从多omics到功能验证:PTMRS对TME进行分层,并在CRC生物学中定位PDGFRB
Yanhong Liu1, Chao Lu2, Luchun Hua1
1Department of General Surgery, Huashan Hospital, Fudan University, Shanghai, China.
Frontiers in immunology
|January 28, 2026
概括
我们开发了一种新的风险签名 (PTMRS),通过整合翻译后修改 (PTM) 数据,准确预测结直肠癌 (CRC) 患者的生存率. 这种特征识别出一种免疫寒冷,富有肌体的表型,并突出显示PDGFRβ作为治疗点.
科学领域:
- 在瘤学瘤学.
- 分子生物学分子生物学
- 生物信息学是一种生物信息学.
背景情况:
- 结肠直肠癌 (CRC) 的预后是高度可变的,挑战了准确的风险分层.
- 翻译后修改 (PTMs) 显著影响CRC进展和瘤微环境 (TME) 相互作用.
- 现有的模型很少将多种PTM信号整合到全面的风险评估中.
研究的目的:
- 通过整合与翻译后修饰 (PTM) 相关的基因,开发结直肠癌的强大预后模型.
- 为了验证模型在不同患者队列和免疫疗法数据集中的性能.
- 调查潜在的生物机制,并确定潜在的治疗点.
主要方法:
- 使用TCGA和GTEx数据集构建了一个翻译后修改相关风险签名 (PTMRS) 模型.
- 考克斯的部分最小平方框架从101个建模策略中进行了选择.
- 进行了外部验证,单细胞RNA测序 (scRNA-seq) 和涉及PDGFRβ的机制研究.
主要成果:
- PTMRS模型有效地分层了结直肠癌患者的整体存活率.
- 较高的PTMRS得分与免疫寒冷的瘤微环境相关.
- 纤维细胞中的PDGFRβ激活促进了CRC细胞的增殖和迁移,而sunitinib显示出抑制作用.
结论:
- PTMRS为结直肠癌预后提供了一个强大的工具,将内在瘤生物学与TME特征联系起来.
- PTMRS可以确定受益于联合免疫疗法和PDGFRβ向治疗的患者.
- 需要在临床前和临床环境中进一步验证,以确认治疗潜力.
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