Gene network-based and ensemble modeling-based selection of tumor-associated antigens with a predicted low risk of tissue damage for targeted immunotherapy.

BACKGROUND: Tumor-associated antigens and their derived peptides constitute an opportunity to design off-the-shelf mainline or adjuvant anti-cancer immunotherapies for a broad array of patients. A performant and rational antigen selection pipeline would lay the foundation for immunotherapy trials with the potential to enhance treatment, tremendously benefiting patients suffering from rare, understudied cancers. METHODS: We present an experimentally validated, data-driven computational pipeline that selects and ranks antigens in a multipronged approach. In addition to minimizing the risk of immune-related adverse events by selecting antigens based on their expression profile in tumor biopsies and healthy tissues, we incorporated a network analysis-derived antigen indispensability index based on computational modeling results, and candidate immunogenicity predictions from a machine learning ensemble model relying on peptide physicochemical characteristics. RESULTS: In a model study of uveal melanoma, Human Leukocyte Antigen (HLA) docking simulations and experimental quantification of the peptide-major histocompatibility complex binding affinities confirmed that our approach discriminates between high-binding and low-binding affinity peptides with a performance similar to that of established methodologies. Blinded validation experiments with autologous T-cells yielded peptide stimulation-induced interferon-γ secretion and cytotoxic activity despite high interdonor variability. Dissecting the score contribution of the tested antigens revealed that peptides with the potential to induce cytotoxicity but unsuitable due to potential tissue damage or instability of expression were properly discarded by the computational pipeline. CONCLUSIONS: In this study, we demonstrate the feasibility of the de novo computational selection of antigens with the capacity to induce an anti-tumor immune response and a predicted low risk of tissue damage. On translation to the clinic, our pipeline supports fast turn-around validation, for example, for adoptive T-cell transfer preparations, in both generalized and personalized antigen-directed immunotherapy settings.

Elucidating the clinical and molecular spectrum of SMARCC2-associated NDD in a cohort of 65 affected individuals.

PURPOSE: Coffin-Siris and Nicolaides-Baraitser syndromes are recognizable neurodevelopmental disorders caused by germline variants in BAF complex subunits. The SMARCC2 BAFopathy was recently reported. Herein, we present clinical and molecular data on a large cohort. METHODS: Clinical symptoms for 41 novel and 24 previously published affected individuals were analyzed using the Human Phenotype Ontology. For genotype-phenotype correlations, molecular data were standardized and grouped into non-truncating and likely gene-disrupting (LGD) variants. Missense variant protein expression and BAF-subunit interactions were examined using 3D protein modeling, co-immunoprecipitation, and proximity-ligation assays. RESULTS: Neurodevelopmental delay with intellectual disability, muscular hypotonia, and behavioral disorders were the major manifestations. Clinical hallmarks of BAFopathies were rare. Clinical presentation differed significantly, with LGD variants being predominantly inherited and associated with mildly reduced or normal cognitive development, whereas non-truncating variants were mostly de novo and presented with severe developmental delay. These distinct manifestations and non-truncating variant clustering in functional domains suggest different pathomechanisms. In vitro testing showed decreased protein expression for N-terminal missense variants similar to LGD. CONCLUSION: This study improved SMARCC2 variant classification and identified discernible SMARCC2-associated phenotypes for LGD and non-truncating variants, which were distinct from other BAFopathies. The pathomechanism of most non-truncating variants has yet to be investigated.