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Upstream open reading frames regulate proto-oncogene translation and encode HLA-presented immunogenic tumor antigens

ABSTRACT: Upstream open reading frames (uORFs) represent translational control elements within eukaryotic transcript leader sequences. Recent data showed that uORFs can encode for biologically active proteins and human leucocyte antigen (HLA)-presented peptides and suggest their potential role in cancer cell development and survival. However, it is so far unclear if uORF-encoded peptides could serve as tumor-associated antigen targets and thus also play a role in cancer immune surveillance. Combining mass spectrometry-based immunopeptidome analysis in primary tumor and healthy tissues and evaluation of proto-oncogene-associated uORF-mediated translational control we here identified a panel of HLA-presented tumor-associated uORF-derived antigens. These uORF-derived tumor antigens were further shown to induce multifunctional antigen-specific T cells, validating their suitability as antigen targets for T cell-based cancer immunotherapy. Our data further unravel the role of uORF-encoded peptides in malignant disease, suggesting uORF-derived tumor-associated antigens as targets for anti-cancer immune surveillance and immunotherapy development.

INSTRUMENT(S): LTQ Orbitrap, Orbitrap Fusion Lumos

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Juliane S. Walz

PROVIDER: MSV000098383 | MassIVE | Mon Jun 30 04:44:00 BST 2025

SECONDARY ACCESSION(S): PXD025716

REPOSITORIES: MassIVE

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Project description:Various cancer immunotherapies rely on the T cell recognition of peptide antigens presented on human leukocyte antigens (HLA). However, the identification and selection of naturally presented peptide targets for the development of personalized as well as off-the-shelf immunotherapy approaches remains challenging. Here, we introduce the open-access Peptides for Cancer Immunotherapy Database (PCI-DB, https://pci-db.org/), a comprehensive resource of immunopeptidome data originating from various malignant and benign primary tissues that provides the research community with a convenient tool to facilitate the identification of peptide targets for immunotherapy development. The PCI-DB includes > 6.6 million HLA class I and > 3.4 million HLA class II peptides from over 40 tissue types and cancer entities analyzed uniformly using high-sensitive nf-core bioinformatics pipelines and applying a global peptide false discovery rate (FDR) approach. First application of the database provided insights into the representation of cancer-testis antigens (CTA) across malignant and benign tissues and enabled the identification and characterization of the cross-tumor entity and entity-specific tumor-associated antigens as well as naturally presented neoepitopes from frequent cancer mutations. Further, we used the PCI-DB to design personalized peptide vaccines for two patients suffering from metastatic cancer. PCI-DB enabled the composition of both a multi-peptide vaccine comprising non-mutated, highly frequent tumor-associated antigens matching the immunopeptidome of the individual patient´s tumor and a neoepitope-based vaccine matching the mutational profile of the cancer patient. Both vaccine approaches induced potent and long-lasting T-cell responses, accompanied by long-term survival of these advanced cancer patients. In conclusion, the PCI-DB provides a highly versatile tool to broaden the understanding of cancer-related antigen presentation and, ultimately, supports the development of novel immunotherapies.

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Upstream open reading frames regulate proto-oncogene translation and encode HLA-presented immunogenic tumor antigens

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