SJPedPanel: A pan-cancer gene panel for childhood malignancies

Abstract

AbstractBackgroundExtensive efforts in the past decade have revolutionized our understanding of the genetic underpinnings of childhood malignancies and identified numerous driver alterations that can provide potential targets for novel therapy and are excellent biomarkers for disease monitoring. For these purposes, a whole genome or exome sequencing approach can be resource prohibitive. Numerous gene panels are developed for adult cancers to address these challenges. Due to the dramatic differences in driver gene landscapes between pediatric and adult cancers, a gene panel for childhood cancers is needed.ResultsHere, we have developed a gene panel dedicated to childhood cancers. This panel (2.82 Mbp) covers 5275 coding exons of 357 driver genes, 297 introns frequently involved in rearrangements that generate fusion oncoproteins, commonly deleted regions, such asCDKN2AandPAX5(for B-/T-ALL) andSMARCB1(for ATRT), and 7,590 polymorphism sites to detect copy number alterations for interrogating tumors with aneuploidy, such as hyperdiploid and hypodiploid B-ALL or 17q gain neuroblastoma. We used driver alterations reported from an established real-time clinical genomics cohort (n=253) to investigate the effectiveness of this gene panel. Among the 485 pathogenic variants reported, our panel covered 417 variants (86%). For 90 rearrangements responsible for oncogenic fusions, our panel covered 74 events (82%). We re-sequenced 113 previously characterized clinical specimens at an average depth of 2,500X using SJPedPanel and recovered 355 (90%) of the 396 reported pathogenic variants. Among the 30 unique genes of the 41 missed alterations, 29 genes are mutated in pediatric cancers with a low frequency (<0.21%) and hence not covered in the panel. We then investigated the power of this panel in detecting mutations from specimens with low tumor content (as low as 0.1%) using cell line-based dilution experiments and discovered that this gene panel enabled us to detect ∼80% variants with allele fraction of 0.2%, while the detection rate decreases to ∼50% when the allele fraction is 0.1%. We finally demonstrate its utility in disease monitoring on clinical specimens collected from AML patients in morphologic remission.ConclusionsOverall, our gene panel enables the detection of clinically relevant genetic alterations including rearrangements responsible for subtype-defining fusions for childhood cancers by targeted sequencing of ∼0.15% of human genome. Our panel will significantly enhance the analysis of specimens with low tumor burdens for cancer monitoring and early detection.