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Quantitative digital imaging analysis of HER2 immunohistochemistry predicts the response to anti-HER2 neoadjuvant chemotherapy in HER2-positive breast carcinoma

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Abstract

Purpose

Patients with HER2-positive breast cancer commonly receive anti-HER2 neoadjuvant chemotherapy and pathologic complete response (pCR) can be achieved in up to half of the patients. HER2 protein expression detected by immunohistochemistry (IHC) can be quantified using digital imaging analysis (DIA) as a value of membranous connectivity. We aimed to investigate the association HER2 IHC DIA quantitative results with response to anti-HER2 neoadjuvant chemotherapy.

Methods

Digitized HER2 IHC whole slide images were analyzed using Visiopharm HER2-CONNECT to obtain quantitative HER2 membranous connectivity from a cohort of 153 HER2+ invasive breast carcinoma cases treated with anti-HER2 neoadjuvant chemotherapy (NAC). HER2 connectivity and other factors including age, histologic grade, ER, PR, and HER2 fluorescence in situ hybridization (FISH) were analyzed for association with the response to anti-HER2 NAC.

Results

Eighty-three cases (54.2%) had pCR, while 70 (45.8%) showed residual tumor. Younger age, negative ER/PR, higher HER2 DIA connectivity, higher HER2 FISH ratio and copy number were significantly associated with pCR in univariate analysis. Multivariate analysis demonstrated only age, HER2 DIA connectivity, PR negativity, and HER2 copy number was significantly associated with pCR, whereas HER2 DIA connectivity had the strongest association.

Conclusions

HER2 IHC DIA connectivity is the most important factor predicting pCR to anti-HER2 neoadjuvant chemotherapy in patients with HER2-positive breast cancer.

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Authors and Affiliations

  1. Dublin Jerome High School, Dublin, OH, USA

    Aidan C. Li

  2. Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China

    Jing Zhao

  3. Center for Biostatistics, Emory University, Atlanta, GA, USA

    Chao Zhao

  4. Department of Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China

    Zhongliang Ma

  5. Department of Pathology, The Ohio State University, Columbus, OH, USA

    Ramon Hartage & Anil V. Parwani

  6. Department of Pathology, Weifang People’s Hospital, Weifang, China

    Yunxiang Zhang

  7. Department of Pathology, Emory University, Atlanta, GA, USA

    Xiaoxian Li

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  1. Aidan C. Li
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  2. Jing Zhao
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  3. Chao Zhao
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  4. Zhongliang Ma
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  5. Ramon Hartage
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  6. Yunxiang Zhang
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  7. Xiaoxian Li
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  8. Anil V. Parwani
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Contributions

Study design: All. Data collection: All. Data analysis: CZ, XL, AVP. Statistical oversight: CZ. Manuscript preparation: ACL, XL, AVP. Manuscript approval: All.

Corresponding authors

Correspondence to Xiaoxian Li or Anil V. Parwani.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Informed consent was obtained from all individual patients included in the study.

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Li, A.C., Zhao, J., Zhao, C. et al. Quantitative digital imaging analysis of HER2 immunohistochemistry predicts the response to anti-HER2 neoadjuvant chemotherapy in HER2-positive breast carcinoma. Breast Cancer Res Treat 180, 321–329 (2020). https://doi.org/10.1007/s10549-020-05546-0

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