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1.
J Clin Invest ; 132(13)2022 07 01.
Artigo em Inglês | MEDLINE | ID: mdl-35775490

RESUMO

Cancers avoid immune surveillance through an array of mechanisms, including perturbation of HLA class I antigen presentation. Merkel cell carcinoma (MCC) is an aggressive, HLA-I-low, neuroendocrine carcinoma of the skin often caused by the Merkel cell polyomavirus (MCPyV). Through the characterization of 11 newly generated MCC patient-derived cell lines, we identified transcriptional suppression of several class I antigen presentation genes. To systematically identify regulators of HLA-I loss in MCC, we performed parallel, genome-scale, gain- and loss-of-function screens in a patient-derived MCPyV-positive cell line and identified MYCL and the non-canonical Polycomb repressive complex 1.1 (PRC1.1) as HLA-I repressors. We observed physical interaction of MYCL with the MCPyV small T viral antigen, supporting a mechanism of virally mediated HLA-I suppression. We further identify the PRC1.1 component USP7 as a pharmacologic target to restore HLA-I expression in MCC.


Assuntos
Carcinoma de Célula de Merkel , Poliomavírus das Células de Merkel , Infecções por Polyomavirus , Neoplasias Cutâneas , Antígenos Virais de Tumores/genética , Antígenos Virais de Tumores/metabolismo , Carcinoma de Célula de Merkel/genética , Carcinoma de Célula de Merkel/patologia , Epigênese Genética , Humanos , Poliomavírus das Células de Merkel/genética , Poliomavírus das Células de Merkel/metabolismo , Infecções por Polyomavirus/genética , Neoplasias Cutâneas/patologia , Peptidase 7 Específica de Ubiquitina/metabolismo
2.
Nat Biotechnol ; 38(2): 199-209, 2020 02.
Artigo em Inglês | MEDLINE | ID: mdl-31844290

RESUMO

Prediction of HLA epitopes is important for the development of cancer immunotherapies and vaccines. However, current prediction algorithms have limited predictive power, in part because they were not trained on high-quality epitope datasets covering a broad range of HLA alleles. To enable prediction of endogenous HLA class I-associated peptides across a large fraction of the human population, we used mass spectrometry to profile >185,000 peptides eluted from 95 HLA-A, -B, -C and -G mono-allelic cell lines. We identified canonical peptide motifs per HLA allele, unique and shared binding submotifs across alleles and distinct motifs associated with different peptide lengths. By integrating these data with transcript abundance and peptide processing, we developed HLAthena, providing allele-and-length-specific and pan-allele-pan-length prediction models for endogenous peptide presentation. These models predicted endogenous HLA class I-associated ligands with 1.5-fold improvement in positive predictive value compared with existing tools and correctly identified >75% of HLA-bound peptides that were observed experimentally in 11 patient-derived tumor cell lines.


Assuntos
Bases de Dados de Proteínas , Epitopos/metabolismo , Antígenos de Histocompatibilidade Classe I/metabolismo , Peptídeos/metabolismo , Proteoma/metabolismo , Algoritmos , Alelos , Motivos de Aminoácidos , Linhagem Celular , Loci Gênicos , Humanos , Ligantes , Peptídeo Hidrolases/metabolismo , Peptídeos/química , Complexo de Endopeptidases do Proteassoma/metabolismo
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