The Systematic Analyses of RING Finger Gene Signature for Predicting the Prognosis of Patients with Hepatocellular Carcinoma

Abstract

RING finger (RNF) proteins are frequently dysregulated in human malignancies and are tightly associated with tumorigenesis. However, the expression profiles of RNF genes in hepatocellular carcinoma (HCC) and their relations with prognosis remain undetermined. Here, we aimed at constructing a prognostic model according to RNF genes for forecasting the outcomes of HCC patients using the data from The Cancer Genome Atlas (TCGA) program. We collected HCC datasets to validate the values of our model in predicting prognosis of HCC patients from International Cancer Genome Consortium (ICGC) platform. Then, functional experiments were carried out to explore the roles of the representative RNF in HCC progression. A total of 107 differentially expressed RNFs were obtained between TCGA-HCC tumor and normal tissues. After comprehensive evaluation, a prognostic signature composed of 11 RNFs (RNF220, RNF25, TRIM25, BMI1, RNF216P1, RNF115, RNF2, TRAIP, RNF157, RNF145, and RNF19B) was constructed based on TCGA cohort. Then, the Kaplan-Meier (KM) curves and the receiver operating characteristic curve (ROC) were employed to evaluate predictive power of the prognostic model in testing cohort (TCGA) and validation cohort (ICGC). The KM and ROC curves illustrated the good predictive power in testing and validation cohort. The areas under the ROC curve are 0.77 and 0.76 in these two cohorts, respectively. Among the prognostic signature genes, BMI1 was selected as a representative for functional study. We found that BMI1 protein level was significantly upregulated in HCC tissues. Moreover, the inhibitor of BMI1, PTC-209, displayed an excellent anti-HCC effect in vitro. Enrichment analysis of BMI1 downstream targets showed that BMI1 might be involved in tumor immunotherapy. Together, our overall analyses revealed that the 11-RNFs prognostic signature might provide us latent chances for evaluating HCC prognosis and developing novel HCC therapy.

Identification of N7-methylguanosine-related lncRNAs for the risk stratification of hepatocellular carcinoma

“…MKLN1-AS affects HCC progression by regulating microRNAs ( 62 ). Several studies have also reported that AL031985.3, TMCC1-AS1, LINC01224, SNHG10, RNF216P1, and AC025176.1 are potential prognostic predictors in HCC ( 63 - 69 ). AL031985.3, an immune- and autophagy-related lncRNA, was shown to be a predictor for HCC prognosis ( 63 , 64 ).…”

As a matter of fat: Emerging roles of lipid‐sensitive E3 ubiquitin ligases

“…Single nucleotide polymorphisms within RNF145's coding region in humans are associated with obesity and dyslipidemia while its differential expression in hepatocellular carcinoma affects disease progression. [74][75][76][77] RNF145's lipid-modulating effects are intimately linked to its ability to target lipid metabolic enzymes for degradation. [74,[78][79][80][81] Accordingly, RNF145's substrates include the ER-resident lipid hydrolase adiponectin receptor 2 (ADIPOR2) and the cholesterol biosynthetic enzyme HMGCR.…”

“…Single nucleotide polymorphisms within RNF145's coding region in humans are associated with obesity and dyslipidemia while its differential expression in hepatocellular carcinoma affects disease progression. [ 74–77 ]…”

A Statistical Approach to the Diagnosis and Prediction of HCC Using CK19 and Glypican 3 Biomarkers

“…The cost-efficiency of using biomarkers to screen patients at risk of developing HCC is a topic of debate [ 10 , 11 ]. Multiple biomarkers have been studied for their potential role in the surveillance and early detection of HCC, alongside new prognostic or therapeutic targets for HCC [ 12 , 13 ]. Among them, alpha-fetoprotein (AFP) is the most extensively studied, and guidelines recommend it be used with ultrasound to screen patients at risk for HCC [ 6 ].…”