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Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group
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 guideli...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217824/ https://www.ncbi.nlm.nih.gov/pubmed/32411818 http://dx.doi.org/10.1038/s41523-020-0154-2 |
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author | 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 Chen, I-Chun 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 Lien, Huang-Chun 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. |
author_facet | 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 Chen, I-Chun 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 Lien, Huang-Chun 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. |
author_sort | Amgad, Mohamed |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7217824 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-72178242020-05-14 Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group 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 Chen, I-Chun 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 Lien, Huang-Chun 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. NPJ Breast Cancer Review Article 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. Nature Publishing Group UK 2020-05-12 /pmc/articles/PMC7217824/ /pubmed/32411818 http://dx.doi.org/10.1038/s41523-020-0154-2 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Review Article 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 Chen, I-Chun 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 Lien, Huang-Chun 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. Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group |
title | Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group |
title_full | Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group |
title_fullStr | Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group |
title_full_unstemmed | Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group |
title_short | Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group |
title_sort | report on computational assessment of tumor infiltrating lymphocytes from the international immuno-oncology biomarker working group |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217824/ https://www.ncbi.nlm.nih.gov/pubmed/32411818 http://dx.doi.org/10.1038/s41523-020-0154-2 |
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