumour biopsy and circulating DNA from blood samples. Surprisingly, our patient-to-patient analysis of the junction reads identified five cellular HPV status whose signatures reveal new insights into the mechanisms of HPV integration and concomitant formation of large deletions or duplications at the insertion sites. Furthermore, these distinct HPV integration signatures prove to be relevant, both biologically and clinically.−6 ratio). The probes were designed to detect the entire length of the HPV genomes from >200 HPV genotypes or variants, allowing an exhaustive and unbiased method to capture any chromosomally integrated, or episomally non-integrated HPV DNA sequence. The HPV-enriched DNA library was then sequenced to obtain single-end long reads (~500 nt average length) using Roche 454 Life Sciences  Junior or paired-end reads (2×150 nucleotides (nts)) using Illumina MiSeq . These read lengths allowed the characterisation of the HPV type and of the insertion junctions. In 2 out of the 50 HPV-integrated samples (#83 and 202), one of the HPV–chromosomal junction was unambiguously mapped but the second junction read could not be definitively oriented as it overlapped a repetitive region of the human genome. To be noticed, as a proof of concept workflow, we successfully performed barcoded multiplexing of up to 7 and 12 patient DNA samples at once for the Roche 454- and Illumina MiSeq-sequenced samples, respectively. The NGS captured reads were subsequently aligned against all of the prototypical HPV genotypes, as well as the hg19 human reference and analysed using standard mapping algorithms, compiled into a dedicated pipeline  of HPV viral integration  per tumour in 30/70 cases, indicating a simple integration pattern of a truncated viral genome into a single chromosomal locus . Most inegration .The above case studies utilised DNA from biopsy samples, allowing the identification of pertinent personalised genomic biomarkers. However, a tumour biopsy is an invasive procedure as compared with taking a blood sample. For the same reason, the analysis of circulating tumour DNA (ct-DNA) samples would also be preferable for the optimal follow-up of patients during and after treatment. Therefore, we investigated whether our Capture-HPV method could also detect the HPV integration signature biomarkers from blood samples. We analysed the ctDNA  of serum specimens taken at the time of diagnosis in five patients in which the 2J-COL , 2J-NL  and MJ-CL (case 29) signatures had been found, respectively. Capture-HPV from serum/plasma specimens was conducted as for biopsies  and yielded numerous HPV and viral–human hybrid NGS reads. Most importantly, the same viral-junction patterns were identified in the blood and tumour samples from each patient . FurtherGAPDH, KLK3 and RAB7A) captured in the same tube of probes . As illustrated in R2=0.93 and R2=0.87 for the 454 and Illumina sequenced samples, respectively). Also, the quantitative analyses of the reads led us to observe a positive correlation between the integration signature pattern and the absolute number of purely viral reads detected (R2=0.61). The lowest number of reads  was observed in cases with two junctions (2J-COL and 2J-NL), and increases  in tumours with multiple junctions (MJ-CL and MJ-SC). The highest number of reads  was observed in the EPI cases, a feature indicating a high copy episomal HPV content, consistent with the high viral load also detected by quantitative PCR . In the second case (No. 3), a 196.5-kb deletion is located near the ZBTB18 and C1ORF100 genes (1q44). Finally in the third case (No. 5) we found a 351.8-kb deletion leading to the partial deletion of both the MAPK10 and PTPN13 genes (4q21.3). Among the remaining cases in the 2J-COL category, we detected two additional deletion cases  as well as flat CGH profile cases  and one flat profile, bordering on a chromosomal amplification (208), consistent with the observation that the interval between the breakpoint is small (1–6 nts) and the deletion event is not detectable by CGH  up to 402.4 kb No. 1; . Remarkae by CGH .In sharp contrast, most 2J-NL events (15/17) exhibited a 1.5 to 4-fold increase of chromosomal copy number between the two HPV-cellular junctions . In the 27 but to our knowledge, this is the first comprehensive analysis integrating the relative architecture of the two junctions in individual tumours and the detection of a deletion pattern arising from HPV integration. In contrast, to the usually large amplification events that are likely to affect several adjacent genes, the small size of the associated deletions are more likely to yield a single-gene dysfunction, more amenable for the design of precision therapeutics.Overall, the cases within the 2J-COL category share, as a common structural feature, the deletion of the chromosomal region within the interval of the two breakpoints. In contrast, the 2J-NL and MJ categories only show local amplifications. Amplification events at the HPV insertion locus have been previously described,30 Herein, we identified 175 robust viral–chromosomal sequence fusions (KLF5/KLF12 locus (five cases), and near MYC (three cases). Among the genes not previously reported in the literature as directly targeted by HPV integration, we found RB1, AKT3, SST and ID1, implied in the regulation of cell proliferation, LPP in cell adhesion/motility, transcription factors such as AFF3, BCL6, CCAT1 and CCAT2, and oncogenes such as RAB11A and RAB22A , histology and clinical staging (I-IV). In contrast, a strikingly unbalanced distribution of HPV genotypes was observed according to the integration signatures. Unexpectedly, a majority (11/18) of the HPV18 associated cases were found in the 2J-NL group whereas only three of the most prevalent HPV16 genotypes  exhibited this signature . In thisP=0.264; 2J-NL versus EPI, P=0.099; MJ-CL versus EPI, P=0.185; and MJ-SC versus EPI, 0.959) and between all the integrated versus EPI, the P value is 0.12. Finally, follow-up data recorded at least 6 months after diagnosis were available for 58 cervical cancer patients. Half were either deceased (14/29), diagnosed with pelvic relapse (10/29) or metastasis (3/29). By comparing the HPV signatures with the disease outcomes, we noted that a poor outcome was more frequently recorded in tumours from the 2J category (17/24) than in the EPI (9/17) and MJ (5/17) categories , rapid (few days without the need to reiterate PCR attempts), technically relatively simple for a molecular biologist, and is therefore able to be implemented today in clinical settings, with the benefits of providing in one experiment: (i) the capture of any HPV genotype regardless of its prevalence in the population, (ii) its full sequence identity by the de novo assembly of the NGS reads, (iii) the viral load assessment as measured by the read coverage normalised against house keeping gene(s) included in the capture probes, (iv) the physical status, integrated or episomal of the viral sequences, (vi) the pattern of integration into the diverse chromosomal insertion sites, (vii) the sequence of the hybrid viral–chromosomal junctions that provide exquisitely specific biomarkers, as well as (viii) the nature and coordinates of the associated chromosomal deletions or amplifications. This method also provides insights into the tumour biology and potential therapeutic opportunities to treat HPV-associated cancers, by characterizing the status of the HPV E6/E7 oncogenes and their E1/E2 repressor as well as all other possible viral rearrangements and the identification of the gene(s) that are directly or indirectly altered via HPV insertion.Compared with PCR-based methods for HPV typing, the comprehensive Capture-HPV approach is unbiased and able to provide single-nucleotide level information, as deep genome-wide based-sequencing approaches, provide.17 Integration of HPV16 DNA was observed in 78.8% of their cases, which correlates well with the 71.4% cases of integration found in our series, collected in two French hospitals. In comparison with previous approaches, one of the assets of Capt-HPV is the incorporation of a large set of probes representing >200 HPV genotypes and variants that allowed us to detect and identify all HPV sequences, including those of various worldwide geographic prevalences such as HPV16, HPV18 and HPV45 in America, HPV45 and HPV33 in Africa or HPV52 in Eastern Asia,29 