Thousands of novel unannotated proteins expand the MHC I immunopeptidome in cancer
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA599422 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR10846525.fastq.gz | Fastqsanger.gz | |||
| SRR10846526.fastq.gz | Fastqsanger.gz | |||
| SRR10846527.fastq.gz | Fastqsanger.gz | |||
| SRR10846528.fastq.gz | Fastqsanger.gz | |||
| SRR10846529.fastq.gz | Fastqsanger.gz |
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Project description:Tumor epitopes – peptides that are presented on surface-bound MHC I proteins - provide targets for cancer immunotherapy and have been identified extensively in the annotated protein-coding regions of the genome. Motivated by the recent discovery of translated novel unannotated open reading frames (nuORFs) using ribosome profiling (Ribo-seq), we hypothesized that cancer-associated processes could generate nuORFs that can serve as a new source of tumor antigens that harbor somatic mutations or show tumor-specific expression. To identify cancer-specific nuORFs, we generated Ribo-seq profiles for 29 malignant and healthy samples. These included primary normal and chronic lymphocytic leukemia (CLL) B cells, patient-derived primary glioblastoma (GBM) and melanoma cell cultures, primary healthy melanocytes, as well as established colon carcinoma and melanoma cell lines. These also included B721.221 cells, the parental cell line previously used to generate 92 single HLA allele-expressing lines from which we collected mono-allelic MHC I immunopeptidome data. We developed a hierarchical approach to identify translated novel unannotated open reading frames that leverages the large amount of Ribo-seq data we have generated in order to uncover lowly expressed nuORFs, while also preserving tissue specificity. We constructed a database of novel unannotated ORFs (nuORFdb) and used it to analyze mass spectrometry datasets of MHC I-bound peptides, where we detected peptides from 3,555 nuORFs. Additionally, we used nuORFdb to identify cancer-specific nuORFs, as well as nuORFs harboring cancer-specific somatic variants as potential sources of neoantigens in cancer. *This repository contains data from the publicly available cell lines used in this study, including B721.221 cells, A375 cells, HCT116 cells and primary healthy melanocytes (Thermo C0025C). The data pertaining to primary patient samples that are part of this study is deposited in dbGaP.
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Project description:Ouspenskaia T, Law T, Clauser KR, Klaeger S, Sarkizova S, Aguet F, Li B, Christian E, Knisbacher BA, Le P, Hartigan CR, Keshishian H, Oliveira G, Zhang W, Chow YT, Ji Z, Shukla SA, Bachireddy P, Getz G, Hacohen N, Keskin DB, Carr SA, Wu CJ, Regev A. Tumor epitopes, peptides that are presented on surface-bound MHC I proteins, provide targets for cancer immunotherapy and have been identified extensively in the annotated protein-coding regions of the genome. Motivated by the recent discovery of translated novel unannotated open reading frames (nuORFs) using ribosome profiling (Ribo-seq), we hypothesized that cancer-associated processes could generate nuORFs that can serve as a new source of tumor antigens that harbor somatic mutations or show tumor-specific expression. To identify cancer-specific nuORFs, we generated Ribo-seq profiles for 29 malignant and healthy samples, developed a sensitive analytic approach for hierarchical ORF prediction, and constructed a high-confidence database of translated nuORFs across tissues. Peptides from 3,555 unique translated nuORFs were presented on MHC I, based on analysis of an extensive dataset of MHC I-bound peptides detected by mass spectrometry, with >20-fold more nuORF peptides detected in the MHC I immunopeptidomes compared to whole proteomes. We further detected somatic mutations in nuORFs of cancer samples and identified nuORFs with tumor-specific translation in melanoma, chronic lymphocytic leukemia and glioblastoma. NuORFs thus expand the pool of MHC I-presented, tumor-specific peptides, targetable by immunotherapies.
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Project description:Tumor-associated epitopes presented on MHC-I that can activate the immune system against cancer cells are typically identified from annotated protein-coding regions of the genome, but whether peptides originating from novel or unannotated open reading frames (nuORFs) can contribute to antitumor immune responses remains unclear. Here we show that peptides originating from nuORFs detected by ribosome profiling of malignant and healthy samples can be displayed on MHC-I of cancer cells, acting as additional sources of cancer antigens. We constructed a high-confidence database of translated nuORFs across tissues (nuORFdb) and used it to detect 3,555 translated nuORFs from MHC-I immunopeptidome mass spectrometry analysis, including peptides that result from somatic mutations in nuORFs of cancer samples as well as tumor-specific nuORFs translated in melanoma, chronic lymphocytic leukemia and glioblastoma. NuORFs are an unexplored pool of MHC-I-presented, tumor-specific peptides with potential as immunotherapy targets.
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Project description:The features of peptide antigens that contribute to their immunogenicity are poorly understood. Although the stability of peptide-MHC (pMHC) is known to be important, current assays assess this interaction only for peptides in isolation and not in the context of natural antigen processing and presentation. Here, we present a novel method which provides a comprehensive and unbiased measure of pMHC stability for thousands of individual ligands detected simultaneously by mass spectrometry (MS). The method allows rapid assessment of intra- and inter-allelic differences in pMHC stability and reveals broader profiles of stability than previously appreciated. The additional dimensionality of the data facilitated the training of a model which improved the prediction of peptide immunogenicity, specifically of cancer neoepitopes. This assay can be applied to any cells bearing MHC or MHC-like molecules, offering insight into not only the endogenous immunopeptidome, but also that of neoepitopes and pathogen-derived sequences.
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Project description:Ribosome profiling and mass spectrometry have revealed thousands of previously unannotated small and alternative open reading frames (sm/alt-ORFs) that are translated into micro-/alt-proteins in mammalian cells. However, their prevalence across human tissues and biological roles remain largely unexplored. The placenta is an ideal model for identifying unannotated microproteins and alt-proteins due to its considerable protein diversity that is required to sustain fetal development during pregnancy. Here, we profiled unannotated microproteins and alt-proteins in human placenta tissues from preeclampsia patients or healthy individuals by mass spectrometry, identified 66 unannotated microproteins or alt-proteins, and validated the expression of five microproteins biochemically. We further demonstrated that one microprotein, XRCC6P1, associates with translation initiation complex eIF3, and negatively regulates translation. Thus, we revealed a hidden sm/alt-ORF-encoded proteome in the human placenta, which may advance the mechanism studies for placenta development, as well as placental disorders such as preeclampsia.
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