Abstract
BACKGROUND: Colorectal cancer (CRC) remains one of the leading causes of cancer-related morbidity and mortality worldwide. Growing evidence suggests that gut microbial dysbiosis plays a crucial role in tumorigenesis and can influence therapeutic responses. AIM: To explore the associations between serum S100A12 and soluble CD14 (sCD14) levels and gut microbiota alterations in patients with CRC, and to assess the predictive utility of these biomarkers in forecasting chemotherapy response. METHODS: A retrospective analysis was conducted on 104 patients diagnosed with advanced CRC (CRC group) and 104 age-matched and sex-matched healthy controls. Serum concentrations of S100A12 and sCD14 were measured using enzyme-linked immunosorbent assay. Fecal samples collected before chemotherapy were subjected to 16S rRNA sequencing to profile gut microbial composition. Pearson correlation analysis was used to evaluate the relationship between biomarker levels and microbial abundance. Receiver operating characteristic (ROC) curves were used to assess the predictive performance of S100A12 and sCD14 for chemotherapy response. RESULTS: CRC patients exhibited significantly higher serum levels of S100A12 and sCD14 compared to healthy individuals (P < 0.05). Patients with moderate to severe gut dysbiosis showed the highest elevations of these biomarkers (P < 0.05). Elevated levels of S100A12 and sCD14 were positively correlated with Fusobacterium nucleatum and Prevotella abundance, and negatively correlated with Faecalibacterium prausnitzii and Akkermansia muciniphila (P < 0.05). Both biomarkers significantly decreased following chemotherapy (P < 0.05). Non-responders to chemotherapy had higher pre-treatment levels of S100A12 and sCD14 compared to responders (P < 0.05). Combined ROC analysis showed improved diagnostic accuracy compared to either marker alone. CONCLUSION: Serum S100A12 and sCD14 levels are closely associated with gut microbiota imbalance and chemotherapy response in CRC patients. These markers may serve as promising predictive indicators for treatment efficacy and offer potential value in individualized treatment strategies.