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Abstract
Mass spectrometry (MS) is the state-of-the-art methodology for capturing the breadth and depth of the immunopeptidome across human leukocyte antigen (HLA) allotypes and cell types. The majority of studies in the immunopeptidomics field are discovery driven. Hence, data-dependent tandem MS (MS/MS) acquisition (DDA) is widely used, as it generates high-quality references of peptide fingerprints. However, DDA suffers from the stochastic selection of abundant ions that impairs sensitivity and reproducibility. In contrast, in data-independent acquisition (DIA), the systematic fragmentation and acquisition of all fragment ions within given isolation m/z windows yield a comprehensive map for a given sample. However, many DIA approaches commonly require generating comprehensive DDA-based spectrum libraries, which can become impractical for studying noncanonical and personalized neoantigens. Because the amount of HLA peptides eluted from biological samples such as small tissue biopsies is typically not sufficient for acquiring both meaningful DDA data necessary for generating comprehensive spectral libraries and DIA MS measurements, the implementation of DIA in the immunopeptidomics translational research domain has remained limited. We implemented a DIA immunopeptidomics workflow and assessed its sensitivity and accuracy by matching DIA data against libraries with growing complexity—from sample-specific libraries to libraries combining 2 to 40 different immunopeptidomics samples. Analyzing DIA immunopeptidomics data against a complex multi-HLA spectral library resulted in a two-fold increase in peptide identification compared with sample-specific library and in a three-fold increase compared with DDA measurements, yet with no detrimental effect on the specificity. Furthermore, we demonstrated the implementation of DIA for sensitive personalized neoantigen discovery through the analysis of DIA data with predicted MS/MS spectra of clinically relevant HLA ligands. We conclude that a comprehensive multi-HLA library for DIA approach in combination with MS/MS prediction is highly advantageous for clinical immunopeptidomics, especially when low amounts of biological samples are available.
Highlights
HuiSong Pak1, Justine Michaux1, Florian Huber1, Chloe Chong1, Brian J
We started our investigation of assessing the sensitivity of a data-independent acquisition (DIA) immunopeptidomics approach using sample-specific spectral libraries (Fig. 1A) to reflect the ‘best case’ results that would allow comparisons with multi-human leukocyte antigen (HLA) spectral libraries generated from publicly available dependent tandem Mass spectrometry (MS) (MS/MS) acquisition (DDA) data from our laboratory (Fig. 1B)
We isolated from the RA957B cell line HLA-I-binding peptides by immunoaffinity purification with the pan-HLA W6/32 antibody followed by a desalting step
Summary
In Brief The implementation of DIA in the immunopeptidomics translational research domain has remained limited because the amount of HLA peptides eluted from clinical samples is typically not sufficient for acquiring both meaningful DDA data for generating comprehensive spectral libraries and DIA MS measurements. Because the amount of HLA peptides eluted from clinical samples, such as small tumor tissue biopsies, is typically not sufficient for acquiring both meaningful DDA data for generating comprehensive spectral libraries and DIA MS measurements, the implementation of DIA in the immunopeptidomics translational research domain has remained limited. A few proof-of-concept DIA immunopeptidomics studies in cell line models have been published to date [39,40,41,42] They reported the feasibility of using large spectral libraries of peptides with defined HLA-binding specificities [39], and that, as expected, DIA outcompetes DDA in terms of both reproducibility and sensitivity when measuring low-yield samples [40, 42]. We demonstrated how integration of Prosit-based prediction of MS/MS spectra with DIA-based immunopeptidomics can lead to the sensitive detection of neoantigens and other clinically relevant antigens
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