ABSTRACT
We perform an immunogenomics analysis utilizing whole-transcriptome sequencing of 657 pediatric extracranial solid cancer samples representing 14 diagnoses, and additionally utilize transcriptomes of 131 pediatric cancer cell lines and 147 normal tissue samples for comparison. We describe patterns of infiltrating immune cells, T cell receptor (TCR) clonal expansion, and translationally relevant immune checkpoints. We find that tumor-infiltrating lymphocytes and TCR counts vary widely across cancer types and within each diagnosis, and notably are significantly predictive of survival in osteosarcoma patients. We identify potential cancer-specific immunotherapeutic targets for adoptive cell therapies including cell-surface proteins, tumor germline antigens, and lineage-specific transcription factors. Using an orthogonal immunopeptidomics approach, we find several potential immunotherapeutic targets in osteosarcoma and Ewing sarcoma and validated PRAME as a bona fide multi-pediatric cancer target. Importantly, this work provides a critical framework for immune targeting of extracranial solid tumors using parallel immuno-transcriptomic and -peptidomic approaches.
Subject(s)
Neoplasms/genetics , Neoplasms/immunology , Transcriptome/genetics , Adolescent , Antigens, Neoplasm , Cell Line, Tumor , Child , Child, Preschool , Female , Gene Expression/genetics , Gene Expression Profiling/methods , Humans , Immune Checkpoint Proteins/genetics , Immune Checkpoint Proteins/immunology , Immunogenetics/methods , Immunotherapy, Adoptive , Infant , Lymphocytes, Tumor-Infiltrating/immunology , Male , Receptors, Antigen, T-Cell/genetics , Receptors, Antigen, T-Cell/immunology , Transcriptome/immunology , Tumor Microenvironment , Exome Sequencing/methodsABSTRACT
Children with treatment-refractory or relapsed (R/R) tumors face poor prognoses. As the genomic underpinnings driving R/R disease are not well defined, we describe here the genomic and transcriptomic landscapes of R/R solid tumors from 202 patients enrolled in Beat Childhood Cancer Consortium clinical trials. Tumor mutational burden (TMB) was elevated relative to untreated tumors at diagnosis, with one-third of tumors classified as having a pediatric high TMB. Prior chemotherapy exposure influenced the mutational landscape of these R/R tumors, with more than 40% of tumors demonstrating mutational signatures associated with platinum or temozolomide chemotherapy and two tumors showing treatment-associated hypermutation. Immunogenomic profiling found a heterogenous pattern of neoantigen and MHC class I expression and a general absence of immune infiltration. Transcriptional analysis and functional gene set enrichment analysis identified cross-pathology clusters associated with development, immune signaling, and cellular signaling pathways. While the landscapes of these R/R tumors reflected those of their corresponding untreated tumors at diagnosis, important exceptions were observed, suggestive of tumor evolution, treatment resistance mechanisms, and mutagenic etiologies of treatment. SIGNIFICANCE: Tumor heterogeneity, chemotherapy exposure, and tumor evolution contribute to the molecular profiles and increased mutational burden that occur in treatment-refractory and relapsed childhood solid tumors.
Subject(s)
Antineoplastic Combined Chemotherapy Protocols/therapeutic use , Biomarkers, Tumor/genetics , Drug Resistance, Neoplasm , Immune Evasion , Mutation , Neoplasm Recurrence, Local/pathology , Neoplasms/pathology , Adolescent , Adult , Child , Child, Preschool , Female , Follow-Up Studies , Gene Expression Regulation, Neoplastic , Humans , Infant , Longitudinal Studies , Male , Neoplasm Recurrence, Local/drug therapy , Neoplasm Recurrence, Local/genetics , Neoplasm Recurrence, Local/immunology , Neoplasms/drug therapy , Neoplasms/genetics , Neoplasms/immunology , Prognosis , Survival Rate , Transcriptome , Young AdultABSTRACT
SUMMARY: The Annotation, Visualization and Impact Analysis (AVIA) is a web application combining multiple features to annotate and visualize genomic variant data. Users can investigate functional significance of their genetic alterations across samples, genes and pathways. Version 3.0 of AVIA offers filtering options through interactive charts and by linking disease relevant data sources. Newly incorporated services include gene, variant and sample level reporting, literature and functional correlations among impacted genes, comparative analysis across samples and against data sources such as TCGA and ClinVar, and cohort building. Sample and data management is now feasible through the application, which allows greater flexibility with sharing, reannotating and organizing data. Most importantly, AVIA's utility stems from its convenience for allowing users to upload and explore results without any a priori knowledge or the need to install, update and maintain software or databases. Together, these enhancements strengthen AVIA as a comprehensive, user-driven variant analysis portal. AVAILABILITYAND IMPLEMENTATION: AVIA is accessible online at https://avia-abcc.ncifcrf.gov.
