Background: Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease worldwide. With an increasing number of patients, NAFLD has been identified as a risk factor for Hepatocellular Carcinoma (HCC). The precise pathophysiology of NAFLD-related HCC has not been completely understood recently. Objective: We analyzed the hub genes related to NAFLD and HCC to predict the risk of NAFLD progressing to HCC. Methods: Two datasets of NAFLD were used to identify differentially expressed genes. Lasso-Cox regression analysis was performed to determine a gene model to predict the risk of the progression from NAFLD to HCC. Three validation datasets were analyzed to evaluate the performance of the gene model, including normal and NAFLD with fibrosis, NAFLD with fibrosis and NAFLD-related HCC, and normal and NASH-related HCC. Results: Seven genes, including COL1A1, TIPM1, VCAN, FOS, CD79A, CXCL9, and VWF, were identified as the hub genes, and then a gene model was constructed. By calculating, the area under the receiver operating characteristic curves (AUCs) for risk prediction were 0.97, 0.886, and 0.751 in the three validation datasets, respectively. Gene set enrichment analysis indicated that the MAPK, TGFβ, p53, PPAR, insulin signaling pathways, and fatty acid metabolism were significantly upregulated in the high-risk group. GTPase activity and intrinsic apoptotic signaling pathway had significant upregulation in the low-risk group. Conclusion: The seven hub genes may predict the risk of NAFLD developing into HCC by mediating the potential molecular mechanism, which could be used as biomarkers for predicting the progression, diagnosis, and treatment of NAFLD.

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参与非酒精性脂肪肝向肝细胞癌进展的 Hub 基因

背景：非酒精性脂肪肝病（NAFLD）是全世界慢性肝病的最常见原因。随着患者数量的增加，NAFLD 已被确定为肝细胞癌 (HCC) 的危险因素。NAFLD 相关 HCC 的精确病理生理学最近尚未完全了解。目的：我们分析与 NAFLD 和 HCC 相关的枢纽基因，以预测 NAFLD 进展为 HCC 的风险。方法：使用 NAFLD 的两个数据集来识别差异表达基因。进行 Lasso-Cox 回归分析以确定基因模型来预测从 NAFLD 进展为 HCC 的风险。分析了三个验证数据集以评估基因模型的性能，包括正常和伴有纤维化的 NAFLD、伴有纤维化的 NAFLD 和 NAFLD 相关 HCC、以及正常和 NASH 相关 HCC。结果：确定COL1A1、TIPM1、VCAN、FOS、CD79A、CXCL9、VWF 7个基因为枢纽基因，并构建基因模型。通过计算，三个验证数据集中风险预测的受试者工作特征曲线下面积（AUC）分别为0.97、0.886和0.751。基因集富集分析表明，高危组的MAPK、TGFβ、p53、PPAR、胰岛素信号通路和脂肪酸代谢显着上调。GTPase 活性和内在凋亡信号通路在低风险组中显着上调。结论：7个hub基因可能通过介导潜在的分子机制预测NAFLD发展为HCC的风险，可作为预测NAFLD进展、诊断和治疗的生物标志物。