Identification of regulatory SNPs associated with genetic modifications in lung adenocarcinoma

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• 作者：Tzu-Pin Lu (1)
  Chuhsing K Hsiao (1) (2)
  Liang-Chuan Lai (2) (3)
  Mong-Hsun Tsai (2) (4)
  Chung-Ping Hsu (5)
  Jang-Ming Lee (6)
  Eric Y Chuang (2) (7)
  
  1. Department of Public Health ; Institute of Epidemiology and Preventive Medicine ; National Taiwan University ; Taipei ; Taiwan
  2. Bioinformatics and Biostatistics Core ; Center of Genomic Medicine ; National Taiwan University ; Taipei ; Taiwan
  3. Graduate Institute of Physiology ; National Taiwan University ; Taipei ; Taiwan
  4. Institute of Biotechnology ; National Taiwan University ; Taipei ; Taiwan
  5. Division of Thoracic Surgery ; Taichung Veterans General Hospital ; Taichung ; Taiwan
  6. Department of Surgery ; National Taiwan University Hospital ; Taipei ; Taiwan
  7. Graduate Institute of Biomedical Electronics and Bioinformatics and Department of Electrical Engineering ; National Taiwan University ; Taipei ; Taiwan
  
• 关键词：Lung adenocarcinoma ; Integrated analysis ; Copy number variation ; Methylation ; Microarray ; SNP
• 刊名：BMC Research Notes
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：8
• 期：1
• 全文大小：3,115 KB
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• 刊物主题：Biomedicine general; Medicine/Public Health, general; Life Sciences, general;
• 出版者：BioMed Central
• ISSN：1756-0500

文摘

Background Although much research effort has been devoted to elucidating lung cancer, the molecular mechanism of tumorigenesis still remains unclear. A major challenge to improve the understanding of lung cancer is the difficulty of identifying reproducible differentially expressed genes across independent studies, due to their low consistency. To enhance the reproducibility of the findings, an integrated analysis was performed to identify regulatory SNPs. Thirty-two pairs of tumor and adjacent normal lung tissue specimens were analyzed using Affymetrix U133plus2.0, Affymetrix SNP 6.0, and Illumina Infinium Methylation microarrays. Copy number variations (CNVs) and methylation alterations were analyzed and paired t-tests were used to identify differentially expressed genes. Results A total of 505 differentially expressed genes were identified, and their dysregulated patterns moderately correlated with CNVs and methylation alterations based on the hierarchical clustering analysis. Subsequently, three statistical approaches were performed to explore regulatory SNPs, which revealed that the genotypes of 551 and 66 SNPs were associated with CNV and changes in methylation, respectively. Among them, downstream transcriptional dysregulation was observed in 9 SNPs for CNVs and 4 SNPs for methylation alterations. Conclusions In summary, these identified SNPs concurrently showed the same direction of gene expression changes with genetic modifications, suggesting their pivotal roles in the genome for non-smoking women with lung adenocarcinoma.