2026/06/08 by Namsoo Kim, Yu Jin Park, Young Kyu Min +6 · 1 voice
Medicine · Biochemistry, Genetics and Molecular Biology · #Acute Myeloid Leukemia Research #Acute Lymphoblastic Leukemia research #Genomic variations and chromosomal abnormalities
paper · doi:10.3390/cells15121048
openalex publication_date 2026/06/08 · openalex created_date 2026/06/09 · openalex updated_date 2026/07/29
BACKGROUND: Gene fusions play a pivotal role in the pathogenesis and classification of hematologic malignancies. RNA sequencing (RNA-seq) has emerged as a powerful tool for detecting gene fusions; however, many clinical studies have focused on targeted RNA-seq, and optimal parameters for whole transcriptome RNA-seq remain uncertain. METHODS: We retrospectively analyzed whole RNA-seq data from 301 patients diagnosed with acute leukemia between October 2022 and May 2025 to characterize the landscape of pathogenic gene fusions. Fusions were identified using the Arriba algorithm, and subsampling analyses were performed on cases with recurrent fusions to determine the minimum sequencing output required for reliable detection. RESULTS: rearrangements. Subsampling analysis demonstrated that a sequencing output ≥ 100 million reads (moderate confidence) or ≥300 million reads (high confidence) was sufficient for 100% detection of recurrent fusions. CONCLUSIONS: Whole RNA-seq reliably detects clinically relevant gene fusions in acute leukemia, aligns well with conventional karyotyping results, and surpasses targeted RNA-seq in comprehensiveness. A sequencing output of at least 100 million reads is recommended for clinical fusion detection.