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The need for a network to establish and validate predictive biomarkers in cancer immunotherapy

Immunotherapies have emerged as one of the most promising approaches to treat patients with cancer. Recently, the entire medical oncology field has been revolutionized by the introduction of immune checkpoints inhibitors. Despite success in a variety of malignancies, responses typically only occur i...

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Autores principales: Masucci, Giuseppe V., Cesano, Alessandra, Eggermont, Alexander, Fox, Bernard A., Wang, Ena, Marincola, Francesco M., Ciliberto, Gennaro, Dobbin, Kevin, Puzanov, Igor, Taube, Janis, Wargo, Jennifer, Butterfield, Lisa H., Villabona, Lisa, Thurin, Magdalena, Postow, Michael A., Sondel, Paul M., Demaria, Sandra, Agarwala, Sanjiv, Ascierto, Paolo A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5670700/
https://www.ncbi.nlm.nih.gov/pubmed/29100546
http://dx.doi.org/10.1186/s12967-017-1325-2
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author Masucci, Giuseppe V.
Cesano, Alessandra
Eggermont, Alexander
Fox, Bernard A.
Wang, Ena
Marincola, Francesco M.
Ciliberto, Gennaro
Dobbin, Kevin
Puzanov, Igor
Taube, Janis
Wargo, Jennifer
Butterfield, Lisa H.
Villabona, Lisa
Thurin, Magdalena
Postow, Michael A.
Sondel, Paul M.
Demaria, Sandra
Agarwala, Sanjiv
Ascierto, Paolo A.
author_facet Masucci, Giuseppe V.
Cesano, Alessandra
Eggermont, Alexander
Fox, Bernard A.
Wang, Ena
Marincola, Francesco M.
Ciliberto, Gennaro
Dobbin, Kevin
Puzanov, Igor
Taube, Janis
Wargo, Jennifer
Butterfield, Lisa H.
Villabona, Lisa
Thurin, Magdalena
Postow, Michael A.
Sondel, Paul M.
Demaria, Sandra
Agarwala, Sanjiv
Ascierto, Paolo A.
author_sort Masucci, Giuseppe V.
collection PubMed
description Immunotherapies have emerged as one of the most promising approaches to treat patients with cancer. Recently, the entire medical oncology field has been revolutionized by the introduction of immune checkpoints inhibitors. Despite success in a variety of malignancies, responses typically only occur in a small percentage of patients for any given histology or treatment regimen. There are also concerns that immunotherapies are associated with immune-related toxicity as well as high costs. As such, identifying biomarkers to determine which patients are likely to derive clinical benefit from which immunotherapy and/or be susceptible to adverse side effects is a compelling clinical and social need. In addition, with several new immunotherapy agents in different phases of development, and approved therapeutics being tested in combination with a variety of different standard of care treatments, there is a requirement to stratify patients and select the most appropriate population in which to assess clinical efficacy. The opportunity to design parallel biomarkers studies that are integrated within key randomized clinical trials could be the ideal solution. Sample collection (fresh and/or archival tissue, PBMC, serum, plasma, stool, etc.) at specific points of treatment is important for evaluating possible biomarkers and studying the mechanisms of responsiveness, resistance, toxicity and relapse. This white paper proposes the creation of a network to facilitate the sharing and coordinating of samples from clinical trials to enable more in-depth analyses of correlative biomarkers than is currently possible and to assess the feasibilities, logistics, and collated interests. We propose a high standard of sample collection and storage as well as exchange of samples and knowledge through collaboration, and envisage how this could move forward using banked samples from completed studies together with prospective planning for ongoing and future clinical trials.
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spelling pubmed-56707002017-11-15 The need for a network to establish and validate predictive biomarkers in cancer immunotherapy Masucci, Giuseppe V. Cesano, Alessandra Eggermont, Alexander Fox, Bernard A. Wang, Ena Marincola, Francesco M. Ciliberto, Gennaro Dobbin, Kevin Puzanov, Igor Taube, Janis Wargo, Jennifer Butterfield, Lisa H. Villabona, Lisa Thurin, Magdalena Postow, Michael A. Sondel, Paul M. Demaria, Sandra Agarwala, Sanjiv Ascierto, Paolo A. J Transl Med Commentary Immunotherapies have emerged as one of the most promising approaches to treat patients with cancer. Recently, the entire medical oncology field has been revolutionized by the introduction of immune checkpoints inhibitors. Despite success in a variety of malignancies, responses typically only occur in a small percentage of patients for any given histology or treatment regimen. There are also concerns that immunotherapies are associated with immune-related toxicity as well as high costs. As such, identifying biomarkers to determine which patients are likely to derive clinical benefit from which immunotherapy and/or be susceptible to adverse side effects is a compelling clinical and social need. In addition, with several new immunotherapy agents in different phases of development, and approved therapeutics being tested in combination with a variety of different standard of care treatments, there is a requirement to stratify patients and select the most appropriate population in which to assess clinical efficacy. The opportunity to design parallel biomarkers studies that are integrated within key randomized clinical trials could be the ideal solution. Sample collection (fresh and/or archival tissue, PBMC, serum, plasma, stool, etc.) at specific points of treatment is important for evaluating possible biomarkers and studying the mechanisms of responsiveness, resistance, toxicity and relapse. This white paper proposes the creation of a network to facilitate the sharing and coordinating of samples from clinical trials to enable more in-depth analyses of correlative biomarkers than is currently possible and to assess the feasibilities, logistics, and collated interests. We propose a high standard of sample collection and storage as well as exchange of samples and knowledge through collaboration, and envisage how this could move forward using banked samples from completed studies together with prospective planning for ongoing and future clinical trials. BioMed Central 2017-11-03 /pmc/articles/PMC5670700/ /pubmed/29100546 http://dx.doi.org/10.1186/s12967-017-1325-2 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. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Commentary
Masucci, Giuseppe V.
Cesano, Alessandra
Eggermont, Alexander
Fox, Bernard A.
Wang, Ena
Marincola, Francesco M.
Ciliberto, Gennaro
Dobbin, Kevin
Puzanov, Igor
Taube, Janis
Wargo, Jennifer
Butterfield, Lisa H.
Villabona, Lisa
Thurin, Magdalena
Postow, Michael A.
Sondel, Paul M.
Demaria, Sandra
Agarwala, Sanjiv
Ascierto, Paolo A.
The need for a network to establish and validate predictive biomarkers in cancer immunotherapy
title The need for a network to establish and validate predictive biomarkers in cancer immunotherapy
title_full The need for a network to establish and validate predictive biomarkers in cancer immunotherapy
title_fullStr The need for a network to establish and validate predictive biomarkers in cancer immunotherapy
title_full_unstemmed The need for a network to establish and validate predictive biomarkers in cancer immunotherapy
title_short The need for a network to establish and validate predictive biomarkers in cancer immunotherapy
title_sort need for a network to establish and validate predictive biomarkers in cancer immunotherapy
topic Commentary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5670700/
https://www.ncbi.nlm.nih.gov/pubmed/29100546
http://dx.doi.org/10.1186/s12967-017-1325-2
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