Abstract
Introduction
Interaction between HIV and human papillomavirus (HPV) increases the risk of HPV persistence. However, a few studies have explored the interplay between host genetic factors and HPV in women living with HIV (WLWH). We report on a study investigating the role of TP53 mutations among HPV DNA-positive cervical and vulvar tissue from Zimbabwean WLWH.
Methods
This cross-sectional study recruited 102 WLWH aged over 18 years, with histologically confirmed vulvar (n = 13) or cervical disease (n = 89). Vulvar or cervical tissue biopsies, preserved in formalin-fixed paraffin-embedded (FFPE) blocks, were retrieved. Tumour DNA was extracted and analyzed for 17 HPV genotypes using the ATILA multiplex system. The DNA was also examined for TP53 variants located in codon 72 and 47 using Sanger sequencing. Associations between HPV genotypes and TP53 variants were assessed using logistic regression.
Results
The histological classifications had the following proportions: cervical intraepithelial neoplasia (CIN)1: 10%, CIN2: 4.5%, CIN3: 82%, and cervical cancer: 3.4%. Vulvar disease was classified as: vulvar intraepithelial neoplasia (VIN)3: 84.6%, and vulvar cancer (15.4%). HPV16 prevalence was 40% and 64% in vulvar tissue. Codon 72G and codon 47 T alleles had frequencies of 34.1% and 2.9% in cervical tissue, and 29.2% and 4.2% in vulvar tissue, respectively. There was no significant association between TP53 codon 72 and 47 mutations, and HPV genotypes (p > 0.05).
Discussion and Conclusion
These findings underscore the need to conduct further research to identify other genetic variants within the TP53 gene that may contribute to the role of TP53 in HPV susceptibility that has been previously reported in other studies.
Keywords: HIV, HPV, HIV opportunistic infections, cervical cancer, vulvar cancer, Sub-Saharan Africa, CIN, VIN
Introduction
Human papillomavirus (HPV) commonly infects the reproductive tract of sexually active individuals (1). The persistence of some human papillomavirus genotypes in the cervix and anogenital regions leads to the development of cervical and a subset of anogenital cancers including vulvar, anal and vaginal (2). HPV genotypes, that are classified as high-risk, account for >95% of cervical cancers, and up to 75% of vulvar cancers (3, 4). Both cervical and vulvar cancers greatly threaten the health of women living in sub-Saharan Africa (SSA), leading to death if not diagnosed and treated early (5).
Only less than 1% of HPV-infected individuals develop HPV-related cancers in their lifetime, indicating the need for investigating factors involved in carcinogenesis. A primary example is the Human Immunodeficiency Virus (HIV), an established driver of HPV persistent infections, that significantly increases the risk of carcinogenesis (6–8). Women living with HIV (WLHIV) are at a 4-fold and 6-fold higher risk of acquiring HPV and developing HPV-related cancers, respectively, compared to HIV-uninfected women (9, 10). Furthermore, infection with hrHPVs increases the risk of HIV acquisition, on account of the highly inflammatory vaginal environment that is induced by HPV positivity (11).
In the pathogenesis of high-risk HPV, oncoproteins E6 and E7 target tumour suppressor proteins such as TP53 and pRb, respectively, to dysregulate the normal protein activity. Of great interest to this study is TP53, which is key to cell cycle regulation by repairing DNA damage, initiating apoptosis, and modulating cell proliferation, all of which, when deregulated, are hallmarks of cancer (12). Therefore, variations in the TP53 genome sequence can be useful biomarkers for hrHPV persistence and cervical cancer.
The highly conserved DNA binding domain of TP53, exons 5–8, has been frequently described as the hotspot for mutations within the gene. The most widely researched is the TP53 codon 72 single nucleotide polymorphism (SNP), which results in the substitution of the amino acid proline with arginine in a proline-rich region (13). The TP53 codon 72 G allele translates to a less stable p53 isoform that is more susceptible to degradation, compared to the wild type (C allele). The TP53 codon 72 G is associated with higher apoptosis, increased DNA repair mechanisms and an overall decreased genomic instability – potentiating the decreased risk of carcinogenesis (14). However, there has been conflicting data on the role of TP53 codon 72 in hrHPV infection, persistence and cervical carcinogenesis in different populations and sub-populations. As a result, the relationship between TP53 codon 72 and HPV or cervical cancer is still unknown, prompting the need for further research in diverse populations.
Moreover, there is limited data on the role of other genetic variants within the conserved region of TP53, such as at the codon 47 position. The exact functional role of the TP53 codon 47 is not well understood; however, this variant has been reported to be prevalent in African populations and has shown the potential of modulating the functionality of the p53 protein. The dearth of available data coupled with the evidence of genetic diversity of African populations calls to attention the need to describe genetic factors of HPV among African populations where HIV is endemic and there are limited diagnostic and screening tools.
The present study aims to determine the frequency of genetic variants in TP53 (codon 72 and 47) in Zimbabwean WLWH with cervical and vulvar disease, and determine their association with HPV positivity. This study builds on previous data where genetic variants were associated with HPV positivity, however, no association between TP53 codon 72 and HPV was reported (15). In the present study, we employ robust genetic characterisation methods to detect TP53 genetic variants among WLWH, and investigate the understudied codon 47 variant which has been detected mostly among African populations. This study is of significance because WLWH in Zimbabwe have higher HPV prevalence (16) higher prevalence of oncogenic HPV infection (17), and a more diverse HPV profile compared to HIV negative women (18). Determining genetic variants associated with HPV is an important step to identifying biomarkers that can be used to screen WLWH that are more prone to HPV related cancers, to administer preventive measures, towards better health outcomes.
Materials and methods
Study design and setting
This cross-sectional study recruited participants from Newlands Clinic, an HIV care and treatment centre located in Harare, Zimbabwe. Participants’ biospecimens were retrieved from Lancet Pathologies, CIMAS diagnostics and Baines private laboratories, and were sectioned at the University of Zimbabwe Faculty of Medicine and Health Sciences, Histopathology unit. Biospecimen analyses were done at the University of Cape Town, Human Genetics Division, in South Africa.
Ethical approval and informed consent
All study procedures were in accordance with the Helsinki Declaration of 2013. Ethical approvals were obtained from the Medical Research Council of Zimbabwe (MRCZ/A/2396) and the Research Council of Zimbabwe (Permit number: 03879). All participants were administered information to participate verbally by the research assistant and provided the informed consent form to read through. We obtained consent to participate in writing. Consent was administered in English or Shona (the main native language spoken in the city spoken in Harare).
Inclusion/exclusion criteria
Women who were aged at least 18 years, sexually active, HIV-1 positive, and reporting for HIV antiretroviral therapy and management of opportunistic infections were eligible for recruitment into this study. To be included in the study, women had to have histologically confirmed diagnoses of cervical and/or vulvar pre-cancer and cancer lesions, with respective biopsies collected through Newlands Clinic between 2016 and 2019. Individuals failing to meet these criteria and being unable to give written informed consent were excluded from the study.
