Identification and Verification of Immune-Related Genes Prognostic Signature Based on ssGSEA for Adrenocortical Carcinoma (ACC)

PURPOSE: Adrenocortical carcinoma (ACC) is an endocrine malignant tumor with poor prognosis. The study aimed to construct ACC immune-related gene prognostic signature and verify the efficacy of prognostic signature. METHODS: ACC RNA-seq data and clinical information are downloaded from TCGA databases and GEO databases. We used single sample gene set enrichment analysis (ssGSEA) to assess immune cell infiltration in ACC patients and ACC patients were divided into high- and low-immune cell infiltration clusters. The validity of ssGSEA grouping was verified using the ESTIMATE algorithm. A total of 275 differentially expressed immune-related genes (IRGs) were obtained from the intersection of IRGs and differentially expressed genes (DEGs) in high and low immune cell infiltration clusters. LASSO analysis was used to identify 13 IRGs that regulate the prognosis of ACC patients through immune infiltration. Kaplan–Meier analysis, ROC curve, univariate and multivariate Cox regression further confirmed that these 13 immune-related gene signatures were innovative and significant prognostic factors, which were independent of clinical features. Finally, ACC prognostic nomogram was constructed, ROC curve and calibration curve were drawn to evaluate the accuracy of the prognostic nomogram. RESULTS: LASSO regression analysis was used to screen out ACC survival-related genes. Univariate and multivariate Cox proportional risk regression models were used to analyze and construct the ACC prognosis nomogram. The AUC for predicting 1-, 3- and 5-year overall survival rate of ACC patients was 0.799, 0.966 and 0.969, suggesting good prediction accuracy. The calibration curve shows that the predicted results of the prognostic nomogram are in good agreement with the actual situation. CONCLUSION: ssGSEA technique plays an important role in the construction of ACC prognostic model. Based on IRGs associated with survival independently predicted ACC prognosis, we identified thirteen immune-related genes as prognostic signature for ACC.