Abstract B015: Transcriptome-based assessment of immune infiltration for molecular selection of pediatric patients with solid tumors for combination immune checkpoint inhibitor therapy

Abstract Introduction Immune checkpoint inhibitors (ICI) have shown great success in the treatment of several types of adult cancers, yet their efficacy is limited in pediatric cancers. Studies have demonstrated differences in immunogenicity of pediatric and adult cancers, advocating for the need for genetic biomarkers that predict ICI therapy response specific to pediatric cancers. Methods Based on previous work in adult and pediatric cancers, we developed an immune profiling bioinformatic workflow container, RICO (Rna-seq Immune COntainer), which takes raw sequencing data as input, and utilizes RNA-seq quantification data to infer three putative biomarkers; (a) CD8+ T-cell score: expression-based deconvolution to estimate CD8+ T cell abundance using CIBERSORT; (b) M1/M2 score: a ten-gene signature to assess the ratio of M1 (pro-inflammatory) and M2(anti-inflammatory) macrophages,and (c) IPASS score: a 15-gene signature that predicts T-cell infiltration. The percentiles were derived with reference to a pediatric pan-cancer cohort of 222 samples and further validated in an extended cohort of 600 samples. Outlier high scores were defined as CD8+ T cell score 80 percentile, M1M2 score 80 percentile, and IPASS prediction of T-cell infiltration, excluding samples of lymph node origin and hematologic malignancies. Results We constructed RICO using 222 samples from the Canadian PROFYLE (PRecision Oncology For Young peopLE) program and validated using 600 samples from Australian ZERO (Zero Childhood Cancer precision medicine program). Both studies enrolled children with poor prognosis cancers and undertook somatic whole genome, transcriptome and matched germline sequencing. The cohorts were combined (N=822 samples) to form a large dataset showing the profile of immune-related biomarker scores across pediatric solid and central nervous system tumors. Outlier high scores were observed across many cancer types (i.e., sarcoma, rhabdoid tumor, low- and high-grade glioma, neuroblastoma, chordoma, melanoma, mesothelioma, carcinoma and others). Using FASTQ files as input, RICO generated concordant results across sequencing sites(3 across Canada and 1 in Australia). The proportions of tumors with an immune infiltrated phenotype were similar between the two cohorts, indicating that the percentiles were cohort-agnostic and captured the range of immune infiltration across pediatric solid tumors. Conclusions RICO provides a robust, tumor-agnostic and platform-independent tool that takes raw sequencing data as input and consistently evaluates biomarkers that have been associated with immune infiltration and/or response to ICI. In the setting of the international early phase pediatric precision oncology basket trial OPTIMISE “Optimal Precision Therapies to CustoMISE Care in Childhood and Adolescent Cancer” (NCT06208657), RICO will be used to assess patient eligibility within a planned arm testing an ICI combination therapy. Citation Format: Yaoqing Shen, Chelsea Mayoh, Arash Nabbi, Raoul Santiago, Stephanie Bianco, Iain R. Bancarz, Laura Williamson, Richard Corbett, Zakhar Krekhno, Scott Davidson, Alexander Fortuna, Kyoko E. Yuki, Denise Connolly, Daniel Morgenstern, Paul G. Ekert, Adam Shlien, Steven J.M. Jones, Rebecca J. Deyell, Sarah Cohen-Gogo. Transcriptome-based assessment of immune infiltration for molecular selection of pediatric patients with solid tumors for combination immune checkpoint inhibitor therapy abstract. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr B015.