Expression data from Normal Prostate Tissue Adjacent to Tumor. Homo sapiens

Prostate cancer is characterized by heterogeneity in the clinical course that often does not to correlate with morphologic features of the tumor. Metastasis reflects the most adverse outcome of prostate cancer, and to date there are no reliable morphologic features or serum biomarkers that can reliably predict which patients are at higher risk of developing metastatic disease. Understanding the differences in the biology of metastatic and organ confined primary tumors is essential for developing new prognostic markers and therapeutic targets. Using Affymetrix oligonucleotide arrays, we analyzed gene expression profiles of 24 androgen-ablation resistant metastatic samples obtained from 4 patients and a previously published dataset of 64 primary prostate tumor samples. Differential gene expression was analyzed after removing potentially uninformative stromal genes, addressing the differences in cellular content between primary and metastatic tumors. The metastatic samples are highly heterogeneous in expression; however, differential expression analysis shows that 415 genes are upregulated and 364 genes are downregulated at least 2 fold in every patient with metastasis. The expression profile of metastatic samples reveals changes in expression of a unique set of genes representing both the androgen ablation related pathways and other metastasis related gene networks such as cell adhesion, bone remodeling and cell cycle. The differentially expressed genes include metabolic enzymes, transcription factors such as Forkhead Box M1 (FoxM1) and cell adhesion molecules such as Osteopontin (SPP1). We hypothesize that these genes have a role in the biology of metastatic disease and that they represent potential therapeutic targets for prostate cancer. Keywords: disease state analysis Overall design: Using Affymetrix oligonucleotide arrays, we analyzed gene expression profiles of 24 androgen-ablation resistant metastatic samples obtained from 4 patients and a previously published dataset of 64 primary prostate tumor samples. Differential gene expression was analyzed after removing potentially uninformative stromal genes, addressing the differences in cellular content between primary and metastatic tumors.

前列腺癌的临床进程具有显著异质性，且该异质性通常与肿瘤的形态学特征无明显关联。转移是前列腺癌最凶险的转归结局，截至目前尚无可靠的形态学特征或血清生物标志物，能够精准预测哪些患者发生转移性疾病的风险更高。明确转移性前列腺癌与器官局限性原发肿瘤的生物学差异，对于开发新型预后标志物及治疗靶点至关重要。
本研究采用阿菲曼特寡核苷酸芯片（Affymetrix oligonucleotide arrays），对4名患者的24份雄激素剥夺抵抗（androgen-ablation resistant）转移性样本，以及已发表的64份原发性前列腺肿瘤样本数据集的基因表达谱进行了分析。在去除可能无信息价值的基质基因后，对差异基因表达进行分析，以校正原发肿瘤与转移性肿瘤之间的细胞组成差异。
转移性样本的基因表达存在高度异质性，但差异表达分析显示，在所有转移性患者样本中，共有415个基因上调、364个基因至少下调2倍。转移性样本的表达谱揭示了一组独特基因的表达变化，这些基因既涉及雄激素剥夺相关通路，也涵盖细胞黏附、骨重塑、细胞周期等其他与转移相关的基因网络。差异表达基因包括代谢酶、转录因子（如叉头框蛋白M1（Forkhead Box M1，FoxM1））以及细胞黏附分子（如骨桥蛋白（Osteopontin，SPP1））。
本研究推测，上述基因在转移性疾病的生物学进程中发挥关键作用，同时可作为前列腺癌潜在的治疗靶点。
关键词：疾病状态分析
整体实验设计：采用阿菲曼特寡核苷酸芯片（Affymetrix oligonucleotide arrays），对4名患者的24份雄激素剥夺抵抗转移性样本，以及已发表的64份原发性前列腺肿瘤样本数据集的基因表达谱进行分析。在去除可能无信息价值的基质基因后，对差异基因表达进行分析，以校正原发肿瘤与转移性肿瘤之间的细胞组成差异。