NCBP3/SNHG6 inhibits GBX2 transcription in a histone modification manner to facilitate the malignant biological behaviour of glioma cells

Oncogenic role of RNA-binding protein GNL2 in glioma: Promotion of tumor development through enhancing protein synthesis

RNA-binding proteins (RBPs) are aberrantly expressed in various diseases, including glioma. In the present study, the role and mechanism of RBPs in glioma were investigated. Differentially expressed genes (DEGs) in glioma were screened from public databases and overlapping genes between DEGs and RBPs were selected in a bioinformatics analysis to identify the hub gene. Next, evaluation of expression, survival analysis and cell experiments were performed to examine the impact of the hub gene on glioma. Through bioinformatics analysis, G protein nucleolar 2 (GNL2), programmed cell death 11 (PDCD11) and ribosomal protein S6 (RPS6) were identified as potential biomarkers in glioma prognosis and GNL2 was chosen as the hub gene for further investigation. GNL2 was increased in glioma tissues and related to poor survival outcomes. Cell experiments revealed that GNL2 knockdown inhibited glioma cell growth, migration and invasion. In addition, GNL2 was found to affect the overall protein synthesis of ribosomal protein L11 in glioma cells. In conclusion, GNL2, PDCD11 and RPS6 may serve as potential biomarkers in glioma prognosis. Importantly, GNL2 acts as an oncogene in glioma and it enhances protein synthesis to promote the development of brain glioma.

The roles of FLOT1 in human diseases (Review)

FLOT1, a scaffold protein of lipid rafts, is involved in several biological processes, including lipid raft protein‑-dependent or clathrin‑independent endocytosis, and the formation of hippocampal synapses, amongst others. Increasing evidence has shown that FLOT1 can function as both a cancer promoter and cancer suppressor dependent on the type of cancer. FLOT1 can affect the occurrence and development of several types of cancer by affecting epithelial‑mesenchymal transition, proliferation of cancer cells, and relevant signaling pathways, and is regulated by long intergenic non‑coding RNAs or microRNAs. In the nervous system, overexpression or abnormally low expression of FLOT1 may lead to the occurrence of neurological diseases, such as Alzheimer's disease, Parkinson's disease, major depressive disorder and other diseases. Additionally, it is also associated with dilated cardiomyopathy, pathogenic microbial infection, diabetes‑related diseases, and gynecological diseases, amongst other diseases. In the present review, the structure and localization of FLOT1, as well as the physiological processes it is involved in are reviewed, and then the upstream and downstream regulation of FLOT1 in human disease, particularly in different types of cancer and neurological diseases are discussed, with a focus on potentially targeting FLOT1 for the clinical treatment of several diseases.

LncRNA SNHG6 role in clinicopathological parameters in cancers

RNA sequencing has revealed that a substantial portion of the human genome undergoes transcription, yet a minimal fraction of these transcripts translates into proteins. LncRNAs, RNA molecules less than 200 nt in length, once deemed as transcriptional noise, have now emerged as crucial regulators of numerous cellular processes. This review focuses on the lncRNA SNHG6, aiming to elucidate its biogenesis, the pivotal roles it plays, and its mechanisms in facilitating the hallmarks of cancer. A comprehensive literature review and analysis were undertaken to delve into the biogenesis of SNHG6, its roles in cellular processes, and the mechanisms through which it contributes to the hallmarks of cancer. SNHG6 is a notable lncRNA, observed to be overexpressed in various cancer types; its perturbation has been linked to tumor progression, emphasizing its significance in oncogenesis. This lncRNA contributes to a range of cellular aberrations, influencing transcriptional, post-transcriptional, and epigenetic processes of mRNA, ultimately driving cancerous transformations. LncRNA SNHG6 serves as a potential biomarker and therapeutic target due to its association with tumorigenesis. Understanding its mechanism and role in cancer can pave the way for novel diagnostic and therapeutic strategies.

A comprehensive insight into the role of small nucleolar RNAs (snoRNAs) and SNHGs in human cancers

Long non-coding RNAs (lncRNAs), which comprise most non-coding RNAs (ncRNAs), have recently become a focus of cancer research. How many functional ncRNAs exist is still a matter of debate. Although insufficient evidence supports that most lncRNAs function as transcriptional by-products, it is widely known that an increasing number of lncRNAs play essential roles in cells. Small nucleolar RNAs (snoRNAs), 60-300 nucleotides in length, have been better studied than long non-coding RNAs (lncRNAs) and are predominantly present in the nucleolus. Most snoRNAs are encoded in introns of protein- and non-protein-coding genes called small nucleolar RNA host genes (SNHGs). In this article, we explore the biology and characteristics of SNHGs and their role in developing human malignancies. In addition, we provide an update on the ability of these snoRNAs to serve as prognostic and diagnostic variables in various forms of cancer.

