Investigating the Role of CDKN1B rs34330 and CDKN2B rs3217986 for Cervical Cancer Phenotype and Prognosis

Background and Objectives Cervical cancer is one of the most commonly diagnosed cancers among females globally. Perturbations of cell cycle proteins via germline variation have been linked to various cancers. Genes CDKN1B and CDKN2B encode cyclin-dependent kinase inhibitors which are tumor suppressor proteins found to have aberrant genetic changes in certain cancers. Rs34330 and rs3217986 are single nucleotide polymorphisms (SNPs) located in untranslated regions of CDKN1B and CDKN2B, respectively. Since SNPs in untranslated regions play an important role in regulating gene expression, we hypothesized that rs34330 and rs3217986 may be important for the morphology of cervical cancer and patients’ survival. In this study we aimed to investigate the impact of the aforementioned SNPs on cervical cancer phenotype and prognosis. Material and Methods A total of 165 patients with stage I-IV cervical cancer treated at the Hospital of Lithuanian University of Health Sciences Kaunas Clinics were enrolled in this study. Patient exclusion criteria were other malignancies and incomplete medical documentation. Clinicopathological characteristics were obtained from medical records by oncologists. The age at the time of diagnosis ranged from 22 to 83 years. Genomic DNA was isolated from peripheral blood leukocytes with a spin column-based method. Genomic variants were detected through real-time PCR using Taqman probes on Quantstudio 3 PCR System. Associations between genotypes, alleles and clinicopathological characteristics were analyzed using Pearson’s chi-square or Fisher’s exact tests. Binary logistic regression analyses were performed to estimate the odds ratios (OR) associating different genotypes and alleles with clinicopathological features. Survival curves were generated using the Kaplan-Meier method and compared by a log-rank test. The hazard ratios (HRs) were calculated using univariate and multivariate Cox proportional hazards models. Statistical analyses were conducted using IBM SPSS Statistics 30.0.0.0. A p<0.05 was considered statistically significant. The study was approved by Kaunas Regional Biomedical Research Ethical Committee (nos. BE-2-10 and P1-BE-2-10/2014). Results In a group of 165 patients, the CDKN2B rs3217986 genotype distribution was 88% TT, 10% TG and 2% GG. The distribution of CDKN1B rs34330 genotypes was 53% CC, 38% TC and 9% TT. No significant associations between genotypes or alleles and cervical cancer phenotype and prognosis (patient age at the time of diagnosis, tumor size, differentiation grade, metastasis, lymph node involvement, presence of disease progression and death) were identified by Pearson’s chi-square test and logistic regression analysis. However, association was determined between CDKN2B rs3217986 genotype and progression-free survival (PFS) (log-rank p=0.012). Patients presenting GG genotype had shorter PFS (HR 4.879, 95% CI 1.496-15.910, p=0.009) compared to TT carriers. In multivariate analysis (including patient age, tumor size, differentiation grade, metastasis, lymph node involvement) the association remained statistically significant (HR 8.580, 95 % 2.488-29.587, p<0.001). A shorter PFS was less common in TG carriers in comparison to GG (HR 0.181, 95% CI 0.043-0.767, p=0.020). This association stayed significant after adjustment for the analyzed clinicopathological features (HR 0.136, 95% CI 0.031-0.601, p=0.008). Regarding alleles of rs3217986, T carriers were less likely to have a shorter PFS (log-rank p=0.003, HR 0.203 95% CI 0.062-0.659, p=0.008) compared with non-carriers. When additional variables were included in multivariate analysis, the association remained unaffected (HR 0.118, 95% CI 0.034-0.407, p<0.001). No significant link between the genotypes or alleles of CDKN2B rs3217986 and overall survival (OS) was detected. There was no significant association found between the CDKN1B rs34330 genotypes or alleles and PFS or OS. Conclusions and Recommendations Results of the present study suggest that CDKN2B rs3217986 predicts the course of disease in Lithuanian cervical cancer population. To evaluate the SNP as a genetic biomarker to forecast how the disease may progress, further thorough investigation is necessary.