lncRNA cytoskeleton regulator RNA (CYTOR): Diverse functions in metabolism, inflammation and tumorigenesis, and potential applications in precision oncology

Matrix stiffness-dependent regulation of immunomodulatory genes in human MSCs is associated with the lncRNA CYTOR

Cell-matrix interactions in 3D environments significantly differ from those in 2D cultures. As such, mechanisms of mechanotransduction in 2D cultures are not necessarily applicable to cell-encapsulating hydrogels that resemble features of tissue architecture. Accordingly, the characterization of molecular pathways in 3D matrices is expected to uncover insights into how cells respond to their mechanical environment in physiological contexts, and potentially also inform hydrogel-based strategies in cell therapies. In this study, a bone marrow-mimetic hydrogel was employed to systematically investigate the stiffness-responsive transcriptome of mesenchymal stromal cells. High matrix rigidity impeded integrin-collagen adhesion, resulting in changes in cell morphology characterized by a contractile network of actin proximal to the cell membrane. This resulted in a suppression of extracellular matrix-regulatory genes involved in the remodeling of collagen fibrils, as well as the upregulation of secreted immunomodulatory factors. Moreover, an investigation of long noncoding RNAs revealed that the cytoskeleton regulator RNA (CYTOR) contributes to these 3D stiffness-driven changes in gene expression. Knockdown of CYTOR using antisense oligonucleotides enhanced the expression of numerous mechanoresponsive cytokines and chemokines to levels exceeding those achievable by modulating matrix stiffness alone. Taken together, our findings further our understanding of mechanisms of mechanotransduction that are distinct from canonical mechanotransductive pathways observed in 2D cultures.

Transcriptomics analysis of long non-coding RNAs in smooth muscle cells from patients with peripheral artery disease and diabetes mellitus

Diabetes mellitus (DM) is a significant risk factor for peripheral arterial disease (PAD), and PAD is an independent predictor of cardiovascular disorders (CVDs). Growing evidence suggests that long non-coding RNAs (lncRNAs) significantly contribute to disease development and underlying complications, particularly affecting smooth muscle cells (SMCs). So far, no study has focused on transcriptome analysis of lncRNAs in PAD patients with and without DM. Tissue samples were obtained from our Vascular Biobank. Due to the sample's heterogeneity, expression analysis of lncRNAs in whole tissue detected only ACTA2-AS1 with a 4.9-fold increase in PAD patients with DM. In contrast, transcriptomics of SMCs revealed 28 lncRNAs significantly differentially expressed between PAD with and without DM (FDR < 0.1). Sixteen lncRNAs were of unknown function, six were described in cancer, one connected with macrophages polarisation, and four were associated with CVDs, mainly with SMC function and phenotypic switch (NEAT1, MIR100HG, HIF1A-AS3, and MRI29B2CHG). The enrichment analysis detected additional lncRNAs H19, CARMN, FTX, and MEG3 linked with DM. Our study revealed several lncRNAs in diabetic PAD patients associated with the physiological function of SMCs. These lncRNAs might serve as potential therapeutic targets to improve the function of SMCs within the diseased tissue and, thus, the clinical outcome.

Direct and indirect effects of CYTOR lncRNA regulate HIV gene expression

The implementation of antiretroviral therapy (ART) has effectively restricted the transmission of Human Immunodeficiency Virus (HIV) and improved overall clinical outcomes. However, a complete cure for HIV remains out of reach, as the virus persists in a stable pool of infected cell reservoir that is resistant to therapy and thus a main barrier towards complete elimination of viral infection. While the mechanisms by which host proteins govern viral gene expression and latency are well-studied, the emerging regulatory functions of non-coding RNAs (ncRNA) in the context of T cell activation, HIV gene expression and viral latency have not yet been thoroughly explored. Here, we report the identification of the Cytoskeleton Regulator (CYTOR) long non-coding RNA (lncRNA) as an activator of HIV gene expression that is upregulated following T cell stimulation. Functional studies show that CYTOR suppresses viral latency by directly binding to the HIV promoter and associating with the cellular positive transcription elongation factor (P-TEFb) to activate viral gene expression. CYTOR also plays a global role in regulating cellular gene expression, including those involved in controlling actin dynamics. Depletion of CYTOR expression reduces cytoplasmic actin polymerization in response to T cell activation. In addition, treating HIV-infected cells with pharmacological inhibitors of actin polymerization reduces HIV gene expression. We conclude that both direct and indirect effects of CYTOR regulate HIV gene expression.

