To identify sensitive, and specific biomarkers for colorectal cancer (CRC) and to obtain deeper insights into the underlying pathophysiology and potential pharmacological targets associated with CRC. Forty cancer tissues and their paired paracancer counterparts were collected and systematically profiled using non-targeted metabolomics to characterize endogenous metabolites and related metabolic pathways. Proteomic analysis integrated with machine learning approaches was employed to screen and identify featured proteins. Molecular docking analysis was subsequently conducted to validate potential therapeutic targets in CRC. Significant differences in metabolic characteristics were observed between cancer and paired paracancer tissues, between colon cancer (CC) and rectal cancer (RC), and between the mFOLFOX6 and XELOX treatment regimens. The differential metabolites identified demonstrated high diagnostic area under the curve values and were capable of serving as endogenous biomarkers for CRC diagnosis, distinguishing CC from RC, and reflecting regimen-specific metabolic responses induced by mFOLFOX6 and XELOX. Additionally, featured proteins distinguishing cancer from paracancer tissues, as well as CC from RC, were successfully validated. Notably, several of these featured proteins were further identified as therapeutic targets associated with the mFOLFOX6 regimen. This study delineates the comprehensive metabolic and proteomic landscape of CRC, identifies candidate biomarkers for disease diagnosis and subtype differentiation, and reveals potential chemotherapy-related therapeutic targets. These findings provide a preliminary foundation for developing more precise diagnostic biomarkers and targeted therapeutic approaches for CRC.
Li et al. (Sat,) studied this question.