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Breast Cancer Research and Treatment
Published in: Breast Cancer Research and Treatment 2/2017

01-11-2017 | Epidemiology

Assessment of Ki67 expression for breast cancer subtype classification and prognosis in the Nurses’ Health Study

Authors: Megan A. Healey, Kelly A. Hirko, Andrew H. Beck, Laura C. Collins, Stuart J. Schnitt, A. Heather Eliassen, Michelle D. Holmes, Rulla M. Tamimi, Aditi Hazra

Published in: Breast Cancer Research and Treatment | Issue 2/2017

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Abstract

Purpose

Ki67 is a proliferation marker commonly assessed by immunohistochemistry in breast cancer, and it has been proposed as a clinical marker for subtype classification, prognosis, and prediction of therapeutic response. However, the clinical utility of Ki67 is limited by the lack of consensus on the optimal cut point for each application.

Methods

We assessed Ki67 by immunohistochemistry using Definiens digital image analysis (DIA) in 2653 cases of incident invasive breast cancer diagnosed in the Nurses’ Health Study from 1976 to 2006. Ki67 was scored as continuous percentage of positive tumor cells, and dichotomized at various cut points. Multivariable hazard ratios (HR) and 95% confidence intervals (CI) were calculated using Cox regression models for distant recurrence, breast cancer-specific mortality and overall mortality in relation to luminal subtypes defined with various Ki67 cut points, adjusting for breast cancer prognostic factors, clinico-pathologic features and treatment.

Results

DIA was highly correlated with manual scoring of Ki67 (Spearman correlation ρ = 0.86). Mean Ki67 score was higher in grade-defined luminal B (12.6%), HER2-enriched (17.9%) and basal-like (20.6%) subtypes compared to luminal A (8.9%). In multivariable-adjusted models, luminal B tumors had higher breast cancer-specific mortality compared to luminal A cancer classified using various cut points for Ki67 positivity including the 14% cut point routinely reported in the literature (HR 1.38, 95% CI 1.11–1.72, p = 0.004). There was no significant difference in clinical outcomes for ER− tumors according to Ki67 positivity defined at various cut points.

