Identification of novel pancreatic cancer biomarkers

描述（由申请方提供）：胰腺导管腺癌是最致命的恶性肿瘤之一。早期发现对于患者接受可能治愈的手术至关重要，但胰腺癌在最早最可治愈的阶段通常无症状。因此，识别新的预测性肿瘤生物标志物对于检测早期胰腺癌至关重要。我们将使用两阶段方法鉴定胰腺癌的新生物标志物。首先，我们将确定复制人类胰腺癌遗传学和疾病的自发小鼠模型循环中的蛋白质组变化。将在体内对遗传上易患胰腺癌的小鼠进行代谢标记，以允许对血浆蛋白质组进行定量分析。将通过多维蛋白质鉴定技术（MudPIT）分析在肿瘤发生之前和期间采集的系列血浆样本，以鉴定在疾病发作和/或进展期间升高的蛋白质。MudPIT是一个定量和高灵敏度的蛋白质组学平台，有助于发现复杂样品中差异表达的蛋白质。MudPIT数据的生物统计学分析将鉴定在小鼠疾病进展期间显示循环水平显著变化的标志物。为了鉴定人类疾病的预测标志物，将通过多反应监测（MRM）分析患者血浆中是否存在统计学相关的小鼠标志物。MRM是一种基于质谱（MS）的方法，允许同时定量样品（如血浆）中的多种目标分析物。在第二种方法中，我们将使用新的基于活性的蛋白质组学方法直接鉴定小鼠和人类肿瘤活检中的病理学相关生物标志物。这种方法将确定酶活性，其显示作为肿瘤进展的函数的统计学上有意义的变化。我们将在胰腺癌的荧光原位小鼠模型中验证酶活性的生理作用，这些酶活性通过遗传调节随疾病进展而变化。新的肿瘤相关生物标志物的鉴定可能使胰腺癌的检测在最早的阶段，并促进这种致命疾病的新的治疗策略的发展。胰腺癌的发展往往没有明显的症状，由于不存在准确和特异性的筛查测试，诊断往往为时已晚，手术是一种选择。使用两种最先进的分析方法，我们将检查血液样本和肿瘤活检，以确定在最早阶段表明胰腺癌存在的标志物。这些研究可能会产生一种基于血液的筛查测试，用于胰腺癌的早期检测，以及可能深刻影响疾病结局的新治疗策略。

DESCRIPTION (provided by applicant): Pancreatic ductal adenocarcinoma is among the most lethal malignancies. Early detection is vital for patients to receive potentially curative surgery, but pancreatic cancer is often asymptomatic at the earliest most curable stages. Thus, the identification of new predictive tumor biomarkers is essential to permit the detection of early-stage pancreatic cancer. We will identify novel biomarkers of pancreatic carcinoma using a two stage approach. First, we will identify proteomic changes in the circulation of a spontaneous mouse model that replicates human pancreatic cancer genetics and disease. Mice, genetically predisposed to pancreatic cancer, will be metabolically labeled in vivo to allow quantitative analysis of the plasma proteome. Serial plasma samples collected before and during tumor development will be analyzed by Multidimensional Protein Identification Technology (MudPIT) to identify proteins that are elevated during the onset and/or progression of disease. MudPIT is a quantitative and highly sensitive proteomics platform that facilitates the discovery of differentially expressed proteins in complex samples. Biostatistical analysis of the MudPIT data will identify markers that display a significant change in circulating levels during disease progression in the mouse. To identify predictive markers of human disease, plasma from patients will be assayed by multiple reaction monitoring (MRM) for the presence of the statistically relevant mouse markers. MRM is a mass spectrometry (MS)-based approach that allows the simultaneous quantitation of multiple target analytes in samples such as plasma. In a second approach we will directly identify pathology-associated biomarkers in murine and human tumor biopsies using a novel activity-based proteomics method. This approach will identify enzymatic activities that show statistically meaningful changes as a function of tumor progression. We will validate the physiological role of enzymatic activities that change concomitant with disease progression through genetic modulation in a fluorescence orthotopic mouse model of pancreatic cancer. Identification of novel tumor-associated biomarkers may enable detection of pancreatic cancer at the earliest stages and facilitate the development of novel therapeutic strategies for this lethal disease. Pancreatic cancer often develops without obvious symptoms and since an accurate & specific screening test does not exist, diagnosis is frequently made too late for surgery to be an option. Using two state-of-the-art analytical methods, we will examine blood samples and tumor biopsies to identify markers that indicate the presence of pancreatic cancer at the earliest stages. These studies could result in a blood-based screening test for early detection of pancreatic cancer, as well as novel therapeutic strategies that could profoundly influence disease outcome.