Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: a report of the international immuno-oncology biomarker working group

Thagaard J, Broeckx G, Page DB, Jahangir CA, Verbandt S, Kos Z, Gupta R, Khiroya R, Abduljabbar K, Acosta Haab G, Acs B, Akturk G, Almeida JS, Alvarado-Cabrero I, Amgad M, Azmoudeh-Ardalan F, Badve S, Baharun NB, Balslev E, Bellolio ER, Bheemaraju V, Blenman KR, Botinelly Mendonça Fujimoto L, Bouchmaa N, Burgues O, Chardas A, Chon U Cheang M, Ciompi F, Cooper LA, Coosemans A, Corredor G, Dahl AB, Dantas Portela FL, Deman F, Demaria S, Doré Hansen J, Dudgeon SN, Ebstrup T, Elghazawy M, Fernandez-Martín C, Fox SB, Gallagher WM, Giltnane JM, Gnjatic S, Gonzalez-Ericsson PI, Grigoriadis A, Halama N, Hanna MG, Harbhajanka A, Hart SN, Hartman J, Hauberg S, Hewitt S, Hida AI, Horlings HM, Husain Z, Hytopoulos E, Irshad S, Janssen EA, Kahila M, Kataoka TR, Kawaguchi K, Kharidehal D, Khramtsov AI, Kiraz U, Kirtani P, Kodach LL, Korski K, Kovács A, Laenkholm AV, Lang-Schwarz C, Larsimont D, Lennerz JK, Lerousseau M, Li X, Ly A, Madabhushi A, Maley SK, Manur Narasimhamurthy V, Marks DK, McDonald ES, Mehrotra R, Michiels S, Minhas FuAA, Mittal S, Moore DA, Mushtaq S, Nighat H, Papathomas T, Penault-Llorca F, Perera RD, Pinard CJ, Pinto-Cardenas JC, Pruneri G, Pusztai L, Rahman A, Rajpoot NM, Rapoport BL, Rau TT, Reis-Filho JS, Ribeiro JM, Rimm D, Roslind A, Vincent-Salomon A, Salto-Tellez M, Saltz J, Sayed S, Scott E, Siziopikou KP, Sotiriou C, Stenzinger A, Sughayer MA, Sur D, Fineberg S, Symmans F, Tanaka S, Taxter T, Tejpar S, Teuwen J, Thompson EA, Tramm T, Tran WT, van der Laak J, van Diest PJ, Verghese GE, Viale G, Vieth M, Wahab N, Walter T, Waumans Y, Wen HY, Yang W, Yuan Y, Zin RM, Adams S, Bartlett J, Loibl S, Denkert C, Savas P, Loi S, Salgado R, Specht Stovgaard E (2023)

