Oncotarget

Research Papers:

Using computer assisted image analysis to determine the optimal Ki67 threshold for predicting outcome of invasive breast cancer

Timothy Kwang Yong Tay, Aye Aye Thike, Nirmala Pathmanathan, Ana Richelia Jara-Lazaro, Jabed Iqbal, Adeline Shi Hui Sng, Heng Seow Ye, Jeffrey Chun Tatt Lim, Valerie Cui Yun Koh, Jane Sie Yong Tan, Joe Poh Sheng Yeong, Zi Long Chow, Hui Hua Li, Chee Leong Cheng and Puay Hoon Tan _

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Oncotarget. 2018; 9:11619-11630. https://doi.org/10.18632/oncotarget.24398

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Abstract

Timothy Kwang Yong Tay1, Aye Aye Thike1, Nirmala Pathmanathan1,2, Ana Richelia Jara-Lazaro1,3, Jabed Iqbal1, Adeline Shi Hui Sng1, Heng Seow Ye1, Jeffrey Chun Tatt Lim1, Valerie Cui Yun Koh1, Jane Sie Yong Tan1, Joe Poh Sheng Yeong1, Zi Long Chow1, Hui Hua Li4, Chee Leong Cheng1 and Puay Hoon Tan5

1Department of Anatomical Pathology, Singapore General Hospital, Singapore

2Current affiliation: Westmead Breast Cancer Institute, Westmead Hospital, Westmead, NSW, Australia

3Current affiliation: Q2 Solutions – Central Laboratories, Singapore Science Park One, Singapore

4Division of Medicine, Singapore General Hospital, Singapore

5Division of Pathology, Singapore General Hospital, Singapore

Correspondence to:

Puay Hoon Tan, email: tan.puay.hoon@singhealth.com.sg

Keywords: Ki67; breast cancer; computer assisted image analysis; prognosis

Received: October 10, 2017     Accepted: January 25, 2018     Published: February 05, 2018

ABSTRACT

Background: Ki67 positivity in invasive breast cancers has an inverse correlation with survival outcomes and serves as an immunohistochemical surrogate for molecular subtyping of breast cancer, particularly ER positive breast cancer. The optimal threshold of Ki67 in both settings, however, remains elusive. We use computer assisted image analysis (CAIA) to determine the optimal threshold for Ki67 in predicting survival outcomes and differentiating luminal B from luminal A breast cancers.

Methods: Quantitative scoring of Ki67 on tissue microarray (TMA) sections of 440 invasive breast cancers was performed using Aperio ePathology ImmunoHistochemistry Nuclear Image Analysis algorithm, with TMA slides digitally scanned via Aperio ScanScope XT System.

Results: On multivariate analysis, tumours with Ki67 ≥14% had an increased likelihood of recurrence (HR 1.941, p=0.021) and shorter overall survival (HR 2.201, p=0.016). Similar findings were observed in the subset of 343 ER positive breast cancers (HR 2.409, p=0.012 and HR 2.787, p=0.012 respectively). The value of Ki67 associated with ER+HER2-PR<20% tumours (Luminal B subtype) was found to be <17%.

Conclusion: Using CAIA, we found optimal thresholds for Ki67 that predict a poorer prognosis and an association with the Luminal B subtype of breast cancer. Further investigation and validation of these thresholds are recommended.


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