Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2012 Jan 6;14(1):R3.
doi: 10.1186/bcr3084.

Prognostic value of proliferation assay in the luminal, HER2-positive, and triple-negative biologic classes of breast cancer

Mohammed A Aleskandarany  1 , Andrew R Green, Ahmed A Benhasouna, Fabricio F Barros, Keith Neal, Jorge S Reis-Filho, Ian O Ellis, Emad A Rakha
Affiliations

Prognostic value of proliferation assay in the luminal, HER2-positive, and triple-negative biologic classes of breast cancer

Mohammed A Aleskandarany et al. Breast Cancer Res. .

Abstract

Introduction: Although the prognostic significance of proliferation in early invasive breast cancer has been recognized for a long time, recent gene-expression profiling studies have reemphasized its biologic and prognostic value and the potential application of its assessment in routine practice, particularly to define prognostic subgroups of luminal/hormone receptor-positive (HR+) tumors. This study aimed to assess the prognostic value of a proliferation assay by using Ki-67 immunohistochemistry as compared with mitotic count scores.

Method: Proliferation was assessed by using Ki-67 labeling index (Ki-67LI) and mitotic scores in a large (n = 1,550) and well-characterized series of clinically annotated primary operable invasive breast cancer with long-term follow-up. Tumors were phenotyped based on their IHC profiles into luminal/HR+, HER2+, and triple-negative (TN) classes. We used a split-sample development and validation approach to determine the optimal Ki-67LI cut-offs.

Results: The optimal cut-points of Ki-67LI were 10% and 50% for the luminal class. Both Ki7LI and MS were able to split luminal tumors into subgroups with significantly variable outcomes, independent of other variables. Neither mitotic count scores nor Ki-67LI was associated with outcome in the HER2+ or the TN classes.

Conclusions: Assessment of proliferation by using Ki-67LI and MS can distinguish subgroups of patients within luminal/hormone receptor-positive breast cancer significantly different in clinical outcomes. Overall, both Ki-67 LI and mitotic-count scores showed comparable results. The method described could provide a cost-effective method for prognostic subclassification of luminal/hormone receptor-positive breast cancer in routine clinical practice.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Box plot of Ki-67LI in different BC molecular classes, and their corresponding levels of significance in post hoc analysis.
Figure 2
Figure 2
Association between BCSS and Ki-67LI expressed in 10% increments (10% each.) However, tumors showing 50% to 69% and 80% to 100% Ki-67LI were considered as two groups, as the number in each 10% subgroup was small). Labels 1 through 8 represent patients' subsets based on tumor Ki-67LI, where 1 is 0 to 9%; 2 is 10% to 19%; 3 is 20% to 29%; 4 is 30% to 39%; 5 is 40% to 49%; 6 is 50% to 69%; 7 is 70% to 79%; and 8 is 80% to 100%.
Figure 3
Figure 3
Kaplan-Meier survival plot for luminal BC training set using Ki-67LI and MS. (a) Breast cancer-specific survival (BCSS). (b) Metastasis-free survival at 10% and 50% Ki-67LI cut-off point. (c, d) BCSS and DMFS for mitosis-frequency scores.
Figure 4
Figure 4
Kaplan-Meier survival plot for luminal BC validation set using Ki-67LI and MS. (a) Breast cancer-specific survival (BCSS) and (b) metastasis-free survival at 10% and 50% Ki-67LI cut-off point. (c, d) BCSS and DMFS for mitosis frequency scores (by using the validation set only).
Figure 5
Figure 5
Kaplan-Meier survival plot of luminal tumors showing association between HER2 status and proliferation. (Ki-67LI, a, and MS, b) and BCSS (LR = 88; P < 0.0001; HR, 1.683; 95% CI, 1.492 to 1.898, and LR, 90.239; P < 0.0001; HR, 1.749; 95% CI, 1. 543 to 1.982, respectively; validation set only). Number of patients at risk is shown above the curves.
See this image and copyright information in PMC

References

    1. Daidone MG, Silvestrini R. Prognostic and predictive role of proliferation indices in adjuvant therapy of breast cancer. J Natl Cancer Inst Monogr. 2001;30:27–35. - PubMed
    1. Wirapati P, Sotiriou C, Kunkel S, Farmer P, Pradervand S, Haibe-Kains B, Desmedt C, Ignatiadis M, Sengstag T, Schütz F, Goldstein DR, Piccart M, Delorenzi M. Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Res. 2008;10:R65. doi: 10.1186/bcr2124. - DOI - PMC - PubMed
    1. Weigelt B, Baehner FL, Reis-Filho JS. The contribution of gene expression profiling to breast cancer classification, prognostication and prediction: a retrospective of the last decade. J Pathol. 2010;220:263–80. - PubMed
    1. Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M, Baehner FL, Walker MG, Watson D, Park T, Hiller W, Fisher ER, Wickerham DL, Bryant J, Wolmark N. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med. 2004;351:2817–26. doi: 10.1056/NEJMoa041588. - DOI - PubMed
    1. Sotiriou C, Wirapati P, Loi S, Harris A, Fox S, Smeds J, Nordgren H, Farmer P, Praz V, Haibe-Kains B, Desmedt C, Larsimont D, Cardoso F, Peterse H, Nuyten D, Buyse M, Van de Vijver MJ, Bergh J, Piccart M, Delorenzi M. Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst. 2006;98:262–72. doi: 10.1093/jnci/djj052. - DOI - PubMed

Publication types

MeSH terms