A 10-miRNA risk score-based prediction model for pathological complete response to neoadjuvant chemotherapy in hormone receptor-positive breast cancer

Chang Gong, Ziliang Cheng, Yaping Yang, Jun Shen, Yingying Zhu, Li Ling, Wanyi Lin, Zhigang Yu, Zhihua Li, Weige Tan, Chushan Zheng, Wenbo Zheng, Jiajie Zhong, Xiang Zhang, Yunjie Zeng, Qiang Liu, R. Stephanie Huang, Andrzej L. Komorowski, Eddy S. Yang, François BertucciFrancesco Ricci, Armando Orlandi, Gianluca Franceschini, Kazuaki Takabe, Suzanne Klimberg, Naohiro Ishii, Angela Toss, Mona P. Tan, Mathew A. Cherian, Erwei Song

Research output: Contribution to journalArticlepeer-review

Abstract

Patients with hormone receptor (HR)-positive tumors breast cancer usually experience a relatively low pathological complete response (pCR) to neoadjuvant chemotherapy (NAC). Here, we derived a 10-microRNA risk score (10-miRNA RS)-based model with better performance in the prediction of pCR and validated its relation with the disease-free survival (DFS) in 755 HR-positive breast cancer patients (273, 265, and 217 in the training, internal, and external validation sets, respectively). This model, presented as a nomogram, included four parameters: the 10-miRNA RS found in our previous study, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) status, and volume transfer constant (Ktrans). Favorable calibration and discrimination of 10-miRNA RS-based model with areas under the curve (AUC) of 0.865, 0.811, and 0.804 were shown in the training, internal, and external validation sets, respectively. Patients who have higher nomogram score (>92.2) with NAC treatment would have longer DFS (hazard ratio=0.57; 95%CI: 0.39–0.83; P=0.004). In summary, our data showed the 10-miRNA RS-based model could precisely identify more patients who can attain pCR to NAC, which may help clinicians formulate the personalized initial treatment strategy and consequently achieves better clinical prognosis for patients with HR-positive breast cancer.

Original languageEnglish (US)
JournalScience China Life Sciences
DOIs
StateAccepted/In press - 2022

Bibliographical note

Funding Information:
This work was supported by the National Natural Science Foundation of China (92159303, 81621004, 81720108029, 81930081, 91940305, 81672594, 81772836, 81872139, 82072907, and 82003311), Guangdong Science and Technology Department (2020B1212060018 and 2020B1212030004), Clinical Innovation Research Program of Bioland Laboratory (2018GZR0201004), Bureau of Science and Technology of Guangzhou (20212200003), Program for Guangdong Introducing Innovative and Enterpreneurial Teams (2019BT02Y198), the Project of The Beijing Xisike Clinical Oncology Research Foundation (Y-Roche2019/2-0078), the Technology Development Program of Guangdong province (2021A0505030082), the Project of The Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation (2020B1212060018), Sun Yat-Sen Memorial Hospital Cultivation Project for Clinical Research (SYS-C-201805 and SYS-Q-202004), Guangzhou Science and Technology Program (202102010272), and Medical Science and Technology Research Fund of Guangdong Province (A2020391). The authors appreciate the academic support from the AME Breast Cancer Collaborative Group and Claire Verschraegen for her critical review of the manuscript.

Publisher Copyright:
© 2022, Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature.

Keywords

  • dynamic contrast-enhanced magnetic resonance imaging
  • hormone receptor-positive breast cancer
  • microRNA signature
  • neoadjuvant chemotherapy
  • nomogram

PubMed: MeSH publication types

  • Journal Article

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