POU4F1 drives colorectal cancer progression by promoting cell proliferation, metastasis, and chemoresistance

Background: Colorectal cancer remains one of the most prevalent gastrointestinal malignancies. This study aims to identify key genes associated with colorectal cancer recurrence, offering novel insights for prognostic assessment and personalized treatment strategies. Methods: Leveraging the TCGA dataset, we conducted a comprehensive analysis of differentially expressed genes between recurrent and non-recurrent colorectal cancer patients. We developed a Recurrence Associated Genes Signature (RAGS) model for prognostic evaluation and employed nine machine learning algorithms to predict recurrence risk. Furthermore, we performed extensive functional studies on the most significant genes, examining their expression patterns, prognostic relevance, and effects on cellular proliferation, metastasis, and chemoresistance. Results: Our analyses identified 45 key genes linked to colorectal cancer recurrence and prognosis. Using LASSO regression, we constructed the RAGS model, incorporating TMEM213, SAP25, POU4F1, RSPO4, and PAGE2B. This model demonstrated exceptional performance in predicting overall prognosis and post-chemotherapy outcomes. Among the machine learning algorithms tested, XGBoost exhibited the highest diagnostic accuracy for recurrence prediction, with POU4F1 emerging as the most significant predictive gene. Functional experiments revealed that POU4F1 knockdown substantially inhibited colorectal cancer cell proliferation and metastasis both in vitro and in vivo, while also reducing resistance to 5-fluorouracil and oxaliplatin. Conclusion: This study successfully identified crucial genes associated with colorectal cancer recurrence and developed a robust RAGS prognostic model. The XGBoost algorithm underscored the importance of POU4F1 in predicting colorectal cancer recurrence. Our functional analysis of POU4F1 provides fresh insights into colorectal cancer progression mechanisms and informs the development of targeted therapeutic approaches. These findings not only enhance our understanding of colorectal cancer's molecular underpinnings but also establish a solid foundation for advancing precision diagnosis and treatment in clinical practice.