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

IF 3.6 3区 医学 Q2 GASTROENTEROLOGY & HEPATOLOGY
Digestion Pub Date : 2025-09-25 DOI:10.1159/000548266
HaiLi Li, PeiZhen Gao, QingShui Wang, Chao Xu, FangQin Xue
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引用次数: 0

Abstract

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.

POU4F1通过促进细胞增殖、转移和化疗耐药来驱动结直肠癌的进展。
背景:结直肠癌仍然是最常见的胃肠道恶性肿瘤之一。本研究旨在确定与结直肠癌复发相关的关键基因,为预后评估和个性化治疗策略提供新的见解。方法:利用TCGA数据集,我们对复发和非复发结直肠癌患者的差异表达基因进行了全面分析。我们开发了用于预后评估的复发相关基因签名(RAGS)模型,并采用了9种机器学习算法来预测复发风险。此外,我们对最重要的基因进行了广泛的功能研究,检查了它们的表达模式、预后相关性以及对细胞增殖、转移和化疗耐药的影响。结果:我们的分析确定了45个与结直肠癌复发和预后相关的关键基因。利用LASSO回归,我们构建了包含TMEM213、SAP25、POU4F1、RSPO4和PAGE2B的RAGS模型。该模型在预测总体预后和化疗后结果方面表现出色。在测试的机器学习算法中,XGBoost在复发预测方面表现出最高的诊断准确性,其中POU4F1成为最重要的预测基因。功能实验显示,在体外和体内,POU4F1敲低均能显著抑制结直肠癌细胞的增殖和转移,同时降低对5-氟尿嘧啶和奥沙利铂的耐药性。结论:本研究成功鉴定了与结直肠癌复发相关的关键基因,并建立了一个可靠的RAGS预后模型。XGBoost算法强调了POU4F1在预测结直肠癌复发中的重要性。我们对POU4F1的功能分析为结直肠癌的进展机制提供了新的见解,并为靶向治疗方法的发展提供了信息。这些发现不仅加深了我们对结直肠癌分子机制的认识,也为在临床实践中推进精准诊断和治疗奠定了坚实的基础。
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来源期刊
Digestion
Digestion 医学-胃肠肝病学
CiteScore
7.90
自引率
0.00%
发文量
39
审稿时长
6-12 weeks
期刊介绍: ''Digestion'' concentrates on clinical research reports: in addition to editorials and reviews, the journal features sections on Stomach/Esophagus, Bowel, Neuro-Gastroenterology, Liver/Bile, Pancreas, Metabolism/Nutrition and Gastrointestinal Oncology. Papers cover physiology in humans, metabolic studies and clinical work on the etiology, diagnosis, and therapy of human diseases. It is thus especially cut out for gastroenterologists employed in hospitals and outpatient units. Moreover, the journal''s coverage of studies on the metabolism and effects of therapeutic drugs carries considerable value for clinicians and investigators beyond the immediate field of gastroenterology.
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