Heliyon (Jan 2024)
The construction, validation and promotion of the nomogram prognosis prediction model of UCEC, and the experimental verification of the expression and knockdown of the key gene GPX4
Abstract
Background: Adequate prognostic prediction of Uterine Corpus Endometrial Carcinoma (UCEC) is crucial for informing clinical decision-making. However, there is a scarcity of research on the utilization of a nomogram prognostic evaluation model that incorporates pyroptosis-related genes (PRGs) in UCEC. Methods: By analyzing data from UCEC patients in the TCGA database, four PRGs associated with prognosis were identified. Subsequently, a “risk score” was developed using these four PRGs and LASSO. Ordinary and web-based dynamic nomogram prognosis prediction models were constructed. The discrimination, calibration, clinical benefit, and promotional value of the selected GPX4 were validated. The expression level of GPX4 in UCEC cell lines was subsequently verified. The effects of GPX4 knock-down on the malignant biological behavior of UCEC cells were assessed. Results: Four key PRGs and a “risk score” were identified, with the “risk score” calculated as (−0.4323) * GPX4 + (0.2385) * GSDME + (0.0525) * NLRP2 + (−0.3299) * NOD2. The nomogram prognosis prediction model, incorporating the “risk score,” “age,” and “FIGO stage,” demonstrated moderate predictive performance (AUC >0.7), good calibration, and clinical significance for 1, 3, and 5-year survival. The web-based dynamic nomogram demonstrated significant promotional value (https://shibaolu.shinyapps.io/DynamicNomogramForUCEC/). UCEC cells exhibited abnormally elevated expression of GPX4, and the knockdown of GPX4 effectively suppressed malignant biological activities, including proliferation and migration, while inducing apoptosis. The findings from tumorigenic experiments conducted on nude mice further validated the results obtained from cellular experiments. Conclusion: Following validation, the nomogram prognosis prediction model, which relies on four pivotal PRGs, demonstrated a high degree of accuracy in forecasting the precise probability of prognosis for patients with UCEC. Additionally, the web-based dynamic nomogram exhibited considerable potential for promotion. Notably, the key gene GPX4 exhibited characteristics of a potential oncogene in UCEC, as it facilitated malignant biological behavior and impeded apoptosis.
