Abstract 3665: Integrative analysis of whole-genome and RNA sequencing in high-risk pediatric malignancies

Abstract

Abstract Clinical use of gene-panel based sequencing has become increasingly common in the management of pediatric cancer patients. For many patients, gene-panel tests have identified clinically actionable findings. However, highly targeted approaches will miss unanticipated (but potentially clinically meaningful) or novel alterations. In diseases with unknown or complex etiologies, including many pediatric high-risk and solid tumors, an unbiased approach may yield more actionable findings. To accomplish this, we examined the feasibility and utility of whole genome sequencing (WGS) and RNA sequencing (RNAseq) in the management of high-risk pediatric oncology patients. Here we describe our experience with an expanded cohort of over 100 high-risk pediatric oncology patients, with a combination of solid tumors, brain tumors, and leukemia/lymphomas represented. The majority of patients were deemed high-risk due to relapsed/refractory disease. An additional group of patients were defined as high-risk at time of initial diagnosis due to metastatic disease, a rare tumor, prior history of another cancer type, an undifferentiated tumor, or less than 50% estimated overall survival. WGS (tumor/germline) and RNAseq were used to characterize available samples and compared to results from panel testing for each patient (performed as part of their clinical evaluation). When possible, multiple samples from an individual patient were collected (i.e. specimens obtained at biopsy, resection, relapse, and/or from metastatic sites). Somatic DNA samples were sequenced to an average depth of at least 60X and germline samples to at least 30X. RNAseq was performed to a depth of at least 20 million paired-end reads for each sample. WGS samples were analyzed for single nucleotide variants (SNVs), structural rearrangements (SV), and copy-number alterations (CNA). RNAseq samples were analyzed to identify known and novel gene-fusions, to measure allele specific expression of SNVs, and to perform gene-expression outlier analysis. Expression of variants (SNV/SV) identified using WGS were confirmed using RNAseq. For gene expression outliers detected using RNAseq, the WGS data was used to predict possible mechanisms for the aberrant expression (such as CNA, gene fusions, or promoter hijacking). This analysis suggests that WGS and RNAseq analysis is feasible in a clinical setting and can reliably identify variants reported on gene panel tests. However, the use of WGS/RNAseq resulted in additional clinically informative findings while also enabling novel research to further advance our understanding of these rare and highly aggressive pediatric malignancies. Citation Format: Marcus R. Breese, Avanthi T. Shah, Alex G. Lee, Bogdan Tanasa, Stanley G. Leung, Aviv Spillinger, Heng-Yi Liu, Inge Behroozfard, Phuong Dinh, Florette K. Hazard, Arun Rangaswami, Sheri L. Spunt, Norman J. Lacayo, Tabitha Cooney, Jennifer G. Michlitsch, Anurag K. Agrawal, 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 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3665.