Neoantigens are peptides deviating from a canonical protein sequence, and arise from not only variable types of genomic mutations, but also pseudogenes and aberrant splicing and translation. These peptides provide a promising source for targeting cancer cells through targeted re-activation of immune cells. However, identifying neoantigens is a challenging task due to their low abundance and cancer heterogeneity, and requires exhaustive mass spectrometry (MS) proteomics and therewith compute. In a previous project application, we successfully implemented a Nextflow workflow to perform proteogenomics analysis for identifying neoantigens on several cancer cohorts using MS. Results from those analyses are to be published, and we are currently pursuing three objectives: - Scaling up our workflow to be able to use in more experiments, especially with larger amounts of samples - Extending the workflow to be able to find neoantigens deriving from more mutation types, e.g. gene fusions - Leveraging new MS technology (DIA, PRM) to quickly identify confirmed neoantigens in new samples, requiring less instrument and compute time. As implemented earlier, batches of neoantigens will be analyzed in a cross-check Nextflow pipeline, searching for their expression in healthy tissue public data. This step is to validate there is no unexpected expression in healthy tissue which would render the neoantigen useless as either a cancer marker or target, and also requires exhaustive analysis.