The genomic landscape of pediatric T-cell acute lymphoblastic leukemia reveals novel X-linked somatic mutations associated with apoptosis resistance. [RNA-Seq]
Transcriptomics Dataset
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General Information
AccessionGSE78785
TitleThe genomic landscape of pediatric T-cell acute lymphoblastic leukemia reveals novel X-linked somatic mutations associated with apoptosis resistance. [RNA-Seq]
DescriptionBackground. T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy with a dismal prognosis. It represents 15%% of pediatric ALL and has a threefold higher incidence among males. T-cell transformation is a multi-step process involving cooperating events leading to altered T-cell signaling, proliferation, differentiation and survival. Many recurrent alterations have been identified and help define molecular subgroups of T-ALL, however the full range of events involved in driving transformation remain to be defined. Results. Using an integrative approach combining genomic and transcriptomic data, we performed comprehensive molecular characterization of 30 pediatric T-ALLs. We identified common T-ALL targets and confirmed the overall poor outcome of early immature cases. We also showed that deletion of the CDKN2A locus is associated with lower risk of relapse. In addition, we identified novel T-ALL drivers including a member of the spliceosome machinery U2AF1 as well as novel X-linked tumor suppressors MED12 and USP9X, that had never been associated to T-ALL before. Interestingly, almost 60%% of these events were found in early immature cases which represented only 35%% of the cohort. Functional validations further demonstrated the putative role of these novel T-ALL genes in driving transformation by demonstrating the aberrant splicing provoked by U2AF1 p.R35L and the protective effect against apoptosis of MED12 and USP9X repression. Conclusions. This study highlights the underlying genomic complexity of pediatric T-ALL, and the need for larger integrative studies to decipher the mechanisms that contribute to its various subtypes and provide opportunities to refine patient stratification and treatment.
Landing Pagehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE78785
RepositoryGene Expression Omnibus
Tools used to analyze the dataset

Dataset Accession

ARCHS4
Published September 2017
ARCHS4 provides access to gene counts from HiSeq 2000 and HiSeq 2500 platforms for human and mouse experiments from GEO ...
4645
Clustergrammer
Published October 2017
Web-based tool for visualizing and analyzing high-dimensional data as interactive and shareable heatmaps
4645
Canned Analyses generated with the dataset

Dataset Accession
Tool Name

Interactive heatmap visualization of RNA-seq dataset GSE78785
Highly interactive web-based heatmap visualization of the top 500 most variable genes in t...
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