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


Authors: Masucci, G. V.; Cesano, A.; Eggermont, A.; Fox, B. A.; Wang, E.; Marincola, F. M.; Ciliberto, G.; Dobbin, K.; Puzanov, I.; Taube, J.; Wargo, J.; Butterfield, L. H.; Villabona, L.; Thurin, M.; Postow, M. A.; Sondel, P. M.; Demaria, S.; Agarwala, S.; Ascierto, P. A.
Article Title: The need for a network to establish and validate predictive biomarkers in cancer immunotherapy
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. © 2017 The Author(s).
Keywords: protein expression; treatment planning; validation process; note; flow cytometry; biological marker; protein analysis; cancer immunotherapy; proteomics; standardization; feasibility study; peer review; epigenetics; cytotoxic t lymphocyte antigen 4; programmed death 1 ligand 1; programmed death 1 receptor; non small cell lung cancer; metabolomics; intention to treat analysis; human; pembrolizumab
Journal Title: Journal of Translational Medicine
Volume: 15
ISSN: 1479-5876
Publisher: Biomed Central Ltd  
Date Published: 2017-11-03
Start Page: 223
Language: English
DOI: 10.1186/s12967-017-1325-2
PROVIDER: scopus
PMCID: PMC5670700
PUBMED: 29100546
DOI/URL:
Notes: Note -- Export Date: 4 December 2017 -- Source: Scopus
Altmetric Score
MSK Authors
  1. Michael Andrew Postow
    185 Postow