Genome-Wide Analysis of Kidney Renal Cell Carcinoma: Exploring Differentially Expressed Genes for Diagnostic and Therapeutic Targets

Kidney renal cell carcinoma (KIRC) is the most common type of renal cancer. Kidney malignancies have been ranked in the top 10 most frequently occurring cancers. KIRC is a prevalent malignancy with a poor prognosis. The disease has risen for the last 40 years, and robust biomarkers for KIRC are needed for precision/personalized medicine. In this bioinformatics study, we utilized genomic data of KIRC patients from The Cancer Genome Atlas for biomarker discovery. A total of 314 samples were used in this study. We identified many differentially expressed genes (DEGs) categorized as upregulated or downregulated. A protein-protein interaction network for the DEGs was then generated and analyzed using the Search Tool for the Retrieval of Interacting Genes plugin of Cytoscape. A set of 10 hub genes was selected based on the Maximum Clique Centrality score defined by the CytoHubba plugin. The elucidated set of genes, that is, CALCA, CRH, TH, CHAT, SLC18A3, FSHB, MYH6, CAV3, KCNA4, and GBX2, were then categorized as potential candidates to be explored as KIRC biomarkers. The survival analysis plots for each gene suggested that alterations in CHAT, CAV3, CRH, MYH6, SLC18A3, and FSHB resulted in decreased survival of KIRC patients. In all, the results suggest that genomic alterations in selected genes can be explored to inform biomarker discovery and for therapeutic predictions in KIRC.

Impact of epigenetic reprogramming on antitumor immune responses in glioma

Epigenetic remodeling is a molecular hallmark of gliomas, and it has been identified as a key mediator of glioma progression. Epigenetic dysregulation contributes to gliomagenesis, tumor progression, and responses to immunotherapies, as well as determining clinical features. This epigenetic remodeling includes changes in histone modifications, chromatin structure, and DNA methylation, all of which are driven by mutations in genes such as histone 3 genes (H3C1 and H3F3A), isocitrate dehydrogenase 1/2 (IDH1/2), α-thalassemia/mental retardation, X-linked (ATRX), and additional chromatin remodelers. Although much of the initial research primarily identified how the epigenetic aberrations impacted glioma progression by solely examining the glioma cells, recent studies have aimed at establishing the role of epigenetic alterations in shaping the tumor microenvironment (TME). In this review, we discuss the mechanisms by which these epigenetic phenomena in glioma remodel the TME and how current therapies targeting epigenetic dysregulation affect the glioma immune response and therapeutic outcomes. Understanding the link between epigenetic remodeling and the glioma TME provides insights into the implementation of epigenetic-targeting therapies to improve the antitumor immune response.

N7-methylguanosine methylation-related regulator genes as biological markers in predicting prognosis for melanoma

The aim of this study is to find those N7-methylguanosine (m7G) methylation-related regulator genes (m7GMRRGs) which were associated with melanoma prognosis and use them to develop a prognostic prediction model. Clinical information was retrieved online from The Cancer Gene Atlas (TCGA) and the Gene Expression Omnibus (GEO). R software was used to extract m⁷GMRRGs by differential expression analysis. To create a prognostic risk model, univariate and multivariate Cox regression analyses were employed for the evaluation of the prognostic significance of m⁷G methylation modifiers. Internal validation using cohort from TCGA (training set) and external validation using cohort from GEO (validation set) of the model were carried out. The model's predictive performance was confirmed by using the Kaplan-Meier, univariate, and multivariate Cox regression, and receiver operating characteristic curve (ROC) by constructing column line plots incorporating clinical factor characteristics. Immune infiltration analyses were performed to assess the immune function of m⁷GMRRGs. Drug sensitivity analysis was conducted to study chemotherapeutic drug treatment cues. Prognostic models using four m⁷GMRRGs (EIF4E3, LARP1, NCBP3, and IFIT5) showed good prognostic power in training and validation sets. The area under the curve (AUC) at 1, 3, and 5 years for GEO-melanoma were 0.689, 0.704, and 0.726, respectively. The prediction model could distinctly classify patients with melanoma into different risk subgroups (P < 0.001 for TCGA-melanoma and P < 0.05 for GEO-melanoma). Clinical characteristics were taken into account in Cox regression and AUC analysis, which highlighted that the risk score served as an independent risk factor determining the prognosis of patients with melanoma. Immuno-infiltration analysis showed that m⁷GMRRGs could potentially regulate CD8⁺ T cells as well as regulatory T cells (Treg cells). Results of our study indicate a association between m⁷GMRRGs and melanoma prognosis, and the prognostic prediction model using m⁷GMRRGs may predict the prognosis of patients with melanoma well. Nevertheless, these results may provide a clue for potential better options of melanoma treatment but need further validation in futural studies.

