title: Finding genes discriminating smokers from non-smokers by applying a growing self-organizing clustering method to large airway epithelium cell microarray data.
abstract: BACKGROUND
  Cigarette smoking is the major risk factor for development of lung cancer. Identification of effects of tobacco on airway gene expression may provide insight into the causes. This research aimed to compare gene expression of large airway epithelium cells in normal smokers (n=13) and non-smokers (n=9) in order to find genes which discriminate the two groups and assess cigarette smoking effects on large airway epithelium cells.
  
  
  METHODS
  Genes discriminating smokers from non-smokers were identified by applying a neural network clustering method, growing self-organizing maps (GSOM), to microarray data according to class discrimination scores. An index was computed based on differentiation between each mean of gene expression in the two groups. This clustering approach provided the possibility of comparing thousands of genes simultaneously.
  
  
  RESULTS
  The applied approach compared the mean of 7,129 genes in smokers and non-smokers simultaneously and classified the genes of large airway epithelium cells which had differently expressed in smokers comparing with non-smokers. Seven genes were identified which had the highest different expression in smokers compared with the non-smokers group: NQO1, H19, ALDH3A1, AKR1C1, ABHD2, GPX2 and ADH7. Most (NQO1, ALDH3A1, AKR1C1, H19 and GPX2) are known to be clinically notable in lung cancer studies. Furthermore, statistical discriminate analysis showed that these genes could classify samples in smokers and non-smokers correctly with 100% accuracy. With the performed GSOM map, other nodes with high average discriminate scores included genes with alterations strongly related to the lung cancer such as AKR1C3, CYP1B1, UCHL1 and AKR1B10.
  
  
  CONCLUSIONS
  This clustering by comparing expression of thousands of genes at the same time revealed alteration in normal smokers. Most of the identified genes were strongly relevant to lung cancer in the existing literature. The genes may be utilized to identify smokers with increased risk for lung cancer. A large sample study is now recommended to determine relations between the genes ABHD2 and ADH7 and smoking.
authors.affiliation: Tarbiat Modares University, Pathologist, Thyroid Research Center, Arak University of Medical Sciences, Iran. m.shahdoost@gmail.com
authors.forename: Maryam
authors.initials: M
authors.lastname: Shahdoust
authors.forename: Ebrahim
authors.initials: E
authors.lastname: Hajizadeh
authors.forename: Hossein
authors.initials: H
authors.lastname: Mozdarani
authors.forename: Ali
authors.initials: A
authors.lastname: Chehrei
mesh_terms: D015089:20-Hydroxysteroid Dehydrogenases / Q000235:genetics / Q000378:metabolism; D000426:Alcohol Dehydrogenase / Q000235:genetics / Q000378:metabolism; D000444:Aldehyde Dehydrogenase / Q000235:genetics / Q000378:metabolism; D014408:Biomarkers, Tumor / Q000235:genetics* / Q000378:metabolism; D004847:Epithelial Cells / Q000378:metabolism*; D015870:Gene Expression; D005979:Glutathione Peroxidase / Q000235:genetics; D006801:Humans; D006867:Hydrolases / Q000235:genetics / Q000378:metabolism; D008175:Lung Neoplasms / Q000235:genetics* / Q000378:metabolism; D046228:Microarray Analysis; D016660:NAD(P)H Dehydrogenase (Quinone) / Q000235:genetics / Q000378:metabolism; D062085:RNA, Long Noncoding / Q000235:genetics / Q000378:metabolism; D012137:Respiratory System / Q000378:metabolism*; D012907:Smoking / Q000235:genetics*
chemical_list: D014408:Biomarkers, Tumor; C094335:H19 long non-coding RNA; D062085:RNA, Long Noncoding; D015089:20-Hydroxysteroid Dehydrogenases; C115140:3 alpha-beta, 20 beta-hydroxysteroid dehydrogenase; C526911:ADH7 protein, human; D000426:Alcohol Dehydrogenase; C117436:GPX2 protein, human; D005979:Glutathione Peroxidase; C480021:ALDH3A1 protein, human; D000444:Aldehyde Dehydrogenase; D016660:NAD(P)H Dehydrogenase (Quinone); C447479:NQO1 protein, human; D006867:Hydrolases; C525115:ABHD2 protein, human