as well as their status of integration. Furthermore, our case-by-case analysis of the HPV sequences led us to identify 5 HPV signatures distinguished by the relative orientation of the hybrid viral–cellular junctions (2J-COL versus 2J-NL), the proximity of HPV breakpoints in the 2J-COL category and their larger spacing in 2J-NL, the multiplicity of junction reads in certain tumours  and finally the presence of the viral genome in the episomal state only (EPI). Remarkably, the distinction between the 2J-COL and 2J-NL integration patterns was independently validated by two characteristic genomic alterations found at their respective loci, namely deletions (2J-COL) or amplifications (2J-NL). These correlated features can be simultaneously explained by two modes of integration. In the first mode, the two ends of the linearised intact gapped viral DNA align to the host target, such that by ‘ends-out’ replacement, the virus is inserted creating a deletion of the intervening chromosome segment, explaining the formation of the 2J-COL architecture / amplification(s) at the target sequence. In our seventeen 2J-NL cases, the length of the amplified regions varies from ten to several hundreds of kilobase pairs. This can be explained by the variable efficiency of gap repair synthesis, as observed in other assays in yeast and mammalian cell cultures.32 The limited homology we observed at the final viral–chromosomal junctions , but since the presence of an episomal form of HPV is likely to be a prerequisite for integration, it is likely that the integrated versus episomal status is important, as a marker of oncogenicity levels that govern the length of time of neoplasias at their intraepithelial stages, before invasion develops. Oncogenicity could also influence the outcome of invasive carcinomas. We noticed in our case panel, that the rate of relapses was higher in tumours with a simple integration pattern, harbouring only two junctions than in cases with multiple viral insertions or with no insertions, developed in older women, an observation in line with the poor outcomes reported in tumours developed in younger women.34 To test the robustness of the above mechanistic/clinical analyses, and comprehensively explore the significance of the multi-parametric genomic and functional diversity of the HPV virus, extended series of cervical HPV-associated cancers examined as reported here are warranted.To estimate the impact of our HPV tumour classification system, we analysed the available patient clinical and biological data. The first unexpected finding was that, within the 2J-NL category, the majority (11/17) of the HPV18-associated cases were found in this group, whereas only 3/21 of the highly prevalent HPV16 genotype  exhibited this signature . Also, n35 Collectively, the deep molecular analysis of viral-associated alterations nearby integration sites and genome-wide identification of candidate gene mutations should help the stratification of patients for innovative therapies in cervical cancer, targeting cellular genes37 or viral sequences.39 It should also be stressed that our approach allows the primary detection of any HPV-associated carcinoma using a simple blood test, an alternative method when detection of gynaecological cancers is difficult to implement. Another perspective will be to validate prospectively the potential value of this approach for the triage of cervical intraepithelial neoplasias at risk of progression. Finally, beyond cervical tumours, the present Capture-HPV approach is likely applicable to diagnose other HPV-associated cancers, such as head and neck carcinomas in which the proportion of HPV is increasing40 and is also applicable for detecting other viral-associated tumours or the movement of mobile elements in genomes.Altogether, our data sheds light on several key aspects of HPV-associated tumours from biopsy and ct-DNA samples, allowing new perspectives in clinical oncology. Most importantly, the optimal molecular characterisation of the associated HPV junction sequences by Capture-NGS will provide in 1–2 weeks the specific DNA biomarkers for the patient biological follow-up, during and after treatment, an approach that has recently demonstrated its interest in the follow-up of patients with breast cancers.DNA from 72 frozen biopsy cervical tissue samples were taken from patients diagnosed with SCC (squamous cell carcinomas), AC (adenocarcinomas) or AS (adenosquamous carcinomas). The patients were diagnosed in France, at the Institut Curie hospital in Paris  or Saint Cloud  and the Centre François Baclesse in Caen . The DNA samples were provided by the Biological Resource Center at the Institute Curie (AFNOR certification No. 2009/33837b). In accordance with French regulations, the patients were informed of the research performed on tissue specimens and did not express opposition. The FIGO stage and size of tumours were determined for each patient, with the average female age of 48 and with all tumour stages represented .hg19) genome.Single-stranded biotinylated probes were designed with Roche NimbleGen , in which over 22,000 individual and unique sequences, with an average probe length of 75 nucleotides, were synthesised to recognise 235 unique HPV types and variants, containing over 84 different low, medium, high-risk and even non-risk HPV’s. The list of sequences used for the NimbleGen SeqCap EZ design of these biotinylated probes is shown in 20 is to increase the specificity of the capture and enrich the fraction of relevant reads for subsequent bioinformatic analysis. DNA sequences captured by streptavidin were analysed using Roche 454 (GS Junior sequencing system) for patient cases 1–46, and Illumina MiSeq instruments, for the remaining 26 cases. Library samples were multiplexed, using one biotinylated HPV oligonucleotide probe set per 6 or 7 library samples. Single-end 454 shotgun reads were obtained, with an average length of about 500 nucleotides, allowing for easily identifiable viral-cellular junction reads, as well as purely viral reads, used for genotyping. The Illumina paired-end MiqSeq reads are 2×150 nt. Contig assemblies were also performed, using the Newbler software allowing for the full HPV integration status . The sequencing parameters of each sample is provided in Two hundred to 500 ng of DNA were used for each patient sample for subsequent DNA library preparation. The DNA libraries are prepared by nebulising, which shears the DNA mechanically and randomly with nitrogen, polishing the double-stranded DNA ends and T/A cloning of adapters, containing unique barcodes for each sample. This is followed by the Double Capture system, using the SeqCap EZ Rapid Library Small Target Capture method, developed by Roche. This is adapted to enrich for and capture small DNA targets, in which the DNA library samples are hybridised, two successive times, with the target HPV oligonucleotide probes. The expected technical advantage of this double capture method versus a single captureThe ct-DNA was prepared from 200 μl of serum collected from a patient blood sample at the time of diagnosis, using the QIAamp viral DNA  enrichment and blood kits. No sonication was performed before library preparation. The size profiles of the library DNA fragments were controlled on a Bioanalyzer before and after adaptor ligation. Fragments between 150 to 500 bps were purified and used for the subsequent Capture steps, performed as for the biopsy tumour samples described above.http://bioinf.comav.upv.es/sff_extract/). All tools used thereafter were obtained from the Galaxy interface, at the Insitut Curie, whose development is based on a similar interface, available at  and is shown in Raw sequence data reads were obtained as either sff (binary) or fna (txt) formatted files. The sff files were converted into fastq files, using a python script: sff_extract 0.3.0 (http://pave.niaid.nih.gov/). Next, we used the Bowtie 2 tool from Galaxy set at default parameters, with an ‘end-to-end’ mode of global alignment. The alignment (SAM file) is visualised using Tablet (http://bioinf.scri.ac.uk/tablet/). In this manner, we identify the HPV type of the sample, as Tablet displays the number of reads that are aligned against each of the 37 different HPV reference viral genomes.We began by analysing the genotype of the sample. First, all of the sff reads were converted to fastq reads, that