TY - JOUR
T1 - Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group
AU - International Immuno-Oncology Biomarker Working Group
AU - Amgad, Mohamed
AU - Stovgaard, Elisabeth Specht
AU - Balslev, Eva
AU - Thagaard, Jeppe
AU - Chen, Weijie
AU - Dudgeon, Sarah
AU - Sharma, Ashish
AU - Kerner, Jennifer K.
AU - Denkert, Carsten
AU - Yuan, Yinyin
AU - AbdulJabbar, Khalid
AU - Wienert, Stephan
AU - Savas, Peter
AU - Voorwerk, Leonie
AU - Beck, Andrew H.
AU - Madabhushi, Anant
AU - Hartman, Johan
AU - Sebastian, Manu M.
AU - Horlings, Hugo M.
AU - Hudeček, Jan
AU - Ciompi, Francesco
AU - Moore, David A.
AU - Singh, Rajendra
AU - Roblin, Elvire
AU - Balancin, Marcelo Luiz
AU - Mathieu, Marie Christine
AU - Lennerz, Jochen K.
AU - Kirtani, Pawan
AU - Chen, I. Chun
AU - Braybrooke, Jeremy P.
AU - Pruneri, Giancarlo
AU - Demaria, Sandra
AU - Adams, Sylvia
AU - Schnitt, Stuart J.
AU - Lakhani, Sunil R.
AU - Rojo, Federico
AU - Comerma, Laura
AU - Badve, Sunil S.
AU - Khojasteh, Mehrnoush
AU - Symmans, W. Fraser
AU - Sotiriou, Christos
AU - Gonzalez-Ericsson, Paula
AU - Pogue-Geile, Katherine L.
AU - Kim, Rim S.
AU - Rimm, David L.
AU - Viale, Giuseppe
AU - Hewitt, Stephen M.
AU - Bartlett, John M.S.
AU - Michiels, Stefan
AU - Andre, Fabrice
N1 - Publisher Copyright:
© 2020, The Author(s).
PY - 2020/12/1
Y1 - 2020/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85083451193&partnerID=8YFLogxK
U2 - 10.1038/s41523-020-0154-2
DO - 10.1038/s41523-020-0154-2
M3 - Review article
AN - SCOPUS:85083451193
SN - 2374-4677
VL - 6
JO - npj Breast Cancer
JF - npj Breast Cancer
IS - 1
M1 - 16
ER -