Study participants
At enrolment, the participant's data such as age, histological diagnosis, and disease stage were collected from their clinical records. To maintain confidentiality, participant data were deidentified, and all participants were assigned a unique identifier, that was used to associate their data to the respective biospecimen throughout the study.
Biospecimen retrieval
Archived and deidentified formalin-fixed paraffin-embedded (FFPE) blocks were retrieved and sectioned to 3–4 µm scrolls that were placed into two separate cryotubes tubes assigned with the respective unique identifiers. Histology slides were prepared at the beginning and end of sectioning each block, and a Histopathologist from Parirenyatwa hospital confirmed that the sectioned scrolls had tumour tissue using the haematoxylin and eosin stain.
Genomic DNA extraction and quality check
Genomic DNA was extracted from each cryotube with FFPE scrolls, using a modified protocol from Zymo genomic DNA extraction kit for FFPE, utilizing a slightly modified protocol (Zymo Research, California, USA). Briefly, a xylene-based deparaffinization solution was used to remove the paraffin layer, and the tissue was digested for 12 h using 10 mg/mL Proteinase K (Zymo Research, California, USA). The DNA was bound to a Spin Column, washed in 70% ethanol, and eluted in DNA/RNA-free water. Quantity and quality of DNA were checked using a NanodropTM Spectrophotometer ND-1000 (NanodropTM, ThermoFisher, Denver, USA). Absorbances at 230 nm, 260 nm and 280 nm were used to compute the purity of the extracted DNA. Only DNA that had absorbance ratios for 230/260 and 260/280 ratios of 1.8–2.0 were included in this study for further analysis.
HPV genotyping
DNA was used to genotype 17 HPVs, using the ATILA Genotyping Fluorescent High-risk HPV Detection Kit (ATILA Biosystems, USA), as described in the manufacturer's protocol. Only samples with a positive amplification of the internal beta-globin control (IC+) were considered for further analysis.
Characterisation of TP53 codons 47 and 72
Genomic DNA was characterised for the loci of interest using Sanger Sequencing. Amplification of TP53 exon 4 was done using the International Agency Research on Cancer (IARC) designed primers (IARC protocol, 2019): 5’-TGCTCTTTTCACCCATCTAC-3’ (forward) and 5’- ATACGGCCAGGCATTGAAGT-3’ (reverse primer) (Inqaba Biotechnical Industries, Pretoria, South Africa). A 25μl PCR reaction mix with 1 ng/µL template DNA, 5X Green Go Taq Reaction Buffer (Promega Cooperation, Madison, USA), 5 mM dNTPs (Kappa Biosystems, Cape Town, South Africa), 5U/µL Go Taq Polymerase (Promega Illinois, USA), 25 mM MgCl2 (Thermo Scientific, Waltham, USA), 100 µM forward primer, 100 µM reverse primer was run in an Applied Biosystems SimpliAmpTM Thermal Cycler (Thermo Scientific, USA). Thermocycling conditions were initial denaturation at 95°C for 3 min followed by 35 cycles of denaturation at 95°C for 30 s; annealing at 55.7°C for 30 s; and extension at 72°C for 1 min; and a final extension at 72°C for 5 min. Unbound PCR reagents were removed from the PCR templates using FastAp™ Thermosensitive Alkaline Phosphatase (FastAPTM) and Exonuclease I (ExoITM) (Thermo Scientific, Waltham, USA). The Big-Dye Terminator V3.1 cycle sequencing kit (Life Technologies, CA, USA) was used for sequencing following the manufacturer's protocol. The ethanol/EDTA precipitation was used for the template purification, and highly de-ionized formamide was used to denature DNA in preparation for electrokinetic injection in the ABI 3130 Genetic Analyzer capillary (ThermoFisher Scientific, New York, USA), using the POP-7TM polymer with 80 cm capillary length protocol.
Data analyses
STATA/BE 17.0 (StataCorp LLC, Station College, TX, USA) was used to analyse data. Demographic and HPV prevalence data were assigned into continuous or categorical data. Continuous data were expressed into mean ± standard deviation while categorical data were expressed into absolute/relative frequencies, respectively. Unpaired T-tests and Wilcoxon's unparametric T-tests were applied to compare continuous and categorical data. Chromas Pro Ver 2.0 (Technelysium, Australia) was used to visualise, assemble, and analyse TP53 Exon 4 chromatograms. Adherence of the SNPs to Hardy Weinberg equilibrium was tested using the Pearson's chi-square test. Linkage disequilibrium and haplotype analysis were evaluated using SHEsis. SHEsis was also used to calculate genotypic and allelic frequencies of the two SNPs being investigated. GraphPad PrismTM version 8.0.2 (GraphPadTM Software Inc., San Diego, California, USA) was used for bivariate analysis where the association between allelic variants and phenotypes for two groups was done using the unpaired non-parametric t-test and for more than two groups was done using One-way ANOVA T-test. A value of P < 0.05 was considered to indicate a statistically significant result. Statistical power analysis of the study was done using post-hoc Power Calculator from ClinCalc (ClinCalc LLC, Illinois, USA). Descriptive analysis and correlation matrix with Pearson coefficient was performed using the Jamovi statistical program version 2.2. Ggplot2 3.3.3 treemap 2.4–2 and ComplexUpset were used for graphics under R software 4.1.0. The R function (glm) was used to calculate the logistic regression (family = binomial (link = “logit”) controlling for age. rs1800371 (CC, CT), rs1042522 (CC, CG, GG) have been tested against each infection group [High-risk, Low-risk, Quadrivalent vaccine (6/11/16/18), 16/18, Mono-infections, Multiple infections, HPV 16, HPV 18, HPV 31, HPV 33, HPV 35, HPV 39, HPV 45, HPV 51, HPV 52, HPV 53, HPV 56, HPV 58, HPV 59, HPV 66, HPV 68, HPV 6, HPV 11]. Adjusted odds ratios, 95% confidence intervals and p-values were used to determine significance.
Results
This cohort was made up of 102 WLWH, 89 (87%) with cervical disease (pre-cancerous + cancerous) and 13 (13%) with vulval disease (precancerous + cancerous). The overall mean age for the cohort was 43 years (SD = 9), with an age range of 25 to 64 years (Table 1). The distribution of cervical disease was cervical intraepithelial neoplasia (CIN) 1 (10.1%), CIN2 (4.5%), CIN3 (82%) and invasive cervical cancer (3.4%). All participants with vulval disease either presented with VIN3 (84.6%) or cancer (15.4%). Two (2%) participants had both CIN3 and vulval cancer. Age and histopathological stage were not associated with cervical or vulval disease.
Table 1.
