T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive malignancy originating from T-cell precursors. The genetic landscape of T-ALL has been largely characterized by next-generation sequencing. Yet, the transcriptome of miRNAs (miRNome) of T-ALL has been less extensively studied. Using small RNA sequencing, we characterized the miRNome of 34 pediatric T-ALL samples, including the expression of isomiRs and the identification of candidate novel miRNAs (not previously annotated in miRBase). For the first time, we show that immunophenotypic subtypes of T-ALL present different miRNA expression profiles. To extend miRNome characteristics in T-ALL (to 82 T-ALL cases), we combined our small RNA-seq results with data available in Gene Expression Omnibus. We report on miRNAs most abundantly expressed in pediatric T-ALL and miRNAs differentially expressed in T-ALL versus normal mature T-lymphocytes and thymocytes, representing candidate oncogenic and tumor suppressor miRNAs. Using eight target prediction algorithms and pathway enrichment analysis, we identified differentially expressed miRNAs and their predicted targets implicated in processes (defined in Gene Ontology and Kyoto Encyclopedia of Genes and Genomes) of potential importance in pathogenesis of T-ALL, including interleukin-6–mediated signaling, mTOR signaling, and regulation of apoptosis. We finally focused on hsa-mir-106a-363 cluster and functionally validated direct interactions of hsa-miR-20b-5p and hsa-miR-363-3p with 3′ untranslated regions of their predicted targets ( PTEN , SOS1 , LATS2 ), overrepresented in regulation of apoptosis. hsa-mir-106a-363 is a paralogue of prototypic oncogenic hsa-mir-17-92 cluster with yet unestablished role in the pathogenesis of T-ALL. Our study provides a firm basis and data resource for functional analyses on the role of miRNA-mRNA interactions in T-ALL.

Optimal endogenous controls enable reliable normalization of microRNA (miRNA) expression in reverse-transcription quantitative PCR (RT-qPCR). This is particularly important when miRNAs are considered as candidate diagnostic or prognostic biomarkers. Universal endogenous controls are lacking, thus candidate normalizers must be evaluated individually for each experiment. Here we present a strategy that we applied to the identification of optimal control miRNAs for RT-qPCR profiling of miRNA expression in T-cell acute lymphoblastic leukemia (T-ALL) and in normal cells of T-lineage. First, using NormFinder for an iterative analysis of miRNA stability in our miRNA-seq data, we established the number of control miRNAs to be used in RT-qPCR. Then, we identified optimal control miRNAs by a comprehensive analysis of miRNA stability in miRNA-seq data and in RT-qPCR by analysis of RT-qPCR amplification efficiency and expression across a variety of T-lineage samples and T-ALL cell line culture conditions. We then showed the utility of the combination of three miRNAs as endogenous normalizers (hsa-miR-16-5p, hsa-miR-25-3p, and hsa-let-7a-5p). These miRNAs might serve as first-line candidate endogenous controls for RT-qPCR analysis of miRNAs in different types of T-lineage samples: T-ALL patient samples, T-ALL cell lines, normal immature thymocytes, and mature T-lymphocytes. The strategy we present is universal and can be transferred to other RT-qPCR experiments.

No abstract