Gene expression profiling of renal cell carcinoma: a DNA macroarray analysis
OBJECTIVES To examine differences in gene expression levels between renal cell carcinoma (RCC) tissue and ‘normal’ appearing renal tissue using a commercially available DNA macroarray. MATERIALS AND METHODS Tissue was obtained from 47 consecutive radical nephrectomies, 29 of which were eligible. DNA...
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Published in | BJU international Vol. 98; no. 1; pp. 205 - 216 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
Oxford, UK
Blackwell Publishing Ltd
01.07.2006
Blackwell |
Subjects | |
Online Access | Get full text |
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Abstract | OBJECTIVES
To examine differences in gene expression levels between renal cell carcinoma (RCC) tissue and ‘normal’ appearing renal tissue using a commercially available DNA macroarray.
MATERIALS AND METHODS
Tissue was obtained from 47 consecutive radical nephrectomies, 29 of which were eligible. DNA macroarrays were analysed on the tumour and normal‐appearing control tissue to measure the expression of 1185 cancer‐related genes. The group of samples was also stratified according to the presence or absence of granular cells and according to tumour grade. Quantitative real‐time polymerase‐chain reaction (PCR) was also performed on seven key genes present on the macroarray.
RESULTS
In all, 444 genes were over‐expressed and 33 genes were under‐expressed. Using selection criteria reduced the list to nine that were significantly over‐expressed and 23 that were under‐expressed. These significant genes belonged to the families of oncogenes, growth factors, interleukins, receptors, immune system components, cytoskeleton, matrix proteins and intracellular modulators, or they coded for proteins involved in DNA transcription and RNA translation, DNA repair, protein turnover, and metabolism of carbohydrates and lipids. There were differences in gene expression according to the presence or absence of granular cells and according to tumour grade. Using quantitative real‐time PCR there was over‐expression of epidermal growth factor receptor, c‐myc, transforming growth factor‐α, vascular endothelial growth factor and vimentin, and under‐expression of TYRO3 protein tyrosine kinase. The von Hippel–Lindau gene was under‐expressed but not significantly.
CONCLUSIONS
A procedure for collecting and storing fresh renal tissue and subsequent gene expression profiling of RCC and normal renal tissue was established. A commercially available DNA macroarray coupled with the significance analysis of macroarrays allowed the identification of sets of differentially expressed cancer‐related genes that were characteristic of RCC, compared with apparently normal renal tissue, and which distinguished among subgroups divided according to tumour grade and histological subtype. Quantitative PCR is important to validate the results of macroarray experiments. |
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AbstractList | OBJECTIVES
To examine differences in gene expression levels between renal cell carcinoma (RCC) tissue and ‘normal’ appearing renal tissue using a commercially available DNA macroarray.
MATERIALS AND METHODS
Tissue was obtained from 47 consecutive radical nephrectomies, 29 of which were eligible. DNA macroarrays were analysed on the tumour and normal‐appearing control tissue to measure the expression of 1185 cancer‐related genes. The group of samples was also stratified according to the presence or absence of granular cells and according to tumour grade. Quantitative real‐time polymerase‐chain reaction (PCR) was also performed on seven key genes present on the macroarray.
RESULTS
In all, 444 genes were over‐expressed and 33 genes were under‐expressed. Using selection criteria reduced the list to nine that were significantly over‐expressed and 23 that were under‐expressed. These significant genes belonged to the families of oncogenes, growth factors, interleukins, receptors, immune system components, cytoskeleton, matrix proteins and intracellular modulators, or they coded for proteins involved in DNA transcription and RNA translation, DNA repair, protein turnover, and metabolism of carbohydrates and lipids. There were differences in gene expression according to the presence or absence of granular cells and according to tumour grade. Using quantitative real‐time PCR there was over‐expression of epidermal growth factor receptor, c‐
myc
, transforming growth factor‐α, vascular endothelial growth factor and vimentin, and under‐expression of TYRO3 protein tyrosine kinase. The von Hippel–Lindau gene was under‐expressed but not significantly.