Demographic characteristics of participants in the study (n = 102).
| Characteristic | Cervical (%) (n = 89) | Vulvar (%) (n = 13) | Dual site (%) (n = 2) | p -value a |
|---|---|---|---|---|
| Age: | ||||
| 0–30 years | 8 (9.0) | 0 (0.0) | ||
| 31–40 years | 28 (31.5) | 8 (61.5) | 2 (100.0) | |
| 41–50 years | 34 (38.2) | 4 (30.8) | ||
| 51–60 years | 16 (18.0) | 1 (7.7) | ||
| 61–70 years | 3 (3.3) | 0 (0.0) | ||
| Mean ± SD | 43 ± 9 years | 39 ± 7 years | 0 . 081 | |
| Disease stage: | ||||
| Cervical: | ||||
| CIN1 | 9 (10.1) | – | ||
| CIN2 | 4 (4.5) | – | ||
| CIN3 | 73 (82.0) | -– | 2 (100.0) | |
| Cervical cancer | 3 (3.4) | |||
| Vulvar: | ||||
| VIN 3 | – | 11 (84.6) | – | |
| Vulval cancer | – | 2 (15.4) | 2 (100.0) | |
CIN, cervical intraepithelial neoplasia; VIN, vulval intraepithelial neoplasia. Total sample size: HPV genotyping were performed for the 102 WLWH enrolled in this study. Of these, 100 biospecimens were successfully genotyped, and two cervical tissue were excluded from further analysis because, there was failure to detect the beta-globin internal control. Therefore, this study is comprised of cervical tissue n = 87; vulvar tissue n = 13.
Comparison between cervical and vulval disease Dual-site cases refer to participants with lesions identified at more than one anatomical site.
HPV genotyping were performed for the 102 WLWH enrolled in this study. Of these, 100 biospecimens were successfully genotyped, and two cervical tissue were excluded from further analysis because, there was failure to detect the beta-globin internal control. Therefore, this study is comprised of cervical tissue n = 87; vulvar tissue n = 13. Distribution of HPV genotypes by location is summarised in Figure 1. The overall prevalence of HPV DNA was 75% in cervical tissue and 85% in vulvar tissue. HPV 16 was the most common genotype detected in both cervical tissue (40%; n = 26/65) and vulvar tissue (64%; n = 7/11). Other commonly observed genotypes in cervical tissue included HPV 18 (22%), HPV 52 (20%), HP V35 (15%) and HPV 58 (15%). In vulvar tissue HPV 31 (2%), HPV 66 (2%), HPV 33 (1%), HPV 6 (1%) and HPV 11 (1%) were detected. From the 3 WLWH presenting with confirmed cervical cancer, multiple infections with HPVs 16, 45 and 58 were detected. While the 2 patients with vulvar cancer presented with multiple infection with HPVs 16, 18, 33, 35, and 52. Eight HPV types were detected only in cervical tissue, high-risk HPV types: 58, 45, 39, 51, 53, 59, 68 and low-risk type: HPV 6. HPV 66 was exclusive to two vulvar samples. Twenty-two samples were positive for HPV consensus DNA but were not positive for any of the specific genotypes included in the assay.
Figure 1.
Distribution of HPV genotypes among women living with HIV that presented with cervical (n = 65) and vulvar (n = 11) precancerous and cancerous lesions.
Forty WLWH (40%) presented with multiple HPV genotypes (Table 2). The highest number of HPV co-infections observed in 2 cervical tissues was 5.
Table 2.
Number of HPV infections detected in cervical and vulvar samples (n = 100).
| Number of HPV types | Cervical (%) (n = 87) | Vulvar (%) (n = 13) |
|---|---|---|
| 0 | 22 (25.3) | 2 (15.3) |
| 1 | 31 (35.6) | 5 (38.5) |
| 2 | 23 (26.4) | 5 (38.5) |
| 3 | 6 (6.9) | 1 (7.7) |
| 4 | 3 (3.5) | 0 (0) |
| 5 | 2 (2.3) | 0 (0) |
Total sample size: HPV genotyping were performed for the 102 WLWH enrolled in this study. Of these, 100 biospecimens were successfully genotyped, and two cervical tissue were excluded from further analysis because, there was failure to detect the beta-globin internal control. Therefore, this study is comprised of cervical tissue n = 87; vulvar tissue n = 13.
The distribution of HPV infections stratified by age and diagnoses were computed (Figure 2). Sixteen percent (n = 16) of WLWH had HPV 16 mono-infections, while 3% (n = 3) had HPV 35 and 52 mono-infections, and 2% (n = 2) were infected with HPV 18. HPVs 16 (17%, n = 17), 18 (12%, n = 12), and 52 (9%, n = 9) were the most common multiple infections detected in both cervical samples. Analyses of the profiles for the 2 WLWH with both vulvar cancer and CIN3 showed the presence of HPV genotypes 18, 33, and 52 DNA in tissue from both vulvar and cervix’ woman 1’ and HPVs 16 and 35 DNA positivity in both sites of ‘woman 2’. Both participants with CIN3 and vulvar cancer were aged between 31 and 40 years old. The two WLWH infected by HPV 66 were under the 31–40 years age category and also diagnosed with VIN3. Four percent (n = 4) WLWH were positive for HPV 11 DNA (n = 3 cervical, n = 1 vulvar). Among these cases, two women had a single HPV 11 infection and were aged between 31 and 50 years old and either diagnosed CIN1 or VIN3. The distribution of distinct HPV genotypes were comparable by age (p > 0.05), except for HPV 18 (p < 0.05) Supplementary Figure 1.
Figure 2.
Upset plot of genotype distribution by age group and diagnosis. This figure illustrates the intersection of genotyping profiles for 102 samples analyzed across 17 different HPV targets. The identified genotypes are included in the intersection matrix. Each row of this matrix is dedicated to a specific HPV type, with ‘HPV detected’ indicating positive HPV detection in 100 of the samples. The vertical columns represent a total of 46 genotype combinations. The bar plot on the left displays the number of cases with frequencies in cervical or vulvar regions. The frequency bar plot for each genotype is color-coded by age group. Additionally, a stacked bar plot presents the distribution of diagnoses, with the number of cases indicated within each subgroup.
TP53 tumour tissue mutation characterization was successfully performed for 69 cervical and 12 vulvar tissue samples. The remaining samples (n = 21) were excluded for failure to amplify. The distribution of the rs1800371 (codon 47) and rs1042522 (codon 72) haplotype variants in cervical and vulval tissue showed that the CC/CG haplotype was most common in cervical (33.7%) and vulval tissue (38.5%) (Figure 3). The variant allele frequencies (VAFs) for codon 47 and codon 72 were comparable in both cervical (p = 0.700) and vulval tissue (p = 0.446). Both SNPs were in Hardy-Weinberg Equilibrium (HWE) in both cervical and vulval tissue (Table 3).
Figure 3.
