Rational design of therapeutic cancer vaccines or TCR-based adoptive transfer approaches requires knowledge of the epitope repertoire presented on the surface of tumor cells. However, direct detection of viral or mutation-derived epitopes remains an analytical challenge, as currently several hundred million cells are required for their detection, which so far prevents systematic application in clinical settings.
Previously we reported a multiple reaction monitoring with multi-stage fragmentation (MRM3) targeted strategy for the detection of HLA-presented human papillomavirus (HPV)16 epitopes, undetectable by untargeted approaches. Here we present the transfer and adoption of the strategy to a high-resolution mass spectrometer that ensures confident detection based on high mass accuracy in the parallel reaction monitoring (PRM) mode.
To achieve ultra-high sensitivity for the detection of low abundant target HLA-presented peptides, extremely long MS2 injection times are required. However, due to the presence of interfering signals, including background proteins, detergent and other contaminants present in the immune-isolates, careful selection of acquisition parameters is mandatory to prevent excessive overfilling of the orbitrap, which may compromise the sensitivity of detection. Our approach includes the generation of a high quality spectral library, and dominant charge state determination of the predicted target epitopes by prior analysis of their stable isotope labeled (SIL) surrogates. Although the default collision energy is normalized to the mass-to-charge ratio (NCE) of the precursor ion, we found that additional tuning of the NCE greatly improves detection. Moreover, spiking an unrelated peptide-rich background proteome into the sample allows detection of very low abundance peptides that otherwise would remain undetected.
Our preliminary results show better consistency of detection of HPV-derived epitopes than with the previously used MRM3 approach. However, further optimization is mandatory to achieve the analysis of tumor biopsies, for instance as part of larger personalized clinical diagnostic and therapeutic pipelines.