PO.CL01.15 · 临床研究
用于标准化胃癌、GEJ和食管癌（GEC）染色体不稳定性评估的统一临床与分子框架
A unified clinical and molecular framework to standardize chromosomal instability assessment in gastric, GEJ, and esophageal cancer (GEC)
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
背景：
染色体不稳定性（CIN）是胃食管腺癌的一个主导分子特征，与标准化疗和化疗免疫治疗的不良结局相关。鉴于其高患病率以及缺乏标准化、可临床部署的CIN识别方法，我们试图开发一个统一的临床与分子框架，以在真实世界和III期数据集中量化CIN，并构建基于NGS和组织病理学的工具用于常规CIN分类。
方法：
我们跨互补平台分析了3,822例肿瘤：2,613例经MSK-IMPACT分析的患者、587例来自III期CheckMate-649（CM649）试验患者的RNA-seq和全外显子组测序样本，以及622例TCGA样本。CIN由基因组改变比例（绝对log₂偏差>0.2）定义，并使用FACETS通过臂级和局灶拷贝数指标加以补充。在CIN分层间评估临床病理、分子和结局关联。CIN将与CM649转录组程序和生存整合，以评估其对联合或不联合nivolumab化疗的预测价值。
结果：
MSK-IMPACT队列中63%的肿瘤存在CIN，其中食管癌为76%、GEJ为68%、胃癌为47%。在2,445例微卫星稳定肿瘤中，CIN肿瘤富集TP53突变（79%对比64%）、CDKN2A缺失（24%对比10%）以及CCND1、MYC、EGFR、ERBB2、VEGFA和CCNE1的局灶扩增（FDR <0.001），而CDH1和RHOA突变则在非CIN肿瘤中富集。CIN呈现分级谱系，较高的FGA与增加的非整倍性和更多独特转移部位数量相关。基于H&E全切片图像训练的深度学习模型正在开发以推断CIN，其与CM649临床结局的验证正在进行中。此外，正在分析配对的原发-转移及纵向样本，以定义CIN进化轨迹。
结论：
我们提供了一个统一的基因组和组织学框架，以在临床和III期食管胃癌样本中标准化CIN评估。通过将CIN与可重复的分子特征和治疗结局相联系——并通过开发与常规病理工作流程兼容的基于NGS和H&E的工具——这项工作为将CIN整合为一种用于患者分层、风险富集和未来靶向染色体不稳定性试验设计的实用生物标志物奠定了基础。
查看英文原文 English abstract
Background:
Chromosomal instability (CIN) is a dominant molecular feature of gastroesophageal adenocarcinomas and is associated with poor outcomes to standard chemotherapy and chemo-immunotherapy. Given its high prevalence and the absence of standardized, clinically deployable methods to identify CIN, we sought to develop a unified clinical and molecular framework to quantify CIN across real-world and phase III datasets and to build NGS- and histopathology-based tools for routine CIN classification.
Methods:
We analyzed 3,822 tumors across complementary platforms: 2,613 patients profiled with MSK-IMPACT, 587 RNA-seq and whole-exome sequencing samples from patients treated on Phase III CheckMate-649 (CM649) trial, and 622 TCGA samples. CIN was defined by fraction of genome altered (absolute log₂ deviation >0.2) and complemented by arm-level and focal copy-number metrics using FACETS. Clinicopathologic, molecular, and outcome associations were evaluated across CIN strata. CIN will be integrated with CM649 transcriptomic programs and survival to assess predictive value for chemotherapy with and without nivolumab.
Results:
CIN was present in 63% of tumors within the MSK-IMPACT cohort, including 76% in esophageal, 68% in GEJ, and 47% in gastric cancers. Among 2,445 microsatellite-stable tumors, CIN tumors were enriched for TP53 mutations (79% vs 64%), CDKN2A loss (24% vs 10%), and focal amplifications in CCND1, MYC, EGFR, ERBB2, VEGFA, and CCNE1 (FDR <0.001), whereas CDH1 and RHOA mutations were enriched in non-CIN tumors. CIN exhibited a graded spectrum, with higher FGA associated with increased aneuploidy and a greater number of unique metastatic sites. Deep-learning models trained on H&E whole-slide images are being developed to infer CIN, with validation alongside CM649 clinical outcomes ongoing. Matched primary-metastatic and longitudinal samples are additionally being analyzed to define CIN evolutionary trajectories.
Conclusions:
We provide a unified genomic and histologic framework to standardize CIN assessment across clinical and phase III esophagogastric cancer samples. By linking CIN to reproducible molecular features and treatment outcomes-and by developing NGS- and H&E-based tools compatible with routine pathology workflows-this work lays the foundation for integrating CIN as a practical biomarker for patient stratification, risk enrichment, and future trial design targeting chromosomal instability.
利益披露 Disclosure
J. Xu, None..
C. Tsai, None..
H. Walch, None..
P. Evans, None..
J. Posada, None.
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