Skip to main content

Characterization of multiple human papillomavirus types in the human vagina following ovarian hormonal stimulation

Abstract

The objective of study was to characterize HPV in vaginal samples from women being seen at the Center for Reproductive Medicine and Infertility at Weill Cornell Medicine before and following ovarian stimulation. A total of 29 women made samples available for analysis by viral metagenomics. Eighteen women were HPV-positive, six (33.3%) at their initial visit and 15 (83.3%) following hormone stimulation (p = 0.0059). Pairwise comparison of nucleotide sequences and phylogenetic analysis showed the classification sequences into two genera: Alphapapillomavirus and Gammapapillomavirus. Sequences were from 8 HPV types: HPV 51 (n = 2), HPV 68 (n = 1), HPV 83 (n = 9), HPV 84 (n = 2), HPV 121 (n = 6), HPV 175 (n = 1) and HPV 190 (n = 1). Additionally, C16b and C30 likely represent new types. In summary, multiple HPV types are present in the vagina of reproductive age women and are induced by hormone used to stimulate ovulation.

Introduction

Papillomaviruses (PVs) is diverse group of viruses that infect humans and animals [1,2,3]. Their genome consists of circular double-stranded DNA ranging in size from 5,748 bp to 8,607 bp, organized into six to nine open reading frames (ORF) that encode a set of viral proteins arranged in three functional regions [4]. The early region encodes the proteins E6, E7, E5, E4, E2 and E1 [5,6,7,8,9]. The late region encodes the viral structural proteins L1 and L2 [10, 11]. The regulatory region (URR) or long control region (LCR) contains the replication origin [12].

PVs according to the International Committee on Viral Taxonomy (ICTV) they are subdivided into two subfamilies: Firstpapillomavirinae (reptiles, birds, and mammals) and Secondpapillomavirinae (fish). The subfamily Firstpapillomavirinae includes the human papillomaviruses (HPV), classified into 5 genera Alphapapillomavirus (Apha), Betapapillomavirus (Beta), Gammapapillomavirus (Gamma), Mupapillomavirus (Mu) and Nupapillomavirus (Nu) [4].

The classification of new members of the Papillomaviridae according to the ICTV is based on the identity of the nucleotide pairs in ORF L1. Members of different subfamilies share less than 45% identity of the same genera more than 60% and same species between 60 and 70% [4, 13]. The International HPV Reference Center classifies HPVs below the species level into new types that share less than 90% nucleotide identity in ORFL1 (> 90%) [13,14,15,16,17]. On January 23, 2024, 223 types of HPV were recognized, which are classified into two categories: high-risk oncogenic HPV (HPV-HR). Among the most common are types 16 and 18, described in 70% of cases of cervical cancer, and low-risk HPV (HPV-LR) (types 6 and 11 identified in 90% of genital condylomas and laryngeal papillomas) [14, 18, 19].

Among infected individuals, it is estimated that only 5% will present with some clinical manifestation, characterized predominantly by the appearance of condylomata acuminata (warts) in the genital areas, mouth, and throat in women and men. In the remainder there are no visible lesions, the individual does not present signs and symptoms but HPV is present [19]. In both situations, transmission of the virus is possible, which can ultimately culminate in the development of neoplasms including cervical, vaginal or vulvar cancer [12, 20,21,22,23,24,25].

Cervical cancer carcinogenesis is uniquely tied to human papillomavirus (HPV) infection, particularly high-risk types HPV16 and HPV18, which account for 50% and 20% of cases, respectively [26, 27]. HPV infects the cervical epithelium, where cancer progression is driven by complex interactions between metabolic, immune, and hormonal signals. These interactions facilitate viral DNA integration into the host genome, leading to carcinogenesis.

Estrogen signaling plays a crucial role by inhibiting apoptosis, influencing cell cycle progression, and enhancing metabolism through mechanisms like the Warburg effect. Although the integration of HPV DNA marks a decline in viral activity, it simultaneously triggers malignancy. Estrogen signaling can both promote and suppress cervical intraepithelial neoplasia, with ERα expression correlating with better patient survival [28,29,30].

However, the effects of estrogen receptors vary by cell context, and certain variants can increase cell proliferation and invasion [31, 32]. Animal models have provided insights into estrogen’s role in cervical carcinogenesis, but they do not fully replicate human conditions. Distinguishing between transient and chronic HPV infections is vital, as chronic infections pose a higher risk of immune evasion and cancer. Cytokines like IL-10 are limited in assessing immunosuppression in cervical tissue [33,34,35].

Future research should focus on the tumor microenvironment (TME) and the role of estrogen receptors, as cervical carcinoma cells rely on TME estrogen signaling. A comprehensive approach to cervical cancer treatment is needed, combining selective estrogen receptor modulators (SERMs), disruptors (SERDs), aromatase inhibitors (AIs), immune checkpoint inhibitors (ICIs), and adoptive T-cell therapy (ACT) [36, 37]. Given the challenges in HPV vaccination and screening, cervical cancer therapy remains a crucial issue for women’s health.

In the present study, we document that investigation of HPV in vaginal samples from women following hormonal ovarian stimulation results in identification of multiple HPV types including two probable new types.

