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Background: Ubiquitin-proteasome system (UPS) is implicated in cancer occurrence and progression. Targeting UPS is emerging as a promising therapeutic target for cancer treatment. Nevertheless, the clinical significance of UPS in hepatocellular carcinoma (HCC) has not been entirely elucidated. Methods: Differentially expressed UPS genes (DEUPS) were screened from LIHC-TCGA datasets. The least absolute shrinkage and selection operator (LASSO) and stepwise multivariate regression analysis were conducted to establish a UPS-based prognostic risk model. The robustness of the risk model was further validated in HCCDB18, GSE14520, and GSE76427 cohorts. Subsequently, immune features, clinicopathologic characteristics, enrichment pathways, and anti-tumor drug sensitivity of the model were further evaluated. Moreover, a nomogram was established to improve the predictive ability of the risk model. Results: Seven UPS-based signatures (ATG10, FBXL7, IPP, MEX3A, SOCS2, TRIM54, and PSMD9) were developed for the prognostic risk model. Individuals with HCC with high-risk scores presented a more dismal prognosis than those with low-risk scores. Moreover, larger tumor size, advanced TNM stage, and tumor grade were observed in the high-risk group. Additionally, cell cycle, ubiquitin-mediated proteolysis, and DNA repair pathways were intimately linked to the risk score. In addition, obvious immune cell infiltration and sensitive drug response were identified in low-risk patients. Furthermore, both nomogram and risk score showed a significant prognosis-predictive ability. Conclusion: Overall, we established a novel UPS-based prognostic risk model in HCC. Our results will facilitate a deep understanding of the functional role of UPS-based signature in HCC and provide a reliable prediction of clinical outcomes and anti-tumor drug responses for patients with HCC.
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PURPOSE: Hepatocellular carcinoma (HCC) has high morbidity and poor prognosis due to the propensity of recurrence and metastasis. Emerging studies have confirmed that proline-rich coiled-coil2A (PRRC2A) plays a crucial role in tumorigenesis and immunoregulation. However, its expression status and biological functions in HCC remain poorly documented. METHODS: The presence and prognostic value of PRRC2A were determined by a tissue microarray (TMA) cohort and multiple databases, mainly from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Clinical Proteomic Tumor Analysis Consortium (CPTAC). Functional enrichment analysis was applied to identify the mechanisms of PRRC2A in HCC. The biological function of PRRC2A in HCC progression in vitro was determined by CCK-8, colony formation, EdU, transwell migration and invasion assays. Moreover, the Estimation of STromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE), single-sample gene set enrichment analysis (ssGSEA), tumor immune dysfunction and exclusion (TIDE) algorithms, immunophenoscore (IPS) and public available immunotherapy cohorts were performed to classify their associations with tumor-infiltrating immune cells and immunotherapy. RESULTS: PRRC2A was upregulated in HCC at both mRNA and protein levels. High PRRC2A expression was correlated with poor prognosis and could be an independent risk factor. Functional enrichment analysis demonstrated that elevated PRRC2A was significantly correlated with the activation of various oncogenic pathways. Additionally, in vitro experiments confirmed that silencing PRRC2A could suppress the proliferation and metastasis capacities of HCC cells. More importantly, PRRC2A was negatively associated with many anti-tumor immune cells, but positively related to the expression of markers of exhaustive T cells. And HCC patients with high PRRC2A were more likely to be nonresponsive to immunotherapy. CONCLUSION: This study explored the predictive value and biological roles of PRRC2A in HCC progression and indicated that it might be a potential biomarker for HCC patients and a predictor for immunotherapy.
