Knowledge about the presence or absence of miRNA isoforms (isomiRs) can successfully discriminate amongst 32 TCGA cancer types

Abstract

Isoforms of human miRNAs (isomiRs) are constitutively expressed with tissue- and disease-subtype-dependencies. We studied 10 271 tumor datasets from The Cancer Genome Atlas (TCGA) to evaluate whether isomiRs can distinguish amongst 32 TCGA cancers. Unlike previous approaches, we built a classifier that relied solely on ‘binarized’ isomiR profiles: each isomiR is simply labeled as ‘present’ or ‘absent’. The resulting classifier successfully labeled tumor datasets with an average sensitivity of 90% and a false discovery rate (FDR) of 3%, surpassing the performance of expression-based classification. The classifier maintained its power even after a 15× reduction in the number of isomiRs that were used for training. Notably, the classifier could correctly predict the cancer type in non-TCGA datasets from diverse platforms. Our analysis revealed that the most discriminatory isomiRs happen to also be differentially expressed between normal tissue and cancer. Even so, we find that these highly discriminating isomiRs have not been attracting the most research attention in the literature. Given their ability to successfully classify datasets from 32 cancers, isomiRs and our resulting ‘Pan-cancer Atlas’ of isomiR expression could serve as a suitable framework to explore novel cancer biomarkers.

Unification of miRNA and isomiR research: the mirGFF3 format and the mirtop API

“…However, it has already been shown that, in humans, these endpoint variations are constitutive in both healthy individuals and patients [10,24,25]. In fact, isomiRs have been shown to depend on a person's sex, population origin, and ethnicity [10,24], as well as on tissue, tissue state, and disease subtype [26,27]. Nontemplated nucleotide additions at the 3'-end can be due to nucleotide transferases (TUTase) that generally add adenine or uridine nucleotides [28].…”

“…Finally, post-transcriptional processing of miRNAs can generate nucleotide changes at any position of the sequence by RNA processing enzymes, such as A-to-I editing by ADAR enzymes [30]. The specific function of isomiRs is still not well understood, but multiple studies have suggested a context-specific effect of isomiRs on gene regulation [26,28,31,32]. This is further supported by the fact that different isomiRs from the same mature miRNA can target virtually non-overlapping sets of transcripts [10,[33][34][35].…”

AQ-seq: Accurate quantification of microRNAs and their variants

“…Growing evidence suggests that isomiRs are generated in a context-dependent manner and play physiologically relevant roles during developmental and pathological processes (Hinton et al 2014;Tan et al 2014;Guo et al 2016;Wang et al 2016). Notably, it was shown that isomiR profiles successfully classify diverse cancer types and, when combined with miRNA profiles, improve discrimination between cancer and normal tissues (Telonis et al 2015;Koppers-Lalic et al 2016;Telonis et al 2017), highlighting isomiRs as potential diagnostic biomarkers. Therefore, applying AQ-seq to biosamples may enhance the diagnostic power of sRNA-seq.…”

Direct detection of circulating microRNA-122 using dynamic chemical labelling with single molecule detection overcomes stability and isomiR challenges for biomarker qualification

“…These isomiRs increase the complexity of correctly identifying and quantifying specific microRNA species. Specific isomiR patterns have been reported to stratify diseases, such as cancer 6 , suggesting that accurate measurement of specific isomiRs may have clinical utility. At present, RNA sequencing is the only technique able to accurately detect and quantify isomiRs.…”