The machine‐learning classifier ALLCatchR2 identifies 20 T‐ALL subtypes across cohorts and age groups

This is the authors' abstract. We don't add key points for this paper.

T‐cell acute lymphoblastic leukemia (T‐ALL) comprises molecularly diverse subtypes, but robust cross‐cohort validations and operational gene‐expression definitions are lacking. To establish a gene‐expression–anchored framework for T‐ALL subtyping, we aggregated 2314 transcriptomes (15 cohorts, age: 0.8–90.8 years). An extended unsupervised approach defined 17 main clusters and 3 subclusters in samples with high blast fractions. Supervised analyses added an overarching immature T‐ALL (early T cell precursor [ETP]‐like) definition and resolved the LMO2 γδ‐like subtype. All clusters contained samples from at least two cohorts. Characteristic genomic driver enrichments were consistent across cohorts, while gene‐expression clusters did not correspond exclusively to single driver events but also reflected developmental origins. A machine‐learning classifier based on ALLCatchR, our B‐cell acute lymphoblastic leukemia (B‐ALL) classifier, identified these 20 transcriptomic subtypes and the immature T‐ALL (ETP‐like) signature with 0.995–1.0 accuracy in a validation set ( n = 203). Testing the classifier on a second hold‐out data set ( n = 265 samples) showed that 92.7% of predictions matched with corresponding driver alterations. Across all samples, 83.2% of cases received high‐confidence predictions, 7.3% candidate predictions, and 9.5% remained unclassified, largely because of low blast fractions. We identified a novel gene‐expression cluster markedly enriched (P < 0.001) for clonal hematopoiesis mutations ( IDH2 R140Q , DNMT3A ) and a stem‐/progenitor cell‐like gene expression. This novel clonal hematopoiesis‐related T‐ALL subtype was observed in six cohorts and accounted for 8.9% of adults and 39.5% of patients aged >50 years. We extended ALLCatchR into ALLCatchR2, a free R package that now enables B‐/T‐lineage separation, gene‐expression subtyping, blast estimation, and developmental annotation to harmonize T‐ALL classification across studies and clinical contexts.