Ding Ping'an, Wu Jiaxiang, Wu Haotian, Li Tongkun, Niu Xiaoman, Yang Peigang, Guo Honghai, Tian Yuan, He Jinchen, Yang Jiaxuan, Gu Renjun, Zhang Lilong, Meng Ning, Li Xiaolong, Guo Zhenjiang, Meng Lingjiao, Zhao Qun
The Third Department of Surgery, the Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, China.
Hebei Key Laboratory of Precision Diagnosis and Comprehensive Treatment of Gastric Cancer, Shijiazhuang, 050011, China.
Adv Sci (Weinh). 2024 Dec;11(47):e2406276. doi: 10.1002/advs.202406276. Epub 2024 Nov 18.
The study presents a transcriptomics-based liquid biopsy approach for early recurrence detection in locally advanced gastric cancer (LAGC). Four mRNA biomarkers (AGTR1, DNER, EPHA7, and SUSD5) linked to recurrence are identified through transcriptomic data analysis. A Risk Stratification Assessment (RSA) model combining these biomarkers with clinical features showed superior predictive accuracy for postoperative recurrence, with AUCs of 0.919 and 0.935 in surgical and liquid biopsy validation cohorts, respectively. Functional studies using human gastric cancer cell lines AGS and HGC-27 demonstrated that silencing the identified mRNA panel genes impaired cell migration, invasion, and proliferation. In vivo experiments further showed reduced tumor growth, metastasis, and lymphangiogenesis in mice, possibly mediated by the cAMP signaling pathway. This non-invasive approach offers significant potential for enhancing recurrence detection and enabling personalized treatment strategies, thereby improving patient outcomes in the management of LAGC.
该研究提出了一种基于转录组学的液体活检方法，用于局部晚期胃癌（LAGC）的早期复发检测。通过转录组数据分析确定了四种与复发相关的mRNA生物标志物（AGTR1、DNER、EPHA7和SUSD5）。将这些生物标志物与临床特征相结合的风险分层评估（RSA）模型对术后复发显示出卓越的预测准确性，在手术验证队列和液体活检验证队列中的曲线下面积（AUC）分别为0.919和0.935。使用人胃癌细胞系AGS和HGC-27进行的功能研究表明，沉默所鉴定的mRNA基因面板会损害细胞迁移、侵袭和增殖。体内实验进一步表明，小鼠的肿瘤生长、转移和淋巴管生成减少，这可能由cAMP信号通路介导。这种非侵入性方法在增强复发检测和制定个性化治疗策略方面具有巨大潜力，从而改善LAGC管理中的患者预后。
