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Published in: Breast Cancer Research and Treatment 2/2016

01-09-2016 | Preclinical study

St Gallen 2015 subtyping of luminal breast cancers: impact of different Ki67-based proliferation assessment methods

Authors: Cornelia M. Focke, Paul J. van Diest, Thomas Decker

Published in: Breast Cancer Research and Treatment | Issue 2/2016

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Abstract

Ki67 has been proposed as prognostic proliferation marker in luminal breast cancer (BC), but little is known on the influence of Ki67 assessment methods on subtyping into luminal A- and B-like tumors. Our aim was to study the influence of different Ki67-labeling index (Ki67-LI) assessment methods on the proportion of BCs classified as luminal A-like. 280 early BCs were subtyped according to the St Gallen 2015 definitions into 71 % luminal (HER2 negative), 6 % luminal B-like (HER2 positive), 13 % triple negative, 1 % HER2 positive (nonluminal), and 9 % special type. Digitized whole slides were counted manually on the screen. We used nine defined counting methods to assess the Ki67-LI (including the International Ki67 in Breast Cancer Working Group recommendations), and compared the resulting medians and the proportions of cancers classified as luminal A-like according to the formerly used cut-off <20 %. Methods assessing hot spots and tumor periphery resulted in significantly higher Ki67-LI medians than those measuring an average proliferation (27.45 % vs 16.96 %, p < 0.0001). Substantially lower median Ki67-LI were found when assessing 1020 compared to counting 100, 200, 300 cells (17.65 vs 33 %, vs 28 %, vs 24.33 %, respectively; p < 0.0001), or 510 cells (20.59 %, p = 0.019). Applying a standard Ki67-LI cut-off <20 % to define low proliferation for all methods, the proportion of luminal A-like cancers varied between 13 and 44 %. The proportion of BCs classified as luminal A-like is highly influenced by the Ki67-LI assessment method. As a consequence, the selection of a specific Ki67-LI assessment method may have a direct effect on the proportion of patients considered having low-risk disease and thus influence therapeutic decision making. This calls for a standardized assessment method.
Literature
1.
2.
go back to reference Sorlie T et al (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA 98(19):10869–10874PubMedPubMedCentralCrossRef Sorlie T et al (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA 98(19):10869–10874PubMedPubMedCentralCrossRef
3.
go back to reference Sorlie T et al (2003) Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci USA 100(14):8418–8423PubMedPubMedCentralCrossRef Sorlie T et al (2003) Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci USA 100(14):8418–8423PubMedPubMedCentralCrossRef
4.
go back to reference Blows FM et al (2010) Subtyping of breast cancer by immunohistochemistry to investigate a relationship between subtype and short and long term survival: a collaborative analysis of data for 10,159 cases from 12 studies. PLoS Med 7(5):e1000279PubMedPubMedCentralCrossRef Blows FM et al (2010) Subtyping of breast cancer by immunohistochemistry to investigate a relationship between subtype and short and long term survival: a collaborative analysis of data for 10,159 cases from 12 studies. PLoS Med 7(5):e1000279PubMedPubMedCentralCrossRef
5.
go back to reference Nielsen TO et al (2010) A comparison of PAM50 intrinsic subtyping with immunohistochemistry and clinical prognostic factors in tamoxifen-treated estrogen receptor-positive breast cancer. Clin Cancer Res 16(21):5222–5232PubMedPubMedCentralCrossRef Nielsen TO et al (2010) A comparison of PAM50 intrinsic subtyping with immunohistochemistry and clinical prognostic factors in tamoxifen-treated estrogen receptor-positive breast cancer. Clin Cancer Res 16(21):5222–5232PubMedPubMedCentralCrossRef
7.