Conclusions

Assessment of Ki67 in breast tumors by DIA was a robust and quantitative method. Results from this large prospective cohort study provide support for the clinical relevance of using Ki67 at the 14% cut point for luminal subtype classification and breast cancer prognosis.
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Literature
1.
Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H et al (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA 98(19):10869–10874CrossRefPubMedPubMedCentral
2.
Sotiriou C, Neo SY, McShane LM, Korn EL, Long PM, Jazaeri A et al (2003) Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci USA 100(18):10393–10398CrossRefPubMedPubMedCentral
3.
Kao KJ, Chang KM, Hsu HC, Huang AT (2011) Correlation of microarray-based breast cancer molecular subtypes and clinical outcomes: implications for treatment optimization. BMC Cancer 11(143):1471–2407
4.
Prat A, Lluch A, Albanell J, Barry WT, Fan C, Chacon JI et al (2014) Predicting response and survival in chemotherapy-treated triple-negative breast cancer. Br J Cancer 111(8):1532–1541CrossRefPubMedPubMedCentral
5.
Cancer Genome Atlas Network (2012) Comprehensive molecular portraits of human breast tumours. Nature 490(7418):61–70CrossRef
6.
Nielsen TO, Hsu FD, Jensen K, Cheang M, Karaca G, Hu Z et al (2004) Immunohistochemical and clinical characterization of the basal-like subtype of invasive breast carcinoma. Clin Cancer Res 10(16):5367–5374CrossRefPubMed
7.
Onitilo AA, Engel JM, Greenlee RT, Mukesh BN (2009) Breast cancer subtypes based on ER/PR and Her2 expression: comparison of clinicopathologic features and survival. Clin Med Res 7(1–2):4–13CrossRefPubMedPubMedCentral
8.
Goldhirsch A, Winer EP, Coates AS, Gelber RD, Piccart-Gebhart M, Thurlimann B 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):2206–2223CrossRefPubMedPubMedCentral
9.
Coates AS, Winer EP, Goldhirsch A, Gelber RD, Gnant M, Piccart-Gebhart M 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):1533–1546CrossRefPubMedPubMedCentral
10.
Cheang MC, Chia SK, Voduc D, Gao D, Leung S, Snider J et al (2009) Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. J Natl Cancer Inst 101(10):736–750CrossRefPubMedPubMedCentral
11.
Carey LA, Perou CM, Livasy CA, Dressler LG, Cowan D, Conway K et al (2006) Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA 295(21):2492–2502CrossRefPubMed
12.
Elston CW, Ellis IO (1991) Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. Histopathology 19(5):403–410CrossRefPubMed
13.
Simpson JF, Gray R, Dressler LG, Cobau CD, Falkson CI, Gilchrist KW et al (2000) Prognostic value of histologic grade and proliferative activity in axillary node-positive breast cancer: results from the Eastern Cooperative Oncology Group Companion Study, EST 4189. J Clin Oncol 18(10):2059–2069CrossRefPubMed
14.
Sotiriou C, Wirapati P, Loi S, Harris A, Fox S, Smeds J et al (2006) Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst 98(4):262–272CrossRefPubMed
15.
Schonk DM, Kuijpers HJ, van Drunen E, van Dalen CH, Geurts van Kessel AH, Verheijen R et al (1989) Assignment of the gene(s) involved in the expression of the proliferation-related Ki-67 antigen to human chromosome 10. Hum Genet 83(3):297–299CrossRefPubMed
16.
Bullwinkel J, Baron-Luhr B, Ludemann A, Wohlenberg C, Gerdes J, Scholzen T (2006) Ki-67 protein is associated with ribosomal RNA transcription in quiescent and proliferating cells. J Cell Physiol 206(3):624–635CrossRefPubMed
17.
Urruticoechea A, Smith IE, Dowsett M (2005) Proliferation marker Ki-67 in early breast cancer. J Clin Oncol 23(28):7212–7220CrossRefPubMed
18.
Dowsett M, Nielsen TO, A’Hern R, Bartlett J, Coombes RC, Cuzick J 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):1656–1664CrossRefPubMedPubMedCentral
19.
Polley MY, Leung SC, McShane LM, Gao D, Hugh JC, Mastropasqua MG et al (2013) An international Ki67 reproducibility study. J Natl Cancer Inst 105(24):1897–1906CrossRefPubMedPubMedCentral
20.
Zhang X, Giovannucci EL, Wu K, Smith-Warner SA, Fuchs CS, Pollak M et al (2012) Magnesium intake, plasma C-peptide, and colorectal cancer incidence in US women: a 28-year follow-up study. Br J Cancer 106(7):1335–1341CrossRefPubMedPubMedCentral
21.
Tamimi RM, Baer HJ, Marotti J, Galan M, Galaburda L, Fu Y et al (2008) Comparison of molecular phenotypes of ductal carcinoma in situ and invasive breast cancer. Breast Cancer Res 10(4):R67CrossRefPubMedPubMedCentral
