LncRNA ZEB1-AS1 regulates hepatocellular carcinoma progression by targeting miR-23c

Epigenetic regulation of hepatocellular carcinoma progression: MicroRNAs as therapeutic, diagnostic and prognostic factors

Hepatocellular carcinoma (HCC), a significant challenge for public healthcare systems in developed Western countries including the USA, Canada, and the UK, is influenced by different risk factors including hepatitis virus infections, alcoholism, and smoking. The disruption in the balance of microRNAs (miRNAs) plays a vital function in tumorigenesis, given their function as regulators in numerous signaling networks. These miRNAs, which are mature and active in the cytoplasm, work by reducing the expression of target genes through their impact on mRNAs. MiRNAs are particularly significant in HCC as they regulate key aspects of the tumor, like proliferation and invasion. Additionally, during treatment phases such as chemotherapy and radiotherapy, the levels of miRNAs are key determinants. Pre-clinical experiments have demonstrated that altered miRNA expression contributes to HCC development, metastasis, drug resistance, and radio-resistance, highlighting related molecular pathways and processes like MMPs, EMT, apoptosis, and autophagy. Furthermore, the regulatory role of miRNAs in HCC extends beyond their immediate function, as they are also influenced by other epigenetic factors like lncRNAs and circular RNAs (circRNAs), as discussed in recent reviews. Applying these discoveries in predicting the prognosis of HCC could mark a significant advancement in the therapy of this disease.

Long noncoding RNA ZEB1-AS1 attenuates ferroptosis of gastric cancer cells through modulating miR-429/BGN axis

Gastric cancer (GC) is the fifth utmost common malignant cancer type globally, in which ferroptosis acts a critical function in the progress of GC. Long noncoding RNA ZEB1-AS1 has been recognized in numerous cancers, but the role of ZEB1-AS1 in ferroptosis remains obscure. Hence, we investigated the efficacy of ZEB1-AS1 on ferroptosis of GC cells. The cell growth and viability were analyzed via cell counting kit assay and xenograft tumor model in vivo and in vitro, respectively. The RNA and protein expression were measured by qRT-PCR and western blot analysis assay, respectively. The levels of Fe2+ , malondialdehyde (MDA), and lipid reactive oxygen species (ROS) were tested to determine ferroptosis. The erastin and RSL3 were used to induce ferroptosis. The mechanism was analyzed via luciferase reporter gene and RIP assays. The treatment of ferroptosis inducer Erastin and RSL3 suppressed the viability of GC cells and the ZEB1-AS1 overexpression rescued the phenotype in the cells. The levels of Fe2+ , MDA, and ROS were enhanced through the depletion of ZEB1-AS1 in Erastin/RSL3 treated GC cells. ZEB1-AS1 directly sponged miR-429 in GC cells and miR-429 targeted BGN in GC cells, and the inhibition of miR-429 rescued ZEB1-AS1 depletion-inhibited BGN expression. We validated that miR-429 induced and BGN-repressed ferroptosis in cancer cells. The BGN overexpression and miR-429 suppression could reverse the efficacy of ZEB1-AS1 on proliferation and ferroptosis in cancer cells. The expression of ZEB1-AS1 and BGN was enhanced and miR-429 expression was decreased in clinical GC tissues. ZEB1-AS1 attenuated ferroptosis of cancer cells by modulating miR-429/BGN axis.

The integration of machine learning and multi-omics analysis provides a powerful approach to screen aging-related genes and predict prognosis and immunotherapy efficacy in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a highly malignant tumor with high incidence and mortality rates. Aging-related genes are closely related to the occurrence and development of cancer. Therefore, it is of great significance to evaluate the prognosis of HCC patients by constructing a model based on aging-related genes.