CONCLUSIONS
A procedure for collecting and storing fresh renal tissue and subsequent gene expression profiling of RCC and normal renal tissue was established. A commercially available DNA macroarray coupled with the significance analysis of macroarrays allowed the identification of sets of differentially expressed cancer‐related genes that were characteristic of RCC, compared with apparently normal renal tissue, and which distinguished among subgroups divided according to tumour grade and histological subtype. Quantitative PCR is important to validate the results of macroarray experiments. To examine differences in gene expression levels between renal cell carcinoma (RCC) tissue and 'normal' appearing renal tissue using a commercially available DNA macroarray. Tissue was obtained from 47 consecutive radical nephrectomies, 29 of which were eligible. DNA macroarrays were analysed on the tumour and normal-appearing control tissue to measure the expression of 1185 cancer-related genes. The group of samples was also stratified according to the presence or absence of granular cells and according to tumour grade. Quantitative real-time polymerase-chain reaction (PCR) was also performed on seven key genes present on the macroarray. In all, 444 genes were over-expressed and 33 genes were under-expressed. Using selection criteria reduced the list to nine that were significantly over-expressed and 23 that were under-expressed. These significant genes belonged to the families of oncogenes, growth factors, interleukins, receptors, immune system components, cytoskeleton, matrix proteins and intracellular modulators, or they coded for proteins involved in DNA transcription and RNA translation, DNA repair, protein turnover, and metabolism of carbohydrates and lipids. There were differences in gene expression according to the presence or absence of granular cells and according to tumour grade. Using quantitative real-time PCR there was over-expression of epidermal growth factor receptor, c-myc, transforming growth factor-alpha, vascular endothelial growth factor and vimentin, and under-expression of TYRO3 protein tyrosine kinase. The von Hippel-Lindau gene was under-expressed but not significantly. A procedure for collecting and storing fresh renal tissue and subsequent gene expression profiling of RCC and normal renal tissue was established. A commercially available DNA macroarray coupled with the significance analysis of macroarrays allowed the identification of sets of differentially expressed cancer-related genes that were characteristic of RCC, compared with apparently normal renal tissue, and which distinguished among subgroups divided according to tumour grade and histological subtype. Quantitative PCR is important to validate the results of macroarray experiments. OBJECTIVETo examine differences in gene expression levels between renal cell carcinoma (RCC) tissue and 'normal' appearing renal tissue using a commercially available DNA macroarray.MATERIALS AND METHODSTissue was obtained from 47 consecutive radical nephrectomies, 29 of which were eligible. DNA macroarrays were analysed on the tumour and normal-appearing control tissue to measure the expression of 1185 cancer-related genes. The group of samples was also stratified according to the presence or absence of granular cells and according to tumour grade. Quantitative real-time polymerase-chain reaction (PCR) was also performed on seven key genes present on the macroarray.RESULTSIn all, 444 genes were over-expressed and 33 genes were under-expressed. Using selection criteria reduced the list to nine that were significantly over-expressed and 23 that were under-expressed. These significant genes belonged to the families of oncogenes, growth factors, interleukins, receptors, immune system components, cytoskeleton, matrix proteins and intracellular modulators, or they coded for proteins involved in DNA transcription and RNA translation, DNA repair, protein turnover, and metabolism of carbohydrates and lipids. There were differences in gene expression according to the presence or absence of granular cells and according to tumour grade. Using quantitative real-time PCR there was over-expression of epidermal growth factor receptor, c-myc, transforming growth factor-alpha, vascular endothelial growth factor and vimentin, and under-expression of TYRO3 protein tyrosine kinase. The von Hippel-Lindau gene was under-expressed but not significantly.CONCLUSIONSA procedure for collecting and storing fresh renal tissue and subsequent gene expression profiling of RCC and normal renal tissue was established. A commercially available DNA macroarray coupled with the significance analysis of macroarrays allowed the identification of sets of differentially expressed cancer-related genes that were characteristic of RCC, compared with apparently normal renal tissue, and which distinguished among subgroups divided according to tumour grade and histological subtype. Quantitative PCR is important to validate the results of macroarray experiments. OBJECTIVES: To examine differences in gene expression levels between renal cell carcinoma (RCC) tissue and 'normal' appearing renal tissue using a commercially available DNA macroarray. MATERIALS AND METHODS: Tissue was obtained from 47 consecutive radical nephrectomies, 29 of which were eligible. DNA macroarrays were analysed on the tumour and normal-appearing control tissue to measure the expression of 1185 cancer-related genes. The group of samples was also stratified according to the presence or absence of granular cells and according to tumour grade. Quantitative real-time polymerase-chain reaction (PCR) was also performed on seven key genes present on the macroarray. RESULTS: In all, 444 genes were over-expressed and 33 genes were under-expressed. Using selection criteria reduced the list to nine that were significantly over-expressed and 23 that were under-expressed. These significant genes belonged to the families of oncogenes, growth factors, interleukins, receptors, immune system components, cytoskeleton, matrix proteins and intracellular modulators, or they coded for proteins involved in DNA transcription and