Front Pharmacol. 2025 ;16 1577232
Lin Shi,
Dongqi Yuan,
Fuyi Zhu,
Yuchao He,
Ran Zuo,
Liwei Chen,
Yi Luo,
Yu Wang,
Dingzhi Huang,
Peng Chen,
Hua Guo.
Background: 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.
Methods: 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.
Results: 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.
Conclusion: 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.
Keywords: EMT; FUCA1; immune cell; machine learning; malignant pleural mesothelioma