A 10-miRNA risk score-based prediction model for pathological complete response to neoadjuvant chemotherapy in hormone receptor-positive breast cancer
| Autor: | 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 |
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| Přispěvatelé: | ESCP-EAP (ESCP-EAP), Ecole Supérieure de Commerce de Paris, Baylor College of Medicine (BCM), Baylor University, Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138)), École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité), Métabolisme et physiologie rénales (ERL 8228), Centre de Recherche des Cordeliers (CRC), Université Pierre et Marie Curie - Paris 6 (UPMC)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), College of Information and Technology Science [Jilin], Jilin Agricultural University (JAU), Sun Yat-Sen University [Guangzhou] (SYSU), University of Manchester [Manchester], Centre de Recherche en Cancérologie de Marseille (CRCM), Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut Curie [Paris] |
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
microRNA signature
Settore MED/08 - ANATOMIA PATOLOGICA hormone receptor-positive breast cancer [SDV]Life Sciences [q-bio] Settore MED/18 - CHIRURGIA GENERALE dynamic contrast-enhanced magnetic resonance imaging neoadjuvant chemotherapy nomogram Breast Neoplasms General Biochemistry Genetics and Molecular Biology Neoadjuvant Therapy MicroRNAs Risk Factors Antineoplastic Combined Chemotherapy Protocols Humans Female General Agricultural and Biological Sciences General Environmental Science |
| Zdroj: | SCIENCE CHINA-LIFE SCIENCES SCIENCE CHINA-LIFE SCIENCES, 2022, 65 (11), pp.2205-2217. ⟨10.1007/s11427-022-2104-3⟩ |
| DOI: | 10.1007/s11427-022-2104-3⟩ |
| Popis: | International audience; 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. |
| Databáze: | OpenAIRE |
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