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首页> 外文期刊>Journal of proteome research >Identification of a Collagen Marker in Urine Improves the Detection of Colorectal Liver Metastases
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Identification of a Collagen Marker in Urine Improves the Detection of Colorectal Liver Metastases

机译:尿液中胶原蛋白标志物的鉴定改善了结直肠肝转移的检测

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Previously, we reported a combination of an urine collagen alpha-1(I) natural occurring peptide (NOP) AGPP(-OH)GEAGKP(-OH)GEQGVP(-OH)GDLGAP(-OH)GP (AGP) and serum carcinoembryonic antigen (CEA) to have the potential to detect colorectal liver metastasis (CRLM). The combined method requires further adaption for better sensitivity and specificity prior to clinical implementation. This mass spectrometry study aimed to identify additional collagen NOPs in urine and determine the most discriminating NOP panel. We improved the combined method on the basis of analysis of urine samples from 100 healthy controls and 100 CRLM patients. Two additional NOPs were identified: GPPGEAGK(-OH)P(-OH)GEQGVP(-OH)GDLGAP(-OH)GP (GPP), collagen alpha-1(I), and GNDGARGSDGQPGPP(-OH)GP(-OH)P(-OH)GTAGFP(-OH)GSP(-OH)GAK(-OH)GEVGP (GND), collagen alpha-1(III). A molecular model combining NOPs (AGP, GPP, and GND) and CEA was generated. Molecules that did not contribute significantly were removed, resulting in a model consisting of GND and CEA. With this model, 88% sensitivity and 88% specificity were reached in the discovery set and 75% sensitivity and 100% specificity in the validation set (control, n = 12; CRLM, n = 10). The AUC of the ROC curve is significantly higher than the current model based on AGP and CEA (p = 3.3 x 10(-4)). The new model performs better than the currently used techniques in the clinic that have a 57-70% sensitivity and a 90-96% specificity.
机译:以前,我们报道了尿胶原α-1(i)天然发生的肽(NOP)AGPP(-OH)GEAGKP(-OH)GEQGVP(-OH)GP(-OH)GP(AGP)和血清癌胚抗原的组合(CEA)有可能检测结肠直肠肝转移(CRLM)。组合方法需要进一步适应临床实施之前更好的敏感性和特异性。该质谱研究旨在鉴定尿液中额外的胶原NOP,并确定最辨别的NOP面板。我们基于从100种健康对照和100名CRLM患者的尿液样本的分析来改善组合方法。鉴定了两种额外的NOP:GPPGeagk(-OH)P(-OH)GEQGVP(-OH)GDLGAP(-OH)GP(GPP),胶原α-1(I)和GNDGARGSDGQPGPP(-OH)GP(-OH) P(-OH)GTAGFP(-OH)GSP(-OH)GAK(-OH)GAK(GND),胶原醛α-1(III)。将NOPS(AGP,GPP和GND)和CEA组合的分子模型。除去没有显着贡献的分子,导致由GND和CEA组成的模型。通过该模型,在发现集中达到88%的灵敏度和88%的特异性,验证集中的75%灵敏度和100%特异性(控制,n = 12; CRLM,n = 10)。 ROC曲线的AUC显着高于基于AGP和CEA的电流模型(P = 3.3×10(-4))。新模型比临床中的目前使用的技术更好,具有57-70%的灵敏度和90-96%的特异性。

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