Wang Shunda, Ma Cuidie, Ren Zhihua, Zhang Yufei, Hao Kun, Liu Chengxiu, Xu Lida, He Shun, Zhang Jianwei
Department of Pancreatic and Gastric Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, People's Republic of China.
College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, People's Republic of China.
Cancer Manag Res. 2025 Jan 25;17:145-160. doi: 10.2147/CMAR.S494747. eCollection 2025.
Early diagnosis is crucial for improving the prognosis of patients with gastric cancer (GC). However, the currently used biomarkers for diagnosing GC have limited sensitivity and specificity. This study aimed to develop a novel diagnostic model based on miRNAs from glycosylated extracellular vesicles and evaluate its effectiveness in diagnosing gastric cancer.
GlyExo-capture technology was used to isolate glycosylated extracellular vesicles from serum samples. The signatures were screened in a discovery cohort of GC patients (n=55) and non-disease controls (n=46) using an integrated process, including high-throughput sequencing technology, screening using a complete bioinformatics algorithm, validation using RT-qPCR, and evaluation by constructing a diagnostic model. The diagnostic model was evaluated in an independent validation cohort (n=139).
We developed a diagnostic model for GC based on five miRNA pairs. This diagnostic model demonstrated high sensitivity, specificity, and stable performance in distinguishing GC patients from non-cancer controls with AUC of 0.930 in the independent validation cohort, particularly in differentiating early-stage GC from benign patients. The markers also showed excellent performance in indicating perineural invasion status and lymph node metastasis in the testing cohort.
The model demonstrated high sensitivity and specificity in diagnosing patients with GC, especially in differentiating early-stage GC from benign patients. The five miRNA pairs could also aid in making treatment decisions. Thus, miRNAs derived from glycosylated exosomes are promising biomarkers for cancer diagnosis.
早期诊断对于改善胃癌（GC）患者的预后至关重要。然而，目前用于诊断GC的生物标志物的敏感性和特异性有限。本研究旨在开发一种基于糖基化细胞外囊泡中miRNA的新型诊断模型，并评估其在诊断胃癌中的有效性。
采用GlyExo捕获技术从血清样本中分离糖基化细胞外囊泡。在一个包括55例GC患者和46例非疾病对照的发现队列中，使用包括高通量测序技术、完整生物信息学算法筛选、RT-qPCR验证和构建诊断模型评估在内的综合流程筛选特征。在一个独立的验证队列（n = 139）中评估该诊断模型。
我们基于五对miRNA开发了一种GC诊断模型。该诊断模型在区分GC患者与非癌症对照方面表现出高敏感性、特异性和稳定性能，在独立验证队列中的AUC为0.930，特别是在区分早期GC与良性患者方面。这些标志物在测试队列中指示神经周围浸润状态和淋巴结转移方面也表现出优异性能。
该模型在诊断GC患者时表现出高敏感性和特异性，尤其是在区分早期GC与良性患者方面。这五对miRNA还可有助于做出治疗决策。因此，源自糖基化外泌体的miRNA是有前途的癌症诊断生物标志物。