Meta-Analysis of RNA-Seq Datasets Identifies Novel Players in Glioblastoma

Glioblastoma is a devastating grade IV glioma with poor prognosis. Identification of predictive molecular biomarkers of disease progression would substantially contribute to better disease management. In the current study, we performed a meta-analysis of different RNA-seq datasets to identify differentially expressed protein-coding genes (PCGs) and long non-coding RNAs (lncRNAs). This meta-analysis aimed to improve power and reproducibility of the individual studies while identifying overlapping disease-relevant pathways. We supplemented the meta-analysis with small RNA-seq on glioblastoma tissue samples to provide an overall transcriptomic view of glioblastoma. Co-expression correlation of filtered differentially expressed PCGs and lncRNAs identified a functionally relevant sub-cluster containing DANCR and SNHG6, with two novel lncRNAs and two novel PCGs. Small RNA-seq of glioblastoma tissues identified five differentially expressed microRNAs of which three interacted with the functionally relevant sub-cluster. Pathway analysis of this sub-cluster identified several glioblastoma-linked pathways, which were also previously associated with the novel cell death pathway, ferroptosis. In conclusion, the current meta-analysis strengthens evidence of an overarching involvement of ferroptosis in glioblastoma pathogenesis and also suggests some candidates for further analyses.

Construction of N-7 methylguanine-related mRNA prognostic model in uterine corpus endometrial carcinoma based on multi-omics data and immune-related analysis

N-7 methylguanine (m7G) is one of the most common RNA base modifications in post-transcriptional regulation, which participates in multiple processes such as transcription, mRNA splicing and translation during the mRNA life cycle. However, its expression and prognostic value in uterine corpus endometrial carcinoma (UCEC) have not been systematically studied. In this paper, the data such as gene expression profiles, clinical data of UCEC patients, somatic mutations and copy number variants (CNVs) are obtained from the cancer genome atlas (TCGA) and UCSC Xena. By analyzing the expression differences of m7G-related mRNA in UCEC and plotting the correlation network maps, a risk score model composed of four m7G-related mRNAs (NSUN2, NUDT3, LARP1 and NCBP3) is constructed using least absolute shrinkage and selection operator (LASSO), univariate and multivariate Cox regression in order to identify prognosis and immune response. The correlation of clinical prognosis is analyzed between the m7G-related mRNA and UCEC via Kaplan-Meier method, receiver operating characteristic (ROC) curve, principal component analysis (PCA), t-SNE, decision curve analysis (DCA) curve and nomogram etc. It is concluded that the high risk is significantly correlated with (P < 0.001) the poorer overall survival (OS) in patients with UCEC. It is one of the independent risk factors affecting the OS. Differentially expressed genes are identified by R software in the high and low risk groups. The functional analysis and pathway enrichment analysis have been performed. Single sample gene set enrichment analysis (ssGSEA), immune checkpoints, m6A-related genes, tumor mutation burden (TMB), stem cell correlation, tumor immune dysfunction and rejection (TIDE) scores and drug sensitivity are also used to study the risk model. In addition, we have obtained 3 genotypes based on consensus clustering, which are significantly related to (P < 0.001) the OS and progression-free survival (PFS). The deconvolution algorithm (CIBERSORT) is applied to calculate the proportion of 22 tumor infiltrating immune cells (TIC) in UCEC patients and the estimation algorithm (ESTIMATE) is applied to work out the number of immune and matrix components. In summary, m7G-related mRNA may become a potential biomarker for UCEC prognosis, which may promote UCEC occurrence and development by regulating cell cycles and immune cell infiltration. It is expected to become a potential therapeutic target of UECE.

