Identification of shared tumor epitopes from endogenous retroviruses inducing high-avidity cytotoxic T cells for cancer immunotherapy - Archive ouverte HAL
Article Dans Une Revue Science Advances Année : 2022

Identification of shared tumor epitopes from endogenous retroviruses inducing high-avidity cytotoxic T cells for cancer immunotherapy

Virginie Mutez
Emilie Michel
Rasha Boulos
Yann Estornes
Qing Wang

Résumé

Human endogenous retroviruses (HERVs) represent 8% of the human genome. HERV products may represent tumor antigens relevant for cancer immunotherapy. We developed a bioinformatic approach to identify shared CD8 + T cell epitopes derived from cancer-associated HERVs in solid tumors. Six candidates among the most commonly shared HLA-A2 epitopes with evidence of translation were selected for immunological evaluation. In vitro priming assays confirmed the immunogenicity of these epitopes, which induced high-avidity CD8 + T cell clones. These T cells specifically recognize and kill HLA-A2 + tumor cells presenting HERV epitopes on HLA molecules, as demonstrated by mass spectrometry. Furthermore, epitope-specific CD8 + T cells were identified by dextramer staining among tumor-infiltrating lymphocytes from HLA-A2 + patients with breast cancer. Last, we showed that HERV-specific T cells lyse patient-derived organoids. These shared virus-like epitopes are of major interest for the development of cancer vaccines or T cell–based immunotherapies, especially in tumors with low/intermediate mutational burden.
Fichier principal
Vignette du fichier
Bonaventura et al. - 2022 - Identification of shared tumor epitopes from endog.pdf (11.8 Mo) Télécharger le fichier
Origine Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-03552937 , version 1 (15-11-2022)

Identifiants

Citer

Paola Bonaventura, Vincent Alcazer, Virginie Mutez, Laurie Tonon, Juliette Martin, et al.. Identification of shared tumor epitopes from endogenous retroviruses inducing high-avidity cytotoxic T cells for cancer immunotherapy. Science Advances , 2022, 8 (4), ⟨10.1126/sciadv.abj3671⟩. ⟨hal-03552937⟩
184 Consultations
182 Téléchargements

Altmetric

Partager

More