go back to reference Goldhirsch A et al (2013) Personalizing the treatment of women with early breast cancer: highlights of the St Gallen international expert consensus on the primary therapy of early breast cancer 2013. Ann Oncol 24(9):2206–2223PubMedPubMedCentralCrossRef Goldhirsch A et al (2013) Personalizing the treatment of women with early breast cancer: highlights of the St Gallen international expert consensus on the primary therapy of early breast cancer 2013. Ann Oncol 24(9):2206–2223PubMedPubMedCentralCrossRef
8.
go back to reference Coates AS et al (2015) Tailoring therapies-improving the management of early breast cancer: St Gallen international expert consensus on the primary therapy of early breast cancer 2015. Ann Oncol 26(8):1533–1546PubMedPubMedCentralCrossRef Coates AS et al (2015) Tailoring therapies-improving the management of early breast cancer: St Gallen international expert consensus on the primary therapy of early breast cancer 2015. Ann Oncol 26(8):1533–1546PubMedPubMedCentralCrossRef
9.
go back to reference Goldhirsch A et al (2011) Strategies for subtypes—dealing with the diversity of breast cancer: highlights of the St. Gallen international expert consensus on the primary therapy of early breast cancer 2011. Ann Oncol 22(8):1736–1747PubMedPubMedCentralCrossRef Goldhirsch A et al (2011) Strategies for subtypes—dealing with the diversity of breast cancer: highlights of the St. Gallen international expert consensus on the primary therapy of early breast cancer 2011. Ann Oncol 22(8):1736–1747PubMedPubMedCentralCrossRef
10.
go back to reference Yerushalmi R et al (2010) Ki67 in breast cancer: prognostic and predictive potential. Lancet Oncol 11(2):174–183PubMedCrossRef Yerushalmi R et al (2010) Ki67 in breast cancer: prognostic and predictive potential. Lancet Oncol 11(2):174–183PubMedCrossRef
11.
go back to reference Dowsett M et al (2011) Assessment of Ki67 in breast cancer: recommendations from the International Ki67 in Breast Cancer Working Group. J Natl Cancer Inst 103(22):1656–1664PubMedPubMedCentralCrossRef Dowsett M et al (2011) Assessment of Ki67 in breast cancer: recommendations from the International Ki67 in Breast Cancer Working Group. J Natl Cancer Inst 103(22):1656–1664PubMedPubMedCentralCrossRef
12.
go back to reference Lakhani SR et al (2012) WHO classification of tumours of the breast. International Agency for Research on Cancer, Lyon Lakhani SR et al (2012) WHO classification of tumours of the breast. International Agency for Research on Cancer, Lyon
13.
go back to reference Decker T, Ruhnke M, Schneider W (1997) Standardized pathologic examination of breast excision specimen. Relevance within an interdisciplinary practice protocol for quality management of breast saving therapy. Pathologe 18(1):53–59PubMedCrossRef Decker T, Ruhnke M, Schneider W (1997) Standardized pathologic examination of breast excision specimen. Relevance within an interdisciplinary practice protocol for quality management of breast saving therapy. Pathologe 18(1):53–59PubMedCrossRef
14.
go back to reference Perry N et al (2008) European guidelines for quality assurance in breast cancer screening and diagnosis. Fourth edition—summary document. Ann Oncol 19(4):614–622PubMedCrossRef Perry N et al (2008) European guidelines for quality assurance in breast cancer screening and diagnosis. Fourth edition—summary document. Ann Oncol 19(4):614–622PubMedCrossRef
15.
go back to reference Hammond ME et al (2010) American Society of Clinical Oncology/College of American Pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer (unabridged version). Arch Pathol Lab Med 134(7):e48–e72PubMed Hammond ME et al (2010) American Society of Clinical Oncology/College of American Pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer (unabridged version). Arch Pathol Lab Med 134(7):e48–e72PubMed
16.
go back to reference Wolff AC et al (2007) American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer. Arch Pathol Lab Med 131(1):18–43PubMed Wolff AC et al (2007) American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer. Arch Pathol Lab Med 131(1):18–43PubMed
17.
