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Biomarkers to predict prognosis and response to checkpoint inhibitors

Nivolumab is a fully human immunoglobulin (Ig) G4 antibody that selectively inhibits the programmed death 1 (PD-1) immune checkpoint molecule, and has recently been launched for the treatment of renal cell cancer (RCC) in Japan. Based on its promising anti-tumor efficacy and manageable safety profil...

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Autores principales: Yuasa, Takeshi, Masuda, Hitoshi, Yamamoto, Shinya, Numao, Noboru, Yonese, Junji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Japan 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5533827/
https://www.ncbi.nlm.nih.gov/pubmed/28382562
http://dx.doi.org/10.1007/s10147-017-1122-1
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author Yuasa, Takeshi
Masuda, Hitoshi
Yamamoto, Shinya
Numao, Noboru
Yonese, Junji
author_facet Yuasa, Takeshi
Masuda, Hitoshi
Yamamoto, Shinya
Numao, Noboru
Yonese, Junji
author_sort Yuasa, Takeshi
collection PubMed
description Nivolumab is a fully human immunoglobulin (Ig) G4 antibody that selectively inhibits the programmed death 1 (PD-1) immune checkpoint molecule, and has recently been launched for the treatment of renal cell cancer (RCC) in Japan. Based on its promising anti-tumor efficacy and manageable safety profile demonstrated in the phase III Checkmate 025 trial, nivolumab therapy is rapidly being introduced in metastatic RCC clinical practice. The phase Ia study of atezolizumab, which is a humanized anti-PD-ligand 1 (PD-L1) monoclonal IgG1 antibody, also demonstrated excellent treatment results. The identification of biomarkers to predict the response and side-effects of checkpoint inhibitor therapy is thus urgently needed. In this review, we introduce the current candidate biomarkers of immune checkpoint inhibitor therapy. Based on the mechanism of efficacy, the number of neoantigens and expression of major histocompatibility complex molecules are strong candidate biomarkers. Despite the various interference factors, PD-L1 expression can be considered a potential biomarker. In terms of clinical factors, serum clinical factors and severity of adverse events are examined. Although further implementation in prospective studies is necessary, if validated, these biomarkers can be utilized to measure therapeutic response and design treatment strategies for metastatic RCC.
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spelling pubmed-55338272017-08-11 Biomarkers to predict prognosis and response to checkpoint inhibitors Yuasa, Takeshi Masuda, Hitoshi Yamamoto, Shinya Numao, Noboru Yonese, Junji Int J Clin Oncol Review Article Nivolumab is a fully human immunoglobulin (Ig) G4 antibody that selectively inhibits the programmed death 1 (PD-1) immune checkpoint molecule, and has recently been launched for the treatment of renal cell cancer (RCC) in Japan. Based on its promising anti-tumor efficacy and manageable safety profile demonstrated in the phase III Checkmate 025 trial, nivolumab therapy is rapidly being introduced in metastatic RCC clinical practice. The phase Ia study of atezolizumab, which is a humanized anti-PD-ligand 1 (PD-L1) monoclonal IgG1 antibody, also demonstrated excellent treatment results. The identification of biomarkers to predict the response and side-effects of checkpoint inhibitor therapy is thus urgently needed. In this review, we introduce the current candidate biomarkers of immune checkpoint inhibitor therapy. Based on the mechanism of efficacy, the number of neoantigens and expression of major histocompatibility complex molecules are strong candidate biomarkers. Despite the various interference factors, PD-L1 expression can be considered a potential biomarker. In terms of clinical factors, serum clinical factors and severity of adverse events are examined. Although further implementation in prospective studies is necessary, if validated, these biomarkers can be utilized to measure therapeutic response and design treatment strategies for metastatic RCC. Springer Japan 2017-04-05 2017 /pmc/articles/PMC5533827/ /pubmed/28382562 http://dx.doi.org/10.1007/s10147-017-1122-1 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Review Article
Yuasa, Takeshi
Masuda, Hitoshi
Yamamoto, Shinya
Numao, Noboru
Yonese, Junji
Biomarkers to predict prognosis and response to checkpoint inhibitors
title Biomarkers to predict prognosis and response to checkpoint inhibitors
title_full Biomarkers to predict prognosis and response to checkpoint inhibitors
title_fullStr Biomarkers to predict prognosis and response to checkpoint inhibitors
title_full_unstemmed Biomarkers to predict prognosis and response to checkpoint inhibitors
title_short Biomarkers to predict prognosis and response to checkpoint inhibitors
title_sort biomarkers to predict prognosis and response to checkpoint inhibitors
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5533827/
https://www.ncbi.nlm.nih.gov/pubmed/28382562
http://dx.doi.org/10.1007/s10147-017-1122-1
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