The accurate identification and prioritization of antigenic peptides presented by class-I and -II human leukocyte antigens (HLA-I and -II) recognized by autologous T cells is crucial for the development of cancer immunotherapies. While several clinical neoantigen prediction pipelines are now publicly available, none of them allows the direct integration of mass spectrometry immunopeptidomics data that can uncover antigenic peptides derived from various canonical and non-canonical sources. Therefore, we have developed and shared a unique ‘end-to-end’ clinical proteo-genomic pipeline, called NeoDisc. NeoDisc is a fast and modular computational pipeline that combines state-of-the-art publicly available and in-house software for genomics, transcriptomics, mass-spectrometry-based immunopeptidomics, and in silico tools for the identification, prediction, and prioritization of tumor-specific and immunogenic antigens from multiple sources. We demonstrated the application of NeoDisc for personalized antigen discovery, in the context of heterogenic antigenic landscape and defective cellular antigen presentation machineries, and we highlighted its clinical implementation.