go back to reference Hida AI et al (2015) Visual assessment of Ki67 using a 5-grade scale (Eye-5) is easy and practical to classify breast cancer subtypes with high reproducibility. J Clin Pathol 68(5):356–361PubMedCrossRef Hida AI et al (2015) Visual assessment of Ki67 using a 5-grade scale (Eye-5) is easy and practical to classify breast cancer subtypes with high reproducibility. J Clin Pathol 68(5):356–361PubMedCrossRef
18.
go back to reference Ekholm M et al (2015) Highly reproducible results of breast cancer biomarkers when analysed in accordance with national guidelines—a Swedish survey with central re-assessment. Acta Oncol 54(7):1040–1048PubMedCrossRef Ekholm M et al (2015) Highly reproducible results of breast cancer biomarkers when analysed in accordance with national guidelines—a Swedish survey with central re-assessment. Acta Oncol 54(7):1040–1048PubMedCrossRef
19.
go back to reference van Diest PJ et al (1992) Reproducibility of mitosis counting in 2,469 breast cancer specimens: results from the Multicenter Morphometric Mammary Carcinoma Project. Hum Pathol 23(6):603–607PubMedCrossRef van Diest PJ et al (1992) Reproducibility of mitosis counting in 2,469 breast cancer specimens: results from the Multicenter Morphometric Mammary Carcinoma Project. Hum Pathol 23(6):603–607PubMedCrossRef
20.
go back to reference Baak JP et al (2008) Proliferation accurately identifies the high-risk patients among small, low-grade, lymph node-negative invasive breast cancers. Ann Oncol 19(4):649–654PubMedCrossRef Baak JP et al (2008) Proliferation accurately identifies the high-risk patients among small, low-grade, lymph node-negative invasive breast cancers. Ann Oncol 19(4):649–654PubMedCrossRef
21.
go back to reference Baak JP et al (2009) Proliferation is the strongest prognosticator in node-negative breast cancer: significance, error sources, alternatives and comparison with molecular prognostic markers. Breast Cancer Res Treat 115(2):241–254PubMedCrossRef Baak JP et al (2009) Proliferation is the strongest prognosticator in node-negative breast cancer: significance, error sources, alternatives and comparison with molecular prognostic markers. Breast Cancer Res Treat 115(2):241–254PubMedCrossRef
22.
go back to reference Cancello G et al (2013) Progesterone receptor loss identifies Luminal B breast cancer subgroups at higher risk of relapse. Ann Oncol 24(3):661–668PubMedCrossRef Cancello G et al (2013) Progesterone receptor loss identifies Luminal B breast cancer subgroups at higher risk of relapse. Ann Oncol 24(3):661–668PubMedCrossRef
23.
go back to reference Prat A et al (2013) Prognostic significance of progesterone receptor-positive tumor cells within immunohistochemically defined luminal A breast cancer. J Clin Oncol 31(2):203–209PubMedCrossRef Prat A et al (2013) Prognostic significance of progesterone receptor-positive tumor cells within immunohistochemically defined luminal A breast cancer. J Clin Oncol 31(2):203–209PubMedCrossRef
24.
go back to reference Feeley LP et al (2014) Distinguishing luminal breast cancer subtypes by Ki67, progesterone receptor or TP53 status provides prognostic information. Mod Pathol 27(4):554–561PubMedCrossRef Feeley LP et al (2014) Distinguishing luminal breast cancer subtypes by Ki67, progesterone receptor or TP53 status provides prognostic information. Mod Pathol 27(4):554–561PubMedCrossRef
25.
go back to reference Varga Z et al (2015) Standardization for Ki-67 assessment in moderately differentiated breast cancer. A retrospective analysis of the SAKK 28/12 study. PLoS One 10(4):e0123435PubMedPubMedCentralCrossRef Varga Z et al (2015) Standardization for Ki-67 assessment in moderately differentiated breast cancer. A retrospective analysis of the SAKK 28/12 study. PLoS One 10(4):e0123435PubMedPubMedCentralCrossRef
27.
go back to reference Konsti J et al (2011) Development and evaluation of a virtual microscopy application for automated assessment of Ki-67 expression in breast cancer. BMC Clin Pathol 11:3PubMedPubMedCentralCrossRef Konsti J et al (2011) Development and evaluation of a virtual microscopy application for automated assessment of Ki-67 expression in breast cancer. BMC Clin Pathol 11:3PubMedPubMedCentralCrossRef
