Treatment-Modulated Antigens: A Quantitative Mass Spectrometry Based Approach to Identify Changes in Peptide MHC Repertoires in Response to Tyrosine Kinase Inhibitors Lauren Stopfer1,2, Douglas Lauffenburger, Ph.D.1, Forest White, Ph.D.1,2 1Massachusetts Institute of Technology, Department of Biological Engineering; 2Koch Institute for Integrative Cancer Research
Combining current cancer therapies such as kinase inhibitors and immunotherapies can extend patient survival, but the optimal order and timing of these drugs remain poorly understood. Recent work has demonstrated that tumor cells often increase surface MHC presentation in response to treatment with kinase inhibitors, which is likely due to increased IFN- production, a known modulator of MHC presentation. We aim to understand at least some aspects of adaptive immune consequences of administering kinase inhibitors by investigating how antigens repertoires presented to the immune system change with treatment. To do so, we have developed a quantitative mass spectrometry based approach where we seek to identify “treatment-associated antigens” (TAAs), antigens that increase their presentation in response to treatment relative to others. We hypothesize these antigens can be leveraged for targeted immunotherapies and inform combination clinical trial design. Current methods typically use label-free quantification to assess relative changes in antigen repertoires between samples. Our method enables the direct quantification of antigen surface expression through a combination of heavy amino acid labeled peptide MHC monomer standards and isobaric mass tags for multiplexed MS analysis. Heavy-labeled peptide-MHC standards are added directly to cell lysate, thus correcting for variations in sample processing and immunoprecipitation efficiency. These monomer standards also allow us to achieve absolute quantification of antigen levels, which to our knowledge has not been shown before. Using in vitro melanoma samples, we have discovered that a majority of antigens do not change their presentation levels in response to MEK inhibition, while a few antigens change significantly (i.e. TAAs). Future work includes validating identified TMA candidates through T-cell killing assays, and moving this workflow into in vivo patient derived xenograft melanoma samples comparing control tumors and those treated with a MEK inhibitor.
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