Exosomes and their cargo proteins in diagnosis, process and treatment of gastric cancer

Gastric cancer is one of the common malignant tumors of digestive tract. Early diagnosis, process monitoring, and appropriate treatment strategies are crucial to reducing mortality and improving patient outcomes. However, the lack of specific early symptoms and reliable diagnostic markers often lead...

Full description

Saved in:
Bibliographic Details
Main Authors: Wenjing Lu, Minghan Li, DanZeng LaMu, Hui Qian, Zhaofeng Liang, Xuezhong Xu
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Cell and Developmental Biology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fcell.2025.1560583/full
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Gastric cancer is one of the common malignant tumors of digestive tract. Early diagnosis, process monitoring, and appropriate treatment strategies are crucial to reducing mortality and improving patient outcomes. However, the lack of specific early symptoms and reliable diagnostic markers often leads to delayed diagnosis and suboptimal treatment strategies. Exosomes, as small vesicular structures derived from endosomes, play crucial roles in cell-to-cell communication and have emerged as promising biomarkers and therapeutic targets in various cancers, including gastric cancer. This comprehensive review delves into the significance of exosomes and their cargo proteins, particularly focusing on their applications in the diagnosis, progress and treatment of gastric cancer. Based on this review, we believe that the real-time release characteristics of extracellular vesicle proteins make them an ideal tool for dynamically monitoring gastric cancer progression and treatment response. The potential of extracellular vesicles in “liquid biopsy” can be explored to replace traditional invasive examinations and achieve non-invasive and continuous disease monitoring. In the future, nanotechnology can be combined with artificial intelligence to develop an efficient extracellular vesicle protein capture and analysis platform, in order to enhance diagnostic sensitivity and specificity.
ISSN:2296-634X