Renal cell carcinoma (RCC) is a highly aggressive tumor with a poor prognosis. Despite advancements in therapeutic approaches, the current treatments often exhibit limited efficacy, underscoring the urgent need for novel strategies. Considering the tumor's immune environment, we hypothesize that RCC could be an ideal candidate for immunotherapeutic interventions, particularly those aimed at enhancing the activity of cytotoxic (CD8+) T cells. In this study, we explore the immunopeptidomic landscape of RCC using the RENCA xenograft model to compare tumor tissue with benign tissue samples. We employ an immune affinity purification method coupled with LC-MS/MS acquisition for peptide identification, as well as gene identification, and label-free quantification.
To identify novel canonical and non-canonical tumor-specific antigens resulting from genetic and epigenetic alterations during tumor progression, we employ a LC-MS/MS data analysis workflow with a specific focus on both discovery and validation steps. For discovery steps, the workflow integrates database search and peptide de novo sequencing. To ensure the accuracy of peptide identifications, a group-specific False Discovery Rate (FDR) was calculated to control for false positives from canonical and non-canonical databases searching, as well as those from de novo sequencing.
By integrating chromosome loci information with our quantification analysis, which compares the immunopeptidomes of xenograft model tumor and benign tissue samples, we identify both canonical and non-canonical peptides unique or upregulated in RCC. Binding affinity assays and immunogenicity predictions suggest that most of the peptides identified from RCC tumor cells bind to class I major histocompatibility complex (MHC-I) and a subset may elicit an immune response. In addition, our findings reveal that certain peptides are uniquely presented on RCC tumors, some of which are derived from non-coding regions of the genome, potentially serving as novel therapeutic targets. Discovering these peptides enhances our understanding of MHC-I peptide presentation and the tumor's antigenic profile. Overall, the study underscores the potential of immunopeptidomics in revealing novel targets for immunotherapy in RCC. This approach not only opens new avenues for treatment but also contributes to the broader understanding of RCC's immune landscape, paving the way for advancements in cancer immunotherapy.