PO.CL01.07 · 临床研究

基于甲基化的肿瘤分数监测可识别具有推定分子进展、可能受益于综合基因组分析的患者

Methylation-based tumor fraction monitoring identifies patients with putative molecular progression who may benefit from comprehensive genomic profiling

海报缩略图:基于甲基化的肿瘤分数监测可识别具有推定分子进展、可能受益于综合基因组分析的患者
编号 1122 展板 3 时间 4/19 02:00–05:00 区域 Section 44 主讲 Jun Zhao
分会场 Liquid Biopsies: Circulating Nucleic Acids 1
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作者与单位 Authors & Affiliations

Jun Zhao1, Rihao Qu1, Katie Quinn1, Tingting Jiang1, Jack Tung1, Carin R. Espenschied2, Samantha I. Liang3, Vishnu Ramani1, Jing Wang1, Sean Gordon1, Martina Lefterova1, Darya Chudova1

1Guardant Health, Palo Alto, CA,2Guardant Health, Spokane, WA,3Parker Institute for Cancer Immunotherapy, San Francisco, CA

摘要 Abstract

中文摘要
背景:利用基于甲基化的肿瘤分数(TF)对循环肿瘤DNA(ctDNA)进行纵向监测,可随时间灵敏地检测癌症患者的疾病动态变化。TF升高的患者可能正在经历分子进展(MP),先于临床进展发生。这些患者可能已产生具有临床相关性的变异(CRVs,与靶向治疗的应答或耐药相关),这些变异可通过综合基因组分析(CGP)检出,从而指导治疗选择。在此,我们描述了一种工作流程,通过应用TF变化阈值来识别具有推定MP的患者,以最大化CRVs的检出。 方法:为确定显著TF变化的阈值,我们利用来自临床样本的计算机模拟稀释(ISD)来训练一个以90%分析特异性为目标的输入依赖性模型。我们还确定了一个绝对TF阈值以最大化CRVs的检出。这些阈值通过比较同一次采血的两份等分样本(n=1061,模拟连续样本间“无TF变化”)以及接受治疗患者的纵向泛癌种样本(n=2103,代表真实世界的TF变化)进行了分析评估。该模型还在RADIOHEAD队列1(n=116)中进行了临床评估,该队列中晚期实体瘤患者接受了标准治疗的免疫检查点抑制剂(ICI)。校正风险比(aHR)和p值(p)通过以性别、年龄和基线TF为协变量的Cox比例风险模型确定。 结果:模拟和优化方法得出的推定MP评估阈值为:连续时间点间TF升高>50%,同时绝对TF>0.1%。在模拟无生物学变化的重复血浆样本中评估时,这些阈值显示出97%的经验特异性。在接受治疗的晚期癌症患者的系列样本中,29.5%符合MP标准。关键的是,55%的推定MP患者携带了基线时未检出的CRVs。在RADIOHEAD队列中,推定MP患者的真实世界无进展生存期(rwPFS)显著差于TF稳定/下降的患者(HR=4.30,95% CI:2.93-6.33,p<0.001)。在推定MP患者中,65.1%出现新的CRVs,而TF下降的患者中该比例为26.2%。 结论:我们建立了推定MP的标准,其特异性达到97%,并与接受ICI治疗患者的rwPFS缩短相关。对符合这些标准的患者进行CGP,可在55-65%的病例中检出新的可靶向变异,支持其在纵向ctDNA监测期间MP发生时指导治疗决策的效用。 参考文献 1. Liang S, 等. Cancer Res Commun. 2025;5(8):1384。
查看英文原文 English abstract
Background: Longitudinal monitoring of circulating tumor DNA (ctDNA) using methylation-based tumor fraction (TF) provides sensitive detection of disease dynamics in cancer patients over time. Patients with increasing TF may be undergoing molecular progression (MP) preceding clinical progression. They may have developed clinically relevant variants (CRVs, associated with response or resistance to targeted therapies) detectable by comprehensive genomic profiling (CGP) that can guide treatment options. Here, we describe a workflow that applies TF change thresholds to identify patients with putative MP, maximizing detection of CRVs. Methods: To establish the thresholds for significant TF change, we used in-silico dilutions (ISD) from clinical samples to train an input-dependent model targeting 90% analytical specificity. We also determined an absolute TF threshold to maximize detection of CRVs. These thresholds were analytically evaluated by comparing two aliquots from the same blood draw (n=1061, simulating “no TF change” between consecutive samples), as well as longitudinal pan-cancer samples from patients undergoing treatment (n=2103, representing real-world TF changes). The model was also clinically evaluated in the RADIOHEAD cohort 1 (n=116) in which patients with advanced solid tumors received standard-of-care immune checkpoint inhibitors (ICI). Adjusted hazard ratios (aHR) and p-values (p) were determined via Cox proportional hazards with sex, age, and baseline TF as covariates. Results: Significant TF change between consecutive timepoints of >50% increase, along with an absolute TF of >0.1% were yielded from simulation and optimization approach as thresholds for putative MP assessment. When evaluated in replicate plasma samples that simulate no biological change, these thresholds demonstrated empirical specificity of 97%. In serial samples from advanced cancer patients undergoing treatment, 29.5% met the criteria for MP. Critically, 55% of patients with putative MP harbored CRVs not detected at baseline. In the RADIOHEAD cohort, patients with putative MP had significantly worse real-world progression-free survival (rwPFS) compared to those with stable/decreasing TF (HR=4.30, 95% CI: 2.93-6.33, p<0.001). Among patients with putative MP, 65.1% had new CRVs, compared to 26.2% in patients with TF decrease. Conclusions: We developed criteria for putative MP that achieve 97% specificity and are associated with shorter rwPFS in patients receiving ICI. CGP in patients meeting these criteria detects new actionable variants in 55-65% of cases, supporting its utility for guiding therapeutic decision-making upon MP during longitudinal ctDNA monitoring. References 1. Liang S, et al. Cancer Res Commun. 2025;5(8):1384.
利益披露 Disclosure
J. Zhao, Guardant Health Employment. R. Qu, Guardant Health Employment. K. Quinn, Guardant Health Employment. T. Jiang, Guardant Health Employment. J. Tung, Guardant Health Employment. C. R. Espenschied, Guardant Health Employment. S. I. Liang, None. V. Ramani, Guardant Health Employment. J. Wang, Guardant Health Employment. S. Gordon, Guardant Health Employment. M. Lefterova, Guardant Health Employment. D. Chudova, Guardant Health Employment.

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