Long non-coding RNAs defining major subtypes of B cell precursor acute lymphoblastic leukemia.

BACKGROUND: Long non-coding RNAs (lncRNAs) have emerged as a novel class of RNA due to its diverse mechanism in cancer development and progression. However, the role and expression pattern of lncRNAs in molecular subtypes of B cell acute lymphoblastic leukemia (BCP-ALL) have not yet been investigated. Here, we assess to what extent lncRNA expression and DNA methylation is driving the progression of relapsed BCP-ALL subtypes and we determine if the expression and DNA methylation profile of lncRNAs correlates with established BCP-ALL subtypes. METHODS: We performed RNA sequencing and DNA methylation (Illumina Infinium microarray) of 40 diagnosis and 42 relapse samples from 45 BCP-ALL patients in a German cohort and quantified lncRNA expression. Unsupervised clustering was applied to ascertain and confirm that the lncRNA-based classification of the BCP-ALL molecular subtypes is present in both our cohort and an independent validation cohort of 47 patients. A differential expression and differential methylation analysis was applied to determine the subtype-specific, relapse-specific, and differentially methylated lncRNAs. Potential functions of subtype-specific lncRNAs were determined by using co-expression-based analysis on nearby (cis) and distally (trans) located protein-coding genes. RESULTS: Using an integrative Bioinformatics analysis, we developed a comprehensive catalog of 1235 aberrantly dysregulated BCP-ALL subtype-specific and 942 relapse-specific lncRNAs and the methylation profile of three subtypes of BCP-ALL. The 1235 subtype-specific lncRNA signature represented a similar classification of the molecular subtypes of BCP-ALL in the independent validation cohort. We identified a strong correlation between the DUX4-specific lncRNAs and genes involved in the activation of TGF-ß and Hippo signaling pathways. Similarly, Ph-like-specific lncRNAs were correlated with genes involved in the activation of PI3K-AKT, mTOR, and JAK-STAT signaling pathways. Interestingly, the relapse-specific lncRNAs correlated with the activation of metabolic and signaling pathways. Finally, we found 23 promoter methylated lncRNAs epigenetically facilitating their expression levels. CONCLUSION: Here, we describe a set of subtype-specific and relapse-specific lncRNAs from three major BCP-ALL subtypes and define their potential functions and epigenetic regulation. The subtype-specific lncRNAs are reproducible and can effectively stratify BCP-ALL subtypes. Our data uncover the diverse mechanism of action of lncRNAs in BCP-ALL subtypes defining which lncRNAs are involved in the pathogenesis of disease and are relevant for the stratification of BCP-ALL subtypes.

Integrated analysis of relapsed B-cell precursor Acute Lymphoblastic Leukemia identifies subtype-specific cytokine and metabolic signatures.

Recent efforts reclassified B-Cell Precursor Acute Lymphoblastic Leukemia (BCP-ALL) into more refined subtypes. Nevertheless, outcomes of relapsed BCP-ALL remain unsatisfactory, particularly in adult patients where the molecular basis of relapse is still poorly understood. To elucidate the evolution of relapse in BCP-ALL, we established a comprehensive multi-omics dataset including DNA-sequencing, RNA-sequencing, DNA methylation array and proteome MASS-spec data from matched diagnosis and relapse samples of BCP-ALL patients (n = 50) including the subtypes DUX4, Ph-like and two aneuploid subtypes. Relapse-specific alterations were enriched for chromatin modifiers, nucleotide and steroid metabolism including the novel candidates FPGS, AGBL and ZNF483. The proteome expression analysis unraveled deregulation of metabolic pathways at relapse including the key proteins G6PD, TKT, GPI and PGD. Moreover, we identified a novel relapse-specific gene signature specific for DUX4 BCP-ALL patients highlighting chemotaxis and cytokine environment as a possible driver event at relapse. This study presents novel insights at distinct molecular levels of relapsed BCP-ALL based on a comprehensive multi-omics integrated data set including a valuable proteomics data set. The relapse specific aberrations reveal metabolic signatures on genomic and proteomic levels in BCP-ALL relapse. Furthermore, the chemokine expression signature in DUX4 relapse underscores the distinct status of DUX4-fusion BCP-ALL.