Poster Presentation 32nd Lorne Cancer 2020

Protein level expression of somatic mutations and their role as cancer neo-antigens (#312)

Sonali V Mohan 1 2 , Keshava K Datta 1 , Corey Smith 3 4 5 6 , Harsha Gowda 1 2 7
  1. Cancer Precision Medicine Group, , QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
  2. Faculty of Medicine, The University of Queensland, Herston, 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
  6. School of Clinical Medicine, The University of Queensland, Brisbane, QLD, Australia
  7. School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, 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. Till now, functional consequences of single nucleotide variations have been mostly predicted based on amino acid alterations and their sequence context. Various prediction programs are employed to predict potential neo-antigens based on cancer genome sequencing data. However, these approaches can result in significant number of false positives and false negatives. 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 analysis with proteomics and MHC peptidome mass spectrometry to identify potential neo-antigens from melanoma cell lines. 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.