LncRNA ZFAS1: Role in tumorigenesis and other diseases

An update on the molecular mechanisms of ZFAS1 as a prognostic, diagnostic, or therapeutic biomarker in cancers

Zinc finger antisense 1 (ZFAS1), a newly discovered long noncoding RNA, is expressed in various tissues and organs and has been introduced an oncogenic gene in human malignancies. In various cancers, ZFAS1 regulates apoptosis, cell proliferation, the cell cycle, migration, translation, rRNA processing, and spliceosomal snRNP assembly; targets signaling cascades; and interacts with transcription factors via binding to key proteins and miRNAs, with conflicting findings on its effect on these processes. ZFAS1 is elevated in different types of cancer, like colorectal, colon, osteosarcoma, and gastric cancer. Considering the ZFAS1 expression pattern, it also has the potential to be a diagnostic or prognostic marker in various cancers. The current review discusses the mode of action of ZFAS1 in various human cancers and its regulation function related to chemoresistance comprehensively, as well as the potential role of ZFAS1 as an effective and noninvasive cancer-specific biomarker in tumor diagnosis, prognosis, and treatment. We expected that the current review could fill the current scientific gaps in the ZFAS1-related cancer causative mechanisms and improve available biomarkers.

LncRNA ZFAS1 promotes invasion of medullary thyroid carcinoma by enhancing EPAS1 expression via miR-214-3p/UCHL1 axis

lncRNA ZFAS1 was identified to facilitate thyroid cancer, but its role in medullary thyroid carcinoma (MTC) remains unknown. This study aimed to unravel the potential function of this lncRNA in MTC by investigating the involvement of the lncRNA ZFAS1 in a ceRNA network that regulates MTC invasion. Proliferation, invasion, and migration of cells were evaluated using EdU staining and Transwell assays. Immunoprecipitation (IP) assays, dual-fluorescence reporter, and RNA IP assays were employed to examine the binding interaction among genes. Nude mice were used to explore the role of lncRNA ZFAS1 in MTC in vivo. ZFAS1 and EPAS1 were upregulated in MTC. Silencing ZFAS1 inhibited MTC cell proliferation and invasion under hypoxic conditions, which reduced EPAS1 protein levels. UCHL1 knockdown increased EPAS1 ubiquitination. ZFAS1 positively regulated UCHL1 expression by binding to miR-214-3p. Finally, silencing ZFAS1 significantly repressed tumor formation and metastasis in MTC. LncRNA ZFAS1 promotes invasion of MTC by upregulating EPAS1 expression via the miR-214-3p/UCHL1 axis.

Long non-coding RNAs in cardiac hypertrophy and heart failure: functions, mechanisms and clinical prospects

The surge in reports describing non-coding RNAs (ncRNAs) has focused attention on their possible biological roles and effects on development and disease. ncRNAs have been touted as previously uncharacterized regulators of gene expression and cellular processes, possibly working to fine-tune these functions. The sheer number of ncRNAs identified has outpaced the capacity to characterize each molecule thoroughly and to reliably establish its clinical relevance; it has, nonetheless, created excitement about their potential as molecular targets for novel therapeutic approaches to treat human disease. In this Review, we focus on one category of ncRNAs - long non-coding RNAs - and their expression, functions and molecular mechanisms in cardiac hypertrophy and heart failure. We further discuss the prospects for this specific class of ncRNAs as novel targets for the diagnosis and treatment of these conditions.

Comprehensive analyses of mitophagy-related genes and mitophagy-related lncRNAs for patients with ovarian cancer

BACKGROUND

Both mitophagy and long non-coding RNAs (lncRNAs) play crucial roles in ovarian cancer (OC). We sought to explore the characteristics of mitophagy-related gene (MRG) and mitophagy-related lncRNAs (MRL) to facilitate treatment and prognosis of OC.

METHODS

The processed data were extracted from public databases (TCGA, GTEx, GEO and GeneCards). The highly synergistic lncRNA modules and MRLs were identified using weighted gene co-expression network analysis. Using LASSO Cox regression analysis, the MRL-model was first established based on TCGA and then validated with four external GEO datasets. The independent prognostic value of the MRL-model was evaluated by Multivariate Cox regression analysis. Characteristics of functional pathways, somatic mutations, immunity features, and anti-tumor therapy related to the MRL-model were evaluated using abundant algorithms, such as GSEA, ssGSEA, GSVA, maftools, CIBERSORT, xCELL, MCPcounter, ESTIMATE, TIDE, pRRophetic and so on.

