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Published on: October 17, 2025
Prediction of relapse in paediatric pre-B acute lymphoblastic leukaemia using a three-gene risk index
Katrin Hoffmann1, Martin J Firth, Alex H Beesley
1Division of Children's Leukaemia and Cancer Research, Telethon Institute for Child Health Research, Centre for Child Health Research, Unviersity of Western Australia, Perth, WA, Australia.
Insights
Gene expression profiles identify a three-gene signature to predict relapse in children with acute lymphoblastic leukemia (ALL). This improves risk stratification beyond standard risk, aiding treatment decisions for high-risk patients.
Area of Science:
- Pediatric Oncology
- Molecular Biology
- Genomics
Background:
- Acute lymphoblastic leukemia (ALL) has high cure rates, but 25% of pediatric patients relapse with poor outcomes.
- Current risk stratification for ALL may not adequately identify all patients at high risk of relapse.
- Improved prognostic markers are needed to guide treatment intensity.
Purpose of the Study:
- To investigate the utility of gene expression profiles (GEP) for predicting long-term clinical outcome in children with pre-B ALL.
- To develop a gene expression-based classifier for improved risk stratification in pediatric ALL.
Main Methods:
- Diagnostic bone marrow specimens from 101 children with pre-B ALL were analyzed.
- Gene expression profiling was performed using HG-U133A microarrays on 55 patients.
- A three-gene quantitative reverse transcription polymerase chain reaction (qRT-PCR) risk index was developed and validated.
Main Results:
- An 18-gene classifier (GC) derived from GEP was more predictive of outcome than conventional parameters.
- A three-gene qRT-PCR risk index [glutamine synthetase (GLUL), ornithine decarboxylase antizyme inhibitor (AZIN), immunoglobulin J chain (IGJ)] achieved 89% accuracy in the initial cohort and 87% in the validation cohort.
- GEP demonstrated feasibility for enhancing risk stratification in childhood ALL.
Conclusions:
- Gene expression profiling can significantly improve risk stratification for pediatric ALL patients.
- The developed three-gene qRT-PCR index accurately predicts clinical outcome, identifying patients at risk of relapse.
- This approach is crucial for identifying standard-risk patients who may benefit from more intensive front-line therapy.
Abstract:
Despite high cure rates 25% of children with acute lymphoblastic leukaemia (ALL) relapse and have dismal outcome. Crucially, many are currently stratified as standard risk (SR) and additional markers to improve patient stratification are required. Here we have used diagnostic bone marrow specimens from 101 children with pre-B ALL to examine the use of gene expression profiles (GEP) as predictors of long-term clinical outcome. Patients were divided into two cohorts for model development and validation based on availability of specimen material. Initially, GEP from 55 patients with sufficient material were analysed using HG-U133A microarrays, identifying an 18-gene classifier (GC) that was more predictive of outcome than conventional prognostic parameters. After feature selection and validation of expression levels by quantitative reverse transcription polymerase chain reaction (qRT-PCR), a three-gene qRT-PCR risk index [glutamine synthetase (GLUL), ornithine decarboxylase antizyme inhibitor (AZIN), immunoglobulin J chain (IGJ)] was developed that predicted outcome with an accuracy of 89% in the array cohort and 87% in the independent validation cohort. The data demonstrate the feasibility of using GEP to improve risk stratification in childhood ALL. This is particularly important for the identification of patients destined to relapse despite their current stratification as SR, as more intensive front-line treatment options for these individuals are already available.
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