探索多种omics液体活检方法用于多种癌症的早期检测:PROMISE研究
Jianchun Duan1,2, Qiang Gao3,4,5, Zhijie Wang2
1Shanxi Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Shanxi 030013, China.
Innovation (Cambridge (Mass.))
|February 25, 2026
概括
将蛋白质标记物与无细胞DNA甲基化集成,可以改善多种癌症检测血液测试 (MCDBTs). 这种多omics方法提高了灵敏度和准确性,特别是在肝癌和卵巢癌.
科学领域:
- 在瘤学瘤学.
- 生物标志物发现发现
- 基因组学就是基因组学.
背景情况:
- 循环无细胞DNA (cfDNA) 甲基化是多种癌症检测血液测试 (MCDBTs) 的主要方法.
- 对MCDBTs的cfDNA甲基化整合蛋白质和突变数据的附加值尚不清楚.
研究的目的:
- 评估MCDBTs多学科整合战略的可行性.
- 调查9种癌症类型中联合甲基化,突变和蛋白质生物标志物的性能.
主要方法:
- 在PROMISE研究中,从1,706名参与者 (866名癌症患者,840名非癌症患者) 收集了前性血液样本.
- 分析了omics数据 (甲基化,突变,蛋白质),并为多式模式模型构建选择了特征.
- 评估了基于甲基化,突变,蛋白质和多模式组合的分类器.
主要成果:
- 以甲基化为基础的分类器与仅以突变或蛋白质为基础的分类器相比,表现优越.
- 结合甲基化和蛋白质特征的多式分类器在98.8%的特异性下提高了对75.1%的灵敏度.
- 多模式分类器在甲基化测试呈阴性结果时,实现了对肝癌和卵巢癌起源预测的100%准确性.
结论:
- 蛋白质标记物在MCDBT中提供了基于cfDNA甲基化的分类器的补充价值.
- 综合甲基化和蛋白质数据的多模式模型提高了癌症检测的准确性和灵敏性.
- 这种综合方法在检测肝癌和卵巢癌等特定癌症方面特别有前途.
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