Development and prognostic significance of inflammation-related key genes model in hepatocellular carcinoma
Objective:To screen key inflammatory genes closely related to the prognosis of hepatocellular carcino-ma(HCC),construct a prognostic risk score model,and evaluate the prognostic value of this model in HCC.Methods:The mRNA expression data of liver tumor tissues and normal liver tissues of HCC patients were obtained from the TCGA database as the training set,and the mRNA expression data of HCC patients from the GEO database as the validation set.LASSO regression and Random survival forest(RSF)method were used to screen the key genes of inflammatory response related to HCC prognosis.Based on these key genes,a prognostic risk score model was constructed and validated.Cox proportional risk regression was applied to evaluate the effect of this model on patient prognosis.Construct a nomogram and perform a consistency analysis.Results:The study identified fifteen inflammation-related genes associated with HCC prognosis.After conducting LASSO regression and RSF analysis,eleven key inflammation-related genes were determined:IL18RAP,MEP1A,RIPK2,CYBB,SLC7A1,ADM,IL7R,P2RX4,ACVR2A,SERPINE1,and SLC7A2.The prognostic risk scoring model predicted 1-year,3-year,and 5-year survival rates with AUC values exceeding 0.60 in both the training and validation sets.Kaplan-Meier a-nalysis revealed that the high-risk group exhibited significantly lower overall survival rates compared to the low-risk group(P＜0.01).Furthermore,the PCA and t-SNE analyses demonstrated the model's effectiveness in distinguis-hing high-and low-risk patients.The Cox regression analysis showed that the prognostic risk score was an independ-ent prognostic factor significantly correlated with overall survival(P＜0.01).The nomogram model attained a C-in-dex of 0.672,indicating high predictive accuracy.The calibration and standard curves for 1-year and 3-year pre-dictions demonstrated good concordance,although slightly weaker concordance was observed for 5-year predictions.Conclusion:This study successfully developed and validated a risk scoring model based on inflammation-related genes.The eleven identified genes(IL18RAP,MEP1A,RIPK2,CYBB,SLC7A1,ADM,IL7R,P2RX4,ACVR2A,SERPINE1,and SLC7A2)are closely associated with HCC progression and demonstrate robust prognos-tic predictive power within the model.
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