Puig-Costa Manuel, Codina-Cazador Antonio, Cortés-Pastoret Elisabet, Oliveras-Ferraros Cristina, Cufí Sílvia, Flaquer Sílvia, Llopis-Puigmarti Francesca, Pujol-Amado Eulalia, Corominas-Faja Bruna, Cuyàs Elisabet, Ortiz Rosa, Lopez-Bonet Eugeni, Queralt Bernardo, Guardeño Raquel, Martin-Castillo Begoña, Roig Josep, Joven Jorge, Menendez Javier A
Department of General and Digestive Surgery, Dr. Josep Trueta University Hospital, Catalonia, Spain.
Oncotarget. 2014 Apr 15;5(7):1942-54. doi: 10.18632/oncotarget.1879.
This study aimed to improve gastric cancer (GC) diagnosis by identifying and validating an INflammatory PROtein-driven GAstric cancer Signature (hereafter INPROGAS) using low-cost affinity proteomics. The detection of 120 cytokines, 43 angiogenic factors, 41 growth factors, 40 inflammatory factors and 10 metalloproteinases was performed using commercially available human antibody microarray-based arrays. We identified 21 inflammation-related proteins (INPROGAS) with significant differences in expression between GC tissues and normal gastric mucosa in a discovery cohort of matched pairs (n=10) of tumor/normal gastric tissues. Ingenuity pathway analysis confirmed the "inflammatory response", "cellular movement" and "immune cell trafficking" as the most overrepresented biofunctions within INPROGAS. Using an expanded independent validation cohort (n = 22), INPROGAS classified gastric samples as "GC" or "non-GC" with a sensitivity of 82% (95% CI 59-94) and a specificity of 73% (95% CI 49-89). The positive predictive value and negative predictive value in this validation cohort were 75% (95% CI 53-90) and 80% (95% CI 56-94), respectively. The positive predictive value and negative predictive value in this validation cohort were 75% (95% CI 53-90) and 80% (95% CI 56-94), respectively. Antibody microarray analyses of the GC-associated inflammatory proteome identified a 21-protein INPROGAS that accurately discriminated GC from noncancerous gastric mucosa.
本研究旨在通过使用低成本亲和蛋白质组学鉴定并验证一种由炎症蛋白驱动的胃癌特征(以下简称INPROGAS),以改善胃癌(GC)的诊断。使用基于市售人类抗体微阵列的芯片检测120种细胞因子、43种血管生成因子、41种生长因子、40种炎症因子和10种金属蛋白酶。我们在一个由肿瘤/正常胃组织匹配对(n = 10)组成的发现队列中,鉴定出21种炎症相关蛋白(INPROGAS),其在GC组织和正常胃黏膜之间的表达存在显著差异。 Ingenuity通路分析证实,“炎症反应”、“细胞运动”和“免疫细胞迁移”是INPROGAS中最显著的生物功能。使用一个扩大的独立验证队列(n = 22),INPROGAS将胃样本分类为“GC”或“非GC”,灵敏度为82%(95% CI 59 - 94),特异性为73%(95% CI 49 - 89)。该验证队列中的阳性预测值和阴性预测值分别为75%(95% CI 53 - 90)和80%(95% CI 56 - 94)。该验证队列中的阳性预测值和阴性预测值分别为75%(95% CI 53 - 90)和80%(95% CI 56 - 94)。对与GC相关的炎症蛋白质组进行抗体微阵列分析,鉴定出一种21蛋白的INPROGAS,它能准确地区分GC和非癌性胃黏膜。