title: Identification and validation of potential prognostic lncRNA biomarkers for predicting survival in patients with multiple myeloma.
abstract: BACKGROUND
  Dysregulated long non-coding RNAs (lncRNAs) have been found to have oncogenic and/or tumor suppressive roles in the development and progression of cancer, implying their potentials as novel independent biomarkers for cancer diagnosis and prognosis. However, the prognostic significance of expression profile-based lncRNA signature for outcome prediction in patients with multiple myeloma (MM) has not yet been investigated.
  
  
  METHODS
  LncRNA expression profiles of a large cohort of patients with MM were obtained and analyzed by repurposing the publically available microarray data. An lncRNA-focus risk score model was developed from the training dataset, and then validated in the testing and another two independent external datasets. The time-dependent receiver operating characteristic (ROC) curve was used to evaluate the prognostic performance for survival prediction. The biological function of prognostic lncRNAs was predicted using bioinformatics analysis.
  
  
  RESULTS
  Four lncRNAs were identified to be significantly associated with overall survival (OS) of patients with MM in the training dataset, and were combined to develop a four-lncRNA prognostic signature to stratify patients into high-risk and low-risk groups. Patients of training dataset in the high-risk group exhibited shorter OS than those in the low-risk group (HR = 2.718, 95 % CI = 1.937-3.815, p <0.001). The similar prognostic values of four-lncRNA signature were observed in the testing dataset, entire GSE24080 dataset and another two independent external datasets. Multivariate Cox regression and stratified analysis showed that the prognostic power of four-lncRNA signature was independent of clinical features, including serum beta 2-microglobulin (Sβ2M), serum albumin (ALB) and lactate dehydrogenase (LDH). ROC analysis also demonstrated the better performance for predicting 3-year OS. Functional enrichment analysis suggested that these four lncRNAs may be involved in known genetic and epigenetic events linked to MM.
  
  
  CONCLUSIONS
  Our results demonstrated potential application of lncRNAs as novel independent biomarkers for diagnosis and prognosis in MM. These lncRNA biomarkers may contribute to the understanding of underlying molecular basis of MM.
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, PR China. biofomeng@hotmail.com.
authors.forename: Meng
authors.initials: M
authors.lastname: Zhou
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, PR China. zhaohengqiang921@163.com.
authors.forename: Hengqiang
authors.initials: H
authors.lastname: Zhao
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, PR China. wangzz@ems.hrbmu.edu.cn.
authors.forename: Zhenzhen
authors.initials: Z
authors.lastname: Wang
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, PR China. liangcheng@hrbmu.edu.cn.
authors.forename: Liang
authors.initials: L
authors.lastname: Cheng
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, PR China. leiyang_hmu@163.com.
authors.forename: Lei
authors.initials: L
authors.lastname: Yang
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, PR China. shihongbo@ems.hrbmu.edu.cn.
authors.forename: Hongbo
authors.initials: H
authors.lastname: Shi
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, PR China. yanghaixiu@ems.hrbmu.edu.cn.
authors.forename: Haixiu
authors.initials: H
authors.lastname: Yang
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, PR China. suncarajie@hotmail.com.
authors.forename: Jie
authors.initials: J
authors.lastname: Sun
mesh_terms: D014408:Biomarkers, Tumor / Q000235:genetics / Q000378:metabolism*; D005260:Female; D020869:Gene Expression Profiling; D063990:Gene Ontology; D006801:Humans; D053208:Kaplan-Meier Estimate; D008297:Male; D005810:Multigene Family; D009101:Multiple Myeloma / Q000378:metabolism* / Q000401:mortality; D015999:Multivariate Analysis; D011379:Prognosis; D016016:Proportional Hazards Models; D062085:RNA, Long Noncoding / Q000235:genetics / Q000378:metabolism*; D012372:ROC Curve
chemical_list: D014408:Biomarkers, Tumor; D062085:RNA, Long Noncoding