METHOD

Non-negative matrix factorization (NMF) clustering analysis was used to cluster the samples. The correlation between the risk score and immune cells, immune checkpoints, and Mismatch Repair (MMR) was evaluated through Spearman correlation test. Real Time Quantitative PCR (RT-qPCR) and immunohistochemistry were used to validate the expression levels of key genes in tissue and cells for the constructed model.

RESULT

By performing NMF clustering, we were able to effectively group the liver cancer samples into two distinct clusters. Considering the potential correlation between aging-related genes and the prognosis of liver cancer patients, we used aging-related genes to construct a prognostic model. Spearman correlation analysis showed that the model risk score was closely related to MMR and immune checkpoint expression. Drug sensitivity analysis also provided guidance for the clinical use of chemotherapy drugs. RT-qPCR showed that TFDP1, NDRG1, and FXR1 were expressed at higher levels in different liver cancer cell lines compared to normal liver cells.

CONCLUSION

In summary, we have developed an aging-related model to predict the prognosis of hepatocellular carcinoma and guide clinical drug treatment for different patients.

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.

A review on the role of ZEB1-AS1 in human disorders

ZEB1 Antisense RNA 1 (ZEB1-AS1) is a type of RNA characterized as long non-coding RNA (lncRNA). This lncRNA has important regulatory roles on its related gene, Zinc Finger E-Box Binding Homeobox 1 (ZEB1). In addition, role of ZEB1-AS1 has been approved in diverse malignancies such as colorectal cancer, breast cancer, glioma, hepatocellular carcinoma and gastric cancer. ZEB1-AS1 serves as a sponge for a number of microRNAs, namely miR-577, miR-335-5p, miR-101, miR-505-3p, miR-455-3p, miR-205, miR-23a, miR-365a-3p, miR-302b, miR-299-3p, miR-133a-3p, miR-200a, miR-200c, miR-342-3p, miR-214, miR-149-3p and miR-1224-5p. In addition to malignant conditions, ZEB1-AS1 has functional role in non-malignant conditions like diabetic nephropathy, diabetic lung, arthrosclerosis, Chlamydia trachomatis infection, pulmonary fibrosis and ischemic stroke. This review outlines different molecular mechanisms of ZEB1-AS1 in a variety of disorders and highlights its importance in their pathogenesis.

Investigating microRNA Profiles in Prostate Cancer Bone Metastases and Functional Effects of microRNA-23c and microRNA-4328

MicroRNAs (miRNAs) are aberrantly expressed in prostate cancer (PC), but comprehensive knowledge about their levels and function in metastatic PC is lacking. Here, we explored the differential expression of miRNA profiles during PC progression to bone metastasis, and further focused on the downregulation of miRNA-23c and -4328 and their impact on PC growth in experimental models. Using microarray screening, the levels of 1510 miRNAs were compared between bone metastases (n = 14), localized PC (n = 7) and benign prostate tissue (n = 7). Differentially expressed miRNAs (n = 4 increased and n = 75 decreased, p < 0.05) were identified, of which miRNA-1, -23c, -143-3p, -143-5p, -145-3p, -205-5p, -221-3p, -222-3p and -4328 showed consistent downregulation during disease progression (benign > localized PC > bone metastases). The downregulation of miRNA-23c and -4328 was confirmed by reverse transcription and quantitative polymerase chain reaction analysis of 67 metastasis, 12 localized PC and 12 benign prostate tissue samples. The stable overexpression of miRNA-23c and -4328 in the 22Rv1 and PC-3 cell lines resulted in reduced PC cell growth in vitro, and in the secretion of high levels of miRNA-23c (but not -4328) in extracellular vesicles. However, no tumor suppressive effects were observed from miRNA-23c overexpression in PC-3 cells subcutaneously grown in mice. In conclusion, bone metastases display a profound reduction of miRNA levels compared to localized PC and benign disease. The downregulation of those miRNAs, including miRNA-23c and -4328, may lead to a loss of tumor suppressive effects and provide biomarker and therapeutic possibilities that deserve to be further explored.