Materials and methods

Study population

Twenty-nine women seeking in vitro fertilization (IVF), in the Center for Reproductive Medicine and Infertility at Weill Cornell Medicine in New York. signed informed consent and provided were collected samples from the vaginal walls with a cotton swab during a routine speculum-based vaginal examination. After the initial collection, all were treated with gonadotropins to stimulate the growth of multiple ovarian follicles. A second sample was collected 12–21 days later, at the time of oocyte collection. The material was stored at -80oC dry ice to the virology laboratory at the Faculty of Medicine of the University of São Paulo. All samples arrived intact and frozen. Clinical and demographic data were subsequently obtained by chart review.

Sample processing

The homogenized vaginal sample was centrifuged at 8,000 g for 10 min and approximately 500 µL of the supernatant was then percolated through a 0.45 μm filter (Merck Millipore, Billerica, MA, USA). Approximately 100 µL of PEG-it Virus Precipitation Solution (System Biosciences, Palo Alto, CA, USA) was added to the filtrate and the contents of the tube were gently mixed and incubated at 4 °C for 24 h. The mixture was centrifuged at 8,000 g for 30 min at 4 °C. The pellet was treated with a combination of nuclease enzymes. Total nucleic acids were extracted using an automated Maxwell® Viral Total Nucleic Acid Purification Kit (Promega, Madison, WI, USA).

cDNA synthesis was performed with Superscript IV Reverse Transcriptase (Thermo Fisher Scientific, Waltham, MA, USA). To second strand cDNA synthesis was using a DNA Polymerase I Large (Klenow) Fragment (Promega, Madison, WI, USA). Viral DNA was enriched for circular DNA molecules using rolling circle amplification (RCA) with the Illustra TempliPhi kit (Cytiva, Marlborough, MA, USA) and then purified with ProNex Size-Selective Purification System (Promega, Madison, WI, USA) and submitted to fluorometric quantification with QuantiFluor ONE dsDNA System (Promega, Madison, WI, USA).

The samples duplicate, one for total nucleic acid only and the other enriched for viruses with circular genomes, was submitted to Nextera XT Sample Preparation Kit (Illumina, San Diego, CA, USA) and used to construct a DNA library, which was identified using dual barcodes. Pippin Prep (Sage Science, Inc., Beverly, MA, USA) was used to select a 500 bp insert (range 400–600 bp). The library was deep sequenced using a NovaSeq 6000 Sequencer (Illumina, CA, USA) with 2 × 250 bp ends.

Genome annotation

Open reading frames (ORFs) in genomes were identified using ORFfinder (https://www.ncbi.nlm.nih.gov/orffinder/). The protein domains and motifs were predicted using the Conserved Domain Database [38] and Motif Finder (http://www.genome.jp/tools/motif/), respectively.

Alignment and phylogenetic analysis

HPV nucleotide sequences of the L1 gene were obtained from the reference database (Papillomavirus Episteme-Pave) and compared with the sequences detected in the study. Alignments edited in the Ugene toolkit version 4.6 [39]. Trees were infer using the IQ-Tree [40] and visualized using FigTree version 1.4.2 (http://tree.bio.ed.ac.uk/software/figtree).

HPV taxonomic classification

For the taxonomic classification of HPV, the sequences were consulted using BLAST and the best results (highest identity) were selected, to reduce the number of random matches, E values ​​were defined in each search. HPV types were assigned using the L1 taxonomy tool available on the PaVe website (https://pave.niaid.nih.gov/#analyze/l1_taxonomy_tool). To confirm types and classify sequences at the species level, similarity was calculated using Mega and a paired method implemented in the SDT program [41,42,43,44].

Results

Characteristics of study participants

HPV was detected in 18 (62.1%) women. The ages ranged from 32 to 44 years with a mean of 37.2. The majority (62.1%) were White. There were no associations between HPV detection and age or race (Table 1). Of the cases in which HPV was detected, three (16.7%) were HPV-positive only in the first collection, 12 (66.7%) in the second, and three (16.7%) in both collections. A total of six women were positive for HPV in the first sample as opposed to 15 who were positive in their second sample. This difference is statistically significant (p = 0.0059 Fisher’s exact test).

Fourteen women (77.8%) were positive for a single HPV type, three (16.7%) had the co-occurrence of two types, while one woman (5.6%) had three types. Among the HPV types detected, 60% were associated with HPV-LR. 20% with HPV-HR (HPV51 and HPV68) and 20% with unclassified risk HPV. The detected HPV resulted in 26 contigs that shared a high identity (> 98%) with other viruses belonging to the Papillomavirus family (Table S1).

Table 1 HPV types detected in study subjects and clinical diagnosis

Organization of the HPV Genome

The contig identified exhibit double-stranded circular DNA genomes of 7,186 bp to 8771 bp in length and had a GC content of 36.2–46.4%. Six to eight ORFs that encode early proteins (E6, E7, E1, E2, E4, and E5), two late (L2 and L1) and a regulatory region (URR) were identified (Table 1; Fig. 1). The genomic organization indicates the presence of domains, and conserved motifs consistent with other genomes of the Papillomaviridae family (Table S2-S8).

