Shi Lin, Yuan Dongqi, Zhu Fuyi, He Yuchao, Zuo Ran, Chen Liwei, Luo Yi, Wang Yu, Huang Dingzhi, Chen Peng, Guo Hua
Department of Tumor Cell Biology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Department of Thoracic Oncology, Lung Cancer Diagnosis and Treatment Center, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Front Pharmacol. 2025 May 23;16:1577232. doi: 10.3389/fphar.2025.1577232. eCollection 2025.
Malignant pleural mesothelioma (MPM) is a rare type of tumor closely associated with asbestos exposure. Increasing evidence shows that high immuno-heterogeneity reduces the therapeutic efficacy of MPM. At present, good biomarkers to screen immunodominant populations and predict the efficacy of immunotherapy are lacking.
In this study, expression data from TCGA, GSE2459, GSE51024, and GSE29354 were integrated for model construction. An eight-gene risk score model (FLI1, IL32, FUCA1, CCR2, PSMB10, CCL5, WT1, and KRT5) was constructed using CIBERSORT, weighted gene co-expression network analysis, Cox regression analysis, differentially expressed gene analysis, and protein-protein interaction network. The K-M survival analysis was used to evaluate the prediction ability of the risk score model. The TIDE database and Oncology Drug Sensitivity Genomics database were used to assess the predictive power of risk score models for treatment. In addition, the expression of the key gene in para-carcinoma tissue and MPM samples were detected by Immunohistochemistry. Patient clinical information was employed to evaluate the relationship between key genes and patient survival. Finally, the biological functions of the key gene were examined by in vitro and in vivo experiments.
The score model was used to divide patients with MPM into low- and high-risk groups. The high-risk group was characterized by a survival disadvantage, and they were less sensitive to immunotherapy. Clinical data suggest that FUCA1, which is a key gene in the model, is an independent risk factor for predicting the prognosis of patients with MPM. A series of experiments demonstrated that FUCA1 expression was negatively correlated with the proliferation, invasion and migration abilities of MPM cells. Further studies revealed that FUCA1 inhibited epithelial-mesenchymal transition in MPM cells by regulating the PI3K-AKT signaling pathway.
The risk score model provides a new perspective for screening potential populations to benefit from immunotherapy and predicting their survival. FUCA1 may be a potential prognostic biomarker and promising therapeutic target for patients with MPM.
恶性胸膜间皮瘤（MPM）是一种与石棉暴露密切相关的罕见肿瘤类型。越来越多的证据表明，高度的免疫异质性降低了MPM的治疗效果。目前，缺乏用于筛选免疫优势人群和预测免疫治疗疗效的良好生物标志物。
在本研究中，整合了来自TCGA、GSE2459、GSE51024和GSE29354的表达数据用于模型构建。使用CIBERSORT、加权基因共表达网络分析、Cox回归分析、差异表达基因分析和蛋白质-蛋白质相互作用网络构建了一个八基因风险评分模型（FLI1、IL32、FUCA1、CCR2、PSMB10、CCL5、WT1和KRT5）。采用K-M生存分析评估风险评分模型的预测能力。使用TIDE数据库和肿瘤药物敏感性基因组学数据库评估风险评分模型对治疗的预测能力。此外，通过免疫组织化学检测癌旁组织和MPM样本中关键基因的表达。利用患者临床信息评估关键基因与患者生存之间的关系。最后，通过体外和体内实验研究关键基因的生物学功能。
该评分模型用于将MPM患者分为低风险和高风险组。高风险组具有生存劣势，且对免疫治疗不太敏感。临床数据表明，模型中的关键基因FUCA1是预测MPM患者预后的独立危险因素。一系列实验表明，FUCA1表达与MPM细胞的增殖、侵袭和迁移能力呈负相关。进一步研究发现，FUCA1通过调节PI3K-AKT信号通路抑制MPM细胞的上皮-间质转化。
风险评分模型为筛选可能从免疫治疗中获益的潜在人群及其生存预测提供了新的视角。FUCA1可能是MPM患者潜在的预后生物标志物和有前景的治疗靶点。
