Metabolomic biomarkers for the diagnosis and post-transplant outcomes of AFP negative hepatocellular carcinoma.
Metabolomic biomarkers for the diagnosis and post-transplant outcomes of AFP negative hepatocellular carcinoma.
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DOI：
10.3389/fonc.2023.1072775
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发表时间：
2023
影响因子：
4.7
通讯作者：
中科院分区：
文献类型：
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作者：
甲胎蛋白（AFP）阴性的肝细胞癌（HCC）的早期诊断仍是一个关键问题.代谢组学主要涉及新的生物标志物的鉴定。本研究旨在寻找新的有效的AFP阴性肝癌标志物。共纳入147例肝移植患者，包括肝硬化患者（LC，n=25）、AFP阴性的HCC患者（NEG，n=44）和AFP> 20 ng/mL的HCC患者（POS，n=78）。本研究还招募了52名健康志愿者（HC）。对这些患者和健康志愿者的血浆进行代谢组学分析，以选择候选代谢组学生物标志物。基于随机森林分析建立了AFP阴性肝癌的新诊断模型，并鉴定了预后生物标志物。鉴定出15种差异代谢产物，能够将NEG组与LC和HC组区分开。随机森林分析和Logistic回归分析显示，PC（16：0/16：0）、PC（18：2/18：2）和SM（d18：1/18：1）是AFP阴性肝癌的独立危险因素。建立AFP阴性HCC患者的代谢物评分三指标模型，其时间依赖性受试者工作特征曲线下面积（AUROC）为0.913，并建立列线图。当评分的截断值设为1.2895时，模型的敏感性和特异性分别为0.727和0.92。该模型也适用于区分肝癌和肝硬化。值得注意的是，代谢物评分与肿瘤或机体营养参数无关，但不同嗜中性粒细胞-淋巴细胞比率（NLR）组之间的评分差异具有统计学意义（≤5 vs. >5，P=0.012）。此外，MG（18：2/0：0/0：0）是15种代谢产物中唯一的预后标志物，与AFP阴性HCC患者的无瘤生存率显著相关（HR=1.160，95%CI 1.012-1.330，P=0.033）。基于代谢组学的三标记物模型和诺模图可作为AFP阴性HCC的无创诊断工具。MG水平（18：2/0：0/0：0）对AFP阴性的HCC有较好的预后预测价值。
Early diagnosis for α-fetoprotein (AFP) negative hepatocellular carcinoma (HCC) remains a critical problem. Metabolomics is prevalently involved in the identification of novel biomarkers. This study aims to identify new and effective markers for AFP negative HCC. In total, 147 patients undergoing liver transplantation were enrolled from our hospital, including liver cirrhosis patients (LC, n=25), AFP negative HCC patients (NEG, n=44) and HCC patients with AFP over 20 ng/mL (POS, n=78). 52 Healthy volunteers (HC) were also recruited in this study. Metabolomic profiling was performed on the plasma of those patients and healthy volunteers to select candidate metabolomic biomarkers. A novel diagnostic model for AFP negative HCC was established based on Random forest analysis, and prognostic biomarkers were also identified. 15 differential metabolites were identified being able to distinguish NEG group from both LC and HC group. Random forest analysis and subsequent Logistic regression analysis showed that PC(16:0/16:0), PC(18:2/18:2) and SM(d18:1/18:1) are independent risk factor for AFP negative HCC. A three-marker model of Metabolites-Score was established for the diagnosis of AFP negative HCC patients with an area under the time-dependent receiver operating characteristic curve (AUROC) of 0.913, and a nomogram was then established as well. When the cut-off value of the score was set at 1.2895, the sensitivity and specificity for the model were 0.727 and 0.92, respectively. This model was also applicable to distinguish HCC from cirrhosis. Notably, the Metabolites-Score was not correlated to tumor or body nutrition parameters, but difference of the score was statistically significant between different neutrophil-lymphocyte ratio (NLR) groups (≤5 vs. >5, P=0.012). Moreover, MG(18:2/0:0/0:0) was the only prognostic biomarker among 15 metabolites, which is significantly associated with tumor-free survival of AFP negative HCC patients (HR=1.160, 95%CI 1.012-1.330, P=0.033). The established three-marker model and nomogram based on metabolomic profiling can be potential non-invasive tool for the diagnosis of AFP negative HCC. The level of MG(18:2/0:0/0:0) exhibits good prognosis prediction performance for AFP negative HCC.
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影响因子：
81.5
作者：
Llovet, Josep M.;Zucman-Rossi, Jessica;Gores, Gregory
通讯作者：
Gores, Gregory
影响因子：
5.5
作者：
Insausti-Urkia N;Solsona-Vilarrasa E;Garcia-Ruiz C;Fernandez-Checa JC
通讯作者：
Fernandez-Checa JC
影响因子：
3.7
作者：
Cala MP;Aldana J;Medina J;Sánchez J;Guio J;Wist J;Meesters RJW
通讯作者：
Meesters RJW
影响因子：
25.7
作者：
Sakakima, Y.;Hayakawa, A.;Nakao, A.
通讯作者：
Nakao, A.
影响因子：
7.3
作者：
Saito RF;Andrade LNS;Bustos SO;Chammas R
通讯作者：
Chammas R