Fig. 1
figure 1

Genomic organization of HPV-68 (C36a). The viral proteins (E6, E7, E1, E2, E4, E5, L2, and L1) and the non-coding region (URR) located between L1 and E6 are indicated

E6 and E7 are frequently described as acting in the regulation of cell proliferation. Both proteins were identified in all sequences. E6 contains 139 to 162 amino acids. This protein displays two zinc-binding domains (CxxC (x-29 aa) CxxC) flanked by short N-terminal and C-terminal tails. Terminal involved in intracellular stability and conformation [45]. Furthermore, in some sequences (C16a, C36a, and C48a) in the C terminal region, the PDZ (ETQV), PBM (GTTL/RTEV), PKA (RRYS/RRRT) and AKT (RERPRT) motifs present in high oncogenic risk HPV were identified [46]. E7 consists of 92 to 110 amino acids and has two conserved regions (CR1 and CR2). In the CR2 region, in fifteen sequences, a motif (LXCXE) was predicted: LYCNE (C09a, C09b, C29, C34c, C36b, C18b, C45, C46 andC48c), LYCDE (C18a and C34b), LQCYE (C16a and C48b), LLCNE (C30) and LVCHE (C36a), which has an important function in binding to the conserved retinoblastoma tumor suppressor protein (pRB) [47]. In the C-terminal domain in all sequences, the zinc-binding domain was identified, which helps the formation of dimers and the functioning of viruses.

The E1 protein ranges from 422 to 652 amino acids in length. The protein was observed in all sequences. The N-terminal transport domain with nuclear localization signal (NLS) was found in sequences C05, C14, C38, C40, C42 C43, and C48a. A DNA binding domain (PF20450), and a helicase domain (PF00519) were also predicted and in 10 sequences the conserved ATPASE oligomerization region (GXXXXGKT/S) was found: GPPDTGKS (C05, C34c), GPSDTGKS (C14, C16b, C18a, C34b, C43 e), GPPNTGKS (C16a and C36a) and GPPDTGKS (C30) this structure is important for replication and amplification of viral episomes in the nuclei of keratinocyte cells infected [5, 48].

E2 is 158 to 408 aa long and participates in the recruitment of cellular factors to viral genomes, which activate or repress transcriptional processes [6]. An N-terminal transactivation domain (PF00508) and a C-terminal DNA binding and dimerization domain (PF00508) were predicted in all sequences, except in sequences C38, C42, and C45 in which the binding domain was not detected, and C-terminal DNA dimerization.

A total of 20 sequences were predicted for the E4 protein (except C05, C14, C16a, C30, C34a, and C48a), with lengths ranging from 94 to 166 aa. In the N-terminal region, a conserved leucine motif (LLKLL) was detected in C18a and C34b, with the proline cluster (PXXP) also being observed in all sequences. These motifs are important for keratin binding and cell cycle arrest, respectively [48].

L1 and L2 major and minor structural proteins of the capsid, respectively. L1 is the most conserved HPV protein consisting of 173 to 521 aa. L2 plays a role in the assembly stage and infectious processes are between 234 and 531 aa in length and are highly conserved [10, 11, 13]. In 16 sequences, a highly conserved furin motif (RXK/RR) was predicted: RRKR (C16a, C16b, C18a, C36a, C48b and C34b), RVKR (C31, C32, C38, C40, C42 and C48a), RLKR (C05, C34a), RAKR (C14, C43).

The URR was located between ORF L1 and L6. contains a putative polyadenylation site (AATAAA) at the 5’ end essential for adding the polyadenylation tail to the 3’ end and processing late viral transcripts [15, 49].

Types of HPV

To taxonomic classification at the level of types, the Pavic L1. HPV of the same type shares more than 90% of the L1 protein region with another officially established type. Based on these criteria, 22 sequences showed identity ranging from 94.19 to 100% with other HPV sequences (Table S9), Four sequences, C05 (77.37%), C34 (77.41%), C16b (78.11%), and C30 (74.15%) shared less than 90% identity with any other type.

Phylogenetic analysis and genetic distance

The inference phylogenetic was conducted based on the nucleotide sequences of the L1 gene region (Fig. 2). The tree showed the grouping of sequences into two genera: Alphapapillomavirus and Gammapapillomavirus. In the first, the sequences were grouped into three clades: Clade I is made up of sequences classified in the Alpha_5, including C16a and C48a, sharing 99.80% identity, 99.93% and 99.73% with the closest OP971008 sequence in BLASTn and 99.40% and 99 0.60% with HPV51 reference MT783412, respectively. Clade II of Alpha_7, C36a, has 98.13% identity with KC470279 and 92.84% with HPV68 reference DQ080079.

Clade III of Alpha_3, C09a, C09b, C18b C29, C34a, C36b, C44 - C48b, exhibited 99.53–100% identity to each other, 97.90–99.73% with OP712020 and 97.42–98.61% compared to HPV83 AF151983. C18a and C34b were closely related, it has 99.93% identity with BLASTn OP970998 and 99.27% with HPV84 reference AF293960.

In the second genus Gamma, the sequences grouped into five clades. Clade I include C30, which has 99.71% identity compared to the unclassified sequence MH777367, 72.56% with NC_040728 from Pavic L1 and 65.49% with MH172379 from HPV222 of the (Gamma 19). Gamma_19 references ranged from 64.54 to 68.70%.

Clade II of Gamma_15, has C05 and C34c share 98.77% identity, 99.00% and 98.76% with MH777317 unclassified, 98.74% and 99.93% with OQ915151 of HPV230 and 78, 80% and 77.67% when compared to the MK645900 sequence of HPV207, respectively. MH777317 and OQ915151 share 98.70% identity, this suggests that the sequences belong to the same type (HPV230).

Clade III of Gamma_12, C16b has 78.21% identity compared to MH460955 of HPV210 of Pavic L1, 78.28% with GU117632 reference of HPV132 and 98.22% with MF588718 of BLASTn classified as HPV132. Note that GU117632 and MF588718 share 78.08% identity. This indicates that GU117632 and MF588718 are not the same type of HPV132.

