Potential Long Non-coding RNA Research Articles

The potential of long non-coding RNAs for motor function recovery after spinal cord injury in rodents: A systematic review and meta-analysis

ObjectiveLong non-coding RNAs (LncRNAs) have garnered significant attention in preclinical studies for their potential in treating spinal cord injury (SCI). This meta-analysis aimed to assess the overall efficacy of lncRNA treatments in improving motor function in rodent models of SCI. MethodsThe Embase, PubMed, Web of Science, and Scopus databases were searched. Meta-analysis was performed using STATA 14.0. The standardized mean difference (SMD) was employed to combine various motor function scores. ResultsA total of 33 studies were included in this review. Key findings indicated that lncRNA treatments could markedly enhance locomotor function in rodents with SCI compared to control groups (SMD = 4.20, 95% CI: 3.35 to 5.05, I2 = 80.0%, P < 0.0001). Furthermore, in male rats with contusion/compression injuries, targeting specific cytosol-enriched lncRNAs to downregulate their expression may significantly improve motor function recovery. Specifically, intrathecal injection of non-viral vectors for lncRNA delivery proved to be the most effective method in this study. ConclusionsLncRNA treatments have demonstrated the potential to improve motor function in rodent models with SCI. However, the therapeutic efficacy may be overestimated. Future research should rigorously assess the clinical translational efficacy and safety of lncRNA treatments.

Abstract A020: LncTransformer: Identifying novel prognostic long-noncoding RNA biomarkers for pancreatic cancer using deep learning

Abstract Pancreatic cancer remains a formidable challenge due to high mortality rates and limited therapeutic options due to late detection of the cancer. Recent literature has focused on investigating the potential of long noncoding RNAs (lncRNAs) as biomarkers in several cancers. To identify significantly altered expression of lncRNA in pancreatic cancer, I collected information from the Cancer Genome Atlas (TCGA) and extracted RNA- sequencing (RNA-seq) transcriptomic profiles of pancreatic carcinomas. Out of 60,660 gene transcripts shared between 151 pancreatic cancer patients, 38 lncRNAs were identified to be significantly differentially expressed. To find the lncRNAs related to metastatic progression of pancreatic cancer, different machine learning algorithms, including logistic regression (LR), support vector machine (SVM), random forest classifier (RFC), and a custom autoencoder model were trained to identify potential prognostic biomarkers. The custom deep learning model predicted metastatic prognostic biomarkers with a 92% accuracy, with the second-best accuracies coming from the SVM and RFC models, having an accuracy of 76%. Using the deep learning model, the following novel lncRNA and gene biomarkers were identified: LINC01300, SERPINB13, AC010789.1, TMPRSS15, DUSP5- DT, AL513128.3, MIR205HG, LINC00486, RF00019, LINC01115, and AC133530.1. Further investigating these results, specifically the identified lncRNA, the LINC01300 was identified to be potentially circulating in the blood. If further analysis proves this hypothesis correct then LINC01300 along with other identified genes could serve as biomarkers in a liquid biopsy. The identified biomarkers would be especially helpful in rural areas with lower accessibility to healthcare as it would allow for an easier, more efficient, and cost-effective method of pancreatic cancer detection. Based on these findings, further investigations of this gene panel in vitro and in vivo will be conducted, as they could be targeted for improved outcomes in pancreatic cancer patients and assist in the diagnosis of metastatic progression based on RNA-seq data of primary pancreatic tumors or the development of a liquid biopsy. Citation Format: Shivali Singh. LncTransformer: Identifying novel prognostic long-noncoding RNA biomarkers for pancreatic cancer using deep learning [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: RNAs as Drivers, Targets, and Therapeutics in Cancer; 2024 Nov 14-17; Bellevue, Washington. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(11_Suppl):Abstract nr A020.

