T-cell diversification reflects antigen selection in the blood of patients on immune checkpoint inhibition and may be exploited as liquid biopsy biomarker.
Int J Cancer
; 140(11): 2535-2544, 2017 06 01.
Article
em En
| MEDLINE
| ID: mdl-27925177
ABSTRACT
Cancer immunotherapy with antibodies targeting immune checkpoints, such as programmed cell death protein 1 (PD-1), shows encouraging results, but reliable biomarkers predicting response to this costly and potentially toxic treatment approach are still lacking. To explore an immune signature predictive for response, we performed liquid biopsy immunoprofiling in 18 cancer patients undergoing PD-1 inhibition before and shortly after initiation of treatment by multicolor flow cytometry and next-generation T- and B-cell immunosequencing (TCRß/IGH). Findings were correlated with clinical outcomes. We found almost complete saturation of surface PD-1 on all T-cell subsets after the first dose of the antibody. Both T- and B-cell compartments quantitatively expanded during treatment. These expansions were mainly driven by an increase in the activated T-cell compartments, as well as of naïve B- and plasma cells. Deep immunosequencing revealed a clear diversification pattern of the clonal T-cell space indicative of antigenic selection in 47% of patients, while the remaining patients showed stable repertoires. 43% of the patients with a diversification pattern showed disease control in response to the PD-1 inhibitor. No disease stabilizations were observed without clonal T-cell space diversification. Our data show for the first time a clear impact of PD-1 targeting not only on circulating T-cells, but also on B-lineage cells, shedding light on the complexity of the anti-tumor immune response. Liquid biopsy T-cell next-generation immunosequencing should be prospectively evaluated as part of a composite response prediction biomarker panel in the context of clinical studies.
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Base de dados:
MEDLINE
Assunto principal:
Biomarcadores Tumorais
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Subpopulações de Linfócitos T
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Antígenos de Neoplasias
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Neoplasias
Tipo de estudo:
Prognostic_studies
Limite:
Aged
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article