Microarray gene expression profiling and analysis in renal cell carcinoma

被引：42

作者：

Liou L.S. ^{[1
,2
,6
,7
]}

Shi T. ^{[1
]}

Duan Z.-H. ^{[4
]}

Sadhukhan P. ^{[1
,2
]}

Der S.D. ^{[5
]}

Novick A.A. ^{[2
]}

Hissong J. ^{[1
]}

Skacel M. ^{[3
]}

Almasan A. ^{[1
]}

DiDonato J.A. ^{[1
]}

机构：

[1] Department of Cancer Biology, Cleveland Clinic Foundation, Cleveland, OH

[2] Glickman Urological Institute, Cleveland Clinic Foundation, Cleveland, OH

[3] Department of Pathology, Cleveland Clinic Foundation, Cleveland, OH

[4] Department of Computer Science, University of Akron, Akron, OH

[5] Dept. of Lab. Med. and Pathobiology, University of Toronto, Toronto, Ont.

[6] Department of Urology and Pathology, Boston Medical Center, Boston University, Boston, MA

[7] Department of Urology, Cleveland Clinic Foundation, Cleveland, OH

来源：

BMC Urology | / 4卷 / 1期

关键词：

Renal Cell Carcinoma; Reverse Transcription Polymerase Chain Reaction; Singular Value Decomposition; Clear Cell Renal Cell Carcinoma; Liver Fatty Acid Binding Protein;

D O I：

10.1186/1471-2490-4-9

中图分类号：

学科分类号：

摘要：

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.

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