Abstract A067: lncTransformer: Identifying novel prognostic biomarkers for pancreatic cancer using deep learning models

Abstract Pancreatic cancer remains a formidable challenge due to high mortality rates and limited therapeutic options due to late detection of the cancer. Recent literature has focused on investigating the potential of long noncoding RNAs (lncRNAs) as biomarkers in several cancers. To identify significantly altered expression of lncRNA in pancreatic cancer, I collected information from the Cancer Genome Atlas (TCGA) and extracted RNA-sequencing (RNA-seq) transcriptomic profiles of pancreatic carcinomas. Out of 60,660 gene transcripts shared between 151 pancreatic cancer patients, 38 lncRNAs were identified to be significantly differentially expressed. To find the lncRNAs related to metastatic progression of pancreatic cancer, different machine learning algorithms, including logistic regression (LR), support vector machine (SVM), random forest classifier (RFC), and a custom autoencoder model were trained to identify potential prognostic biomarkers. The custom deep learning model predicted metastatic prognostic biomarkers with a 92% accuracy, with the second-best accuracies coming from the SVM and RFC models, having an accuracy of 76%. Using the deep learning model, the following novel lncRNA and gene biomarkers were identified: LINC01300, SERPINB13, AC010789.1, TMPRSS15, DUSP5-DT, AL513128.3, MIR205HG, LINC00486, RF00019, LINC01115, and AC133530.1. Further investigating these results, specifically the identified lncRNA, the LINC01300 was identified to be potentially circulating in the blood. If further analysis proves this hypothesis correct then LINC01300 along with other identified genes could serve as a biomarker panel for a liquid biopsy. The identified biomarkers would be especially helpful in rural areas with lower accessibility to healthcare as it would allow for an easier, more efficient, and cost-effective method of pancreatic cancer detection. Based on these findings, further investigations of this gene panel are being conducted, in vitro and in vivo, to create a novel liquid biopsy to assist in the prognostic diagnosis of metastatic progression of pancreatic cancer. Citation Format: Shivali Singh. lncTransformer: Identifying novel prognostic biomarkers for pancreatic cancer using deep learning models [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A067.

Changes in the expression profile of serum lncRNAs in pregnant women with high hepatitis B viral load during antiviral and non-antiviral treatment

ObjectiveThis research analyzes the potential of long non-coding RNAs (lncRNAs) as markers in determining the necessity of antiviral treatment in pregnant women by examining alterations in the expression profile of serum lncRNAs in pregnant women with elevated hepatitis B viral load (HBVL) under antiviral and non-antiviral treatment regimens between the second trimester and delivery.MethodsSerum was obtained from 6 s-trimester pregnant women with high HBVL and no intrauterine infection. Then, 3 of these women were randomly selected for antiviral treatment, with the remaining 3 women undergoing non-antiviral treatment as control. Serum samples were again collected from these 6 women before delivery. The expression profile of lncRNAs was analyzed with microarray technology, followed by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The axes of hub lncRNA-miRNA-mRNA were identified based on the competing endogenous RNA (ceRNA) network.ResultsThe expression profile of serum lncRNAs in pregnant women with high HBVL changed significantly from the second trimester of pregnancy until delivery under antiviral or non-antiviral treatment. The Venn diagram was utilized to screen out the jointly up-regulated and down-regulated lncRNAs in the serum of pregnant women under antiviral and non-antiviral treatment before delivery. Additionally, the KEGG pathway enrichment analysis results showed that lncRNAs might mediate the Hippo pathway in HBV infection. Based on the ceRNA network, 3 hub lncRNAs (CATG00000076041.1, LINC01310, and G014655) were found to potentially regulate the key gene TP73 in the Hippo pathway.ConclusionIn this study, we retrieved co-differentially expressed lncRNAs in pregnant women with high HBVL under antiviral or non-antiviral treatment, which may be used as markers for evaluating whether pregnant women with high HBVL may be free of antiviral treatment. This study may provide a basis for preventing potential adverse effects of antiviral treatment on maternal and fetal health.

Upregulation of long non-coding RNA ENSG00000267838 is related to the high risk of progression and non-response to chemoradiotherapy treatment for cervical cancer

Cervical cancer (CC) is a global public health concern, primarily caused by persistent infection with oncogenic types of human papillomavirus (HPV). The World Health Organization (WHO) has established a plan to eliminate CC as a public health issue by the year 2100. However, the implementation of the HPV vaccine is impeded by vaccine restrictions and misinformation despite its demonstrated effectiveness. The CC treatment is influenced by the disease stage, with an unfavorable prognosis for those in advanced stages. This study aimed to investigate the potential of long non-coding RNAs (lncRNAs) in CC by identifying and characterizing related lncRNAs, elucidating their regulatory mechanisms and molecular interactions, and analyzing their expression patterns in patients with diverse responses to chemoradiotherapy. Non-stem cells from CC were isolated using flow cytometry sorting and used for total RNA extraction. The RNA was used to build libraries that were subsequently sequenced using the Illumina Nextseq 550.417 lncRNAs that showed differentially expressed between CC patients who responded or not to treatment. Further analysis demonstrated that these lncRNAs significantly interact with several molecules, which play crucial roles in CC progression and therapeutic resistance. Statistical analysis correlated the expression profile of these lncRNAs with treatment efficacy. Three lncRNAs, ENSG00000267838, ENSG00000266340, and FRMD6-AS1, were identified with positive expression related to non-response to chemoradiotherapy and worse progression-free survival in CC patients. Specifically, lncRNA ENSG00000267838 has its up-regulation related to non-response and down-regulation to response to chemoradiotherapy treatment.