Identification of cuproptosis-related long non-coding ribonucleic acid signature as a novel prognosis model for colon cancer

Cuproptosis is a novel type of cell death that may play a vital role in preventing various types of cancer. Studies examining cuproptosis are limited, and the cuproptosis-related lncRNAs (long non-Coding ribonucleic acids) involved in the regulation of colon cancer remain unclear. This study aimed to identify the prognostic signature of cupronosis-related lncRNAs and explore their potential molecular functions in colon cancer. Data on the clinical correlation were obtained from The Cancer Genome Atlas (TCGA) database. The differentially expressed cuproptosis-related long non-coding ribonucleic acids (lncRNAs) were analyzed using the "limma" package. Then, the prognostic cuproptosis-related lncRNA signature (CupRLSig) was identified through univariate Cox and co-expression analyses, and a prognostic model was constructed based on CupRLSig using the least absolute shrinkage selection operator (LASSO) algorithm and Cox regression analysis. The Kaplan-Meier survival curve and receiver operating characteristic (ROC) curve were used for evaluating the model's capacity for prognosis prediction. In addition, the immune landscape, and drug sensitivity of CupRLSig were analyzed. Finally, the functions of AL512306.3 and ZEB1-AS1 were verified through in vitro experiments. The high- or low-risk groups were classified according to the risk score. The signature-based risk score showed a stronger ability to predict patient's survival compared with the traditional clinicopathological features. In addition, immune responses, such as inflammation-promoting response and T-cell co-inhibition, were significantly different between the two groups. Moreover, chemotherapy drugs or inhibitors, such as axitinib, cisplatin, doxorubicin, and elesclomol, may be considered as potential therapeutic drugs for patients in high-risk groups. Finally, inhibition of AL512306.3 and ZEB1-AS1 significantly suppressed the cell proliferation in colon cancer cells. These results provide novel insights into the pathogenesis of colon cancer and offer promising biomarkers with the potential to guide research on carcinogenesis and cancer treatment.

[Long noncoding RNA ZEB1-AS1 aggravates cerebral ischemia/reperfusion injury in rats through the HMGB1/TLR-4 signaling axis]

OBJECTIVE

To investigate the role of long non-coding RNA ZEB1-AS1 in cerebral ischemia/reperfusion injury (CI/RI).

METHODS

We detected the temporal changes of ZEB1-AS1 and HMGB1 expression using qPCR and Western blotting in SD rats following CI/RI induced by middle cerebral artery occlusion (MCAO). The rat models of CI/RI were subjected to injections of vectors for ZEB1-AS1 overexpression or knockdown into the lateral ventricle, and the changes in cognitive function, brain water content, blood-brain barrier integrity, and IL-1β and TNF-α levels in the cerebrospinal fluid (CSF) and serum were observed. Neuronal loss and cell apoptosis in the cortex of the rat models were detected by FJC and TUNEL methods, and HMGB1 and TLR-4 expressions were analyzed with Western blotting. We also examined the effects of ZEB1-AS1 knockdown on apoptosis and expressions of HMGB1 and TLR-4 in SH-SY5Y cells with oxygen-glucose deprivation/reoxygenation (OGD/R).

RESULTS

In CI/RI rats, the expressions of ZEB1-AS1 and HMGB1 in the brain tissue increased progressively with the extension of reperfusion time, reaching the peak levels at 24 h followed by a gradual decline. ZEB1-AS1 overexpression significantly aggravated icognitive impairment and increased brain water content, albumin content in the CSF, and IL-1β and TNF-α levels in the CSF and serum in CI/RI rats (P < 0.05), while ZEB1-AS1 knockdown produced the opposite effects (P < 0.05 or 0.01). ZEB1-AS1 overexpression obviously increased the number of FJC-positive neurons in the cortex and enhanced the expressions of HMGB1 and TLR-4 in the rat models (P < 0.01); ZEB1-AS1 knockdown significantly reduced the number of FJC-positive neurons and lowered HMGB1 and TLR-4 expressions (P < 0.01). In SH-SY5Y cells with OGD/R, ZEB1-AS1 knockdown significantly suppressed cell apoptosis and lowered the expressions of HMGB1 and TLR-4 (P < 0.01).

