The Differential Gene Expression Profiles between Sensitive and Resistant Breast Cancer Cells to Adriamycin by cDNA Microarray.
- Author:
Myung Ju AHN
1
;
Ki Hwan LEE
;
Joon Ik AHN
;
Dong Hyun YU
;
Hye Sook LEE
;
Jung Hye CHOI
;
Joung Soon JANG
;
Jong Min BAE
;
Yong Sung LEE
Author Information
1. Department of Internal Medicine, College of Medicine, Hanyang University, Seoul, Korea.
- Publication Type:Original Article
- Keywords:
Breast cancer cells;
Drug resistance;
cDNA microarray;
Adriamycin
- MeSH:
Breast Neoplasms*;
Breast*;
Cell Line;
DNA, Complementary*;
Doxorubicin*;
Drug Resistance;
Gene Expression*;
Guanylate Cyclase;
Humans;
Interferons;
Matrix Metalloproteinase 1;
Mitogen-Activated Protein Kinase 6;
Oligonucleotide Array Sequence Analysis*;
Phospholipases A2;
Phosphotransferases;
Spindle Apparatus;
Transcriptome*;
Tumor Necrosis Factor-alpha;
Vimentin
- From:Cancer Research and Treatment
2004;36(1):43-49
- CountryRepublic of Korea
- Language:English
-
Abstract:
PURPOSE: Adriamycin(R) is one of the most commonly used drugs in the treatment of breast cancer. This study was performed to understand the molecular mechanisms of drug resistance in breast cancer cells. MATERIALS AND METHODS: We have analyzed the MCF-7 breast cell line and its adriamycin-resistant variants, MCF-7/ADR using human 10 K element cDNA microarrays. RESULTS: We defined 68 genes that were up-regulated (14 genes) or down-regulated (54 genes) in adriamycin resistant breast cancer cells. Several genes, such as G protein-coupled receptor kinase 5, phospholipase A2, guanylate cyclase 1, vimentin, matrix metalloproteinase 1 are up-regulated in drug resistant cells. Several genes, such as interferon, alpha-inducible protein 27, forkhead box M1, mitogen-activated protein kinase 6, regulator of mitotic spindle assembly 1 and tumor necrosis factor superfamily are down-regulated in adriamycin resistant cells. The altered expression of genes observed in microarray was verified by RT-PCR. CONCLUSION: These findings show that cDNA microarray analysis can be used to obtain gene expression profiles reflecting the effect of anticancer drugs on breast cancer cells. Such data may lead to the assigning of signature expression profiles of drug-resistant tumors which may help predict responses to drugs and assist in the design of tailored therapeutic regimens to overcome drug resistance.
