Computational Insights into the Functional Impact of Missense Mutations in RFX1

Abstract: Genetic variations, particularly non-synonymous SNPs (nsSNPs), can profoundly influence protein function by altering stability, molecular interactions, and regulatory pathways, thereby contributing to disease mechanisms, including cancer. Despite advancements in high-throughput sequencing, the effects of nsSNPs on structure and function, especially in transcriptional regulators like RFX1, remain poorly understood. Addressing these challenges is crucial for uncovering potential biomarkers and therapeutic targets in cancer biology. This study focused on assessing the impact of deleterious nsSNPs in RFX1 on the stability, function, and structure of proteins, with a particular emphasis on its interaction with HDAC1. Using data from the COSMIC database and computational tools such as I-Mutant, MutPred, and Arpeggio, we identified 19 missense mutations predicted to be deleterious, significantly impacting RFX1 function. The most detrimental variants included R495L, V786G, R494C, A715P, Y460C, L812R, R311H, and R311C. Further analysis using STRING highlighted RFX1's involvement in gene transcription and chromatin remodeling pathways, mediated through interactions with key regulatory proteins such as CREB1, CIITA, and HDAC1. RFX1 expression analysis revealed its potential as a prognostic biomarker, with statistically significant hazard ratios (HR < 1) observed in breast, ovarian, and pancreatic cancers, suggesting its role as a protective factor in these malignancies. Prognostic evaluations further underscored RFX1's potential as a key biomarker in cancer. Future research will focus on experimental validation of these deleterious mutations and expression-based findings to further elucidate their diagnostic and therapeutic relevance.