Stacked bar chart showing the percentage distribution of rs1800371/rs1042522 variant combinations in cervical tissue (69 samples) and vulvar tissue (12 samples) with the relative frequencies of each combination.
Table 3.
Allelic and genotype frequencies of TP53 exon 4 codon 47 (rs1800371) and codon 72 (rs1042522) for cervical and vulvar samples (n = 81).
| Disease | N | SNP | Variant allele frequency | Genotype frequency | HWE p-value | ||
|---|---|---|---|---|---|---|---|
| Cervical | 69 | Codon 47 | T | CC | CT | TT | |
| (rs1800371) | 0 . 029 | 0 . 942 | 0 . 058 | 0 | 0 . 804 | ||
| 69 | Codon 72 | G | CC | CG | GG | ||
| (rs1042522) | 0 . 341 | 0 . 435 | 0 . 449 | 0 . 116 | 0 . 998 | ||
| Vulvar | 12 | Codon 47 | T | CC | CT | TT | |
| (rs1800371) | 0 . 042 | 0 . 917 | 0 . 083 | 0 | 0 . 880 | ||
| 12 | Codon 72 | G | CC | CG | GG | ||
| (rs1042522) | 0 . 292 | 0 . 500 | 0 . 417 | 0 . 083 | 0 . 977 | ||
Univariate regression analyses showed that none of the genetic polymorphisms in TP53 were associated with vulval disease (Supplementary Table S1). Heterozygote carriers of TP53 codon 47 (rs1800371 CT) were protected against type specific HPV DNA positivity, namely HPV 16 (OR = 0.1; 95% CI = 0.0–0.4; p = 0.001), HPV18 (OR = 0.1; OR = 0.0–0.6; p = 0.017), HPV52 (OR = 0.1; 95% CI = 0.0–0.9; p = 0.037) in univariate regression. While TP53 codon 72 (rs1042522) GG was a protective factor against HPV 16 (OR = 0.1; 95% CI = 0.0–0.7; p = 0.01), HPV 18 (OR = 0.1, 95% CI = 0.0- 0.7, p = 0.022) and HPV 52 (OR = 0.1; 95% CI = 0.0–0.9; p = 0.037) in cervical tissue in univariate regression. However, in multivariate regression analyses adjusting for age, histological diagnosis and number of HPVs (Table 4), none of the TP53 genetic polymorphisms were associated with any of the HPV genotypes (p > 0.05).
Table 4.
Multivariate regression analyses associating the distinct HPV genotypes with TP53 host genetic polymorphisms.
| Predictor/Covariate | aOR (95% CI) | P -value |
|---|---|---|
| HPV 16 (R2 = 0.2182) | 0.0037(global) | |
| Age | 1.0 (0.9–1.1) | 0.658 |
| Histological Diagnosis | NA | NA |
| Number of HPV types | 2.6 (1.4–5.1) | 0.05 |
| Tp53 codon 47 | 1.6 (0.1–19.4) | 0.715 |
| Tp53 codon 72 | 0.4 (0.0–22.0) | 0.321 |
| HPV 18 (R2 = 0.3101) | 0.001(global) | |
| Age | 0.9 (0.8–1.1) | 0.534 |
| Histological Diagnosis | 0.9 (0.3–2.2) | 0.753 |
| Number of HPV types | 3.2 (1.5–6.8) | 0.003* |
| Tp53 codon 47 | 1.2 (0.03–46.1) | 0.905 |
| Tp53 codon 72 | 1.0 (0.3–3.3) | 0.997 |
| HPV 31 (R2 = 0.1827) | 0.48 (global) | |
| Age | 1.0 (0.8–1.1) | 0.71 |
| Histological Diagnosis | 2.2 (0.08–62.3) | 0.65 |
| Number of HPVs | 1.7 (0.6–4.4) | 0.28 |
| Tp53 codon 47 | 14.8 (0.6–339.4) | 0.09 |
| Tp53 codon 72 | 1.7 (0.2–11.8) | 0.59 |
| HPV 33 (R2 = 0.3024) | 0.06 (global) | |
| Age | 1.0 (0.9–1.2) | 0.63 |
| Histological Diagnosis | 0.5 (0.1–2.0) | 0.31 |
| Number of HPV | 3.1 (1.3–7.5) | 0.01* |
| Tp53 codon 47 | - | - |
| Tp53 codon 72 | 2.1 (0.3–12.7) | 0.43 |
| HPV 35 (R2 = 0.0737) | 0.52 (global) | |
| Age | 1.0 (0.9–1.1) | 0.69 |
| Histological Diagnosis | 1.1 (0.3–4.0) | 0.80 |
| Number of HPVs | 1.7 (0.9–3.1) | 0.09 |
| Tp53 codon 47 | - | - |
| Tp53 codon 72 | 0.0 (0.0–2.9) | 0.11 |
| HPV 39 (R2 = 0.3747) | 0.06 (global) | |
| Age | 1.1 (0.9–1.3) | 0.22 |
| Histological Diagnosis | 2.0 (0.2–23.4) | 0.59 |
| Number of HPVs | 4.5 (1.2–16.7) | 0.03* |
| Tp53 codon 47 | - | NA |
| Tp53 codon 72 | 5.2 (0.6–47.2) | 0.14 |
| HPV 45 (r2 = 0.3301) | 0.02 (global) | |
| Age | 1.0 (0.9–1.2) | 0.95 |
| Histological Diagnosis | 17.1 (0.7–426.2) | 0.08 |
| Number of HPVs | 2.8 (1.2–6.6) | 0.02* |
| TP53 codon 47 | - | - |
| TP53 codon 72 | 4.0 (0.7–23.1) | 0.13 |
| HPV 51 (R2 = 0.2056) | 0.40 (global) | |
| Age | 1.1 (0.9–1.3) | 0.44 |
| Histological Diagnosis | 1.6 (0.2–12.9) | 0.64 |
| Number of HPVs | 2.8 (1.2–6.6) | 0.22 |
| Tp53 codon 47 | - | - |
| Tp53 codon 72 | - | - |
| HPV 52 (R2 = 0.127) | 0.21 (global) | |
| Age | 1.0 (0.9–1.3) | 0.72 |
| Histological Diagnosis | 0.9 (0.3–2.7) | 0.89 |
| Number of HPV types | 1.8 (1.0–3.0) | 0.03* |
| Tp53 codon 47 | 1.6 (0.1–20.1) | 0.71 |
| Tp53 codon 72 | 0.5 (0.1–1.7) | 0.28 |
| HPV 53 (R2 = 0.2073) | 0.45 (global) | |
| Age | 1.0 (0.9–1.2) | 0.71 |
| Histological Diagnosis | 1.8 (0.1–47.6) | 0.72 |
| Number of HPVs | 2.6 (0.8–8.3) | 0.11 |
| Tp53 codon 47 | - | - |
| Tp53 codon 72 | 2.8 (0.3–25.3) | 0.18 |
| HPV 56 (R2 = 0.2182) | 0.45 (global) | |
| Age | 1.1 (1.0–1.2) | 0.09 |
| Histological Diagnosis | 0.6 (0.2–2.4) | 0.48 |
| Number of HPVs | 1.7 (0.9–3.3) | 0.11 |
| Tp53 codon 47 | 2.8 (0.2–36.7) | 0.42 |
| Tp53 codon 72 | 0.4 (0.0–1.5) | 0.25 |
| HPV 58 (R2 = 0.0865) | 0.35 (global) | |
| Age | 1.0 (0.9–1.1) | 0.76 |
| Histological Diagnosis | 0.6 (0.2–1.5) | 0.25 |
| Number of HPVs | 1.7 (1.0–2.9) | 0.07 |
| Tp53 codon 47 | - | - |
| Tp53 codon 72 | 1.4 (0.5–4.2) | 0.55 |
| HPV 59 (R2 = 0.3124) | 0.52 (global) | |
| Age | 0.7 (0.3–1.4) | 0.28 |
| Histological Diagnosis | 14.2 (0.0 – 50.2) | 0.52 |
| Number of HPVs | 0.7 (0.1–4.1) | 0.68 |
| Tp53 codon 47 | - | - |
| Tp53 codon 72 | 6.2 (0.1–386.5) | 0.39 |
| HPV 6 (R2 = 0.0669) | 0.95 (global) | |
| Age | 1.0 (0.8–1.3) | 0.69 |
| Histological Diagnosis | 1.7 (0.0–111.3) | 0.81 |
| Number of HPV types | 1.6 (0.3–7.3) | 0.52 |
| Tp53 codon 47 | - | - |