Clade IV of Gamma_23, C43 is closest to KC108721 of HPV175 with 99.00% identity. Clade V of Gamma_24, C14 has the highest identity (99.13%) with KR816177 of HPV190. While Clade VI of Gamma_10, including C31, C32, C38, C40, C42 and C48c, has 99.62–100% identity with each other. And greater identity (99.67–100%) with HPV121 reference GQ845443.

Based on the demarcation criteria of ICTV, it suggests that C16b and C30 are new species of HPV.

Fig. 2
figure 2

HPV phylogenetic tree based on the L1 protein. The tree was constructed using the maximum likelihood approach. The evolutionary model used for the analysis was LG + F + R6. The sequences identified in this study were highlighted in red. (a) Complete tree containing all reference sequences of HPV types classified in the genera Gammapapillomavirus (blue), Alphapapillomavirus (purple), Betapapillomavirus (orange), Mupapillomavirus (green) and Nupapillomavirus (yellow). (b) Expanded representation of sequences that grouped in the Gammapapillomavirus genus. (c) Expanded representation of sequences that grouped in the Alphapapillomavirus genus

Discussion

Epidemiological studies show that the incidence and prevalence of HPV vary in different populations and geographic locations [50]. In the present study, 62.07% (18/29) of women were positive for HPV and the percentage was significantly greater in the second vaginal sample than in the initial. This difference may be due to their utilization of gonadotropins after their first consultation. It is known that steroid hormones can induce HPV gene expression [51]. While a single investigation from Germany reported that ovarian stimulation did not increase the expression of high risk HPV types in the cervix of women undergoing IVF [52], it remains to be determined if this extends to other HPV types and to different populations. In any event, studies have determined that HPV expression has little, if any, effect on IVF outcomes [53]. In the present study outcomes of the IVF cycle were not available.

The majority of subjects were infected with HPV-LR. However, HPV-HR was identified in two cases. This contributes to the fact that most HPV infections do not manifest clinically [54]. It was found that 77.8% (14/18) of the participants had a single type of HPV, 16.7% (3/18) had two types and 5.6% (1/18) had three types. Similar results were described and highlight that the occurrence of a single type of HPV is most common [20].

Some studies show that the presence of multiple types of HPV in a single individual increases the risk of developing cervical cancer [55]. However, others have shown that there are no differences between the occurrence of single or multiple HPV types in the development of cancer [56]. This shows the importance of better exploring these data through screening women to assess the prevalence, and distribution of HPV types and their association with the development of cancer.

Based on ICTV genus and species classification and phylogenetic inference [4]. The 26 sequences belong to two genera Alphapapillomavirus (14) and Gammapapillomavirus (12). Members of Alphapapillomavirus are described as infecting mainly the mucosa or anogenital; there are 82 types of HPV classified into 14 species [4]. The sequences of this study belonging to the species Alphapapillomavirus 3 (C09a, C09b, C18a, C18b, C29, C34a, C34b, C36b, C45- C48b), followed by Alphapapillomavirus 5 (C16a, C48a) and Alphapapillomavirus 7 (C36a). This result is consistent with research that shows a higher frequency of the Alpha-3 species in North American women [57].

Gammapapillomaviruses are described on mucous and skin surfaces. There are 171 types of HPV classified into 27 species [4]. But the species Gammapapillomavirus 10 (C31, C32, C38, C40, C42 and C48c) was the most common. But the species Gammapapillomavirus 12 (C16b), Gammapapillomavirus 15 (C05, C34c), Gammapapillomavirus 19 (C30), Gammapapillomavirus 23 (C43) and Gammapapillomavirus 24 (C14) were identified. In general, evaluation of the frequency of members of the genus Gammapapillomavirus are less common. In an investigation carried out on samples from men, Gamma-10 was the most detected [58].

Regarding the types of HPV, it was found that 8 types of HPV were present. The most predominant type was HPV83, followed by HPV121. In general, the prevalence of the HPV type vary around the world [24]. An interesting finding is that four sequences (C16b, C30 C05, and C34c) showed identity below 90% when compared with more similar sequences in the Pavic L1 taxonomy tool. However, they exhibit identity greater than 90% with better BLASTn results.

The C16b sequence shares a high identity of 98.2% with MF588718 previously classified as HPV132 in a study in the United States (USA) in 2013. However, MF588718 has 78.1% identity with the reference sequence GU117632 identified in keratotic lesions of immunosuppressed individuals. This fact suggests that MF588718 and C16b are new types of HPV, given that they share less than 90% identity with any other type. These results agree with the study that analyzed the incorrect classification of human papillomavirus sequences available in the GenBank database which detected 110 nucleotide sequences named as a type of HPV, different to which they corresponded [59].

Similarly, C30 shows greater identity with MH777367 described in the USA in 2009 (99,71%). However, 65.54% have the HPV222 reference sequence MH172379 [60], indicating that MH777367 and C30 may represent new types of HPV. On the other hand, C05 and C34c exhibit high identity of 99.0% the 98.8% with MH777317 (HPV-mSK_175) identified in 2015 in the USA in skin metagenomic samples [61], and 98.7% the 99.9% with OQ915151 (HPV230) described in the USA in 2010, respectively. MH777317 was almost identical (98.7%) to the officially established HPV230 sequence (OQ915151), that is, C05 and C34c correspond to the HPV230 type.