Fatty acid metabolism-related lncRNAs are potential biomarkers for survival prediction in clear cell renal cell carcinoma

Metabolic reprogramming of energy is a newly recognized characteristic of cancer. In our current investigation, we examined the possible predictive importance of long noncoding RNAs (lncRNAs) associated to fatty acid metabolism in clear cell renal cell carcinoma (ccRCC). We conducted an analysis of the gene expression data obtained from patients diagnosed with ccRCC using the Cancer Genome Atlas (TCGA) database and the ArrayExpress database. We performed a screening to identify lncRNAs that are differentially expressed in fatty acid metabolism. Based on these findings, we developed a prognostic risk score model using these fatty acid metabolism-related lncRNAs. We then validated this model using Cox regression analysis, Kaplan-Meier survival analysis, and principal-component analysis (PCA). Furthermore, the prognostic risk score model was successfully validated using both the TCGA cohort and the E-MTAB-1980 cohort. We utilized gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) to determine the correlation between fatty acid metabolism and the PPAR signaling pathway in patients with ccRCC at various clinical stages and prognoses. We have discovered compelling evidence of the interaction between immune cells in the tumor microenvironment and tumor cells, which leads to immune evasion and resistance to drugs. This was achieved by the utilization of advanced techniques such as the CIBERSORT method, ESTIMATE R package, ssGSEA algorithm, and TIMER database exploration. Ultimately, we have established a network of competing endogenous RNA (ceRNA) that is related to fatty acid metabolism. The findings of our study suggest that medicines focused on fatty acid metabolism could be clinically significant for individuals with ccRCC. The utilization of this risk model, which is centered around the lncRNAs associated with fatty acid metabolism, could potentially provide valuable prognostic information and hold immunotherapeutic implications for patients with ccRCC.

Long non-coding RNAs in non-small cell lung cancer: implications for preventing therapeutic resistance

Lung cancer has the highest mortality and morbidity rates among all cancers worldwide. Despite many complex treatment options, including radiotherapy, chemotherapy, targeted drugs, immunotherapy, and combinations of these treatments, efficacy is low in cases of resistance to therapy, metastasis, and advanced disease, contributing to low overall survival. There is a pressing need for the discovery of novel biomarkers and therapeutic targets for the early diagnosis of lung cancer and to determine the efficacy and outcomes of drug treatments. There is now substantial evidence for the diagnostic and prognostic value of long noncoding RNAs (lncRNAs). This review briefly discusses recent findings on the roles and mechanisms of action of lncRNAs in the responses to therapy in non-small cell lung cancer.

MicroRNAs Function in Dental Stem Cells as a Promising Biomarker and Therapeutic Target for Dental Diseases

Undifferentiated, highly proliferative, clonogenic, and self-renewing dental stem cells have paved the way for novel approaches to mending cleft palates, rebuilding lost jawbone and periodontal tissue, and, most significantly, recreating lost teeth. New treatment techniques may be guided by a better understanding of these cells and their potential in terms of the specificity of the regenerative response. MicroRNAs have been recognized as an essential component in stem cell biology due to their role as epigenetic regulators of the processes that determine stem cell destiny. MicroRNAs have been proven to be crucial in a wide variety of molecular and biological processes, including apoptosis, cell proliferation, migration, and necrocytosis. MicroRNAs have been recognized to control protein translation, messenger RNA stability, and transcription and have been reported to play essential roles in dental stem cell biology, including the differentiation of dental stem cells, the immunological response, apoptosis, and the inflammation of the dental pulp. Because microRNAs increase dental stem cell differentiation, they may be used in regenerative medicine to either preserve the stem cell phenotype or to aid in the development of tooth tissue. The development of novel biomarkers and therapies for dental illnesses relies heavily on progress made in our knowledge of the roles played by microRNAs in regulating dental stem cells. In this article, we discuss how dental stem cells and their associated microRNAs may be used to cure dental illness.

HOXC Cluster Antisense RNA 3, a Novel Long Non-Coding RNA as an Oncological Biomarker and Therapeutic Target in Human Malignancies

HOXC cluster antisense RNA 3 (HOXC-AS3) is a novel long noncoding RNA (lncRNA) that exhibits aberrant expression patterns in various cancer types. Its expression is closely related to clinicopathological features, demonstrating significant clinical relevance across multiple tumors. And HOXC-AS3 plays multifaceted roles in tumor progression, impacting cell proliferation, apoptosis, migration, invasion, epithelial-mesenchymal transition (EMT), autophagy, senescence, tumor growth, and metastasis. In this review, we summarized and comprehensively analyzed the expression and clinical significance of HOXC-AS3 as a diagnostic and prognostic biomarker for malignancies. Additionally, we presented an in-depth update on HOXC-AS3's functions and regulatory mechanisms in cancer pathogenesis. This narrative review underscores the importance of HOXC-AS3 as a promising lncRNA candidate in cancer research and its potential as a predictive biomarker and therapeutic target in clinical applications.