LncRNA HAGLR regulates gastric cancer progression by regulating the miR-20a-5p/E2F1 axis.

Gastric cancer (GC) stands as a prevalent and challenging malignancy within the gastrointestinal tract. The potential of long non-coding RNAs (lncRNAs) as biomarkers and therapeutic targets in oncology has garnered immense research interest. This study aims to elucidate the relevance, biological roles, and mechanistic pathways of LncRNA HAGLR in the context of GC. The assessments of cell proliferation, migration, and invasion were executed using CCK-8, wound healing, and Transwell assays. The interactions between HAGLR, miR-20a-5p, and E2F1 were appraised through luciferase reporter assays, fluorescence in situ hybridization (FISH), and RNA immunoprecipitation (RIP). A tumor xenograft model provided in vivo validation for in vitro findings. Elevated levels of HAGLR in GC cells and tissue specimens were linked to worse patient outcomes. The inhibition of HAGLR led to a decrease in GC cell proliferation, migration, and invasion, whereas its activation prompted contrary effects. The impact of HAGLR on cell migration and invasion was notably associated with epithelial-mesenchymal transition (EMT). Through bioinformatics, luciferase reporter assays, FISH, RIP, and Western blot analyses, it was revealed that HAGLR acts as a molecular sponge for miR-20a-5p, consequently augmenting E2F1 levels. The data suggest that the HAGLR/miR-20a-5p/E2F1 regulatory cascade is implicated in GC pathogenesis, offering a novel therapeutic avenue for GC management.

Exploring the translational landscape of the long noncoding RNA transcriptome in acute respiratory distress syndrome: it is a long way to the top.

Acute respiratory distress syndrome (ARDS) poses a significant and widespread public health challenge. Extensive research conducted in recent decades has considerably improved our understanding of the disease pathophysiology. Nevertheless, ARDS continues to rank among the leading causes of mortality in intensive care units and its management remains a formidable task, primarily due to its remarkable heterogeneity. As a consequence, the syndrome is underdiagnosed, prognostication has important gaps and selection of the appropriate therapeutic approach is laborious. In recent years, the noncoding transcriptome has emerged as a new area of attention for researchers interested in biomarker development. Numerous studies have confirmed the potential of long noncoding RNAs (lncRNAs), transcripts with little or no coding information, as noninvasive tools for diagnosis, prognosis and prediction of the therapeutic response across a broad spectrum of ailments, including respiratory conditions. This article aims to provide a comprehensive overview of lncRNAs with specific emphasis on their role as biomarkers. We review current knowledge on the circulating lncRNAs as potential markers that can be used to enhance decision making in ARDS management. Additionally, we address the primary limitations and outline the steps that will be essential for integration of the use of lncRNAs in clinical laboratories. Our ultimate objective is to provide a framework for the implementation of lncRNAs in the management of ARDS.

Investigating diagnostic potential of long non-coding RNAs in head and neck squamous cell carcinoma using TCGA database and clinical specimens

