Evidence for the presence of disease-perturbed networks in prostate cancer cells by genomic and proteomic analyses: A systems approach to disease
Evidence for the presence of disease-perturbed networks in prostate cancer cells by genomic and proteomic analyses: A systems approach to disease
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DOI：
10.1158/0008-5472.can-04-3218
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发表时间：
2005-04-15
期刊：
影响因子：
11.2
通讯作者：
Hood, L
中科院分区：
文献类型：
--
作者：
Lin, BY;White, JT;Hood, L
前列腺癌最初对雄激素消融治疗有反应，并进展为对治疗难治的雄激素无反应状态。这种转变的机制尚不清楚。疾病的系统方法始于对各种疾病状态中的信息元素（mRNA和蛋白质）的定量描述。我们采用了两个最近开发的高通量技术，大规模并行签名测序（MPSS）和同位素编码的亲和标签，以获得mRNA水平的变化和更严格的蛋白质水平的分析，分别从雄激素依赖性LNCaP（早期前列腺癌模型）的过渡到雄激素非依赖性CL1细胞（晚期前列腺癌模型）的全面图片。我们测序了超过500万个MPSS签名，获得了超过142，000个串联质谱，并建立了全面的MPSS和蛋白质组数据库。整合的mRNA和蛋白表达数据揭示了雄激素依赖性和雄激素非依赖性前列腺癌细胞之间的潜在功能差异。MPSS的高灵敏度使我们能够识别几乎所有表达的转录本，并量化这两种细胞状态之间的基因表达变化，包括功能上重要的低丰度mRNA，如编码转录因子和信号转导分子的mRNA。这些数据使我们能够将差异映射到现存的生理网络上，创建反映前列腺癌进展的扰动网络。我们找到了37个BioCarta和14个。与CL1细胞相比，LNCaP细胞中上调的23条基因和基因组通路以及23条BioCarta和22条基因和基因组通路。我们的努力代表了系统方法理解前列腺癌进展的重要一步。
Prostate cancer is initially responsive to androgen ablation therapy and progresses to androgen-unresponsive states that are refractory to treatment. The mechanism of this transition is unknown. A systems approach to disease begins with the quantitative delineation of the informational elements (mRNAs and proteins) in various disease states. We employed two recently developed high-throughput technologies, massively parallel signature sequencing (MPSS) and isotope-coded affinity tag, to gain a comprehensive picture of the changes in mRNA levels and more restricted analysis of protein levels, respectively, during the transition from androgen-dependent LNCaP (model for early-stage prostate cancer) to androgen-independent CL1 cells (model for late-stage prostate cancer). We sequenced > 5 million MPSS signatures, obtained > 142,000 tandem mass spectra, and built comprehensive MPSS and proteomic databases. The integrated mRNA and protein expression data revealed underlying functional differences between androgen-dependent and androgen-independent prostate cancer cells. The high sensitivity of MPSS enabled us to identify virtually all of the expressed transcripts and to quantify the changes in gene expression between these two cell states, including functionally important low-abundance mRNAs, such as those encoding transcription factors and signal transduction molecules. These data enable us to map the differences onto extant physiologic networks, creating perturbation networks that reflect prostate cancer progression. We found 37 BioCarta and 14. Kyoto Encyclopedia of Genes and Genomes pathways that are up-regulated and 23 BioCarta and 22 Kyoto Encyclopedia of Genes and Genomes pathways that are down-regulated in LNCaP cells versus CL1 cells. Our efforts represent a significant step toward a systems approach to understanding prostate cancer progression.