Prostate Tumor Diagnosis:Blood Cell Multigene Signatures

描述（由申请人提供）：目前的前列腺癌筛查和风险评估技术，作为手术活检的先决条件，是基于个体血清生物标志物或循环恶性细胞中个体基因表达的测量。这些技术具有许多局限性，包括诊断缺乏特异性和准确性，以及缺乏详细的预后信息。由此产生的大量假阳性诊断导致了大量不必要的手术活检。有证据表明，患有前列腺癌和其他形式恶性疾病的个体表现出的免疫反应可以在外周血循环中白细胞基因表达改变的水平上检测到。在循环白细胞中，一些个体基因的mRNA转录物的定量已经证明了基因表达水平与肿瘤存在之间的关联。此外，研究表明，血清中单个蛋白的水平与白细胞中的差异基因表达有一定程度的相关性，可以提供肿瘤分期的一些信息。我们已经启动了一项初步研究，以测量白细胞中的基因表达，并产生了与先前报告一致的初步数据。我们进一步记录了使用算法对前列腺癌患者和健康对照进行分类。在具体目标一下，我们将收集和处理前列腺癌患者和健康对照者的血液。然后，我们将采用微阵列技术同时测量来自前列腺癌患者和对照受试者血液中的白细胞中多达14,000个基因的表达水平，并采用数据分析算法来确定每个受试者组特异性的基因表达模式。通过这项技术，我们建议研究我们的中心假设：患有前列腺癌的个体在其外周血白细胞中表现出一种保守的基因表达水平模式，这与对照组外周血白细胞的表达模式不同。在Specific Aim 2中，我们将进一步验证以下假设：不同组织学分级的前列腺肿瘤患者会产生不同的表达特征，反映肿瘤的生物学分期和侵袭性，从而可以用于区分不同病理分期的肿瘤。我们相信，我们建议开发的诊断技术最终可能会形成临床检测的基础，在患者不适最小的情况下，有能力识别前列腺癌患者，并提供重要的分期特异性信息。

DESCRIPTION (provided by applicant): Current techniques for the screening and risk assessment of prostate cancer, as a prerequisite to surgical biopsy, are based upon measurements of either individual serum biomarkers, or of expression of individual genes in circulating malignant cells. These techniques possess a number of limitations, including lack of specificity and accuracy in diagnosis, and a lack of detailed prognostic information. The resultant high numbers of false positive diagnoses lead to numerous unnecessary surgical biopsies. There is evidence that individuals with prostate cancer and other forms of malignant disease exhibit immune responses that can be detected at the level of altered gene expression in leukocytes circulating in peripheral blood. Quantitation of the mRNA transcripts in circulating leukocytes of a number of individual genes has demonstrated an association between gene expression level and the presence of a tumor. Furthermore, it has been shown that serum levels of individual proteins, which exhibit a degree of correlation with differential gene expression in leukocytes, provide some information on tumor stage. We have initiated a pilot study to measure gene expression in leukocytes and have produced initial data that concurs with previous reports. We have further documented the use of algorithms to classify prostate cancer patients and healthy controls. Under Specific Aim One, we will collect and process blood from prostate cancer patients and healthy control subjects. We will then employ microarray technology to measure simultaneously the expression levels of up to 14,000 genes transcribed in leukocytes derived from the blood of prostate cancer patients and control subjects, and employ data analysis algorithms to determine patterns of gene expression specific for each subject group. With this technology we propose to investigate our central hypothesis: that individuals suffering from prostate cancer exhibit a conserved pattern of gene expression levels in their peripheral blood leukocytes, which is distinct from the pattern of expression in peripheral blood leukocytes from control subjects. Under Specific Aim Two, we will test the further hypothesis that cancer patients with prostate tumors at different histological grades will yield distinct expression signatures that reflect the biological stage and aggressiveness of the tumor, and that can thus be employed to differentiate among tumors at different pathological stages. We believe that the diagnostic technique we propose to develop may ultimately form the basis of a clinical assay that will, with a minimum of patient discomfort, have the capacity to identify men with prostate cancer, and also provide important stage-specific information.