| Tp53 codon 72 | 2.2 (0.1–37.3) | 0.58 |
| HPV 11 (R2 = 0.5719) | 0.01 (global) | |
| Age | 1.0 (0.9–1.3) | 0.65 |
| Histological Diagnosis | 0.1 (0.0–0.8) | 0.04* |
| Number of HPV types | 5.2 (1.0–26.3) | 0.04* |
| Tp53 codon 47 | - | - |
| Tp53 codon 72 | 728.1 (0.5–123.7) | 0.13 |
Discussion
The primary aim of this study was to investigate the HPV genotype-specific distribution in cervical and vulvar tissue in a group of Zimbabwean women, attending a HIV clinic for monitoring. Furthermore, we investigated the association of TP53 codon 47 and codon 72 polymorphisms with these HPV genotypes detected. To our knowledge, this is one of the first studies from Zimbabwe to explore both viral distribution and host genetic profiles in cervical and vulvar cancer. Building on our previous work examining GSTP, GSTT1, XRCC1, and CASP8 genetic variations in cervical cancer cases using blood samples (15), the current study advances the field by focusing on pre-malignant lesions (CIN1 to CIN3) using FFPE tissue samples. This approach offers novel insights into the genetic underpinnings of HPV-related lesions. We suggest that future research should further investigate sample-related differences in polymorphic analysis to refine our understanding of these associations. HPV genotype profiles for cervical tissue have been widely reported in Zimbabwe for both WLWH and HIV-uninfected women. In the present study, HPVs 16 and 18 were the most reported, corresponding with the published data in Zimbabwe (16–20). Moreover, a high prevalence of genotypes such as HPV 35 (10%), HPV 56 (9%), HPV 39 (3%), HPV 51 (3%) and HPV 53 (2%) was also observed in cervical tissue, in this cohort, even though these HPV genotypes are not incorporated in any of the available HPV prophylactic vaccines. The presence of HPV 35 in WLWH warrants further analyses, given the recent association of this genotype with cervical cancers in different geographic regions (21).
HPV has been associated with the development of a small subset of vulvar lesions and cancer. HPV positivity in the vulvar has been associated with poor prognosis and disease recurrence (22). Even with the high prevalence of HPV in Zimbabwe (17%–27%), especially in WLHIV (33%), there have not many studies analyzing the prevalence of HPV in vulvar tissue in Zimbabwe (19). In this study, 75% and 85% of cervical and vulvar biopsies were positive for HPV DNA respectively. The selected HPV genotyping method inherently reports negative when samples do not have any of the 17 genotypes it assays. It is possible that some samples were positive for HPV DNA but not the genotypes picked by assay and hence HPV positivity can be expected to be higher than 25.3%. Validation for false negatives may have assisted in accurately identifying biospecimens with HPV DNA. In this study, HPV 16 (7%) was the most prevalent genotype in vulvar tissue, consistent with the published literature (23, 24). HPVs 31 (2%), 66 (2%), 11 (1%), 6 (1%), 33 (1%), 56 (1%), 35(1%), 52 (1%) and 18 (1%) were also detected, suggesting that these genotypes may also play a role in the onset or progression of vulvar disease in agreement with previous data (23–25). HPVs 66, 56, and 35 are not encompassed in any available HPV vaccines, potentiating the need to develop broader and inclusive HPV vaccines that can provide adequate protection. Although we are among the first to report on HPV genotypes in vulvar tissue within a Zimbabwean cohort, the prevalence of distinct HPV genotypes observed in this study may not fully represent the burden of HPV in vulvar disease in Zimbabwe, due to the small sample size of vulvar tissue analyzed. Further research is essential to understand better the extent of HPV in vulvar disease, particularly in under-represented and vulnerable populations such as Moreover, the prevalence of the distinct HPV genotypes in vulvar tissue recorded presently may not accurately represent the burden of HPV in vulvar disease in Zimbabwe, on account of the small sample size of vulvar tissue analysed in this study.
Evidence that individuals vaccinated against specific HPV genotypes can be protected against a host of HPV genotypes via immunological cross-protection and cross-reaction has been provided (26). Factors such as HPV phylogenetic diversity, immune suppression, and duration since vaccination also affect cross-protection (27). In our data, the diverse HPV genotypes detected, may potentiate limited protection provided by the vaccines in heterogenous populations such as the topical cohort. Moreover, in Zimbabwe the HPV vaccination program began in 2018, administering the bivalent vaccine that targets HPV 16/18 and there has been conflicted data on the duration of protection elicited by this bivalent vaccine obtained from other countries (28–30). With the evidence of the diverse HPV genotype profile observed in Zimbabwe, it may be of greater benefit to consider administering the more diverse nanovalent HPV vaccine. Taken together, these data point to the essentiality of developing an African-specific HPV vaccine to ensure maximal coverage of HPV genotypes that are prevalent in Africa, protection of these populations who are burdened with HIV and are at a much greater risk of HPV acquisition and persistence compared to other populations.
