SJPedPanel: A pan-cancer gene panel for childhood malignancies to enhance cancer monitoring and early detection.

PURPOSE: To design a pan-cancer gene panel for childhood malignancies and validate it using clinically characterized patient samples. EXPERIMENTAL DESIGN: In addition to 5,275 coding exons, SJPedPanel also covers 297 introns for fusions/structural variations and 7,590 polymorphic sites for copy number alterations. Capture uniformity and limit of detection are determined by targeted sequencing of cell lines using dilution experiment. We validate its coverage by in silico analysis of an established real-time clinical genomics (RTCG) cohort of 253 patients. We further validate its performance by targeted re-sequencing of 113 patient samples from the RTCG cohort. We demonstrate its power in analyzing low tumor burden specimens using morphologic remission and monitoring samples. RESULTS: Among the 485 pathogenic variants reported in RTCG cohort, SJPedPanel covered 86% of variants, including 82% of 90 rearrangements responsible for fusion oncoproteins. In our targeted re-sequencing cohort, 91% of 389 pathogenic variants are detected. The gene panel enabled us to detect ~95% of variants at allele fraction 0.5%, while the detection rate is ~80% at allele fraction 0.2%. The panel detected low frequency driver alterations from morphologic leukemia remission samples and relapse-enriched alterations from monitoring samples, demonstrating its power for cancer monitoring and early detection. CONCLUSIONS: SJPedPanel enables the cost-effective detection of clinically relevant genetic alterations including rearrangements responsible for subtype-defining fusions by targeted sequencing of ~0.15% of human genome for childhood malignancies. It will enhance the analysis of specimens with low tumor burdens for cancer monitoring and early detection.

Genomic and global gene expression profiling in pediatric and young adult acute leukemia with PICALM::MLLT10 Fusion.

PICALM: MLLT10 fusion is a rare but recurrent genetic driver in acute leukemias. To better understand the genomic landscape of PICALM::MLLT10 (PM) positive acute leukemia, we performed genomic profiling and gene expression profiling in twenty PM-positive patients, including AML (n = 10), T-ALL/LLy (n = 8), Mixed-phenotype acute leukemia (MPAL), T/B (n = 1) and acute undifferentiated leukemia (AUL) (n = 1). Besides confirming the known activation of HOXA, differential gene expression analysis compared to hematopoietic stem cells demonstrated the enrichment of genes associated with cell proliferation-related pathways and relatively high expression of XPO1 in PM-AML and PM-T-ALL/LLy. Our study also suggested PHF6 disruption as a key cooperating event in PICALM::MLLT10-positive leukemias. In addition, we demonstrated differences in gene expression profiles as well as remarkably different spectra of co-occurring mutations between PM-AML and PM-T-ALL/LLy. Alterations affecting TP53 and NF1, hallmarks of PM-AML, are strongly associated with disease progression and relapse, whereas EZH2 alterations are highly enriched in PM-T-ALL/LLy. This comprehensive genomic and transcriptomic profiling provides insights into the pathogenesis and development of PICALM::MLLT10 positive acute leukemia.

A new genomic framework to categorize pediatric acute myeloid leukemia.

Recent studies on pediatric acute myeloid leukemia (pAML) have revealed pediatric-specific driver alterations, many of which are underrepresented in the current classification schemas. To comprehensively define the genomic landscape of pAML, we systematically categorized 887 pAML into 23 mutually distinct molecular categories, including new major entities such as UBTF or BCL11B, covering 91.4% of the cohort. These molecular categories were associated with unique expression profiles and mutational patterns. For instance, molecular categories characterized by specific HOXA or HOXB expression signatures showed distinct mutation patterns of RAS pathway genes, FLT3 or WT1, suggesting shared biological mechanisms. We show that molecular categories were strongly associated with clinical outcomes using two independent cohorts, leading to the establishment of a new prognostic framework for pAML based on these updated molecular categories and minimal residual disease. Together, this comprehensive diagnostic and prognostic framework forms the basis for future classification of pAML and treatment strategies.