Identification of genes associated with tumor progression using microarrays.
BACKGROUND
The progression of a metastatic disease is a multistep process involving various genetic events. High-throughput technologies such as microarrays offer the unique opportunity of screening the entire gene expression profile of malignant cells. Defining consistent changes in the gene expression pattern of cancer models may lead to detection of genes essential for tumor progression and may ultimately identify new targets for therapy.


METHODS
Gene expression was determined in multiple progression models of human prostate cancer cell lines derived from tumors after 1 to 5 passages as orthotopic xenografts in nude mice. Samples were analyzed using Affymetrix microarrays determining expression of 7,129 genes. Changes in gene expression were calculated referring to normal epithelial cells and confirmed by quantitative PCR. Data were validated by comparison to expression profiles of tumors induced by these cell lines and were also compared to expression data from clinical samples.


RESULTS
Two hundred and fourteen genes were regulated in the same direction in all cell lines compared to RNA of normal epithelial cells. Seventy-nine % of the 214 gene consensus class of the cell culture models were also found to be differentially-regulated in orthotopic tumors induced in mice and 83% also in clinical samples.


CONCLUSIONS
The expression pattern of these genes is consistent with their potential role in cancer progression. The results indicate the relevance of these xenograft models for expression analysis in the progression and development of metastatic cancer.
Gebauer
Gerhard
G
Sidney Kimmel Cancer Center, San Diego, CA, USA. gerhard.gebauer@med.uni-heidelberg.de
Krones-Herzig
Anja
A
Glinskii
Anna B
AB
Glinsky
Gennadi V
GV
D018450:Disease Progression; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D009369:Neoplasms / Q000235:genetics / Q000473:pathology*; D020411:Oligonucleotide Array Sequence Analysis; D016133:Polymerase Chain Reaction