Microarray gene expression profiling and analysis in renal cell carcinoma - PubMed
- ️Thu Jan 01 2004
Microarray gene expression profiling and analysis in renal cell carcinoma
Louis S Liou et al. BMC Urol. 2004.
Abstract
Background: Renal cell carcinoma (RCC) is the most common cancer in adult kidney. The accuracy of current diagnosis and prognosis of the disease and the effectiveness of the treatment for the disease are limited by the poor understanding of the disease at the molecular level. To better understand the genetics and biology of RCC, we profiled the expression of 7,129 genes in both clear cell RCC tissue and cell lines using oligonucleotide arrays.
Methods: Total RNAs isolated from renal cell tumors, adjacent normal tissue and metastatic RCC cell lines were hybridized to affymatrix HuFL oligonucleotide arrays. Genes were categorized into different functional groups based on the description of the Gene Ontology Consortium and analyzed based on the gene expression levels. Gene expression profiles of the tissue and cell line samples were visualized and classified by singular value decomposition. Reverse transcription polymerase chain reaction was performed to confirm the expression alterations of selected genes in RCC.
Results: Selected genes were annotated based on biological processes and clustered into functional groups. The expression levels of genes in each group were also analyzed. Seventy-four commonly differentially expressed genes with more than five-fold changes in RCC tissues were identified. The expression alterations of selected genes from these seventy-four genes were further verified using reverse transcription polymerase chain reaction (RT-PCR). Detailed comparison of gene expression patterns in RCC tissue and RCC cell lines shows significant differences between the two types of samples, but many important expression patterns were preserved.
Conclusions: This is one of the initial studies that examine the functional ontology of a large number of genes in RCC. Extensive annotation, clustering and analysis of a large number of genes based on the gene functional ontology revealed many interesting gene expression patterns in RCC. Most notably, genes involved in cell adhesion were dominantly up-regulated whereas genes involved in transport were dominantly down-regulated. This study reveals significant gene expression alterations in key biological pathways and provides potential insights into understanding the molecular mechanism of renal cell carcinogenesis.
Figures

Biological process ontology tree of 1,340 genes associated with RCC tissues. The first integer following the name of each functional group represents the number of genes associated with the group. The first percent number stands for the percentage of genes in the group that are at least two-fold up regulated in average. The second number is the percentage of down-regulated genes.

Semi-quantitative RT-PCR of SLC6A3, BIGH3 and vWF. Total RNA was extracted from 8 pairs of RCC tissue (C) and patient-matched normal kidney tissue (N). The over-expression of SLC6A3 was seen in all 8 tissue pairs and the over-expression of BIGH3 and vWF was seen in 7 of the 8 tissue pairs (sample 1, 3, 4, 5, 6, 7, 8). Amplification of DNA fragment of α-tubulin was used as quantitative control.

SVD projections of the five expression profiles based on 3,145 genes. The horizontal axis represents the first singular vector. The vertical axis is for the second singular vector. Normal tissue sample profiles are clustered together while RCC tissue sample profiles are grouped into a distinct group. The cell line profile is well separated from the tissue profiles.
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