Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing, China.
PYLOTUM Key Joint Laboratory for Upper GI Cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Munich, Germany.
Int J Cancer. 2024 Mar 15;154(6):1111-1123. doi: 10.1002/ijc.34739. Epub 2023 Oct 16.
Effective screening and early detection are critical to improve the prognosis of gastric cancer (GC). Our study aims to explore noninvasive multianalytical biomarkers and construct integrative models for preliminary risk assessment and GC detection. Whole genomewide methylation marker discovery was conducted with CpG tandems target amplification (CTTA) in cfDNA from large asymptomatic screening participants in a high-risk area of GC. The methylation and mutation candidates were validated simultaneously using one plasma from patients at various gastric lesion stages by multiplex profiling with Mutation Capsule Plus (MCP). Helicobacter pylori specific antibodies were detected with a recomLine assay. Integrated models were constructed and validated by the combination of multianalytical biomarkers. A total of 146 and 120 novel methylation markers were found in CpG islands and promoter regions across the genome with CTTA. The methylation markers together with the candidate mutations were validated with MCP and used to establish a 133-methylation-marker panel for risk assessment of suspicious precancerous lesions and GC cases and a 49-methylation-marker panel as well as a 144-amplicon-mutation panel for GC detection. An integrated model comprising both methylation and specific antibody panels performed better for risk assessment than a traditional model (AUC, 0.83 and 0.63, P < .001). A second model for GC detection integrating methylation and mutation panels also outperformed the traditional model (AUC, 0.82 and 0.68, P = .005). Our study established methylation, mutation and H. pylori-specific antibody panels and constructed two integrated models for risk assessment and GC screening. Our findings provide new insights for a more precise GC screening strategy in the future.
有效的筛查和早期检测对于改善胃癌(GC)的预后至关重要。我们的研究旨在探索非侵入性多分析生物标志物,并构建综合模型,用于初步风险评估和 GC 检测。在高危 GC 地区的大量无症状筛查参与者的 cfDNA 中,通过 CpG 串联目标扩增(CTTA)进行全基因组甲基化标记发现。通过使用 Mutation Capsule Plus(MCP)进行多重分析,同时验证了候选甲基化和突变。使用 recomLine 测定法检测幽门螺杆菌特异性抗体。通过多分析生物标志物的组合构建和验证综合模型。在整个基因组中,通过 CTTA 在 CpG 岛和启动子区域中发现了 146 个和 120 个新的甲基化标记。这些甲基化标记与候选突变一起通过 MCP 进行验证,用于建立用于可疑癌前病变和 GC 病例风险评估的 133 个甲基化标记面板以及 49 个甲基化标记面板和 144 个扩增子突变面板。包含甲基化和特异性抗体面板的综合模型在风险评估方面的性能优于传统模型(AUC,0.83 和 0.63,P < 0.001)。另一个整合甲基化和突变面板的 GC 检测模型也优于传统模型(AUC,0.82 和 0.68,P = 0.005)。我们的研究建立了甲基化、突变和幽门螺杆菌特异性抗体面板,并构建了两个用于风险评估和 GC 筛查的综合模型。我们的发现为未来更精确的 GC 筛查策略提供了新的见解。