遗传 ›› 2025, Vol. 47 ›› Issue (7): 768-785.doi: 10.16288/j.yczz.25-007

• 研究报告 • 上一篇    下一篇

失巢凋亡相关转录特征预测肝癌预后和免疫微环境的潜在价值

程芙蓉1,2(), 宋文煜2, 曹鹏博2, 周钢桥1,2()   

  1. 1.河北大学生命科学学院,保定 071002
    2.军事科学院军事医学研究院,医学蛋白质组学全国重点实验室,国家蛋白质科学中心(北京),北京 100850
  • 收稿日期:2025-01-06 修回日期:2025-03-17 出版日期:2025-03-26 发布日期:2025-03-26
  • 通讯作者: 周钢桥,博士,研究员,研究方向:医学遗传与基因组学。E-mail: zhougq114@126.com
  • 作者简介:程芙蓉,硕士研究生,专业方向:生物学。E-mail: 1578877852@qq.com
  • 基金资助:
    国家自然科学基金项目(82002573);国家自然科学基金项目(82172707);国家重点研发计划项目(2017YFA0504301)

Potential value of anoikis transcriptional signatures in predicting prognosis and immune microenvironment in hepatocellular carcinoma

Furong Cheng1,2(), Wenyu Song2, Pengbo Cao2, Gangqiao Zhou1,2()   

  1. 1. College of Life Science, Hebei University, Baoding 071002, China
    2. State Key Lab of Medical Proteomics, National Center for Protein Sciences at Beijing, Academy of Military Medical Sciences, Academy of Military Sciences, Beijing 100850, China
  • Received:2025-01-06 Revised:2025-03-17 Published:2025-03-26 Online:2025-03-26
  • Supported by:
    National Natural Science Foundation of China(82002573);National Natural Science Foundation of China(82172707);National Key Research and Development Program of China(2017YFA0504301)

摘要:

抵抗失巢凋亡(anoikis)进而促进癌细胞存活是许多癌症发生、发展的关键特征。肝细胞癌(hepatocellular carcinoma,HCC)是一种复发率高、转移性强的恶性肿瘤,但其失巢凋亡相关研究仍然较少。因此,基于失巢凋亡相关基因(anoikis-related gene,ARG)预测HCC的预后及免疫微环境变化,可为基于失巢凋亡的治疗策略提供新的理论依据。本文基于癌症基因组图谱(The Cancer Genome Atlas,TCGA)HCC转录组数据,鉴定出74个在肝癌中显著差异表达的ARG。通过LASSO-Cox回归模型建立了包含其中9个特征基因的HCC预后风险评分模型。多因素Cox比例风险回归分析表明,该模型能准确预测患者总体生存率,是HCC新的独立预后指标。基于ARG建立的不同风险组在通路活性、免疫细胞浸润和HCC患者生存状态等多方面存在显著差异。与低风险组相比,高风险组中细胞增殖相关通路显著活化,免疫抑制性细胞的浸润比例显著增加,且与肝癌患者对PD-L1单抗治疗耐药相关。上述结果表明,本研究建立的ARG风险评分模型作为一种新的指标可以预测HCC患者的预后,并初步揭示了ARG在肝癌进展中的重要作用。

关键词: 肝细胞癌, 失巢凋亡, 预后模型, 免疫微环境

Abstract:

Resistance to anoikis, a crucial factor in cancer cell survival, drives the development and progression of numerous malignancies. Hepatocellular carcinoma (HCC) is a malignant liver tumor characterized by high rates of recurrence and metastasis. However, the role of anoikis in HCC remains poorly understood. In this study, we identify 74 anoikis-related genes (ARGs) differentially expressed in HCC using the transcriptional data from The Cancer Genome Atlas (TCGA). Then, we develop a prognostic model incorporating 9 of these genes through LASSO-Cox regression analysis, and confirm the model’s independent prognostic significance for overall survival in HCC patients by using multivariable Cox proportional hazards analysis. Furthermore, we observe significant enrichment of activated proliferation-related pathways, increased infiltration of immunosuppressive cells and resistance to anti-PD-L1 therapy in the high-risk group defined by this model. These findings suggest that the ARG model may serve as a novel prognostic indicator for HCC patients and underscore the critical role of anoikis in HCC progression.

Key words: hepatocellular carcinoma, anoikis, prognostic model, immune microenvironment