Long noncoding RNAs: pivotal regulators in acute myeloid leukemia.
Ontology highlight
ABSTRACT:
SUBMITTER: Wei S
PROVIDER: S-EPMC5153810 | biostudies-other | 2015
REPOSITORIES: biostudies-other
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Project description:PurposeOptimized strategies for risk classification are essential to tailor therapy for patients with biologically distinctive disease. Risk classification in pediatric acute myeloid leukemia (pAML) relies on detection of translocations and gene mutations. Long noncoding RNA (lncRNA) transcripts have been shown to associate with and mediate malignant phenotypes in acute myeloid leukemia (AML) but have not been comprehensively evaluated in pAML.MethodsTo identify lncRNA transcripts associated with outcomes, we evaluated the annotated lncRNA landscape by transcript sequencing of 1,298 pediatric and 96 adult AML specimens. Upregulated lncRNAs identified in the pAML training set were used to establish a regularized Cox regression model of event-free survival (EFS), yielding a 37 lncRNA signature (lncScore). Discretized lncScores were correlated with initial and postinduction treatment outcomes using Cox proportional hazards models in validation sets. Predictive model performance was compared with standard stratification methods by concordance analysis.ResultsTraining set cases with positive lncScores had 5-year EFS and overall survival rates of 26.7% and 42.7%, respectively, compared with 56.9% and 76.3% with negative lncScores (hazard ratio, 2.48 and 3.16; P < .001). Pediatric validation cohorts and an adult AML group yielded comparable results in magnitude and significance. lncScore remained independently prognostic in multivariable models, including key factors used in preinduction and postinduction risk stratification. Subgroup analysis suggested that lncScores provide additional outcome information in heterogeneous subgroups currently classified as indeterminate risk. Concordance analysis showed that lncScore adds to overall classification accuracy with at least comparable predictive performance to current stratification methods that rely on multiple assays.ConclusionInclusion of the lncScore enhances predictive power of traditional cytogenetic and mutation-defined stratification in pAML with potential, as a single assay, to replace these complex stratification schemes with comparable predictive accuracy.
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Project description:Background: High-throughput next generation sequencing (NGS) technologies enable the detection of biomarkers used for tumor classification, disease monitoring and cancer therapy. Whole-transcriptome analysis using RNA-seq is important, not only as a means of understanding the mechanisms responsible for complex diseases but also to efficiently identify novel genes/exons, splice isoforms, RNA editing, allele-specific mutations, differential gene expression and fusion-transcripts or chimeric RNA (chRNA). Methods: We used Crac, a tool that uses genomic locations and local coverage to classify biological events and directly infer splice and chimeric junctions within a single read. Crac's algorithm extracts transcriptional chimeric events irrespective of annotation with a high sensitivity, and CracTools was used to aggregate, annotate and filter the chRNA reads. The selected chRNA candidates were validated by real time PCR and sequencing. In order to check the tumor specific expression of chRNA, we analyzed a publicly available dataset using a new tag search approach. Results: We present data related to acute myeloid leukemia (AML) RNA-seq analysis. We highlight novel biological cases of chRNA, in addition to previously well characterized leukemia chRNA. We have identified and validated 17 chRNAs among 3 AML patients: 10 from an AML patient with a translocation between chromosomes 15 and 17 (AML-t(15;17), 4 from patient with normal karyotype (AML-NK) 3 from a patient with chromosomal 16 inversion (AML-inv16). The new fusion transcripts can be classified into four groups according to the exon organization. Conclusions: All groups suggest complex but distinct synthesis mechanisms involving either collinear exons of different genes, non-collinear exons, or exons of different chromosomes. Finally, we check tumor-specific expression in a larger RNA-seq AML cohort and identify new AML biomarkers that could improve diagnosis and prognosis of AML.
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Project description:Circular RNAs (circRNAs) are dynamically regulated during differentiation and show cell type-specific expression, which is altered in cancer and can have a direct impact on its various hallmarks. We hypothesized that circRNA expression is deregulated in acute myeloid leukemia (AML) and that circRNA candidates might contribute to the pathogenesis of the disease. To identify leukemia-associated and differentiation-independent changes in circRNA expression, we determined the circular RNAome of 61 AML patients and 16 healthy hematopoietic stem and progenitor cell (HSPC) samples using ribosomal RNA-depleted RNA sequencing. We found hundreds of circRNAs that were differentially expressed between AML and healthy HSPCs. Gene set analysis found that many of these circRNAs were transcribed from genes implicated in leukemia biology. We discovered a circRNA derived from the T-cell transcription factor gene B cell CLL/lymphoma 11B, circBCL11B, which was exclusively expressed in AML patients, but not detected in healthy HSPCs, and associated with a T-cell-like gene expression signature. We were able to validate this finding in an independent cohort of 332 AML patients. Knockdown of circBCL11B had a negative effect on leukemic cell proliferation and resulted in increased cell death of leukemic cells, thereby suggesting circBCL11B as a novel functionally relevant candidate in AML pathogenesis. In summary, our study enables comprehensive insights into circRNA expression changes upon leukemic transformation and provides valuable information on the biology of leukemic cells and potential novel pathway dependencies that are relevant for AML therapy.
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