RNA-sequencing improves risk stratification and guides treatment decision-making in acute lymphoblastic leukemia- a UK single centre experience

Abstract Background: Acute lymphoblastic leukemia (ALL) is genetically heterogeneous, necessitating precise molecular characterization for optimal management. At our institution, the diagnostic workflow for newly diagnosed ALL patients included fluorescence in situ hybridization (FISH) and chromosomal microarray to assess for the presence of fusion genes and copy number changes and screening for Ig/TCR clonal markers for subsequent measurable residual disease (MRD) monitoring. From 2021, we also performed routine RNA next-generation sequencing (NGS). We assessed whether integrating routine RNA sequencing (RNA-seq) enhanced risk classification, MRD assay design, and clinical decision-making. Methods: We retrospectively reviewed clinical and molecular data from 121 ALL patients (81 B-ALL, 40 T-ALL) diagnosed at University College London Hospitals between January 2021–March 2025), according to WHO 5th edition criteria. We evaluated the clinical impact of RNA-seq-detected fusions on risk stratification, MRD monitoring, and therapeutic decisions. RNAseq was performed using targeted Oncomine Myeloid Assay GX v2 or Archer® FusionPlex Pan-Heme panels. Our targeted ALL FISH panel can detect BCR::ABL1, ETV6::RUNX1, KMT2A, E2A(TCF3) and IGH/TCR rearrangement. Results: Median age was 20 years (range 2–77). 114 patients had FISH and 107 patients had RNAseq (11 B-ALL and 3 T-ALL did not have RNAseq). Standard of care FISH testing detected 17 fusion genes [BCR::ABL1 (n=10), t(1;19)(n=4), IGH::MYC (n=1), IGH::BCL2 (n=1), t(20;21) (n=1)], two of which were not detected by RNAseq [t(1;19) (n=1), t(20;21) (n=1)]. FISH also detected rearrangement with unknown partners in TCR (n=9), IGH (n=5), KMT2A (n=3), E2A (n=1). In contrast, RNA-seq identified 38 gene fusions in 35 patients (31% B-ALL; 35% T-ALL), 26 of which were not detected by FISH. . Pathogenic/likely pathogenic fusions detected by RNAseq: B-ALL: BCR::ABL1 (n=9), TCF3::PBX1 (n=3), KMT2A::AFF1 (n=2), ETV6::RUNX1 (n=1), TCF3::HLF (n=1), PAX5::NOL4L (n=1), PAX5::ESRRB (n=1), EBF1::PDGFRB (n=1), ETV6::ABL1 (n=1), KMT2A::MLLT1 (n=1), IGH::MYC (n=1), IGH::BCL2 (n=1), P2RY8::IgH (n=1) T-ALL: STIL::TAL1 (n=4), KMT2A::MLLT1 (n=1), SPTAN1::ABL1 (n=1), NUP98::RAP1GDS1 (n=1), SET::NUP214 (n=1), SEC16A::NOTCH1 (n=1), CD3G::KMT2A (n=1), PICALM::MLLT10 (n=1), low-level NUP214::ABL1 (n=1), P2RY8::CD99P1 (n=1), LMO1::RIC3 (n=1) Impact on Risk Stratification RNA-seq upgraded 6/107 (5%) patients to high-risk due to identification of high-risk fusions (TCF3::HLF, SET::NUP214, CD3G::KMT2A, PICALM::MLLT10, SPTAN1::ABL1, EBF1::PDGFRB). None of these fusions were detected by standard of care FISH. Impact on MRD Monitoring: Of 121 patients, 89 (74%) had Ig/TCR MRD markers at diagnosis. Among the remaining 32 patients without Ig/TCR markers, RNA-seq revealed unique fusions suitable for MRD tracking in 3 cases, and in 1 additional case, only a BCR::ABL1 fusion was available for MRD monitoring. Impact on Treatment Decisions: RNA-seq findings directly influenced treatment decisions in 20/107 (18%) cases, including:BCR::ABL1 fusion isoform and ABL1 mutation identification guided TKI selection in 8 patients.Detection of rare ABL-class fusions (SPTAN1::ABL1, EBF1::PDGFRB) enabled TKI-based induction therapy. Conclusion: Our findings strongly support the routine integration of RNA sequencing into diagnostic workflows for ALL. RNA-seq enhances detection of clinically relevant fusions, improves risk stratification, and enables fusion-based MRD monitoring—particularly in patients lacking conventional Ig/TCR MRD markers. It also informs personalized therapeutic strategies, including targeted treatment and MRD-guided management.