■TGF-β信号传导是癌症中免疫和多种细胞行为的关键调节因子。然而,TGF-β信号传导相关基因在卵巢癌(OV)中的预后和治疗作用尚待研究.
■当前研究中使用的OV数据来自TCGA和GEO数据库。使用TGF-β信号传导相关基因,将共识聚类用于将OV患者分类为不同的聚类。通过“limma”R包筛选不同簇之间的差异表达基因(DEGs)。通过单变量Cox回归从DEGs中筛选预后基因,其次是TGF-β信号相关评分的构建。在训练和测试OV队列中评估TGF-β信号传导相关评分的预后价值。此外,免疫状态,进行了低评分组和高评分组之间的GSEA和治疗反应,以进一步揭示潜在的机制。
■通过共识聚类,OV患者分为具有不同肿瘤免疫环境的两个集群。在差异表达和单变量Cox回归分析后,GMPR,PIEZO1、EMP1、CXCL13、GADD45B、SORCS2,FOSL2,PODN,选择LYNX1和SLC38A5作为预后基因。使用PCA算法,OV患者的TGF-β信号相关评分基于预后基因计算.然后将OV患者分为TGF-β信号相关评分低和高的组。我们观察到两个评分组的生存率明显不同,肿瘤免疫环境和免疫检查点的表达。此外,GSEA结果显示,免疫相关通路和生物过程,像趋化因子信号通路,TNF信号通路和T细胞迁移在低分组中显著富集。此外,低评分组和高评分组患者对化疗和免疫治疗的敏感性显著不同.
■第一次,我们的研究确定了十个与TGF-β信号相关的预后基因,构建了TGF-β信号相关的预后评分,并研究了TGF-β信号相关评分对OV免疫和治疗的影响。这些发现可以丰富我们对OV预后中TGF-β信号传导的认识,并有助于改善OV的预后预测和治疗策略。
UNASSIGNED: TGF-beta signaling is a key regulator of immunity and multiple cellular behaviors in cancer. However, the prognostic and therapeutic role of TGF-beta signaling-related genes in ovarian cancer (OV) remains unexplored.
UNASSIGNED: Data of OV used in the current study were sourced from TCGA and GEO databases. Consensus clustering was applied to classify OV patients into different clusters using TGF-beta signaling-related genes. Differentially expressed genes (DEGs) between different clusters were screened by the \"limma\" R package. Prognostic genes were screened from DEGs by univariate Cox regression, followed by the construction of the TGF-beta signaling-related score. The prognostic value of TGF-beta signaling-related score was evaluated in both training and testing OV cohorts. Moreover, the immune status, GSEA and therapeutic response between low- and high-score groups were performed to further reveal the potential mechanisms.
UNASSIGNED: By consensus clustering, OV patients were classified into two clusters with different tumor immune environments. After differential expression and univariate Cox regression analyses, GMPR, PIEZO1, EMP1, CXCL13, GADD45B, SORCS2, FOSL2, PODN, LYNX1 and SLC38A5 were selected as prognostic genes. Using PCA algorithm, the TGF-beta signaling-related score of OV patients was calculated based on prognostic genes. Then OV patients were divided into low- and high-TGF-beta signaling-related score groups. We observed that the two score groups had significantly different survivals, tumor immune environments and expressions of immune checkpoints. In addition, GSEA results showed that immune-related pathways and biological processes, like chemokine signaling pathway, TNF signaling pathway and T cell migration were significantly enriched in the low-score group. Moreover, patients in the low- and high-score groups had remarkably different sensitivity to chemo- and immunotherapy.
UNASSIGNED: For the first time, our study identified ten prognostic genes associated with TGF-beta signaling, constructed a prognostic TGF-beta signaling-related score and investigated the effect of TGF-beta signaling-related score on OV immunity and therapy. These findings may enrich our knowledge of the TGF-beta signaling in OV prognosis and help to improve the prognosis prediction and treatment strategies in OV.