A retrospective Case-Control study investigating the association of XPC Lys939Gln (rs2228001), XPD Lys751Gln (rs13181), and TP53 Arg72Pro (rs1042522) with papillary thyroid carcinoma susceptibility in the Bangladeshi population.

BACKGROUND

Papillary thyroid carcinoma (PTC) is the most common thyroid malignancy, particularly among females. Polymorphisms in DNA repair and tumor suppressor genes such as XPC, XPD, and TP53 may influence cancer susceptibility. This study investigated the association of XPC Lys939Gln, XPD Lys751Gln, and TP53 Arg72Pro variants and PTC risk in a Bangladeshi population, supported by in-silico analyses.

METHODS

A retrospective case-control study was conducted involving 166 PTC patients and 180 controls. Genotyping was performed using PCR-RFLP and allele-specific multiplex PCR. Logistic regression assessed associations, with subgroup analyses stratified by gender, smoking, and family history. Functional, structural, RNA, splicing, and regulatory effects of each variant were predicted using multiple bioinformatics tools. Pearson's correlation evaluated genotype co-occurrence.

RESULTS

Mutant genotypes of all three genes were significantly more frequent in cases. XPD Gln/Gln and TP53 Arg/Pro variants conferred the highest risk. Associations were stronger in females, non-smokers, and individuals with a family history of cancer. Combined genotype analysis suggested synergistic effects. In silico predictions flagged TP53 as most functionally impactful. Structural modeling revealed minimal protein-level disruptions; however, mRNA-level analysis showed reduced transcript stability and increased conformational variability for XPD and TP53. Splicing predicted altered motifs and cryptic site activation for XPD. RegulomeDB suggested strong regulatory potential for XPC. Pearson's correlation revealed mutual exclusivity between XPC and XPD in cases.

CONCLUSION

XPC, XPD, and TP53 variants are significantly associated with PTC risk in Bangladeshi population. Combined genetic and bioinformatics evidence supports their potential as biomarkers for risk stratification, warranting larger functional studies.