Department of Medicine, University of Washington, Seattle, Washington 98195, United States.
J Proteome Res. 2011 May 6;10(5):2359-76. doi: 10.1021/pr101148r. Epub 2011 Mar 28.
Pancreatic cancer is a lethal disease that is difficult to diagnose at early stages when curable treatments are effective. Biomarkers that can improve current pancreatic cancer detection would have great value in improving patient management and survival rate. A large scale quantitative proteomics study was performed to search for the plasma protein alterations associated with pancreatic cancer. The enormous complexity of the plasma proteome and the vast dynamic range of protein concentration therein present major challenges for quantitative global profiling of plasma. To address these challenges, multidimensional fractionation at both protein and peptide levels was applied to enhance the depth of proteomics analysis. Employing stringent criteria, more than 1300 proteins total were identified in plasma across 8-orders of magnitude in protein concentration. Differential proteins associated with pancreatic cancer were identified, and their relationship with the proteome of pancreatic tissue and pancreatic juice from our previous studies was discussed. A subgroup of differentially expressed proteins was selected for biomarker testing using an independent cohort of plasma and serum samples from well-diagnosed patients with pancreatic cancer, chronic pancreatitis, and nonpancreatic disease controls. Using ELISA methodology, the performance of each of these protein candidates was benchmarked against CA19-9, the current gold standard for a pancreatic cancer blood test. A composite marker of TIMP1 and ICAM1 demonstrate significantly better performance than CA19-9 in distinguishing pancreatic cancer from the nonpancreatic disease controls and chronic pancreatitis controls. In addition, protein AZGP1 was identified as a biomarker candidate for chronic pancreatitis. The discovery and technical challenges associated with plasma-based quantitative proteomics are discussed and may benefit the development of plasma proteomics technology in general. The protein candidates identified in this study provide a biomarker candidate pool for future investigations.
胰腺癌是一种致命的疾病，在早期阶段难以诊断，此时有效的治疗方法可以治愈。能够改善当前胰腺癌检测的生物标志物将在改善患者管理和生存率方面具有重要价值。进行了一项大规模的定量蛋白质组学研究，以寻找与胰腺癌相关的血浆蛋白变化。血浆蛋白质组的巨大复杂性和蛋白质浓度的巨大动态范围对血浆的定量全局分析构成了重大挑战。为了解决这些挑战，在蛋白质和肽水平上应用了多维分级分离，以增强蛋白质组学分析的深度。采用严格的标准，在蛋白质浓度的 8 个数量级范围内总共鉴定出超过 1300 种蛋白质。鉴定出与胰腺癌相关的差异蛋白，并讨论了它们与我们之前研究中胰腺组织和胰液的蛋白质组的关系。选择了一组差异表达蛋白作为生物标志物进行测试，使用来自已确诊的胰腺癌、慢性胰腺炎和非胰腺疾病对照患者的独立血浆和血清样本队列。使用 ELISA 方法，针对这些蛋白质候选物中的每一个，与当前胰腺癌血液检测的金标准 CA19-9 进行了性能基准测试。TIMP1 和 ICAM1 的组合标志物在区分胰腺癌与非胰腺疾病对照和慢性胰腺炎对照方面的性能明显优于 CA19-9。此外，还鉴定出蛋白质 AZGP1 是慢性胰腺炎的生物标志物候选物。讨论了与基于血浆的定量蛋白质组学相关的发现和技术挑战，这可能有益于一般的血浆蛋白质组学技术的发展。本研究中鉴定的蛋白质候选物为未来的研究提供了一个生物标志物候选物池。
