与乳酸代谢相关的相互作用干扰网络使肝细胞癌的强大分层成为可能
Shizong Li1, Lin Wang2, Xuehua Xing2
1Department of Hepatobiliary and Pancreatic Surgery, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Xiuying District, Haikou, Hainan, 570311, China.
Discover oncology
|February 14, 2026
概括
这项研究基于乳酸代谢 (LM) 网络确定了新的肝细胞癌 (HCC) 亚型. 一种亚型表现出不良预后和对免疫检查点抑制剂 (ICI) 的耐药性,突出了个性化HCC治疗的潜力.
科学领域:
- 在瘤学瘤学.
- 代谢途径 代谢途径
- 系统生物学 系统生物学
背景情况:
- 肝细胞癌 (HCC) 呈现出显著的分子异质性,复杂的诊断和治疗.
- 乳酸代谢 (LM) 越来越多地被认为在瘤进展中的作用.
- 目前缺乏基于LM相关分子相互作用的HCC综合分类.
研究的目的:
- 使用LM相关的基因相互作用网络,开发一个强大的HCC亚型分层框架.
- 以临床特征,免疫微环境和微生物组合构成为基础,对已识别的亚型进行表征.
- 为了确定一个预测基因签名用于HCC的预后.
主要方法:
- 构建一个与LM相关的基因相互作用网络.
- 达成共识的聚类来识别HCC的分子亚型.
- 多维分析包括临床数据,免疫分析,突变分析和微生物组测序.
- 使用LASSO回归的5基因预后签名的开发和验证.
主要成果:
- 根据LM网络确定了四种不同的HCC亚型.
- 集群2亚型显示出最糟糕的预后和对免疫检查点抑制剂 (ICI) 的反应不佳.
- 亚型在临床特征,免疫透,突变景观和微生物群多样性方面存在显著差异,Cluster2显示微生物多样性减少和特定属的丰富.
- 一个经验证的5基因签名准确地预测了多个HCC队列的存活率.
结论:
- 这项研究建立了一个新的LM网络驱动的HCC亚型系统,增强对瘤异质性的理解.
- 已识别的亚型为预测患者预后和对治疗的反应提供了一个框架,特别是ICI.
- 这些发现为开发HCC个性化治疗策略提供了临床可行的工具.
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