Identification of Salivary Biomarkers in Colorectal Cancer by Integrating Olink Proteomics and Metabolomics

Identifying novel
biomarkers is crucial for early detection
of
colorectal cancer (CRC). Saliva, as a noninvasive sample, holds promise
for CRC detection. Here, we used Olink proteomics and untargeted metabolomics
to analyze saliva samples from CRC patients and healthy controls with
the aim of identifying candidate biomarkers in CRC saliva. Univariate
and multivariate analyses revealed 16 differentially expressed proteins
(DEPs) and 40 differentially accumulated metabolites (DAMs). Pathway
enrichment showed DEPs were mainly involved in cancer transcriptional
dysregulation, Toll-like receptor signaling, and chemokine signaling.
Metabolomics analysis highlighted significant changes in amino acid
metabolites, particularly in pathways such as arginine biosynthesis,
histidine metabolism, and cysteine and methionine metabolism. Random
forest analysis and ELISA validation identified four potential biomarkers:
succinate, l-methionine, GZMB, and MMP12. A combined protein-metabolite
diagnostic model was developed using logistic regression, achieving
an area under the curve of 0.933 (95% CI: 0.871–0.996) for
the discovery cohort and 0.969 (95% CI: 0.918–1.000) for the
validation cohort, effectively distinguishing CRC patients from healthy
individuals. In conclusion, our study identified and validated a panel
of noninvasive saliva-based biomarkers that could improve CRC screening
and provide new insights into clinical CRC diagnosis.