多模态代谢学破译了泛癌代谢景观和空间-利基-特定的替代
Tingze Feng1,2, Hai-Long Piao1,2,3, Di Chen1,2
1State Key Laboratory of Phytochemistry and Natural Medicines, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 568 Lvshunzhong Road, Dalian 116051, China.
癌细胞为生长重编程新陈代谢,但这些变化差异很大. 这项研究揭示了跨癌症类型和瘤内的共同和独特的代谢特征,识别了关键代谢物,如肉素,以便进一步研究.
科学领域:
- 在瘤学瘤学.
- 代谢学 代谢学 代谢学
- 系统生物学 系统生物学
背景情况:
- 代谢重编程对于癌症的生长和适应在瘤微环境 (TME) 中至关重要.
- 癌症代谢在不同癌症类型和瘤内的空间异质性之间表现出显著的变化.
- 对代谢变化及其特异性的系统,泛癌理解仍然不完整.
研究的目的:
- 系统地研究泛癌的代谢特征,使用集成的多omics数据.
- 为了确定特定于癌症类型,空间利基或跨癌症共享的代谢变化.
- 探索瘤代谢在批量和空间层面上的异质性.
主要方法:
- 集成的散装和空间代谢学,与血液代谢学和空间转录学一起用于验证.
- 在多种癌症类型中对瘤和正常组织之间的代谢差异进行比较分析.
- 应用两步聚类框架来识别TME内的空间代谢模块.
主要成果:
- 确定了一系列代谢特征,包括癌症特异性,空间特异性和共享性变化.
- 与散装分析相比,通过空间代谢学可以独特地辨认出发现的代谢特征.
- 在散装和空间数据中发现了19种一致变化的代谢物 (例如,肉类物种),与脂肪酸代谢有关,可以在血液中检测到.
结论:
- 这种泛癌症分析揭示了TME和癌症类型之间显著的代谢异质性.
- 识别了在多个分析层中具有一致变化的代谢物,作为潜在的生物标志物.
- 强调了多层次,综合性方法对于理解瘤代谢的重要性.
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