Department of Urology, Dongguan People's Hospital, Affiliated to Southern Medical University, Dongguan, China.
Dongguan Institute of Clinical Cancer Research, Department of Medical Oncology, Affiliated to Dongguan Hospital, Southern Medical University (Dongguan People's Hospital), Dongguan, China.
Dis Markers. 2023 Feb 21;2023:7342882. doi: 10.1155/2023/7342882. eCollection 2023.
FGF signaling is critical to controlling various cancers. Nevertheless, the functions of FGF-related genes in PCa are still unknown.
The objective of this study is to build a FGF-related signature that was capable of accurately predicting PCa survival and prognosis for BCR.
The univariate and multivariate Cox regression, infiltrating immune cells, LASSO, and GSEA analyses were carried out to build a prognostic model.
A FGF-related signature that consists of PIK3CA and SOS1 was developed for the purpose of predicting PCa prognosis, and all patients were categorized into low- and high-risk groups. In comparison to the low-risk group, high-risk score patients had poorer BCR survival. This signature's predictive power has been investigated utilizing the AUC of the ROC curves. The risk score has been shown to be an independent prognostic factor by multivariate analysis. The four enriched pathways of the high-risk group were obtained by gene set enrichment analysis (GSEA) and found to be associated with the tumorigenesis and development of PCa, including focal adhesion, TGF- signaling pathway, adherens junction, and ECM receptor interaction. The high-risk groups had considerably higher levels of immune status and tumor immune cell infiltration, suggesting a more favorable response to immune checkpoint inhibitors. IHC found that the expression of the two FGF-related genes in the predictive signature was extremely different in PCa tissues.
To summarize, our FGF-related risk signature may effectively predict and diagnose PCa, indicating that in PCa patients, they are potential therapeutic targets and promising prognostic biomarkers.
FGF 信号对于控制各种癌症至关重要。然而,FGF 相关基因在前列腺癌中的功能仍不清楚。
本研究旨在构建一个能够准确预测前列腺癌患者无生化复发生存(BCR)预后的 FGF 相关基因签名。
采用单因素和多因素 Cox 回归、浸润免疫细胞、LASSO 和 GSEA 分析构建预后模型。
构建了一个由 PIK3CA 和 SOS1 组成的 FGF 相关基因签名,用于预测前列腺癌的预后,所有患者被分为低风险组和高风险组。与低风险组相比,高风险评分患者的 BCR 生存较差。通过 ROC 曲线的 AUC 研究了该签名的预测能力。多因素分析表明,风险评分是独立的预后因素。通过基因集富集分析(GSEA)获得了高风险组的四个富集途径,发现它们与前列腺癌的发生和发展有关,包括粘着斑、TGF-信号通路、粘着连接和 ECM 受体相互作用。高风险组的免疫状态和肿瘤免疫细胞浸润水平明显较高,提示对免疫检查点抑制剂有更好的反应。免疫组织化学发现预测签名中两个 FGF 相关基因在前列腺癌组织中的表达差异极大。
总之,我们的 FGF 相关风险签名可能有效地预测和诊断前列腺癌,表明在前列腺癌患者中,它们是潜在的治疗靶点和有前途的预后生物标志物。