we aligned against a reference fasta file, containing 37 HPV low, medium and high-risk reference HPV genomes, obtained from the NIH PaVE website . We remove PCR-duplicates using the ‘Mark Duplicate reads’ Picard tool on the BAM file, to obtain unique, yet overlapping reads. We then convert the BAM into SAM files and filter all unaligned reads (using SAM tools).hg19 reference using the blat tool (http://genome.ucsc.edu), to identify the precise insertion site of the virus in the human genome.The alignment with Tablet easily reveals simple  from multiple viral insertion cases. For such 2J cases, the alignment of reads against the reference viral strain, allows the identification of non-pure HPV reads, or viral–host junctions, that do not entirely align against the viral reference genome. This alignment also shows the portion of the viral genome that is deleted upon integration. The CIGAR code is used to confirm the alignment ends of each NGS read at precise positions that contain an additional sequence, not aligned against HPV ('S' flag). In this manner, we obtain the non HPV portion of these reads that align against the hg19 reference sequence. After removing PCR duplicates and unaligned reads, the Galaxy tool, ‘Compare Two Data Sets’, is used and allows comparison between two data sets. Thus, by comparing both SAM files (HPV and Human) we find the common read names that are partially aligned on both HPV and human sequences, that we call hybrid reads. As before, we visualise the SAM files in Tablet, with clearly visible viral-host breakpoints.Alternatively, if a deleted or gapped region in the Tablet alignment is not detected, then we implement a filter to remove all purely viral reads and to highlight only viral–host junction reads. For this, we performed two local read alignments: the first against the HPV reference and the second against the hg19 reference genome and HPV Pave website, for reference HPV genomes. Fifty- to 55-nt sequences overlapping the viral–cellular breakpoints were aligned, resulting in 5 up to 24 nts of gapped sequence identity either at or surrounding the breakpoint, within the entirely aligned sequence  was used as input and the following default parameters were used as following: minimum read length 20; minimum overlap length 40; minimum overlap identity; 90%.We performed a hg19 (with the BLAT tool). This allowed us to confirm junctions that we identified previously, from single reads and confirm our integration breakpoints obtained from our single reads. Indeed, for most of the 2J cases, Newbler was able to assemble one or two long contigs, encompassing both the 5′ and 3′ flanking viral–human breakpoints, as well as the entire integrated viral sequence.The output fna file, containing all of the contig sequences were aligned against the HPV genome. Then, the non-HPV portion of the contig was identified by aligning on 26The DIPS-PCR (Detection of integrated papillomavirus sequences) method, followed by Sanger sequencing was performed on all samples, to validate our NGS identified junctions using the Capture-HPV-NGS method, as described previously.8 by quantitative PCR, in which the HPV E7 gene is quantified relative to the reference PSA gene (2 copies of DNA per cell) using quantitative PCR (Sybr Green PCR Core Reagents). The viral charge is obtained using the formula CV=2−ΔCt×2. Differently, the HPV viral load was measured from the capture NGS results, by counting and comparing the nucleotide coverage of the HPV sequences and those of the three control house-keeping genes, included in the same tube as the HPV capture probes. These three unique genes  with a size (6–11 kb each) comparable to the HPV were captured with a total of ~3,000 copy-number control probes. The estimated viral load was determined by the ratio of HPV versus control gene read coverage, normalised per nucleotide. Correlation between these methods is shown in HPV viral loads were determined in two ways. First, as previously described,41 Frequency of Amplicon, Gain and Loss (FrAGL) was performed on the bioinformatics platform  of the Institut Curie.All samples  were analysed at the Genetic platform at the Institut Curie, using the Genome-Wide Human CytoScan HD Array from Affymetrix, for comprehensive whole-genome coverage of DNA from cervical biopsy samples . Analysis was performed using the Chromosome Analysis Suite software (ChAS) version 3.0 (Affymetrix), as well as the Genome Alteration Print (GAP) software, developed at the Institut Curie.


Objective: To assess, among parents of predominantly minority, low-income adolescent girls who had either not initiated (NI) or not completed (NC) the HPV vaccine series, attitudes and other factors important in promoting the series, and whether attitudes differed by language preference. Design/Methods: From August 2013–October 2013, we conducted a mail survey among parents of girls aged 12–15 years randomly selected from administrative data in a Denver safety net system; 400 parents from each group (NI and NC) were targeted. Surveys were in English or Spanish. Results: The response rate was 37% . Safety attitudes of NIs and NCs differed, with 40% NIs vs. 14% NCs reporting they thought HPV vaccine was unsafe (p < 0.0001) and 43% NIs vs. 21% NCs that it may cause long-term health problems (p < 0.001). Among NCs, 42% reported they did not know their daughter needed more shots  and 39% reported that “I wasn’t worried about the safety of the HPV vaccine before, but now I am” . Items rated as very important among NIs in the decision regarding vaccination included: more information about safety (74%), more information saying it prevents cancer (70%), and if they knew HPV was spread mainly by sexual contact (61%). Conclusions: Safety concerns, being unaware of the need for multiple doses, and low perceived risk of infection remain significant barriers to HPV vaccination for at-risk adolescents. Some parents’ safety concerns do not appear until initial vaccination. Attitudinal and logistical factors were identified early on as barriers to human papillomavirus (HPV) vaccination and, despite more than a decade of vaccine availability and recommendation, these barriers persist . In studWhile barriers to HPV vaccine have been explored, there remain unanswered questions. There have been relatively few studies among parents who had actually declined or delayed vaccination. Also, no prior studies have specifically examined differences in the perspectives of those parents whose daughters had not initiated the series versus those who did not complete it. Moreover, there may be important differences in attitudes about the vaccine by ethnicity and language ,5 that hWe conducted a cross-sectional survey among parents of adolescent girls in a large safety net system in Denver, Colorado ). The Colorado Multiple Institutional Review Board (COMIRB) approved this study. From August to October 2013, a mail survey was conducted among parents of girls aged 12–15 years randomly selected from administrative data in the DH system. DH serves a population of >17,000 adolescents annually that is predominantly Hispanic, and approximately 40% of the total patient population identify Spanish as their primary language. In 2013, at the time of the study, HPV coverage of ≥1 dose in 13–17 years old girls was 89.8% and coverage for ≥3 doses was 66.8%. The population of girls age 12–15 at the time of the study was 6848. From this population, random samples of 400 parents of girls who were identified as not having received any HPV vaccine doses (non-initiators) and 400 parents of girls who had started but not completed the HPV vaccine series (non-completers) were targeted based on information from the electronic health record. Non-initiators were adolescents with a well-child visit within the previous 2 years but no record of an HPV vaccine in DH administrative data or the state immunization registry. Non-completers were adolescents who had received 1–2 HPV vaccines within the previous 2 years with no record of a 2nd or 3rd dose within 6 or 12 months of the first dose, respectively (or record of subsequent completion of the series). These cutoffs were chosen based on discussions of the study team with CDC (Centers for Disease Control and Prevention) and Denver Health collaborators.Denver Health has its own immunization registry, VaxTracks, that has been shown to be highly accurate . There