Journal Article

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

Reisenbichler Emily, van der Laak Jeroen A W M, Sua, Luz, Kirtani Pawan, Kim Seong- Rim, Singh, Rajendra, Blackley, Elizabeth F, Christie, Michael, Salgado, Roberto, Barnes, Michael, Broeckx Glenn, Michiels, Stefan, Francis, Prudence A, Dhanusha, Sabanathan, AbdulJabbar Khalid, Radosevic-Robin Nina, Schnitt, Stuart J, Gluz Oleg, Peeters Dieter, Chan, Jack, Bethmann, Daniel, Giltnane, Jennifer, Maartje, van Seijen, Swanton, Charles, Goetz, Matthew P, Chen, Weijie, Hida, Akira I, Naber, Stephen, Piccart Martine, Balslev, Eva, Höflmayer Doris, Gruosso, bius Tina, Laudus Nele, Thagaard Jeppe, Fraser, Symmans W, Sharma, Ashish, Willis Scooter, Tran, William T, Bartlett, John M, Castillo Miluska, Siziopikou Kalliopi, Tom, John, Hiley Crispin, Lazar, Alexander J, Goel Shom, Savas, Peter, Blenman Kim R M, Gaire Fabien, ElGabry, Ehab A, Sebastian, Manu M, Tutt, Andrew, Braybrooke, Jeremy P, Regan, Meredith M, Curigliano Giuseppe, Korski Konstanty, Lacroix-Triki Magali, Soler, Teresa, Sanchez Joselyn, Swain, Sandra, Srinivasan, Ashok, Paik Soonmyung, Hudeček, Jan, Kim, Rim S, Wienert Stephan, I-Chun, Chen, Hewitt, Stephen

2020

Overview

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.

• Publisher: Nature Publishing Group
• Subject: Algorithms / Biomarkers / Breast cancer / Deep learning / Histology / Lymphocytes / Machine learning / Medical research / Oncology / Tumors / Working groups