Head and neck squamous cell carcinoma (HNSCC) is a prevalent and prognostically challenging cancer worldwide. The role of long non-coding RNAs (lncRNAs) in cancer regulation is progressively being understood. This study aims to identify lncRNAs with diagnostic potential as biomarkers for HNSCC. Statistical analysis was performed on expression data from the Cancer Genome Atlas (TCGA) database to identify potential lncRNAs associated with HNSCC. Four selected lncRNAs were validated using real-time quantitative reverse transcription polymerase chain reaction and correlated with clinical factors. Functional roles were further investigated. A total of 488 differentially expressed lncRNAs were identified in TCGA-HNSC. After rigorous evaluation based on p-values, survival analysis, and ROC analysis, 24 lncRNAs were prioritized for additional investigation. LINC00460, LINC00941, CTC-241F20.4, and RP11-357H14.17 were established as candidate diagnostic biomarkers. These lncRNAs exhibited elevated expression in HNSCC tissues and were associated with poor prognosis. Combining them showed high diagnostic accuracy. Notably, LINC00460 and CTC-241F20.4 demonstrated a significant elevation in the advanced stages of HNSCC. We constructed an lncRNA-mRNA regulatory network, and the array of significant regulatory pathways identified included focal adhesion, regulation of epithelial cell migration, and others. Additionally, these lncRNAs were found to influence immune responses by modulating immune cell infiltration in the HNSCC microenvironment. Our research indicates that LINC00460, LINC00941, RP11-357H14.17, and CTC-241F20.4 may have diagnostic and prognostic importance in HNSCC. Furthermore, we have gained insights into their potential functional roles, particularly about immune responses and interactions in the microenvironment.

Harnessing the potential of long non-coding RNAs in breast cancer: from etiology to treatment resistance and clinical applications.

Breast cancer (BC) is the most common malignancy among women and a leading cause of cancer-related deaths of females worldwide. It is a complex and molecularly heterogeneous disease, with various subtypes that require different treatment strategies. Despite advances in high-resolution single-cell and multinomial technologies, distant metastasis and therapeutic resistance remain major challenges for BC treatment. Long non-coding RNAs (lncRNAs) are non-coding RNAs with more than 200 nucleotides in length. They act as competing endogenous RNAs (ceRNAs) to regulate post-transcriptional gene stability and modulate protein-protein, protein-DNA, and protein-RNA interactions to regulate various biological processes. Emerging evidence suggests that lncRNAs play essential roles in human cancers, including BC. In this review, we focus on the roles and mechanisms of lncRNAs in BC progression, metastasis, and treatment resistance, and discuss their potential value as therapeutic targets. Specifically, we summarize how lncRNAs are involved in the initiation and progression of BC, as well as their roles in metastasis and the development of therapeutic resistance. We also recapitulate the potential of lncRNAs as diagnostic biomarkers and discuss their potential use in personalized medicine. Finally, we provide lncRNA-based strategies to promote the prognosis of breast cancer patients in clinical settings, including the development of novel lncRNA-targeted therapies.

Dysregulation of long non-coding RNAs in Takayasu arteritis: A proof-of-concept study.

Takayasu arteritis (TAK) is a rare systemic vasculitis primarily affecting the aorta and its major branches. Early diagnosis is critical to prevent severe vascular complications, yet current biomarkers are insufficient. This proof-of-concept study explores the potential of long non-coding RNAs (lncRNAs) in TAK, an area largely unexplored. In this cross-sectional study, 53 TAK patients, 53 healthy controls, and 10 rheumatoid arthritis (RA) patients were enrolled. Clinical evaluations, disease activity assessments, and lncRNA expression levels were analyzed. TAK patients exhibited significant dysregulation in several lncRNAs, including THRIL (19.4, 11.1-48.8 vs. 62.5, 48.6-91.4 arbitrary units [a.u.]; p < 0.0001), HIF1A-AS1 (4.5, 1.8-16.6 vs. 26.5, 19.8-33.7 a.u.; p < 0.0001), MALAT-1 (26.9, 13.8-52.5 vs. 92.1, 58.5-92.1 a.u.; p < 0.0001), and HOTAIR (8.0, 2.5-24.5 vs. 36.0, 30.0-43.8 a.u.; p < 0.0001), compared to healthy controls. Notably, HOTAIR (area under the ROC curve [AUC] = 0.825), HIF1A-AS1 (AUC = 0.820), and THRIL (AUC = 0.781) demonstrated high diagnostic potential with superior specificity (approximately 95%). While lncRNAs showed diagnostic promise, no significant correlations with TAK activity were observed. Comparative analysis with RA patients revealed distinct lncRNA expression patterns. This study unveils significant dysregulation of lncRNAs THRIL, HIF1A-AS1, and HOTAIR in TAK patients, underscoring their potential as biomarkers and opening avenues for further research into the mechanistic roles of these lncRNAs in TAK pathogenesis.