It is important to highlight the need for new classification tools that simplify the curation of sequences to avoid erroneous frequency data and HPV prevalence and likely future changes to the classification system [62].

Conclusions

We describe 26 HPV sequences identified in eighteen women, mostly only available following hormonal stimulation, associated with multiple types of HPV including two probable new types.

Data availability

The study was conducted by the 1975 Declaration of Helsinki (https://www.wma.net/what-we-do/medical-ethics/declaration-of-helsinki/, accessed on 9 February 2024). The project was approved by the Institutional Review Board at Weill Cornell Medicine, protocol number 20-04021885, in October 2022. Viral genome sequences have been deposited in the NCBI GenBank database (accession numbers PP718696-PP718721).

References

  1. Liu Z, Yang S, Wang Y, Shen Q, Yang Y, Deng X, Zhang W, Delwart E. Identification of a Novel Human Papillomavirus by Metagenomic Analysis of Vaginal Swab Samples from pregnant women. Virol J. 2016;13. https://doi.org/10.1186/s12985-016-0583-6.

  2. Kraberger S, Austin C, Farkas K, Desvignes T, Postlethwait JH, Fontenele RS, Schmidlin K, Bradley RW, Warzybok P, Van Doorslaer K, et al. Discovery of Novel Fish papillomaviruses: from the Antarctic to the commercial Fish Market. Virology. 2022;565:65–72. https://doi.org/10.1016/j.virol.2021.10.007.

    Article  CAS  PubMed  Google Scholar 

  3. Chen Z, Van Doorslaer K, DeSalle R, Wood CE, Kaplan JR, Wagner JD, Burk RD. Genomic diversity and Interspecies Host Infection of Α12 Macaca Fascicularis Papillomaviruses (MfPVs). Virology. 2009;393:304–10. https://doi.org/10.1016/j.virol.2009.07.012.

    Article  CAS  PubMed  Google Scholar 

  4. Van Doorslaer K, Chen Z, Bernard H-U, Chan PKS, DeSalle R, Dillner J, Forslund O, Haga T, McBride AA, Villa LL, et al. ICTV Virus Taxonomy Profile: Papillomaviridae. J Gen Virol. 2018;99:989–90. https://doi.org/10.1099/jgv.0.001105.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  5. Bergvall M, Melendy T, Archambault J. The E1 proteins. Virology. 2013;445:35–56. https://doi.org/10.1016/j.virol.2013.07.020.

    Article  CAS  PubMed  Google Scholar 

  6. McBride AA, The Papillomavirus E, Proteins. Virology. 2013;445:57–79. https://doi.org/10.1016/j.virol.2013.06.006.

    Article  CAS  PubMed  Google Scholar 

  7. Willemsen A, Bravo IG. Origin and evolution of Papillomavirus (Onco)genes and genomes. Phil Trans R Soc B. 2019;374. https://doi.org/10.1098/rstb.2018.0303.

  8. DiMaio D, Petti LM. The E5 proteins. Virology. 2013;445:99–114. https://doi.org/10.1016/j.virol.2013.05.006.

    Article  CAS  PubMed  Google Scholar 

  9. Doorbar J. The E4 protein; structure, function and patterns of expression. Virology. 2013;445:80–98. https://doi.org/10.1016/j.virol.2013.07.008.

    Article  CAS  PubMed  Google Scholar 

  10. Buck CB, Day PM, Trus BL. The Papillomavirus Major Capsid protein L1. Virology. 2013;445:169–74. https://doi.org/10.1016/j.virol.2013.05.038.

    Article  CAS  PubMed  Google Scholar 

  11. Wang JW, Roden RBS. L2, the minor capsid protein of Papillomavirus. Virology. 2013;445:175–86. https://doi.org/10.1016/j.virol.2013.04.017.

    Article  CAS  PubMed  Google Scholar 

  12. Bernard H-U. Regulatory Elements in the viral genome. Virology. 2013;445:197–204. https://doi.org/10.1016/j.virol.2013.04.035.

    Article  CAS  PubMed  Google Scholar 

  13. Bernard H-U, Burk RD, Chen Z, Van Doorslaer K, Hausen HZ, De Villiers E-M. Classification of Papillomaviruses (PVs) based on 189 PV types and proposal of taxonomic amendments. Virology. 2010;401:70–9. https://doi.org/10.1016/j.virol.2010.02.002.

    Article  CAS  PubMed  Google Scholar 

  14. Van Doorslaer K, Tan Q, Xirasagar S, Bandaru S, Gopalan V, Mohamoud Y, Huyen Y, McBride AA. The Papillomavirus Episteme: a Central Resource for Papillomavirus sequence data and analysis. Nucleic Acids Res. 2012;41:D571–8. https://doi.org/10.1093/nar/gks984.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  15. De Villiers E-M, Fauquet C, Broker TR, Bernard H-U, Zur Hausen H. Classification of Papillomaviruses. Virology. 2004;324:17–27. https://doi.org/10.1016/j.virol.2004.03.033.

    Article  CAS  PubMed  Google Scholar 

  16. De Villiers E-M. Cross-roads in the classification of Papillomaviruses. Virology. 2013;445:2–10. https://doi.org/10.1016/j.virol.2013.04.023.

    Article  CAS  PubMed  Google Scholar 

  17. Bzhalava D, Eklund C, Dillner J. International standardization and classification of human papillomavirus types. Virology. 2015;476:341–4. https://doi.org/10.1016/j.virol.2014.12.028.

