基于氨死亡特征的多组学分子分型构建肝癌患者预后模型，探讨肿瘤微环境（TME）重塑机制与精准治疗策略。

本研究整合癌症基因组图谱（TCGA）、国际癌症基因组联盟（ICGC）队列的常规转录组及多个单细胞转录组测序（scRNA-seq）数据集。首先利用单样本基因集富集分析（ssGSEA）量化样本的氨死亡通路活性，并结合加权基因共表达网络分析（WGCNA）鉴定关键氨死亡基因模块；随后最小绝对收缩与选择算子（Lasso）回归构建风险评分预后模型。进一步联合多种免疫浸润算法、单细胞调控网络（SCENIC）、细胞通讯推断（CellChat）及靶向药物敏感性预测，系统解析高风险TME的“内皮-髓系”免疫排斥重塑机制及合成致死干预靶点。相关性分析采用Pearson或Spearman相关系数。生存分析采用Kaplan-Meier法和Log-rank检验。

本研究基于TCGA-LIHC队列的371例样本数据，聚类分析共识别出17个基因共表达模块。将其中两个关键模块内的1 073个基因定义为氨死亡候选基因。功能富集分析显示，上述候选基因在生物学功能上与免疫调节密切相关。基于氨死亡相关基因成功构建具有独立预后价值的氨死亡风险评分预后模型，ROC分析显示该模型具有良好的预测效能，其预测肝癌1、3、5年生存率的AUC分别为0.855、0.824和0.787。ICGC队列外部验证证实了该模型在识别高侵袭性肝癌亚群及预后风险分层方面具有良好的跨队列一致性。高风险表型以TP53突变驱动的基因组不稳定性为主；TME呈现符合“免疫排斥”表型的宏观特征，存在“内皮-髓系”免疫排斥屏障，CD4⁺ 中央记忆T细胞（CD4⁺ Tcm）浸润明显下调；以单核细胞谱系为代表的抑制性髓系细胞明显上调，成纤维细胞及平滑肌细胞的浸润得分明显上调。TME内CD8⁺ T细胞处于未激活的静息状态，表现为终末效应亚群比例明显下调，而过渡态与初始态细胞相对富集。调控网络提示，高风险内皮细胞中MYC的异常激活可能通过ANGPTL/JAM信号轴促进髓系细胞招募，参与构筑物理与免疫双重屏障。治疗策略方面，高风险亚型肝癌对WEE1抑制剂（adavosertib）展现出明显的潜在敏感性。

本研究构建了具有独立预后价值的氨死亡相关肝癌预后模型，该模型能够有效识别伴有TP53突变的高侵袭性肝癌亚型。高风险组肝癌的TME呈现典型的“内皮-髓系”免疫排斥特征，且伴随CD8⁺ T细胞的激活阻滞现象。WEE1抑制剂有望成为高风险肝癌患者的潜在靶向干预药物。

To construct a prognostic model for patients with hepatocellular carcinoma (HCC) based on multi-omics subtyping of ammonia-induced cell death features, and to explore the mechanism of tumor microenvironment (TME) remodeling and precision treatment strategy.

In this study, The Cancer Genome Atlas (TCGA), conventional transcriptome of International Cancer Genome Consortium (ICGC) cohort and multiple single-cell RNA sequencing (scRNA-seq) datasets were integrated. Firstly, the activity of ammonia-induced cell death pathway of samples was quantified by single-sample gene set enrichment analysis (ssGSEA), and the modules of key ammonia-induced cell death genes were identified by weighted gene co-expression network analysis (WGCNA). The risk scoring prognostic model was constructed by the least absolute shrinkage and selection operator (Lasso) regression analysis. Multiple immune infiltration algorithms, SCENIC, CellChat and drug sensitivity prediction were employed to systematically analyze the "endothelial-myeloid" immune rejection remodeling mechanism of high-risk TME and synthesize lethal intervention targets. Correlation analysis was conducted by Pearson or Spearman correlation coefficients. Survival analysis was performed by Kaplan-Meier method and Log-rank test.

Based on the sample data of 371 cases in TCGA-LIHC cohort, 17 gene co-expression modules were identified by cluster analysis. 1 073 genes in two key modules were defined as candidate genes of ammonia-induced cell death. Functional enrichment analysis showed that the above candidate genes were closely associated with immune regulation in biological function. Based on the genes related to ammonia-induced cell death, a risk scoring prognostic model of ammonia-induced cell death with independent prognostic value was successfully constructed. ROC analysis demonstrated that the model possessed high predictive efficiency. The area under the ROC curve (AUC) for predicting the 1-, 3-and 5-year survival rates of liver cancer was 0.855, 0.824 and 0.787, respectively. External validation of ICGC cohort confirmed that the model showed high cross-cohort consistency in identifying highly-invasive liver cancer subgroups and prognostic risk stratification. High-risk phenotype was mainly characterized with genomic instability driven by TP53 mutation. TME was characterized with "immune rejection" phenotype, with an "endothelial-myeloid" immune rejection barrier. The infiltration of CD4⁺ central memory T cells (CD4⁺ Tcm) was significantly down-regulated. Inhibitory myeloid cells represented by monocyte lineage were significantly up-regulated, and the infiltration scores of fibroblasts and smooth muscle cells were also significantly up-regulated. CD8⁺ T cells in TME were in an inactive resting state, manifested with a significant decrease in the proportion of terminal effector subsets and relative enrichment of transitional and naive cells. The regulatory network suggested that abnormal activation of MYC in high-risk endothelial cells promoted the recruitment of myeloid cells probably through the ANGPTL/JAM signal axis and participated in the construction of physical and immune barriers. In terms of therapeutic strategies, HCC patients of high-risk subtypes showed significant potential sensitivity to WEE1 inhibitors (adavosertib).

In this study, a risk scoring prognostic model of ammonia-induced cell death with independent prognostic value is established, which can effectively identify high-risk HCC subtypes with TP53 mutation. TME in the high-risk group is characterized with typical "endothelial-myeloid" immune rejection, accompanied by activation blockade of CD8⁺ T cells. WEE1 inhibitors are expected to become potential targeted interventional drugs for high-risk patients.