A Ubiquitin-Proteasome Gene Signature for Predicting Prognosis in Patients With Lung Adenocarcinoma - Tang, Yunliang; Guo, Yinhong (Frontiers in Genetics, 2022)
Background: Dysregulation of the ubiquitin-proteasome system (UPS) can lead to instability in the cell cycle and may act as a crucial factor in both tumorigenesis and tumor progression. However, there is no established prognostic signature based on UPS genes (UPSGs) for lung adenocarcinoma (LUAD) despite their value in other cancers. Methods: We retrospectively evaluated a training dataset of 477 LUAD patients from The Cancer Genome Atlas was analyzed through multivariate Cox and Lasso regression analyses. Two independent datasets (GSE31210 and GSE50081) containing 226 and 128 LUAD samples, respectively, were used for validation. Results: An eight-UPSG signature, including ARIH2, FBXO9, KRT8, MYLIP, PSMD2, RNF180, TRIM28, and UBE2V2, was established. Kaplan-Meier survival analysis and time-receiver operating characteristic curves for the training and validation datasets revealed that this risk signature presented with good performance in predicting overall and relapsed-free survival. Based on the signature and its associated clinical features, a nomogram and corresponding web-based calculator for predicting survival were established. Calibration plot and decision curve analyses showed that this model was clinically useful for both the training and validation datasets. Finally, a web-based calculator (https://ostool.shinyapps.io/lungcancer) was built to facilitate convenient clinical application of the signature. Conclusion: Au UPSG based model was developed and validated in this study, which may be useful as a novel prognostic predictor for LUAD.