后转移性瘤微环境中的代谢重编程:对免疫疗法反应的决定因素的多omics见解
Mengxi Li1, Tingting Wang2,3, Zhenwang Zhang1
1School of Nuclear Technology and Chemistry & Biology, Hubei University of Science and Technology, Xianning, Hubei, China.
Frontiers in immunology
|January 21, 2026
概括
瘤免疫微环境 (TIME) 中的代谢重编程驱动癌症的进展和免疫疗法耐药性. 通过多组学理解这些代谢转变是开发个性化疗法和改善患者治疗结果的关键.
科学领域:
- 在瘤学瘤学.
- 免疫学 免疫学 免疫学
- 代谢过程中的代谢.
背景情况:
- 代谢重编程在塑造瘤免疫微环境 (TIME) 中至关重要.
- 关键的代谢变化包括糖溶解,脂质代谢,铁,,以及托-IDO1-kynurenine轴.
- 这些代谢转变创造了一个免疫抑制的利基,促进瘤的进展和治疗耐药性.
研究的目的:
- 探索在转移性癌症中代谢重编程和免疫调节之间的复杂联系.
- 利用多种omics技术,更深入地了解代谢-免疫交叉通话.
- 确定克服免疫疗法耐药性的新疗法策略.
主要方法:
- 利用了多种omics技术:代谢学,蛋白质学,单细胞测序和空间omics.
- 在时间内分析了复杂的代谢和免疫相互作用.
- 集成的多层数据集,以识别生物标志物和治疗漏洞.
主要成果:
- 代谢变化显著影响免疫细胞功能和免疫疗法的有效性.
- 多omics数据揭示了关键的代谢免疫特征和预测生物标志物.
- 在代谢-免疫交叉通话中确定了治疗漏洞.
结论:
- 整合多omics数据使得准确医学方法能够根据个体的新陈代谢和免疫特征量身定制.
- 结合代谢抑制剂与免疫疗法或针对特定代谢途径的治疗策略显示出有前途.
- 未来的方向包括人工智能驱动的分析和临床翻译的先进交付系统,旨在提高免疫疗法疗效和患者存活率.
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