Training pathologists to assess stromal tumour‐infiltrating lymphocytes in breast cancer synergises efforts in clinical care and scientific research

Author:

Ly Amy1ORCID,Garcia Victor2,Blenman Kim R M34,Ehinger Anna5ORCID,Elfer Katherine2,Hanna Matthew G6,Li Xiaoxian7,Peeters Dieter J E89ORCID,Birmingham Ryan210,Dudgeon Sarah11,Gardecki Emma2,Gupta Rajarsi12,Lennerz Jochen13,Pan Tony10,Saltz Joel12,Wharton Keith A14,Ehinger Daniel1516ORCID,Acs Balazs1718,Dequeker Elisabeth M C19,Salgado Roberto2021,Gallas Brandon D2ORCID

Affiliation:

1. Department of Pathology Massachusetts General Hospital Boston MA USA

2. Center for Devices and Radiological Health, Office of Science and Engineering Laboratories, Division of Imaging, Diagnostics, and Software Reliability US Food and Drug Administration Silver Spring MD USA

3. Department of Internal Medicine, Section of Medical Oncology and Yale Cancer Center Yale School of Medicine New Haven CT USA

4. Department of Computer Science Yale School of Engineering and Applied Science New Haven CT USA

5. Department of Genetics, Pathology and Molecular Diagnostics, Laboratory Medicine, Region Skane Lund University Lund Sweden

6. Department of Pathology and Laboratory Medicine Memorial Sloan Kettering Cancer Center New York NY USA

7. Department of Pathology and Laboratory Medicine Emory University Atlanta GA USA

8. Department of Pathology University Hospital Antwerp Edegem Belgium

9. Department of Pathology Algemeen Ziekenhuis (AZ) Sint‐Maarten Mechelen Belgium

10. Department of Biomedical Informatics Emory University Atlanta GA USA

11. Center for Computational Health Yale School of Medicine New Haven CT USA

12. Department of Biomedical Informatics Stony Brook University Stony Brook NY USA

13. Department of Pathology, Center for Integrated Diagnostics Massachusetts General Hospital Boston MA USA

14. Roche Diagnostic Solutions Oro Valley AZ USA

15. Department of Clinical Sciences, Division of Oncology Lund University Lund Sweden

16. Department of Genetics, Pathology, and Molecular Diagnostics Skane University Hospital Lund Sweden

17. Department of Oncology and Pathology, Cancer Centre Karolinska Karolinksa Institutet Stockholm Sweden

18. Department of Clinical Pathology and Cancer Diagnostics Karolinska University Hospital Stockholm Sweden

19. Department of Public Health and Primary Care, Biomedical Quality Assurance Research Unit University of Leuven Leuven Belgium

20. Department of Pathology Gasthuiszusters Antwerpen‐Ziekenhuis Netwerk Antwerpen (GZA‐ZNA) Hospitals Antwerp Belgium

21. Division of Research Peter MacCallum Cancer Centre Melbourne Australia

Abstract

A growing body of research supports stromal tumour‐infiltrating lymphocyte (TIL) density in breast cancer to be a robust prognostic and predicive biomarker. The gold standard for stromal TIL density quantitation in breast cancer is pathologist visual assessment using haematoxylin and eosin‐stained slides. Artificial intelligence/machine‐learning algorithms are in development to automate the stromal TIL scoring process, and must be validated against a reference standard such as pathologist visual assessment. Visual TIL assessment may suffer from significant interobserver variability. To improve interobserver agreement, regulatory science experts at the US Food and Drug Administration partnered with academic pathologists internationally to create a freely available online continuing medical education (CME) course to train pathologists in assessing breast cancer stromal TILs using an interactive format with expert commentary. Here we describe and provide a user guide to this CME course, whose content was designed to improve pathologist accuracy in scoring breast cancer TILs. We also suggest subsequent steps to translate knowledge into clinical practice with proficiency testing.

Funder

Stony Brook University

Emory University

Yale University

Publisher

Wiley

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