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The application of RNA sequencing for the diagnosis and genomic classification of pediatric acute lymphoblastic leukemia

ABSTRACT: Acute lymphoblastic leukaemia (ALL) is the most common childhood malignancy, and implementation of risk-adapted therapy has been instrumental in the dramatic improvements in clinical outcomes. A key to risk-adapted therapies includes the identification of genomic features of individual tumors, including chromosome number (for hyper- and hypodiploidy) and gene fusions, notably ETV6-RUNX1, TCF3-PBX1 and BCR-ABL1 in B-cell ALL (B-ALL). RNA-sequencing (RNA-seq) of large ALL cohorts has expanded the number of recurrent gene fusions recognized as drivers in ALL, and identification of these new entities will contribute to refining ALL risk stratification. We used RNA-seq on 126 ALL patients from our clinical service to test the utility of including RNA-seq in standard of care diagnostic pipelines to detect gene rearrangements and IKZF1 deletions. RNA-seq identified 86% of rearrangements detected by standard of care diagnostics. KMT2A-rearrangements (MLL), whilst usually identified, were the most commonly missed by RNA-seq as a result of low expression. RNA-seq identified rearrangements that were not detected by standard of care testing in nine patients. These were found in patients who were not classifiable using standard molecular assessment. We developed an approach to detect the commonest IKZF1 deletion from RNA-seq data and validated this using a RQ-PCR assay. We applied an expression classifier to identify Ph-like B-ALL patients. T-ALL proved a rich source of novel gene fusions which have clinical implications or provide insights into disease biology. Our experience shows that RNA-seq can be implemented within an individual clinical service to enhance the current molecular diagnostic risk classification of ALL.

PROVIDER: EGAS00001004212 | EGA |

REPOSITORIES: EGA

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Project description:We studied a cohort of 221 high-risk pediatric B-progenitor ALL patients that excluded known high risk ALL subtypes (BCR-ABL1 and infant ALL), using Affymetrix single nucleotide polymorphism microarrays, gene expression profiling and candidate gene resequencing. A CNA poor outcome predictor was identified using a semi-supervised principal components approach, and tested in an independent validation cohort of 258 pediatric B-progenitor ALL cases. Over 50 regions of recurring somatically acquired CNA, with the most frequently targeted genes encoding regulators of B-lymphoid development (66.8% of cases; with PAX5 targeted in 31.7% and IKZF1 in 28.6%). A CNA classifier identified a very poor outcome subgroup in the high-risk cohort (P=4.2x10-5) and was strongly associated with the presence of deletions involving IKZF1, which encodes the early lymphoid transcription factor IKAROS. This classifier, and IKZF1 deletions, also predicted poor outcome and elevated minimal residual disease at the end of induction therapy in the validation cohort. The gene expression signature of the poor outcome group was characterized by reduced expression of B lineage specific genes, and was highly related to the expressing signature of BCR-ABL1 ALL, a known high-risk ALL subtype also characterized by a high frequency of IKZF1 deletion.Somatically acquired deletions involving IKZF1 identify a very poor outcome subgroup of pediatric ALL patients. Incorporation of molecular tests to identify IKZF1 deletion in diagnostic leukemic blasts should improve the ability to accurately risk stratify patients for appropriate therapy. Affymetrix U133A arrays were performed according to the maufacturers directions on RNA extracted from cryopreserved diagnostic bone marrow or peripheral blood samples. Samples with less than 80% blasts were flow sorted prior to RNA extraction Experiment Overall Design: One hundred seventy five pediatric B-progenitor ALL samples were studied using either Affymetrix U133A

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The application of RNA sequencing for the diagnosis and genomic classification of pediatric acute lymphoblastic leukemia

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