Abstract 54: Integrative analysis of whole-genome and RNA sequencing in high-risk pediatric malignancies

Abstract

Abstract The use of sequencing-based assays for clinical management of pediatric cancer patients has become increasingly common. However, for many pediatric patients, gene panel based sequencing tests yield few actionable results. Given the complex genomic alterations present in many pediatric cancers, especially high-risk solid tumors, we hypothesized that an unbiased approach might reveal more actionable findings and lead to a more comprehensive understanding of these diseases. To accomplish this, we integrated whole-genome sequencing (WGS) with RNAseq in the analysis of a pediatric oncology cohort, with a focus on longitudinal cases to capture potential tumor evolution in metastatic or treated cases. Our cohort consists of 269 high-risk pediatric oncology patients, including patients with relapsed/refractory disease, metastatic disease at diagnosis, prior cancer history, a rare diagnosis, or an estimated overall survival <50%. Solid tumors, CNS tumors, and leukemia/lymphomas are all represented. In total, 391 samples were characterized using WGS (tumor ~60X; germline ~30X) and/or RNAseq (tumor, polyA selected, ≥20 million reads). For 85 of these patients, multiple samples were collected at different time points (diagnosis, resection, relapse, etc.) to identify changes in the cancer over time. If panel testing was performed as part of their clinical care, a comparison to the integrated WGS/RNA analysis was made. WGS was used to identify variants (SNVs), structural rearrangements (SVs), mutational signatures, and copy-number alterations (CNAs). RNAseq was used to identify gene expression outliers, gene fusions, and confirm the expression of variants identified using WGS. The combination of WGS and RNAseq was then used to identify and prioritize potentially actionable variants for each patient. Our results show that the integration of WGS and RNAseq can provide more and higher-quality actionable information than either modality alone, whilst also capturing the majority of actionable variants detected by panel sequencing. RNAseq identified not only druggable fusions and expression outliers, but also many rare and novel fusions. WGS provided fusion validation but highlighted the limitations of WGS alone in identifying fusions resulting from complex SVs. Conversely, WGS was adept at capturing genome-wide patterns of CNAs and loss of heterozygosity that are missed by gene-centric panels. Further RNAseq integration enabled prioritization of expressed SNVs as well as CNAs and SVs that significantly alter gene expression. We also used WGS to extract mutational signatures and tracked their evolution across longitudinal samples. We found potentially biologically significant differences in therapy-induced mutations caused by platinum and alkylating agents. Our unbiased approach has enabled further discovery that advances our understanding of these rare and highly aggressive malignancies. Citation Format: Henry J. Martell, Avanthi Tayi Shah, Alex G. Lee, Bogdan Tanasa, Stanley G. Leung, Aviv Spillinger, Heng-Yi Liu, Inge Behroozfard, Phuong Dinh, Maria V. Pons Ventura, Florette K. Hazard, Arun Rangaswami, Sheri L. Spunt, Norman J. Lacayo, Tabitha Cooney, Jennifer G. Michlitsch, Anurag K. Agrawal, Marcus R. Breese, E. Alejandro Sweet-Cordero. Integrative analysis of whole-genome and RNA sequencing in high-risk pediatric malignancies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 54.