This study adopted a case-control research design to investigate the prevalence and risk of SNPs in TP53 and BRCA2 genes in cervical and ovarian cancers in Nigerian women using hormonal contraceptives.

This was a case-control study carried out in the family planning unit in the Civil Defence Medical Centre, Abuja. Abuja is both a Federal Capital Territory within the nation of Nigeria and a city within that territory which serves as the nation’s capital. It is slightly west of the centre of the country. Abuja lies at 1180 feet (360 m) above sea level; the latitude of Abuja is 9.072264 and the longitude is 7.491302, and its area covers 2824 square miles (7315 square km). The Federal Capital Territory falls within the Savannah Zone vegetation of the West African sub-region.¹⁴

The study population consisted of women between the ages of 18 years and 60 years on hormonal contraceptives who will be attending the family planning unit in the Civil Defence Medical Centre. They were recruited from the Nigeria Security and Civil Defence Corps Medical Centre, Abuja. The control groups were recruited from the same hospitals and were non-contraceptive (hormonal) users at any point in time in their lives. Basic demographic biodata was collected via a questionnaire on the type of contraceptive, administration route and usage duration.

These sample selections were carried out through a random sampling technique as described by Naing¹⁵ and Usiobeigbe.¹⁶ A total of 108 samples were obtained for the study, with 98 individuals categorised as hormonal contraceptive users and 10 as non-users that served as a control.

Five millilitres of venous blood were collected aseptically without stasis from the prominent vein of the cubital fossa and dispensed into potassium EDTA (K₃EDTA) bottles. The whole blood was stored at −20 °C until analysed. Participant data were collected using a structured questionnaire.

Inclusion criteria include subjects between the ages of 18 years and 60 years that were on hormonal contraceptives of any type and had not been diagnosed with breast cancer or ovarian cancer. Control subjects were women who had never taken any form of contraceptive – combined, single or emergency – and also free of, either and both, breast and/or ovarian cancer.

Subjects that have reached menopause, are below the age of 18 years or above 60 years or are currently undergoing treatment for metabolic disorders were excluded, and those who had these diseases before taking hormonal contraception were also excluded, and those who refused to give consent were excluded from this study.

To investigate SNPs in the TP53 and BRCA2 genes, we employed the polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) technique as previously described by Chang et al.¹⁷ and Tarach,¹⁸ and with slight modifications by Damin.¹⁹ This method enables rapid and cost-effective genotyping of known point mutations by leveraging sequence-specific restriction enzyme digestion of PCR-amplified DNA, and the robust PCR-RFLP protocol enabled precise discrimination of allelic variants in TP53 and BRCA2, making it a reliable approach for genotyping SNPs associated with cancer susceptibility in small- to medium-scale molecular epidemiological studies.

Genomic DNA was extracted from peripheral whole blood samples using the QIAamp DNA Mini Kit (Qiagen, Germany) following the manufacturer’s instructions. Briefly, 200 µL of blood was lysed, mixed with ethanol and passed through a spin column for purification, followed by washes and elution with Tris-EDTA elution buffer (AE). Purified genomic DNA was stored at −20 °C until further use. DNA quality was assessed using a NanoDrop spectrophotometer (Thermo Fisher Scientific, Waltham, Massachusetts, United States). Samples were considered suitable for downstream analysis based on the following predefined benchmarks: an A260/280 absorbance ratio between 1.8 and 2.0, indicating acceptable protein-free DNA purity, and a minimum DNA concentration of 20 ng/µL. Only samples meeting these criteria were selected for PCR analysis.

Polymerase chain reaction amplification was carried out in a total reaction volume of 25 µL, comprising 12.5 µL of 2× PCR Master Mix (Promega, United States), 0.2 µM of each forward and reverse primer specific to SNP loci in TP53 and BRCA2 and 50 100 ng of genomic DNA as a template (corresponding to a minimum template concentration of 2 ng/µL per reaction). Nuclease-free water was added to complete the reaction volume. Negative controls containing no template DNA were included in each PCR run to monitor contamination. Thermocycling consisted of initial denaturation at 94° C, followed by 40 cycles of denaturation, annealing at 48 °C and extension and finalised with an elongation step at 72 °C. Following amplification, PCR products were digested with appropriate restriction enzymes such as EcoRI and MspI in 20 µL reactions at 37 °C, following the manufacturer’s guidelines, to detect polymorphisms affecting restriction sites.

The restriction fragments generated were analysed using 2% (weight per volume [w/v]) agarose gel electrophoresis pre-stained with ethidium bromide. Deoxyribonucleic acid fragments, being negatively charged, migrated towards the positive electrode when an electric field was applied, with smaller fragments moving faster than larger ones, resulting in separation based on size. Fragmented samples were loaded into the gel chamber, and after electrophoresis, the gels were treated with ethidium bromide (0.5 µg/mL for 10 min) to enhance DNA band visibility. Bands were visualised using an ultraviolet (UV) transilluminator (Dark Reader X), and photographic records were taken. Fragment sizes were compared to a molecular weight marker to determine SNP genotypes based on digestion patterns observed.

