Abstract A036: Combining data-independent acquisition and targeted immunopeptidomics to enhance neoepitope discovery

Abstract Personalized cancer immunotherapies such as therapeutic vaccines and adoptive transfer of T cell receptor (TCR)-transgenic T cells rely on the presentation of tumor-specific peptides by human leukocyte antigen (HLA) class I molecules to cytotoxic T cells. Such neoepitopes arise from somatic mutations and their identification is crucial for the rational design of new immunotherapeutic interventions. In this study, we analyzed samples of dedifferentiated liposarcoma (DDLS), which is characterized by focal amplifications on chromosome 12. Using whole exome/whole genome and RNA sequencing, we previously found that these structural changes generate open reading frames and thus presumably transcribed and translated chimeric genes. The encoded neoepitopes are promising targets for epitope-centric individualized therapies if they are presented by HLA class I molecules. Liquid chromatography mass spectrometry (LC-MS)-based immunopeptidomics is currently the only method to directly prove actual peptide presentation. We have recently developed a parameter optimization workflow to tune targeted assays for maximum detection sensitivity on a per peptide basis, termed optiPRM (optimized parallel reaction monitoring). In this study, we combined this workflow with an untargeted approach, data-independent acquisition with ion mobility separation by high-field asymmetric waveform ion mobility spectrometry (FAIMS-DIA). Using FAIMS-DIA on DDLS samples, we identified up to 16500 unique peptides per patient, including several neoepitope candidates. For the subsequent optiPRM analysis, candidate neoepitopes identified by FAIMS-DIA as well as additional candidates from variant calling with excellent predicted binding properties were synthesized as stable isotope-labeled (SIL) variant and assay-relevant parameters such as normalized collision energy (NCE) and exact retention times were determined relative to indexed retention time (iRT) peptides. Targeted analysis not only confirmed several of the FAIMS-DIA candidates but also yielded additional detections in 5 out of 6 analyzed patients. Using our complimentary FAIMS-DIA and PRM immunopeptidomics workflows, we have identified fusion-derived neoepitopes in 5 out of 8 DDLS patient samples. Importantly, the identifications contained both neoepitopes which would have been missed by the less sensitive FAIMS-DIA approach or which would have been excluded from the targeted analysis due to their poor predicted binding properties, highlighting the advantage of the combined approach. The detected neoepitopes, currently being functionally tested, represent candidates for the clinical development of personalized treatment options in liposarcoma such as cancer vaccines or TCR-based therapies. Citation Format: Jonas P Becker, Jonas D Förster, Sven Blobner, David Weber, Sebastian Uhrig, Annika Baude, Johanna Wagner, Isabel Poschke, Michael Platten, Stefan Fröhling, Peter Horak, Angelika B Riemer. Combining data-independent acquisition and targeted immunopeptidomics to enhance neoepitope discovery [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2024 Oct 18-21; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2024;12(10 Suppl):Abstract nr A036.