How microRNAs go awry in cancer: Exploring the underlying factors of miRNA dysregulation

Abstract

MicroRNAs (miRNA) are short, non-coding molecules (~23nt) that fine-tune mRNA expression at the post-transcriptional level by repressing or cleaving their targets. A single miRNA targets several mRNAs; dysfunctions disrupt biological systems. Unravelling the interactome of regulators and targets is vital for biological networks. Cancer research is one of the hottest fields, due to its high prevalence and financial burden. Despite improvements in prevention and therapy, challenges from disease complexity and precision medicine limit the effciency of targeted approaches. Accurate characterization of all interactions and mechanisms is essential to fight it. In this study, we matched whole genome, RNA and small RNA sequencing data acquired from the International Cancer Genome Consortium (ICGC) for Liver cancer patients, resulting in a dataset of 40 samples with the aim to explain the dysregulation of miRNA expression. DNA variants were readily extracted using the “Broad variant call pipeline” of ICGC. Utilization of DNase-seq data indicated an average promoter region activity of 1500bp upstream and 500bp downstream of the transcription start site. Variations were then intersected to promoter regions. Analysis of transcription factors (TF), which regulate the expression of DNA bound genes, as well as miRNAs, was done using FIMO prediction algorithm (25bp proximal window centered on identified variants, p-value < 0.000001) combined with JASPAR transcription factor motifs to identify mutated transcription factor binding sites. Matching RNA-seq expression was then combined with small RNA-seq expression and correlation analysis was performed so as to identify dysregulated TF::miRNA interacting pairs with mutations on their regulatory elements, on the basis that their correlated expression is potentially disrupted due to overlapping variation events. A total of 172691 variants events were identified in liver promoter regions. Analysis of mutational load using chi-square test in various gene biotypes indicated differences with protein-coding and small RNA (excluding miRNA) categories exhibiting the higher rates. Variants in TF genes generally showed low frequency (3.64% of all TF genes analyzed), necessitating a deeper analysis to discover if the underling mechanisms of TFBS are affected by variation events. Of all TFs utilized in the FIMO analysis (n=39), ZNF263, which has been associated to a variety of tumours, was found to have the highest percentage of mutated binding motif (31%) followed by ZNF384 (28%). Pearson correlation analysis between the expression of miRNAs and TFs with and without mutations overlapping TF binding sites in miRNA promoters identified HNF4A (Hepatocyte Nuclear Factor 4) and hsa-mir-122 having significant difference in their correlated expression (Transcripts per million normalized values) between wildtype samples (n=20, r=0.8, p=0.00002) and mutated individuals (n=20, r=0.25, p=026), with both molecules being associated with liver localized functions in the literature. These results demonstrate the importance of further enriching the interactome towards a more complete network in order to achieve a more effective and accurate precision medicine. Hellenic Foundation for Research and Innovation (H.F.R.I.) under the ‘1st Call for H.F.R.I. Research Projects to support Faculty Members & Researchers and the procurement of high-cost research equipment grant’ [2563]. Funding for open access charge. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.