Guo Pengda, Yang Yang, Wang Lu, Zhang Yu, Zhang Bei, Cai Jinping, de Melo Fabrício Freire, Strickland Matthew R, Huang Min, Liu Biao
Department of Pathology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China.
Gusu School, Nanjing Medical University, Suzhou, China.
J Gastrointest Oncol. 2024 Oct 31;15(5):2053-2066. doi: 10.21037/jgo-24-345. Epub 2024 Sep 13.
The Cancer Genome Atlas (TCGA) has identified four distinct molecular subtypes of gastric cancer (GC) with prognostic significance: Epstein-Barr virus (EBV)-positive, microsatellite instability (MSI)-high, genomically stable (GS), and chromosomal instability (CIN). Unfortunately, the complex analysis required for TCGA classification limits its practical use in clinical settings. Our study sought to devise a next-generation sequencing (NGS)-based method to classify GC more efficiently, serving as a promising biomarker for prognosis and immunotherapy efficacy.
This study was a retrospective observation study, and we employed 2 independent GC cohorts. The 3DMed cohort (n=765), comprising data on 733 cancer-related genes along with 4 EBV-encoded genes, was utilized to develop the new NGS classification. Additionally, the secondary Korean cohort (n=55), which includes both genomic data and information on immune checkpoint inhibitor (ICI) treatment, was employed to establish a correlation between NGS subtypes and ICI responsiveness.
In the 3DMed cohort, we identified 5.2% EBV, 4.6% MSI, 30.6% GS, and 59.6% CIN subtypes. The MSI subtype exhibited the highest number of mutation events, along with the highest tumor mutational burden (TMB) and strong programmed cell death ligand 1 (PD-L1) expression. CIN tumors showed extensive copy number variations (CNVs) and genomic heterogeneity. The EBV subtype presented recurrent and mutations and fewer mutations. GS tumors exhibited specific mutations in and . In the Korean cohort, ICIs were most effective in MSI and EBV cases, showing disease control rates of 100%, compared to 62.9% in GS and 12.5% in CIN subtypes.
The NGS method successfully maps the mutational landscape of GC, providing a practical TCGA classification surrogate to optimize patient-specific treatment strategies.
癌症基因组图谱（TCGA）已确定了具有预后意义的四种不同分子亚型的胃癌（GC）：爱泼斯坦-巴尔病毒（EBV）阳性、微卫星不稳定（MSI）高、基因组稳定（GS）和染色体不稳定（CIN）。不幸的是，TCGA分类所需的复杂分析限制了其在临床环境中的实际应用。我们的研究旨在设计一种基于二代测序（NGS）的方法，以更有效地对GC进行分类，作为一种有前景的预后和免疫治疗疗效生物标志物。
本研究为回顾性观察研究，我们采用了2个独立的GC队列。3DMed队列（n = 765）包含733个癌症相关基因以及4个EBV编码基因的数据，用于开发新的NGS分类。此外，韩国二级队列（n = 55）包括基因组数据和免疫检查点抑制剂（ICI）治疗信息，用于建立NGS亚型与ICI反应性之间的相关性。
在3DMed队列中，我们鉴定出5.2%的EBV、4.6%的MSI、30.6%的GS和59.6%的CIN亚型。MSI亚型表现出最高的突变事件数量，以及最高的肿瘤突变负荷（TMB）和强烈的程序性细胞死亡配体1（PD-L1）表达。CIN肿瘤显示出广泛拷贝数变异（CNV）和基因组异质性。EBV亚型呈现复发性 和 突变以及较少的 突变。GS肿瘤在 和 中表现出特定突变。在韩国队列中，ICI在MSI和EBV病例中最有效，疾病控制率为100%，而GS亚型为62.9%，CIN亚型为12.5%。
NGS方法成功绘制了GC的突变图谱，提供了一个实用的TCGA分类替代方法，以优化针对患者的治疗策略。
