ITRAQ and PRM-based quantitative saliva proteomics in gastric cancer: biomarker discovery
Zhanyan Liu1,2, Jieren Liu3, Zaid Chachar4,5
1The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Medical Innovation Technology Transformation Center of Shenzhen Second People's Hospital, Shenzhen University, Shenzhen Translational Medicine Institute, Shenzhen, China.
Background:
Salivary proteomics is a non-invasive, low-cost, and real-time diagnostic approach increasingly applied in cancer research. Salivary biomarkers hold particular promise for the early identification of gastric cancer (GC). This study aimed to detect salivary proteins altered in GC and evaluate their potential as novel non-invasive biomarkers.
Methods:
We analyzed salivary proteomes from GC patients (group 1: n = 12; group 2: n = 13) and healthy controls (n = 11) using isobaric tags for relative and absolute quantitation (iTRAQ). Differentially expressed proteins (DEPs) were identified and functionally annotated using gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and protein-protein interaction (PPI) networks. Candidate proteins were further validated by parallel reaction monitoring (PRM), and prognostic significance was assessed through Kaplan-Meier (KM) survival analysis.
Results:
A total of 671 proteins with unique peptide segments were identified. Among them, 124 and 102 proteins were significantly differentially expressed in GC groups 1 and 2, respectively, compared with controls. Fifty-six overlapping DEPs were detected between the two GC groups, including 24 upregulated and 32 downregulated proteins. Functional enrichment and PRM validation highlighted four key proteins (S100A8, S100A9, CST4, CST5) with consistent differential expression. Interestingly, CST4 and CST5 were downregulated in saliva but upregulated in GC tissue and blood.
Conclusion:
Our findings demonstrate that salivary proteins, particularly S100A8, S100A9, CST4, and CST5, hold significant potential as non-invasive biomarkers for gastric cancer detection. These results provide new insights into saliva-based diagnostics and highlight the importance of cross-comparison with tissue and blood expression profiles.
