title: In silico comparative genomic analysis of two non-small cell lung cancer subtypes and their potentials for cancer classification.
abstract: OBJECTIVE
  Lung adenocarcinoma (AC) and squamous cell lung carcinoma (SCC) are two main subtypes of non-small cell lung cancer. In order to understand their biological differences, we conducted an in silico comparative genomic analysis of their expression profiles.
  
  
  METHODS
  We utilized the published microarray data of 18 SCC samples and 40 AC samples to discriminate genes differentially expressed in SCC and AC. Genes were employed to construct a functional module network and build a support vector machine classifier. Another set of published non-small cell lung cancer microarray data was used to test the predictive accuracy of support vector machine classifier.
  
  
  RESULTS
  Our analysis showed that SCC shows an elevated expression of genes related to cell division and DNA replication while AC presents an elevated expression of the genes related to protein transport and cell junction. ROC analysis demonstrates that the support vector machine classifier has a high classification accuracy for AC and SCC.
  
  
  CONCLUSIONS
  AC and SCC are distinctively different in certain biological network modules. This proposes different pathological mechanisms involved in these two non-small cell lung cancer subtypes.
authors.affiliation: Department of Thoracic Surgery, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, P.R. China.
authors.forename: Jindong
authors.initials: J
authors.lastname: Li
authors.affiliation: Department of Thoracic Surgery, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, P.R. China.
authors.forename: Dongfang
authors.initials: D
authors.lastname: Li
authors.affiliation: Department of Thoracic Surgery, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, P.R. China.
authors.forename: Xudong
authors.initials: X
authors.lastname: Wei
authors.affiliation: Department of Thoracic Surgery, the Second Affiliated Hospital of Zhengzhou University, Zhengzhou, P.R. China.
authors.forename: Yanhe
authors.initials: Y
authors.lastname: Su
mesh_terms: D000230:Adenocarcinoma / Q000145:classification / Q000235:genetics; D000077192:Adenocarcinoma of Lung; D002289:Carcinoma, Non-Small-Cell Lung / Q000145:classification* / Q000235:genetics*; D003198:Computer Simulation; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D023281:Genomics; D006801:Humans; D008175:Lung Neoplasms / Q000145:classification* / Q000235:genetics*; D058977:Molecular Sequence Annotation; D012372:ROC Curve; D012984:Software; D060388:Support Vector Machine; D015854:Up-Regulation / Q000235:genetics
keywords: Lung adenocarcinoma; functional module network analysis; microarray data; squamous cell lung carcinoma; support vector machine classifier