Frontiers in Oncology · 2020 · 21 citations · 31 references
MedicineHematologyOncologyGene ExpressionHematologic OncologyMolecular OncologyCancer CytogeneticsGene Fusions In CancerLymphoid NeoplasmsMolecular CytogeneticsOncogenic Fusion GenesPediatric LeukemiasBcr-abl1 Fusion GeneLeukemia CytogeneticsLeukemia-associated Fusion GenesLineage-specific Gene ExpressionPolymerase Chain Reaction AnalysisRna SequencingRna Sequencing (Rna-seq)Survival Rates
Background: Recently, various blood cell lineages expressing the BCR-ABL fusion gene in Philadelphia chromosome (Ph)-positive acute lymphoblastic leukemia (ALL) have been reported. However, the biological and clinical significance of these BCR-ABL lineages has not been established; therefore, we aimed to clarify the impacts of these different BCR-ABL-expressing lineages. Patients: Multi-lineage BCR-ABL expression (multi-Ph) was defined as BCR-ABL expression outside of the B-lineage compartment, as determined by fluorescence in situ hybridization (FISH) in peripheral blood neutrophils and bone marrow clots, and flow cytometry-sorted polymerase chain reaction (PCR). We analyzed IKZF1 deletion patterns by PCR, examined gene expression profiles using RNA sequencing, and compared treatment outcomes across different BCR-ABL-expressing lineages. Results: Among the 21 multi-Ph patients in our 59-patient cohort (36%), BCR-ABL expression was detected at the multipotential progenitor level. However, no IKZF1 deletion patterns or gene expression profiles were identified that were specific for multi-Ph. However, multi-Ph patients were found to have better survival rates than patients with uni-lineage BCR-ABL expression [event-free survival (EFS): 74% vs. 33%, P = 0.01; overall survival (OS): 79% vs. 44% at 4 years, P = 0.01]. In multivariate analyses, multi-Ph was identified as a good prognostic factor for both EFS and OS. Conclusion: We confirmed that more than one-third of Ph+ALL patients could be classified as mutli-Ph. Although no specific molecular characteristics were identified for multi-Ph, this phenotype was associated with better treatment outcomes.
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HTSeq—a Python framework to work with high-throughput sequencing data
Simon Anders, Paul Theodor Pyl, Wolfgang Huber · Bioinformatics · 2014 · 22.7K citations · Full text
Daehwan Kim, Geo Pertea, Cole Trapnell et al. · Genome biology · 2013 · 13.7K citations · Full text