title: Prognostic Value of a BCSC-associated MicroRNA Signature in Hormone Receptor-Positive HER2-Negative Breast Cancer.
abstract: OBJECTIVE
  Breast cancer patients with high proportion of cancer stem cells (BCSCs) have unfavorable clinical outcomes. MicroRNAs (miRNAs) regulate key features of BCSCs. We hypothesized that a biology-driven model based on BCSC-associated miRNAs could predict prognosis for the most common subtype, hormone receptor (HR)-positive, HER2-negative breast cancer patients.
  
  
  METHODS
  After screening candidate miRNAs based on literature review and a pilot study, we built a miRNA-based classifier using LASSO Cox regression method in the training group (n=202) and validated its prognostic accuracy in an internal (n=101) and two external validation groups (n=308).
  
  
  RESULTS
  In this multicenter study, a 10-miRNA classifier incorporating miR-21, miR-30c, miR-181a, miR-181c, miR-125b, miR-7, miR-200a, miR-135b, miR-22 and miR-200c was developed to predict distant relapse free survival (DRFS). With this classifier, HR+HER2- patients were scored and classified into high-risk and low-risk disease recurrence, which was significantly associated with 5-year DRFS of the patients. Moreover, this classifier outperformed traditional clinicopathological risk factors, IHC4 scoring and 21-gene Recurrence Score (RS). The patients with high-risk recurrence determined by this classifier benefit more from chemotherapy.
  
  
  CONCLUSIONS
  Our 10-miRNA-based classifier provides a reliable prognostic model for disease recurrence in HR+HER2- breast cancer patients. This model may facilitate personalized therapy-decision making for HR+HER2- individuals.
authors: Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Breast Tumor Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.
authors: Chang
authors: C
authors: Gong
authors: Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Breast Tumor Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.
authors: Weige
authors: W
authors: Tan
authors: Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Breast Tumor Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.
authors: Kai
authors: K
authors: Chen
authors: Department of Statistical Science, School of Mathematics and Computational Science & Southern China Research Center of Statistical Science, Sun Yat-sen University, Guangzhou 510275 China.
authors: Na
authors: N
authors: You
authors: Department of Statistical Science, School of Mathematics and Computational Science & Southern China Research Center of Statistical Science, Sun Yat-sen University, Guangzhou 510275 China.
authors: Shan
authors: S
authors: Zhu
authors: Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Breast Tumor Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.
authors: Gehao
authors: G
authors: Liang
authors: Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 510060, China.
authors: Xinhua
authors: X
authors: Xie
authors: Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Breast Tumor Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.
authors: Qian
authors: Q
authors: Li
authors: Department of Pathology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.
authors: Yunjie
authors: Y
authors: Zeng
authors: Department of Pathology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.
authors: Nengtai
authors: N
authors: Ouyang
authors: Prevention and Cure Center of Breast Disease, Key Laboratory of Breast Disease, the Third Hospital of Nanchang City, Nanchang, Jiangxi 330009, China.
authors: Zhihua
authors: Z
authors: Li
authors: Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 510060, China.
authors: Musheng
authors: M
authors: Zeng
authors: Key Laboratory of Gene Engineering of Ministry of Education, Collaborative Innovation Center for Cancer Medicine, School of Life Science, Sun Yat-sen University, Guangzhou 510275, China.
authors: ShiMei
authors: S
authors: Zhuang
authors: Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong, China; Department of Hepatobiliary Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.
authors: Wan-Yee
authors: WY
authors: Lau
authors: Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Breast Tumor Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.
authors: Qiang
authors: Q
authors: Liu
authors: Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Breast Tumor Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.
authors: Dong
authors: D
authors: Yin
authors: Department of Statistical Science, School of Mathematics and Computational Science & Southern China Research Center of Statistical Science, Sun Yat-sen University, Guangzhou 510275 China.
authors: Xueqin
authors: X
authors: Wang
authors: Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Breast Tumor Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China. Electronic address: fengxisu@vip.163.com.
authors: Fengxi
authors: F
authors: Su
authors: Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Breast Tumor Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China; Collaborative Innovation Center for Cancer Medicine, China. Electronic address: songerwei02@aliyun.com.
authors: Erwei
authors: E
authors: Song
mesh_terms: D000328:Adult; D014408:Biomarkers, Tumor; D001943:Breast Neoplasms / Q000235:genetics* / Q000401:mortality* / Q000473:pathology / Q000628:therapy; D003131:Combined Modality Therapy; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D018734:Genes, erbB-2; D006801:Humans; D053208:Kaplan-Meier Estimate; D035683:MicroRNAs / Q000235:genetics*; D008875:Middle Aged; D060787:Neoplasm Grading; D009362:Neoplasm Metastasis; D009364:Neoplasm Recurrence, Local; D009367:Neoplasm Staging; D014411:Neoplastic Stem Cells / Q000378:metabolism*; D011379:Prognosis; D012372:ROC Curve; D011960:Receptors, Estrogen / Q000235:genetics; D011980:Receptors, Progesterone / Q000235:genetics; D059467:Transcriptome; D016896:Treatment Outcome
chemical_list: D014408:Biomarkers, Tumor; D035683:MicroRNAs; D011960:Receptors, Estrogen; D011980:Receptors, Progesterone
keywords: Biology-driven approach; Breast cancer stem cell; Classifier; Prognosis; miRNA