Pan-cancer proteogenomics expands the landscape of therapeutic targets. Integrating proteogenomic data from 1,043 patients across 10 cancer types with cell line data and tumor antigen predictions reveals a comprehensive landscape of protein and peptide targets for drug repurposing and therapy development. The study identifies pan-cancer druggable targets, synthetic lethality strategies for targeting tumor suppressor loss, and computational workflows for identifying tumor antigens. A web portal provides access to these targets and supporting data. The analysis includes 2,863 druggable proteins, with proteomics data covering 71% of them. The study highlights the importance of protein abundance over mRNA abundance for druggable genes. Targetable dependencies driven by protein overexpression and hyperactivation were identified, with 51 proteins shared by at least 5 cancer types. The study also identified neoantigens and tumor-associated antigens, with 2,315 putative neoantigens associated with 846 somatic mutations. These findings provide a comprehensive landscape of protein and peptide targets for companion diagnostics, drug repurposing, and therapy development. The study also identified potential therapeutic targets for immunotherapy, including MAGE family proteins and other tumor-associated antigens. The results suggest that proteogenomics can expand the therapeutic target landscape for cancer treatment.Pan-cancer proteogenomics expands the landscape of therapeutic targets. Integrating proteogenomic data from 1,043 patients across 10 cancer types with cell line data and tumor antigen predictions reveals a comprehensive landscape of protein and peptide targets for drug repurposing and therapy development. The study identifies pan-cancer druggable targets, synthetic lethality strategies for targeting tumor suppressor loss, and computational workflows for identifying tumor antigens. A web portal provides access to these targets and supporting data. The analysis includes 2,863 druggable proteins, with proteomics data covering 71% of them. The study highlights the importance of protein abundance over mRNA abundance for druggable genes. Targetable dependencies driven by protein overexpression and hyperactivation were identified, with 51 proteins shared by at least 5 cancer types. The study also identified neoantigens and tumor-associated antigens, with 2,315 putative neoantigens associated with 846 somatic mutations. These findings provide a comprehensive landscape of protein and peptide targets for companion diagnostics, drug repurposing, and therapy development. The study also identified potential therapeutic targets for immunotherapy, including MAGE family proteins and other tumor-associated antigens. The results suggest that proteogenomics can expand the therapeutic target landscape for cancer treatment.