Ph.D. Candidate: Kerem Yıldız
Program: Medical Informatics
Date: 09.06.2026 / 13:00
Place: A-212

Abstract: Micro RNAs (miRNAs) play a role in post-transcriptional gene regulation through a distinct mechanism to down-regulate gene translation. Recent studies have shown that dysfunction at the miRNA level can be the underlying etiology of complex disorders such as cancers and cardiovascular diseases. miRNA binds to its target messenger RNAs (mRNA) in mammalian cells at 3'UTR. The nucleotides at positions 2 to 8 of the miRNAs are named the seed region and complement the mRNA's target sequence. The Single-nucleotide variants (SNV) overlapping with these seed regions or the complementary sequences can affect miRNA function, causing diseases. Even though several databases and tools analyze the effects of 3'UTR SNVs on miRNA binding, they were developed based on different experimental datasets. This study has developed a database called miRHub that integrates experimental results from expression analysis and genotyping for the same sample sets to demonstrate the effects of 3'UTR SNVs on miRNA binding. We obtained miRNA and mRNA expression data for differential expression analysis from The Cancer Genome Atlas (TCGA) and identified the duplexes by integrating the miRTarBase database and those co-locating with TCGA SNV data. In addition, we located seed/non-seed SNVs by mapping the SNV dataset of TCGA on mRNA with the miRanda database. Since miRanda is a predictive miRNA target database, it was not used to match miRNA-mRNA duplexes but to map seed/non-seed SNVs. The miRHub portal presented here integrates the expression analysis results for mRNA, miRNA, and co-locating SNVs with matching TCGA samples and duplexes. As a use case of the miRHub, we present the statistically significant changes in mRNA regulation in "Primary Solid Tumor" and "Metastatic" sample types concerning SNVs from the same experimental data, respectively in Lung Adenocarcinoma (LUAD)/Lung Squamous Cell Carcinoma (LUSC) and Skin Cutaneous Melanoma (SKCM). The interactions between SNVs and miRNAs identified through miRHub can be further investigated as potential biomarkers for prognosis or targets for therapy.