Integrated analysis reveals an immune evasion prognostic signature for predicting the overall survival in patients with hepatocellular carcinoma.

IF 6 2区 医学 Q1 ONCOLOGY Cancer Cell International Pub Date : 2025-03-18 DOI:10.1186/s12935-025-03743-9
Jiahua Wen, Kai Wen, Meng Tao, Zhenyu Zhou, Xing He, Weidong Wang, Zian Huang, Qiaohong Lin, Huoming Li, Haohan Liu, Yongcong Yan, Zhiyu Xiao
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Abstract

Background: The development of immunotherapy has enriched the treatment of hepatocellular carcinoma (HCC), but the efficacy is not as expected, which may be due to immune evasion. Immune evasion is related to the immune microenvironment of HCC, but there is little research on it.

Methods: We employed unsupervised clustering analysis to categorize patients from TCGA based on 182 immune evasion-related genes (IEGs). We utilized single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT to calculate differences in immune cell infiltration between clusters. The differences in immune cells and immune-related pathways were assessed using GSEA. We constructed an immune escape prognosis signature (IEPS) using univariate Cox and LASSO Cox algorithms and evaluated the predictive performance of IEPS with receiver operating characteristic (ROC) curves and survival curves. Additionally, we established a nomogram for clinical application based on IEPS. IHC validated the expression of Carbamoyl phosphate synthetase 2, Aspartate transcarbamylase, and Dihydroorotase (CAD) and Phosphatidylinositol Glycan Anchor Biosynthesis Class U (PIGU) in HCC. We transfected liver cancer cell lines with siRNA and overexpression plasmids, and confirmed the relationship between CAD, PIGU, and the potential downstream TGF-β1 in HCC using qRT-PCR and Western blot. Finally, we validated the tumor response of CAD overexpression using an animal model.

Results: Unsupervised clustering analysis based on IEGs divided HCC patients from TCGA into two groups. There were significant differences in prognosis and immune characteristics between the two groups of patients. Scoring of TCGA patients using IEPS revealed that higher scores were associated with poorer overall survival (OS). Validation was performed using the ICGC database. TIME analysis indicated that patients in the high-IEPS group were in an immunosuppressive state, possibly due to a significant increase in Treg infiltration. Compared to normal liver cells, HCC cells expressed higher levels of CAD and PIGU. Cellular experimental results showed a positive correlation between CAD, PIGU and the potential downstream TGF-β1 expression. Animal experiments demonstrated that CAD significantly promoted tumor progression, with an increase in Treg infiltration.

Conclusion: IEPS has strong prognostic value for HCC patients, and CAD and PIGU provide perspectives on new biomarkers and therapeutic targets for HCC.

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综合分析揭示了预测肝细胞癌患者总体生存的免疫逃避预后特征。
背景:免疫疗法的发展丰富了肝细胞癌(HCC)的治疗,但其疗效不如预期,这可能与免疫逃避有关。免疫逃避与肝癌的免疫微环境有关,但相关研究较少。方法:采用无监督聚类分析方法,根据182个免疫逃避相关基因(IEGs)对TCGA患者进行分类。我们使用单样本基因集富集分析(ssGSEA)和CIBERSORT来计算免疫细胞浸润在集群之间的差异。使用GSEA评估免疫细胞和免疫相关途径的差异。我们使用单变量Cox和LASSO Cox算法构建了免疫逃逸预后特征(IEPS),并使用受试者工作特征(ROC)曲线和生存曲线评估IEPS的预测性能。此外,我们基于IEPS建立了临床应用的nomogram。免疫组化证实了氨甲酰磷酸合成酶2、天冬氨酸转氨基甲酰胺酶、二氢化酶(CAD)和磷脂酰肌醇聚糖锚定生物合成类U (PIGU)在HCC中的表达。我们用siRNA和过表达质粒转染肝癌细胞系,通过qRT-PCR和Western blot证实了CAD、PIGU和HCC中潜在下游TGF-β1之间的关系。最后,我们用动物模型验证了CAD过表达的肿瘤反应。结果:基于eeg的无监督聚类分析将TCGA HCC患者分为两组。两组患者预后及免疫特性差异有统计学意义。使用IEPS对TCGA患者进行评分显示,评分越高,总生存期(OS)越差。使用ICGC数据库进行验证。TIME分析提示高ieps组患者处于免疫抑制状态,可能是Treg浸润明显增加所致。与正常肝细胞相比,HCC细胞表达更高水平的CAD和PIGU。细胞实验结果显示,CAD、PIGU与潜在的下游TGF-β1表达呈正相关。动物实验表明,CAD显著促进肿瘤进展,Treg浸润增加。结论:IEPS对HCC患者具有较强的预后价值,CAD和PIGU为HCC提供了新的生物标志物和治疗靶点。
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来源期刊
CiteScore
10.90
自引率
1.70%
发文量
360
审稿时长
1 months
期刊介绍: Cancer Cell International publishes articles on all aspects of cancer cell biology, originating largely from, but not limited to, work using cell culture techniques. The journal focuses on novel cancer studies reporting data from biological experiments performed on cells grown in vitro, in two- or three-dimensional systems, and/or in vivo (animal experiments). These types of experiments have provided crucial data in many fields, from cell proliferation and transformation, to epithelial-mesenchymal interaction, to apoptosis, and host immune response to tumors. Cancer Cell International also considers articles that focus on novel technologies or novel pathways in molecular analysis and on epidemiological studies that may affect patient care, as well as articles reporting translational cancer research studies where in vitro discoveries are bridged to the clinic. As such, the journal is interested in laboratory and animal studies reporting on novel biomarkers of tumor progression and response to therapy and on their applicability to human cancers.
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