Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group.
Embargo End Date
ICR Authors
Authors
Amgad, M
Stovgaard, ES
Balslev, E
Thagaard, J
Chen, W
Dudgeon, S
Sharma, A
Kerner, JK
Denkert, C
Yuan, Y
AbdulJabbar, K
Wienert, S
Savas, P
Voorwerk, L
Beck, AH
Madabhushi, A
Hartman, J
Sebastian, MM
Horlings, HM
Hudeček, J
Ciompi, F
Moore, DA
Singh, R
Roblin, E
Balancin, ML
Mathieu, M-C
Lennerz, JK
Kirtani, P
Chen, I-C
Braybrooke, JP
Pruneri, G
Demaria, S
Adams, S
Schnitt, SJ
Lakhani, SR
Rojo, F
Comerma, L
Badve, SS
Khojasteh, M
Symmans, WF
Sotiriou, C
Gonzalez-Ericsson, P
Pogue-Geile, KL
Kim, RS
Rimm, DL
Viale, G
Hewitt, SM
Bartlett, JMS
Penault-Llorca, F
Goel, S
Lien, H-C
Loibl, S
Kos, Z
Loi, S
Hanna, MG
Michiels, S
Kok, M
Nielsen, TO
Lazar, AJ
Bago-Horvath, Z
Kooreman, LFS
van der Laak, JAWM
Saltz, J
Gallas, BD
Kurkure, U
Barnes, M
Salgado, R
Cooper, LAD
International Immuno-Oncology Biomarker Working Group,
Stovgaard, ES
Balslev, E
Thagaard, J
Chen, W
Dudgeon, S
Sharma, A
Kerner, JK
Denkert, C
Yuan, Y
AbdulJabbar, K
Wienert, S
Savas, P
Voorwerk, L
Beck, AH
Madabhushi, A
Hartman, J
Sebastian, MM
Horlings, HM
Hudeček, J
Ciompi, F
Moore, DA
Singh, R
Roblin, E
Balancin, ML
Mathieu, M-C
Lennerz, JK
Kirtani, P
Chen, I-C
Braybrooke, JP
Pruneri, G
Demaria, S
Adams, S
Schnitt, SJ
Lakhani, SR
Rojo, F
Comerma, L
Badve, SS
Khojasteh, M
Symmans, WF
Sotiriou, C
Gonzalez-Ericsson, P
Pogue-Geile, KL
Kim, RS
Rimm, DL
Viale, G
Hewitt, SM
Bartlett, JMS
Penault-Llorca, F
Goel, S
Lien, H-C
Loibl, S
Kos, Z
Loi, S
Hanna, MG
Michiels, S
Kok, M
Nielsen, TO
Lazar, AJ
Bago-Horvath, Z
Kooreman, LFS
van der Laak, JAWM
Saltz, J
Gallas, BD
Kurkure, U
Barnes, M
Salgado, R
Cooper, LAD
International Immuno-Oncology Biomarker Working Group,
Document Type
Journal Article
Date
2020-05-12
Date Accepted
2020-02-18
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.
Citation
NPJ breast cancer, 2020, 6 pp. 16 - ?
Source Title
Publisher
NATURE RESEARCH
ISSN
2374-4677
eISSN
2374-4677
Collections
Research Team
Computational Pathology & Integrated Genomics