aThe survey was in English or Spanish based on language of preference recorded in the medical record. The language of record is what is used for all DH communications. The survey was based on a combination of qualitative work performed by the study group within the same study population  and stanParents of non-initiators (n = 400) and non-completers (n = 400) were mailed a pre-letter followed by the survey two weeks later. Non-respondents were sent a reminder postcard and up to two additional surveys over a two-week period. All surveys included cover letters describing that the survey was regarding HPV vaccine and sought to understand their thoughts about HPV vaccine to better understand how parents make decisions above HPV vaccination for their daughters. There were up to two reminder phone calls to non-respondents from a physician within DH recorded in English and Spanish. A $5 bill was included in the initial survey mailing. For surveys that were returned as undeliverable, the study team contacted staff at DH to identify those patients who had moved or gone elsewhere (MOGE) and if confirmed as unreachable, were then removed from the sample. For those undeliverable surveys not identified as MOGE, an Internet search was performed to determine new addresses if available . Initially, 154 surveys were returned as undeliverable or identified by DH staff as MOGE and were searched using Intellius. This search yielded 33 new addresses, and of these, 19 surveys were again returned as undeliverable and 14 surveys were successfully delivered. These 14 were included in the final analysis and the remainder (n = 140) classified as MOGE.Chi-squared test of proportions or Fisher’s Exact test were used for comparisons of characteristics of respondents and non-respondents. When results regarding attitudes were stratified into non-initiators and non-completers, this was based on self-reported vaccination status rather than electronic data, as we hypothesized that parental perception of vaccination status was more relevant to attitudinal responses than actual vaccination status. Results stratified by electronic data are available in an online The overall response rate was 37% . Respondents were similar to non-respondents in terms of age of the child and language preference (the only variables available for comparison). Overall, 83% of respondents reported being the patient’s mother, 7% the father, 7% the legal guardian, and 3% other. As shown in There were significant differences in self-reported vaccination status and vaccination status determined electronically . Based oOverall, 62% of parents disagreed that their daughter was at risk for HPV infection. Regarding specific reasons, most parents agreed that their daughter was not at risk for HPV infection because she was not having sexual intercourse (71%). Twenty-four percent of parents agreed that their daughter was only at risk of HPV if she had premarital sex. Few parents (10%) agreed that it was better to get HPV infection than vaccination, or that HPV is not a problem because it can be treated (13%) or because few people have cervical cancer (9%). There were some notable differences in attitudes regarding HPV infection and HPV vaccine between self-reported non-initiators and non-completers . Non-iniThirty-eight parents reported their daughters had completed the series and were skipped out of questions regarding reasons for non-completion and decisional regret. Among those parents who reported that their daughters had initiated but not completed the HPV vaccine series , the most commonly reported reasons for not having completed the series were reporting not being due for the next dose yet (52%), not knowing more doses were needed (42%), and reporting that they had not initially had safety concerns about HPV vaccine, but do now (39%). Few parents regretted the decision to vaccinate their daughter (21%) or thought that the HPV vaccine caused their daughter harm (8%). Among these parents who reported their daughter had started but not finished the series (“don’t know/not sure” did not answer this question), 39 out of 40 (98%) reported they planned to complete the series.Parents who reported that their daughter had not started the HPV series were asked to rate the importance of several possible influences on the decision of whether or not to vaccinate their daughter against HPV . The infp = 0.02). Among non-completers who answered that their daughter had received 1 or 2 doses of HPV vaccine, more SS parents reported that they did not think it was important to get all 3 HPV shots  and that “I wasn’t worried about the safety of the HPV vaccine before, but now I am” .Items where there were statistically significant differences between English- (ES) and Spanish-speaking (SS) parents of non-initiators are shown in We report the results of a survey regarding attitudes related to HPV vaccine conducted in an underserved population at high risk for HPV-related disease. We show that safety concerns continue to be a barrier to HPV vaccination, and that there are differences in attitudes of parents who report their daughters have started the series compared to those who have not. We also present new information showing that parents whose daughters have started but not finished the series may acquire safety concerns after initiating the series. Finally, our data show important differences in the reasons for non-initiation and non-completion between Spanish- and English-speaking parents.Although concerns from parents about the safety of HPV vaccine are not new, two findings from our analysis are cause for concern. First, in 2013, at the time of this survey and a full seven years after licensure of HPV4, there was a great deal more safety data available than there was in the first few years ,13,14, yResponses among parents who reported their daughters had not started the HPV series provide some focus for vaccine advocates, researchers, and health educators in the creation of future educational interventions to improve vaccination uptake. Similar to prior work, parents request more information about the vaccine’s safety. In addition, it appears there should be more emphasis on cancer prevention. We were somewhat surprised that more parents did not endorse a strong provider recommendation as “very important”, since much of the current messaging around increasing uptake of HPV vaccine is focused on the importance of the provider’s recommendation. A strong provider recommendation was not even in the top five of the possible strategies considered “very important” in the decision to receive the HPV vaccine. While provider recommendation has consistently been shown to influence HPV vaccine uptake ,18,19, oAn actionable finding from our study, and consistent with our recently published qualitative study , is the Electronic data and self-report are often used to assess vaccination status in research studies. The differences we found between electronic data and self-report have several potential interpretations and implications. For those we identified electronically as non-initiators or non-completers but whose parents reported initiation or completion, respectively, there are at least three possibilities: that their daughters had received the vaccine after the data were pulled but before they answered the survey; that their daughters had received the HPV vaccines but these were not captured electronically; or that they were mistaken and their daughters had not received the vaccines. This last possibility seems less likely as prior work has shown that over-reporting of HPV vaccination is unusual . For thoThis study had several strengths and limitations. It is complementary to our recently published qualitative study within the same population , confirmOngoing safety concerns and low perceived risk of HPV infection remain significant barriers to HPV vaccination among at risk adolescents. Spanish-speaking parents appear to have different barriers than English-speaking parents for initiation of the HPV vaccine, and a concerning proportion of Spanish-speaking parents whose daughters start the series are unaware of the need for subsequent doses. Many parents develop safety concerns about HPV vaccine after starting the series. Providers and health educators should emphasize cancer prevention and vaccine safety when counseling parents and developing educational materials.