Subsequently, the purified samples from the PCR technique were used for amplification of the DNA fragments, which were sequenced using a Genetic Analyzer 3130xl sequencer from Applied Biosystems using the manufacturers’ manual; Bio-Edit software (version 7.2) and Mega 6 were used for all genetic analysis, as described by Njoko²⁰ and modified by Olukayode.²

Data were analysed using the Chi-square test of independence, Fisher’s exact test and regression analysis. Quantitative and qualitative variables were summarised using frequencies, tables, charts and pictorial diagrams. Appropriate statistical tools within Microsoft Excel were used to determine the significance of the result; the level of significance was set at p ≤ 0.05.

Ethical clearance to conduct this study was obtained from the Nigeria Security and Civil Defence Corps, National headquarters, Abuja (reference number: NSCDC/NHQ/HMSU/023/04). Participants’ consent was obtained along with a consent form.

The total number of samples collected was 108; this number encompassed different age ranges, ethnic groups, religions, marital status, education backgrounds, employment and duration of contraceptive usage and various types of hormonal contraceptives, as shown in Table 1. The data from the questionnaire shows that the age bracket of 25–31 years old showed the highest frequency (n = 28) and percentage (26%), and ages 53–60 years showed the lowest frequency (n = 6) and percentage (6%). The Hausa ethnic group had the highest frequency of 60 (55.5%), and the Christian religion had a frequency of 66 (61%). A high number of the participants were married, with a frequency of 68 (63%), and most have received a tertiary level of education, with a frequency of 44 (41%); however, the majority had a semi-skilled form of employment, with a frequency of 35 (32%). Also, the majority of the participants had been on one form of hormonal contraceptives for at least 5 years and above, with a frequency of 59 (55%), and having injectable types of hormonal contraceptives was the highest form of contraceptives used, with a frequency of 40 (37%).

PCR-RFLP analysis followed by gel electrophoresis revealed the presence of SNPs in the TP53 gene in a subset of the test group. In contrast, no BRCA2 gene polymorphisms were detected in the participant samples. Sequence analysis using NCBI BLAST confirmed both wild-type and variant isoforms of the TP53 gene. Two types of mutations were observed in the TP53 gene: G > A transition: 2 cases (40%) and G > C transversion: 3 cases (60%). These mutations resulted in missense changes, potentially altering protein function.

Polymorphisms on the TP53 gene for cervical cancer were observed in some samples, which was indicated by the restriction enzyme not being able to cleave the right sequence of the gene and showing variants of shortening of the bands on the electrophoresis gel. The nucleotide sequence was blasted on the NCBI website, which confirms the presence of isoforms of the TP53 gene nucleotide sequences. It was observed that missense mutations were caused by changes in the nucleotide sequences.

However, polymorphisms of the BRCA2 gene for ovarian cancer were not seen in samples from participants from the present study. This was indicated by the restriction enzyme not being able to cleave the right sequence of the gene to show a shortened band on the electrophoresis gel, and when blasted on the NCBI website, it returned the normal nucleotide sequence for the BRCA2 gene, which means that polymorphism did not occur.

Out of the 98 hormonal contraceptive users, 5 were found to have TP53 SNPs, giving a prevalence rate of approximately 5.1%. BRCA2 SNPs were absent across all participants.

A Chi-square test of independence was performed to determine if the type of hormonal contraceptive used had any significant association with the presence of TP53 SNPs. The contingency table (Table 1)^{21, 22} included data from injectables, implants, intrauterine devices (IUD), oral contraceptives and non-users (χ² = 1.08, degree of freedom [df] = 4, p = 0.897). The results did not show statistical significance (p > 0.05), indicating no significant association between contraceptive type and TP53 SNP prevalence.

To compare the prevalence of SNPs between the TP53 and BRCA2 genes, Fisher’s exact test was applied (p = 0.059). It showed a marginally close statistical significance (p > 0.05).

The biodata distribution of the participants in this research study, as shown in Table 2 provides valuable insight into the demographic characteristics of the participants of the sample population. A total of 108 women participated in the study, the majority of whom were users of hormonal contraceptives. The data were analysed across various parameters, including age, ethnicity, religion, marital status, educational background, employment status and duration of contraceptive use. These variables play significant roles in influencing health outcomes, including cancer risk factors, as they reflect underlying socioeconomic and cultural factors that may impact access to healthcare, lifestyle choices and genetic predispositions.

