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 Bertucci; Francesco Ricci; Armando Orlandi; Gianluca Franceschini; Kazuaki Takabe; Suzanne Klimberg; Naohiro Ishii; Angela Toss; Mona P. Tan; Mathew A. Cherian; Erwei Song

doi:10.1007/s11427-022-2104-3

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

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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 (K^trans). 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 language	English (US)
Pages (from-to)	2205-2217
Number of pages	13
Journal	Science China Life Sciences
Volume	65
Issue number	11
DOIs	https://doi.org/10.1007/s11427-022-2104-3
State	Published - Nov 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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/s11427-022-2104-3

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Gong, C., Cheng, Z., Yang, Y., Shen, J., Zhu, Y., Ling, L., Lin, W., Yu, Z., Li, Z., Tan, W., Zheng, C., Zheng, W., Zhong, J., Zhang, X., Zeng, Y., Liu, Q., Huang, R. S., Komorowski, A. L., Yang, E. S., ... Song, E. (2022). A 10-miRNA risk score-based prediction model for pathological complete response to neoadjuvant chemotherapy in hormone receptor-positive breast cancer. Science China Life Sciences, 65(11), 2205-2217. https://doi.org/10.1007/s11427-022-2104-3

Gong, C, Cheng, Z, Yang, Y, Shen, J, Zhu, Y, Ling, L, Lin, W, Yu, Z, Li, Z, Tan, W, Zheng, C, Zheng, W, Zhong, J, Zhang, X, Zeng, Y, Liu, Q, Huang, RS, Komorowski, AL, Yang, ES, Bertucci, F, Ricci, F, Orlandi, A, Franceschini, G, Takabe, K, Klimberg, S, Ishii, N, Toss, A, Tan, MP, Cherian, MA & Song, E 2022, 'A 10-miRNA risk score-based prediction model for pathological complete response to neoadjuvant chemotherapy in hormone receptor-positive breast cancer', Science China Life Sciences, vol. 65, no. 11, pp. 2205-2217. https://doi.org/10.1007/s11427-022-2104-3

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

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.",

keywords = "dynamic contrast-enhanced magnetic resonance imaging, hormone receptor-positive breast cancer, microRNA signature, neoadjuvant chemotherapy, nomogram",

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

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: {\textcopyright} 2022, Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature.",

year = "2022",

month = nov,

doi = "10.1007/s11427-022-2104-3",

language = "English (US)",

volume = "65",

pages = "2205--2217",

journal = "Science China Life Sciences",

issn = "1674-7305",

publisher = "Science in China Press",

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TY - JOUR

T1 - A 10-miRNA risk score-based prediction model for pathological complete response to neoadjuvant chemotherapy in hormone receptor-positive breast cancer

AU - Gong, Chang

AU - Cheng, Ziliang

AU - Yang, Yaping

AU - Shen, Jun

AU - Zhu, Yingying

AU - Ling, Li

AU - Lin, Wanyi

AU - Yu, Zhigang

AU - Li, Zhihua

AU - Tan, Weige

AU - Zheng, Chushan

AU - Zheng, Wenbo

AU - Zhong, Jiajie

AU - Zhang, Xiang

AU - Zeng, Yunjie

AU - Liu, Qiang

AU - Huang, R. Stephanie

AU - Komorowski, Andrzej L.

AU - Yang, Eddy S.

AU - Bertucci, François

AU - Ricci, Francesco

AU - Orlandi, Armando

AU - Franceschini, Gianluca

AU - Takabe, Kazuaki

AU - Klimberg, Suzanne

AU - Ishii, Naohiro

AU - Toss, Angela

AU - Tan, Mona P.

AU - Cherian, Mathew A.

AU - Song, Erwei

N1 - 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.

PY - 2022/11

Y1 - 2022/11

N2 - 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.

AB - 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.

KW - dynamic contrast-enhanced magnetic resonance imaging

KW - hormone receptor-positive breast cancer

KW - microRNA signature

KW - neoadjuvant chemotherapy

KW - nomogram

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

Abstract

Bibliographical note

Keywords

UN SDGs

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