Systematic Analysis of Long Non-Coding RNAs in Inflammasome Activation in Monocytes/Macrophages

The NLRP3 inflammasome plays a pivotal role in regulating inflammation and immune responses. Its activation can lead to an inflammatory response and pyroptotic cell death. This is beneficial in the case of infections, but excessive activation can lead to chronic inflammation and tissue damage. Moreover, while most of the mammalian genome is transcribed as RNAs, only a small fraction codes for proteins. Among non-protein-coding RNAs, long non-coding RNAs (lncRNAs) have been shown to play key roles in regulating gene expression and cellular processes. They interact with DNA, RNAs, and proteins, and their dysregulation can provide insights into disease mechanisms, including NLRP3 inflammasome activation. Here, we systematically analyzed previously published RNA sequencing (RNA-seq) data of NLRP3 inflammasome activation in monocytes/macrophages to uncover inflammasome-regulated lncRNA genes. To uncover the functional importance of inflammasome-regulated lncRNA genes, one inflammasome-regulated lncRNA, ENSG00000273124, was knocked down in an in vitro model of macrophage polarization. The results indicate that silencing of ENSG00000273124 resulted in the up-regulation tumor necrosis factor (TNF), suggesting that this lncRNA might be involved in pro-inflammatory response in macrophages. To make our analyzed data more accessible, we developed the web database InflammasomeDB.

The interactions between DNA methylation machinery and long non-coding RNAs in tumor progression and drug resistance

DNA methylation is one of the main epigenetic mechanisms in cancer development and progression. Aberrant DNA methylation of CpG islands within promoter regions contributes to the dysregulation of various tumor suppressors and oncogenes; this leads to the appearance of malignant features, including rapid proliferation, metastasis, stemness, and drug resistance. The discovery of two important protein families, DNA methyltransferases (DNMTs) and Ten-eleven translocation (TET) dioxygenases, respectively, which are responsible for deregulated transcription of genes that play pivotal roles in tumorigenesis, led to further understanding of DNA methylation-related pathways. But how these enzymes can target specific genes in different malignancies; recent studies have highlighted the considerable role of Long Non-coding RNAs (LncRNAs). LncRNAs recruit these enzymes to promoter regions of genes and mediate their functions, showing great potential as therapeutic agents targeting the epigenetic regulation of various genes. Considering the importance of combining the current treatment methods, especially chemotherapies, with DNA methylation inhibitors in improving patients' outcomes, this review aimed to summarize the recent findings about the interaction between DNA methylation machinery and LncRNAs in regulating genes involved in tumorigenesis and drug resistance. So, these studies could provide insights toward developing novel strategies for cancer-targeted therapy.

Identification of key differentially expressed genes in SARS-CoV-2 using RNA-seq analysis with a systems biology approach

COVID-19 is associated with dysregulation of several genes and signaling pathways. Based on the importance of expression profiling in identification of the pathogenesis of COVID-19 and proposing novel therapies for this disorder, we have employed an in silico approach to find differentially expressed genes between COVID-19 patients and healthy controls and their relevance with cellular functions and signaling pathways. We obtained 630 DEmRNAs, including 486 down-regulated DEGs (such as CCL3 and RSAD2) and 144 up-regulated DEGs (such as RHO and IQCA1L), and 15 DElncRNAs, including 9 down-regulated DElncRNAs (such as PELATON and LINC01506) and 6 up-regulated DElncRNAs (such as AJUBA-DT and FALEC). The PPI network of DEGs showed the presence of a number immune-related genes such as those coding for HLA molecules and interferon regulatory factors. Taken together, these results highlight the importance of immune-related genes and pathways in the pathogenesis of COVID-19 and suggest novel targets for treatment of this disorder.

Thermodynamic and structural characterization of an EBV infected B-cell lymphoma transcriptome

Epstein-Barr virus (EBV) is a widely prevalent human herpes virus infecting over 95% of all adults and is associated with a variety of B-cell cancers and induction of multiple sclerosis. EBV accomplishes this in part by expression of coding and noncoding RNAs and alteration of the host cell transcriptome. To better understand the structures which are forming in the viral and host transcriptomes of infected cells, the RNA structure probing technique Structure-seq2 was applied to the BJAB-B1 cell line (an EBV infected B-cell lymphoma). This resulted in reactivity profiles and secondary structural analyses for over 10000 human mRNAs and lncRNAs, along with 19 lytic and latent EBV transcripts. We report in-depth structural analyses for the human MYC mRNA and the human lncRNA CYTOR. Additionally, we provide a new model for the EBV noncoding RNA EBER2 and provide the first reported model for the EBV tandem terminal repeat RNA. In-depth thermodynamic and structural analyses were carried out with the motif discovery tool ScanFold and RNAfold prediction tool; subsequent covariation analyses were performed on resulting models finding various levels of support. ScanFold results for all analyzed transcripts are made available for viewing and download on the user-friendly RNAStructuromeDB.