Park Jisook, Lee Eunjung, Park Kyoung-Jin, Park Hyung-Doo, Kim Jong-Won, Woo Hye In, Lee Kwang Hyuck, Lee Kyu-Taek, Lee Jong Kyun, Park Joon-Oh, Park Young Suk, Heo Jin Seok, Choi Seong Ho, Choi Dong Wook, Jang Kee-Taek, Lee Soo-Youn
Samsung Biomedical Research Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Division of Genetics and Genomics, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.
Oncotarget. 2017 Jun 27;8(26):42761-42771. doi: 10.18632/oncotarget.17463.
We performed an integrated analysis of proteomic and transcriptomic datasets to develop potential diagnostic markers for early pancreatic cancer. In the discovery phase, a multiple reaction monitoring assay of 90 proteins identified by either gene expression analysis or global serum proteome profiling was established and applied to 182 clinical specimens. Nine proteins (P < 0.05) were selected for the independent validation phase and quantified using stable isotope dilution-multiple reaction monitoring-mass spectrometry in 456 specimens. Of these proteins, four proteins (apolipoprotein A-IV, apolipoprotein CIII, insulin-like growth factor binding protein 2 and tissue inhibitor of metalloproteinase 1) were significantly altered in pancreatic cancer in both the discovery and validation phase (P < 0.01). Moreover, a panel including carbohydrate antigen 19-9, apolipoprotein A-IV and tissue inhibitor of metalloproteinase 1 showed better performance for distinguishing early pancreatic cancer from pancreatitis (Area under the curve = 0.934, 86% sensitivity at fixed 90% specificity) than carbohydrate antigen 19-9 alone (71% sensitivity).Overall, we present the panel of robust biomarkers for early pancreatic cancer diagnosis through bioinformatics analysis that combined transcriptomic and proteomic data as well as rigorous validation on a large number of independent clinical samples.
我们对蛋白质组学和转录组学数据集进行了综合分析,以开发早期胰腺癌的潜在诊断标志物。在发现阶段,建立了针对通过基因表达分析或全球血清蛋白质组分析鉴定出的90种蛋白质的多反应监测分析方法,并将其应用于182份临床标本。选择了9种蛋白质(P<0.05)进入独立验证阶段,并在456份标本中使用稳定同位素稀释-多反应监测-质谱法进行定量。在这些蛋白质中,有4种蛋白质(载脂蛋白A-IV、载脂蛋白CIII、胰岛素样生长因子结合蛋白2和金属蛋白酶组织抑制剂1)在发现阶段和验证阶段的胰腺癌中均有显著变化(P<0.01)。此外,与单独的糖类抗原19-9(敏感性71%)相比,包含糖类抗原19-9、载脂蛋白A-IV和金属蛋白酶组织抑制剂1的检测组合在区分早期胰腺癌和胰腺炎方面表现更佳(曲线下面积=0.934,在固定90%特异性时敏感性为86%)。总体而言,我们通过生物信息学分析展示了用于早期胰腺癌诊断的强大生物标志物组合,该分析结合了转录组学和蛋白质组学数据以及对大量独立临床样本的严格验证。