Difference of gene expression profiles between HL-60/VCR and HL-60 cells detected by human genome genechip.
- Author:
Bao-Xian DONG
1
;
Xie-Qun CHEN
;
Zhe WANG
;
Rong LIANG
;
Qing-Xian BAI
;
Gao-Sheng HUANG
;
Wei-Ping ZHANG
;
Guang-Xun GAO
;
Dong-Mei HAN
Author Information
1. Department of Hematology, Xijing Hospital, Xi'an 710032, China.
- Publication Type:Journal Article
- MeSH:
Drug Resistance, Neoplasm;
genetics;
Gene Expression Profiling;
Gene Expression Regulation, Neoplastic;
Genome, Human;
HL-60 Cells;
Humans;
Oligonucleotide Array Sequence Analysis;
Vincristine;
pharmacology
- From:
Journal of Experimental Hematology
2006;14(3):492-496
- CountryChina
- Language:Chinese
-
Abstract:
This study was aimed to detect the gene expression profile changes between human acute leukemia cell line HL-60 and VCR-resistance HL-60, and to investigate the underlying mechanisms of MDR by using genechip technology. In experiments, mRNA were harvested using TrizoL reagent from these two cell lines, through RT-PCR, the biotinylated nucleotide were incorporated into the cRNA during the in vitro transcription reaction. The high quality RNA was hybridized to the gene expression array--human genome U133A developed by Affymetrix. It was scanned by G2500A GeneArray Scanner and the acquired image was analysed by a series of softwares. The results showed that 5,507 genes were differentially expressed between human acute leukemia cell line HL-60 and VCR-resistant HL-60. Compared with HL-60, 3,100 genes were up-regulated and 2,407 genes were down-regulated in VCR-resistant cell line. These genes were involved in different cell activities such as growth regulation and signal transduction. Among the genes with remarkable differential expression between the two cell lines, 435 were up-regulated and 605 were down-regulated. It is concluded that many different kinds of genes are involved in the mechanism of MDR and there is an intricate molecular network that controls the sensitivity of leukemia cells to the chemotherapeutic agents. Genechip is an efficient tool for parallel gene expression analysis.
