Digital expression profiles of the prostate androgen-response program

被引:31
作者
Clegg, N [1 ]
Eroglu, B [1 ]
Ferguson, C [1 ]
Arnold, H [1 ]
Moorman, A [1 ]
Nelson, PS [1 ]
机构
[1] Fred Hutchinson Canc Res Ctr, Div Human Biol, Seattle, WA 98109 USA
关键词
androgen; prostate; EST; SAGE; transcriptome;
D O I
10.1016/S0960-0760(01)00167-4
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
The androgen receptor (AR) and cognate ligands regulate vital aspects of prostate cellular growth and function including proliferation, differentiation, apoptosis, lipid metabolism, and secretory action. In addition, the AR pathway also influences pathological processes of the prostate such as benign prostatic hypertrophy and prostate carcinogenesis. The pivotal role of androgens and the AR in prostate biology prompted this study with the objective of identifying molecular mediators of androgen action. Our approach was designed to compare transcriptomes of the LNCaP prostate cancer cell line under conditions of androgen depletion and androgen stimulation by generating and comparing collections of expressed sequence tags (ESTs). A total of 4400 ESTs were produced from LNCaP cDNA libraries and these ESTs assembled into 2486 distinct transcripts. Rigorous statistical analysis of the expression profiles indicated that 17 genes exhibited a high probability (P > 0.9) of androgen-regulated expression. Northern analysis confirmed that the expression of KLK3/PSA, FKBP5, KRT18. DKFZP564K247, DDX15, and HSP90 is regulated by androgen exposure. Of these. only KLK3/PSA is known to be androgen-regulated while the other genes represent new members of the androgen-response program in prostate epithelium. LNCaP gene expression profiles defined by two independent experiments using the serial analysis of gene expression (SAGE) method were compared with the EST profiles. Distinctly different expression patterns were produced from each dataset. These results are indicative of the sensitivity of the methods to experimental conditions and demonstrate the power and the statistical limitations of digital expression analyses. (C) 2002 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:13 / 23
页数:11
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