This study also described the association of two genetic polymorphisms in the tumour suppressor gene, TP53, (codon 72 and 47) with distinctive HPV genotypes in cervical and vulvar tissue. The TP53 codon 72 has been widely studied in relation to HPV and related diseases, and, in our study population, there was no association between TP53 codon 72 G with any of the HPVs. Our findings are consistent with a previous study from Zimbabwe (31), and some data obtained from African and Asian populations (22, 32, 33). Contrastingly, data from Bangladesh found TP53 C to be associated with cervical cancer risk (34). However, in TP53 codon 72 G has been associated with cervical precancerous lesion, and cancer among Tunisian (35).
Although we were unable to compare frequency of the variant with normal tissue, the frequency of TP53 codon 72 polymorphism in our precancerous lesions did not differ much from frequencies in healthy African individuals as previously reported elsewhere and in public databases like dbSNP (36). Interestingly, enough data obtained from populations of European ancestry has been largely conflicted, with some studies reporting a lack of association in agreement with our study, while other contradicting studies have found a strong association between TP53 codon 72 G and HPV persistence or cervical cancer (37, 38). The antithetic relationship between TP53 codon 72 and HPV/cervical cancer can be attributed to differences in the frequency of the G observed in different population groups (39). In this study, the average G allele frequency was 32%, which is significantly lower than the frequencies reported in European (78%) and Asian (60%) ancestry populations (35). Genetic interactions with environmental factors such as distance from the equator, latitude and ecological adaptation can lead to allelic variation in different ethnic groups (39, 40). Therefore, in some populations, variants such as the TP53 codon 72 G may have significant functionality in some populations, but not others. Therefore, variants such as TP53 codon 72 may not be useful as universal HPV biomarkers but are instead population-specific.
The data presented here also reports on a 2.9% prevalence of TP53 codon 47 T allele in cervical tissue, and 4.2% in vulvar tissue, resonating with other African population data (41–43). The codon 47 variant is described as “African-centric” for its presence among African populations (up to 8%), which is higher than what has been observed in African Americans (1.2%), Finnish Europeans (0%) and Caucasian Americans (0%) (41–43). We found no association between TP53 at codon 47 (rs1800371) and HPV reported in this study, resonating with data conducted on Bangladeshi women (44). Further studies are needed to identify genetic variants in TP53 that may increase the role of this gene in cancer susceptibility and prognosis.
Study limitations
One limitation of this study was that we analysed samples that were available, potentially limiting the power of the study. In future, we will conduct effective sample size calculation to ensure sufficient study power. As a result, we interrogated a small sample size, particularly for vulvar tissue, which resulted in wide confidence intervals in the association analyses for vulvar data. Future studies with larger sample sizes are needed to explore potential biomarkers for HPV-related vulvar disease better. Our study did not evaluate or control for important factors such as viral load, CD4/8 counts, and BMI in the statistical analyses due to missing data. These factors may influence the risk of TP53 mutations or polymorphisms, as well as the relationship between HPV and cervical/vulvar cancer. The predominance of pre-malignant lesions (93%) in the study cohort may have limited the detection of certain associations, this focus on early-stage disease provides valuable insight into the genetic factors associated with the progression of HPV-related lesions. Future research will broaden the range of lesion stages and incorporate a more comprehensive set of variables to further strengthen the findings.
Our study focused only on HIV infected women and lacked use of normal tissue comparisons of the TP53 polymorphisms. These limitations impede differential comparison of TP53 polymorphism frequencies between HIV infected women and HIV uninfected women with precancerous lesions thus limiting accurate differential inference between the two distinct groups and the ability to decipher any effects HIV may have on TP53 during the process of carcinogenesis. In addition, comparisons of normal vs. precancerous lesions allows understanding of any genetic changes that occur as a result of infection. Future studies should look at differential mutations and gene expression according to HIV status.
Our study was also limited because we conducted a cross-sectional study where we recruited participants from a single site, an HIV referral centre – potentially introducing selection bias. Future research should look into a prospective study that recruits participants from multiple recruitment sites to reduce risk of selection bias. In addition, functional studies should also be conducted in to determine the functional significance of the variants. Another limitation of this study is the absence of an HPV-positive, lesion-free comparator group, which limits assessment of variant-specific persistence and progression risk; this will be addressed prospectively in future longitudinal studies.
Emerging evidence also points to the role of vaginal microbiota in driving HPV persistence and cancer development (45). Our study was limited in that we did not consider the microbiome in our analyses. Future studies, should incorporate vaginal microbiota analyses, towards obtaining a holistic understanding in variability in disease risk, and advancing personalised medicine.
Conclusion
Genotypes such as HPV 35, 39, 51, 53 and 56 were detected in cervical and vulvar tissue in Zimbabwean WLWH, underscoring the heterogeneity of HPV in Africa. The data presented here underscore the need for broader vaccines that include prevalent genotypes in Africa. This study also reports on the relationship between two genetic polymorphisms in TP53 codons 72 and 47, and HPV in women living with HIV in Zimbabwe. Although no direct relationship was observed between TP53 codons 47 and 72 and HPV in the current cohort, the current data confirm the presence of the TP53 codon 47 T allele, which has been shown to be a strong prognostic marker for chemotherapy. Future studies to analyse the role of the TP53 codon 47 T allele in treatment response among African cancer patients can be conducted, towards personalising therapy.
Acknowledgments
We would like to thank the participants who consented to participate in this study.
Funding Statement
The author(s) declared that financial support was received for this work and/or its publication. This project was supported by the Fogarty International Centre of the National Institutes of Health (NIH) under award number D43TW009343 and the University of California Global Health Institute (UCGHI). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or UCGHI.
Footnotes
Edited by: Nicola Squillace, IRCCS San Gerardo dei Tintori Foundation, Italy
Reviewed by: Jhommara Bautista, University of the Americas, Ecuador
Jonas Wolf, Moinhos de Vento Hospital, Brazil
Data availability statement
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/dbvar/, SUB15751431.
Ethics statement
The studies involving humans were approved by Medical Research Council of Zimbabwe. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study. All study participants provided consent to participate in writing.
Author contributions
OK: Investigation, Supervision, Writing – original draft, Writing – review & editing. MP: Methodology, Writing – review & editing. EL: Data curation, Formal analysis, Visualization, Writing – review & editing. TM: Investigation, Writing – original draft. DM: Writing – review & editing. AM: Methodology, Supervision, Writing – review & editing. NS: Conceptualization, Formal analysis, Methodology, Supervision, Writing – original draft, Writing – review & editing. CD: Funding acquisition, Supervision, Writing – original draft. RM: Methodology, Validation, Writing – review & editing. MF: Conceptualization, Investigation, Methodology, Writing – review & editing. JP: Supervision, Writing – review & editing. TR: Formal analysis, Methodology, Supervision, Writing – review & editing. ZC: Methodology, Software, Supervision, Validation, Writing – review & editing. RD: Formal analysis, Funding acquisition, Investigation, Methodology, Supervision, Writing – original draft.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that generative AI was not used in the creation of this manuscript.
Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/frph.2026.1808566/full#supplementary-material
References
- 1.Brianti P, De Flammineis E, Mercuri SR. Review of HPV-related diseases and cancers. New Microbiol. (2007) 40(2):80–5. [PubMed] [Google Scholar]
- 2.de Martel C, Georges D, Bray F, Ferlay J, Clifford GM. Global burden of cancer attributable to infections in 2018: a worldwide incidence analysis. Lancet Glob Health. (2020) 8(2):180–90. 10.1016/S2214-109X(19)30488-7 [DOI] [PubMed] [Google Scholar]
- 3.Rakislova N, Saco A, Sierra A, Del Pino M, Ordi J. Role of human papillomavirus in vulvar cancer. Adv Anat Pathol. (2017) 24(4):201–14. 10.1097/PAP.0000000000000155 [DOI] [PubMed] [Google Scholar]
- 4.World Health Organisation. Cervical cancer (2022). Available online at: https://www.who.int/news-room/fact-sheets/detail/cervical-cancer (Accessed March 27, 2023).
- 5.MacDuffie E, Sakamuri S, Luckett R, Wang Q, Bvochara-Nsingo M, Monare B, et al. Vulvar cancer in Botswana in women with and without HIV infection: patterns of treatment and survival outcomes. Int J Gynaecol Cancer. (2021) 31(10):1328–34. 10.1136/ijgc-2021-002728 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Dube-Mandishora RS, Christiansen IK, Chin’ombe N, Duri K, Ngara B, Rounge TB, et al. Genotypic diversity of anogenital human papillomavirus in women attending cervical cancer screening in Harare, Zimbabwe. J Med Virol. (2017) 89:1671–7. 10.1002/jmv.24825 [DOI] [PubMed] [Google Scholar]
- 7.Isaguliants M, Bayurova E, Advoshina D, Kondrashova A, Chiodi F, Palefsky JM. Oncogenic effects of HIV-1 proteins, mechanisms behind. Cancer (Basel). (2021) 13(2):305. 10.3390/cancers13020305 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Stelzle D, Tanaka LF, Lee KK, Khalil IA, Baussano I, Shah ASV, et al. Estimates of the global burden of cervical cancer associated with HIV. Lancet Glob Health. (2020) 9(2):161–69. 10.1016/S2214-109X(20)30459-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Moodley JR, Hoffman M, Carrara H, Allan BR, Cooper DD, Rosenburg L, et al. HIV and pre-neoplastic and neoplastic lesions of the cervix in South Africa: a case-control study. BMC cancer. (2006) 6:135. 10.1186/1471-2407-6-135 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Zayats R, Murooka TT, McKinnon LR. HPV and the risk of HIV acquisition in women. Front Cell Infect Microbiol. (2022) 12:814948. 10.3389/fcimb.2022.814948 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Leibenberg LJP, McKinnon LR, Yende Zuma N, Garrett N, Baxter C, Kharsany ABM. HPV infection and the genital cytokine milieu in women at high risk of HIV acquisition. Nat Commun. (2019) 10(1):5227. 10.1038/s41467-019-13089-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Hanahan D. Hallmarks of cancer: new dimensions. Cancer Discov. (2022) 12(1):31–46. 10.1158/2159-8290.CD-21-1059 [DOI] [PubMed] [Google Scholar]
- 13.Khan MA, Tiwari D, Dongre A, Sadaf, Mustafa S, Das CR, et al. Exploring the p53 connection of cervical cancer pathogenesis involving north-east Indian patients. PLoS One. (2020) 15(9):e0238500. 10.1371/journal.pone.0238500 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Shen CC, Cheng WY, Lee CH, Dai XJ, Chiao MT, Liang YJ, et al. Both p53 codon 72 arg/arg and pro/arg genotypes in glioblastoma multiforme are associated with a better prognosis in bevacizumab treatment. BMC Cancer. (2020) 20(1):709. 10.1186/s12885-020-07210-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Kuguyo O, Dube-Mandishora RS, Soko N, Magwaku T, Matimba A, Dandara C. GSTP, GSTT1, XRCC1 and CASP8 genetic variations are associated with human papillomavirus in women with cervical cancer from Zimbabwe. Future Virol. (2024) 19(1):19–32. 10.2217/fvl-2023-0154 [DOI] [Google Scholar]
- 16.Zia N, Dube-Mandishora RS, Chirenje Z, Makunike-Mutasa R, Munjoma M, Gomo E. Prevalence and genotype distribution of high risk human papillomavirus among HIV infected and uninfected women in Harare, Zimbabwe. Cent Afr J Med. (2023) 69(1-6):1–13. [Google Scholar]
- 17.Kufa T, Mandiriri A, Shamu T, Dube-Mandishora RS, Pascoe MJ. Prevalence of cervical high-risk human papillomavirus among Zimbabwean women living with HIV. South Afr J HIV Med. (2024) 25(1):1–7. 10.4102/sajhivmed.v25i1.1633 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Kuguyo O, Dube-Mandishora RS, Thomford NE, Makunike-Mutasa R, Nhachi CF, Matimba A, et al. High-risk HPV genotypes in Zimbabwean women with cervical cancer: comparative analyses between HIV-negative and HIV-positive women. PLoS One. (2021) 16(9):e0257324. 10.1371/journal.pone.0257324 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Baay MF, Kjetland EF, Ndhlovu PD, Deschoolmeester V, Mduluza T, Gomo E, et al. Human papillomavirus in a rural community in Zimbabwe: the impact of HIV co-infection on HPV genotype distribution. J Med Virol. (2004) 73(3):481–5. 10.1002/jmv.20115 [DOI] [PubMed] [Google Scholar]
- 20.Manyere NR, Dube Mandishora RS, Magwali T, Mtisi F, Mataruka K, Mtede B, et al. Human papillomavirus genotype distribution in genital warts among women in Harare, Zimbabwe. J Obstet Gynaecol. (2019) 40(6):830–6. 10.1080/01443615.2019.1673710 [DOI] [PubMed] [Google Scholar]
- 21.Pinheiro M, Gage JC, Clifford GM, Demarco M, Cheung LC, Chen Z, et al. Association of HPV35 with cervical carcinogenesis among women of African ancestry: evidence of viral host interaction with implications for disease intervention. Int J Cancer. (2020) 147(10):2677–86. 10.1002/ijc.33033 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Butt JL, Botha MH. Vulvar cancer is not a disease of the elderly: treatment and outcome at a tertiary referral centre in South Africa. SAMJ. (2017) 47(11). 10.7196/samj.2017.v107i11.12497 [DOI] [PubMed] [Google Scholar]
- 23.Halec G, Alemany L, Quiros B, Clavero O, Hofler D, Alejo M, et al. Biological relevance of human papillomaviruses in vulvar cancer. Mod Pathol. (2017) 30(4):549–62. 10.1038/modpathol.2016.197 [DOI] [PubMed] [Google Scholar]
