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构建一个风险分层模型,整合ctDNA,以预测新辅助剂治疗乳腺癌的反应和存活率

Zhaoyun Liu^1,2,3, Bo Yu⁴, Mu Su⁴

¹Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, 250117, Shandong, China.

|December 13, 2023

概括

在乳腺癌新辅助化疗 (NAC) 中准确预测病理完整反应 (pCR) 是至关重要的. 一个结合基因组突变,循环瘤DNA (ctDNA) 和临床因素的新型模型有效预测pCR并改善患者的预后.

科学领域:

在瘤学瘤学.
基因组学就是基因组学.
生物标志物生物标志物

背景情况:

乳腺癌中新辅助化疗 (NAC) 的病理完整反应 (pCR) 与预后改善有关.
在手术前预测PCR的可靠指标缺乏,需要预测模型.

研究的目的:

开发和验证乳腺癌中pCR到NAC的预测模型.
调查基因组特征,ctDNA和临床特征的预后价值.

主要方法:

预计将招募269名乳腺癌患者,接受以环素和基于税的NAC.
在瘤活检中分析了457个与癌症相关的基因 (DNA测序).
在不同时间点在血液样本中使用个性化的9基因面板检测和分析循环瘤DNA (ctDNA).

主要成果:

一种结合五种SNV突变,四种CNV突变和三种临床因素的瘤预测模型在训练组中实现了0.871的AUC.
该模型还预测了无病生存期 (DFS),AUC为0.749 (1年) 和0.830 (3年).
一个结合化疗预测模型,包括治疗前ctDNA水平,显示出优异的pCR预测,AUC为0.961.

结论:

一个整合基因组特征,ctDNA状态和临床特征的非侵入性预测模型可以准确预测乳腺癌患者的pCR和预后.
包括治疗前的ctDNA水平显著提高了基于基因突变和临床特征的模型的预测能力.

关键词:

乳腺癌乳腺癌乳腺癌新辅助化学疗法新辅助化学疗法预测模型的预测模型.ctDNActDNA是什么意思在 pCR 中,pCR 值为 pCR.

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