RESULTS

We found 52 differentially expressed MRGs and 22 prognostic MRGs in OC. Enrichment analysis revealed that MRGs were involved in mitophagy. Nine prognostic MRLs were identified and eight optimal MRLs combinations were screened to establish the MRL-model. The MRL-model stratified patients into high- and low-risk groups and remained a prognostic factor (P < 0.05) with independent value (P < 0.05) in TCGA and GEO. We observed that OC patients in the high-risk group also had the unfavorable survival in consideration of clinicopathological parameters. The Nomogram was plotted to make the prediction results more intuitive and readable. The two risk groups were enriched in discrepant functional pathways (such as Wnt signaling pathway) and immunity features. Besides, patients in the low-risk group may be more sensitive to immunotherapy (P = 0.01). Several chemotherapeutic drugs (Paclitaxel, Veliparib, Rucaparib, Axitinib, Linsitinib, Saracatinib, Motesanib, Ponatinib, Imatinib and so on) were found with variant sensitivity between the two risk groups. The established ceRNA network indicated the underlying mechanisms of MRLs.

CONCLUSIONS

Our study revealed the roles of MRLs and MRL-model in expression, prognosis, chemotherapy, immunotherapy, and molecular mechanism of OC. Our findings were able to stratify OC patients with high risk, unfavorable prognosis and variant treatment sensitivity, thus improving clinical outcomes for OC patients.

LncRNA-mediated cell autophagy: An emerging field in bone destruction in rheumatoid arthritis

In recent years, research on the mechanism of bone destruction in rheumatoid arthritis (RA) has remained in the initial stages, and the mechanism has not been fully elucidated to date. Recent studies have shown that long noncoding RNAs (lncRNAs) participate in RA bone destruction via autophagy, but the specific regulatory mechanism of lncRNA-mediated autophagy is unclear. Therefore, in this article, we review the mechanisms of lncRNA-mediated autophagy in fibroblast-like synoviocytes and chondrocytes in RA bone destruction. We explain that lncRNAs mediate autophagy and participate in many specific pathological processes of RA bone destruction by regulating signalling pathways and the expression of target genes. Specific lncRNAs can be used as markers for molecular diagnosis, mechanistic regulation, treatment and prognosis of RA.

Expression of pyroptosis-related genes are correlated with immune microenvironment and predict prognosis in ESCA

OBJECTIVES

Pyroptosis-related genes (PRGs) are abnormally expressed in a variety of gastrointestinal tumors, this study aimed to investigate the role of pyroptosis genes in assessing the prognosis of esophageal cancer (ESCA).

METHODS

Through consensus clustering, we identified two subtypes associated with PRGs. After Lasso regression and multivariate Cox regression analysis, a polygenic signature based on six prognostic PRGS was constructed. Afterwards, we combined the risk score with clinical predictors to construct and validate a PRGs-associated ESCA prognostic model.

RESULTS

Through analysis, we Successfully constructed and validated a PRGs-associated ESCA prognostic model that predicts ESCA survival and correlates with the tumor immune microenvironment.

CONCLUSION

Based on PRGs features, we established a new ESCA hierarchical model. This model has important clinical implications for ESCA patients, both in terms of assessing prognosis and in terms of targeted and immunotherapy.

Zinc Finger Proteins in the War on Gastric Cancer: Molecular Mechanism and Clinical Potential

According to the 2020 global cancer data released by the World Cancer Research Fund (WCRF) International, gastric cancer (GC) is the fifth most common cancer worldwide, with yearly increasing incidence and the second-highest fatality rate in malignancies. Despite the contemporary ambiguous molecular mechanisms in GC pathogenesis, numerous in-depth studies have demonstrated that zinc finger proteins (ZFPs) are essential for the development and progression of GC. ZFPs are a class of transcription factors with finger-like domains that bind to Zn²⁺ extensively and participate in gene replication, cell differentiation and tumor development. In this review, we briefly outline the roles, molecular mechanisms and the latest advances in ZFPs in GC, including eight principal aspects, such as cell proliferation, epithelial-mesenchymal transition (EMT), invasion and metastasis, inflammation and immune infiltration, apoptosis, cell cycle, DNA methylation, cancer stem cells (CSCs) and drug resistance. Intriguingly, the myeloid zinc finger 1 (MZF1) possesses reversely dual roles in GC by promoting tumor proliferation or impeding cancer progression via apoptosis. Therefore, a thorough understanding of the molecular mechanism of ZFPs on GC progression will pave the solid way for screening the potentially effective diagnostic indicators, prognostic biomarkers and therapeutic targets of GC.

