肿瘤细胞治疗研究
英文原题：Immune Microenvironment Signatures Predict Response and Survival in Rectal Cancer Patients After Neoadjuvant Chemoradiation.
免疫相关基因表达模式与直肠癌nCRT反应相关。S100A8、SPINK5、ANXA1、FOXJ1和CLEC7A的高表达水平提示治疗反应良好，且S100A8和SPINK5与预后相关。由免疫相关基因组成的机器学习模型显示出强大的预测潜力。我们的结果支持使用免疫基因特征来指导直肠癌的个性化治疗。
直肠癌对新辅助放化疗（nCRT）的反应存在差异。近期研究强调了肿瘤免疫微环境在影响肿瘤行为中的作用。在此，我们旨在评估直肠癌nCRT后免疫相关基因的表达，并探讨其作为预测和预后生物标志物的潜力。
对48例接受nCRT后的直肠癌患者，使用NanoString nCounter平台和PanCancer Immune Profiling panel对730个免疫相关基因进行了表达谱分析。比较了良好反应者和不良反应者之间的差异表达基因，并进行了基因集富集分析。分析了这些基因的预后意义。构建了一个遗传模型来预测nCRT反应。
我们鉴定出24个免疫相关基因在应答良好者和应答不良者之间存在差异表达，其中S100A8、SPINK5、ANXA1、FOXJ1和CLEC7A在应答良好者中显示高表达水平（Log2 fold change >1，p <0.05）。通路分析显示，这些基因主要参与与NK 细胞介导的细胞毒性相关的生物学过程。S100A8和SPINK5表达水平与无复发生存期相关（分别为p =0.001和0.036），这些发现在一个公开可用的数据集中得到验证（S100A8；p =0.015，和SPINK5；p =0.024）。由TLR4、CCND3、TCF7、CREB5、TNFRSF10B、DPP4、PBK、DUSP4和MUC1组成的预测模型的准确率为85.7%。
BACKGROUND/AIM: Response to neoadjuvant chemoradiotherapy (nCRT) in rectal cancer varies. Recent studies have highlighted the role of the tumor immune microenvironment in influencing tumor behavior. Herein, we aimed to assess immune-related gene expression in rectal cancer following nCRT and to investigate their potential as predictive and prognostic biomarkers. MATERIALS AND METHODS: Expression profiling of 730 immune-related genes was conducted in 48 post-nCRT rectal cancer using the NanoString nCounter platform and the PanCancer Immune Profiling panel. Differentially expressed genes were compared between good and poor responders, and gene set enrichment analysis was conducted. The prognostic significance of these genes was analyzed. A genetic model was generated to predict nCRT responses. RESULTS: We identified 24 immune-associated genes that were differentially expressed between good and poor responders, among which S100A8, SPINK5, ANXA1, FOXJ1 , and CLEC7A showed high expression levels in good responders (Log2 fold change >1, p <0.05). Pathway analysis revealed that these genes were mainly involved in biological process associated with natural killer cell-mediated cytotoxicity. S100A8 and SPINK5 expression levels were associated with relapse-free survival ( p =0.001 and 0.036, respectively), and these findings were validated in a publicly available dataset ( S100A8 ; p =0.015, and SPINK5 ; p =0.024). The accuracy of the predictive model comprising TLR4, CCND3, TCF7, CREB5, TNFRSF10B, DPP4, PBK, DUSP4 , and MUC1 was 85.7%. CONCLUSION: Immune-related gene expression patterns are associated with response to nCRT in rectal cancer. High expression levels of S100A8, SPINK5, ANXA1, FOXJ1 , and CLEC7A were indicative of favorable treatment response, and S100A8 and SPINK5 were associated with prognosis. A machine learning-based model composed of immune-related genes showed strong predictive potential. Our results support the use of immune gene signatures to guide personalized therapy in rectal cancer.
MEMBER ACCOUNT
登录成功会直接打开下一页。
