Metastasis is a key determinant of cancer progression, influenced significantly by genetic mechanisms. RRP1B, primarily a nucleolar protein, emerges as a suppressor of metastasis, forming alliances with various cellular components and modulating gene expression. This study investigates the involvement of the ribosomal RNA processing 1 homolog B (RRP1B) gene in metastasis regulation in cervical cancer. Through a comprehensive analysis of 172 cervical cancer patients, we evaluated five RRP1B single nucleotide polymorphisms (SNPs) (rs2838342, rs7276633, rs2051407, rs9306160, and rs762400) for their associations with clinicopathological features and survival outcomes. Significant associations were observed between specific genetic variants and clinicopathological parameters. Notably, the A allele of rs2838342 was associated with reduced odds of advanced tumor size, worse prognosis, and, preliminarily, distant metastasis, while the T allele of rs7276633 correlated with a decreased risk of higher tumor size and worse prognosis. Additionally, the C allele of rs2051407 demonstrated protective effects against larger tumors, metastasis, and adverse prognosis. The rs9306160 C allele exhibited a protective effect against metastasis. The rs762400 G allele was significant for reduced tumor size and metastasis risk. Furthermore, the rs2838342 A allele, rs7276633 T allele, rs2051407 C allele, and rs762400 G allele were associated with improved overall survival, demonstrating their potential significance in predicting prognoses in cervical cancer. Linkage disequilibrium and haplotypes analysis enabled us to evaluate the collective effect of the analyzed SNPs, which was in line with the results of allelic models. Our findings underscore the clinical relevance of RRP1B SNPs as prognostic markers in cervical cancer, shedding light on the intricate interplay between genetic factors and disease-progression dynamics. This research provides critical insights for future investigations and underscores the importance of incorporating RRP1B SNP detection into prognostic-assessment tools for accurate prediction of disease outcomes in cervical cancer.
