Abstract A44: Comparative gene expression analysis for identification and prioritization of therapeutic targets in a cohort of childhood cancers

Here we describe the utility of comparative RNA sequencing (RNA-seq) analysis in identifying cancer driver pathways and relevant therapeutics in childhood cancer, and we introduce a novel system for prioritizing gene targets based on analytical and published evidence. The purpose of our study was to evaluate the clinical utility of comparative N-of-1 gene expression analysis in identifying therapeutic options for pediatric patients with relapsed or recurrent cancers. The comparative analysis framework and large cancer background cohorts were developed at the Treehouse Childhood Cancer Initiative at UC Santa Cruz. We employed this analysis in a pilot study of 26 patients at the Lucile Packard Children’s Hospital. We analyzed RNA-seq data from 30 biopsied samples from 26 patient donors, including 16 sarcomas, 5 CNS tumors, 3 hematopoietic cancers, 1 liver, and 1 colon cancer. We compared gene expression from each child’s tumor biopsy to a background cohort of RNA-seq data from over 11,000 cancer patients, and also to a smaller cohort defined by molecular and histopathologic similarity to the child’s tumor biopsy. This comparison yielded outlier gene activations in the child’s biopsy compared to those in the background cohorts, reflecting cancer driver pathways in the child’s tumor that are actionable. We stratified each of the resulting therapeutic leads into 5 baskets: RTK activation, JAK/STAT signaling, PI3K/AKT/mTOR signaling, Cell Cycle activation, or Other. Because 27 of the 30 samples had more than one lead, we developed a novel scoring system to prioritize each sample’s therapeutic gene targets based on the analytical strength of the gene expression analysis result, and on published literature evidence for each gene as a biomarker indicative of drug response. We presented the results of our analysis in genomic consensus meetings at Stanford and surveyed the responses of clinicians and families on the utility of our analysis for treatment decisions. Here we report our experience with the method and highlight case studies in which this analysis informed treatment decisions. Citation Format: Lauren M. Sanders, A. Geoffrey Lyle, Holly C. Beale, Ellen Towle Kephart, Katrina Learned, Jennifer Peralez, Norman Lacayo, Arun Rangaswami, Sheri L. Spunt, Isabel Bjork, David Haussler, Sofie R. Salama, Olena M. Vaske. Comparative gene expression analysis for identification and prioritization of therapeutic targets in a cohort of childhood cancers [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr A44.