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

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...

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Autores principales: Howat, William J, Blows, Fiona M, Provenzano, Elena, Brook, Mark N, Morris, Lorna, Gazinska, Patrycja, Johnson, Nicola, McDuffus, Leigh‐Anne, Miller, Jodi, Sawyer, Elinor J, Pinder, Sarah, van Deurzen, Carolien H M, Jones, Louise, Sironen, Reijo, Visscher, Daniel, Caldas, Carlos, Daley, Frances, Coulson, Penny, Broeks, Annegien, Sanders, Joyce, Wesseling, Jelle, Nevanlinna, Heli, Fagerholm, Rainer, Blomqvist, Carl, Heikkilä, Päivi, Ali, H Raza, Dawson, Sarah‐Jane, Figueroa, Jonine, Lissowska, Jolanta, Brinton, Louise, Mannermaa, Arto, Kataja, Vesa, Kosma, Veli‐Matti, Cox, Angela, Brock, Ian W, Cross, Simon S, Reed, Malcolm W, Couch, Fergus J, Olson, Janet E, Devillee, Peter, Mesker, Wilma E, Seyaneve, Caroline M, Hollestelle, Antoinette, Benitez, Javier, Perez, Jose Ignacio Arias, Menéndez, Primitiva, Bolla, Manjeet K, Easton, Douglas F, Schmidt, Marjanka K, Pharoah, Paul D, Sherman, Mark E, García‐Closas, Montserrat
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4858117/
https://www.ncbi.nlm.nih.gov/pubmed/27499890
http://dx.doi.org/10.1002/cjp2.3
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author Howat, William J
Blows, Fiona M
Provenzano, Elena
Brook, Mark N
Morris, Lorna
Gazinska, Patrycja
Johnson, Nicola
McDuffus, Leigh‐Anne
Miller, Jodi
Sawyer, Elinor J
Pinder, Sarah
van Deurzen, Carolien H M
Jones, Louise
Sironen, Reijo
Visscher, Daniel
Caldas, Carlos
Daley, Frances
Coulson, Penny
Broeks, Annegien
Sanders, Joyce
Wesseling, Jelle
Nevanlinna, Heli
Fagerholm, Rainer
Blomqvist, Carl
Heikkilä, Päivi
Ali, H Raza
Dawson, Sarah‐Jane
Figueroa, Jonine
Lissowska, Jolanta
Brinton, Louise
Mannermaa, Arto
Kataja, Vesa
Kosma, Veli‐Matti
Cox, Angela
Brock, Ian W
Cross, Simon S
Reed, Malcolm W
Couch, Fergus J
Olson, Janet E
Devillee, Peter
Mesker, Wilma E
Seyaneve, Caroline M
Hollestelle, Antoinette
Benitez, Javier
Perez, Jose Ignacio Arias
Menéndez, Primitiva
Bolla, Manjeet K
Easton, Douglas F
Schmidt, Marjanka K
Pharoah, Paul D
Sherman, Mark E
García‐Closas, Montserrat
author_facet Howat, William J
Blows, Fiona M
Provenzano, Elena
Brook, Mark N
Morris, Lorna
Gazinska, Patrycja
Johnson, Nicola
McDuffus, Leigh‐Anne
Miller, Jodi
Sawyer, Elinor J
Pinder, Sarah
van Deurzen, Carolien H M
Jones, Louise
Sironen, Reijo
Visscher, Daniel
Caldas, Carlos
Daley, Frances
Coulson, Penny
Broeks, Annegien
Sanders, Joyce
Wesseling, Jelle
Nevanlinna, Heli
Fagerholm, Rainer
Blomqvist, Carl
Heikkilä, Päivi
Ali, H Raza
Dawson, Sarah‐Jane
Figueroa, Jonine
Lissowska, Jolanta
Brinton, Louise
Mannermaa, Arto
Kataja, Vesa
Kosma, Veli‐Matti
Cox, Angela
Brock, Ian W
Cross, Simon S
Reed, Malcolm W
Couch, Fergus J
Olson, Janet E
Devillee, Peter
Mesker, Wilma E
Seyaneve, Caroline M
Hollestelle, Antoinette
Benitez, Javier
Perez, Jose Ignacio Arias
Menéndez, Primitiva
Bolla, Manjeet K
Easton, Douglas F
Schmidt, Marjanka K
Pharoah, Paul D
Sherman, Mark E
García‐Closas, Montserrat
author_sort Howat, William J
collection PubMed
description 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.
