ArticleFrontiers in genetics2022
A novel approach for a joint analysis of isomiR and mRNA expression data reveals features of isomiR targeting in breast cancer.
Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Targetome profile of hsa-miR-93-5p is resistant to isoform formation in prostate adenocarcinoma.PeerJ · 2026Article
- CorrAdjust unveils biologically relevant transcriptomic correlations by efficiently eliminating hidden confounders.Nucleic acids research · 2025Article
- One locus, several functional RNAs-emerging roles of the mechanisms responsible for the sequence variability of microRNAs.Biologia futura · 2023Review
- Differential co-expression network analysis with DCoNA reveals isomiR targeting aberrations in prostate cancer.Bioinformatics (Oxford, England) · 2023Article
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5 authors.
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Abstract
A widely used procedure for selecting significant miRNA-mRNA or isomiR-mRNA pairs out of predicted interactions involves calculating the correlation between expression levels of miRNAs/isomiRs and mRNAs in a series of samples. In this manuscript, we aimed to assess the validity of this procedure by comparing isomiR-mRNA correlation profiles in sets of sequence-based predicted target mRNAs and non-target mRNAs (negative controls). Target prediction was carried out using RNA22 and TargetScan algorithms. Spearman's correlation analysis was conducted using miRNA and mRNA sequencing data of The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) project. Luminal A, luminal B, basal-like breast cancer subtypes, and adjacent normal tissue samples were analyzed separately. Using the sets of putative targets and non-targets, we introduced adjusted isomiR targeting activity (ITA)-the number of negatively correlated potential isomiR targets adjusted by the background (estimated using non-target mRNAs). We found that for most isomiRs a significant negative correlation between isomiR-mRNA expression levels appeared more often in a set of predicted targets compared to the non-targets. This trend was detected for both classical seed region binding types (8mer, 7mer-m8, 7mer-A1, 6mer) predicted by TargetScan and the non-classical ones (G:U wobbles and up to one mismatch or unpaired nucleotide within seed sequence) predicted by RNA22. Adjusted ITA distributions were similar for target sites located in 3'-UTRs and coding mRNA sequences, while 5'-UTRs had much lower scores. Finally, we observed strong cancer subtype-specific patterns of isomiR activity, highlighting the differences between breast cancer molecular subtypes and normal tissues. Surprisingly, our target prediction- and correlation-based estimates of isomiR activities were practically non-correlated with the average isomiR expression levels neither in cancerous nor in normal samples.
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