Tissue-wide expression profiling using cDNA subtraction and microarrays to identify tumor-specific genes

被引:201
作者
Amatschek, S
Koenig, U
Auer, H
Steinlein, P
Pacher, M
Gruenfelder, A
Dekan, G
Vogl, S
Kubista, E
Heider, KH
Stratowa, C
Schreiber, M
Sommergruber, W
机构
[1] Boehringer Ingelheim Austria, Dept NCE Lead Discovery, A-1120 Vienna, Austria
[2] Univ Vienna, Dept Dermatol, A-1010 Vienna, Austria
[3] Univ Vienna, Dept Pathol, A-1010 Vienna, Austria
[4] Ohio State Univ, Columbus, OH 43210 USA
[5] Inst Mol Pathol, A-1030 Vienna, Austria
[6] Univ Vienna, Dept Obstet & Gynecol, Vienna, Austria
[7] Ludwig Boltzmann Inst Clin & Expt Oncol, Vienna, Austria
关键词
D O I
10.1158/0008-5472.CAN-03-2361
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
With the objective of discovering novel putative intervention sites for anticancer therapy, we compared transcriptional profiles of breast cancer, lung squamous cell cancer (LSCC), lung adenocarcinoma (LAC), and renal cell cancer (RCC). Each of these tumor types still needs improvement in medical treatment. Our intention was to search for genes not only highly expressed in the majority of patient samples but which also exhibit very low or even absence of expression in a comprehensive panel of 16 critical (vital) normal tissues. To achieve this goal, we combined two powerful technologies, PCR-based cDNA subtraction and cDNA microarrays. Seven subtractive libraries consisting of similar to9250 clones were established and enriched for tumor-specific transcripts. These clones, together with similar to1750 additional tumor-relevant genes, were used for cDNA microarray preparation. Hybridizations were performed using a pool of 16 critical normal tissues as a reference in all experiments. In total, we analyzed 20 samples of breast cancer, 11 of LSCC, 11 of LAC, and 8 of RCC. To select for genes with low or even no expression in normal tissues, expression profiles of 22 different normal tissues were additionally analyzed. Importantly, this tissue-wide expression profiling allowed us to eliminate genes, which exhibit also high expression in normal tissues. Similarly, expression signatures of genes, which are derived from infiltrating cells of the immune system, were eliminated as well. Cluster analysis resulted in the identification of 527 expressed sequence tags specifically up-regulated in these tumors. Gene-wise hierarchical clustering of these clones clearly separated the different tumor types with RCC exhibiting the most homogenous and LAC the most diverse expression profile. In addition to already known tumor-associated genes, the majority of identified genes have not yet been brought into context with tumorigenesis such as genes involved in bone matrix mineralization (OSN, OPN, and OSF-2) in lung, breast, and kidney cancer or genes controlling Ca2+ homeostasis (RCN1, CALCA, S100 protein family). EGLN3, which recently has been shown to be involved in regulation of hypoxia-inducible factor, was found to be highly up-regulated in all RCCs and in half of the LSCCs analyzed. Furthermore, 42 genes, the expression level of which correlated with the overall survival of breast cancer patients, were identified. The gene dendogram clearly separates two groups of genes, those up-regulated such as cyclin B1, TGF-beta3, B-Myb, Erg2, VCAM-1, and CD44 and those down-regulated such as MIG-6, Esp15, and CAK in patients with short survival time.
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收藏
页码:844 / 856
页数:13
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