[Microarray in screening for differentially expressed genes of cellular cycle and apoptosis in abdominal aortic aneurysms]

Zhonghua Wai Ke Za Zhi. 2002 Nov;40(11):817-9.
[Article in Chinese]

Abstract

Objective: To analyze the functions of differentially expressed genes between abdominal aortic aneurysm and normal aortic tissue by cDNA microarray.

Methods: Total RNAs were respectively isolated from the normal aorta and aortic aneurysm, purified into mRNAs by oligotex. Subsequently they were reverse-transcribed into cDNAs incorporated with fluorescent dUTP to make hybridization probes, which were hybridized as the cDNA microarray for scanning of fluorescent signals and differentially expressed genes between the normal aortic and aortic aneurysm by using GenePix Pro 3.0 software.

Results: A total of 18 differentially expressed genes were detected, accounting for 0.44% of total genes. Among these genes, 11 were related to cell cycle and the remaining 7 to cell apoptosis. The number of upregulated genes in the aortic aneurysm was 9 (mean ratio: 3.860) and that of the downregulated 9 (mean Ratio: 0.294). Bio-informative analysis showed that these 18 genes might influence the growth and apoptosis of smooth muscle cells in abdominal aortic aneurysms.

Conclusions: During the development of abdominal aortic aneurysms, modulations of multi-gene expression would undergo various changes. Cell cycle and apoptosis-related genes were related to the growth and apoptosis of smooth muscle cells in abdominal aortic aneurysms. Further research into these genes will clarify the mechanisms of abdominal aortic aneurysms.

Publication types

  • English Abstract
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aortic Aneurysm, Abdominal / genetics*
  • Aortic Aneurysm, Abdominal / pathology
  • Apoptosis / physiology*
  • Cell Cycle / genetics
  • Cells, Cultured
  • Gene Expression
  • Gene Expression Profiling
  • Humans
  • Myocytes, Smooth Muscle / metabolism
  • Myocytes, Smooth Muscle / pathology*
  • Oligonucleotide Array Sequence Analysis