title: A systematic analysis of predicted MiR-31-targets identifies a diagnostic and prognostic signature for lung cancer.
abstract: BACKGROUND
  Recent studies have shown that miR-31 could play a potential role as diagnostic and prognostic biomarkers of several cancers including lung cancer. The aim of this study is to globally summarize the predicting targets of miR-31 and their potential function, pathways and networks, which are involved in the biological behavior of lung cancer.
  
  
  METHODS
  We have conducted the natural language processing (NLP) analysis to identify lung cancer-related molecules in our previous work. In this study, miR-31 targets predicted by combinational computational methods. All target genes were characterized by gene ontology (GO), pathway and network analysis. In addition, miR-31 targets analysis were integrated with the results from NLP analysis, followed by hub genes interaction analysis.
  
  
  RESULTS
  We identified 27 hub genes by the final integrative analysis and suggested that miR-31 may be involved in the initiation, progression and treatment response of lung cancer through cell cycle, cytochrome P450 pathway, metabolic pathways, apoptosis, chemokine signaling pathway, MAPK signaling pathway, as well as others.
  
  
  CONCLUSIONS
  Our data may help researchers to predict the molecular mechanisms of miR-31 in the molecular mechanism of lung cancer comprehensively. Moreover, the present data indicate that the interaction of miR-31 targets may be promising candidates as biomarkers for the diagnosis, prognosis and personalized therapy of lung cancer.
authors.affiliation: Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China. Electronic address: yoghurt831030@126.com.
authors.forename: Wen
authors.initials: W
authors.lastname: Gao
authors.affiliation: Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China.
authors.forename: Lingxiang
authors.initials: L
authors.lastname: Liu
authors.affiliation: Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China.
authors.forename: Jing
authors.initials: J
authors.lastname: Xu
authors.affiliation: Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China.
authors.forename: Qianwen
authors.initials: Q
authors.lastname: Shao
authors.affiliation: Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China.
authors.forename: Yiqian
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Shanghai Sensichip Info tech Co Ltd., Shanghai 200433, China.
authors.forename: Huazong
authors.initials: H
authors.lastname: Zeng
authors.affiliation: Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, China. Electronic address: shuyongqian@csco.org.cn.
authors.forename: Yongqian
authors.initials: Y
authors.lastname: Shu
mesh_terms: D017209:Apoptosis / Q000235:genetics*; D014408:Biomarkers, Tumor / Q000378:metabolism; D018925:Chemokines / Q000378:metabolism; D018450:Disease Progression; D006801:Humans; D008175:Lung Neoplasms / Q000175:diagnosis / Q000235:genetics* / Q000473:pathology; D020935:MAP Kinase Signaling System / Q000235:genetics; D035683:MicroRNAs / Q000235:genetics*; D011379:Prognosis
chemical_list: D014408:Biomarkers, Tumor; D018925:Chemokines; C534612:MIRN31 microRNA, human; D035683:MicroRNAs
keywords: Lung cancer; Systematic analysis; miR-31