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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

引用

Science China(Life Sciences) 2022年第11期65卷 2205-2217页

作者： 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 RStephanie Huang Andrzej LKomorowski Eddy SYang François Bertucci Francesco Ricci Armando Orlandi Gianluca Franceschini Kazuaki Takabe Suzanne Klimberg Naohiro Ishii Angela Toss Mona PTan Mathew A Cherian Erwei Song Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation Guangdong-Hong Kong Joint Laboratory for RNA MedicineBreast Tumor CenterSun Yat-sen Memorial HospitalSun Yat-sen UniversityGuangzhou 510120China Department of Radiology Sun Yat-sen Memorial HospitalSun Yat-sen UniversityGuangzhou 510120China Clinical Research Design Division Clinical Research CenterSun Yat-sen Memorial HospitalSun Yat-sen UniversityGuangzhou 510120China Department of Medical Statistics School of Public HealthSun Yat-sen UniversityGuangzhou 510080China Department of Breast Surgery the Second Affiliated HospitalShandong UniversityJinan 250033China Department of Breast Surgery Key Laboratory of Breast DiseasesThird Hospital of NanchangNanchang 330009China Department of Breast Surgery the First Affiliated HospitalGuangzhou Medical UniversityGuangzhou 510120China Department of Pathology Sun Yat-sen Memorial HospitalSun Yat-sen UniversityGuangzhou 510120China Department of Experimental and Clinical Pharmacology University of MinnesotaMinneapolisMN 55455USA Department of Surgery College of MedicineUniversity of RzeszówRzeszów 35-959Poland Department of Radiation Oncology O’Neal Comprehensive Cancer CenterUniversity of Alabama at Birmingham School of MedicineBirminghamALUSA Laboratoty of Predictive Oncology Institut Paoli-CalmettesCentre de Recherche en Cancérologie de MarseilleINSERM UMR1068CNRS UMR725MarseilleFrance Department of Drug Development and Innovation(D3i) Institut CurieParis 75005France Comprehensive Cancer Center UOC di Oncologia MedicaFondazione Policlinico Universitario A.Gemelli IRCCSRome 00168Italy Multidisciplinary Breast Unit Fondazione Policlinico Universitario Agostino Gemelli IRCCSUniversitàCattolica del Sacro CuoreRome 00168Italy Breast Surgery Department of Surgical OncologyRoswell Park Comprehensive Cancer CenterBuffaloNYUSA Department of Surgery MD Anderson Cancer CenterHoustonTX 77030USA Department of Plastic and Reconstructive Surgery

Patients with hormone receptor(HR)-positive tumors breast cancer usually experience a relatively low pathological complete response(p CR)to neoadjuvant chemotherapy(NAC).Here,we derived a 10-micro RNA risk score(10-mi RNA RS)-based model with better performance in the prediction of p CR and validated its relation with the disease-free survival(DFS)in 755 HRpositive 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-mi RNA RS found in our previous study,progesterone receptor(PR),human epidermal growth factor receptor 2(HER2)status,and volume transfer constant(K).Favorable calibration and discrimination of 10-mi RNA 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-mi RNA RS-based model could precisely identify more patients who can attain p CR to NAC,which may help clinicians formulate the personalized initial treatment strategy and consequently achieves better clinical prognosis for patients with HRpositive breast cancer.

关键词： hormone receptor-positive breast cancer micro RNA signature neoadjuvant chemotherapy dynamic contrast-enhanced magnetic resonance imaging nomogram

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