Exploring ceRNA networks for key biomarkers in breast cancer subtypes and immune regulation

Breast cancer is a major global health concern, and recent researches have highlighted the critical roles of non-coding RNAs in both cancer and the immune system. The competing endogenous RNA hypothesis suggests that various types of RNA, including coding and non-coding RNAs, compete for microRNA targets, acting as molecular sponges. This study introduces the Pre_CLM_BCS pipeline to investigate the potential of long non-coding RNAs and circular RNAs as biomarkers in breast cancer subtypes. The pipeline identifies specific modules within each subtype that contain at least one long non-coding RNA or circular RNA exhibiting significantly distinct expression patterns when compared to other subtypes. The results reveal potential biomarker genes for each subtype, such as circ_001845, circ_001124, circ_003925, circ_000736, and circ_003996 for the basal-like subtype, circ_00306 and circ_00128 for the luminal B subtype, circ_000709 and NPHS1 for the normal-like subtype, CAMKV and circ_001855 for the luminal A subtype, and circ_00128 and circ_00173 for the HER2+ subtype. Additionally, certain long non-coding RNAs and circular RNAs, including RGS5-AS1, C6orf223, HHLA3-AS1, circ_000349, circ_003996, circ_003925, circ_002665, circ_001855, and DLEU1, are identified as potential regulators of T cell mechanisms, underscoring their importance in understanding breast cancer progression in various subtypes. This pipeline provides valuable insights into cancer and immune-related processes in breast cancer subtypes.

LncRNA MAGI2-AS3-Encoded Polypeptide Restrains the Proliferation and Migration of Breast Cancer Cells.

Accumulating articles have reported the coding potential of long non-coding RNAs (lncRNAs). However, only a few lncRNAs-encoded peptides have been studied. Breast cancer (BRCA) progression-related gene modules were determined by weighted gene co-expression network analysis (WGCNA). Cell viability, proliferation, and migration capacities were assessed by Cell counting kit-8 (CCK8), 5-ethynyl-2'-deoxyuridine (EdU), and transwell assays. Immunofluorescence (IF) assay was implemented to observe protein expression. Co-immunoprecipitation (Co-IP) and high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) were employed to analyze MAGI2 antisense RNA 3 (MAGI2-AS3)-ORF5-interacted proteins. WGCNA identified that MEpurple and MEblack modules were significantly negatively correlated with T stage in BRCA patients. MAGI2-AS3 was screened as one of the differentially expressed (DE) lncRNAs with translational potential in MEblack and MEpurple modules in BRCA. The data in The Cancer Genome Atlas (TCGA) uncovered that MAGI2-AS3 abundance was significantly decreased in invasive BRCA patients, and it had high diagnostic and prognostic values. MAGI2-AS3-ORF5 notably restrained BRCA cell viability, proliferation, and migration. Mechanically, MAGI2-AS3-ORF5 might affect the progression of BRCA cells by binding to extracellular matrix (ECM)-related proteins. MAGI2-AS3-ORF5 played an anti-tumor role by inhibiting BRCA cell viability, proliferation, and migration. MAGI2-AS3-ORF5 might modulate BRCA cell migration through ECM-associated proteins.

The transcriptional landscape and diagnostic potential of long non-coding RNAs in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a deadly cancer with no clinically relevant biomarkers for early detection. Here, we comprehensively characterized the transcriptional landscape of long non-coding RNAs (lncRNAs) in paired tumor and normal tissue specimens from 93 ESCC patients, and identified six key malignancy-specific lncRNAs that were integrated into a Multi-LncRNA Malignancy Risk Probability model (MLMRPscore). The MLMRPscore performed robustly in distinguishing ESCC from normal controls in multiple in-house and external multicenter validation cohorts, including early-stage I/II cancer. In addition, five candidate lncRNAs were confirmed to have non-invasive diagnostic potential in our institute plasma cohort, showing superior or comparable diagnostic accuracy to current clinical serological markers. Overall, this study highlights the profound and robust dysregulation of lncRNAs in ESCC and demonstrates the potential of lncRNAs as non-invasive biomarkers for the early detection of ESCC.

Recent Advances and Future Potential of Long Non-Coding RNAs in Insects.

Over the last decade, long non-coding RNAs (lncRNAs) have witnessed a steep rise in interest amongst the scientific community. Because of their functional significance in several biological processes, i.e., alternative splicing, epigenetics, cell cycle, dosage compensation, and gene expression regulation, lncRNAs have transformed our understanding of RNA's regulatory potential. However, most knowledge concerning lncRNAs comes from mammals, and our understanding of the potential role of lncRNAs amongst insects remains unclear. Technological advances such as RNA-seq have enabled entomologists to profile several hundred lncRNAs in insect species, although few are functionally studied. This article will review experimentally validated lncRNAs from different insects and the lncRNAs identified via bioinformatic tools. Lastly, we will discuss the existing research challenges and the future of lncRNAs in insects.

