Integrative analysis of saliva-derived exosomal proteome and lipidome for the diagnosis of esophageal squamous cell carcinoma
By: Zhong, Wei, Liu, Jian, Xie, Junhua, Zhang, Zhiyan, Gong, Zhiwen, Yan, Zhixiang, Cao, Qingdong

BioMed Central
2025-08-01; doi: 10.1186/s12885-025-14452-x

Abstract

Background

Early diagnosis of esophageal squamous cell carcinoma (ESCC) is crucial for improving patient prognosis. Currently, the diagnosis of ESCC primarily relies on endoscopic biopsy. Salivary exosomes have shown great potential in non-invasive screening, but their proteomic and lipidomic characteristics remain to be reported.

Methods

Exosomes were isolated from salivary samples of 54 patients with ESCC and 62 healthy controls using ultracentrifugation, and subsequently subjected to non-targeted proteomic and lipidomic analysis by liquid chromatography-tandem mass spectrometry (LC–MS/MS). Differentially expressed proteins and lipids in salivary exosomes were identified through differential analysis, and a comprehensive analysis of multi-omics data was performed using correlation analysis.

Results

Significant proteomic and lipidomic differences were observed between ESCC patients and healthy controls. The proteomic characteristics of ESCC were primarily manifested in immune responses, disruption of tissue structural homeostasis, and enhanced antifungal and antimicrobial humoral immune responses. Through multi-omics analysis, we found that ESCC may regulate fatty acid metabolism by modulating epigenetic modifications, thereby influencing the oral immune microenvironment. Finally, a diagnostic model constructed using 28 lipid features achieved excellent diagnostic performance (Are Under the Curve = 1.000) for ESCC diagnosis.

Conclusions

Our study revealed significant alterations in the proteomic and lipidomic profiles of the oral microenvironment in ESCC patients, which may provide new insights into the development and progression of ESCC. We found that lipid features have high potential for diagnosing ESCC, providing support for further validation in larger cohorts.







Copyright 2026 InterMDnet | Privacy Policy | Disclaimer | System Requirements