Integrated Immunotherapy Target Atlas for Ewing Sarcoma

The purpose of this study was to convert ESS32 from a fusion-associated RNA signature into a compartment-aware immunotherapy target atlas. We integrated GEO transcriptomic cohorts with HPA-derived normal-tissue, protein, subcellular, and secretome information, together with published proteomic and surfaceome evidence, to assign each candidate to a practical therapeutic target class. Our goal was to generate a ranked, biologically interpretable candidate list with explicit validation requirements. In doing so, we asked four linked questions: which ESS32 and comparator genes are most enriched in Ewing tumor relative to skeletal muscle; which of these signals recur across supportive tumor, model, perturbation, or cross-sarcoma contexts; how normal-tissue and protein-level evidence reorder RNA-ranked candidates; and which candidates are most compatible with TCR/vaccine, antibody/ADC/CAR, radioligand, biomarker, or validation-first development paths.