Bioinformatics Analysis of Non-Coding UTR Variants in STAT1 Reveals Disruption of miRNA Binding, mRNA Stability, and Oncogenic Potential

Single nucleotide polymorphisms (SNPs) are associated with a wide range of disorders, including diverse cancer types. In the context of cancer, alterations within non-coding regions, specifically untranslated regions (UTRs), have proven substantially important. SNPs localized in the 3 prime UTRs of the STAT1 gene were assessed for their association with miRNAs using PolymiRTS, miRNASNP, and MicroSNIper. In addition, the 5 UTR SNPs were analyzed by SNP INFO for changes in the transcription factors binding sites. The significant SNPs were further analysed by Cscape to predict their oncogenic probability. The secondary structures of the wild type and the mutant mRNA were analysed by RNAfold.

Out of 605 SNPs analyzed, 14 UTR SNPs (six in the 3⍰ UTR region and eight in the 5⍰ UTR region) were identified with functional annotation ≤2a by RegulomeDB. The associations of 8 SNPs with miRNAs common between the 3 databases (PolymiRTS, miRNASNP, and MicroSNIper) were found.

Moreover we identified six SNPs (rs1197872838, rs3088307, rs45470392, rs1413522785, rs531009254, and rs190508584) destabilize the mRNA structure resulting in substantial change in free energy (ΔG). The SNP rs45470392 in 5⍰ UTR was predicted to alter the transcription factor binding sites. rs188557905, rs1220766131, rs1413522785, rs1168, and rs999207177 were predicted to be oncogenic SNPs in this study using bioinformatics tools.

Our findings highlight the impact of 3⍰ and 5⍰ UTR SNPs on miRNA, transcription, and translation of STAT1 . These analyses suggest that these SNPs can have substantial functional importance in the STAT1 gene. Future experimental validation could establish their potential role in the diagnosis and therapeutics of various diseases, including cancer.