Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group
Journal
NPJ breast cancer
Journal Volume
6
Journal Issue
1
Date Issued
2020
Author(s)
Amgad, Mohamed
Stovgaard, Elisabeth Specht
Balslev, Eva
Thagaard, Jeppe
Chen, Weijie
Dudgeon, Sarah
Sharma, Ashish
Kerner, Jennifer K
Denkert, Carsten
Yuan, Yinyin
AbdulJabbar, Khalid
Wienert, Stephan
Savas, Peter
Voorwerk, Leonie
Beck, Andrew H
Madabhushi, Anant
Hartman, Johan
Sebastian, Manu M
Horlings, Hugo M
Hudeček, Jan
Ciompi, Francesco
Moore, David A
Singh, Rajendra
Roblin, Elvire
Balancin, Marcelo Luiz
Mathieu, Marie-Christine
Lennerz, Jochen K
Kirtani, Pawan
Braybrooke, Jeremy P
Pruneri, Giancarlo
Demaria, Sandra
Adams, Sylvia
Schnitt, Stuart J
Lakhani, Sunil R
Rojo, Federico
Comerma, Laura
Badve, Sunil S
Khojasteh, Mehrnoush
Symmans, W Fraser
Sotiriou, Christos
Gonzalez-Ericsson, Paula
Pogue-Geile, Katherine L
Kim, Rim S
Rimm, David L
Viale, Giuseppe
Hewitt, Stephen M
Bartlett, John M S
Penault-Llorca, Frédérique
Goel, Shom
Loibl, Sibylle
Kos, Zuzana
Loi, Sherene
Hanna, Matthew G
Michiels, Stefan
Kok, Marleen
Nielsen, Torsten O
Lazar, Alexander J
Bago-Horvath, Zsuzsanna
Kooreman, Loes F S
van der Laak, Jeroen A W M
Saltz, Joel
Gallas, Brandon D
Kurkure, Uday
Barnes, Michael
Salgado, Roberto
Cooper, Lee A D
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.
Subjects
Breast cancer; Cancer imaging; Prognostic markers; Tumour biomarkers; Tumour immunology
SDGs
Type
review