    Article  CAS  PubMed  Google Scholar 

  18. Harari A, Chen Z, Burk RD. Human Papillomavirus Genomics: Past, Present and Future. In Current Problems in Dermatology; Ramírez-Fort, M.K., Khan, F., Rady, P.L., Tyring, S.K., Eds.; S. Karger AG, 2014; Vol. 45, pp. 1–18 ISBN 9783318025262.

  19. Cubie HA. Diseases Associated with human papillomavirus infection. Virology. 2013;445:21–34. https://doi.org/10.1016/j.virol.2013.06.007.

    Article  CAS  PubMed  Google Scholar 

  20. Zhou Y, Shi X, Liu J, Zhang L. Correlation between human papillomavirus viral load and cervical lesions classification: a review of current research. Front Med (Lausanne). 2023;10:1111269. https://doi.org/10.3389/fmed.2023.1111269.

    Article  PubMed  Google Scholar 

  21. Alhamlan FS, Alfageeh MB, Al Mushait MA, Al-Badawi IA, Al-Ahdal MN. Human Papillomavirus-Associated Cancers. Adv Exp Med Biol. 2021;1313:1–14. https://doi.org/10.1007/978-3-030-67452-6_1.

    Article  CAS  PubMed  Google Scholar 

  22. Egawa N. Papillomaviruses and Cancer: commonalities and differences in HPV Carcinogenesis at different sites of the body. Int J Clin Oncol. 2023;28:956–64. https://doi.org/10.1007/s10147-023-02340-y.

    Article  PubMed Central  PubMed  Google Scholar 

  23. Global Cancer Burden Growing, amidst Mounting Need for Services Available online. https://www.who.int/news/item/01-02-2024-global-cancer-burden-growing--amidst-mounting-need-for-services (accessed on 10 February 2024).

  24. Lewis RM, Laprise J-F, Gargano JW, Unger ER, Querec TD, Chesson HW, Brisson M, Markowitz LE. Estimated prevalence and incidence of Disease-Associated Human Papillomavirus types among 15- to 59-Year-Olds in the United States. Sex Trans Dis. 2021;48:273–7. https://doi.org/10.1097/OLQ.0000000000001356.

    Article  Google Scholar 

  25. Suk R, Hong Y-R, Rajan SS, Xie Z, Zhu Y, Spencer JC. Assessment of US Preventive Services Task Force Guideline–Concordant Cervical Cancer Screening Rates and reasons for underscreening by Age, race and ethnicity, sexual orientation, rurality, and insurance, 2005 to 2019. JAMA Netw Open. 2022;5:e2143582. https://doi.org/10.1001/jamanetworkopen.2021.43582.

    Article  PubMed Central  PubMed  Google Scholar 

  26. Bouvard V, Baan R, Straif K, Grosse Y, Secretan B, Ghissassi FE, Benbrahim-Tallaa L, Guha N, Freeman C, Galichet L, et al. Rev Hum Carcinogens—Part B: Biol Agents Lancet Oncol. 2009;10:321–2. https://doi.org/10.1016/S1470-2045(09)70096-8.

    Article  Google Scholar 

  27. Gheit T. Mucosal and cutaneous human papillomavirus infections and Cancer Biology. Front Oncol. 2019;9:355. https://doi.org/10.3389/fonc.2019.00355.

    Article  PubMed Central  PubMed  Google Scholar 

  28. Viens LJ, Henley SJ, Watson M, Markowitz LE, Thomas CC, Thompson TD, Razzaghi H, Saraiya M. Human papillomavirus–Associated Cancers — United States, 2008–2012. MMWR Morb Mortal Wkly Rep. 2016;65:661–6. https://doi.org/10.15585/mmwr.mm6526a1.

    Article  PubMed  Google Scholar 

  29. Den Boon JA, Pyeon D, Wang SS, Horswill M, Schiffman M, Sherman M, Zuna RE, Wang Z, Hewitt SM, Pearson R et al. Molecular Transitions from Papillomavirus Infection to Cervical Precancer and Cancer: Role of Stromal Estrogen Receptor Signaling. Proc. Natl. Acad. Sci. U.S.A. 2015, 112, https://doi.org/10.1073/pnas.1509322112

  30. Zhai Y, Bommer GT, Feng Y, Wiese AB, Fearon ER, Cho KR. Loss of Estrogen Receptor 1 enhances cervical Cancer Invasion. Am J Pathol. 2010;177:884–95. https://doi.org/10.2353/ajpath.2010.091166.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  31. Pagano MT, Ortona E, Dupuis ML. A role for estrogen receptor Alpha36 in Cancer Progression. Front Endocrinol. 2020;11:506. https://doi.org/10.3389/fendo.2020.00506.

    Article  Google Scholar 

  32. Ranganathan P, Nadig N, Nambiar S. Non-canonical Estrogen Signaling in Endocrine Resistance. Front Endocrinol. 2019;10:708. https://doi.org/10.3389/fendo.2019.00708.

    Article  Google Scholar 

  33. Li B, Zhang L, Zhao J, Tan G, Zhang W, Zhang N, Tian J, Qu P. The value of cytokine levels in triage and risk prediction for women with Persistent High-Risk Human Papilloma Virus infection of the Cervix. Infect Agents Cancer. 2019;14:16. https://doi.org/10.1186/s13027-019-0231-z.

