title: Diagnosis of lung cancer in individuals with solitary pulmonary nodules by plasma microRNA biomarkers.
abstract: BACKGROUND
  Making a definitive preoperative diagnosis of solitary pulmonary nodules (SPNs) found by CT has been a clinical challenge. We previously demonstrated that microRNAs (miRNAs) could be used as biomarkers for lung cancer diagnosis. Here we investigate whether plasma microRNAs are useful in identifying lung cancer among individuals with CT-detected SPNs.
  
  
  METHODS
  By using quantitative reverse transcriptase PCR analysis, we first determine plasma expressions of five miRNAs in a training set of 32 patients with malignant SPNs, 33 subjects with benign SPNs, and 29 healthy smokers to define a panel of miRNAs that has high diagnostic efficiency for lung cancer. We then validate the miRNA panel in a testing set of 76 patients with malignant SPNs and 80 patients with benign SPNs.
  
  
  RESULTS
  In the training set, miR-21 and miR-210 display higher plasma expression levels, whereas miR-486-5p has lower expression level in patients with malignant SPNs, as compared to subjects with benign SPNs and healthy controls (all P ≤ 0.001). A logistic regression model with the best prediction was built on the basis of miR-21, miR-210, and miR-486-5p. The three miRNAs used in combination produced the area under receiver operating characteristic curve at 0.86 in distinguishing lung tumors from benign SPNs with 75.00% sensitivity and 84.95% specificity. Validation of the miRNA panel in the testing set confirms their diagnostic value that yields significant improvement over any single one.
  
  
  CONCLUSIONS
  The plasma miRNAs provide potential circulating biomarkers for noninvasively diagnosing lung cancer among individuals with SPNs, and could be further evaluated in clinical trials.
authors.affiliation: Department of Pathology, University of Maryland School of Medicine, 10 S, Pine St, Baltimore, MD 21201, USA.
authors.forename: Jun
authors.initials: J
authors.lastname: Shen
authors.forename: Ziling
authors.initials: Z
authors.lastname: Liu
authors.forename: Nevins W
authors.initials: NW
authors.lastname: Todd
authors.forename: Howard
authors.initials: H
authors.lastname: Zhang
authors.forename: Jipei
authors.initials: J
authors.lastname: Liao
authors.forename: Lei
authors.initials: L
authors.lastname: Yu
authors.forename: Maria A
authors.initials: MA
authors.lastname: Guarnera
authors.forename: Ruiyun
authors.initials: R
authors.lastname: Li
authors.forename: Ling
authors.initials: L
authors.lastname: Cai
authors.forename: Min
authors.initials: M
authors.lastname: Zhan
authors.forename: Feng
authors.initials: F
authors.lastname: Jiang
mesh_terms: D000368:Aged; D019540:Area Under Curve; D014408:Biomarkers, Tumor / Q000097:blood*; D005260:Female; D006801:Humans; D016015:Logistic Models; D008175:Lung Neoplasms / Q000097:blood / Q000175:diagnosis* / Q000235:genetics*; D008297:Male; D035683:MicroRNAs / Q000096:biosynthesis / Q000097:blood*; D008875:Middle Aged; D012372:ROC Curve; D015203:Reproducibility of Results; D020133:Reverse Transcriptase Polymerase Chain Reaction; D012907:Smoking / Q000097:blood / Q000235:genetics; D003074:Solitary Pulmonary Nodule / Q000097:blood / Q000175:diagnosis* / Q000235:genetics*; D018709:Statistics, Nonparametric
chemical_list: D014408:Biomarkers, Tumor; D035683:MicroRNAs