PO.CL01.02 · 临床研究
LiquidTME 的盲法临床验证——一种通过无创刻画肿瘤微环境来预测免疫治疗应答的无细胞 DNA 检测
Blinded clinical validation of LiquidTME, a cell-free DNA assay for predicting response to immunotherapy by noninvasively profiling the tumor microenvironment
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
背景：联合免疫检查点抑制剂（ICI）治疗代表了转移性黑色素瘤患者的标准治疗。然而，>40% 的患者对治疗无应答，且高达 60% 的患者受到严重免疫相关毒性的影响。因此，我们需要更精确的方法来为联合 ICI 选择患者。为解决这一问题，我们开发了 LiquidTME，一种基于 Spatial EcoTyper（Cancer Res (2025) 85 (8_Supplement_1): 153）的液体活检方法，利用深度学习方法从无细胞 DNA（cfDNA）甲基化数据无创评估肿瘤微环境。LiquidTME 此前使用在耶鲁大学接受治疗的 78 例晚期黑色素瘤患者训练以预测 ICI 应答。在此，我们与华盛顿大学（WashU）的临床医生协作，对 LiquidTME 进行了盲法验证。
方法：WashU 队列由 34 例晚期黑色素瘤患者的 ICI 治疗前血浆组成，每例患者接受 ipilimumab 和 nivolumab（n=27）或 relatlimab 和 nivolumab（n=7）治疗。ICI 应答由一名获得委员会认证的肿瘤学家分类为持久临床获益（DCB）或无持久获益（NDB）。使用商业 CLIA 检测为 27 例患者测定肿瘤突变负荷（TMB），并分析为每兆碱基（Mb）的非同义突变（mt），使用 FDA 批准的 10 mt/Mb 切点区分 TMB 高组和低组。
WashU 队列被送至一个对所有临床和 TMB 数据设盲的科学团队。从每例患者的 2 mL 血浆中提取无细胞 DNA，并以 15x 的中位深度进行酶法甲基测序（EM-seq）。对所得图谱进行 LiquidTME 分析，为每个样本产生一个二元应答预测和一个连续应答评分。测试结果被锁定并返回。两种检测通过 AUC 和双侧 Wilcoxon 秩和检验进行应答分类比较，并通过 Kaplan-Meier 分析进行无进展生存（PFS）比较。
结果：该队列的中位随访时间为 21.6 个月。在第 1 周期第 1 天 ICI 治疗前血浆上进行的 LiquidTME 显著分层 PFS，风险比（HR）为 0.27（P = 0.005），LiquidTME(+) 患者的中位 PFS 比 LiquidTME(-) 患者长 1.7 年。LiquidTME 以 0.77 的 AUC 区分 DCB 与 NDB（P = 0.007）。在不同的联合 ICI 方案中观察到相似的表现。在具有 TMB 数据的患者中，LiquidTME 维持了全队列的表现，PFS HR 为 0.30（P < 0.03；AUC = 0.77）。相反，TMB 高 vs 低的子集未能分层 PFS（HR = 0.49；P = 0.17）或应答（AUC = 0.53；P = 0.8）。
结论：在这个黑色素瘤患者的盲法验证队列中，LiquidTME 从治疗前血浆中识别出对联合 ICI 的持久应答者。鉴于其良好的表现，LiquidTME 显示出作为指导个体化免疫治疗决策的临床工具的前景。
查看英文原文 English abstract
Background: Combination immune checkpoint inhibitor (ICI) therapy represents a standard-of-care for patients with metastatic melanoma. However, >40% of patients do not respond to treatment and severe immune-related toxicity affects up to 60% of patients. Accordingly, we need more precise ways to select patients for combination ICIs. To address this, we developed LiquidTME, a liquid biopsy method based on Spatial EcoTyper ( Cancer Res (2025) 85 (8_Supplement_1): 153) that leverages a deep learning approach to noninvasively assess the tumor microenvironment from cell-free DNA (cfDNA) methylation data. LiquidTME was previously trained to predict ICI response using 78 patients with advanced melanoma treated at Yale University. Here we performed a blinded validation of LiquidTME in coordination with clinicians at Washington University (WashU).
Methods: The WashU cohort consisted of pre-ICI plasma from 34 patients with advanced melanoma, each treated with ipilimumab and nivolumab (n=27) or relatlimab and nivolumab (n=7). ICI response was classified as durable clinical benefit (DCB) or no durable benefit (NDB) by a board-certified oncologist. Tumor mutational burden (TMB) was determined for 27 patients using commercial CLIA assays and analyzed as nonsynonymous mutations (mt) per megabase (Mb), using the FDA-approved 10 mt/Mb cutpoint for TMB-high and -low groups.
The WashU cohort was sent to a scientific team that was blinded to all clinical and TMB data. Cell-free DNA was extracted from 2 mL plasma per patient and subjected to enzymatic methyl-seq (EM-seq) at a median depth of 15x. LiquidTME was performed on the resulting profiles, yielding a binary response prediction and a continuous response score for each sample. Test results were locked down and returned. Both assays were compared by AUC and two-sided Wilcoxon rank-sum tests for response classification, and Kaplan-Meier analysis for progression-free survival (PFS).
Results: Median follow-up time of the cohort was 21.6 months. LiquidTME performed on cycle 1 day 1 pre-ICI plasma significantly stratified PFS with a hazard ratio (HR) of 0.27 ( P = 0.005), with LiquidTME(+) patients achieving a median PFS of 1.7 years longer than LiquidTME(-) patients. LiquidTME distinguished DCB from NDB with an AUC of 0.77 ( P = 0.007). Similar performance was seen across distinct combination ICI regimens. In patients with TMB data, LiquidTME maintained whole-cohort performance with a PFS HR of 0.30 ( P < 0.03; AUC = 0.77). In contrast, TMB high vs. low subsets failed to stratify PFS (HR = 0.49; P = 0.17) or response (AUC = 0.53; P = 0.8).
Conclusion: LiquidTME identified durable responders to combination ICI from pretreatment plasma in this blinded validation cohort of melanoma patients. Given its favorable performance, LiquidTME shows promise as a clinical tool to guide personalized immunotherapy decision-making.
利益披露 Disclosure
A. A. Chaudhuri,
LiquidCell Dx Stock, Other Business Ownership.
Droplet Biosciences Stock, Other Business Ownership.
Geneoscopy Stock Option.
D. Y. Chen,
Replimune Independent Contractor.
T. Hansen, None.
M. Jarosz,
LiquidCell Dx Independent Contractor, Stock Option.
V. A. Miller,
LiquidCell Dx Independent Contractor, Stock Option.
One Biosciences g., Board of Directors, non-salaried role), Stock Option.
A. M. Newman,
LiquidCell Dx Stock, Other Business Ownership.
CiberMed Stock, Other Business Ownership.