DOI QR코드

DOI QR Code

Screening of Differentially Expressed Genes among Various TNM Stages of Lung Adenocarcinoma by Genomewide Gene Expression Profile Analysis

  • Liu, Ming (Cardiothoracic Surgery Department, Affiliated Daping Hospital) ;
  • Pan, Hong (Department of Clinical Laboratory Sciences, Affiliated South-West Hospital, Third Military Medical University) ;
  • Zhang, Feng (Beijing Institute of Genomics of the Chinese Academy of Sciences, Beijing Genomics Institute, Beijing Proteomics Institute) ;
  • Zhang, Yong-Biao (Beijing Institute of Genomics of the Chinese Academy of Sciences, Beijing Genomics Institute, Beijing Proteomics Institute) ;
  • Zhang, Yang (Department of Clinical Laboratory Sciences, Affiliated South-West Hospital, Third Military Medical University) ;
  • Xia, Han (Department of Clinical Laboratory Sciences, Affiliated South-West Hospital, Third Military Medical University) ;
  • Zhu, Jing (Department of Clinical Laboratory, the First Hospital Affiliated to the Chinese PLA General Hospital) ;
  • Fu, Wei-Ling (Department of Clinical Laboratory Sciences, Affiliated South-West Hospital, Third Military Medical University) ;
  • Zhang, Xiao-Li (Department of Clinical Laboratory Sciences, Affiliated South-West Hospital, Third Military Medical University)
  • Published : 2013.11.30

Abstract

Background: To further investigate the molecular basis of lung cancer development, we utilize a microarray to identify differentially expressed genes associated with various TNM stages of adenocarcinoma, a subtype with increasing incidence in recent years in China. Methods: A 35K oligo gene array, covering about 25,100 genes, was used to screen differentially expressed genes among 90 tumor samples of lung adenocarcinoma in various TNM stages. To verify the gene array data, three genes (Zimp7, GINS2 and NAG-1) were confirmed by real-time RT-PCR in a different set of samples from the gene array. Results: First, we obtained 640 differentially expressed genes in lung adenocarcinomas compared to the surrounding normal lung tissues. Then, from the 640 candidates we identified 10 differentially expressed genes among different TNM stages (Stage I, II and IIIA), of which Zimp7, GINS2 and NAG-1 genes were first reported to be present at a high level in lung adenocarcinoma. The results of qRT-PCR for the three genes were consistent with those from the gene array. Conclusions: We identified 10 candidate genes associated with different TNM stages in lung adenocarcinoma in the Chinese population, which should provide new insights into the molecular basis underlying the development of lung adenocarcinoma and may offer new targets for the diagnosis, therapy and prognosis prediction.

Keywords

Lung adenocarcinoma;TNM stage;gene expression profile;differential gene expression

