Rapid and sensitive identification of major histocompatibility complex class I-associated tumor peptides by Nano-LC MALDI MS/MS.

Identification of major histocompatibility complex (MHC)-associated peptides recognized by T-lymphocytes is a crucial prerequisite for the detection and manipulation of specific immune responses in cancer, viral infections, and autoimmune diseases. Unfortunately immunogenic peptides are less abundant species present in highly complex mixtures of MHC-extracted material. Most peptide identification strategies use microcapillary LC coupled to nano-ESI MS/MS in a challenging on-line approach. Alternatively MALDI PSD analysis has been applied for this purpose. We report here on the first off-line combination of nanoscale (nano) LC and MALDI TOF/TOF MS/MS for the identification of naturally processed MHC peptide ligands. These peptides were acid-eluted from human leukocyte antigen (HLA)-A2, HLA-A3, and HLA-B/-C complexes separately isolated from a renal cell carcinoma cell lysate using HLA allele-specific antibodies. After reversed-phase HPLC, peptides were further fractionated via nano-LC. This additional separation step provided a substantial increase in the number of detectable candidate species within the complex peptide pools. MALDI MS/MS analysis on nano-LC-separated material was then sufficiently sensitive to rapidly identify more than 30 novel HLA-presented peptide ligands. Peptide sequences contained perfect anchor amino acid residues described previously for HLA-A2, HLA-A3, and HLA-B7. The most promising candidate for a T-cell epitope is an HLA-B7-binding nonamer peptide derived from the tumor-associated gene NY-BR-16. To demonstrate the sensitivity of our approach we characterized peptides binding to HLA-C molecules that are usually expressed at the cell surface at approximately only 10% the levels of HLA-A or HLA-B. In fact, multiple renal cell carcinoma peptides were identified that contained anchor amino acid residues of HLA-Cw5 and HLA-Cw7. We conclude that the nano-LC MALDI MS/MS approach is a sensitive tool for the rapid and automated identification of MHC-associated tumor peptides.