Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium

The Journal of Pathology: Clinical Research

William J Howat¹⁰  Fiona M Blows²¹  Elena Provenzano²⁵  Mark N Brook⁹  Lorna Morris¹⁰  Patrycja Gazinska¹  Nicola Johnson¹⁰  Leigh-Anne McDuffus¹⁰  Jodi Miller¹⁰  Elinor J Sawyer¹⁸  Sarah Pinder¹⁶  Carolien H M van Deurzen²  Louise Jones¹⁴  Reijo Sironen^10,28  Daniel Visscher^10,31  Carlos Caldas¹⁰  Frances Daley^10,22  Penny Coulson⁹  Annegien Broeks^10,19  Joyce Sanders^10,27  Jelle Wesseling^10,27  Heli Nevanlinna^10,17  Rainer Fagerholm^10,17  Carl Blomqvist^10,26  Päivi Heikkilä^10,23  H Raza Ali¹⁰  Sarah-Jane Dawson¹⁰  Jonine Figueroa^10,20  Jolanta Lissowska^8,10  Louise Brinton^10,20  Arto Mannermaa^10,28  Vesa Kataja^15,21  Veli-Matti Kosma^10,28  Angela Cox^7,21  Ian W Brock^7,21  Simon S Cross^21,24  Malcolm W Reed^7,21  Fergus J Couch^10,31  Janet E Olson^13,21  Peter Devillee^11,21  Wilma E Mesker^6,21  Caroline M Seyaneve^3,21  Antoinette Hollestelle^3,21  Javier Benitez^4,21  Jose Ignacio Arias Perez^12,21  Primitiva Menéndez^5,21  Manjeet K Bolla^25,30  Douglas F Easton²¹  Marjanka K Schmidt^25,29  Paul D Pharoah²¹  Mark E Sherman^10,20 

[1] Breakthrough Breast Cancer Research Unit, Division of Cancer Studies, King's College London, Guy's Hospital, London, UK;Department of Pathology, Erasmus University Medical Center, Rotterdam, The Netherlands;Family Cancer Clinic, Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands;Human Genetics Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain;Servicio de Anatomía Patológica, Hospital Monte Naranco, Oviedo, Spain;Department of Surgical Oncology, Leiden University Medical Center, The Netherlands;CRUK/YCR Sheffield Cancer Research Centre, Department of Oncology, University of Sheffield, Sheffield, UK;Department of Cancer Epidemiology and Prevention, M. Sklodowska-Curie Memorial Cancer Center & Institute of Oncology, Warsaw, Poland;Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK;Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK;Department of Human Genetics & Department of Pathology, Leiden University Medical Center, The Netherlands;Servicio de Cirugía General y Especialidades, Hospital Monte Naranco, Oviedo, Spain;Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA;Centre for Tumour Biology, Barts Institute of Cancer, Barts, UK;Kuopio University Hospital, Cancer Center, Kuopio, Finland;Research Oncology, Division of Cancer Studies, King's College London, Guy's Hospital, London, UK;Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland;Division of Cancer Studies, NIHR Comprehensive Biomedical Research Centre, Guy's & St. Thomas' NHS Foundation Trust in partnership with King's College London, London, UK;Core Facility for Molecular Pathology and Biobanking, Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands;Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA;Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK;Breakthrough Breast Cancer Research Centre, Division of Breast Cancer Research, The Institute of Cancer Research, London, UK;Department of Pathology, Helsinki University Central Hospital, Helsinki, Finland;Academic Unit of Pathology, Department of Neuroscience, University of Sheffield, Sheffield, UK;Breast Pathology, Addenbrookes Hospital, Cambridge, UK;Department of Oncology, Helsinki University Central Hospital, Helsinki, Finland;Department of Pathology, Division of Diagnostic Oncology, Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands;School of Medicine, Institute of Clinical Medicine, Pathology and Forensic Medicine, Cancer Center of Eastern Finland, University of Eastern Finland, Kuopio, Finland;Division of Molecular Pathology, Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands;Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK;Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA

关键词: breast tumours;    immunohistochemistry;    tissue microarrays;    digital pathology;    automated scoring;   

DOI  :  10.1002/cjp2.3

来源: Wiley

【 摘 要 】

Abstract

Breast cancer risk factors and clinical outcomes vary by tumour marker expression. However, individual studies often lack the power required to assess these relationships, and large-scale analyses are limited by the need for high throughput, standardized scoring methods. To address these limitations, we assessed whether automated image analysis of immunohistochemically stained tissue microarrays can permit rapid, standardized scoring of tumour markers from multiple studies. Tissue microarray sections prepared in nine studies containing 20 263 cores from 8267 breast cancers stained for two nuclear (oestrogen receptor, progesterone receptor), two membranous (human epidermal growth factor receptor 2 and epidermal growth factor receptor) and one cytoplasmic (cytokeratin 5/6) marker were scanned as digital images. Automated algorithms were used to score markers in tumour cells using the Ariol system. We compared automated scores against visual reads, and their associations with breast cancer survival. Approximately 65–70% of tissue microarray cores were satisfactory for scoring. Among satisfactory cores, agreement between dichotomous automated and visual scores was highest for oestrogen receptor (Kappa = 0.76), followed by human epidermal growth factor receptor 2 (Kappa = 0.69) and progesterone receptor (Kappa = 0.67). Automated quantitative scores for these markers were associated with hazard ratios for breast cancer mortality in a dose-response manner. Considering visual scores of epidermal growth factor receptor or cytokeratin 5/6 as the reference, automated scoring achieved excellent negative predictive value (96–98%), but yielded many false positives (positive predictive value = 30–32%). For all markers, we observed substantial heterogeneity in automated scoring performance across tissue microarrays. Automated analysis is a potentially useful tool for large-scale, quantitative scoring of immunohistochemically stained tissue microarrays available in consortia. However, continued optimization, rigorous marker-specific quality control measures and standardization of tissue microarray designs, staining and scoring protocols is needed to enhance results.

【 授权许可】

CC BY-NC   
© 2014 John Wiley and Sons Ltd and The Pathological Society of Great Britain and Ireland

Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.