Dataset Information

Excess congenital non-synonymous variation in leukemia-associated genes in MLL- infant leukemia: a Children's Oncology Group report.

ABSTRACT: Infant leukemia (IL) is a rare sporadic cancer with a grim prognosis. Although most cases are accompanied by MLL rearrangements and harbor very few somatic mutations, less is known about the genetics of the cases without MLL translocations. We performed the largest exome-sequencing study to date on matched non-cancer DNA from pairs of mothers and IL patients to characterize congenital variation that may contribute to early leukemogenesis. Using the COSMIC database to define acute leukemia-associated candidate genes, we find a significant enrichment of rare, potentially functional congenital variation in IL patients compared with randomly selected genes within the same patients and unaffected pediatric controls. IL acute myeloid leukemia (AML) patients had more overall variation than IL acute lymphocytic leukemia (ALL) patients, but less of that variation was inherited from mothers. Of our candidate genes, we found that MLL3 was a compound heterozygote in every infant who developed AML and 50% of infants who developed ALL. These data suggest a model by which known genetic mechanisms for leukemogenesis could be disrupted without an abundance of somatic mutation or chromosomal rearrangements. This model would be consistent with existing models for the establishment of leukemia clones in utero and the high rate of IL concordance in monozygotic twins.

SUBMITTER: Valentine MC

PROVIDER: S-EPMC4045651 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

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Excess congenital non-synonymous variation in leukemia-associated genes in MLL- infant leukemia: a Children's Oncology Group report.

Valentine M C MC Linabery A M AM Chasnoff S S Hughes A E O AE Mallaney C C Sanchez N N Giacalone J J Heerema N A NA Hilden J M JM Spector L G LG Ross J A JA Druley T E TE

Leukemia 20131204 6

Infant leukemia (IL) is a rare sporadic cancer with a grim prognosis. Although most cases are accompanied by MLL rearrangements and harbor very few somatic mutations, less is known about the genetics of the cases without MLL translocations. We performed the largest exome-sequencing study to date on matched non-cancer DNA from pairs of mothers and IL patients to characterize congenital variation that may contribute to early leukemogenesis. Using the COSMIC database to define acute leukemia-associ ...[more]

PMID: 24301523

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Project description:PAPER 1:"Identification of novel subgroups of high-risk pediatric precursor B acute lymphoblastic leukemia (B-ALL) by unsupervised microarray analysis: clinical correlates and therapeutic implications. A Children's Oncology Group (COG) study." ABSTRACT We examined gene expression profiles of pre-treatment specimens from 207 patients from the COG P9906 study to identify signatures of children with high risk B-precursor acute lymphoblastic leukemia (ALL) and to determine whether the resulting clusters are associated with either specific clinical features or treatment response characteristics. Four unsupervised clustering methods were utilized to classify patients into similar groups. The different clustering algorithms showed significant overlap in cluster membership. Two clusters contained all cases with either t(1;19)(q23;p13) translocations or MLL rearrangements. The other six clusters were novel and had no recurring chromosomal abnormalities or distinctive clinical features. Members of two of these novel clusters had significant survival differences when compared to the overall 4-year relapse-free survival (RFS) of 61%. These included clusters of patients with either significantly better (94.7%) or worse (21.0%) RFS at 4 years. Children of Hispanic/Latino ethnicity were disproportionately present in the poor outcome cluster. The poor outcome cluster represents a novel biologically distinctive subset of B-precursor ALL that may occur at least as frequently as BCR/ABL. Further molecular characterization of this cluster may lead to the discovery of genomic abnormalities that can be targeted to improve the currently dismal outcome for children with this gene signature. The Sample data have also been used in another study: PAPER 2: "Gene expression classifiers for minimal residual disease and relapse free survival improve outcome prediction and risk classification in children with high risk acute lymphoblastic leukemia. A Children's Oncology Group study". ABSTRACT Background. Nearly 25% of children with B-precursor ALL present with "high-risk" disease (HR-ALL) that is resistant to current therapies. Gene expression profiling may yield molecular classifiers for outcome prediction that can be used to improve risk classification and therapeutic targeting. Methods. Expression profiles were obtained in pre-treatment leukemic samples from 207 uniformly treated children with HR-ALL. Relapse free survival (RFS) was 61% at 4 years and flow cytometric measures of minimal residual disease (MRD) at the end of induction (day 29) were predictive of outcome (P<0.001). Molecular classifiers predictive of RFS and MRD were developed using extensive cross-validation procedures. Results. A 38 gene molecular risk classifier predictive of RFS (MRC-RFS) distinguished two groups in HR-ALL with different relapse risks: low (4 yr RFS: 81%, n=109) vs. high (4 yr RFS: 50%, n=98) (P<0.0001). In multivariate analysis, the best predictor combined MRC-RFS and day 29 flow MRD data, classifying children into low (87% RFS), intermediate (62% RFS), or high risk (29% RFS) groups (P<0.0001). A 21 gene molecular classifier predictive of MRD could effectively substitute for day 29 flow MRD, yielding a combined classifier that similarly distinguished three risk groups at pre-treatment (low: 82% RFS; intermediate: 63% RFS; and high risk: 45% RFS) (P<0.0001). This combined molecular classifier was further validated on an independent cohort of 84 children with HR-ALL (P = 0.006). Conclusions. Molecular classifiers predictive of RFS and MRD can be used to distinguish distinct prognostic groups within HR-ALL, significantly improving risk classification schemes and the ability to prospectively identify children at diagnosis who will respond to or fail current treatment regimens. NOTE: Due to Children's Oncology Group (COG) restrictions, outcome and MRD data cannot be provided as part of the covariate data for this dataset at the present time. If you would like to arrange individual access to this data, please contact COG or the PI of this study, Dr. Cheryl Willman, at the University of New Mexico Cancer Center (cwillman@unm.edu) to arrange a collaboration.

Dataset Information

Excess congenital non-synonymous variation in leukemia-associated genes in MLL- infant leukemia: a Children's Oncology Group report.

Publications

Excess congenital non-synonymous variation in leukemia-associated genes in MLL- infant leukemia: a Children's Oncology Group report.

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