ArticleNon-coding RNA2025
In Silico Prioritization of STAT1 3' UTR SNPs Identifies rs190542524 as a miRNA-Linked Variant with Potential Oncogenic Impact.
Article in Non-coding RNA, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Genetic Association and Functional Prediction of PTEN and TSC1 3'UTR Variants in Autism Spectrum Disorder Among Tunisian Patients.Molecular neurobiology · 2025Article
- Computational Identification of RNF114 nsSNPs with Potential Roles in Psoriasis and Immune Dysregulation.Medical sciences (Basel, Switzerland) · 2025Article
- The emerging role of miR-362 in cancer: expression and function across different cancer types.Medical oncology (Northwood, London, England) · 2025Review
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Abstract
backgroundSingle-nucleotide polymorphisms (SNPs) are associated with multiple disorders and various cancer types. In the context of cancer, alterations within non-coding regions, specifically 3' untranslated regions (3' UTR), have proven substantially important.
methodsIn this study, we utilized various bioinformatics tools to examine the effect of SNPs in the 3' UTR. We retrieved the 3' UTR SNPs of the Signal Transducer and Activator of Transcription 1 (STAT1) gene from the National Centre for Biotechnology Information (NCBI) website. Next, we employed the Polymorphism in miRNAs and their corresponding target sites (PolymiRTS) database to predict the 3' UTR SNPs that create new microRNA (miRNA) binding sites and their respective miRNAs. The effect of the 3' UTR SNPs on the messenger RNA structure was studied using RNAfold server. We used Cscape tool to predict the oncogenic 3' UTR SNPs. Then, we submitted the miRNAs to the miRNet database to visualize the miRNA-miRNAs' target genes interaction, for which gene enrichment analysis was performed using ShinyGO. Protein-protein interactions were conducted using the STRING database. We conducted miRNA enrichment analysis utilizing miRPathDB, subsequently performing miRNA differential expression analysis through oncoMIR, and the StarBase database. The survival analysis of the upregulated miRNAs in cancer was investigated using the Kaplan-Meier Plotter.
resultTwelve SNPs were predicted to create new miRNA binding sites. Two of them, rs188557905 and rs190542524, were predicted to destabilize the mRNA structures. We predicted rs190542524, rs11305, rs186033487, and rs188557905 to be oncogenic 3' UTR SNPs, with high-confidence predictions and scores > 0.5. Using miRNAs' target genes enrichment analysis, this study indicated that the miRNA target genes were more likely to be involved in cancer-related pathways. Our comprehensive analysis of miRNAs, their functional enrichment, their expression in various types of cancer, and the correlation between miRNA expression and survival outcome yielded these results. Our research shows that the oncogenic 3' UTR SNP rs190542524 creates a new binding site for the oncogenic miRNA hsa-miR-136-5p. This miRNA is significantly upregulated in BLCA, LUSC, and STAD and is linked to poor survival. Additionally, rs114360225 creates a new binding site for hsa-miR-362-3p, influencing LIHC.
conclusionsThese analyses suggest that these 3' UTR SNPs may have a functional impact on the STAT1 gene's regulation through their predicted effect on miRNA binding sites. Future experimental validation could establish their potential role in the diagnosis and treatment of various diseases, including cancer.
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