Makawita Shalini, Dimitromanolakis Apostolos, Soosaipillai Antoninus, Soleas Ireena, Chan Alison, Gallinger Steven, Haun Randy S, Blasutig Ivan M, Diamandis Eleftherios P
Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada.
BMC Cancer. 2013 Sep 3;13:404. doi: 10.1186/1471-2407-13-404.
The identification of new serum biomarkers with high sensitivity and specificity is an important priority in pancreatic cancer research. Through an extensive proteomics analysis of pancreatic cancer cell lines and pancreatic juice, we previously generated a list of candidate pancreatic cancer biomarkers. The present study details further validation of four of our previously identified candidates: regenerating islet-derived 1 beta (REG1B), syncollin (SYCN), anterior gradient homolog 2 protein (AGR2), and lysyl oxidase-like 2 (LOXL2).
The candidate biomarkers were validated using enzyme-linked immunosorbent assays in two sample sets of serum/plasma comprising a total of 432 samples (Sample Set A: pancreatic ductal adenocarcinoma (PDAC, n = 100), healthy (n = 92); Sample Set B: PDAC (n = 82), benign (n = 41), disease-free (n = 47), other cancers (n = 70)). Biomarker performance in distinguishing PDAC from each control group was assessed individually in the two sample sets. Subsequently, multiparametric modeling was applied to assess the ability of all possible two and three marker panels in distinguishing PDAC from disease-free controls. The models were generated using sample set B, and then validated in Sample Set A.
Individually, all markers were significantly elevated in PDAC compared to healthy controls in at least one sample set (p ≤ 0.01). SYCN, REG1B and AGR2 were also significantly elevated in PDAC compared to benign controls (p ≤ 0.01), and AGR2 was significantly elevated in PDAC compared to other cancers (p < 0.01). CA19.9 was also assessed. Individually, CA19.9 showed the greatest area under the curve (AUC) in receiver operating characteristic (ROC) analysis when compared to the tested candidates; however when analyzed in combination, three panels (CA19.9 + REG1B (AUC of 0.88), CA19.9 + SYCN + REG1B (AUC of 0.87) and CA19.9 + AGR2 + REG1B (AUC of 0.87)) showed an AUC that was significantly greater (p < 0.05) than that of CA19.9 alone (AUC of 0.82). In a comparison of early-stage (Stage I-II) PDAC to disease free controls, the combination of SYCN + REG1B + CA19.9 showed the greatest AUC in both sample sets, (AUC of 0.87 and 0.92 in Sets A and B, respectively).
Additional serum biomarkers, particularly SYCN and REG1B, when combined with CA19.9, show promise as improved diagnostic indicators of pancreatic cancer, which therefore warrants further validation.
鉴定具有高灵敏度和特异性的新型血清生物标志物是胰腺癌研究的一项重要优先任务。通过对胰腺癌细胞系和胰液进行广泛的蛋白质组学分析,我们之前生成了一份胰腺癌生物标志物候选清单。本研究详细阐述了对我们之前鉴定出的四个候选物的进一步验证:再生胰岛衍生蛋白1β(REG1B)、突触融合蛋白(SYCN)、前梯度同源蛋白2(AGR2)和赖氨酰氧化酶样蛋白2(LOXL2)。
在总共432个样本的两个血清/血浆样本组中使用酶联免疫吸附测定法对候选生物标志物进行验证(样本组A:胰腺导管腺癌(PDAC,n = 100),健康者(n = 92);样本组B:PDAC(n = 82),良性疾病(n = 41),无病(n = 47),其他癌症(n = 70))。在两个样本组中分别评估生物标志物在区分PDAC与每个对照组方面的性能。随后,应用多参数建模来评估所有可能的二标志物和三标志物组合区分PDAC与无病对照的能力。模型使用样本组B生成,然后在样本组A中进行验证。
单独来看,在至少一个样本组中,与健康对照相比,所有标志物在PDAC中均显著升高(p≤0.01)。与良性对照相比,SYCN、REG1B和AGR2在PDAC中也显著升高(p≤0.01),与其他癌症相比,AGR2在PDAC中显著升高(p < 0.01)。还评估了CA19.9。单独来看,在受试者工作特征(ROC)分析中,与测试的候选物相比,CA19.9显示出最大的曲线下面积(AUC);然而,当进行联合分析时,三个组合(CA19.9 + REG1B(AUC为0.88)、CA19.9 + SYCN + REG1B(AUC为0.87)和CA19.9 + AGR2 + REG1B(AUC为0.87))显示出的AUC显著大于单独的CA19.9(AUC为