22.
Healey MA, Hu R, Beck AH, Collins LC, Schnitt SJ, Tamimi RM et al (2014) Association of H3K9me3 and H3K27me3 repressive histone marks with breast cancer subtypes in the Nurses’ Health Study. Breast Cancer Res Treat 147(3):639–651CrossRefPubMed
23.
Collins LC, Cole KS, Marotti JD, Hu R, Schnitt SJ, Tamimi RM (2011) Androgen receptor expression in breast cancer in relation to molecular phenotype: results from the Nurses’ Health Study. Mod Pathol 24(7):924–931CrossRefPubMedPubMedCentral
24.
Zabaglo L, Salter J, Anderson H, Quinn E, Hills M, Detre S et al (2010) Comparative validation of the SP6 antibody to Ki67 in breast cancer. J Clin Pathol 63(9):800–804CrossRefPubMed
25.
Holmes MD, Chen WY, Feskanich D, Kroenke CH, Colditz GA (2005) Physical activity and survival after breast cancer diagnosis. JAMA 293(20):2479–2486CrossRefPubMed
26.
Colditz GA, Rosner B (2000) Cumulative risk of breast cancer to age 70 years according to risk factor status: data from the Nurses’ Health Study. Am J Epidemiol 152(10):950–964CrossRefPubMed
27.
Kroenke CH, Chen WY, Rosner B, Holmes MD (2005) Weight, weight gain, and survival after breast cancer diagnosis. J Clin Oncol 23(7):1370–1378CrossRefPubMed
28.
Voduc KD, Cheang MC, Tyldesley S, Gelmon K, Nielsen TO, Kennecke H (2010) Breast cancer subtypes and the risk of local and regional relapse. J Clin Oncol 28(10):1684–1691CrossRefPubMed
29.
Engstrom MJ, Opdahl S, Hagen AI, Romundstad PR, Akslen LA, Haugen OA et al (2013) Molecular subtypes, histopathological grade and survival in a historic cohort of breast cancer patients. Breast Cancer Res Treat 140(3):463–473CrossRefPubMedPubMedCentral
30.
Parise CA, Caggiano V (2014) Breast cancer survival defined by the ER/PR/HER2 subtypes and a surrogate classification according to tumor grade and immunohistochemical biomarkers. J Cancer Epidemiol 2014:469251CrossRefPubMedPubMedCentral
31.
Yanagawa M, Ikemot K, Kawauchi S, Furuya T, Yamamoto S, Oka M et al (2012) Luminal A and luminal B (HER2 negative) subtypes of breast cancer consist of a mixture of tumors with different genotype. BMC Res Notes 5:376CrossRefPubMedPubMedCentral
32.
Williams DJ, Cohen C, Darrow M, Page AJ, Chastain B, Adams AL (2011) Proliferation (Ki-67 and phosphohistone H3) and oncotype DX recurrence score in estrogen receptor-positive breast cancer. Appl Immunohistochem Mol Morphol 19(5):431–436CrossRefPubMed
33.
Keam B, Im SA, Lee KH, Han SW, Oh DY, Kim JH et al (2011) Ki-67 can be used for further classification of triple negative breast cancer into two subtypes with different response and prognosis. Breast Cancer Res 13(2):R22CrossRefPubMedPubMedCentral
34.
Huang L, Liu Z, Chen S, Liu Y, Shao Z (2013) A prognostic model for triple-negative breast cancer patients based on node status, cathepsin-D and Ki-67 index. PLoS One 8(12):e83081CrossRefPubMedPubMedCentral
35.
Abubakar M, Orr N, Daley F, Coulson P, Ali HR, Blows F et al (2016) Prognostic value of automated KI67 scoring in breast cancer: a centralised evaluation of 8088 patients from 10 study groups. Breast Cancer Res 18(1):104CrossRefPubMedPubMedCentral
36.
Bustreo S, Osella-Abate S, Cassoni P, Donadio M, Airoldi M, Pedani F et al (2016) Optimal Ki67 cut-off for luminal breast cancer prognostic evaluation: a large case series study with a long-term follow-up. Breast Cancer Res Treat 157(2):363–371CrossRefPubMedPubMedCentral
37.
Huh SJ, Oh H, Peterson MA, Almendro V, Hu R, Bowden M et al (2016) The proliferative activity of mammary epithelial cells in normal tissue predicts breast cancer risk in premenopausal women. Cancer Res 76(7):1926–1934CrossRefPubMedPubMedCentral
38.
Maisonneuve P, Disalvatore D, Rotmensz N, Curigliano G, Colleoni M, Dellapasqua S 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):R65CrossRefPubMedPubMedCentral
Metadata
Title
Assessment of Ki67 expression for breast cancer subtype classification and prognosis in the Nurses’ Health Study
Authors
Megan A. Healey
Kelly A. Hirko
Andrew H. Beck
Laura C. Collins
Stuart J. Schnitt
A. Heather Eliassen
Michelle D. Holmes
Rulla M. Tamimi
Aditi Hazra
Publication date
01-11-2017
Publisher
Springer US
Published in
Breast Cancer Research and Treatment / Issue 2/2017
Print ISSN: 0167-6806
Electronic ISSN: 1573-7217
DOI
https://doi.org/10.1007/s10549-017-4421-3

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