AI Article Synopsis
- The study aimed to compare gene expressions between high metastatic (H0-8910PM) and low metastatic (HO-8910) ovarian carcinoma cell lines using cDNA microarray techniques.
- Researchers used probes labeled with different fluoresceins to analyze gene expression levels and identified a significant number of differentially expressed genes when comparing the cancer cell lines to normal ovarian cells.
- The findings suggest that the identified genes may play a role in the development of ovarian cancer and could aid in future diagnostics, treatment, and prevention strategies.
Article Abstract
Objectives: To study the difference between gene expressions of high (H0-8910PM) and low (HO-8910) metastatic human ovarian carcinoma cell lines and screen novel associated genes by cDNA microarray.
Methods: cDNA retro-transcribed from equal quantities of mRNA derived from high and low metastatic tumor cells or normal ovarian tissues were labeled with Cy5 and Cy3 fluorescein as probes. The mixed probe was hybridized with two pieces of BioDoor 4096 double dot human whole gene chip and scanned with a ScanArray 3000 laser scanner. The acquired image was analyzed by ImaGene 3.0 software.
Results: A total of 355 genes with expression levels more than 3 times larger were found by comparing the HO-8910 cell with normal ovarian epithelial cells. A total of 323 genes with expression levels more than 3 times larger in HO-8910PM cells compared to normal ovarian epithelium cells were also detected. A total of 165 genes whose expression levels were more than two times those of HO-8910PM cells compared to their mother cell line (HO-8910) were detected. Twenty-one genes with expression levels > 3 times were found from comparison of these two tumor cell lines.
Conclusions: cDNA microarray techniques are effective in screening differential gene expression between two human ovarian cancer cell lines (H0-8910PM; HO-8910) and normal ovarian epithelial cells. These genes may be related to the genesis and development of ovarian carcinoma. Analysis of the human ovarian cancer gene expression profile with cDNA microarray may help in gene diagnosis, treatment and prevention.
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