RNA translation, DNA repair, protein turnover, and metabolism of carbohydrates and lipids. There were differences in gene expression according to the presence or absence of granular cells and according to tumour grade. Using quantitative real-time PCR there was over-expression of epidermal growth factor receptor, c-myc, transforming growth factor- alpha , vascular endothelial growth factor and vimentin, and under-expression of TYRO3 protein tyrosine kinase. The von Hippel-Lindau gene was under-expressed but not significantly. CONCLUSIONS: A procedure for collecting and storing fresh renal tissue and subsequent gene expression profiling of RCC and normal renal tissue was established. A commercially available DNA macroarray coupled with the significance analysis of macroarrays allowed the identification of sets of differentially expressed cancer-related genes that were characteristic of RCC, compared with apparently normal renal tissue, and which distinguished among subgroups divided according to tumour grade and histological subtype. Quantitative PCR is important to validate the results of macroarray experiments. OBJECTIVES To examine differences in gene expression levels between renal cell carcinoma (RCC) tissue and ‘normal’ appearing renal tissue using a commercially available DNA macroarray. MATERIALS AND METHODS Tissue was obtained from 47 consecutive radical nephrectomies, 29 of which were eligible. DNA macroarrays were analysed on the tumour and normal‐appearing control tissue to measure the expression of 1185 cancer‐related genes. The group of samples was also stratified according to the presence or absence of granular cells and according to tumour grade. Quantitative real‐time polymerase‐chain reaction (PCR) was also performed on seven key genes present on the macroarray. RESULTS In all, 444 genes were over‐expressed and 33 genes were under‐expressed. Using selection criteria reduced the list to nine that were significantly over‐expressed and 23 that were under‐expressed. These significant genes belonged to the families of oncogenes, growth factors, interleukins, receptors, immune system components, cytoskeleton, matrix proteins and intracellular modulators, or they coded for proteins involved in DNA transcription and RNA translation, DNA repair, protein turnover, and metabolism of carbohydrates and lipids. There were differences in gene expression according to the presence or absence of granular cells and according to tumour grade. Using quantitative real‐time PCR there was over‐expression of epidermal growth factor receptor, c‐myc, transforming growth factor‐α, vascular endothelial growth factor and vimentin, and under‐expression of TYRO3 protein tyrosine kinase. The von Hippel–Lindau gene was under‐expressed but not significantly. CONCLUSIONS A procedure for collecting and storing fresh renal tissue and subsequent gene expression profiling of RCC and normal renal tissue was established. A commercially available DNA macroarray coupled with the significance analysis of macroarrays allowed the identification of sets of differentially expressed cancer‐related genes that were characteristic of RCC, compared with apparently normal renal tissue, and which distinguished among subgroups divided according to tumour grade and histological subtype. Quantitative PCR is important to validate the results of macroarray experiments. |
Author | BONO, ALDO V. MARAFANTE, ERMINIO CLERICI, LIBERO CELATO, NICOLA CASATI, BARBARA SALVADORE, MAURIZIO LOVISOLO, JON A.J. |
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CitedBy_id | crossref_primary_10_1002_jcb_23207 crossref_primary_10_1074_mcp_M600310_MCP200 crossref_primary_10_3233_CBM_181558 crossref_primary_10_2353_ajpath_2010_091218 crossref_primary_10_1007_s13277_013_1344_4 crossref_primary_10_1111_j_1440_1827_2007_02156_x |
Cites_doi | 10.1101/gr.184501 10.1073/pnas.82.20.6980 10.1016/S0022-5347(17)41730-7 10.1073/pnas.241500798 10.1016/S0140-6736(02)08270-3 10.1038/sj.onc.1207979 10.1016/S0002-9440(10)63887-4 10.1056/NEJMoa012914 10.1073/pnas.091062498 10.1038/bjc.1995.75 10.1073/pnas.171209998 10.1002/(SICI)1096-9896(199710)183:2<131::AID-PATH931>3.0.CO;2-G 10.1186/1471-2407-3-31 10.1016/S0002-9440(10)64120-X 10.1007/s001099900022 10.1016/S0002-9440(10)65349-7 10.1158/0008-5472.CAN-03-2361 10.1038/sj.onc.1206869 10.1038/35000501 10.1038/ng0594-85 10.1006/bbrc.1999.0465 10.1073/pnas.1131754100 10.1111/j.1523-1755.2005.00738.x |
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Keywords | Kidney disease Human Nephrology Urinary system disease Carcinoma macroarray Malignant tumor Gene expression Real time quantitative real-time PCR Urology Gene expression profile Polymerase chain reaction renal cell carcinoma Cancerology Kidney cancer Genetics Grawitz tumor genomics Molecular biology DNA macroarray Quantitative analysis |
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To examine differences in gene expression levels between renal cell carcinoma (RCC) tissue and ‘normal’ appearing renal tissue using a commercially... To examine differences in gene expression levels between renal cell carcinoma (RCC) tissue and 'normal' appearing renal tissue using a commercially available... OBJECTIVES: To examine differences in gene expression levels between renal cell carcinoma (RCC) tissue and 'normal' appearing renal tissue using a commercially... OBJECTIVETo examine differences in gene expression levels between renal cell carcinoma (RCC) tissue and 'normal' appearing renal tissue using a commercially... |
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SubjectTerms | Biological and medical sciences Carcinoma, Renal Cell - genetics DNA macroarray DNA, Neoplasm - analysis DNA, Neoplasm - genetics Female gene expression Gene Expression Profiling - methods genomics Humans Kidney Neoplasms - genetics Kidneys macroarray Male Medical sciences Middle Aged Nephrology. Urinary tract diseases Oligonucleotide Array Sequence Analysis quantitative real‐time PCR renal cell carcinoma Tumors of the urinary system |
Title | Gene expression profiling of renal cell carcinoma: a DNA macroarray analysis |
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