CONCLUSION

ZEB1-AS1 overexpression aggravates CI/RI in rats through the HMGB1/TLR-4 signaling axis.

A pyroptosis-related gene signature predicts prognosis and immune microenvironment in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a highly malignant tumor with a very poor prognosis. Pyroptosis is an inflammatory form of cell death and plays an important role in cancer development. The prognostic value of pyroptosis-related genes (PRGs) in HCC has not been studied extensively.

METHODS

Unsupervised consensus clustering analysis was performed to identify two subtypes based on the expression profiles of prognostic PRGs in the The Cancer Genome Atlas (TCGA) database, and the differences between the two subtypes were compared. A prognostic model based on four PRGs was established by further least absolute shrinkage and selection operator (LASSO) Cox regression analysis and multivariate Cox regression analysis.

RESULTS

Two subtypes (clusters 1 and 2) were identified by consensus clustering based on prognostic PRGs in HCC. Survival outcomes, biological function, genomic alterations, immune cell infiltration, and immune checkpoint genes were compared between the subtypes. Cluster 2 had a worse survival outcome than cluster 1. Cluster 2 was enriched for hallmarks of cancer progression, TP53 mutation, tumor-promoting immune cells, and immune checkpoint genes, which may contribute to the poor prognosis. A prognostic risk signature that predicted the overall survival (OS) of patients was constructed and validated. Consequently, a risk score was calculated for each patient. Combined with the clinical characteristics, the risk score was found to be an independent prognostic factor for survival of HCC patients. Further analysis revealed that the risk score was closely associated with the levels of immune cell infiltration and the expression profiles of immune checkpoint genes.

CONCLUSIONS

Collectively, our study established a prognostic risk signature for HCC and revealed a significant correlation between pyroptosis and the HCC immune microenvironment.

Integrated analysis of ceRNA network reveals potential prognostic Hint1-related lncRNAs involved in hepatocellular carcinoma progression

Background

Hint1 is a novel tumor suppressor gene, and inactivation of its expression is closely associated with the carcinogenesis of a variety of malignancies. The effects of Hint1 deficiency on the competing endogenous RNA (ceRNA) regulatory network in the context of HCC remains to be fully characterized. This study aims to explore Hint1-related hub lncRNAs in HCC and to establish a reliable prognostic model for HCC patients based on these hub lncRNAs.

Methods

lncRNA + mRNA microarray was used to identify differentially expressed (DE) lncRNAs and mRNAs in Huh7 cells before and after Hint1 knockdown. A Hint1-related ceRNA network was mapped by bioinformation technology. The DEmRNAs in the network were analyzed via GO and KEGG enrichment analyses. Hub DElncRNAs associated with HCC patient prognosis were then detected through univariate and multivariate Cox regression analyses and were incorporated into a prognostic model. The prognostic value of this model was then assessed through the use of Kaplan-Meier curves, time-related ROC analyses, and nomograms. We also utilized Kaplan-Meier curves to validate the relationship between hub lncRNAs and the overall survival (OS) of HCC patients. Finally, A Hint1-related core ceRNA network based on the hub DElncRNAs and DEmRNAs was mapped.

Results

We identified 417 differentially expressed DElncRNAs and 2096 DEmRNAs in Huh7 cells before and after Hint1 knockdown. Three hub DElncRNAs (LINC00324, SNHG3, and DIO3OS) in the Hint1-associated ceRNA network were screened out using univariate and multivariate Cox regression analyses. A hepatocellular carcinoma (HCC) prognostic risk-scoring model and nomogram were constructed using these three hub lncRNAs, and it was confirmed that the risk score of the model could be used as an independent predictor of HCC prognosis. A Hint1-related core ceRNA network based on the hub DElncRNAs and DEmRNAs was also mapped.