Human papillomavirus (HPV) is a major etiological factor for tonsillar and the base of tongue cancer (TSCC/BOTSCC). HPV-positive and HPV-negative TSCC/BOTSCC present major differences in mutations, mRNA expression and clinical outcome. Earlier protein studies on TSCC/BOTSCC have mainly analyzed individual proteins. Here, the aim was to compare a larger set of cancer and immune related proteins in HPV-positive and HPV-negative TSCC/BOTSCC in relation to normal tissue, presence of HPV, and clinical outcome. Fresh frozen tissue from 42 HPV-positive and 17 HPV-negative TSCC/BOTSCC, and corresponding normal samples, were analyzed for expression of 167 proteins using two Olink multiplex immunoassays. Major differences in protein expression between TSCC/BOTSCC and normal tissue were identified, especially in chemo- and cytokines. Moreover, 34 proteins, mainly immunoregulatory proteins and chemokines, were differently expressed in HPV-positive vs HPV-negative TSCC/BOTSCC. Several proteins were potentially related to clinical outcome for HPV-positive or HPV-negative tumors. For HPV-positive tumors, these were mostly related to angiogenesis and hypoxia. Correlation with clinical outcome of one of these, VEGFA, was validated by immunohistochemistry. Differences in immune related proteins between HPV-positive and HPV-negative TSCC/BOTSCC reflect the stronger activity of the immune defense in the former. Angiogenesis related proteins might serve as potential targets for therapy in HPV-positive TSCC/BOTSCC. The incidence of oropharyngeal squamous cell carcinoma (OPSCC) has increased in many Western countries, due to a rise in incidence of human papillomavirus (HPV) positive tonsillar squamous cell carcinoma (TSCC) and base of tongue squamous cell carcinoma (BOTSCC), the two most commonly HPV-positive OPSCC subsites ,2,3. NotOlink multiplex assays are recently developed immunoassays, based on proximity extension assay (PEA) technology, with high sensitivity and reproducibility over a wide range of protein concentrations . Each paFifty-nine TSCC/BOTSCC  and theip-values < 0.05, with exception of HK8 for which it was p = 0.1). For HPV-negative tumors vs. normal samples 78/155 proteins differed significantly, and 37 proteins . Boxplots presenting the expression levels in Mucin-16, FasL, CD8A, and HK14 for HPV-positive and HPV-negative tumors are shown in As noted above, the difference in expression levels between the groups of HPV-positive and HPV-negative tumors was generally less pronounced than between those of tumors vs. normal tissues. Out of nine proteins with >2-fold higher in expression in HPV-positive tumors, than in HPV-negative tumors, most were surface immunoregulatory proteins that were present on immune or tumor cells  or chemokines. Notably, however Mucin-16, with a nearly five-fold difference in expression, is a glycoprotein that is present in mucosal surfaces. In contrast, five proteins with >2-fold lower expression in HPV-positive tumors than in HPV-negative tumors were not immune related proteins, e.g., two kallikreins, HK8 and 14, and Wnt inhibitory factor 1 (WIF-1).In a heatmap, presenting proteins differentially expressed in the HPV-positive as compared with the HPV-negative tumors, most HPV-positive tumors separated into two out of three main clusters , possibly associated to clinical outcome, are depicted for HPV-positive and HPV-negative tumors in Proteins with formally significant expression differences  was significant after Bonferroni correction for multiple testing). This could be explained by the relatively small sample sizes and these findings require further validation in an extended cohort. For HPV-positive tumors, 15 proteins were related to recurrence after therapy, all with a higher expression in the primary tumors with later recurrence  showing a >2-fold higher expression, while the majority had a lower expression, with IL1α, CXCL11, and TRAIL being the most prominent . ExpressCD8+ positive tumor infiltrating lymphocytes (CD8+ TILs) have earlier been related to improved prognosis for both HPV-positive and HPV-negative TSCC/BOTSCC, although the latter in general have a lower number of CD8+ TILs ,22. For p < 0.01 for all of these analysis are presented in p < 1 × 10−6). The correlates usually remained significant even after the fraction of tumor cells was accounted for as a covariate, indicating that the analysis was largely unaffected by this factor.This evaluation was performed by correcting for % tumor cells in the sample both for all of the tumor samples taken together and then separately for HPV-positive and HPV-negative tumors. Proteins with Protein expression was also evaluated in relation to tumor T-stage, by comparing the pooled set of T1/T2 with that of T3/T4, for HPV-positive and HPV-negative tumors separately. Significant differences are presented in p = 0.027, p = 0.107).To validate the expression of VEGFA in relation to clinical outcome a set of 49 TSCC/BOTSCC biopsies was evaluated for VEGFA expression by IHC. The tumors were then dichotomized based on the VEGFA intensity and analyzed in relation to disease free and progression free survival. Strong VEGFA expression was found to be correlated to poor disease-free survival (DSF), In this study, 55 TSCC/BOTSCC biopsies and corresponding normal samples were analyzed for the expression of 155 cancer and immune related proteins, and differences in protein expression between tumor and normal tissue as well as between HPV-positive and HPV-negative TSCC/BOTSCC, were identified. Furthermore, proteins potentially related to clinical outcome, for HPV-positive and HPV-negative tumors, respectively, were identified. One of these proteins, VEGFA, was validated and was shown to be related to disease-free survival for HPV-positive TSCC/BOTSCC.www.olink.com/products). Therefore, it was not surprising that many differences in protein expression between tumor and normal tissue were found. That fewer (78/155) proteins differed in expression between HPV-negative tumors as compared to HPV-positive tumors (111/155) vs. their corresponding normal samples was likely a combined effect of a smaller cohort  and/or a less active immune defense in the former.The proteins included in the Olink panels utilized in the present study, had been selected as directly or indirectly cancer related and involved in processes such as angiogenesis, cell-cell signaling, cell-cycle control, tumor-immunity, chemotaxis, apoptosis, and cell killing  in culture supernatants harvested from HNSCC tumor tissue-derived cell suspensions, showed, in accordance with the present study, high tumor related levels of CXCL9, CXCL10, and CCL20 and decreased levels of CCL5 . In paraProteins with a distinct lower expression in HPV-positive TSCC/BOTSCC vs. normal samples included kallikreins KLK13, HK8, and HK11. Kallikreins have mostly been investigated as serum markers in prostate cancer, but also in some other cancer types e.g., lung cancer where HK8 has been found to be related to favorable outcome and shown to suppress tumor invasiveness in lung cancer, while little is known about their expression in HNSCC and TSCC/BOTSCC .Proteins with higher expression in HPV-positive vs. HPV-negative TSCC/BOTSCC were mainly immune related. Several were surface proteins expressed on immune cells, e.g., CD8A, and PD-1, or on cancer cells and affecting immune activity, e.g., PD-L1, FASL, and notably PD-1 and its ligand PD-L1 were similarly upregulated. A higher CD8A expression was expected, since increased numbers of CD8+, FoxP3+, and CD4+ TILs in HPV-positive vs. HPV-negative OPSCC have been noted earlier, where in particular a higher number of CD8+TILs is linked to a better clinical outcome, irrespective of the HPV status of the tumor ,21,22.PD-1 and PD-L1 exhibited a higher expression in HPV-positive when compared to HPV-negative tumors in this study. Interaction of PD-1, expressed on the surface of activated T-cells, B-cells, and macrophages, and PD-L1, expressed on immune and cancer cells can suppress the activity of CD8+ T-cell mediated immune response, and have therefore received attention for immunotherapy ,27. ReceIn