利用基于质谱的免疫肽组学在癌症组织样本中发现肿瘤特异性肽和新抗原肽

Therapeutic peptide-based vaccination is a promising strategy for cancer immunotherapies. The identification of tumor-specific antigens is key to developing therapies. Mass spectrometry has emerged as the primary technique for the identification of peptides presented on human leukocyte antigen (HLA), i.e., immunopeptides. While tremendous progress has been made, the analysis of immunopeptides remains challenging. This is especially true for scarce clinical tissue, with amounts below 20mg. Here, we present a robust and scalable workflow utilizing the BeatBox tissue homogenizer that enables deep immunopeptidomics profiling of clinically relevant samples, facilitating the discovery of tumor-specific and neoantigenic peptides for therapeutic development. A total of 33 tissue samples from 11 donors are homogenized under native conditions with the BeatBox tissue homogenizer using the BeatBox Tissue Kit 24x kit (PreOmics). Immunopeptides are isolated using a pan anti-HLA class 1 antibody (W6/32) coupled to magnetic protein A beads in a semi-automated manner on the KingFisher (Thermo Fisher). Peptides are eluted under acidic conditions and filtered using a 10kDa MWCO plate. The immunopeptides are loaded onto Evotips (Evosep) for analysis using the Whisper Zoom method from Evosep coupled to a timsUltra AIP (Bruker) mass spectrometer. Data analysis is performed using Spectronaut 20 (Biognosys) using directDIA. For the RNA sequencing, total RNA was extracted from fresh frozen tissue samples and sequenced using Illumina 2×150 bp paired-end reads (~100M reads per sample). We analyzed matched tissue samples from 11 HLA-typed colorectal cancer donors, including healthy tumor-adjacent tissue, primary tumors, and metastatic tumors (n = 33). We profiled over 80,000 peptides with an average of 10,000 per sample using directDIA. Overall, more than 70% of the peptides were predicted to be binders (MHCFlurry). Integration of MS-based immunopeptidomics data with RNA sequencing enabled the identification of key antigens that could be used for the development of immunotherapy. We identified neoepitopes shared between tumors and metastatic tumors within patients as well as unique neoepitopes in tumors. Amongst detected neoepitopes, multiple patented or previously established immunotherapy targets were observed. Taken together, we have developed a robust workflow for the immunopeptidome profiling of clinically relevant samples and identification of neoepitopes. These findings demonstrate the potential of this workflow to support personalized cancer vaccine development and advance precision immunotherapy strategies.