64 research outputs found
Detection of minimal residual disease identifies differences in treatment response between T-ALL and precursor B-ALL
We performed sensitive polymerase chain reaction-based minimal residual
disease (MRD) analyses on bone marrow samples at 9 follow-up time points
in 71 children with T-lineage acute lymphoblastic leukemia (T-ALL) and
compared the results with the precursor B-lineage ALL (B-ALL) results (n =
210) of our previous study. At the first 5 follow-up time points, the
frequency of MRD-positive patients and the MRD levels were higher in T-ALL
than in precursor-B-ALL, reflecting the more frequent occurrence of
resistant disease in T-ALL. Subsequently, patients were classified
according to their MRD level at time point 1 (TP1), taken at the end of
induction treatment (5 weeks), and at TP2 just before the start of
consolidation treatment (3 months). Patients were considered at low risk
if TP1 and TP2 were MRD negative and at high risk if MRD levels at TP1 and
TP2 were 10(-3) or higher; remaining patients were considered at
intermediate risk. The relative distribution of patients with T-ALL (n =
43) over the MRD-based risk groups differed significantly from that of
precursor B-ALL (n = 109). Twenty-three percent of patients with T-ALL and
46% of patients with precursor B-ALL were classified in the low-risk group
(P =.01) and had a 5-year relapse-free survival (RFS) rate of 98% or
greater. In contrast, 28% of patients with T-ALL were classified in the
MRD-based high-risk group compared to only 11% of patients with precursor
B-ALL (P =.02), and the RFS rates were 0% and 25%, respectively (P =.03).
Not only was the distribution of patients with T-ALL different over the
MRD-based risk groups, the prognostic value of MRD levels at TP1 and TP2
was higher in T-ALL (larger RFS gradient), and consistently higher RFS
rates were found for MRD-negative T-ALL patients at the first 5 follow-up
time points
Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification
The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification
Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification
Abstract The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared to information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known non-pathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification. This article is protected by copyright. All rights reserved.Peer reviewe
Clinical significance of cytogenetic studies in childhood acute lymphoblastic leukemia: experience of the BFM trials
Clinical relevance of chromosomal aberrations in childhood ALL: cytogenetic data of the German therapy studies
Clinical significance of aberrant DNA methylation in childhood acute lymphoblastic leukemia
10.1016/j.leukres.2011.04.015Leukemia Research35101345-1349LERE
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