PO.CL12.03 · 临床研究
基因组及临床因素对早期阶段表观遗传治疗疗效反应的影响：来自两家主要I期研究中心的国际队列
Impact of genomic and clinical factors on therapeutic response to arly‑phase epigenetic therapies: An international cohort from two major phase I units
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摘要 Abstract
中文摘要
引言：表观遗传药物——包括BET溴结构域、PRMT5、EZH2及其他染色质调控因子的抑制剂——已成为多种实体瘤中颇具前景的治疗策略。然而，临床活性仍然多变，且缺乏稳健的预测性生物标志物。我们开展了一项回顾性双中心分析，以刻画在早期阶段试验中接受这些化合物治疗的患者的结局，并评估下一代测序（NGS）图谱对患者间差异的贡献。
方法：共纳入262例在两家学术性早期药物开发中心接受表观遗传药物I期试验治疗的患者。临床数据（人口统计学、肿瘤类型、ECOG状态、既往治疗）和NGS结果（致病性变异、VUS、短变异）在各中心间协调整合为一个统一的数据集。采用双侧单变量Cox比例风险模型评估与总生存期（OS）的相关性。报告了风险比（HR）、95%置信区间（CI）、比例风险假设、赤池信息准则（AIC）和C统计量。
结果：中位年龄为59.9岁（IQR 51-69），55%为女性。多数患者为转移性疾病（88.2%）、ECOG 1（59.2%）、既往化疗（78.5%）及既往免疫治疗（70.9%），既往系统治疗中位数为3线（IQR 1-4）。转移部位中位数为2个（IQR 1-3）。患者接受了多种表观遗传化合物，最常见的是BET抑制剂（46.6%）、PRMT5抑制剂（22.5%）、HDAC抑制剂（14.1%）和EZH2抑制剂（8.4%），涉及的肿瘤类型包括胃肠道（21.4%）、胸部（19.8%）、中枢神经系统（12.6%）和肉瘤/GIST（12.6%）。最佳总体反应包括10% CR/PR（n=21）、39.7% SD（n=104）和44.6% PD（n=117），反映出中等程度的临床活性。在临床Cox模型中，较差的OS与较高的转移负荷（HR 1.19；95% CI, 1.08-1.32；p<0.001）、既往化疗（HR 1.64；95% CI, 1.17-2.31；p=0.004）以及既往治疗线数增加（HR 1.05；95% CI, 1.00-1.11；p=0.044）相关。年龄也具有统计学显著性（HR 0.99；95% CI, 0.98-1.00；p=0.029）。在基因组Cox模型中，短EGFR变异与较差的OS显著相关（HR 2.74；95% CI, 1.36-5.52；p=0.005）。其他改变，包括致病性EGFR突变（HR 1.83；p=0.065）、ATM（HR 3.00；p=0.066）和ASPM（HR 0.29；p=0.087）变异，显示出非显著趋势。
结论：表观遗传治疗在这一异质性早期阶段队列中显示出中等程度的活性。临床因素——而非单个基因组改变——对生存具有中等程度的预后价值。这些发现强调了在表观遗传药物开发中，需要超越单基因预测因子的整合性生物标志物方法来优化患者选择。
查看英文原文 English abstract
Introduction: Epigenetic agents-including inhibitors of BET bromodomains, PRMT5, EZH2, and other chromatin regulators-have emerged as promising therapeutic strategies across solid tumors. However, clinical activity remains variable, and robust predictive biomarkers are lacking. We conducted a retrospective two-center analysis to characterize outcomes of patients treated with these compounds in early-phase trials and to evaluate the contribution of next-generation sequencing (NGS) profiles to interpatient variability.
Methods: A total of 262 patients treated within phase I trials of epigenetic agents at two academic early-phase drug development units were included. Clinical data (demographics, tumor type, ECOG status, prior therapies) and NGS results (pathogenic variants, VUS, short variants) were harmonized across centers into a unified dataset. Associations with overall survival (OS) were assessed using two-sided univariable Cox proportional hazards models. Hazard ratios (HR), 95% confidence intervals (CI), proportional hazards assumptions, Akaike Information Criteria (AIC), and C-statistics were reported.
Results: Median age was 59.9 years (IQR 51-69), and 55% were female. Most patients had metastatic disease (88.2%), ECOG 1 (59.2%), prior chemotherapy (78.5%), and prior immunotherapy (70.9%), with a median of 3 prior systemic lines (IQR 1-4). The median number of metastatic sites was 2 (IQR 1-3). Patients received diverse epigenetic compounds, most commonly BET inhibitors (46.6%), PRMT5 inhibitors (22.5%), HDAC inhibitors (14.1%), and EZH2 inhibitors (8.4%), across tumor types including gastrointestinal (21.4%), thoracic (19.8%), CNS (12.6%), and sarcoma/GIST (12.6%). Best overall response included 10% CR/PR (n=21), 39.7% SD (n=104), and 44.6% PD (n=117), reflecting modest clinical activity.In the clinical Cox model, worse OS was associated with higher metastatic burden (HR 1.19; 95% CI, 1.08-1.32; p<0.001), prior chemotherapy (HR 1.64; 95% CI, 1.17-2.31; p=0.004), and increasing prior lines (HR 1.05; 95% CI, 1.00-1.11; p=0.044). Age was also statistically significant (HR 0.99; 95% CI, 0.98-1.00; p=0.029). In the genomic Cox model, short EGFR variants were significantly associated with worse OS (HR 2.74; 95% CI, 1.36-5.52; p=0.005). Other alterations, including pathogenic EGFR mutations (HR 1.83; p=0.065), ATM (HR 3.00; p=0.066), and ASPM (HR 0.29; p=0.087) variants showed non-significant trends.
Conclusions: Epigenetic therapies showed modest activity in this heterogeneous early-phase cohort. Clinical factors-but not individual genomic alterations-were modestly prognostic for survival. These findings underscore the need for integrated
biomarker approaches beyond single-gene predictors to optimize patient selection in epigenetic drug development.
利益披露 Disclosure
M. Pedregal, None..
M. Avedillo, None..
I. Mahillo, None..
E. Garcia, None..
B. Doger de Spéville, None..
M. Dorta, None..
V. Moreno Garcia, None.