title: Two microRNA panels to discriminate three subtypes of lung carcinoma in bronchial brushing specimens.
abstract: BACKGROUND
  Effective treatment for lung cancer requires accuracy in subclassification of carcinoma subtypes.
  
  
  OBJECTIVE
  To identify microRNAs in bronchial brushing specimens for discriminating small cell lung cancer (SCLC) from non-small cell lung cancer (NSCLC) and for further differentiating squamous cell carcinoma (SQ) from adenocarcinoma (AC).
  
  
  METHODS
  Microarrays were used to screen 723 microRNAs in laser-captured, microdissected cancer cells from 82 snap-frozen surgical lung specimens. Quantitative reverse-transcriptase polymerase chain reaction was performed on 153 macrodissected formalin-fixed, paraffin-embedded (FFPE) surgical lung specimens to evaluate seven microRNA candidates discovered from microarrays. Two microRNA panels were constructed on the basis of a training cohort (n = 85) and validated using an independent cohort (n = 68). The microRNA panels were applied as differentiators of SCLC from NSCLC and of SQ from AC in 207 bronchial brushing specimens.
  
  
  RESULTS
  Two microRNA panels yielded high diagnostic accuracy in discriminating SCLC from NSCLC (miR-29a and miR-375; area under the curve [AUC], 0.991 and 0.982 for training and validation data set, respectively) and in differentiating SQ from AC (miR-205 and miR-34a; AUC, 0.977 and 0.982 for training and validation data set, respectively) in FFPE surgical lung specimens. Moreover, the microRNA panels accurately differentiated SCLC from NSCLC (AUC, 0.947) and SQ from AC (AUC, 0.962) in bronchial brushing specimens.
  
  
  CONCLUSIONS
  We found two microRNA panels that accurately discriminated between the three subtypes of lung carcinoma in bronchial brushing specimens. The identified microRNA panels may have considerable clinical value in differential diagnosis and optimizing treatment strategies based on lung cancer subtypes.
authors.affiliation: Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Huang
authors.forename: Jie
authors.initials: J
authors.lastname: Hu
authors.forename: Da-wei
authors.initials: DW
authors.lastname: Yang
authors.forename: Xin-ting
authors.initials: XT
authors.lastname: Fan
authors.forename: Yi
authors.initials: Y
authors.lastname: Jin
authors.forename: Ying-yong
authors.initials: YY
authors.lastname: Hou
authors.forename: Ji-ping
authors.initials: JP
authors.lastname: Wang
authors.forename: Yun-feng
authors.initials: YF
authors.lastname: Yuan
authors.forename: Yun-shan
authors.initials: YS
authors.lastname: Tan
authors.forename: Xiong-Zeng
authors.initials: XZ
authors.lastname: Zhu
authors.forename: Chun-xue
authors.initials: CX
authors.lastname: Bai
authors.forename: Ying
authors.initials: Y
authors.lastname: Wu
authors.forename: Hong-guang
authors.initials: HG
authors.lastname: Zhu
authors.forename: Shao-hua
authors.initials: SH
authors.lastname: Lu
mesh_terms: D000368:Aged; D018893:Bronchoalveolar Lavage / Q000379:methods; D002289:Carcinoma, Non-Small-Cell Lung / Q000235:genetics / Q000473:pathology* / Q000601:surgery; D002294:Carcinoma, Squamous Cell / Q000235:genetics / Q000473:pathology* / Q000601:surgery; D045744:Cell Line, Tumor; D016009:Chi-Square Distribution; D003937:Diagnosis, Differential; D005260:Female; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D016014:Linear Models; D008175:Lung Neoplasms / Q000235:genetics / Q000473:pathology* / Q000601:surgery; D008297:Male; D035683:MicroRNAs / Q000235:genetics*; D008875:Middle Aged; D016612:Paraffin Embedding; D012372:ROC Curve; D060888:Real-Time Polymerase Chain Reaction / Q000379:methods; D015203:Reproducibility of Results; D012494:Sampling Studies; D055752:Small Cell Lung Carcinoma / Q000235:genetics / Q000473:pathology* / Q000601:surgery
chemical_list: D035683:MicroRNAs