Poster Presentation 26th Annual Lorne Proteomics Symposium 2021

Proteogenomic analysis to identify cancer neo-antigens (#63)

Sonali V Mohan 1 2 , Keshava K Datta 2 , Corey Smith 3 4 5 , Harsha Gowda 1 2 3
  1. Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
  2. Cancer Precision Medicine Group, , QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
  3. School of Biomedical Sciences,Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
  4. QIMR Centre for Immunotherapy and Vaccine Development, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
  5. Translational and Human Immunology Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia

Advent of immunotherapies has revolutionized cancer treatment. Recent success with immunotherapy is predominantly due to checkpoint inhibitors that block inhibitory signals and enable T cell activation that target cancer cells. Other strategies including adoptive cell transfer and cancer vaccines are being investigated in parallel to increase available arsenal for immune therapy. Cancer genome sequencing studies have identified several genomic alterations including single nucleotide variations, insertions/deletions and structural variations across various cancers. It is known that some proteins encoded by mutated genes are processed and presented on the cell surface. These MHC presented mutant peptides serve as neo-antigens that are recognized by T cells. Identification of such neo-antigens can strengthen cancer immunotherapy efforts and reveal neo-antigens that can be potentially targeted. However, it is unclear what fraction of mutant alleles in cancer genomes are expressed at the protein level and what fraction of these are presented on cell surface by MHC complex. Mass spectrometry based immunopeptidome datasets can provide large-scale datasets that can be used to gain insights into sequence features and other principles that potentially determine peptides that are presented by MHC complex. We have combined whole-exome sequencing and transcriptome analysis with proteomics and MHC peptidome mass spectrometry to identify potential neo-antigens from melanoma, lung and breast cancer cell lines. We identified thousands of MHC bound peptides from cancer cell lines including mutant peptides that can potentially serve as neo-antigens. Our proteogenomics analysis revealed that the proportion of genomic variants that are presented by MHC class I complex is significantly small. These observations can prove useful for developing better experimental strategies and prediction tools to identify potential cancer neo-antigens. Reliable identification of cancer neo-antigens can accelerate development of novel therapeutic approaches that can exploit host immune system to treat cancers.