parallel with the higher immune infiltration in HPV-positive than in HPV-negative tumors, some cytokines and chemokines e.g., IL12, CCL4, CCL20, CXCL10, CXCL17 had higher expression in the former, with IL12, notably being an important regulator of T-cell and NK-cells cytotoxicity, and its receptor, IL12R1-β1, was also upregulated in the HPV-positive tumors.Finally, Mucin-16 , a transmembrane protein that functions as a barrier to bacterial infections, protects cancer cells from being killed by immune cells and contains the CA125 peptide , demonstFew other studies have analyzed a large number of proteins simultaneously in OPSCC in relation to tumor HPV status and/or clinical outcome. Proteomic profiling of OPSCC by mass spectrometry disclosed e.g., enrichment of E2F1 and E2F4 in HPV-positive OPSCC, while reverse-phase protein array profiling revealed differences in e.g., P13K/AKT/mTOR and receptor kinase pathways ,31.Here, most HPV-positive tumors separated into clusters, mainly due to differences in the expression of immune related proteins on the cell surface of tumor infiltrating immune cells, e.g., PD-1, FasL, NCR1, and KLRD1 or soluble cytokines/chemokines e.g., IL12 and CCL4 B. High eGlobal mRNA expression between HPV-positive and HPV-negative OPSCC has also shown differences in proteins not included in the present study e.g., CDKN2A, NF-KB, and STAT3, making comparisons difficult ,35,36. NIn this study, some of the proteins with the most pronounced potential correlation to clinical outcome in HPV-positive TSCC/BOTSCC were at least partly related to angiogenesis e.g., DLL1, ESM1 (endocan), VEGFA, CYR61, and PlGF. Higher VEGFA expression in the tumor cells was confirmed by IHC to be associated with poorer DSF. High VEGFA expression, especially in combination with high EGFR expression has earlier been linked to local recurrence in TSCC in one study, and likewise in oral and laryngeal cancer, but not in a third study, including HPV-positive and HPV-negative OPSCC ,38,39,40Angiogenesis is closely linked to hypoxia, and VEGFA together with CA9, are also markers for hypoxia, both being regulated by HIF1α and are involved in the induction of members of the Notch-pathway where DLL1 functions as a ligand for Notch1 . Also, PNoteworthy, the IGF receptor IGF1R also demonstrated a higher expression in tumors that recurred. IGF1R is potentially targetable for therapy and can inhibit the effect of anti-EGFR therapy by acting on the same downstream pathway ,47. SincThere is a need for new targets for therapy of TSCC and BOTSCC irrespective of HPV-status. Recently, earlier treatment that entailed conventional radiotherapy and/or surgery has been intensified by increased radiotherapy, chemoradiotherapy, and/or EGFR-inhibitors. Intensified treatment leaves the patients with more side effects, but has not improved survival for patients with HPV-positive cancer in Stockholm, Sweden . TreatmeProtein expression was also analyzed in relation to tumor T-stage and major differences related to T-stage were found for some proteins in HPV-negative tumors, but not for HPV-positive tumors. Although T-stage has been shown to be related to clinical outcome  the protIn summary, when comparing protein expression in TSCC/BOTSCC with normal tissue, the most prominent differences were found for chemo-and cytokines. Between HPV-positive vs. HPV-negative tumors, most of the differences were detected in the immune related proteins as well as cyto-and chemokines. Some proteins were tentatively related to clinical outcome. For HPV-positive tumors, such proteins were mostly related to hypoxia and angiogenesis, and some may be potentially targetable and need to be further evaluated.Fifty-nine study specific pre-treatment tumor biopsies of TSCC (ICD-10 code C09.0-9) and BOTSCC (ICD-10 code C01.9), and adjacent normal tissue, from patients treated 2002–2011 at the Karolinska University Hospital were snap frozen and stored at −70 °C until the cutting of the samples. Corresponding diagnostic formalin fixed paraffin embedded (FFPE) pre-treatment biopsies from the tumors had previously been analyzed for HPV DNA and p16INK4A (p16) overexpression, where being positive for both was defined as HPV-positive status [Biopsies were cut frozen, embedded in optimal cutting temperature compound (OCT), and six cuts/biopsy were made, 1 × 5 μm, 4 × 20 μm and 1 × 5 μm. The first and last were used for haematoxylin-eosin-staining and evaluation of tumor content by an experienced pathologist. All of the tumor samples included had at least 40% tumor cells and 40/59 had >70% tumor cells (taking tumor infiltrating immune cells into account). For tumors, the remaining cuts (20 μm each) were paired 2 and 2, with each pair dissolved and analyzed separately, to obtain two replicates. For normal tissues, the remaining cuts were all pooled and dissolved together. Samples were then dissolved in different amounts of RIPA-buffer  in relation to the area of the cuts to obtain a standardized protein concentration. Dissolved samples were kept frozen at −70 °C until analysis on the Olink platform.Sample aliquots were analyzed with two Olink multiplex immunoassays, Immuno-Oncology and Oncology II,  at the Clinical Biomarkers facility, Science for Life Laboratory, Uppsala University, with each panel evaluating the concentration of 92 different proteins. In total, 167 unique proteins were analyzed, since 17 proteins overlapped between the two assays . The 17 t-test, regression modeling, the expression profiles were rendered normally distributed by taking log2 of the NPX values. The multiple regression model  under alpha = 1 and other parameters set to their defaults. p-values from t-tests were adjusted to report either family-wise error rates (Bonferroni correction) or the false discovery rate [In order to enable as much tools of parametric statistics, such as Pearson linear correlation, on model  was creaery rate .https://cran.r-project.org/package=heatmaply).Heatmap in Using the default settings in R function boxplot, the boxes contain data points within the 25–75th percentile intervals . The maximal whisker length, MWL, is defined as 1.5 times the box length. Whiskers can extend to either the MWL or to the maximal available data point when the latter is below MWL. Separate markers thus correspond to data points that extend off the box by more than the MWL value.Evaluation of VEGFA expression was performed only in samples that were both HPV DNA and p16 positive and the validation set is presented in Staining was evaluated by two researchers, including one pathologist, blinded for all other information about the samples. For cases where the evaluation differed, a consensus was reached. Staining intensity on tumor cells was scored as 0, absent, 1, weak, 2, moderate, and 3, strong. The percentage of stained tumor cells was assessed to the nearest 10%. Cases where the staining was not possible to be evaluated adequately were excluded.For analysis of survival in relation to protein expression in the PEA-assay, tumors were analyzed separately for HPV-positive and HPV-negative tumors and tumors from patients being tumor-free and alive after four-years were compared with tumors from patients with recurrence within and/or dead with tumor within four-years. There were five recurrences/death with tumor among patients with HPV-negative tumors and four recurrences among patients with HPV-positive tumors.For analysis of survival in relation to VEGF expression by IHC, survival was measured in days from diagnosis until an event occurred, or until four years after diagnosis when the patients were censored. Disease recurrence (TSCC or BOTSCC) was used as event for calculation of disease free survival (DFS) and disease recurrence or death with tumor was used when calculating progression-free survival (PFS). Kaplan-Meier estimator was used for DFS and PFS, and the differences in the survival of patients were tested using the logrank test. The Cox proportional hazards model was used for the calculation of the adjusted and unadjusted hazard ratios (HRs). Calculations and analyses were performed using SPSS Statistics, Version 21.0 .