Prognostic prediction of clear cell renal cell carcinoma based on lipid metabolism-related lncRNA risk coefficient model

Objective: In order to predict the prognosis in patients with clear cell renal cell carcinoma (ccRCC) so as to understand cancer lipid metabolism and sensitivity to immune-targeting drugs, model algorithms were used to establish a risk coefficient model of long non-coding RNAs (lncRNAs) associated with lipid metabolism. Methods: The transcriptome data were retrieved from TCGA, and lncRNAs associated with lipid metabolism were obtained through Pearson correlation and differential expression analyses. Differentially expressed lipid metabolism-related lncRNAs and lipid metabolism-related lncRNA pairs were obtained using the R language software. The minimum absolute shrinkage method and the selector operation regression method were used to construct the model and draw the receiver operator characteristic curve. High-risk patients were differentiated from low-risk patients through the cut-off value, and the correlation analyses of the high-risk subgroup and low-risk subgroup were performed. Results: This research discovered that 25 pairs of lncRNAs were associated with the lipid metabolism of ccRCC, and 12 of these pairs were utilized to build the model. In combination with clinical data, the areas under the 1-, 3- and 5-year survival curves of ccRCC patients were 0.809, 0.764 and 0.792, separately. The cut-off value was used to perform subgroup analysis. The results showed that high-risk patients had poor prognosis. The results of Cox multivariate regressive analyses revealed that age and risk score were independent prediction factors of ccRCC prognosis. In addition, immune cell infiltration, the levels of gene expression at immune checkpoints, and high-risk patients more susceptible to sunitinib-targeted treatment were assessed by the risk model. Conclusion: Our team identified new prognostic markers of ccRCC and established risk models that could assess the prognosis of ccRCC patients and help determine which type of patients were more susceptible to sunitinib. These discoveries are vital for the optimization of risk stratification and personalized management.

LncRNA weighted gene co-expression network analysis reveals novel biomarkers related to prostate cancer metastasis

BACKGROUND

Most prostate cancer patients die from metastasis and lack accurate efficacious biomarkers to monitor the disease behavior, optimize treatment and assess prognosis. Herein, we aimed to identify meaningful lncRNA biomarkers associated with prostate cancer metastatic progression.

METHODS

By repurposing microarray probes, 11,624 lncRNAs in prostate cancer were obtained from Gene Expression Omnibus  database (GSE46691, N = 545; GSE29079, N = 235; GSE94767, N = 130). Weighted gene co-expression network analysis was applied to determine the co-expression lncRNA network pertinent to metastasis. Hub lncRNAs were screened. RNA-seq and clinical data from the Cancer Genome Atlas prostate cancer (TCGA-PRAD) cohort (N = 531) were analyzed. Transwell assay and bioinformatic analysis were performed for mechanism research.

RESULTS

The high expression levels of nine hub lncRNAs (FTX, AC005261.1, NORAD, LINC01578, AC004542.2, ZFAS1, EBLN3P, THUMPD3-AS1, GAS5) were significantly associated with Gleason score and increased probability of metastatic progression. Among these lncRNAs, ZFAS1 had the consistent trends of expression in all of the analysis from different cohorts, and the Kaplan-Meier survival analyses showed higher expression of ZFAS1 was associated with shorter relapse free survival. In-vitro studies confirmed that downregulation of ZFAS1 decreased prostate cancer cell migration.

CONCLUSION

We offered some new insights into discovering lncRNA markers correlated with metastatic progression of prostate cancer using the WGCNA. Some may serve as potential prognostic biomarkers and therapeutic targets for advanced metastatic prostate cancer.

The Coordination of mTOR Signaling and Non-Coding RNA in Regulating Epileptic Neuroinflammation

Epilepsy accounts for a significant proportion of the burden of neurological disorders. Neuroinflammation acting as the inflammatory response to epileptic seizures is characterized by aberrant regulation of inflammatory cells and molecules, and has been regarded as a key process in epilepsy where mTOR signaling serves as a pivotal modulator. Meanwhile, accumulating evidence has revealed that non-coding RNAs (ncRNAs) interfering with mTOR signaling are involved in neuroinflammation and therefore articipate in the development and progression of epilepsy. In this review, we highlight recent advances in the regulation of mTOR on neuroinflammatory cells and mediators, and feature the progresses of the interaction between ncRNAs and mTOR in epileptic neuroinflammation.

The Role of Long Non-Coding RNAs (lncRNAs) in Female Oriented Cancers

Recent advances in molecular biology have discovered the mysterious role of long non-coding RNAs (lncRNAs) as potential biomarkers for cancer diagnosis and targets for advanced cancer therapy. Studies have shown that lncRNAs take part in the incidence and development of cancers in humans. However, previously they were considered as mere RNA noise or transcription byproducts lacking any biological function. In this article, we present a summary of the progress on ascertaining the biological functions of five lncRNAs (HOTAIR, NEAT1, H19, MALAT1, and MEG3) in female-oriented cancers, including breast and gynecological cancers, with the perspective of carcinogenesis, cancer proliferation, and metastasis. We provide the current state of knowledge from the past five years of the literature to discuss the clinical importance of such lncRNAs as therapeutic targets or early diagnostic biomarkers. We reviewed the consequences, either oncogenic or tumor-suppressing features, of their aberrant expression in female-oriented cancers. We tried to explain the established mechanism by which they regulate cancer proliferation and metastasis by competing with miRNAs and other mechanisms involved via regulating genes and signaling pathways. In addition, we revealed the association between stated lncRNAs and chemo-resistance or radio-resistance and their potential clinical applications and future perspectives.