Savli Hakan, Szendröi Attila, Romics Imre, Nagy Balint
Department of Medical Genetics and Clinical Research Unit, Kocaeli University, Kocaeli 41380, Turkey.
Exp Mol Med. 2008 Apr 30;40(2):176-85. doi: 10.3858/emm.2008.40.2.176.
The molecular mechanism playing a role in the development of prostate cancer (PCA) is not well defined. We decided to determine the changes in gene expression in PCA tissues and to compare them to those in non-cancerous samples. Prostate tissue samples were collected by needle biopsy from 21 PCA and 10 benign prostate hyperplasic (BPH) patients. Total RNA was isolated, cDNA was synthesized, and gene expression levels were determined by microarray method. In the progression to PCA, 738 up-regulated and 515 down-regulated genes were detected in samples. Analysis using Ingenuity Pathway Analysis (IPA) software revealed that 466 network and 423 functions-pathways eligible genes were up-regulated, and 363 network and 342 functions-pathways eligible genes were down-regulated. Up-regulated networks were identified around IL-1beta and insulin-like growth factor-1 (IGF-1) genes. The NFKB gene was centered around two up- and down-regulated networks. Up-regulated canonical pathways were assigned and four of them were evaluated in detail: acute phase response, hepatic fibrosis, actin cytoskeleton, and coagulation pathways. Axonal guidance signaling was the most significant down-regulated canonical pathway. Our data provide not only networks between the genes for understanding the biologic properties of PCA but also useful pathway maps for future understanding of disease and the construction of new therapeutic targets.
前列腺癌(PCA)发生发展过程中的分子机制尚未明确。我们决定确定PCA组织中的基因表达变化,并将其与非癌样本中的基因表达变化进行比较。通过针吸活检从21例PCA患者和10例良性前列腺增生(BPH)患者中采集前列腺组织样本。分离总RNA,合成cDNA,并通过微阵列方法测定基因表达水平。在向PCA进展过程中,样本中检测到738个上调基因和515个下调基因。使用Ingenuity Pathway Analysis(IPA)软件进行分析发现,466个网络和423个功能-通路相关基因上调,363个网络和342个功能-通路相关基因下调。上调的网络围绕白细胞介素-1β(IL-1β)和胰岛素样生长因子-1(IGF-1)基因确定。NFKB基因处于两个上调和下调网络的中心。确定了上调的经典通路,并对其中四条进行了详细评估:急性期反应、肝纤维化、肌动蛋白细胞骨架和凝血通路。轴突导向信号是最显著下调的经典通路。我们的数据不仅提供了基因之间的网络,有助于理解PCA的生物学特性,还提供了有用的通路图谱,便于未来对疾病的理解和构建新的治疗靶点。