Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium
van, Deurzen Carolien
Ali, Hamid Raza
Arias, Perez Jose
The Journal of Pathology
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Howat, W., Blows, F., Provenzano, E., Brook, M., Morris, L., Gazinska, P., Johnson, N., et al. (2014). 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, 1 18-32. https://doi.org/10.1002/cjp2.3
Breast cancer risk factors and clinical outcomes vary by tumor 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 (TMAs) can permit rapid, standardized scoring of tumor markers from multiple studies. TMA sections prepared in nine studies containing 20,263 cores from 8,267 breast cancers stained for two nuclear (estrogen receptor, ER; progesterone receptor, PR) two membranous (human epidermal growth factor receptor 2, HER2 and epidermal growth factor receptor, EGFR) and one cytoplasmic (cytokeratin 5/6, CK5/6) marker were scanned as digital images. Automated algorithms were used to score markers in tumor cells using the Ariol system. We compared automated scores against visual reads, and their associations with breast cancer survival. Approximately 65-70% of TMA cores were satisfactory for scoring. Among satisfactory cores, agreement between dichotomous automated and visual scores was highest for ER (Kappa=0.76), followed by HER2 (Kappa=0.69) and PR (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 EGFR or CK5/6 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 TMAs. Automated analysis is a potentially useful tool for large-scale, quantitative scoring of immunohistochemically stained TMAs available in consortia. However, continued optimization, rigorous marker-specific quality control measures, and standardization of TMA designs, staining and scoring protocols is needed to enhance results.
We would like to thank Rob Sykes from Ariol who helped to retrain the SEARCH image analysis for EGFR and CK5/6. We would also like to thank Mike Irwin at the Institute of Astronomy, Cambridge for assistance with methods in the automated analysis. ABCS was supported by the Dutch Cancer Society [grants NKI 2007-3839; 2009 4363]; BBMRI-NL, which is a Research Infrastructure financed by the Dutch government (NWO 184.021.007); and the Dutch National Genomics Initiative. CNIO-BCS was supported by the Genome Spain Foundation, the Red Temática de Investigación Cooperativa en Cáncer and grants from the Asociación Española Contra el Cáncer and the Fondo de Investigación Sanitario (PI11/00923 and PI081120). The Human Genotyping-CEGEN Unit (CNIO) is supported by the Instituto de Salud Carlos III. HEBCS was financially supported by the Helsinki University Central Hospital Research Fund, Academy of Finland (132473), the Finnish Cancer Society, The Nordic Cancer Union and the Sigrid Juselius Foundation. The KBCP was financially supported by the special Government Funding (EVO) of Kuopio University Hospital grants, Cancer Fund of North Savo, the Finnish Cancer Organizations, the Academy of Finland and by the strategic funding of the University of Eastern Finland The MCBCS was supported by an NIH Specialized Program of Research Excellence (SPORE) in Breast Cancer [CA116201], the Breast Cancer Research Foundation, the Mayo Clinic Breast Cancer Registry and a generous gift from the David F. and Margaret T. Grohne Family Foundation and the Ting Tsung and Wei Fong Chao Foundation. ORIGO authors thank E. Krol-Warmerdam, and J. Blom; The contributing studies were funded by grants from the Dutch Cancer Society (UL1997-1505) and the Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL CP16). PBCS was funded by Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. SBCS was supported by Yorkshire Cancer Research S295, S299, S305PA. SEARCH is funded by programme grant from Cancer Research UK [C490/A10124. C490/A16561] and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge. Part of this work was supported by the European Community´s Seventh Framework Programme under grant agreement number 223175 (grant number HEALTH-F2-2009-223175) (COGS). We acknowledge funds from Breakthrough Breast Cancer, UK, in support of MGC and MB.
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External DOI: https://doi.org/10.1002/cjp2.3
This record's URL: https://www.repository.cam.ac.uk/handle/1810/245887
Attribution-NonCommercial 2.0 UK: England & Wales
Licence URL: http://creativecommons.org/licenses/by-nc/2.0/uk/