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Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group

Authors :
Laura Comerma
Marie-Christine Mathieu
Joel H. Saltz
Giancarlo Pruneri
Peter Savas
Shom Goel
Stephan Wienert
Paula I. Gonzalez-Ericsson
Lee Cooper
Sunil R. Lakhani
Stefan Michiels
Pawan Kirtani
Sarah N Dudgeon
Francesco Ciompi
Uday Kurkure
Manu M. Sebastian
Giuseppe Viale
Brandon D. Gallas
Mohamed Amgad
John M. S. Bartlett
Jan Hudecek
Torsten O. Nielsen
Elisabeth Specht Stovgaard
Huang-Chun Lien
Alexander J. Lazar
Johan Hartman
Yinyin Yuan
Rim S. Kim
Jeppe Thagaard
Ashish Sharma
Sylvia Adams
Matthew G. Hanna
Stephen M. Hewitt
Weijie Chen
David L. Rimm
Khalid AbdulJabbar
Sibylle Loibl
Jochen K. Lennerz
I-Chun Chen
Zsuzsanna Bago-Horvath
Mehrnoush Khojasteh
Frédérique Penault-Llorca
Katherine L. Pogue-Geile
Federico Rojo
Marcelo Luiz Balancin
David Moore
Stuart J. Schnitt
Roberto Salgado
Loes F. S. Kooreman
Sherene Loi
Jeremy P Braybrooke
Eva Balslev
Leonie Voorwerk
Sunil S. Badve
Elvire Roblin
Jennifer K. Kerner
Marleen Kok
Andrew H. Beck
Michael Barnes
Jeroen van der Laak
Carsten Denkert
W. Fraser Symmans
Zuzana Kos
Rajendra Singh
Anant Madabhushi
Christos Sotiriou
Sandra Demaria
Hugo M. Horlings
Department of Pathology
Herlev and Gentofte Hospital
The University of Sydney
Charité, Institute of Pathology, Translational Tumorpathology Unit
Division of Experimental Therapy
The Netherlands Cancer Institute NKI/AvL
Innovation North - Faculty of Information and Technology
Leeds Metropolitan University
Pathologie morphologique
Département de biologie et pathologie médicales [Gustave Roussy]
Institut Gustave Roussy (IGR)-Institut Gustave Roussy (IGR)
European Institute of Oncology [Milan] (ESMO)
University of Southern Queensland (USQ)
Instituto de Física Teórica UAM/CSIC (IFT)
Universidad Autónoma de Madrid (UAM)-Consejo Superior de Investigaciones Científicas [Madrid] (CSIC)
Institut Jules Bordet [Bruxelles]
Faculté de Médecine [Bruxelles] (ULB)
Université libre de Bruxelles (ULB)-Université libre de Bruxelles (ULB)
Division of Pathology and Laboratory Medicine
Università degli Studi di Milano = University of Milan (UNIMI)-European Institute of Oncology [Milan] (ESMO)
University of the Sunshine Coast (USC)
Centre Jean Perrin [Clermont-Ferrand] (UNICANCER/CJP)
UNICANCER
Imagerie Moléculaire et Stratégies Théranostiques (IMoST)
Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])
German Breast Group (GBG)
Breast Cancer Translational Research Laboratory
Université libre de Bruxelles (ULB)-Université libre de Bruxelles (ULB)-Faculté de Médecine [Bruxelles] (ULB)
Service de biostatistique et d'épidémiologie (SBE)
Direction de la recherche clinique [Gustave Roussy]
Institut Gustave Roussy (IGR)
Oncostat (U1018 (Équipe 2))
Institut Gustave Roussy (IGR)-Centre de recherche en épidémiologie et santé des populations (CESP)
Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay
The Netherlands Cancer Institute
The University of Texas M.D. Anderson Cancer Center [Houston]
Medizinische Universität Wien = Medical University of Vienna
Computational Biomedicine Lab (CBL)
University of Houston
UCL - SSS/IREC/SLUC - Pôle St.-Luc
UCL - (SLuc) Service d'anatomie pathologique
Universidad Autonoma de Madrid (UAM)-Consejo Superior de Investigaciones Científicas [Madrid] (CSIC)
Università degli Studi di Milano [Milano] (UNIMI)-European Institute of Oncology [Milan] (ESMO)
Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut National de la Santé et de la Recherche Médicale (INSERM)
German Breast Group
Medical University of Vienna, Department of Pathology
Amgad, Mohamed [0000-0001-7599-6162]
Sharma, Ashish [0000-0002-1011-6504]
Savas, Peter [0000-0001-5999-428X]
Hudeček, Jan [0000-0003-1071-5686]
Braybrooke, Jeremy P [0000-0003-1943-7360]
Demaria, Sandra [0000-0003-4426-0499]
Comerma, Laura [0000-0002-0249-4636]
Badve, Sunil S [0000-0001-8861-9980]
Symmans, W Fraser [0000-0002-1526-184X]
Gonzalez-Ericsson, Paula [0000-0002-6292-6963]
Rimm, David L [0000-0001-5820-4397]
Loi, Sherene [0000-0001-6137-9171]
Hanna, Matthew G [0000-0002-7536-1746]
Lazar, Alexander J [0000-0002-6395-4499]
Bago-Horvath, Zsuzsanna [0000-0002-8555-7806]
van der Laak, Jeroen AWM [0000-0001-7982-0754]
Gallas, Brandon D [0000-0001-7332-1620]
Kurkure, Uday [0000-0002-8273-7334]
Cooper, Lee AD [0000-0002-3504-4965]
Apollo - University of Cambridge Repository
Source :
npj Breast Cancer, Vol 6, Iss 1, Pp 1-13 (2020), The International Immuno-Oncology Biomarker Working Group, Lien, H-C, Loibl, S, Kos, Z, Loi, S, Hanna, M G, Michiels, S, Kok, M, Nielsen, T O, Lazar, A J, Bago-Horvath, Z, Kooreman, L F S, van der Laak, J A W M, Saltz, J, Gallas, B D, Kurkure, U, Barnes, M, Salgado, R & Cooper, L A D 2020, ' Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group ', npj Breast Cancer, vol. 6, 16 . https://doi.org/10.1038/s41523-020-0154-2, npj Breast Cancer, npj Breast Cancer, 2020, 6 (1), pp.16. ⟨10.1038/s41523-020-0154-2⟩, NPJ breast cancer, Vol. 6, p. 16 [1-13] (2020), NPJ BREAST CANCER, NPJ breast cancer, 6, npj Breast Cancer, Nature, 2020, 6 (1), pp.16. ⟨10.1038/s41523-020-0154-2⟩, NPJ breast cancer, 6, 1, 2020, ' Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group ', NPJ Breast Cancer . https://doi.org/10.1038/s41523-020-0154-2, NPJ Breast Cancer
Publication Year :
2020

Abstract

Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring.<br />info:eu-repo/semantics/published

Details

ISSN :
23744677
Volume :
6
Database :
OpenAIRE
Journal :
NPJ breast cancer
Accession number :
edsair.doi.dedup.....6a7c7a6ecc3ef9fc2cd6fab6b66d92d9
Full Text :
https://doi.org/10.1038/s41523-020-0154-2