    Article  CAS  Google Scholar 

  34. Nguyen HH, Broker TR, Chow LT, Alvarez RD, Vu HL, Andrasi J, Brewer LR, Jin G, Mestecky J. Immune responses to human papillomavirus in genital tract of women with cervical Cancer. Gynecol Oncol. 2005;96:452–61. https://doi.org/10.1016/j.ygyno.2004.10.019.

    Article  CAS  PubMed  Google Scholar 

  35. Hammes L, Tekmal R, Naud P, Edelweiss M, Kirma N, Valente P, Syrjanen K, Cunhafilho J, Macrophages. Inflammation and risk of cervical intraepithelial neoplasia (CIN) progression—clinicopathological correlation. Gynecol Oncol. 2007;105:157–65. https://doi.org/10.1016/j.ygyno.2006.11.023.

    Article  CAS  PubMed  Google Scholar 

  36. Lagenaur LA, Hemmerling A, Chiu C, Miller S, Lee PP, Cohen CR, Parks TP. Connecting the dots: translating the vaginal Microbiome into a drug. J Infect Dis. 2021;223:S296–306. https://doi.org/10.1093/infdis/jiaa676.

    Article  CAS  PubMed  Google Scholar 

  37. Stevanović S, Pasetto A, Helman SR, Gartner JJ, Prickett TD, Howie B, Robins HS, Robbins PF, Klebanoff CA, Rosenberg SA, et al. Landscape of Immunogenic Tumor Antigens in successful immunotherapy of Virally Induced Epithelial Cancer. Science. 2017;356:200–5. https://doi.org/10.1126/science.aak9510.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  38. Wang J, Chitsaz F, Derbyshire MK, Gonzales NR, Gwadz M, Lu S, Marchler GH, Song JS, Thanki N, Yamashita RA, et al. The conserved domain database in 2023. Nucleic Acids Res. 2023;51:D384–8. https://doi.org/10.1093/nar/gkac1096.

    Article  CAS  PubMed  Google Scholar 

  39. Okonechnikov K, Golosova O, Fursov M. The UGENE team Unipro UGENE: a unified Bioinformatics Toolkit. Bioinformatics. 2012;28:1166–7. https://doi.org/10.1093/bioinformatics/bts091.

    Article  CAS  PubMed  Google Scholar 

  40. Trifinopoulos J, Nguyen L-T, von Haeseler A, Minh BQ, W-IQ-TREE. A fast online phylogenetic Tool for Maximum Likelihood Analysis. Nucleic Acids Res. 2016;44:W232–5. https://doi.org/10.1093/nar/gkw256.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  41. Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: Molecular Evolutionary Genetics Analysis across Computing platforms. Mol Biol Evol. 2018;35:1547–9. https://doi.org/10.1093/molbev/msy096.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  42. Muhire BM, Varsani A, Martin DP, SDT. A virus classification Tool based on pairwise sequence alignment and identity calculation. PLoS ONE. 2014;9:e108277. https://doi.org/10.1371/journal.pone.0108277.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  43. Edgar RC, MUSCLE. A multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics. 2004;5. https://doi.org/10.1186/1471-2105-5-113.

  44. Felsenstein J. Evolutionary trees from DNA sequences: a Maximum Likelihood Approach. J Mol Evol. 1981;17:368–76. https://doi.org/10.1007/BF01734359.

    Article  CAS  PubMed  Google Scholar 

  45. Tommasino M. The Biology of Beta Human papillomaviruses. Virus Res. 2017;231:128–38. https://doi.org/10.1016/j.virusres.2016.11.013.

    Article  CAS  PubMed  Google Scholar 

  46. Ganti K, Broniarczyk J, Manoubi W, Massimi P, Mittal S, Pim D, Szalmas A, Thatte J, Thomas M, Tomaić V, et al. The human papillomavirus E6 PDZ binding motif: from life cycle to Malignancy. Viruses. 2015;7:3530–51. https://doi.org/10.3390/v7072785.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  47. Giarrè M, Caldeira S, Malanchi I, Ciccolini F, Leão MJ, Tommasino M. Induction of pRb degradation by the human papillomavirus type 16 E7 protein is essential to efficiently overcome p16INK4a-Imposed G1 cell cycle arrest. J Virol. 2001;75:4705–12. https://doi.org/10.1128/JVI.75.10.4705-4712.2001.

    Article  PubMed Central  PubMed  Google Scholar 

  48. Harden ME, Munger K. Human papillomavirus Molecular Biology. Mutat Research/Reviews Mutat Res. 2017;772:3–12. https://doi.org/10.1016/j.mrrev.2016.07.002.

    Article  CAS  Google Scholar 

  49. Van Doorslaer K. Evolution of the Papillomaviridae. Virology. 2013;445:11–20. https://doi.org/10.1016/j.virol.2013.05.012.

    Article  CAS  PubMed  Google Scholar 

  50. Kombe Kombe AJ, Li B, Zahid A, Mengist HM, Bounda G-A, Zhou Y, Jin T. Epidemiology and Burden of Human Papillomavirus and Related diseases, Molecular Pathogenesis, and vaccine evaluation. Front Public Health. 2021;8:552028. https://doi.org/10.3389/fpubh.2020.552028.

    Article  PubMed Central  PubMed  Google Scholar 

  51. Mittal R, Tsutsumi K, Pater A, Pater MM. Human papillomavirus type 16 expression in cervical keratinocytes: role of progesterone and glucocorticoid hormones. Gynecol Oncol. 1993;81:5–12.

