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Prioritizing candidate peptides for cancer vaccines through predicting peptide presentation by HLA-I proteins.

ABSTRACT: Cancer (treatment) vaccines that are made of neoantigens, or peptides unique to tumor cells due to somatic mutations, have emerged as a promising method to reinvigorate the immune response against cancer. A key step to prioritizing neoantigens for cancer vaccines is computationally predicting which neoantigens are presented on the cell surface by a human leukocyte antigen (HLA). We propose to address this challenge by training a neural network using mass spectrometry (MS) data composed of peptides presented by at least one of several HLAs of a subject. We embed the neural network within a mixture model and train the neural network by maximizing the likelihood of the mixture model. After evaluating our method using data sets where the peptide presentation status was known, we applied it to analyze somatic mutations of 60 melanoma patients and identified a group of neoantigens more immunogenic in tumor cells than in normal cells. Moreover, neoantigen burden estimated by our method was significantly associated with a measurement of the immune system activity, suggesting these neoantigens could induce an immune response.

SUBMITTER: Zhou LY

PROVIDER: S-EPMC10548401 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Prioritizing candidate peptides for cancer vaccines through predicting peptide presentation by HLA-I proteins.

Zhou Laura Y LY Zou Fei F Sun Wei W

Biometrics 20220729 3

Cancer (treatment) vaccines that are made of neoantigens, or peptides unique to tumor cells due to somatic mutations, have emerged as a promising method to reinvigorate the immune response against cancer. A key step to prioritizing neoantigens for cancer vaccines is computationally predicting which neoantigens are presented on the cell surface by a human leukocyte antigen (HLA). We propose to address this challenge by training a neural network using mass spectrometry (MS) data composed of peptid ...[more]

PMID: 35833513

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Project description:Minor histocompatibility antigens (mHAs), recipient-derived peptide epitopes presented on the cell surface, are known to mediate graft-versus-host disease (GVHD); however, there are no current methods to associate mHA features with GVHD risk. This deficiency is due in part to the lack of technological means to accurately predict, let alone confirm, the tremendous number of potential mHAs in each individual transplant. Previous studies have shown that different HLA molecules present varying fractions of candidate peptide epitopes; however, the genetic "distance" between HLA-matched donors and recipients is relatively constrained. From these 2 observations, it is possible that the HLA type for a donor-recipient pair (DRP) would provide a surrogate measurement of the number of predicted mHAs, which could be related to GVHD risk. Because different HLA molecules present variable numbers of peptide antigens, a predicted cumulative peptide-binding efficiency can be calculated for individual DRP based on the pair's HLA type. The purpose of this study was to test whether cumulative peptide-binding efficiency is associated with the risk of acute GVHD (aGVHD) or relapse. In this retrospective Center for International Blood and Marrow Transplant Research study, a total of 3242 HLA-matched DRPs were analyzed for predicted cumulative peptide-binding efficiency using their HLA types and were divided into tertiles based on their scores. Univariable and multivariable analyses was performed to test for associations between cumulative peptide-binding efficiency for DRPs, divided into the HLA-matched related donor (MRD) and HLA-matched unrelated donor (MUD) cohorts, and the primary outcomes of aGVHD and relapse. Secondary outcomes investigated included overall survival, disease-free survival, and transplantation-related mortality. Using a computationally generated peptidome as a test dataset, the tested series of HLA class I displayed peptide-binding frequencies ranging from 0.1% to 3.8% of the full peptidome, and HLA class II molecules had peptide-binding frequencies of 12% to 77% across the HLA-DRB1 allotypes. By increasing binding efficiency tertile, the cumulative incidence of aGVHD at 6 months for MUD patients was 41%, 41%, and 45% for HLA class I (P = .336) and 44%, 41%, and 42% for HLA class II (P = .452). The cumulative incidences of relapse at 3 years for MUD transplant recipients were 36%, 38%, and 38% for HLA class I (P = .533) and 37%, 37%, and 38% for HLA class II (P = .896). The findings were similar for MRD transplant recipients. Multivariable analysis did not identify any impact of peptide-binding efficiency on aGVHD or relapse in MUD or MRD transplant recipients. Whereas GVHD is mediated by minor antigen mismatches in the context of HLA-matched allo-HCT, peptide-binding efficiency, which was used as a surrogate measurement for predicted number of binding antigens, did not provide additional clinical information for GVHD risk assessment. The negative result may be due to the limitations of this surrogate marker, or it is possible that GVHD is driven by a subset of immunogenic mHAs. Further research should be directed at direct mHA epitope and immunogenicity prediction.

Project description:A subset of class I major histocompatibility complex (MHC)-bound peptides is produced from immature proteins that are rapidly degraded after synthesis. These defective ribosomal products (DRiPs) have been implicated in early alert of the immune system about impending infections. Interferons are important cytokines, produced in response to viral infection, that modulate cellular metabolism and gene expression patterns, increase the presentation of MHC molecules, and induce rapid degradation of proteins and cell-surface presentation of their derived MHC peptides, thereby contributing to the battle against pathogen infections. This study evaluated the role of interferons in the induction of rapid degradation of DRiPs to modulate the repertoire of DRiP-derived MHC peptides. Cultured human breast cancer cells were treated with interferons, and the rates of synthesis and degradation of cellular protein and their degradation products were determined by LC-MS/MS analysis, following the rates of incorporation of heavy stable isotope-labeled amino acids (dynamic stable isotope labeling by amino acids in cell culture, dynamic SILAC) at several time points after the interferon application. Large numbers of MHC peptides that incorporated the heavy amino acids faster than their source proteins indicated that DRiP peptides were abundant in the MHC peptidome; interferon treatment increased by about twofold their relative proportions in the peptidome. Such typical DRiP-derived MHC peptides were from the surplus subunits of the proteasome and ribosome, which are degraded because of the transition to immunoproteasomes and a new composition of ribosomes incorporating protein subunits that are induced by the interferon. We conclude that degradation of surplus subunits induced by the interferon is a major source for DRiP-MHC peptides, a phenomenon relevant to coping with viral infections, where a rapid presentation of MHC peptides derived from excess viral proteins may help alert the immune system about the impending infection.

Dataset Information

Prioritizing candidate peptides for cancer vaccines through predicting peptide presentation by HLA-I proteins.

Publications

Prioritizing candidate peptides for cancer vaccines through predicting peptide presentation by HLA-I proteins.

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