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Mutational patterns and clonal evolution from diagnosis to relapse in pediatric acute lymphoblastic leukemia
Shumaila Sayyab1, Anders Lundmark2, Malin Larsson3
1Department of Medical Sciences, Molecular Medicine and Science for Life Laboratory, Uppsala University, Box 1432, 75144, Uppsala, Sweden. shumaila.sayyab@medsci.uu.se.
Scientific Reports
|August 7, 2021
Summary
Relapsed pediatric acute lymphoblastic leukemia (ALL) shows increased mutations at relapse. Three distinct evolutionary paths were identified, offering potential biomarkers for risk prediction in childhood ALL.
Area of Science:
- Genomics
- Pediatric Oncology
- Cancer Evolution
Background:
- Mechanisms driving clonal heterogeneity and evolution in relapsed pediatric acute lymphoblastic leukemia (ALL) remain unclear.
- Understanding these mechanisms is crucial for improving treatment strategies and patient outcomes.
Purpose of the Study:
- To investigate the genomic landscape and evolutionary trajectories of pediatric ALL at diagnosis and relapse.
- To identify novel genetic alterations and potential biomarkers associated with ALL progression and relapse.
Main Methods:
- Whole genome sequencing (WGS) of diagnostic, relapse, and remission samples from 29 Nordic pediatric ALL patients.
- Somatic mutation and structural variant calling using matched remission samples as controls.
- RNA-sequencing to assess allelic expression of identified mutations.
Main Results:
- An increased burden of somatic mutations was observed at relapse compared to diagnosis, and at second relapse versus first relapse.
- Nine known ALL driver genes had recurrent protein-coding mutations, and seven additional genes showed putative non-protein coding mutations in regulatory regions.
- Cluster analysis revealed three distinct evolutionary trajectories during ALL progression from diagnosis to relapse.
Conclusions:
- Genomic analysis reveals distinct evolutionary paths in relapsed pediatric ALL, driven by accumulating somatic mutations.
- These evolutionary trajectories may serve as biomarkers for improved risk stratification and personalized treatment of pediatric ALL.
