Diagnostic Utility of Comprehensive RNA-Seq Analysis in Adult B-ALL

Introduction Adult B-cell acute lymphoblastic leukemia (B-ALL) comprises 75% of adult ALL cases. The classification and risk stratification of patients have conventionally relied on cytogenetics analysis. However, cytogenetics has limitations due to its reliance on metaphase cells, which can mitigate classification accuracy. In recent years, transcriptome sequencing (RNA-seq) of large pediatrics ALL cohorts has expanded the number of recurrent gene fusions recognized as disease defining events and informed risk stratification [Brady et al. 2022, Mullighan et al. 2017]. This study aims to evaluate the diagnostic utility of RNA-seq for clinical subtype classification in adult B-ALL in a large representative cohort. Methods The study cohort comprised 338 adult patients (25-65 years) with newly diagnosed ALL (UKALL14, ISRCTN66541317, NCT01085617). Paired-end RNA-seq data at 60 Million reads per sample were generated. Analysis focused on the detection of disease-defining gene fusions and gene expression signatures. Three RNA fusion callers (FusionCatcher, FuSeq, and STAR-Fusion) and three expression-based classifiers (ALLSorts, ALLspice, and ALLCatchR) were used for consensus fusion calling and expression-based classification, respectively [Nicorici et al. 2014, Vu et al. 2018, Haas et al. 2019, Schmidt et al., Mäkinen et al., Bader et al. 2022]. Integration of classification results from expression-based classifiers and the consensus gene fusions provides 4 levels of RNA-derived subtype information, denoted as “RNA evidence” in this study. These RNA-seq based classification results were compared with clinical cytogenetics findings. Results Out of 338 samples in this cohort, cytogenetics unequivocally classified 73% (246/338) of the samples. By integrating RNA expression-based classification with fusion subtypes, we confidently classified 87% (295/338) of the cohort with at least 2 levels of RNA evidence. In total, consensus gene fusions were identified in 74% (249/338), while expression-based classifiers assigned a confident subtype to 82% (319/338). Subsequently, we compared cytogenetics with RNA-seq derived classification and found a high concordance of 98% (240/246) between the two approaches. Only 6 (