Department of Blood Transfusion, Longyan First Affiliated Hospital of Fujian Medical University, Longyan City, Fujian Province, 364000, China.
Department of Emergency, Longyan First Affiliated Hospital of Fujian Medical University, Longyan City, Fujian Province, 364000, China.
Curr Pharm Des. 2024;30(39):3131-3152. doi: 10.2174/0113816128326151240820105525.
The Transforming Growth Factor-Beta (TGF-β) signaling pathway plays a crucial role in the pathogenesis of diseases. This study aimed to identify differentially expressed TGF-β-related genes in liver cancer patients and to correlate these findings with clinical features and immune signatures.
The TCGA-STAD and LIRI-JP cohorts were utilized for a comprehensive analysis of TGF-β- related genes. Differential gene expression, functional enrichment, survival analysis, and machine learning techniques were employed to develop a prognostic model based on a TGF-β-related gene signature (TGFBRS).
We developed a prognostic model for liver cancer based on the expression levels of nine TGF-β- related genes. The model indicates that higher TGFBRS values are associated with poorer prognosis, higher tumor grades, more advanced pathological stages, and resistance to chemotherapy. Additionally, the TGFBRS-High subtype was characterized by elevated levels of immune-suppressive cells and increased expression of immune checkpoint molecules. Using a Gradient Boosting Decision Tree (GBDT) machine learning approach, the FKBP1A gene was identified as playing a significant role in liver cancer. Notably, knocking down FKBP1A significantly inhibited the proliferation and metastatic capabilities of liver cancer cells both in vitro and in vivo.
Our study highlights the potential of TGFBRS in predicting chemotherapy responses and in shaping the tumor immune microenvironment in liver cancer. The results identify FKBP1A as a promising molecular target for developing preventive and therapeutic strategies against liver cancer. Our findings could potentially guide personalized treatment strategies to improve the prognosis of liver cancer patients.
转化生长因子-β（TGF-β）信号通路在疾病的发病机制中起着至关重要的作用。本研究旨在鉴定肝癌患者中差异表达的 TGF-β 相关基因，并将这些发现与临床特征和免疫特征相关联。
我们使用 TCGA-STAD 和 LIRI-JP 队列进行了 TGF-β 相关基因的综合分析。采用差异基因表达、功能富集、生存分析和机器学习技术，基于 TGF-β 相关基因特征（TGFBRS）构建了一个预后模型。
我们基于 9 个 TGF-β 相关基因的表达水平建立了肝癌的预后模型。该模型表明，较高的 TGFBRS 值与预后较差、肿瘤分级较高、病理分期较晚以及对化疗的耐药性相关。此外，TGFBRS-High 亚型的特征是免疫抑制细胞水平升高，免疫检查点分子表达增加。使用梯度提升决策树（GBDT）机器学习方法，鉴定 FKBP1A 基因在肝癌中起着重要作用。值得注意的是，敲低 FKBP1A 显著抑制了肝癌细胞在体外和体内的增殖和转移能力。
我们的研究强调了 TGFBRS 在预测化疗反应和塑造肝癌肿瘤免疫微环境方面的潜力。研究结果确定 FKBP1A 是开发预防和治疗肝癌策略的有前途的分子靶标。我们的发现可能为改善肝癌患者的预后提供指导，制定个性化的治疗策略。