28.
go back to reference Gudlaugsson E et al (2012) Comparison of the effect of different techniques for measurement of Ki67 proliferation on reproducibility and prognosis prediction accuracy in breast cancer. Histopathology 61(6):1134–1144PubMedCrossRef Gudlaugsson E et al (2012) Comparison of the effect of different techniques for measurement of Ki67 proliferation on reproducibility and prognosis prediction accuracy in breast cancer. Histopathology 61(6):1134–1144PubMedCrossRef
29.
go back to reference Fasanella S et al (2011) Proliferative activity in human breast cancer: Ki-67 automated evaluation and the influence of different Ki-67 equivalent antibodies. Diagn Pathol 6(Suppl 1):S7PubMedPubMedCentralCrossRef Fasanella S et al (2011) Proliferative activity in human breast cancer: Ki-67 automated evaluation and the influence of different Ki-67 equivalent antibodies. Diagn Pathol 6(Suppl 1):S7PubMedPubMedCentralCrossRef
30.
go back to reference Klauschen F et al (2015) Standardized Ki67 diagnostics using automated scoring—clinical validation in the GeparTrio breast cancer study. Clin Cancer Res 21(16):3651–3657PubMedCrossRef Klauschen F et al (2015) Standardized Ki67 diagnostics using automated scoring—clinical validation in the GeparTrio breast cancer study. Clin Cancer Res 21(16):3651–3657PubMedCrossRef
32.
go back to reference Christgen M et al (2015) The region-of-interest size impacts on Ki67 quantification by computer-assisted image analysis in breast cancer. Hum Pathol 46(9):1341–1349PubMedCrossRef Christgen M et al (2015) The region-of-interest size impacts on Ki67 quantification by computer-assisted image analysis in breast cancer. Hum Pathol 46(9):1341–1349PubMedCrossRef
33.
go back to reference Guiu S et al (2012) Molecular subclasses of breast cancer: how do we define them? The IMPAKT 2012 Working Group Statement. Ann Oncol 23(12):2997–3006PubMedCrossRef Guiu S et al (2012) Molecular subclasses of breast cancer: how do we define them? The IMPAKT 2012 Working Group Statement. Ann Oncol 23(12):2997–3006PubMedCrossRef
34.
go back to reference Maisonneuve P et al (2014) Proposed new clinicopathological surrogate definitions of luminal A and luminal B (HER2-negative) intrinsic breast cancer subtypes. Breast Cancer Res 16(3):R65PubMedPubMedCentralCrossRef Maisonneuve P et al (2014) Proposed new clinicopathological surrogate definitions of luminal A and luminal B (HER2-negative) intrinsic breast cancer subtypes. Breast Cancer Res 16(3):R65PubMedPubMedCentralCrossRef
35.
go back to reference Geyer FC et al (2012) Molecular classification of estrogen receptor-positive/luminal breast cancers. Adv Anat Pathol 19(1):39–53PubMedCrossRef Geyer FC et al (2012) Molecular classification of estrogen receptor-positive/luminal breast cancers. Adv Anat Pathol 19(1):39–53PubMedCrossRef
36.
go back to reference Denkert C et al (2015) Strategies for developing Ki67 as a useful biomarker in breast cancer. Breast 24:S67–S72PubMedCrossRef Denkert C et al (2015) Strategies for developing Ki67 as a useful biomarker in breast cancer. Breast 24:S67–S72PubMedCrossRef
37.
go back to reference Luporsi E et al (2012) Ki-67: level of evidence and methodological considerations for its role in the clinical management of breast cancer: analytical and critical review. Breast Cancer Res Treat 132(3):895–915PubMedCrossRef Luporsi E et al (2012) Ki-67: level of evidence and methodological considerations for its role in the clinical management of breast cancer: analytical and critical review. Breast Cancer Res Treat 132(3):895–915PubMedCrossRef
Metadata
Title
St Gallen 2015 subtyping of luminal breast cancers: impact of different Ki67-based proliferation assessment methods
Authors
Cornelia M. Focke
Paul J. van Diest
Thomas Decker
Publication date
01-09-2016
Publisher
Springer US
Published in
Breast Cancer Research and Treatment / Issue 2/2016
Print ISSN: 0167-6806
Electronic ISSN: 1573-7217
DOI
https://doi.org/10.1007/s10549-016-3950-5

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