From early detection of variants of concern to vaccine and therapeutic design, pandemic preparedness depends on identifying viral mutations that escape the response of the host immune system. While experimental scans are useful for quantifying escape potential, they remain laborious and impractical for exploring the combinatorial space of mutations. Here we introduce a biologically grounded model to quantify the viral escape potential of mutations at scale. Our method - EVEscape - brings together fitness predictions from evolutionary models, structure-based features that assess antibody binding potential, and distances between mutated and wild-type residues. Unlike other models that predict variants of concern based on newly observed variants, EVEscape has no reliance on recent community prevalence, and is applicable before surveillance sequencing or experimental scans are broadly available. We validate EVEscape predictions against experimental data on H1N1, HIV and SARS-CoV-2, including data on immune escape. For SARS-CoV-2, we show that EVEscape anticipates mutation frequency, strain prevalence, and escape mutations. Drawing from GISAID, we provide continually updated escape predictions for all current strains of SARS-CoV-2.
Therapeutic cancer vaccination seeks to elicit activation of tumor-reactive T cells capable of recognizing tumor-associated antigens (TAAs) and eradicating malignant cells. Here, we present a cancer vaccination approach utilizing myeloid lineage reprogramming to directly convert cancer cells into tumor reprogrammed-antigen presenting cells (TR-APCs). Using syngeneic murine leukemia models, we demonstrate that TR-APCs acquire both myeloid phenotype and function, process and present endogenous TAAs, and potently stimulate TAA-specific CD4+ and CD8+ T cells. In vivo TR-APC induction elicits clonal expansion of cancer-specific T cells, establishes cancer-specific immune memory, and ultimately promotes leukemia eradication. We further show that both hematologic cancers and solid tumors, including sarcomas and carcinomas, are amenable to myeloid-lineage reprogramming into TR-APCs. Finally, we demonstrate the clinical applicability of this approach by generating TR-APCs from primary clinical specimens and stimulating autologous patient-derived T cells. Thus, TR-APCs represent a cancer vaccination therapeutic strategy with broad implications for clinical immuno-oncology.
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