Publication Language: English

Publication Type: Journal article, Review article

Publication year: 2023

Journal

Book Volume: 260

Pages Range: 498-513

Journal Issue: 5

DOI: 10.1002/path.6155

Abstract

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Authors with CRIS profile

Involved external institutions

Vanderbilt University United States (USA) (US) Yale University United States (USA) (US) Weill Cornell Medicine United States (USA) (US) Mayo Clinic United States (USA) (US) Hospital Clínico Universitario de Valencia Spain (ES) University College London Hospitals (UCLH) United Kingdom (GB) Iuliu Hațieganu University of Medicine and Pharmacy / Universitatea de Medicină și Farmacie "Iuliu Hațieganu" (UMF Cluj) Romania (RO) Merck & Co., Inc. / Merck Sharp & Dohme Corp (MSD) United States (USA) (US) Icahn School of Medicine at Mount Sinai United States (USA) (US) University of British Columbia Canada (CA) Radboud University Nijmegen Medical Centre / Radboudumc of voluit Radboud Universitair Medisch Centrum (UMC) Netherlands (NL) Technical University of Denmark / Danmarks Tekniske Universitet (DTU) Denmark (DK) Visiopharm A/S Denmark (DK) GZA Ziekenhuizen Belgium (BE) Emory University United States (USA) (US) Hospital Universitário Getúlio Vargas (HUGV) Brazil (BR) Deutsches Krebsforschungszentrum (DKFZ) Germany (DE) Genentech Inc. United States (USA) (US) National Cancer Institute (NCI) United States (USA) (US) The University of Melbourne Australia (AU) Case Western Reserve University United States (USA) (US) Université Mohammed VI Polytechnique (UM6P) Morocco (MA) Tehran University of Medical Sciences (TUMS) / دانشگاه علوم پزشکی تهران Iran, Islamic Republic of (IR) Katholieke Universiteit Leuven (KUL) / Catholic University of Leuven Belgium (BE) Matsuyama Shimin Hospital / 松山市民病院 Japan (JP) Karolinska Institute Sweden (SE) Northwestern University United States (USA) (US) Centro Medico Nacional Siglo XXI Mexico (MX) University of the Frontier / Universidad de La Frontera (UFRO) Chile (CL) The National University of Malaysia / Universiti Kebangsaan Malaysia (UKM) Malaysia (MY) Polytechnic University of Valencia / Universidad Politécnica de Valencia Spain (ES) Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital (NKI / NKI-AVL) Netherlands (NL) Georgia Institute of Technology United States (USA) (US) Massachusetts General Hospital United States (USA) (US) Institut Jules Bordet Belgium (BE) Ziauddin University (ZU) Pakistan (PK) Stavanger University Hospital Norway (NO) Mines ParisTech / École Nationale Supérieure des Mines de Paris (ENSMP) France (FR) University of Warwick United Kingdom (GB) Iwate Medical University Japan (JP) Aakash Healthcare Super Speciality Hospital India (IN) University of Pennsylvania (UPenn) United States (USA) (US) Praava Health Bangladesh (BD) Narayana Medical College & Hospital India (IN) Manipal Hospitals India India (IN) Guy's and St Thomas' (NHS Foundation Trust) United Kingdom (GB) Sahlgrenska University Hospital / Sahlgrenska Universitetssjukhuset Sweden (SE) National Surgical Adjuvant Breast and Bowel Project Foundation (NSABP) United States (USA) (US) Institut Gustave-Roussy France (FR) Tempus Labs United States (USA) (US) Aarhus University Hospital / Aarhus Universitetshospital Denmark (DK) State University of New York at Albany (UNY Albany / UAlbany) United States (USA) (US) University College London (UCL) United Kingdom (GB) New York University (NYU) United States (USA) (US) Fudan University / 复旦大学 China (CN) University of Washington United States (USA) (US) Sunnybrook Health Sciences Centre Canada (CA) CellCarta Canada (CA) University Medical Centre Utrecht (UMC Utrecht) Netherlands (NL) University of Texas MD Anderson Cancer Center United States (USA) (US) All India Institute of Medical Sciences Raipur (AIIMS) / अखिल भारतीय आयुर्विज्ञान संस्थान रायपुर India (IN) Kyoto University / 京都大学 Kyōto daigaku Japan (JP) Kuala Lumpur Hospital Malaysia (MY) Cardiovascular Research Foundation United States (USA) (US) Mayo Clinic Hospital United States (USA) (US) Philipps-Universität Marburg Germany (DE) University of Edinburgh United Kingdom (GB) Copenhagen University Hospital Denmark (DK) Ann & Robert H. Lurie Children's Hospital of Chicago United States (USA) (US) University College Dublin (UCD) Ireland (IE) Memorial Sloan Kettering Cancer Center United States (USA) (US) University of Birmingham United Kingdom (GB) Institut Curie France (FR) The Institute of Cancer Research (ICR) United Kingdom (GB) Universitätsklinikum Heidelberg Germany (DE) Earle A. Chiles Research Institute at the Robert W. Franz Cancer Center United States (USA) (US) King’s College London United Kingdom (GB) Sjællands Universitetshospital, Roskilde Denmark (DK) Peter MacCallum Cancer Centre Australia (AU) University of Surrey United Kingdom (GB) F. Hoffmann-La Roche Ltd Switzerland (CH) ICGA Foundation India (IN) Federal University of Amazonas / Universidade Federal do Amazonas (UFAM) Brazil (BR) European Institute of Oncology / Istituto Europeo di Oncologia (IEO) Italy (IT) King Hussein Cancer Center (KHCC) / مركز الحسين للسرطان Jordan (JO) Aga Khan University (AKU) / آغا خان یونیورسٹی‎ Pakistan (PK) iRhythm Technologies, Inc. United States (USA) (US) Bristol-Myers Squibb United States (USA) (US) Medical Oncology Centre of Rosebank South Africa (ZA) Fondazione IRCCS: Istituto Nazionale dei Tumori Italy (IT) Heinrich-Heine-Universität Düsseldorf Germany (DE) Centre Jean-Perrin (UNICANCER) France (FR) University of London United Kingdom (GB)

How to cite

APA:

Thagaard, J., Broeckx, G., Page, D.B., Jahangir, C.A., Verbandt, S., Kos, Z.,... Specht Stovgaard, E. (2023). Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: a report of the international immuno-oncology biomarker working group. Journal of Pathology, 260(5), 498-513. https://doi.org/10.1002/path.6155

MLA:

Thagaard, Jeppe, et al. "Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: a report of the international immuno-oncology biomarker working group." Journal of Pathology 260.5 (2023): 498-513.

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