- 24.Preti M, Rotondo JC, Holzinger D, Micheletti L, Gallio N, McKay-Chopin S, et al. Role of human papillomavirus infection in the aetiology of vulvar cancer in Italian women. Infect Agents Cancer. (2020) 15:2020. 10.1186/s13027-020-00286-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Sznurkowsi JJ, Zawrocki A, Biernat W. The overexpression of p16 is not a surrogate marker for high-risk human papillomavirus genotypes and predicts clinical outcomes for vulvar cancer. BMC cancer. (2016) 16(1):465. 10.1186/s12885-016-2503-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Pruski D, Laggiedo-Zelazowska M, Millert-Kalinska S, Sikora J, Jach R, Przybylski M. Immunity after HPV vaccination in patients after sexual initiation. Vaccines (Basel). (2022) 10(5):728. 10.3390/vaccines10050728 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Stanley M, Joura E, Yen GP, Kothari S, Luxembourg A, Saah A, et al. Systematic literature review of neutralizing antibody immune responses to non-vaccine targeted high-risk HPV types induced by the bivalent and the quadrivalent vaccines. Vaccine. (2021) 15(39:16):2214–23. 10.1016/j.vaccine.2021.01.060 [DOI] [PubMed] [Google Scholar]
- 28.LaMontagne DS, Manangazira P, Marembo J, Chigodo C, Zvamashakwe C, Tshuma E, et al. HPV Vaccination coverage in three districts in Zimbabwe following national introduction of 0,12 month schedule among 10 to 14 old girls. Vaccine. (2022) 40(1):58–66. 10.1016/j.vaccine.2021.07.012 [DOI] [PubMed] [Google Scholar]
- 29.Brown DR, Joura EA, Yen GP, Kothari S, Luxembourg A, Saah A, et al. Systematic literature review of cross-protective effect of HPV vaccines based on data from randomized clinical trials and real-world evidence. Vaccine. (2012) 39(16):2224–36. 10.1016/j.vaccine.2020.11.076 [DOI] [PubMed] [Google Scholar]
- 30.Carlton JG, Marembo J, Manangazira P, Rupfutse M, Sherley A, Makwabarara E, et al. Nationwide introduction of HPV vaccine in Zimbabwe 2018–2019: experiences with multiple cohort vaccination delivery. PLOS Glob Public Health. (2022) 2(4):e0000101. 10.1371/journal.pgph.0000101 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Kouamou V, Chin'ombe N, Matimba A, Kadzatsa W, Nyandoro G, Musarurwa C. P53 codon 72 polymorphism and the risk of cervical cancer in Zimbabwean women. Int J Trop Dis Health. (2016) 15(3):1–6. 10.9734/IJTDH/2016/24676 [DOI] [Google Scholar]
- 32.Pegoraro R, Moodley J, Naiker S, Lanning P, Rom L. The p53 codon 72 polymorphism in black South African women and the risk of cervical cancer. BJOG. (2000) 107(9):1164–5. 10.1111/j.1471-0528.2000.tb11118.x [DOI] [PubMed] [Google Scholar]
- 33.Assoumou SZ, Boumba AL, Ndjoyi-Mbiguino A, Khattabi A, Ennaji MM. The preliminary study of P53 codon 72 polymorphism and risk of cervical carcinoma in gabobese women. Med Oncol. (2015) 32:281–7. 10.1007/s12032-014-0281-4 [DOI] [PubMed] [Google Scholar]
- 34.Mostaid MS, Mumu SB, Haque MA, Sharmin S, Jamiruddin MR, Rahman SGM, et al. Elevated serum expression of p53 and association codon 72 polymorphisms with risk of cervical cancer in Bangladeshi women. PLoS One. (2021) 16(12):e0261984. 10.1371/journal.pone.0261984 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Jemia ZB, Fehri E, Ardhaoui M, Jaballah-Gabteni A, Lassili T, Essafi-Benkhadir K, et al. The TP53 rs 1042522 polymorphism and its association with precancerous cervical lesions progression among Tunisian women. Diagn Microbiol Infect Dis. (2025) 113(3):116981. 10.1016/j.diagmicrobio.2025.116981 [DOI] [PubMed] [Google Scholar]
- 36.dbSNP. Accessible online at: Available online at: https://www.ncbi.nlm.nih.gov/snp/ (Accessed March 11, 2026).
- 37.Storey A, Thomas M, Kalita A, Harwood C, Gardiol D, Mantovani F, et al. Role of a p53 polymorphism in the development of human papillomavirus-associated cancer. Nature. (1998) 393:229–34. [DOI] [PubMed] [Google Scholar]
- 38.Koshiol J, Hildesheim A, Gonzalez P, Bratti MC, Porras C, Schiffman M, et al. Common genetic variation in TP53 and risk of human papillomavirus persistence and progression to CIN3/cancer revisited. Cancer Epidemiol Biomarkers Prev. (2009) 18(5):1631–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Kuguyo O, Tsikai N, Thomford NE, Magwali T, Madziyire MG, Nhachi CF, et al. Genetic susceptibility for cervical cancer in African populations: what are the host genetic drivers? OMICS. (2018) 22(7):468–83. 10.1089/omi.2018.0075 [DOI] [PubMed] [Google Scholar]
- 40.Siddique MM, Balram C, Fiszer-Maliszewska L, Aggarwal A, Tan A, Tan P, et al. Evidence for selective expression of the p53 codon 72 polymorphs: implications in cancer development. Cancer Epidemiol Biomarkers. (2005) 14(9):2245–52. [DOI] [PubMed] [Google Scholar]
- 41.Jafrin S, Aziz MA, Anonna SN, Akter T, Naznin NE, Reza S, et al. Association of TP53 Codon 72 arg > pro polymorphism with breast and lung cancer risk in the South Asian population: a meta-analysis. Asian Pac J Cancer Prev. (2020) 21(6):1511–9. 10.31557/APJCP.2020.21.6.1511 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Jennis M, Kung CP, Basu S, Budina-Kolomets A, Let JI, Khaku S, et al. An African-specific polymorphism in the TP53 gene impairs p53 tumor suppressor function in a mouse model. Genes Dev. (2016) 30(8):918–30. 10.1101/gad.275891.115 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Murphy ME, Liu S, Yao S, Huo D, Liu Q, Dolfi SC, et al. A functionally significant SNP in TP53 and breast cancer risk in African- American women. NPJ Breast Cancer. (2017) 3:5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Barnoud T, Parris JLD, Murphy ME. Common genetic variants in the TP53 pathway and their impact on cancer. J Mol Cell Biol. (2019) 11(7):578–85. 10.1093/jmcb/mjz052 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Bautista J, Altamirano-Colina A, Lopez-Cortes A. The vaginal microbiome in HPV persistence and cervical cancer progression. Front Cell Infect Microbiol. (2025) 15:1634251. 10.3389/fcimb.2025.1634251 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/dbvar/, SUB15751431.