HGF knockdown suppresses ovarian cancer malignancy: insights from a transient receptor potential-related gene model

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BACKGROUND: Ovarian carcinoma (OV) is a prevalent gynecologic malignancy. While transient receptor potential (TRP) channels are substantially correlated with tumor growth, their role in OV remains unclear. This study therefore aims to construct a comprehensive TRP-related prognostic model and analyze its association with the cell infiltration and checkpoint expression. METHODS: Based on transcriptomic data from public OV databases, TRP activity scores were calculated using single-sample gene set enrichment analysis (ssGSEA), and correlated gene modules were identified through Weighted Gene Co-expression Network Analysis (WGCNA). Functional enrichment analysis was performed to elucidate underlying biological pathways. A prognostic signature was developed via machine learning algorithms, and its clinical utility was validated through construction of a nomogram integrating key clinicopathological parameters. Comprehensive immune characterization was conducted to compare microenvironmental features between risk subgroups. Finally, functional assays including cell counting kit-8 (CCK-8), wound healing, and Transwell were employed to experimentally validate the role of a candidate gene in OV progression. RESULTS: Of the 21 co-expression modules identified, the brown module demonstrated the strongest positive correlation with TRP scores. Functional enrichment analysis revealed that TRP-related genes were predominantly involved in immune system pathways. Using the nine identified genes, a risk model was developed, and Riskscore was employed to categorize patients into high- and low-risk groups. Overall survival (OS) was notably higher for patients in the OV low-risk group than for those in the high-risk group. The nomogram's findings demonstrated that the Riskscore had an independent impact on prognosis. According to immunological characterization, the low-risk group had higher levels of cellular infiltration, including activated B cells and activated CD4 T cells. High-risk group had low expressions of immune checkpoint genes, including LAG3, CD274, and CD27. In vitro tests showed that HGF knockdown markedly reduced the viability, motility, and invasion of OV cells. CONCLUSION: The TRP-related gene signature constructed in this study predicts the prognosis and immune microenvironment status of OV patients, providing a new perspective for prognosis assessment and targeted therapy in OV.

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