Therapeutic Potential of Long Non-Coding RNAs of HIV-1, SARS-CoV-2, and Endogenous Retroviruses

Long non-protein coding RNAs (lncRNAs, predicted to be up to 200,000 in the human genome) are nucleic acids of more than 200 nucleotides that not only play primordial roles in the regulation of chromatin states, but also are capable of decoying or scaffolding proteins (e.g., transcription factors, TFs; host and viral proteins), DNA (e.g., promoters and enhancers), and RNA (e.g., miRNAs and hnRNAs) in 3D conformations acting in a chaperonin-like fashion. Specifically, lncRNAs modulate gene expression during the regulatory layers of transcription, RNA processing (splicing and indirectly editing), translation, and post-translational modifications including phosphorylation, acetylation, and ubiquitination. Accumulated evidence indicates that lncRNAs regulate antiviral immune responses mainly by transcription of IFN regulatory factors 1 (IRF1) and 4 (IRF4), which contribute to type I interferon (IFNα and IFNβ) upregulation. Some of the most common TFs regulated by lncRNAs are TP53, CTCF, MYC, SOX2, EZH2 SFPQ, SUZ12, STAT1, STAT3, and NF-kappa B. In this review, the known functions of selected lncRNAs genes in HIV/AIDS (MALAT1, HEAL, NRON, TAR-gag, TP53COR1/lincRNA-p21, NEAT1, NKILA, LINC01426 [formerly Uc002yug.2], FAS-AS1, LINC00173 [formerly FLJ42957/NCRNA00173], GAS5, and HIV-encoded antisense lncRNA) and COVID-19 (EGOT, MALAT1, NEAT1, DANCR, HOTAIR, FENDRR, LINC1505, FALCOR, and HISLA) are discussed. Furthermore, MALAT1 is also involved in subsequent complications such as deep vein thrombosis (DVT) in COVID-19. In addition, after the increased understanding of the role of lncRNAs from Human Endogenous Retroviruses (HERVs, predicted to be at least 582 different with 725,763 repeats of them in the human genome) in cancer (TROJAN) and heart development (BANCR), transcripts of HERVs as lnc-EPAV and lnc-ALVA1-AS1 have recently drawn attention as host protective agents against viral infections. A deeper knowledge of host and viral lncRNAs interactions and their regulation will pave the way for the design of novel drugs inspired by host- and viral-encoded lncRNAs. These novel drugs have the potential to reduce the burden of HIV/AIDS and COVID-19 twofold: (1) by increasing their efficacy and (2) by minimizing the side effects of current drugs. We expect that lncRNA drugs will be able to modulate human and viral transcription in an unprecedented way but still effectively maintain homeostasis by deploying functionality below the pathogenic threshold.

Diagnostic, prognostic and therapeutic potential of long noncoding RNAs in cancer.

Long noncoding RNAs (lncRNAs) are longer than 200 nucleotides in length and undergo splicing, capping, polyadenylation, and editing just like mRNA. Evidence is growing that they regulate transcription, splicing, RNA degradation, and translation of genes and that their expression has been linked to a variety of illnesses, including cancer. The advancement of next-generation and high-throughput sequencing has changed the way lncRNAs are identified and characterized, revealing a relationship between lncRNAs and several tumor types. Since then, they have gained a significant attraction as a promising candidate in cancer diagnosis, prognosis, and therapy. Furthermore, they are a good candidate for consideration as tumor biomarkers due to their high stability, better tissue/cell selectivity, aberrant expression in certain malignancies, and easy and noninvasive detection. In addition, lncRNAs are being examined as therapeutic targets in clinical trials for a variety of malignancies. This review highlights the potential of lncRNAs as biomarkers or therapeutic targets in light of the current progress, clinical investigations, and patents filed so far.

Long Non-Coding RNAs in Cardiovascular Diseases: Potential Function as Biomarkers and Therapeutic Targets of Exercise Training.