Human papillomaviruses (HPVs) are an ancient group of viruses with small, double-stranded DNA circular genomes. They are species-specific and have a strict tropism for mucosal and cutaneous stratified squamous epithelial surfaces of the host. A subset of these viruses has been demonstrated to be the causative agent of several human cancers. Here, we review the biology, natural history, evolution and cancer association of the oncogenic HPVs.This article is part of the themed issue ‘Human oncogenic viruses’. All papillomaviruses encode four conserved core proteins: E1 and E2 are replication factors [cis regulatory elements. Transcription occurs in three waves, which are dependent on the differentiation status of the host cell [The family  factors ,4. In ad factors –9. Theseost cell . Early t(b)HPVs infect cutaneous and mucosal sites and take advantage of the highly organized process of tissue renewal in stratified squamous epithelia. The virus infects the cells in the lower, basal layer of the epithelium through a micro-abrasion  and estaThe HPV virion is an icosahedral capsid assembled from 360 molecules of the L1 protein . The virThe virion is taken into the cell by endocytosis and is trafficked through the endosomal pathways to the trans-Golgi network. The virus is uncoated during trafficking and only the viral mini-chromosome, in complex with L2, enters the nucleus encased in a membrane vesicle . The celEarly viral transcripts encode the E1 and E2 replication proteins to support limited viral DNA amplification . There aE6 and E7 are the oncoproteins of the high-risk alpha-HPVs. These proteins are less well conserved, and more specialized than the core proteins of the virus. Through a multitude of interactions with cellular proteins, they both promote cellular proliferation and inactivate cell-cycle checkpoints to promote viral replication in differentiated cells . E7 causIn the upper layers of an infected lesion, viral DNA is amplified to a high copy number. This phase requires induction of the DDR, which is thought to recruit repair factors that the virus can hijack to replicate its DNA ,29. The 2.(a)Papillomaviridae contains 49 genera and over 300 individual human and animal papillomavirus types (http://pave.niaid.nih.gov/). Over 200 types are HPVs, which are organized into five phylogenetic genera named alpha, beta, gamma, mu and nu, shown in To date, the family (b)Homo sapiens [Until recently, it was thought that papillomavirus infection was restricted to Amniotes , indicating that virus and host had been coevolving for over 300 Myr . However sapiens . Current sapiens ,32. It i(c)a shows the different human cancers associated with HPV infection, and figure 4b shows the distribution of oncogenic HPV types found associated with different cancer sites [The host specificity and benign nature of most papillomavirus infections is indicative of a long virus–host association . AlthougFigure 4er sites .Figure (d)Individual HPV types have less than 90% nucleotide sequence identity in the L1 gene compared with any other named HPV type . However3.(a)Over 15% of human cancers can be attributed to infectious agents, and almost one-third of these are due to infection by HPVs . HPVs ar(b)There has long been debate as to whether HPV types from the beta genus are associated with skin keratinocyte carcinomas (KC), in particular squamous cell carcinoma ,42. IARC(c)Although many processes ultimately affect persistent HPV infection, the E6 and E7 proteins are necessary and sufficient for HPV-mediated oncogenesis. All HPV E6 and E7 proteins bind to a plethora of cellular proteins and teasing apart the precise interactions that make an E6 or E7 protein oncogenic has not been simple –46. All 4.(a)The oncogenic alpha-HPVs are sexually transmitted and about 30% of young women become infected within 24 months of their first sexual exposure . Infecti(b)During the period of persistent infection, there is no apparent immune detection of the virus . This is(c)in situ methods [A debated question, and closely related topic, is whether HPVs enter a state of true latency . It is challenging to detect low copies of HPV DNA in the persistently infected lower layers of an infected epithelium using  methods , never m methods ,59. Furt methods . If thes methods . These i(d)a). This association may reflect the susceptibility of the epithelium in the tonsillar crypts to HPV infection and persistence [figure 4c). Increased vaginal exposure to HPV  is inversely proportional to the risk of oral HPV infection in women [The link between HPV infection and head and neck cancer (HNSCC) was first noted over 30 years ago , and epifigure 4sistence . Moreovesistence . Men aresistence ,66 figurin women ,66. Thisin women ,66.(e)et al. ‘One virus, one lesion’ [Many studies detect the presence of multiple HPV types at the same anatomical site within a single individual . However lesion’ . Moreove lesion’ .(f)Different HPV types have tropism for different types, and anatomical sites, of cutaneous and mucosal epithelia. Although not well understood, this tropism is thought to be due to the transcriptional activity of each HPV type within permissive cells, rather than the requirement for specific cell surface receptors. All HPVs have a similar life cycle that requires establishment of infection within an epithelial basal cell, and generation of virus in the terminally differentiated progeny of the infected cell. However, the situation is more complex than this and the outcome of infection may depend on the precise nature of the originally infected cell. For example, most cases of cervical cancer arise from the cervical transformation zone, a region of the cervix where the ectocervix and endocervix meet and cells transition from squamous to columnar epithelial cells . This siThe basal layers of stratified epithelia contain both slow-cycling stem-like cells, as well as proliferating transit-amplifying (TA) cells. The TA cells can divide both symmetrically  and asymmetrically, where one of the daughter cells proceeds through the differentiation and tissue renewal process. Infection of a TA basal cell could result in a short-lived infection. In fact, modelling the stochastic dynamics of basal cells predicts that over 80% of infections could spontaneously clear as infected cells mature . Long-te(g)The importance of the immune system in controlling HPV infection is very evident in individuals with specific immunodeficiencies . Individ(h)Oncogenic E6 and E7 manipulate many cellular pathways to induce an environment that supports the viral life cycle, but inactivation of crucial cell-cycle checkpoints lead to genetic instability, accumulation of mutations in cellular genes and malignant progression. There are no mutations found consistently in all HPV-associated cancers, but there are frequent mutations in the PI3 K pathway, as well as in receptor tyrosine kinases, and genes related to keratinocyte differentiation and the immune response –78.The viral genome in most, though not all, HPV-associated cancers is found integrated into the host genome. Integration can disrupt E2-mediated viral gene expression, thus promoting genomic instability by deregulating E6/E7 gene expression. E6/E7 are also expressed from integrated genomes as a viral-cellular fusion transcript that is often more stable than the viral mRNA . There i(i)Infection with an oncogenic HPV does not by itself place individuals at high risk of cancer, as most individuals clear infections within 1–2 years. However, long-term persistence of infection is key to the development of HPV-mediated cancer . Persist5.HPV vaccines have been extremely successful from both a scientific and clinical viewpoint, and there is now a vaccine that protects against nine of the most prevalent HPVs associated with cancer and genital warts ,84. Howe


