ST8SIA6-AS1 promotes the development of hepatocellular carcinoma cells through miR-338-3p/NONO Axis

Making Sense of Antisense lncRNAs in Hepatocellular Carcinoma

Transcriptome complexity is emerging as an unprecedented and fascinating domain, especially by high-throughput sequencing technologies that have unveiled a plethora of new non-coding RNA biotypes. This review covers antisense long non-coding RNAs, i.e., lncRNAs transcribed from the opposite strand of other known genes, and their role in hepatocellular carcinoma (HCC). Several sense-antisense transcript pairs have been recently annotated, especially from mammalian genomes, and an understanding of their evolutionary sense and functional role for human health and diseases is only beginning. Antisense lncRNAs dysregulation is significantly involved in hepatocarcinogenesis, where they can act as oncogenes or oncosuppressors, thus playing a key role in tumor onset, progression, and chemoradiotherapy response, as deduced from many studies discussed here. Mechanistically, antisense lncRNAs regulate gene expression by exploiting various molecular mechanisms shared with other ncRNA molecules, and exploit special mechanisms on their corresponding sense gene due to sequence complementarity, thus exerting epigenetic, transcriptional, post-transcriptional, and translational controls. The next challenges will be piecing together the complex RNA regulatory networks driven by antisense lncRNAs and, ultimately, assigning them a function in physiological and pathological contexts, in addition to defining prospective novel therapeutic targets and innovative diagnostic tools.

Integrated analysis of multiple transcriptomic data identifies ST8SIA6‑AS1 and LINC01093 as potential biomarkers in HBV‑associated liver cancer

The mechanisms of long-non-coding RNAs (lncRNAs) in hepatitis B virus (HBV) infection-associated liver cancer remain largely unclear. Therefore, the aim of the present study was to investigate the regulatory mechanisms of lncRNAs in this disease. HBV-liver cancer related transcriptome expression profile data (GSE121248 and GSE55092) from the Gene Expression Omnibus database and survival prognosis information from The Cancer Genome Atlas (TCGA) database were obtained for analysis. The limma package was used to identify the overlapped differentially expressed RNAs (DERs), including DElncRNAs and DEmRNAs, in the GSE121248 and GSE55092 datasets. The screened optimized lncRNA signatures were used to develop a nomogram model based on the GSE121248 dataset, which was validated using the GSE55092 and TCGA datasets. A competitive endogenous RNA (ceRNA) network was constructed based on the screened prognosis-associated lncRNA signatures from TCGA dataset. In addition, the levels of specific lncRNAs were evaluated in HBV-infected human liver cancer tissues and cells, and Cell Counting Kit-8, ELISA and Transwell assays were performed to evaluate the effects of the lncRNAs in HBV-expressing liver cancer cells. A total of 535 overlapped DERs, including 30 DElncRNAs and 505 DEmRNAs, were identified in the GSE121248 and GSE55092 datasets. An optimized DElncRNA signature comprising 10 lncRNAs was used to establish a nomogram. ST8SIA6-AS1 and LINC01093 were identified as lncRNAs associated with HBV-liver cancer prognosis in TCGA dataset, and were applied to construct a ceRNA network. Reverse transcription-quantitative PCR analysis showed that ST8SIA6-AS1 was upregulated and LINC01093 was downregulated in HBV-infected human liver cancer tissues and HBV-expressing liver cancer cells compared with non-HBV-infected controls. ST8SIA6-AS1 knockdown and LINC01093 overexpression independently reduced the number of copies of HBV DNA, the levels of hepatitis B surface antigen and hepatitis B e antigen, as well as cell proliferation, migration and invasion. In summary, the present study identified ST8SIA6-AS1 and LINC01093 as two potential biomarkers that may be effective therapeutic targets for HBV-associated liver cancer.

