Reproducible Bioinformatics Analysis Workflows for Detecting IGH Gene Fusions in B-Cell Acute Lymphoblastic Leukaemia Patients.

B-cell acute lymphoblastic leukaemia (B-ALL) is characterised by diverse genomic alterations, the most frequent being gene fusions detected via transcriptomic analysis (mRNA-seq). Due to its hypervariable nature, gene fusions involving the Immunoglobulin Heavy Chain (IGH) locus can be difficult to detect with standard gene fusion calling algorithms and significant computational resources and analysis times are required. We aimed to optimize a gene fusion calling workflow to achieve best-case sensitivity for IGH gene fusion detection. Using Nextflow, we developed a simplified workflow containing the algorithms FusionCatcher, Arriba, and STAR-Fusion. We analysed samples from 35 patients harbouring IGH fusions (IGH::CRLF2 n = 17, IGH::DUX4 n = 15, IGH::EPOR n = 3) and assessed the detection rates for each caller, before optimizing the parameters to enhance sensitivity for IGH fusions. Initial results showed that FusionCatcher and Arriba outperformed STAR-Fusion (85-89% vs. 29% of IGH fusions reported). We found that extensive filtering in STAR-Fusion hindered IGH reporting. By adjusting specific filtering steps (e.g., read support, fusion fragments per million total reads), we achieved a 94% reporting rate for IGH fusions with STAR-Fusion. This analysis highlights the importance of filtering optimization for IGH gene fusion events, offering alternative workflows for difficult-to-detect high-risk B-ALL subtypes.

Case report: Rare case of donor cell-derived T-cell acute lymphoblastic leukaemia in a female patient after receiving an allo-transplant from her male sibling.

Donor-derived haematological neoplasms, in which recipients present with haematological malignancies that have evolved from transplant donor stem cells, have previously been described for myelodysplastic syndrome, myeloproliferative neoplasms, acute myeloid leukaemia and less often, leukaemias of lymphoid origin. Here we describe a rare and complex case of donor-derived T-cell acute lymphoblastic leukaemia with a relatively short disease latency of less than 4 years. Through genomic and in vitro analyses, we identified novel mutations in NOTCH1 as well as a novel activating mutation in STAT5B; the latter targetable with the clinically available drugs, venetoclax and ruxolitinib.

RaScALL: Rapid (Ra) screening (Sc) of RNA-seq data for prognostically significant genomic alterations in acute lymphoblastic leukaemia (ALL).

RNA-sequencing (RNA-seq) efforts in acute lymphoblastic leukaemia (ALL) have identified numerous prognostically significant genomic alterations which can guide diagnostic risk stratification and treatment choices when detected early. However, integrating RNA-seq in a clinical setting requires rapid detection and accurate reporting of clinically relevant alterations. Here we present RaScALL, an implementation of the k-mer based variant detection tool km, capable of identifying more than 100 prognostically significant lesions observed in ALL, including gene fusions, single nucleotide variants and focal gene deletions. We compared genomic alterations detected by RaScALL and those reported by alignment-based de novo variant detection tools in a study cohort of 180 Australian patient samples. Results were validated using 100 patient samples from a published North American cohort. RaScALL demonstrated a high degree of accuracy for reporting subtype defining genomic alterations. Gene fusions, including difficult to detect fusions involving EPOR and DUX4, were accurately identified in 98% of reported cases in the study cohort (n = 164) and 95% of samples (n = 63) in the validation cohort. Pathogenic sequence variants were correctly identified in 75% of tested samples, including all cases involving subtype defining variants PAX5 p.P80R (n = 12) and IKZF1 p.N159Y (n = 4). Intragenic IKZF1 deletions resulting in aberrant transcript isoforms were also detectable with 98% accuracy. Importantly, the median analysis time for detection of all targeted alterations averaged 22 minutes per sample, significantly shorter than standard alignment-based approaches. The application of RaScALL enables rapid identification and reporting of previously identified genomic alterations of known clinical relevance.

In-vitro modeling of TKI resistance in the high-risk B-cell acute lymphoblastic leukemia fusion gene RANBP2-ABL1 - implications for targeted therapy.

Acute lymphoblastic leukemia remains a leading cause of cancer-related death in children. Furthermore, subtypes such as Ph-like ALL remain at high-risk of relapse, and treatment resistance remains a significant clinical issue. The patient-derived Ph-like ALL RANBP2-ABL1 fusion gene was transduced into Ba/F3 cells and allowed to become resistant to the tyrosine kinase inhibitors (TKIs) imatinib or dasatinib, followed by secondary resistance to ponatinib. RANBP2-ABL1 Ba/F3 cells developed the clinically relevant ABL1 p.T315I mutation and upon secondary resistance to ponatinib, developed compound mutations, including a novel ABL1 p.L302H mutation. Significantly, compound mutations were targetable with a combination of asciminib and ponatinib. In-vitro modeling of Ph-like ALL RANBP2-ABL1 has identified kinase domain mutations in response to TKI treatment, that may have important clinical ramifications. Early detection of mutations is paramount to guide treatment strategies and improve survival in this high-risk group of patients.