Conclusion

We constructed a reliable prognostic model for HCC patients based on three Hint1-related hub lncRNAs, and we believe these three hub lncRNAs may play critical roles in hepatocarcinogenesis, and progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02535-z.

Development and Validation of a Prognostic Signature Associated With Tumor Microenvironment Based on Autophagy-Related lncRNA Analysis in Hepatocellular Carcinoma

Objective: The present study aimed to establish a prognostic signature based on the autophagy-related long non-coding RNAs (lncRNAs) analysis in patients with hepatocellular carcinoma (HCC).

Methods: Patients with HCC from The Cancer Genome Atlas (TCGA) were taken as the training cohort, and patients from the International Cancer Genome Consortium (ICGC) were treated as the validation cohort. Autophagy-related lncRNAs were obtained via a co-expression network analysis. According to univariate and multivariate analyses, a multigene prognostic signature was constructed in the training cohort. The predictive power of the signature was confirmed in both cohorts. The detailed functions were investigated using functional analysis. The single-sample gene set enrichment analysis (ssGSEA) score was used to evaluate the tumor microenvironment. The expression levels of immunotherapy and targeted therapy targets between the two risk groups were compared. Finally, a nomogram was constructed by integrating clinicopathological parameters with independently predictive value and the risk score.

Results: Four autophagy-related lncRNAs were identified to establish a prognostic signature, which separated patients into high- and low-risk groups. Survival analysis showed that patients in the high-risk group had a shorter survival time in both cohorts. A time-independent receiver-operating characteristic (ROC) curve and principal component analysis (PCA) confirmed that the prognostic signature had a robust predictive power and reliability in both cohorts. Functional analysis indicated that the expressed genes in the high-risk group are mainly enriched in autophagy- and cancer-related pathways. ssGSEA revealed that the different risk groups were associated with the tumor microenvironment. Moreover, the different risk groups had positive correlations with the expressions of specific mutant genes. Multivariate analysis showed that the risk score also exhibited excellent predictive power irrespective of clinicopathological characteristics in both cohorts. A nomogram was established. The nomogram showed good discrimination, with Harrell's concordance index (C-index) of 0.739 and good calibration.

Conclusion: The four autophagy-related lncRNAs could be used as biological biomarkers and therapeutic targets. The prognostic signature and nomogram might aid clinicians in individual treatment optimization and clinical decision-making for patients with HCC.

FoXA2 promotes esophageal squamous cell carcinoma progression by ZEB2 activation

Background

It has been reported that Forkhead transcription family member (FOXA2) regulates esophageal squamous cell carcinoma (ESCC) progression. However, the specific mechanism, by which FOXA2 promotes ESCC malignant progression, remains unclear.

Materials and methods

QRT-PCR and western blotting were applied to measure FOXA2 expression in ESCC tissues, while CCK-8 assay and Transwell assays were used to investigate the effect of FOXA2 on ESCC. Luciferase reporter assay, followed by fast chromatin immunoprecipitation (ChIP) assay, was used to study the relationship between FOXA2 and ZEB2.

Results

FOXA2 was significantly increased in ESCC tissues, when compared to normal tissues. Moreover, high expression of FOXA2 was also found in ESCC cells. Knockdown of FOXA2 inhibited ESCC cell proliferation, invasion, and migration. Mechanically, FOXA2 was verified to regulate ZEB2 expression at transcription level. Moreover, ZEB2 reversed the inhibitory effect of FOXA2 on ESCC proliferation, invasion, and migration. The relationship between ZEB2 and FOXA2 in ESCC tissues was negative.

Conclusions

These results indicate that FOXA2 plays a critical role in ESCC progression and may become a potential candidate target for ESCC treatment.