Cubiella Joaquin, Clos-Garcia Marc, Alonso Cristina, Martinez-Arranz Ibon, Perez-Cormenzana Miriam, Barrenetxea Ziortza, Berganza Jesus, Rodríguez-Llopis Isabel, D'Amato Mauro, Bujanda Luis, Diaz-Ondina Marta, Falcón-Pérez Juan M
Department of Gastroenterology, Complexo Hospitalario Universitario de Ourense, Instituto de Investigación Biomédica Ourense-Vigo-Pontevedra, 32005 Ourense, Spain.
Exosomes Laboratory, CIC bioGUNE, CIBERehd, Bizkaia Technology Park, Derio, 48160 Bizkaia, Spain.
Cancers (Basel). 2018 Sep 1;10(9):300. doi: 10.3390/cancers10090300.
Low invasive tests with high sensitivity for colorectal cancer and advanced precancerous lesions will increase adherence rates, and improve clinical outcomes. We have performed an ultra-performance liquid chromatography/time-of-flight mass spectrometry (UPLC-(TOF) MS)-based metabolomics study to identify faecal biomarkers for the detection of patients with advanced neoplasia. A cohort of 80 patients with advanced neoplasia (40 advanced adenomas and 40 colorectal cancers) and 49 healthy subjects were analysed in the study. We evaluated the faecal levels of 105 metabolites including glycerolipids, glycerophospholipids, sterol lipids and sphingolipids. We found 18 metabolites that were significantly altered in patients with advanced neoplasia compared to controls. The combinations of seven metabolites including ChoE(18:1), ChoE(18:2), ChoE(20:4), PE(16:0/18:1), SM(d18:1/23:0), SM(42:3) and TG(54:1), discriminated advanced neoplasia patients from healthy controls. These seven metabolites were employed to construct a predictive model that provides an area under the curve (AUC) median value of 0.821. The inclusion of faecal haemoglobin concentration in the metabolomics signature improved the predictive model to an AUC of 0.885. In silico gene expression analysis of tumour tissue supports our results and puts the differentially expressed metabolites into biological context, showing that glycerolipids and sphingolipids metabolism and GPI-anchor biosynthesis pathways may play a role in tumour progression.
对结直肠癌和晚期癌前病变具有高灵敏度的低侵入性检测将提高依从率,并改善临床结果。我们进行了一项基于超高效液相色谱/飞行时间质谱(UPLC-(TOF) MS)的代谢组学研究,以鉴定用于检测晚期肿瘤患者的粪便生物标志物。该研究分析了80例晚期肿瘤患者(40例晚期腺瘤和40例结直肠癌)和49名健康受试者组成的队列。我们评估了105种代谢物的粪便水平,包括甘油脂、甘油磷脂、甾醇脂和鞘脂。我们发现,与对照组相比,晚期肿瘤患者中有18种代谢物发生了显著变化。包括ChoE(18:1)、ChoE(18:2)、ChoE(20:4)、PE(16:0/18:1)、SM(d18:1/23:0)、SM(42:3)和TG(54:1)在内的七种代谢物的组合,可将晚期肿瘤患者与健康对照区分开来。利用这七种代谢物构建了一个预测模型,其曲线下面积(AUC)中位数为0.821。将粪便血红蛋白浓度纳入代谢组学特征可将预测模型的AUC提高到0.885。肿瘤组织的计算机基因表达分析支持了我们的结果,并将差异表达的代谢物置于生物学背景中,表明甘油脂和鞘脂代谢以及GPI锚生物合成途径可能在肿瘤进展中起作用。