Department of Oncology, Affiliated Hospital of Nantong University, Nantong, 226001, People's Republic of China.
Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, Nantong, 226001, People's Republic of China.
Eur J Med Res. 2023 Mar 15;28(1):123. doi: 10.1186/s40001-023-01091-w.
An immune-related gene signature (IGS) was established for discriminating prognosis, predicting benefit of immunotherapy, and exploring therapeutic options in hepatocellular carcinoma (HCC).
Based on Immune-related hub genes and The Cancer Genome Atlas (TCGA) LIHC dataset (n = 363), an immune-related gene signature (IGS) was established by least absolute shrinkage and selection operator (LASSO) analysis. The prognostic significance and clinical implications of IGS were verified in International Cancer Genome Consortium (ICGC) and Chinese HCC (CHCC) cohorts. The molecular and immune characteristics and the benefit of immune checkpoint inhibitor (ICI) therapy in IGS-defined subgroups were analyzed. In addition, by leveraging the Cancer Therapeutics Response Portal (CTRP) and PRISM Repurposing datasets, we determined the potential therapeutic agents for high IGS-risk patients.
The IGS was constructed based on 8 immune-related hub genes with individual coefficients. The IGS risk model could robustly predict the survival of HCC patients in TCGA, ICGC, and CHCC cohorts. Compared with 4 previous established immune genes-based signatures, IGS exhibited superior performance in survival prediction. Additionally, for immunological characteristics and enriched pathways, a low-IGS score was correlated with IL-6/JAK/STAT3 signaling, inflammatory response and interferon α/γ response pathways, low TP53 mutation rate, high infiltration level, and more benefit from ICI therapy. In contrast, high IGS score manifested an immunosuppressive microenvironment and activated aggressive pathways. Finally, by in silico screening potential compounds, vindesine, ispinesib and dasatinib were identified as potential therapeutic agents for high-IGS risk patients.
This study developed a robust IGS model for survival prediction of HCC patients, providing new insights into integrating tailored risk stratification with precise immunotherapy and screening potentially targeted agents.
建立了一个免疫相关基因特征（IGS），用于区分预后、预测免疫治疗的获益，并探索肝细胞癌（HCC）的治疗选择。
基于免疫相关枢纽基因和癌症基因组图谱（TCGA）LIHC 数据集（n=363），通过最小绝对收缩和选择算子（LASSO）分析建立免疫相关基因特征（IGS）。在国际癌症基因组联盟（ICGC）和中国 HCC（CHCC）队列中验证 IGS 的预后意义和临床意义。分析 IGS 定义亚组的分子和免疫特征以及免疫检查点抑制剂（ICI）治疗的获益。此外，通过利用癌症治疗反应门户（CTRP）和 PRISM 再利用数据集，我们确定了高 IGS 风险患者的潜在治疗药物。
IGS 是基于 8 个具有个体系数的免疫相关枢纽基因构建的。IGS 风险模型可以在 TCGA、ICGC 和 CHCC 队列中稳健地预测 HCC 患者的生存。与之前建立的 4 个基于免疫基因的特征相比，IGS 在生存预测方面表现出更好的性能。此外，对于免疫特征和富集途径，低 IGS 评分与 IL-6/JAK/STAT3 信号、炎症反应和干扰素α/γ反应途径、低 TP53 突变率、高水平浸润和更多 ICI 治疗获益相关。相反，高 IGS 评分表现出免疫抑制微环境和激活侵袭性途径。最后，通过计算机筛选潜在化合物，长春碱、异长春花碱和达沙替尼被确定为高 IGS 风险患者的潜在治疗药物。
本研究建立了一个用于 HCC 患者生存预测的稳健 IGS 模型，为整合个体化风险分层与精准免疫治疗以及筛选潜在靶向药物提供了新的见解。
