Characterization of a network of tumor suppressor microRNA''s in T Cell acute lymphoblastic leukemia

Purpose: The purpose of this study is to identify functionally inter-connected group of miRNAs whose reduced expression promotes leukemia development in vivo. We searched for relevant target genes of these miRNAs that are upregulated in T-ALL relative to controls. Methods: In order to examine the global gene expression, we generated 9 T-ALL patients and 4 normal controls by deep sequencing using Illumina Hi-Seq sequencer. The sequence reads that passed quality filters were analyzed using Spliced Transcripts Alignment to a Reference aligner (STAR) followed by differential gene expression analysis using DESeq. Results: Using an optimized data analysis workflow, we mapped reads per sample to the human genome (build hg19) and identified transcripts in both patient and controls with STAR workflow. We applied a machine learning approach to eliminate targets with redundant miRNA-mediated control. This strategy finds a convergence on the Myb oncogene and less prominent effects on the Hpb1 transcription factor. The abundance of both genes is increased in T-ALL and each can promote T-ALL in vivo. Conclusion: Our study reveals a Myc regulated network of tumor suppressor miRNAs in T-ALL. We identified a small number of functionally validated tumor suppressor miRNAs. These miRNAs are repressed upon Myc activation and this links their expression directly to Myb a key oncogenic driver in T-ALL. Overall design: Examination of global gene expression in 9 T-ALL patients and 4 normal controls using total RNA sequencing. BaseMeanA in DESeq_results.xlsx is the control.

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Sanghvi VR, Mavrakis KJ, Van der Meulen J, Boice M, Wolfe AL, Carty M, Mohan P, Rondou P, Socci ND, Benoit Y, Taghon T, Van Vlierberghe P, Leslie CS, Speleman F, Wendel HG