MicroRNAs (miRNAs) are critical players in development and homeostasis and potent post-transcriptional regulators of numerous transcripts. Despite tremendous progress during the last two decades, key questions such as how many miRNAs are encoded in the human genome, how many distinct miRNA products arise from a single miRNA locus, and how many transcripts are targeted by each mature miRNA product remain largely open. Their answers directly bear upon the community's attempts to unravel and understand the complexity of post-transcriptional regulation in disease. We recently reported our analyses of deep-sequencing transcriptomic data (short RNA-seq) from 1,323 individuals and the discovery of 3,707 novel human miRNAs that are tissue-specific and pri-mate-specific, effectively tripling the number of human miRNA precursors currently in the miRBase repository. We also reported results from a parallel study of short RNA-seq data from 452 healthy in-dividuals where we found that miRNA precursor arms produce multiple isoforms, the isomiRs, and that the isomiRs' abundance profiles have an unexpected dependency on an individual's gender, population, and race. For many of the novel miRNAs and the isomiRs we showed that they are loaded on Argonaute, thus they function in the RNA interference pathway. Lastly, we analyzed breast cancer (BRCA) datasets from The Cancer Genome Atlas (TCGA) and showed that these observations ex-tend to and hold true in the disease context as well. These results indicate that many molecules that are active in the post-transcriptional regulatory layer have eluded us, as has their unexpected dependency on disease subtype, gender, population, and race. These molecules and the interactions that they mediate await discovery and characterization. Notably, due to their human-/primate-specific nature, many of the newly discovered novel miRNAs and their targeted effectors are absent from and thus cannot be captured by mouse models of cancer. In this project, we will be expanding our TCGA BRCA analyses to four more TCGA cancers. In each of the four cases, we will seek novel miRNAs, establish isomiR profiles for known and novel miRNAs, and characterize their dependencies on cancer sub-type, gender, and race. Based on our preliminary findings we expect that some of the novel miRNAs to be discovered in these cancers will be tissue-specific and human-specific. This will help generate novel highly specific signatures for these cancers and their sub-types. By including in our analyses long RNA-seq datasets we will model the regulatory effects of miRNAs/isomiRs on their messenger-RNA/lncRNA targets. The project will generate a wealth of knowledge that does not currently exist and which will help pave new avenues of exploration for the community and generate insights that can eventually lead to new therapeutic approaches.
We recently showed that miRNAs generate isoforms ('isomiRs') whose expression is gen-der-, population-, and race-dependent as well as reported many novel, uncharacterized, human miRNAs that are primate-/human-specific and have tissue-specific expression. Using TCGA breast cancer datasets we showed that these recent findings extend to the disease context, which suggests that primate-/human-specific miRNAs and gender/race-dependent isomiRs mediate currently uncharacterized aspects of post-transcriptional regulation in human cancers. This project will advance the knowledge in this field by analyzing four more TCGA cancers to generate information about previously unsuspected regulatory molecules and events that are absent from cancer mouse models, and to build a knowledge repository that does not currently exist and which will help the community identify novel therapeutic candidates and targeted therapies.
|Telonis, Aristeidis G; Rigoutsos, Isidore (2018) Race Disparities in the Contribution of miRNA Isoforms and tRNA-Derived Fragments to Triple-Negative Breast Cancer. Cancer Res 78:1140-1154|
|Magee, Rogan G; Telonis, Aristeidis G; Loher, Phillipe et al. (2018) Profiles of miRNA Isoforms and tRNA Fragments in Prostate Cancer. Sci Rep 8:5314|
|Magee, Rogan; Loher, Phillipe; Londin, Eric et al. (2017) Threshold-seq: a tool for determining the threshold in short RNA-seq datasets. Bioinformatics 33:2034-2036|
|Magee, Rogan; Telonis, Aristeidis G; Cherlin, Tess et al. (2017) Assessment of isomiR Discrimination Using Commercial qPCR Methods. Noncoding RNA 3:|