A pilot study in The Journal of Molecular Diagnostics, published by Elsevier, confirms the feasibility of implementing an RNA sequencing analysis (RNA-Seq) workflow for clinical diagnosis of molecular subtypes in pediatric B-acute lymphoblastic leukemia (B-ALL). This promising and cost-efficient global genomic assay for B-ALL may lead to more accurate diagnosis as well as targeted treatment options.
ALL comprises a constellation of diverse molecular subtypes, each with their own individual drug sensitivity pattern, treatment response, and even prognosis. It is important to identify specific subtypes, particularly in the current era of personalized medicine. However, identification requires an array of profiling tools, making the process laborious and expensive.
Investigators reviewed archival clinical, morphologic, immunophenotypic, and molecular data as well as residual DNA, RNA, and frozen bone marrow aspirate and/or leukemic peripheral blood samples from previous clinical testing in a group of 76 pediatric patients. Results were analyzed from 61 newly diagnosed patients and 25 patients who had relapsed/refractory B-ALL who underwent cytogenetic and molecular characterization as part of their standard clinical care at the Center for Personalized Medicine at Children’s Hospital Los Angeles between March 2016 and September 2020. They hypothesized that RNA-Seq, which has been used in the discovery of novel molecular subtypes of B-ALL, could also be a clinically useful tool for diagnostic classification of B-ALL cases.
To test this hypothesis investigators analyzed RNA-Seq data in 28 cases of B-ALL with known subtype and 48 with undetermined subtype following clinical karyotype analysis, fluorescence in situ hybridization, chromosomal microarray, and next-generation sequencing DNA and RNA fusion panel testing (OncoKids). RNA-Seq analysis accurately identified the subtypes in all 28 known cases and determined the genetic subtype in 38 of the 48 previously unknown cases (79%). RNA-Seq analysis was also able to detect oncogenic fusions, large copy number abnormalities, oncogenic hot-spot sequence variants, and intragenic IKZF1 deletions.