References

  1. Boyle GM, Pedley J, Martyn AC, et al (2009). Macrophage inhibitory cytokine-1 is overexpressed in malignant melanoma and is associated with tumorigenicity. J Invest Dermatol, 129, 262-4. https://doi.org/10.1038/jid.2008.366
  2. David B, Robyn W, Philip B, et al (2003).MIC-1 serum level and genotype: associations with progress and prognosis of colorectal carcinoma. Clin Cancer Res, 9, 2642-50.
  3. Hanissian SH, Akbar U, Teng B, et al (2004). cDNA cloning and characterization of a novel gene encoding the MLF1-interacting protein MLF1IP. Oncogene, 23, 3700-7. https://doi.org/10.1038/sj.onc.1207448
  4. Hofmann HS, Bartling B, Simm A, et al (2006). Identification and classification of differentially expressed genes in non-small cell lung cancer by expression profiling on a global human 59.620-element oligonucleotide array. Oncol Rep, 16, 587-95.
  5. Huang Y, Beliakoff J, Li X, et al (2005). hZimp7, a novel PIAS-like protein, enhances androgen receptor-mediated transcription and interacts with SWI/SNF-like BAF complexes. Mol Endocrinol, 19, 2915-29. https://doi.org/10.1210/me.2005-0097
  6. Ji P, Diederichs S, Wang W, et al (2003). MALAT-1, a novel noncoding RNA, and thymosin beta4 predict metastasis and survival in early-stage non-small cell lung cancer. Oncogene, 22, 8031-41. https://doi.org/10.1038/sj.onc.1206928
  7. Kim KS, Baek SJ, Flake GP, et al (2002). Expression and regulation of nonsteroidal anti-inflammatory drug-activated gene (NAG-1) in human and mouse tissue. Gastroenterology, 122, 1388-98. https://doi.org/10.1053/gast.2002.32972
  8. Livak KJ, Schmittgen TD (2001). Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods, 25, 402-8. https://doi.org/10.1006/meth.2001.1262
  9. Loda M, Capodieci P, Mishra R, et al (1996). Expression of Mitogen-Activated Protein KinasePhosphatase-1 in the Early Phases of Human Epithelial Carcinogenesis. Am J Pathol, 149, 1553-64.
  10. Matsuda R, Enokida H, Chiyomaru T, et al (2011). LY6K is a novel molecular target in bladder cancer on basis of integrate genome-wide profiling. Br J Cancer, 104, 376-86. https://doi.org/10.1038/sj.bjc.6605990
  11. Nabeshima K, Inoue T, Shimao Y, Sameshima Y (2002). Matrix metalloproteinases in tumor invasion: role for cell migration. Pathol Annual, 52, 255-6.
  12. Newman D, Sakaue M, Koo JS, et al (2003). Differential regulation of nonsteroidal anti-inflammatory drug-activated gene in normal human tracheobronchial epithelial and lung carcinoma cells by retinoids. Mol Pharmacol, 63, 557-64. https://doi.org/10.1124/mol.63.3.557
  13. Nobuhisa I, Atsushi T, Wataru Y, et al (2007). Cancer-testis antigen lymphocyte antigen 6 complex locus K is a serologic biomarker and a therapeutic target for lung and esophageal carcinomas. Cancer Res, 67, 11601-11. https://doi.org/10.1158/0008-5472.CAN-07-3243
  14. Parkin DM, Bray F, Ferlay J, Pisani P (2002). Global cancer statistics. CA Cancer J Clin, 55, 74-108.
  15. Pfaffl MW (2001). A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res, 29, e45. https://doi.org/10.1093/nar/29.9.e45
  16. Sienel W, Varwerk C, Linder A, et al (2004). Melanoma associated antigen (MAGE)-A3 expression in Stages I and II non-small cell lung cancer: results of a multi-center study. Eur J Cardiothorac Surg, 25, 131-4. https://doi.org/10.1016/j.ejcts.2003.09.015
  17. Singhal S, Miller D, Ramalingamc S, Sun SY (2008). Gene expression profiling of Non-small cell lung cancer. Lung Cancer, 60, 313-24. https://doi.org/10.1016/j.lungcan.2008.03.007
  18. Tai CJ, Wu AT, Chiou JF, et al (2010). The investigation of Mitogen-Activated Protein kinase Phosphatase-1 as a potential pharmacological target in non-small cell lung carcinomas, assisted by non-invasive molecular imaging. BMC Cancer, 10, 95-102. https://doi.org/10.1186/1471-2407-10-95
  19. Tano K, Mizuno R, Okada T, et al (2010). MALAT-1 enhances cell motility of lung adenocarcinoma cells by influencing the expression of motility-related genes. FEBS Lett, 584, 4575-80. https://doi.org/10.1016/j.febslet.2010.10.008
  20. Thomassen M, Tan Q, Kruse TA (2009). Gene expression meta-analysis identifies chromosomal regions and candidate genes involved in breast cancer metastasis. Breast Cancer Res Treat, 113, 239-49. https://doi.org/10.1007/s10549-008-9927-2
  21. Zhang L, Zhou W, Velculescu VE, et al (1997). Gene expression profiles in normal and cancer cells. Science, 276, 1268-72. https://doi.org/10.1126/science.276.5316.1268

Cited by

  1. High GINS2 transcript level predicts poor prognosis and correlates with high histological grade and endocrine therapy resistance through mammary cancer stem cells in breast cancer patients vol.148, pp.2, 2014, https://doi.org/10.1007/s10549-014-3172-7
  2. Evaluation of Machine Learning Algorithm Utilization for Lung Cancer Classification Based on Gene Expression Levels vol.17, pp.2, 2016, https://doi.org/10.7314/APJCP.2016.17.2.835