Abstract
Colorectal cancer (CRC) remains a significant global health challenge due to its high prevalence and mortality rates. Zinc transporter proteins of the SLC39A family are crucial mediators of metal ion transport and have been implicated in numerous diseases, including cancer. However, the specific molecular mechanisms underpinning their impact on CRC progression remain poorly understood. By analyzing thousands of CRC patient samples from large-scale public databases, we constructed a SLC39A family-related signature (SFRS) for prognostic prediction through the integration of 101 combinations of 10 machine learning algorithms. This model was utilized to explore tumor biology, immune microenvironment composition, mutation patterns, and responses to immunotherapy in CRC patients. To reinforce these findings, immunohistochemistry (IHC) analyses were conducted on our in-house cohort (RJ-TMA-Cohort) to examine expression levels of two key molecules, SLC39A8 and SLC39A14, and their associations with CRC progression. The SFRS model demonstrated excellent predictive performance, effectively stratifying CRC patients based on tumor characteristics, immune microenvironment, mutation features, and immunotherapy responses. Moreover, IHC and bioinformatic analyses revealed that SLC39A8 and SLC39A14 expression levels are closely associated with CRC progression, emphasizing their potential roles in tumor microenvironment regulation and their value as biomarkers and therapeutic targets. This study is the first to comprehensively investigate the functions of the SLC39A family in CRC, offering novel insights into their roles in tumor development, prognosis, and potential relevance to immunotherapy response. The SFRS model represents a powerful tool for clinical applications, while SLC39A8 and SLC39A14 present promising avenues for future research and therapeutic strategies.