The Role of Non-Coding RNAs in Glioma

For decades, research in cancer biology has been focused on the protein-coding fraction of the human genome. However, with the discovery of non-coding RNAs (ncRNAs), it has become known that these entities not only function in numerous fundamental life processes such as growth, differentiation, and development, but also play critical roles in a wide spectrum of human diseases, including cancer. Dysregulated ncRNA expression is found to affect cancer initiation, progression, and therapy resistance, through transcriptional, post-transcriptional, or epigenetic processes in the cell. In this review, we focus on the recent development and advances in ncRNA biology that are pertinent to their role in glioma tumorigenesis and therapy response. Gliomas are common, and are the most aggressive type of primary tumors, which account for ~30% of central nervous system (CNS) tumors. Of these, glioblastoma (GBM), which are grade IV tumors, are the most lethal brain tumors. Only 5% of GBM patients survive beyond five years upon diagnosis. Hence, a deeper understanding of the cellular non-coding transcriptome might help identify biomarkers and therapeutic agents for a better treatment of glioma. Here, we delve into the functional roles of microRNA (miRNA), long non-coding RNA (lncRNA), and circular RNA (circRNA) in glioma tumorigenesis, discuss the function of their extracellular counterparts, and highlight their potential as biomarkers and therapeutic agents in glioma.

A putative role for lncRNAs in epigenetic regulation of memory

The central dogma of molecular genetics is defined as encoded genetic information within DNA, transcribed into messenger RNA, which contain the instructions for protein synthesis, thus imparting cellular functionality and ultimately life. This molecular genetic theory has given birth to the field of neuroepigenetics, and it is now well established that epigenetic regulation of gene transcription is critical to the learning and memory process. In this review, we address a potential role for a relatively new player in the field of epigenetic crosstalk - long non-coding RNAs (lncRNAs). First, we briefly summarize epigenetic mechanisms in memory formation and examine what little is known about the emerging role of lncRNAs during this process. We then focus discussions on how lncRNAs interact with epigenetic mechanisms to control transcriptional programs under various conditions in the brain, and how this may be applied to regulation of gene expression necessary for memory formation. Next, we explore how epigenetic crosstalk in turn serves to regulate expression of various individual lncRNAs themselves. To highlight the importance of further exploring the role of lncRNA in epigenetic regulation of gene expression, we consider the significant relationship between lncRNA dysregulation and declining memory reserve with aging, Alzheimer's disease, and epilepsy, as well as the promise of novel therapeutic interventions. Finally, we conclude with a discussion of the critical questions that remain to be answered regarding a role for lncRNA in memory.

Long Non-Coding RNA SNHG6 Supports Glioma Progression Through Upregulation of Notch1, Sox2, and EMT

Gliomas, particularly the advanced grade glioblastomas, have poor 5-year survival rates and worse outcomes. lncRNAs and EMT have been extensively studied in gliomas but the disease progression remains poorly understood. SNHG6 has been shown to affect glioma cell proliferation but its effect on EMT of glioma cells along with its effect on disease progression is not known. We screened four glioma cell lines; H4, A172, U87MG, and SW088 and grouped them based on high vs. low SNHG6 expression. Transfections with SNHG6 specific siRNA resulted in induction of apoptosis of high SNHG6 expressing A172 and U87MG cells. This was accompanied by inhibition of EMT and downregulation of EMT-modulating factor Notch1, β-catenin activity and the cancer stem cell marker Sox2. The regulation was not found to be reciprocal as silencing of Notch1 and Sox2 failed to affect SNHG6 levels. The levels of SNHG6 and Notch1 were also found elevated in Grade IV glioma patients (n = 4) relative to Grade II glioma patients (n = 5). These results identify SNHG6 and Notch1 as valid targets for glioma therapy.

Regulatory role of long non coding RNAs (lncRNAs) in neurological disorders: From novel biomarkers to promising therapeutic strategies

Long non coding RNAs (lncRNAs) are non-protein or low-protein coding transcripts that contain more than 200 nucleotides. They representing a large share of the cell's transcriptional output, demonstrate functional attributes viz. tissue-specific expression, determination of cell fate, controlled expression, RNA processing and editing, dosage compensation, genomic imprinting, conserved evolutionary traits etc. These long non coding variants are well associated with pathogenicity of various diseases including the neurological disorders like Alzheimer's disease, schizophrenia, Huntington's disease, Parkinson's disease etc. Neurological disorders are widespread and there knowing the underlying mechanisms become crucial. The lncRNAs take part in the pathogenesis by a plethora of mechanisms like decoy, scaffold, mi-RNA sequestrator, histone modifiers and in transcriptional interference. Detailed knowledge of the role of lncRNAs can help to use them further as novel biomarkers for therapeutic aspects. Here, in this review we discuss regulation and functional roles of lncRNAs in eight neurological diseases and psychiatric disorders, and the mechanisms by which they act. With these, we try to establish their roles as potential markers and viable diagnostic tools in these disorders.