Shi Yao, Lei Changjiang, Jiang Hong, Hong Yan, Su Wei, Wu Shanxia, Yang Xiaobo
Department of Neonatology, Key Laboratory for Molecular Diagnosis of Hubei Province, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, China.
Department of Oncology, The Fifth Hospital of Wuhan, Hubei, 430050, China.
Mol Biotechnol. 2025 Apr 3. doi: 10.1007/s12033-025-01395-8.
Uveal melanoma (UVM) is the second most common type of malignant melanoma occurring in the eye, which arises from the interstitial melanocytes in the uveal tract. This study aims to identify a highly efficient biomarker for the immunotherapy against UVM. Initially, a comprehensive analysis was conducted using the transcriptional and clinical data from The Cancer Genome Atlas (TCGA) database through the immune and stromal scores to assess the composition of infiltrating immune cells in the tumor microenvironment. Further, the expression of BCL2-Associated X, Apoptosis Regulator (BAX), and its co-expression gene networks were analyzed using the weighted gene co-expression network analysis (WGCNA) to identify relevant gene modules and hub genes. The immunohistochemistry (IHC) analysis was carried out to confirm the influence of BAX on immune infiltration. In addition, the survival analysis on the hub genes, including BAX, was performed using an external dataset from the Gene Expression Omnibus (GEO) to corroborate the prognostic significance of these genes in an independent patient cohort. A nomogram integrating patients' clinical features was developed to predict the survival outcomes. Our investigations revealed that high BAX expression was associated with severe clinical characteristics and poor prognosis in UVM. Our analyses identified 12 hub genes at the intersection of differentially expressed genes categorized by BAX expression levels and a co-expression gene model. Further, the GEO database validated the prognostic significance of these hub genes. The IHC analysis established a significant correlation between BAX expression and immune infiltration. This nomogram model demonstrated robust predictive efficiency with a concordance index (C-index) of 0.909 (95% CI: 0.846-0.971), indicating excellent discriminative ability. The calibration curves for 1-year, 3-year, and 5-year overall survival (OS) rates confirmed the nomogram's accuracy, closely reflecting the actual patient outcomes. Finally, the Decision Curve Analysis (DCA) revealed that this nomogram could accurately predict OS for a majority of patients, covering a probability range of 25-95%. Our research may provide a new therapeutic regimen to benefit the UVM patients.
葡萄膜黑色素瘤（UVM）是眼部发生的第二常见的恶性黑色素瘤类型，它起源于葡萄膜中的间质黑素细胞。本研究旨在确定一种针对UVM免疫治疗的高效生物标志物。首先，通过免疫和基质评分，利用来自癌症基因组图谱（TCGA）数据库的转录和临床数据进行综合分析，以评估肿瘤微环境中浸润免疫细胞的组成。此外，使用加权基因共表达网络分析（WGCNA）分析凋亡调节因子BCL2相关X（BAX）的表达及其共表达基因网络，以识别相关基因模块和枢纽基因。进行免疫组织化学（IHC）分析以确认BAX对免疫浸润的影响。此外，使用来自基因表达综合数据库（GEO）的外部数据集对包括BAX在内的枢纽基因进行生存分析，以证实这些基因在独立患者队列中的预后意义。开发了一个整合患者临床特征的列线图，以预测生存结果。我们的研究表明，BAX高表达与UVM的严重临床特征和不良预后相关。我们的分析在按BAX表达水平分类的差异表达基因与共表达基因模型的交叉点处鉴定出12个枢纽基因。此外，GEO数据库验证了这些枢纽基因的预后意义。IHC分析确定了BAX表达与免疫浸润之间的显著相关性。该列线图模型显示出强大的预测效率，一致性指数（C指数）为0.909（95%CI：0.846 - 0.971），表明具有出色的判别能力。1年、3年和5年总生存率（OS）的校准曲线证实了列线图的准确性，密切反映了实际患者结果。最后，决策曲线分析（DCA）表明，该列线图可以准确预测大多数患者的OS，涵盖概率范围为25% - 95%。我们的研究可能为UVM患者提供一种新的治疗方案。
