TGF-beta信号通路是免疫和癌症中多种细胞行为的关键调控因子。然而，TGF-beta信号通路相关基因在卵巢癌（OV）中的预后和治疗作用仍未被探索。本研究所使用的OV数据来源于TCGA和GEO数据库。应用共识聚类方法，基于TGF-beta信号通路相关基因将OV患者分为不同的簇。利用“limma” R包筛选不同簇之间的差异表达基因（DEGs）。通过单变量Cox回归分析，从DEGs中筛选预后基因，并构建TGF-beta信号通路相关评分。在训练和测试OV队列中评估TGF-beta信号通路相关评分的预后价值。此外，对低评分组和高评分组进行免疫状态、GSEA和治疗反应的比较，以进一步揭示潜在机制。 通过共识聚类方法，我们将OV患者分为两个具有不同肿瘤免疫环境的簇。经差异表达和单变量Cox回归分析后，我们选择了GMPR、PIEZO1、EMP1、CXCL13、GADD45B、SORCS2、FOSL2、PODN、LYNX1和SLC38A5作为预后基因。通过主成分分析算法，我们根据预后基因计算了OV患者的TGF-beta信号通路相关评分。然后将OV患者分为低评分组和高评分组。我们观察到两个评分组的生存期、肿瘤免疫环境和免疫检查点的表达显著不同。此外，GSEA结果显示在低评分组中免疫相关的通路和生物过程，如趋化因子信号通路、TNF信号通路和T细胞迁移，严重富集。此外，低评分组和高评分组的患者对化疗和免疫疗法的敏感性也存在明显差异。 我们的研究首次鉴定了与TGF-beta信号通路相关的十个预后基因，构建了预后相关的TGF-beta信号通路评分，并研究了TGF-beta信号通路评分对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-beta信号通路的认知，并有助于改善OV预后预测和治疗策略。 © 2023 The Authors.

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.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.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.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.© 2023 The Authors.