Researchers have evaluated a new long-read sequencing approach that may improve detection of fusion oncogenes in pediatric B-cell acute lymphoblastic leukemia (B-ALL), one of the most common childhood cancers.
Published in The Journal of Molecular Diagnostics, the study examined whether nanopore-based whole-transcriptome sequencing could help streamline the molecular classification of B-ALL by identifying clinically important gene fusions in a single sequencing workflow.
Fusion oncogenes are important diagnostic and prognostic markers in B-ALL. Subtypes such as BCR::ABL1, ETV6::RUNX1, and TCF3::PBX1 influence risk classification and treatment decisions. Currently, identifying these alterations often requires several separate laboratory tests, including fluorescence in situ hybridization (FISH), karyotyping, immunophenotyping, and targeted molecular assays.
The investigators developed a targeted fusion detection tool called FUSILLI (FUSions In Leukemia Long-read sequencing Investigator) to analyze long-read RNA sequencing data. Unlike conventional short-read sequencing, long-read sequencing can capture larger structural changes and fusion transcripts more directly.
The study included 51 pediatric B-ALL samples sequenced at high depth and 68 sequenced at lower depth. Researchers compared FUSILLI with three existing long-read fusion detection programs: FusionSeeker, JAFFAL, and LongGF.
In the high-depth group, which averaged 11.2 million reads per sample, FUSILLI achieved the highest sensitivity for detecting clinically relevant fusions while maintaining high specificity. The tool identified several important fusion types, including ETV6::RUNX1, BCR::ABL1, TCF3::PBX1, and MEF2D::HNRNPUL1.
Performance was lower in samples sequenced at lower depth, highlighting the importance of sufficient sequencing coverage for reliable detection. Based on additional computational analyses, the authors estimated that approximately 10 million reads per sample may be needed for optimal fusion detection performance.
The study also showed that the sequencing approach could identify secondary genomic alterations that may not always be detected through routine testing. However, the authors noted that some findings may still require manual review or confirmation with additional laboratory methods.
In addition to diagnostic performance, the researchers reported that FUSILLI required less computing time and memory than the other fusion detection tools evaluated. Because the method focuses specifically on leukemia-related genes, it may offer a more practical approach for targeted clinical testing.
The authors concluded that long-read whole-transcriptome sequencing could support more comprehensive molecular profiling of pediatric B-ALL while potentially reducing the need for multiple separate diagnostic assays. They noted, however, that further validation across additional leukemia subtypes and larger patient cohorts will be needed before broader clinical implementation.
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