非酒精性脂肪性肝病相关肝细胞癌（NAFLD-HCC）的发病率和患病率在全球范围内迅速增加。本研究旨在通过整合文本挖掘、临床随访信息、转录组数据和实验验证来确定 NAFLD-HCC 肝切除术预后预测模型的生物标志物基因。从 13 个 NAFLD-HCC 和 12 个 HBV 中收集肿瘤和邻近正常肝脏样本-使用 RNA-Seq 对 HCC 患者进行测序。采用一种新颖的文本挖掘策略——可解释的基因本体指纹方法来筛选NAFLD-HCC特征基因集和细胞类型，并通过一系列实验室实验验证了结果。基于47例患者的随访信息，利用发现的关键基因建立多变量Cox回归模型计算的风险评分并进行评估。筛选与NAFLD-HCC特异性肿瘤微环境相关的差异表达基因，其中FABP4和VWF为特征之前的报道。然后基于47个样本建立了由FABP4、VWF、性别和TNM分期组成的风险预测模型。该模型显示，与低风险评分组相比，高风险评分组的总生存率较低（p = 0.0095）。本研究提供了 NAFLD-HCC 转录组图谱，并阐明我们的模型可以预测肝切除术高精度预后。© 2023。作者。

The incidence and prevalence of nonalcoholic fatty liver disease related hepatocellular carcinoma (NAFLD-HCC) are rapidly increasing worldwide. This study aimed to identify biomarker genes for prognostic prediction model of NAFLD-HCC hepatectomy by integrating text-mining, clinical follow-up information, transcriptomic data and experimental validation.The tumor and adjacent normal liver samples collected from 13 NAFLD-HCC and 12 HBV-HCC patients were sequenced using RNA-Seq. A novel text-mining strategy, explainable gene ontology fingerprint approach, was utilized to screen NAFLD-HCC featured gene sets and cell types, and the results were validated through a series of lab experiments. A risk score calculated by the multivariate Cox regression model using discovered key genes was established and evaluated based on 47 patients' follow-up information.Differentially expressed genes associated with NAFLD-HCC specific tumor microenvironment were screened, of which FABP4 and VWF were featured by previous reports. A risk prediction model consisting of FABP4, VWF, gender and TNM stage were then established based on 47 samples. The model showed that overall survival in the high-risk score group was lower compared with that in the low-risk score group (p = 0.0095).This study provided the landscape of NAFLD-HCC transcriptome, and elucidated that our model could predict hepatectomy prognosis with high accuracy.© 2023. The Author(s).