A novel approach for a joint analysis of isomiR and mRNA expression data reveals features of isomiR targeting in breast cancer

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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“…We recently made a similar observation in the context of breast cancer ( Nersisyan et al , 2022 ). Specifically, we showed that the number of active isomiRs (in terms of anti-correlation patterns with predicted targets) is dramatically lower in luminal A, luminal B and basal-like breast cancer samples compared to the adjacent normal tissue samples.…”

The signature of SARS‐CoV‐2 evolution reflects selective pressures within human guts

“…Commonly, the overlap of the targets by different software is weak at best 26,27 . While RNA22 predicts more individual miRNA‐mRNA interactions than TargetScan does, it misses the majority of classical seed region binding sites in 3 ’ UTRs.…”

“…Commonly, the overlap of the targets by different software is weak at best. 26,27 While RNA22 predicts more individual miRNA-mRNA interactions than TargetScan does, it misses the majority of classical seed region binding sites in 3 ' UTRs. Moreover, the prediction results heavily depend on the tool-specific internal thresholds, with sensitivity and specificity expected to vary depending on particular thresholds.…”

One locus, several functional RNAs—emerging roles of the mechanisms responsible for the sequence variability of microRNAs

“…A recent meta-analysis of available cancer datasets and publications not only supported this approach but could identify specific miRNA isomiRs that can be used as biomarkers for certain tumor types (Zelli et al 2021). A further deep analysis of isomiR datasets could differentiate even among breast cancer subtypes (Nersisyan et al 2022), whereas a recent study provided evidence that the heterogeneous nuclear ribonucleoprotein C (hnRNPC) induced 5' isomiR shift of miR-21-5p could lead to liver cancer (Park et al 2022). All these studies show that isomiR-based tumor profiling seems to be a very encouraging approach for cancer diagnostics but isomiR-based tumor targeting also holds promise for future therapy applications.…”