Skip to main content
Top
Published in: Journal of Translational Medicine 1/2017

Open Access 01-12-2017 | Commentary

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

Authors: Giuseppe V. Masucci, Alessandra Cesano, Alexander Eggermont, Bernard A. Fox, Ena Wang, Francesco M. Marincola, Gennaro Ciliberto, Kevin Dobbin, Igor Puzanov, Janis Taube, Jennifer Wargo, Lisa H. Butterfield, Lisa Villabona, Magdalena Thurin, Michael A. Postow, Paul M. Sondel, Sandra Demaria, Sanjiv Agarwala, Paolo A. Ascierto

Published in: Journal of Translational Medicine | Issue 1/2017

Login to get access

Abstract

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.
Literature
1.
go back to reference Masucci GV, Cesano A, Hawtin R, Janetzki S, Zhang J, Kirsch I, Dobbin KK, Alvarez J, Robbins PB, Selvan SR, et al. Validation of biomarkers to predict response to immunotherapy in cancer: volume I—pre-analytical and analytical validation. J Immunother Cancer. 2016;4:76.CrossRef Masucci GV, Cesano A, Hawtin R, Janetzki S, Zhang J, Kirsch I, Dobbin KK, Alvarez J, Robbins PB, Selvan SR, et al. Validation of biomarkers to predict response to immunotherapy in cancer: volume I—pre-analytical and analytical validation. J Immunother Cancer. 2016;4:76.CrossRef
2.
go back to reference Dobbin KK, Cesano A, Alvarez J, Hawtin R, Janetzki S, Kirsch I, Masucci GV, Robbins PB, Selvan SR, Streicher HZ, et al. Validation of biomarkers to predict response to immunotherapy in cancer: volume II—clinical validation and regulatory considerations. J Immunother Cancer. 2016;4:77.CrossRef Dobbin KK, Cesano A, Alvarez J, Hawtin R, Janetzki S, Kirsch I, Masucci GV, Robbins PB, Selvan SR, Streicher HZ, et al. Validation of biomarkers to predict response to immunotherapy in cancer: volume II—clinical validation and regulatory considerations. J Immunother Cancer. 2016;4:77.CrossRef
3.
go back to reference Galon Jerome, Mlecnik Bernhard, Marliot Florence, Fang-Shu Ou, Bifulco Carlo Bruno, Lugli Alessandro, Zlobec Inti, Rau Tilman T, Hartmann Arndt, Masucci Giuseppe V, et al. Validation of the Immunoscore (IM) as a prognostic marker in stage I/II/III colon cancer: Results of a worldwide consortium-based analysis of 1,336 patients. J Clin Oncol. 2016;34:3500.CrossRef Galon Jerome, Mlecnik Bernhard, Marliot Florence, Fang-Shu Ou, Bifulco Carlo Bruno, Lugli Alessandro, Zlobec Inti, Rau Tilman T, Hartmann Arndt, Masucci Giuseppe V, et al. Validation of the Immunoscore (IM) as a prognostic marker in stage I/II/III colon cancer: Results of a worldwide consortium-based analysis of 1,336 patients. J Clin Oncol. 2016;34:3500.CrossRef
4.
go back to reference Weide B, Martens A, Hassel JC, Berking C, Postow MA, Bisschop K, Simeone E, Mangana J, Schilling B, Di Giacomo AM, et al. baseline biomarkers for outcome of melanoma patients treated with pembrolizumab. Clin Cancer Res. 2016;22:5487–96.CrossRef Weide B, Martens A, Hassel JC, Berking C, Postow MA, Bisschop K, Simeone E, Mangana J, Schilling B, Di Giacomo AM, et al. baseline biomarkers for outcome of melanoma patients treated with pembrolizumab. Clin Cancer Res. 2016;22:5487–96.CrossRef
5.
