谷歌浏览器插件
订阅小程序
在清言上使用

Exosomes multiplex profiling, a promising strategy for early diagnosis of laryngeal cancer.

Journal of translational medicine(2024)

引用 0|浏览8
暂无评分
摘要
BACKGROUND:Exosomes are nanosized vesicles released from all cells into surrounding biofluids, including cancer cells, and represent a very promising direction in terms of minimally invasive approaches to early disease detection. They carry tumor-specific biological contents such as DNA, RNA, proteins, lipids, and sugars, as well as surface molecules that are able to pinpoint the cellular source. By the above criteria, exosomes may be stratified according to the presence of tissue and disease-specific signatures and, due to their stability in such biofluids as plasma and serum, they represent an indispensable source of vital clinical insights from liquid biopsies, even at the earliest stages of cancer. Therefore, our work aimed to isolate and characterize LCa patients' derived exosomes from serum by Flow Cytometry in order to define a specific epitope signature exploitable for early diagnosis. METHODS:Circulating exosomes were collected from serum collected from 30 LCa patients and 20 healthy volunteers by the use of antibody affinity method exploiting CD63 specific surface marker. Membrane epitopes were then characterized by Flow cytometry multiplex analysis and compared between LCa Patients and Healthy donors. Clinical data were also matched to obtain statistical correlation. RESULTS:A distinct overexpression of CD1c, CD2, CD3, CD4, CD11c, CD14, CD20, CD44, CD56, CD105, CD146, and CD209 was identified in LCa patients compared to healthy controls, correlating positively with tumor presence. Conversely, CD24, CD31, and CD40, though not overexpressed in tumor samples, showed a significant correlation with nodal involvement in LCa patients (p < 0.01). CONCLUSION:This approach could allow us to set up a cost-effective and less invasive liquid biopsy protocol from a simple blood collection in order to early diagnose LCa and improve patients' outcomes and quality of life.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要