AIM
To develop a microarray-based prewarning system consisting of gastric cancer chip, prewarning data and analysis software for early detection of gastric cancer and pre-cancerous lesions.
METHODS
Two high-density chips with 8,464 human cDNA sites were used to primarily identify potential genes specific for normal gastric mucosa, pre-cancerous lesion and gastric cancer. The low-density chips, composed of selected genes associated with normal gastric mucosa, precancerous lesion and gastric cancer, were fabricated and used to screen 150 specimens including 60 specimens of gastric cancer, 60 of pre-cancerous tissues and 30 of normal gastric mucosa. CAD software was used to screen out the relevant genes and their critical threshold values of expression levels distinguishing normal mucosa from pre-cancerous lesion and cancer. All data were stored in a computer database to establish a prewarning data library for gastric cancer. Two potential markers brcaa1 and ndr1 were identified by Western blot and immunohistochemistry.
RESULTS
A total of 412 genes associated with three stages of gastric cancer development were identified. There were 216 genes displaying higher expression in gastric cancer, 85 genes displaying higher expression in pre-cancerous lesion and 88 genes displaying higher expression in normal gastric mucosa. Also 15 genes associated with metastasis of gastric cancer and 8 genes associated with risk factors were screened out for target genes of diagnosis chip of early gastric cancer. The threshold values of 412 selected genes to distinguish gastric cancer, pre-cancerous lesion from normal gastric mucosa were defined as 6.01+/-2.40, 4.86+/-1.94 and 5.42+/-2.17, respectively. These selected 412 genes and critical threshold values were compiled into an analysis software, which can automatically provide reports by analyzing the results of 412 genes obtained by examining gastric tissues. All data were compiled into a prewarning database for gastric cancer by CGO software. Northern blot and immunohistochemistry analysis confirmed that gene and protein of brcaa1 displayed lower expression in normal gastric mucosa and higher expression in gastric cancer tissues, conversely, ndr1 displayed lower expression in gastric cancer and higher expression in normal gastric mucosa.
CONCLUSION
The microarray-based prewarning system for gastric cancer was developed. This system consisted of gastric cancer-associated gene chip, prewarning data and analysis software, which has a high potential for applications in the early detection of gastric cancer. The two potential markers brcaa1 and ndr1 identified may be used to distinguish cancer status fand non-cancer status.
[1]
Yusuke Nakamura,et al.
Genome-wide analysis of gene expression in intestinal-type gastric cancers using a complementary DNA microarray representing 23,040 genes.
,
2002,
Cancer research.
[2]
M. Ringnér,et al.
Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks
,
2001,
Nature Medicine.
[3]
K. Mimori,et al.
Prognostic score of gastric cancer determined by cDNA microarray.
,
2002,
Clinical cancer research : an official journal of the American Association for Cancer Research.
[4]
Julian Terry,et al.
CGO: utilizing and integrating gene expression microarray data in clinical research and data management
,
2002,
Bioinform..
[5]
Huajian Gao,et al.
Advance and Prospect of Bionanomaterials
,
2003,
Biotechnology progress.
[6]
L. Franzén,et al.
Prevalence of Subtypes of Intestinal Metaplasia in the General Population and in Patients with Autoimmune Chronic Atrophic Gastritis
,
2002,
Scandinavian journal of gastroenterology.
[7]
K. K. Kim,et al.
Comparative study of angiostatic and anti-invasive gene expressions as prognostic factors in gastric cancer.
,
2001,
International journal of oncology.
[8]
Leif E. Peterson,et al.
Screening of gene expression profiles in gastric epithelial cells induced by Helicobacter pylori using microarray analysis
,
2002,
Alimentary pharmacology & therapeutics.
[9]
Shuichi Tsutsumi,et al.
Global gene expression analysis of gastric cancer by oligonucleotide microarrays.
,
2002,
Cancer research.
[10]
Yudong D. He,et al.
Gene expression profiling predicts clinical outcome of breast cancer
,
2002,
Nature.