Dataset Information

IKZF1 deletions predict relapse in uniformly treated pediatric precursor B-ALL

ABSTRACT: Relapse is the most common cause of treatment failure in pediatric acute lymphoblastic leukemia (ALL) and is often difficult to predict. To explore the prognostic impact of recurrent DNA copy number abnormalities on relapse, we performed high-resolution genomic profiling of 34 paired diagnosis-relapse ALL samples. Recurrent lesions detected at diagnosis, including PAX5, CDKN2A, and EBF1, were frequently absent at relapse, indicating that they represent secondary events that may be absent in the relapse-prone therapy-resistant progenitor cell. In contrast, deletions and nonsense mutations in IKZF1 (IKAROS), were highly enriched and consistently preserved at the time of relapse. A targeted copy number screen in an unselected cohort of 131 precursor B-ALL cases, enrolled in the dexamethasone-based Dutch Childhood Oncology Group treatment protocol ALL9, revealed that IKZF1 deletions are significantly associated with poor relapse-free and overall survival rates. Separate analysis of ALL9-treatment subgroups revealed that non-high-risk patients with IKZF1 deletions exhibited a ~12-fold higher relative relapse rate than those without IKZF1 deletions. Consequently, IKZF1 deletion status allowed the prospective identification of 53% of the relapse-prone non-high-risk-classified patients within this subgroup and, therefore, serves as one of the strongest predictors of relapse at the time of diagnosis with high potential for future risk stratification. Affymetrix NspI 250k array data of 34 paired diagnosis and relapse samples of pediatric ALL. From 13 patients a complete remission sample was available. Four cases had 2 relapses.

ORGANISM(S): Homo sapiens

PROVIDER: GSE20353 | GEO | 2010/03/01

SECONDARY ACCESSION(S): PRJNA125447

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

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

Dataset Information

IKZF1 deletions predict relapse in uniformly treated pediatric precursor B-ALL

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets