DataSheet_2_Development and Validation of Nomograms Based on Gamma-Glutamyl Transpeptidase to Platelet Ratio for Hepatocellular Carcinoma Patients Reveal Novel Prognostic Value and the Ratio Is Negatively Correlated With P38MAPK Expression.csv

BackgroundEarly prediction of recurrence and death risks is significant to the treatment of hepatocellular carcinoma (HCC) patients. We aimed to develop and validate prognosis nomogram models based on the gamma-glutamyl transpeptidase (GGT)-to-platelet (PLT) ratio (GPR) for HCC and to explore the relationship between the GPR and inflammation-related signaling pathways.
MethodsAll data were obtained from 2000 to 2012 in the Affiliated Hospital of Qingdao University. In the training cohort, factors included in the nomograms were determined by univariate and multivariate analyses. In the training and validation cohorts, the concordance index (C-index) and calibration curves were used to assess predictive accuracy, and receiver operating characteristic curves were used to assess discriminative ability. Clinical utility was evaluated using decision curve analysis. Moreover, improvement of the predictive accuracy of the nomograms was evaluated by calculating the decision curve analysis, the integrated discrimination improvement, and the net reclassification improvement. Finally, the relationship between the GPR and inflammation-related signaling pathways was evaluated using the independent-samples t-test.
ResultsA larger tumor size and higher GPR were common independent risk factors for both disease-free survival (DFS) and overall survival (OS) in HCC (P < 0.05). Good agreement between our nomogram models’ predictions and actual observations was detected by the C-index and calibration curves. Our nomogram models showed significantly better performance in predicting the HCC prognosis compared to other models (P < 0.05). Online webserver and scoring system tables were built based on the proposed nomogram for convenient clinical use. Notably, including the GPR greatly improved the predictive ability of our nomogram models (P < 0.05). In the validation cohort, p38 mitogen-activated protein kinase (P38MAPK) expression was significantly negatively correlated with the GPR (P < 0.01) and GGT (P = 0.039), but was not correlated with PLT levels (P = 0.063). And we found that P38MAPK can regulate the expression of GGT by quantitative real-time PCR and Western blotting experiments.
ConclusionsThe dynamic nomogram based on the GPR provides accurate and effective prognostic predictions for HCC, and P38MAPK-GGT may be a suitable therapeutic target to improve the prognosis of HCC patients.

背景 早期预测复发与死亡风险对肝细胞癌（hepatocellular carcinoma, HCC）患者的诊疗具有重要临床意义。本研究旨在基于γ-谷氨酰转肽酶（gamma-glutamyl transpeptidase, GGT）与血小板（platelet, PLT）比值（GPR）构建并验证肝细胞癌预后列线图模型，并探讨GPR与炎症相关信号通路的潜在关联。方法 本研究所有数据采集自2000年至2012年青岛大学附属医院队列。在训练队列中，列线图纳入的危险因素通过单因素与多因素分析确定。在训练队列与验证队列中，分别采用一致性指数（concordance index, C-index）与校准曲线评估预测准确性，受试者工作特征曲线评估模型区分能力；通过决策曲线分析评价临床应用价值。此外，通过决策曲线分析、综合判别改善指数（integrated discrimination improvement, IDI）以及净重新分类指数（net reclassification improvement, NRI），评估列线图预测准确性的提升效果。最后，采用独立样本t检验分析GPR与炎症相关信号通路的关联。结果 研究显示，更大的肿瘤体积与更高的GPR是肝细胞癌无病生存期（disease-free survival, DFS）与总生存期（overall survival, OS）共同的独立危险因素（P < 0.05）。一致性指数与校准曲线结果表明，本研究构建的列线图预测值与实际观测值具有良好的一致性。相较于其他同类模型，本研究列线图在肝细胞癌预后预测中表现更优（P < 0.05）。基于本研究提出的列线图，我们搭建了在线网页工具与评分系统表格，以方便临床推广应用。值得注意的是，纳入GPR可显著提升列线图的预测能力（P < 0.05）。在验证队列中，p38丝裂原活化蛋白激酶（p38 mitogen-activated protein kinase, P38MAPK）的表达与GPR（P < 0.01）及GGT（P = 0.039）呈显著负相关，而与PLT水平无明显关联（P = 0.063）。通过实时定量聚合酶链反应与蛋白质印迹实验，我们证实P38MAPK可调控GGT的表达。结论 基于GPR构建的动态列线图可为肝细胞癌患者提供精准有效的预后预测，且P38MAPK-GGT轴或许可作为改善肝细胞癌患者预后的潜在治疗靶点。