Updated project metadata. HLA class I molecules reflect the health state of cells to cytotoxic T-cells by presenting a repertoire of endogenously derived peptides. However, the extent to which the proteome shapes the peptidome is still largely unknown. Here we present a high-throughput mass-spectrometry-based workflow that allows stringent and accurate identification of thousands of such peptides and direct determination of binding motifs. Applying the workflow to seven cancer cell lines and primary cells, yielded more than 22,000 unique HLA peptides across different allelic binding specificities. By computing a score representing the HLA-I sampling density, we show a strong link between protein abundance and HLA-presentation (P<0.0001). When analyzing over-presented proteins - those with at least five-fold higher density score than expected for their abundance – we noticed that they are degraded almost 3 hours faster than similar but non-presented proteins (top 20% abundance class; median half-life 20.8h vs. 23.6h, p<0.0001). This validates protein degradation as an important factor for HLA presentation. Ribosomal, mitochondrial respiratory chain and nucleosomal proteins as particularly well presented. Taking a set of proteins associated with cancer, we compared the predicted immunogenicity of previously validated T-cell epitopes with other peptides from these proteins in our dataset. The validated epitopes indeed tend to have higher immunogenic scores than the other detected HLA peptides, suggesting the usefulness of combining MS-analysis with immunogenesis prediction for ranking and selection of epitopes for therapeutic use.