The Mutual Relationship between Glycosylation and Non-Coding RNAs in Cancer and Other Physio-Pathological Conditions

Glycosylation, which consists of the enzymatic addition of sugars to proteins and lipids, is one of the most important post-co-synthetic modifications of these molecules, profoundly affecting their activity. Although the presence of carbohydrate chains is crucial for fine-tuning the interactions between cells and molecules, glycosylation is an intrinsically stochastic process regulated by the relative abundance of biosynthetic (glycosyltransferases) and catabolic (glycosidases) enzymes, as well as sugar carriers and other molecules. Non-coding RNAs, which include microRNAs, long non-coding RNAs and circRNAs, establish a complex network of reciprocally interacting molecules whose final goal is the regulation of mRNA expression. Likewise, these interactions are stochastically regulated by ncRNA abundance. Thus, while protein sequence is deterministically dictated by the DNA/RNA/protein axis, protein abundance and activity are regulated by two stochastic processes acting, respectively, before and after the biosynthesis of the protein axis. Consequently, the worlds of glycosylation and ncRNA are closely interconnected and mutually interacting. In this paper, we will extensively review the many faces of the ncRNA-glycosylation interplay in cancer and other physio-pathological conditions.

LncRNA ST8SIA6-AS1 facilitates hepatocellular carcinoma progression by governing miR-651-5p/TM4SF4 axis

The oncogenic role of ST8SIA6-AS1 in different cancers was reported, including hepatocellular carcinoma (HCC). However, the underlying mechanism has not been completely explored. Real time quantitative PCR analysis was conducted to assess the ST8SIA6-AS1, miR-651-5p and TM4SF4 expression in HCC tissues and cells. Cell counting kit-8 and wound-healing migration assays were adopted to evaluate the HCC cell proliferation and migration, respectively. The expression of apoptosis-related proteins (Bax and Bcl-2) in human colorectal cancer cells (HCC) was determined by western blotting. In addition to bioinformatics analysis, RNA immunoprecipitation studies and luciferase reporter assays were undertaken to investigate the direct target relationship among ST8SIA6-AS1 and miR-651-5p or TM4SF4. Highly expressed ST8SIA6-AS1 and TM4SF4 as well as poorly expressed miR-651-5p were detected in HCC tissues and cells. Clinically, miR-651-5p expression in HCC tissues is negatively correlated with ST8SIA6-AS1 or TM4SF4. Cell functional assays demonstrated that ST8SIA6-AS1 silencing resulted in weakened proliferative and migratory capacities in HCC cells in addition to increase Bax expression and reduced Bcl-2 expression. ST8SIA6-AS1 exhibited its oncogenic function by sponging tumor suppressor miR-651-5p, and the anti-oncogenic of miR-651-5p was offset by its TM4SF4. The manipulation of ST8SIA6-AS1/miR-651-5p/TM4SF4 axis-mediated oncogenicity in HCC might shed new light on HCC diagnosis and therapy.

High Expression of RRM1 Mediated by ncRNAs Correlates with Poor Prognosis and Tumor Immune Infiltration of Hepatocellular Carcinoma

Introduction

Hepatocellular carcinoma (HCC) is one of several tumors with poor prognosis and causes a significant social burden. A growing number of studies have shown that RRM1 plays a crucial role in the development and progression of multiple human cancers. However, the specific role and mechanism of RRM1 have not been fully defined in HCC.

Methods

TCGA and GTEx data were used for the first time to conduct a pan-cancer analysis of RRM1 expression and prognosis, and identified RRM1 as a possible potential oncogene in HCC. At the same time, a combination of analyses (including expression analysis, correlation analysis or survival analysis) identified non-coding RNAs (ncRNAs) that contribute to RRM1 overexpression.

Results

MIR4435-2HG/miR-22-3p and SNHG6/miR-101-3p were identified as the most promising RRM1 upstream ncRNA-related pathways in HCC. In addition, RRM1 levels were significantly and positively correlated with tumor immune cell infiltration, immune cell biomarker or immune checkpoint expression.

Conclusion

These results suggest that high expression of RRM1 mediated by ncRNAs is associated with poor prognosis and tumor immune infiltration in HCC.