go back to reference Buyse M, Sargent DJ, Grothey A, Matheson A, de Gramont A. Biomarkers and surrogate end points[mdash]the challenge of statistical validation. Nat Rev Clin Oncol. 2010;7:309–17.CrossRef Buyse M, Sargent DJ, Grothey A, Matheson A, de Gramont A. Biomarkers and surrogate end points[mdash]the challenge of statistical validation. Nat Rev Clin Oncol. 2010;7:309–17.CrossRef
6.
go back to reference Larkin J, Chiarion-Sileni V, Gonzalez R, Rutkowski P, Cowey J-JGCL, Lao CD, Schadendorf D, Ferrucci PF, Smylie M, Dummer R, et al. Overall survival results from a phase III trial of nivolumab combined with ipilimumab in treatment-naïve patients with advanced melanoma (CheckMate 067). AACR, Annual meeting 2017; Abstract Number CT075. Larkin J, Chiarion-Sileni V, Gonzalez R, Rutkowski P, Cowey J-JGCL, Lao CD, Schadendorf D, Ferrucci PF, Smylie M, Dummer R, et al. Overall survival results from a phase III trial of nivolumab combined with ipilimumab in treatment-naïve patients with advanced melanoma (CheckMate 067). AACR, Annual meeting 2017; Abstract Number CT075.
7.
go back to reference Reck M, Rodríguez-Abreu D, Robinson AG, Hui R, Csőszi T, Fülöp A, Gottfried M, Peled N, Tafreshi A, Cuffe S, et al. Pembrolizumab versus chemotherapy for PD-L1–positive non–small-cell lung cancer. N Engl J Med. 2016;375:1823–33.CrossRef Reck M, Rodríguez-Abreu D, Robinson AG, Hui R, Csőszi T, Fülöp A, Gottfried M, Peled N, Tafreshi A, Cuffe S, et al. Pembrolizumab versus chemotherapy for PD-L1–positive non–small-cell lung cancer. N Engl J Med. 2016;375:1823–33.CrossRef
8.
go back to reference Xiao Y, Freeman GJ. The microsatellite instable (MSI) subset of colorectal cancer is a particularly good candidate for checkpoint blockade immunotherapy. Cancer Discov. 2015;5:16–8.CrossRef Xiao Y, Freeman GJ. The microsatellite instable (MSI) subset of colorectal cancer is a particularly good candidate for checkpoint blockade immunotherapy. Cancer Discov. 2015;5:16–8.CrossRef
9.
go back to reference Hirsch FR, McElhinny A, Stanforth D, Ranger-Moore J, Jansson M, Kulangara K, Richardson W, Towne P, Hanks D, Vennapusa B, et al. PD-L1 immunohistochemistry assays for lung cancer: results from phase 1 of the blueprint PD-L1 IHC assay comparison project. J Thorac Oncol. 2017;12:208–22.CrossRef Hirsch FR, McElhinny A, Stanforth D, Ranger-Moore J, Jansson M, Kulangara K, Richardson W, Towne P, Hanks D, Vennapusa B, et al. PD-L1 immunohistochemistry assays for lung cancer: results from phase 1 of the blueprint PD-L1 IHC assay comparison project. J Thorac Oncol. 2017;12:208–22.CrossRef
10.
go back to reference Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377–81.CrossRef Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377–81.CrossRef
Metadata
Title
The need for a network to establish and validate predictive biomarkers in cancer immunotherapy
Authors
Giuseppe V. Masucci
Alessandra Cesano
Alexander Eggermont
Bernard A. Fox
Ena Wang
Francesco M. Marincola
Gennaro Ciliberto
Kevin Dobbin
Igor Puzanov
Janis Taube
Jennifer Wargo
Lisa H. Butterfield
Lisa Villabona
Magdalena Thurin
Michael A. Postow
Paul M. Sondel
Sandra Demaria
Sanjiv Agarwala
Paolo A. Ascierto
Publication date
01-12-2017
Publisher
BioMed Central
Published in
Journal of Translational Medicine / Issue 1/2017
Electronic ISSN: 1479-5876
DOI
https://doi.org/10.1186/s12967-017-1325-2

Other articles of this Issue 1/2017

Journal of Translational Medicine 1/2017 Go to the issue