Cancer classification using the Immunoscore: a worldwide task force

Jérôme Galon(Inserm), Franck Pagès(Délégation Paris 5), Francesco M. Marincola(Society for Immunotherapy of Cancer), Helen K. Angell(Délégation Paris 5), Magdalena Thurin(National Institutes of Health), Alessandro Lugli(University of Bern), Inti Zlobec(University of Bern), Anne Berger(Assistance Publique – Hôpitaux de Paris), Carlo Bifulco(Providence Portland Medical Center), Gerardo Botti(Istituto Nazionale Tumori IRCCS "Fondazione G. Pascale"), Fabiana Tatangelo(Istituto Nazionale Tumori IRCCS "Fondazione G. Pascale"), Cedrik M. Britten(Johannes Gutenberg University Mainz), Sebastian Kreiter(Johannes Gutenberg University Mainz), Lotfi Chouchane(Weill Cornell Medical College in Qatar), Paolo Delrio(Istituto Nazionale Tumori IRCCS "Fondazione G. Pascale"), Hartmann Arndt(Friedrich-Alexander-Universität Erlangen-Nürnberg), Martin Asslaber(Medical University of Graz), Michele Maio(University of Siena), Giuseppe Masucci(Karolinska University Hospital), Martin Mihm(Harvard University), Fernando Vidal‐Vanaclocha(Universidad San Pablo CEU), James P. Allison(Memorial Sloan Kettering Cancer Center), Sacha Gnjatic(Memorial Sloan Kettering Cancer Center), Leif Håkansson(Lund University), Christoph Huber(Johannes Gutenberg University Mainz), Harpreet Singh‐Jasuja(Immatics Biotechnologies (Germany)), Christian H. Ottensmeier(University of Southampton), H. Zwierzina(Innsbruck Medical University), Luigi Laghi(Humanitas University), Fabio Grizzi(Humanitas University), Pamela S. Ohashi(Ontario Institute for Cancer Research), Patricia A. Shaw(Princess Margaret Cancer Centre), Blaise Clarke(Princess Margaret Cancer Centre), Bradly G. Wouters(Princess Margaret Cancer Centre), Yutaka Kawakami(Keio University), Shoichi Hazama(Yamaguchi University), Kiyotaka Okuno(Kindai University), Ena Wang(National Institutes of Health Clinical Center), Jill O’Donnell-Tormey(Cancer Research Institute), Christine Lagorce(Assistance Publique – Hôpitaux de Paris), Graham Pawelec(University of Tübingen), Michael I. Nishimura(Loyola University Medical Center), Robert D. Hawkins(University of Manchester), Réjean Lapointe(Institute for Research in Immunology and Cancer), Andreas Lundqvist(Karolinska Institutet), Samir N. Khleif(Augusta University Health), Shuji Ogino(Brigham and Women's Hospital), Peter Gibbs(The Royal Melbourne Hospital), Paul Waring(The University of Melbourne), Noriyuki Sato(Sapporo Medical University), Toshihiko Torigoe(Sapporo Medical University), Kyogo Itoh(Kurume University), Prabhudas S. Patel(Gujarat Cancer & Research Institute), Shilin N. Shukla(Gujarat Cancer & Research Institute), Richard Palmqvist(Umeå University), Irıs D. Nagtegaal(Radboud University Nijmegen), Yili Wang(Xi'an Jiaotong University), Corrado D’Arrigo(Dorset County Hospital), Scott Kopetz(The University of Texas MD Anderson Cancer Center), Frank A. Sinicrope(Mayo Clinic), Giorgio Trinchieri(National Institutes of Health), Thomas F. Gajewski(Society for Immunotherapy of Cancer), Paolo A. Ascierto(Istituto Nazionale Tumori IRCCS "Fondazione G. Pascale"), Bernard A. Fox(Oregon Health & Science University)
Journal of Translational Medicine
October 3, 2012
Cited by 803Open Access
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Abstract

Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N) and evidence for metastases (M). However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the 'Immunoscore' into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of this initiative, and of the J Transl Med. editorial from January 2012. Immunophenotyping of tumors may provide crucial novel prognostic information. The results of this international validation may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune).


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