In this research study, SNPs were observed in the TP53 gene in 5.1% of the samples, as shown in Figure 1 this is similar to reports in the established literature linking TP53 mutations to an increased risk of cervical cancer, similar to a cohort study by Mørch et al.²⁵ The most common polymorphisms detected were G > A (40%) and G > C (60%), both of which were missense mutations as shown in Figure 2. These mutations lead to amino acid substitutions that could disrupt the tumour-suppressor functions of the TP53 protein. Specifically, the G > A transition results in a glycine to aspartate substitution, while the G > C transversion leads to an arginine to serine substitution. Both mutations are known to alter the structure and function of TP53, impairing its role in DNA repair, apoptosis and cell cycle regulation.

This is consistent with several studies, such as one by Petitjean et al.²⁶, which highlights that TP53 mutations are among the most frequent alterations in cervical cancer patients and are associated with more aggressive tumour phenotypes and poorer prognoses. Studies by Mehta & Singh²⁷ also indicate that TP53 mutations play a key role in the development of cervical and other cancers, further supporting the findings of this research. Additionally, Hu & Wu²⁸ emphasise that TP53 mutations are often linked to cancer progression and poor treatment outcomes, making early detection of these polymorphisms vital for improved patient prognosis. Therefore, the presence of these mutations in the sampled population suggests a heightened risk of developing cervical cancer, especially among individuals with these specific polymorphisms.

In contrast, no polymorphisms were detected in the BRCA2 gene in the samples analysed, as shown in Figure 1. This result is somewhat unexpected, as BRCA2 mutations are strongly associated with an increased risk of ovarian cancer, as reported by Rookus et al.²⁹ and Phillips et al.³⁰, who found a slightly increased risk of breast cancer for BRCA/12 mutation carriers who ever used oral contraceptives. The absence of BRCA2 mutations in this study could be attributed to several factors. Firstly, the sample size might not have been large enough to detect rare polymorphisms in BRCA2. Secondly, other genetic factors or environmental influences, such as HPV infection, might play a more prominent role in the aetiology of ovarian cancer in this population.

Other studies, such as those by Kuchenbaecker et al.³¹, emphasise that not all ovarian cancer cases are linked to BRCA mutations, and some patients may develop ovarian cancer through alternative genetic pathways. Furthermore, Collins et al.³² discuss that while BRCA mutations are significant risk factors, ovarian cancer can also develop independently of BRCA gene mutations, suggesting other genetic and environmental interactions might be at play. Therefore, while BRCA2 mutations are a well-established risk factor, their absence in this study does not necessarily negate the genetic predisposition to ovarian cancer in this population.

The findings from this study have significant implications for understanding the genetic risk factors associated with cervical and ovarian cancer in this population. The presence of TP53 polymorphisms in women on hormonal contraceptives indicates a potential genetic predisposition to cervical cancer; this reinforces the need for early genetic screening and preventive strategies among high-risk individuals. Screening for TP53 mutations could aid in identifying women at higher risk and facilitate timely intervention, which could improve outcomes.

On the other hand, the absence of BRCA2 polymorphisms suggests that BRCA screening may not be as critical for ovarian cancer risk assessment in this particular population. However, considering the small sample size and the localised nature of the study, further research with larger cohorts and additional genetic markers is necessary to draw more definitive conclusions.

Compared to global data, the results of this study are in line with reports that TP53 mutations are prevalent in cervical cancer cases. For example, a study by Wang et al.³³ found similar missense mutations in TP53 to be highly predictive of cervical intraepithelial neoplasia progressing to invasive cervical cancer. Conversely, the lack of BRCA2 mutations contrasts with studies conducted in other populations, where BRCA2 mutations were more frequently observed. This suggests a potential geographical or ethnic variation in the prevalence of these mutations, highlighting the importance of population-specific cancer genetics research.

The category of women attending the clinic is mostly on one form of contraceptives, giving a difficulty in getting a larger number of women in the non-contraceptives category, resulting in a small number of control samples.

The objective of the research was focused on only two categories (non-contraceptive users versus hormonal contraceptive users), so the results of the research were in consideration of how hormonal contraceptives affect SNPs of TP53 and BRCA2.

The genotype of the controls was not reported, because they showed a negative SNP.

There is a need for enhancing nationwide awareness of the effect of hormonal contraceptive usage, conducting further studies to determine the specific type of hormonal contraceptive that primarily predisposes patients to cancers, conducting further studies on other genes with specific restriction enzymes, conducting multi-site studies with larger population sizes to guide decision-making regarding contraceptive use and disuse, and routinely screening women on contraceptives to monitor their effects on the human body. Future studies should aim to include larger sample sizes and explore additional genetic markers, as well as consider the interaction between genetic, environmental and lifestyle factors in the development of cervical and ovarian cancers.