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Updated: Jan 10, 2026

Mass Cytometry Analysis of Systemic and Local Immune Responses in Hepatocellular Carcinoma
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在HCC中解读胆固醇-亡轴:基于机器学习的多omics集成和单细胞转录组分析.

Yang Li1, Jun Shi2, Aiqing Zhao3

  • 1Department of Emergency, Ningbo Medical Center Lihuili Hospital, The Affiliated Lihuili Hospital of Ningbo University, Ningbo, 315040, Zhejiang, China.

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概括
此摘要是机器生成的。

这项研究确定了六个关键基因与亡和胆固醇代谢相关,作为肝肝细胞癌 (LIHC) 的关键预后标志物. 这一发现有助于早期风险评估和LIHC患者的个性化治疗策略.

关键词:
细胞灭亡 (apoptosis) 是一种死亡的过程.胆固醇的新陈代谢肝脏肝细胞癌是肝脏肝细胞癌.预测模型是一个预测模型.一个单细胞序列的序列.

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科学领域:

  • 在瘤学瘤学.
  • 分子生物学分子生物学
  • 遗传学 是一个遗传学.

背景情况:

  • 肝肝细胞癌 (LIHC) 是一种流行癌症,发病率不断增加,对健康和经济构成重大挑战.
  • 早期诊断LIHC是困难的,导致晚期检测和治疗效率降低.

研究的目的:

  • 研究LIHC中亡和胆固醇代谢的作用.
  • 确定新的预后生物标志物,并开发LIHC的风险预测模型.

主要方法:

  • 利用多omics数据和机器学习进行基因表达分析.
  • 采用LASSO回归来识别枢纽基因,并构建了一个预后风险评分模型.
  • 进行了免疫细胞透,基因丰富和单细胞分析.

主要成果:

  • 确定了与亡和胆固醇代谢相关的差异表达基因 (ACMRDEGs).
  • 在LIHC.中,六个枢纽基因 (EPHX2,FABP5,SQLE,ADH4,HMGCS2,CYP7A1) 被验证为总生存期 (OS) 的显著预后生物标志物.
  • 在LIHC中揭示了显著的免疫细胞透差异和丰富的胆固醇/酒精代谢途径,单细胞分析详细说明了细胞异质性.

结论:

  • 开发并验证了基于细胞亡和胆固醇代谢途径的LIHC的第一个综合性六基因预后模型.
  • 该模型显示了改善LIHC临床实践中的风险分层和指导个性化治疗策略的潜力.