Shi Qingmiao, Jiang Shuwen, Zeng Yifan, Yuan Xin, Zhang Yaqi, Chu Qingfei, Xue Chen, Li Lanjuan
State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, China.
J Transl Int Med. 2025 Jan 10;12(6):553-568. doi: 10.1515/jtim-2024-0020. eCollection 2024 Dec.
Prior studies have highlighted an escalating global burden of hepatocellular carcinoma (HCC). The Notch signaling pathway regulates the initiation and development of HCC and determines the HCC prognosis.
The expression data of genes related to the Notch signaling pathway were acquired from public databases. To filter prognostic gene signatures and establish the risk model, the analyses of consensus clustering, least absolute shrinkage and selection operator (LASSO), and multivariate Cox were conducted. Subsequently, the risk stratification was optimized using a decision tree and nomogram. The immune landscapes were revealed utilizing the single-sample gene set enrichment analysis, and tumor immune dysfunction and exclusion score.
According to the mRNA expression profile of Notch signaling pathway-related genes, HCC patients were stratified to three clusters, which have different survival probability and immune infiltration characteristic. Subsequently, we developed a risk model based on five prognostic Notch signaling-related gene signatures (SPP1, SMG5, HMMR, PLOD2, and CFHR4). The model demonstrated an accurate estimation of overall survival, revealing alterations in immune status and immunotherapy sensitivity among HCC patients with different risk scores.
This study constructed a Notch signaling pathway-related prognostic model, offering valuable insights for the assessment of immune characteristics and immunotherapy responses in HCC patients.
先前的研究强调了全球肝细胞癌(HCC)负担不断加重。Notch信号通路调节HCC的发生和发展,并决定HCC的预后。
从公共数据库获取与Notch信号通路相关的基因表达数据。为筛选预后基因特征并建立风险模型,进行了一致性聚类分析、最小绝对收缩和选择算子(LASSO)分析以及多变量Cox分析。随后,使用决策树和列线图对风险分层进行优化。利用单样本基因集富集分析以及肿瘤免疫功能障碍和排除评分来揭示免疫景观。
根据Notch信号通路相关基因的mRNA表达谱,将HCC患者分为三个簇,它们具有不同的生存概率和免疫浸润特征。随后,我们基于五个与Notch信号相关的预后基因特征(SPP1、SMG5、HMMR、PLOD2和CFHR4)建立了一个风险模型。该模型对总生存期进行了准确估计,揭示了不同风险评分的HCC患者免疫状态和免疫治疗敏感性的变化。
本研究构建了一个与Notch信号通路相关的预后模型,为评估HCC患者的免疫特征和免疫治疗反应提供了有价值的见解。