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spelling pubmed-48581172016-08-05 Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium Howat, William J Blows, Fiona M Provenzano, Elena Brook, Mark N Morris, Lorna Gazinska, Patrycja Johnson, Nicola McDuffus, Leigh‐Anne Miller, Jodi Sawyer, Elinor J Pinder, Sarah van Deurzen, Carolien H M Jones, Louise Sironen, Reijo Visscher, Daniel Caldas, Carlos Daley, Frances Coulson, Penny Broeks, Annegien Sanders, Joyce Wesseling, Jelle Nevanlinna, Heli Fagerholm, Rainer Blomqvist, Carl Heikkilä, Päivi Ali, H Raza Dawson, Sarah‐Jane Figueroa, Jonine Lissowska, Jolanta Brinton, Louise Mannermaa, Arto Kataja, Vesa Kosma, Veli‐Matti Cox, Angela Brock, Ian W Cross, Simon S Reed, Malcolm W Couch, Fergus J Olson, Janet E Devillee, Peter Mesker, Wilma E Seyaneve, Caroline M Hollestelle, Antoinette Benitez, Javier Perez, Jose Ignacio Arias Menéndez, Primitiva Bolla, Manjeet K Easton, Douglas F Schmidt, Marjanka K Pharoah, Paul D Sherman, Mark E García‐Closas, Montserrat J Pathol Clin Res Original Articles 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. John Wiley and Sons Inc. 2014-12-04 /pmc/articles/PMC4858117/ /pubmed/27499890 http://dx.doi.org/10.1002/cjp2.3 Text en © 2014 John Wiley and Sons Ltd and The Pathological Society of Great Britain and Ireland This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial (http://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Original Articles
Howat, William J
Blows, Fiona M
Provenzano, Elena
Brook, Mark N
Morris, Lorna
Gazinska, Patrycja
Johnson, Nicola
McDuffus, Leigh‐Anne
Miller, Jodi
Sawyer, Elinor J
Pinder, Sarah
van Deurzen, Carolien H M
Jones, Louise
Sironen, Reijo
Visscher, Daniel
Caldas, Carlos
Daley, Frances
Coulson, Penny
Broeks, Annegien
Sanders, Joyce
Wesseling, Jelle
Nevanlinna, Heli
Fagerholm, Rainer
Blomqvist, Carl
Heikkilä, Päivi
Ali, H Raza
Dawson, Sarah‐Jane
Figueroa, Jonine
Lissowska, Jolanta
Brinton, Louise
Mannermaa, Arto
Kataja, Vesa
Kosma, Veli‐Matti
Cox, Angela
Brock, Ian W
Cross, Simon S
Reed, Malcolm W
Couch, Fergus J
Olson, Janet E
Devillee, Peter
Mesker, Wilma E
Seyaneve, Caroline M
Hollestelle, Antoinette
Benitez, Javier
Perez, Jose Ignacio Arias
Menéndez, Primitiva
Bolla, Manjeet K
Easton, Douglas F
Schmidt, Marjanka K
Pharoah, Paul D
Sherman, Mark E
García‐Closas, Montserrat
Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium
title Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium
title_full Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium
title_fullStr Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium
title_full_unstemmed Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium
title_short Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium
title_sort performance of automated scoring of er, pr, her2, ck5/6 and egfr in breast cancer tissue microarrays in the breast cancer association consortium
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4858117/
https://www.ncbi.nlm.nih.gov/pubmed/27499890
http://dx.doi.org/10.1002/cjp2.3
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