Abstract
A hallmark of cancer evolution is that the tumor may change its cell identity and improve its survival and fitness. Drastic change in microRNA (miRNA) composition and quantities accompany such dynamic processes. Cancer samples are composed of cells’ mixtures of varying stages of cancerous progress. Therefore, cell-specific molecular profiling represents cellular averaging. In this study, we consider the degree to which altering miRNAs composition shifts cell behavior. We used COMICS, an iterative framework that simulates the stochastic events of miRNA-mRNA pairing, using a probabilistic approach. COMICS simulates the likelihood that cells change their transcriptome following many iterations (100 k). Results of COMICS from the human cell line (HeLa) confirmed that most genes are resistant to miRNA regulation. However, COMICS results suggest that the composition of the abundant miRNAs dictates the nature of the cells (across three cell lines) regardless of its actual mRNA steady-state. In silico perturbations of cell lines (i.e., by overexpressing miRNAs) allowed to classify genes according to their sensitivity and resilience to any combination of miRNA perturbations. Our results expose an overlooked quantitative dimension for a set of genes and miRNA regulation in living cells. The immediate implication is that even relatively modest overexpression of specific miRNAs may shift cell identity and impact cancer evolution.
Highlights
Mature microRNAs are non-coding RNA molecules that regulate genes through base complementarity with their cognate mRNAs, at the 3′-untranslated regions (3′-UTR) (Moore et al, 2015)
Our previous study modeled the outcome of the miRNA-mRNA network in living cells by simulating the stochastic nature of miRNA regulation (Mahlab-Aviv et al, 2019)
The nature of miRNA regulation in living cells is depicted by the absolute quantities, composition, and stoichiometry of miRNAs and mRNAs (Balaga et al, 2012)
Summary
Mature microRNAs (miRNAs) are non-coding RNA molecules that regulate genes through base complementarity with their cognate mRNAs, at the 3′-untranslated regions (3′-UTR) (Moore et al, 2015). In each human cell, only a few dozens of miRNAs are expressed in substantial amounts. In reality, ∼60% of the human coding genes are postulated as targets for miRNA regulation (Ha and Kim, 2014; Jonas and Izaurralde, 2015). Experimental results using CLIP-based deep sequencing protocols provide quantitative amounts of miRNAs and mRNAs in living cells (Li et al, 2014). These protocols suffer from poor consistency (Lu and Leslie, 2016)
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