title: A four-long non-coding RNA signature in predicting breast cancer survival.
abstract: BACKGROUND
  Many long non-coding RNAs(lncRNAs) have been found to be a good marker for several tumors. Using lncRNA-mining approach, we aimed to identify lncRNA expression signature that can predict breast cancer patient survival.
  
  
  METHODS
  We performed LncRNA expression profiling in 887 breast cancer patients from Gene Expression Omnibus (GEO) datasets. The association between lncRNA signature and clinical survival was analyzed using the training set(n = 327, from GSE 20685). The validation for the association was performed in another three independent testing sets(252 from GSE21653, 204 from GSE12276, and 104 from GSE42568).
  
  
  RESULTS
  A set of four lncRNA genes (U79277, AK024118, BC040204, AK000974) have been identified by the random survival forest algorithm. Using a risk score based on the expression signature of these lncRNAs, we separated the patients into low-risk and high-risk groups with significantly different survival times in the training set. This signature was validated in the other three cohorts. Further study revealed that the four-lncRNA expression signature was independent of age and subtype. Gene Set Enrichment Analysis (GSEA) suggested that gene sets were involved in several cancer metastasis related pathways.
  
  
  CONCLUSIONS
  These findings indicate that lncRNAs may be implicated in breast cancer pathogenesis. The four-lncRNA signature may have clinical implications in the selection of high-risk patients for adjuvant therapy.
authors.affiliation: Department of Radiation Oncology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yi Shan Rd, Shanghai, 200233, China. jademj@gmail.com.
authors.forename: Jin
authors.initials: J
authors.lastname: Meng
authors.affiliation: Department of Radiation Oncology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yi Shan Rd, Shanghai, 200233, China. liping529@gmail.com.
authors.forename: Ping
authors.initials: P
authors.lastname: Li
authors.affiliation: Radiation Oncology Center, Fudan University Shanghai Cancer Center (FUSCC), 399 LingLing Rd, Xu Hui District, Shanghai, 200032, China. zhangqingcyw@hotmail.com.|Radiation Oncology Department, Shanghai Proton and Heavy Ion Center (SPHIC), 4365 Kang Xin Rd, Pudong New District, Shanghai, 201321, China. zhangqingcyw@hotmail.com.
authors.forename: Qing
authors.initials: Q
authors.lastname: Zhang
authors.affiliation: Department of Radiation Oncology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yi Shan Rd, Shanghai, 200233, China. 59747438@qq.com.
authors.forename: Zhangru
authors.initials: Z
authors.lastname: Yang
authors.affiliation: Radiation Oncology Center, Fudan University Shanghai Cancer Center (FUSCC), 399 LingLing Rd, Xu Hui District, Shanghai, 200032, China. fushen1117@gmail.com.|Radiation Oncology Department, Shanghai Proton and Heavy Ion Center (SPHIC), 4365 Kang Xin Rd, Pudong New District, Shanghai, 201321, China. fushen1117@gmail.com.
authors.forename: Shen
authors.initials: S
authors.lastname: Fu
mesh_terms: D019540:Area Under Curve; D014408:Biomarkers, Tumor / Q000235:genetics*; D001943:Breast Neoplasms / Q000235:genetics* / Q000401:mortality / Q000628:therapy; D030541:Databases, Genetic; D018572:Disease-Free Survival; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods; D006801:Humans; D053208:Kaplan-Meier Estimate; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D062085:RNA, Long Noncoding / Q000235:genetics*; D012372:ROC Curve; D015203:Reproducibility of Results; D012307:Risk Factors; D013997:Time Factors; D016896:Treatment Outcome
chemical_list: D014408:Biomarkers, Tumor; D062085:RNA, Long Noncoding