Despite advances in treatments and therapies, cardiovascular diseases (CVDs) remain one of the leading causes of death worldwide. The discovery that most of the human genome, although transcribed, does not encode proteins was crucial for focusing on the potential of long non-coding RNAs (lncRNAs) as essential regulators of cell function at the epigenetic, transcriptional, and post-transcriptional levels. This class of non-coding RNAs is related to the pathophysiology of the cardiovascular system. The different expression profiles of lncRNAs, in different contexts of CVDs, change a great potential in their use as a biomarker and targets of therapeutic intervention. Furthermore, regular physical exercise plays a protective role against CVDs; on the other hand, little is known about its underlying molecular mechanisms. In this review, we look at the accumulated knowledge on lncRNAs and their functions in the cardiovascular system, focusing on the cardiovascular pathology of arterial hypertension, coronary heart disease, acute myocardial infarction, and heart failure. We discuss the potential of these molecules as biomarkers for clinical use, their limitations, and how the manipulation of the expression profile of these transcripts through physical exercise can begin to be suggested as a strategy for the treatment of CVDs.

FOXD1-AS1 upregulates FOXD1 to promote oral squamous cell carcinoma progression.

Recently, increasing attention has been concentrated on decrypting the potential of long non-coding RNAs (lncRNAs) in influencing the progression of human tumors, oral squamous cell carcinoma (OSCC) included. The role of a novel lncRNA, forkhead box D1 antisense RNA 1 (FOXD1-AS1), has been discussed in multiple cancers. Nevertheless, its function and relevant mechanism in OSCC have been not probed yet. FOXD1-AS1 expression was detected via RT-qPCR. Colony formation, EdU, transwell and Western blot analyses tested the functional role of FOXD1-AS1 in OSCC cells. The relationship between RNAs was assessed by a series of mechanical assays. FOXD1-AS1 was expressed at a high level in head and neck squamous cell carcinoma (HNSC). Knockdown of FOXD1-AS1 exerted repressive impacts on OSCC cell proliferation, migration, invasion, and EMT. Moreover, FOXD1-AS1 positively regulated its nearby gene FOXD1 via interacting with miR-369-3p. In addition, adenosine deaminase RNA specific (ADAR), known as a RNA-binding protein (RBP), was capable to bind with FOXD1-AS1 and FOXD1simultaneously, and could regulate the stability of FOXD1mRNA. Aside from that, rescue assays delineated that FOXD1-AS1 promoted OSCC progression via upregulating FOXD1. FOXD1-AS1 elevates FOXD1 expression to promote OSCC malignant phenotypes through miR-369-3p and ADAR.

Potential of Long Non-Coding RNAs in Age-Related Macular Degeneration.

Age-related macular degeneration (AMD) is the leading cause of visual impairment in the aging population with poorly known pathogenesis and lack of effective treatment. Age and family history are the strongest AMD risk factors, and several loci were identified to contribute to AMD. Recently, also the epigenetic profile was associated with AMD, and some long non-coding RNAs (lncRNAs) were shown to involve in AMD pathogenesis. The Vax2os1/2 (ventral anterior homeobox 2 opposite strand isoform 1) lncRNAs may modulate the balance between pro- and anti-angiogenic factors in the eye contributing to wet AMD. The stress-induced dedifferentiation of retinal pigment epithelium cells can be inhibited by the ZNF503-AS1 (zinc finger protein 503 antisense RNA 2) and LINC00167 lncRNAs. Overexpression of the PWRN2 (Prader-Willi region non-protein-coding RNA 2) lncRNA aggravated RPE cells apoptosis and mitochondrial impairment induced by oxidative stress. Several other lncRNAs were reported to exert protective or detrimental effects in AMD. However, many studies are limited to an association between lncRNA and AMD in patients or model systems with bioinformatics. Therefore, further works on lncRNAs in AMD are rational, and they should be enriched with mechanistic and clinical studies to validate conclusions obtained in high-throughput in vitro research.

The Indirect Antiviral Potential of Long Noncoding RNAs Encoded by IFITM Pseudogenes.

The interferon-induced transmembrane (IFITM) gene family performs multiple functions in immunity, including inhibition of virus entry into cells. The IFITM repertoire varies widely between species and consists of protein-coding genes and pseudogenes. The selective forces driving pseudogenization within gene families are rarely understood. In this issue, the human pseudogene IFITM4P is characterized as a virus-induced, long noncoding RNA that contributes to restriction of influenza A virus by regulating mRNA levels of IFITM1, IFITM2, and IFITM3.