title: Systemically identifying and prioritizing risk lncRNAs through integration of pan-cancer phenotype associations.
abstract: LncRNAs have emerged as a major class of regulatory molecules involved in normal cellular physiology and disease, our knowledge of lncRNAs is very limited and it has become a major research challenge in discovering novel disease-related lncRNAs in cancers. Based on the assumption that diverse diseases with similar phenotype associations show similar molecular mechanisms, we presented a pan-cancer network-based prioritization approach to systematically identify disease-specific risk lncRNAs by integrating disease phenotype associations. We applied this strategy to approximately 2800 tumor samples from 14 cancer types for prioritizing disease risk lncRNAs. Our approach yielded an average area under the ROC curve (AUC) of 80.66%, with the highest AUC (98.14%) for medulloblastoma. When evaluated using leave-one-out cross-validation (LOOCV) for prioritization of disease candidate genes, the average AUC score of 97.16% was achieved. Moreover, we demonstrated the robustness as well as the integrative importance of this approach, including disease phenotype associations, known disease genes and the numbers of cancer types. Taking glioblastoma multiforme as a case study, we identified a candidate lncRNA gene SNHG1 as a novel disease risk factor for disease diagnosis and prognosis. In summary, we provided a novel lncRNA prioritization approach by integrating pan-cancer phenotype associations that could help researchers better understand the important roles of lncRNAs in human cancers.
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
authors.forename: Chaohan
authors.initials: C
authors.lastname: Xu
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
authors.forename: Rui
authors.initials: R
authors.lastname: Qi
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
authors.forename: Yanyan
authors.initials: Y
authors.lastname: Ping
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
authors.forename: Jie
authors.initials: J
authors.lastname: Li
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
authors.forename: Hongying
authors.initials: H
authors.lastname: Zhao
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
authors.forename: Li
authors.initials: L
authors.lastname: Wang
authors.affiliation: Weston High School of Massachusetts, Massachusetts, USA.
authors.forename: Michael Yifei
authors.initials: MY
authors.lastname: Du
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.|Key Laboratory of Cardiovascular Medicine Research, Harbin Medical University, Ministry of Education, China.
authors.forename: Yun
authors.initials: Y
authors.lastname: Xiao
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
authors.forename: Xia
authors.initials: X
authors.lastname: Li
mesh_terms: D020869:Gene Expression Profiling / Q000379:methods; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D005909:Glioblastoma / Q000175:diagnosis / Q000235:genetics; D006801:Humans; D008957:Models, Genetic; D009369:Neoplasms / Q000145:classification / Q000175:diagnosis / Q000235:genetics*; D010641:Phenotype; D011379:Prognosis; D062085:RNA, Long Noncoding / Q000235:genetics*; D012372:ROC Curve; D012307:Risk Factors
chemical_list: D062085:RNA, Long Noncoding; C000613724:long non-coding RNA SNHG1, human
keywords: disease phenotype association; identification and prioritization; pan cancer; risk lncRNA