CircASPH Promotes Hepatocellular Carcinoma Progression Through Methylation and Expression of HAO2

Inhibition of circular RNA ASPH reduces the proliferation and promotes the apoptosis of hepatic stellate cells in hepatic fibrosis

Circular RNAs (circRNAs) are a newly identified form of non-coding RNA that play a crucial role in various pathological processes. However, the expression profile and function of circRNAs in hepatic fibrosis (HF) remain largely unknown. In this study, we showed that a novel circRNA ASPH (circASPH) mediates HF by targeting the miR-139-5p/Notch1 axis. We investigated the expression profile of circRNAs in hepatocyte exosomes of mice with HF using circRNA-sequencing and found significant upregulation of circASPH. Loss- and gain-of-function analysis of circASPH was performed to assess its role in HF. Furthermore, we performed luciferase reporter assay, RNA pull-down, and fluorescence in situ hybridization analyses and confirmed that circASPH directly binds to miR-139-5p. We also found that circASPH was upregulated in liver fibrogenesis. Downregulation of circASPH expression inhibited hepatic stellate cell (HSC) activation and proliferation, induced apoptosis, and attenuated mouse liver fibrogenic injury. Mechanistically, circASPH directly targeted miR-139-5p to regulate the expression of Notch1 in HF. Thus, downregulation of circASPH may suppress the activation of HSCs and HF through the circASPH/miR-139-5p/Notch1 axis. Our findings indicated that circASPH may be a potential biomarker for HF diagnosis and therapy.

BmNPV circular RNA-encoded peptide VSP39 promotes viral replication

CircRNAs are covalently closed single-stranded circular RNA molecules, which are not easily degraded by endonucleases and play vital roles in many biological processes. Currently, most studies on circRNAs focus on endogenous circRNAs in cells, and there are few studies on virus-encoded circRNAs. In this study, a viral circRNA (circRNA-000010) derived from the region (-/bp: 114514-115,319) of the complementary strand of Bombyx mori Nucleopolyhedrovirus (BmNPV) genome was identified with the circRNA-sequencing. The authenticity of viral circRNA-000010 was further confirmed by reverse transcription PCR, reverse transcription-rolling circle amplification (TCA), in situ hybridization, immunofluorescent staining, and Northern blotting. The results of overexpression and knockdown experiments showed that circRNA-000010 promoted viral replication. Furthermore, a viral small peptide VSP39 with 39 amino acid residues translated by circRNA-000010 but not its linear molecule was confirmed. Finally, VSP39 was found to promote viral replication. Our findings indicated that a viral circRNA encoded by BmNPV promoted viral replication. These findings will provide new clues for further understanding coding information of the BmNPV genome and open a new insight for investigating host-virus interactions.

Analysis on heterogeneity of hepatocellular carcinoma immune cells and a molecular risk model by integration of scRNA-seq and bulk RNA-seq

Background

Studies have shown that hepatocellular carcinoma (HCC) heterogeneity is a main cause leading to failure of treatment. Technology of single-cell sequencing (scRNA) could more accurately reveal the essential characteristics of tumor genetics.

Methods

From the Gene Expression Omnibus (GEO) database, HCC scRNA-seq data were extracted. The FindCluster function was applied to analyze cell clusters. Autophagy-related genes were acquired from the MSigDB database. The ConsensusClusterPlus package was used to identify molecular subtypes. A prognostic risk model was built with the Least Absolute Shrinkage and Selection Operator (LASSO)–Cox algorithm. A nomogram including a prognostic risk model and multiple clinicopathological factors was constructed.

Results

Eleven cell clusters labeled as various cell types by immune cell markers were obtained from the combined scRNA-seq GSE149614 dataset. ssGSEA revealed that autophagy-related pathways were more enriched in malignant tumors. Two autophagy-related clusters (C1 and C2) were identified, in which C1 predicted a better survival, enhanced immune infiltration, and a higher immunotherapy response. LASSO–Cox regression established an eight-gene signature. Next, the HCCDB18, GSA14520, and GSE76427 datasets confirmed a strong risk prediction ability of the signature. Moreover, the low-risk group had enhanced immune infiltration and higher immunotherapy response. A nomogram which consisted of RiskScore and clinical features had better prediction ability.

Conclusion

To precisely assess the prognostic risk, an eight-gene prognostic stratification signature was developed based on the heterogeneity of HCC immune cells.