    CAS  Google Scholar 

  52. Strehler E, Sterzik K, Malthaner D, Hoyer H, Nindl I, Schneider A. Influence of ovarian stimulation on the detection of human papillomavirus DNA in cervical scrapes obtained from patients undergoing assisted reproductive techniques. Fertil Steril. 1999;71:815–20.

    Article  CAS  PubMed  Google Scholar 

  53. Zullo F, Fiano V, Gilio-Tos A, Leoncini S, Nesi G, Macri L, Preti M, Rolfo A, Benedetto C, Revelli A, De Marco L. Human papillomavirus infection in women undergoing in-vitro fertilization: effects on embryo development kinetics and live birth rate. Reproductive Biology Endocrinol. 2023;21:39–46.

    Article  Google Scholar 

  54. Burchell AN, Winer RL, De Sanjosé S, Franco EL. Chapter 6: Epidemiology and Transmission Dynamics of Genital HPV Infection. Vaccine 2006, 24, S52–S61, https://doi.org/10.1016/j.vaccine.2006.05.031

  55. Dickson EL, Vogel RI, Geller MA, Downs LS. Cervical cytology and multiple type HPV infection: a study of 8182 women ages 31–65. Gynecol Oncol. 2014;133:405–8. https://doi.org/10.1016/j.ygyno.2014.03.552.

    Article  PubMed Central  PubMed  Google Scholar 

  56. Liu S, Li Y, Song Y, Wu X, Baloch Z, Xia X. The diversity of vaginal microbiome in women infected with single HPV and multiple genotype HPV infections in China. Front Cell Infect Microbiol. 2022;12:642074. https://doi.org/10.3389/fcimb.2022.642074.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  57. Hariri S, Unger ER, Sternberg M, Dunne EF, Swan D, Patel S, Markowitz LE. Prevalence of Genital Human Papillomavirus among females in the United States, the National Health and Nutrition Examination Survey, 2003–2006. J Infect Dis. 2011;204:566–73. https://doi.org/10.1093/infdis/jir341.

    Article  PubMed  Google Scholar 

  58. Meiring TL, Mbulawa ZZA, Lesosky M, Coetzee D, Williamson A-L. Alta diversidade de papilomavírus humanos alfa, beta e gama em amostras genitais de Homens Sul-Africanos Heterossexuais HIV negativos e HIV positivos. Pesquisa Sobre Papilomavírus. 2017;3:160–7. https://doi.org/10.1016/j.pvr.2017.05.001.

    Article  Google Scholar 

  59. Arroyo Mühr LS, Eklund C, Dillner J. Misclassifications in human papillomavirus databases. Virology. 2021;558:57–66. https://doi.org/10.1016/j.virol.2021.03.002.

    Article  CAS  PubMed  Google Scholar 

  60. Murahwa AT, Meiring TL, Mbulawa ZZA, Williamson A-L. Complete genome sequences of four Novel Human Gammapapillomavirus types, HPV-219, HPV-220, HPV-221, and HPV-222, isolated from Penile skin swabs from South African men. Genome Announc. 2018;6:e00584–18. https://doi.org/10.1128/genomeA.00584-18.

    Article  PubMed Central  PubMed  Google Scholar 

  61. NISC Comparative Sequencing Program, Tirosh O, Conlan S, Deming C, Lee-Lin S-Q, Huang X, Su HC, Freeman AF, Segre JA, Kong HH. Expanded skin virome in DOCK8-Deficient patients. Nat Med. 2018;24:1815–21. https://doi.org/10.1038/s41591-018-0211-7.

    Article  CAS  Google Scholar 

  62. Van Doorslaer K. Revisiting Papillomavirus Taxonomy: a proposal for updating the current classification in line with evolutionary evidence. Viruses. 2022;14:2308. https://doi.org/10.3390/v14102308.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

Download references

Acknowledgements

We thank the Pró-rhetoric de Pesquisa e pós-graduação of UFPA for supporting the publication costs.

Funding

EdSFR is supported by a scholarship provided by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES). ACdC is supported by a scholarship from HCFMUSP with funds donated by NUBANK under the #HCCOMVIDA scheme.

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization, S.S.W.; methodology, T.R.R.M; P.B; E.M.G.B; I.M.L; S.S.W.; formal analysis, E.d.S.F.R; investigation, P.B; N.EF; S.D.S; M.C.M.C.; data curation, E.d.S.F.R.; writing—original draft preparation, E.d.S.F.R; R.d.S.C, E.L; writing—review and editing, E.L; A.C.d.C; M.C.MC; S.S.W; supervision, E.L; A.C.d.C; M.C.MC; S.S.W ; funding acquisition, M.C.M.C.

Corresponding authors

Correspondence to Antonio Charlys da Costa, Elcio Leal, Maria Cassia Mendes-Correa or Steven S. Witkin.

Ethics declarations

Ethics approval and consent to participate

The study was conducted by the 1975 Declaration of Helsinki (https://www.wma.net/what-we-do/medical-ethics/declaration-of-helsinki/, accessed on 9 February 2024). The project was approved by the Institutional Review Board at Weill Cornell Medicine, protocol number 20-04021885, in October 2022.

Consent for publication

Not applicable.

Conflict of interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Foro Ramos, E., da Silva Couto, R., Tozetto-Mendoza, T.R. et al. Characterization of multiple human papillomavirus types in the human vagina following ovarian hormonal stimulation. Virol J 21, 229 (2024). https://doi.org/10.1186/s12985-024-02507-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12985-024-02507-7

Keywords