Human papillomavirus (HPV) is associated with the genesis of cervical carcinoma. The co-infection among HPV genotypes is frequent, but the clinical significance is controversial; in Mexico, the prevalence and pattern of co-infection differ depending on the geographic area of study. We analyzed the mono- and co-infection prevalence of multiple HPV genotypes, as well as preferential interactions among them in a Mexico City sample population.This study was designed as a retrospective cohort study. Cervical cytology samples from 1163 women and 166 urethral scraping samples of men were analyzed between 2010 and 2012. The detection of HPV infection was performed using the hybrid capture and the genotyping was by PCR .36% of women were HPV-positive and the most prevalent genotypes were HPV 51, 52, 16, and 33 . The prevalence of co-infection was higher (75.37%) than mono-infection in women HPV positives. All genotypes were co-infected with HPV 16, but the co-infection with 51–52 genotypes was the most frequent combination in all cases.The co-infection was very common; each HPV genotype showed different preferences for co-infection with other genotypes, HPV 51–52 co-infection was the most frequent. The HPV 16, 33, 51 and 52 were the most prevalent and are a public health concern to the Mexican population.The online version of this article (doi:10.1186/s12885-017-3519-7) contains supplementary material, which is available to authorized users. Papillomaviridae family, is an infectious agent of epithelial tissue with high clinical relevance for its association with the generation of cervical carcinoma [The human papillomavirus (HPV), belonging to the arcinoma –3. Therearcinoma , 4, 5. Tarcinoma , 7. The arcinoma , 9. In carcinoma .Co-infection among HPV types is common in women,  and men,It is important to determine the epidemiology of mono- and co-infections of HPV in order to establish appropriate prevention strategies for the design of new vaccines according to each population , 20. In This study was designed as a retrospective cohort study. Samples were obtained from patients that performed clinical tests for the diagnosis of HPV infection in Mexico City; endocervical cytology from women and urethral scrapings from men between 2010 and 2012 were analyzed. These data were not collected or used for another study and have not been previously published. The protocol of analysis of the data obtained for diagnostic purposes was reviewed and approved by Carpermor’s Laboratory Ethics Committee, and was conducted according to the ethical guidelines of the Declaration of Helsinki and to the Official Mexican Standard NOM-012-SSA3–2012, this study was risk free and all information of individuals was anonymized. The study included 1329 patients, of which 1163 were women aged 16 to 72 (31.65 ± 0.43), and 166 were men aged 21 to 68 years (36.07 ± 1.5). An endocervical brush and swab for urethral scraping were used, and the samples were placed in tubes with a Digene transport medium. Finally, they were frozen at −20 °C prior to analysis. All samples were obtained and processed properly; therefore, all data were included for analysis.To identify the HPV-positive patients, we used the Hybrid Capture II test (Digene) according to the manufacturer’s instructions. Hybridization was performed in a microplate with the samples and corresponding probes . The hybridized samples were transferred to wells of capture microplate coated with anti-hybrid antibody (anti-RNA/DNA). Then, anti-RNA/DNA-alkaline phosphatase-conjugated and substrate dioxetane were added for detection in the luminometer. The HPV-positives samples (hybrid capture assay) were used to determine the viral genotype by PCR.DNA extraction was performed in 300–500 μL of each sample using QIAamp UltraSens Virus kit (Qiagen) according to the manufacturer’s instructions. On DNA viral amplification by PCR, we used specific primers for E6 and E7 region of HPV 6, 11, 16, 18, 30, 31, 33, 35, 45, 51, and 52 types (Invitrogen). For the mixture preparation, the multiplex PCR amplification kit (TaqMan) was used according to the manufacturer’s instructions. Then, the samples were placed in the thermocycler (GeneAmp PCR system 9700) and amplified during 45 cycles to the temperature corresponding to each primer. The amplified samples were loaded into 2% agarose gel and set in an electrophoresis chamber  at 80 V for 45 min. Finally, the gel bands were observed with ethidium bromide in the transilluminator  , 26.p < 0.05.Proportions were calculated from the total number of analyzed patients: HPV-positive patients for any type, and HPV-positive patients for specific types. The analysis of proportions was performed using the z-test from the statistical software, Sigma Plot 11.0, and the graphs were made in GraphPad Prism 5 software. Differences were considered statistically significant for values of #p < 0.001). We identified patients with co-infections of two or more HPV genotypes : 858 (64.56%) were negative and 471 (35.44%) patients were HPV-positive in the hybrid capture test. From 1163 women evaluated, 36% were HPV-positive; while from the 166 men tested, 24% were positive ; in contrast, HPV 45 was less frequent (2.56%). In men, genotype 16 was found in 63.41% of patients (#p < 0.001), while others such as genotype 11 and 51 were found in ~22% of patients. HPV 18 and 31 were not identified in any of the men samples evaluated. When comparing genders, the infection frequency by genotypes 31, 33, 51, and 52 was higher in women than men (*p < 0.05); but the prevalence of HPV 16 was higher in men than women (**p < 0.01).The different HPV genotypes assessed had distinct prevalence Fig. ; women hp < 0.001, Table ‡p < 0.05); however, the positive samples of men were too scarce for a conclusive statistical analysis of other genotypes.All evaluated HPV genotypes showed a preference for co-infection in women Table . Over 80p < 0.01). The HPV 11 showed preference for co-infection with four genotypes   increased with the number of genotypes that co-infected in women. HPV 6 frequency increased with the number of genotypes that interacts Fig. , so that05) Fig. .Fig. 2Thp < 0.001), with maximum 64.5% of individuals infected by five HPV genotypes  in co-infection with others genotypes . For the cervical samples with HPV 16 , we found that the ~20% positive samples to HPV 16 co-infected mainly with HPV 33, 51 or 52  had a higher prevalence,  but in pThe above evidence establishes the correlation of HPV 16 and 58 in the carcinogenesis of Mexican women; meanwhile, HPV 18 appears to have no role . Our resThe HPV co-infection with multiple genotypes probably promotes the progression of intraepithelial lesions and cervical cancer in Mexican women. We found that the co-infection among HPV genotypes was more frequent than mono-infection in the tested population, involving a greater number of viral genotypes (7 and 8 different genotypes identified in one case). In contrast, in another study from southeast Mexico, only 23.5% of HPV-positive patients showed multiple infections with 2 and 3 different genotypes . In ItalThe genotypes 16 and 18 are classified as oncogenic in humans (group 2A),  our dataCurrently, the clinical relevance of co-infection in the generation and progress of cervical cancer is unclear. It is likely to happen that initial infection with a particular genotype creates the best conditions for another genotype to infect, and without the first, a second one does not infect per se. This phenomenon may occur for HPV 18 and 35, genotypes only presented in co-infection Table . In ColoIn co-infections detected in the primary tumor, it was found that a viral genotype DNA integrates into the host genome, while the other was maintained in episomal form;  but in m, and invasive generation [The interaction among multiple HPVs may have implications in oncogenic risk . In Brazneration . A studyneration . In Mexineration . Our datBased on this data, we concluded that besides HPV 16, the genotypes 33, 51 and 52 are public health concerns and could contribute to cervical carcinogenesis within the Mexican population due to their high frequency. Moreover, the preferential associations among different HPV types (mainly HR-HPV), most likely represent a synergistic interaction in cervical carcinogenesis. These findings call for focusing our research efforts on the clinical implications of the interaction among the different HPV genotypes in co-infections, and for developing new preventive and therapeutic strategies according to the pattern of prevalence in Mexico or other countries.Additional file 1:HPV genotypes data. The file includes the hybrid capture and genotyping results for each sample and age ranges. The information of gender and age were removed to maintain participant confidentiality. (XLSX 44 kb)Additional file 2:Graph of interactions among HPV genotypes. The graph corresponds to the data shown in Table