In Silico Comparative Genomic Analysis of Two Non-small Cell Lung Cancer Subtypes and their Potentials for Cancer Classification

Cancer Genomics - Proteomics

YANHE SU¹  DONGFANG LI²  JINDONG LI²  XUDONG WEI² 

[1] Department of Thoracic Surgery, the Second Affiliated Hospital of Zhengzhou University, Zhengzhou, P.R. ChinDepartment of Thoracic Surgery, the Second Affiliated Hospital of Zhengzhou University, Zhengzhou, P.R. ChinDepartment of Thoracic Surgery, the Second Affiliated Hospital of Zhengzhou University, Zhengzhou, P.R. Chin;Department of Thoracic Surgery, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, P.R. ChinDepartment of Thoracic Surgery, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, P.R. ChinDepartment of Thoracic Surgery, the Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, P.R. Chin

关键词: Lung adenocarcinoma;    squamous cell lung carcinoma;    microarray data;    functional module network analysis;    support vector machine classifier;   

DOI  :  

来源: Delinasios GJ CO

【 摘 要 】

Background/Aim: 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. Materials and 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. Conclusion: 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.

【 授权许可】

Unknown