The Biological Roles of lncRNAs and Future Prospects in Clinical Application

The Emerging Role of IGF2BP2 in Cancer Therapy Resistance: From Molecular Mechanism to Future Potential

Tumor resistance is one of the primary reasons for cancer treatment failure, significantly limiting the options and efficacy of cancer therapies. Therefore, overcoming resistance has become a critical factor in improving cancer treatment outcomes. IGF2BP2, as a reader of m6A methylation, plays a pivotal role in the post-transcriptional regulation of RNA through the methylation of m6A sites. It not only contributes to cancer initiation and progression but also plays a key role in tumor drug resistance. This review provides a comprehensive summary of the mechanisms by which IGF2BP2 contributes to therapy resistance, with the aim of improving the efficacy of chemotherapy in cancer treatment. Advancing research in this area is crucial for developing more effective therapies that could significantly improve the quality of life for cancer patients.

In-Silico and In-Vitro Investigation of Key Long Non-coding RNAs Involved in 5-Fluorouracil Resistance in Colorectal Cancer Cells: Analyses Highlighting NEAT1 and MALAT1 as Contributors

Background Acquired resistance to 5-fluorouracil (5-FU) frequently results in chemotherapy failure and disease recurrence in advanced colorectal cancer (CRC) patients. Research has demonstrated that dysregulation of long non-coding RNAs (lncRNAs) mediates the development of chemotherapy resistance in cancerous cells. The present study aims to identify key lncRNAs associated with 5-FU resistance in CRC using bioinformatic and experimental validation approaches. Methods The Gene Expression Omnibus (GEO) dataset GSE119481, which contains miRNA expression profiles of the parental CRC HCT116 cell line (HCT116/P) and its in-vitro established 5-FU-resistant sub-cell line (HCT116/FUR), was downloaded. Firstly, differentially expressed microRNAs (DEmiRNAs) between the parental and 5-FU resistance cells were identified. LncRNAs and mRNAs were then predicted using online databases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to uncover relevant biological mechanisms and pathways. Networks integrating lncRNAs, miRNAs, and mRNAs interactions were constructed, and topological analyses were used to identify key lncRNAs associated with 5-FU resistance. An in-vitro model of the HCT116/FUR sub-cell line was developed by exposing the HCT116/P cell line to increasing concentrations of 5-FU. Finally, real-time quantitative PCR (RT-qPCR) was performed on total RNA extracted from the HCT116/P cell line and the HCT116/FUR sub-cell line to validate the in-silico predictions of key lncRNAs. Results A total of 32 DEmiRNAs were identified. Enrichment analysis demonstrated that these DEmiRNAs were mainly enriched in several cancer hallmark pathways that regulate cell growth, cell cycle, cell survival, inflammation, immune response, and apoptosis. The predictive analysis identified 237 unique lncRNAs and 123 mRNAs interacting with these DEmiRNAs. The pathway analysis indicated that most of these predicted genes were enriched in the cellular response to starvation, protein polyubiquitination, chromatin remodeling, and negative regulation of gene expression. Topological analyses of the lncRNA-miRNA-mRNA network highlighted the nuclear enriched abundant transcript 1 (NEAT1), metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), and Opa interacting protein 5 antisense RNA 1 (OIP5-AS1) as central lncRNAs. Experimental analysis by RT-qPCR confirmed that the expression levels of NEAT1 and MALAT1 were significantly increased in HCT116/FUR cells compared to HCT116/P cells. However, no significant difference was observed in the OIP5-AS1 expression level between the two cells. Conclusion Our findings specifically highlight MALAT1 and NEAT1 as significant contributors to 5-FU resistance in CRC. These lncRNAs are promising biomarkers for diagnosing and predicting outcomes in CRC.

A prominent role of LncRNA H19 in H. pylori CagA induced DNA damage response and cell malignancy

Helicobacter pylori (H. pylori), together with its CagA, has been implicated in causing DNA damage, cell cycle arrest, apoptosis, and the development of gastric cancer. Although lncRNA H19 is abundantly expressed in gastric cancer and functions as a pro-oncogene, it remains unclear whether lncRNA H19 contributes to the oncogenic process of H. pylori CagA. This study investigates the role of H19 in the DNA damage response and malignancy induced by H. pylori. It was observed that cells infected with CagA+ H. pylori strain (GZ7/cagA) showed significantly higher H19 expression, resulting in increased γH2A.X and p-ATM expression and decreased p53 and Rad51 expression. Faster cell migration and invasion was also observed, which was reversed by H19 knockdown in H. pylori. YWHAZ was identified as an H19 target protein, and its expression was increased in H19 knockdown cells. GZ7/cagA infection responded to the increased YWHAZ expression induced by H19 knockdown. In addition, H19 knockdown stimulated cells to enter the G2-phase and attenuated the effect of GZ7/cagA infection on the cellular S-phase barrier. The results suggest that H. pylori CagA can upregulate H19 expression, participate in the DNA damage response and promote cell migration and invasion, and possibly affect cell cycle arrest via regulation of YWHAZ.

Long Non-Coding RNAs in Drug Resistance of Gastric Cancer: Complex Mechanisms and Potential Clinical Applications

Gastric cancer (GC) ranks as the third most prevalent malignancy and a leading cause of cancer-related mortality worldwide. However, the majority of patients with GC are diagnosed at an advanced stage, highlighting the urgent need for effective perioperative and postoperative chemotherapy to prevent relapse and metastasis. The current treatment strategies have limited overall efficacy because of intrinsic or acquired drug resistance. Recent evidence suggests that dysregulated long non-coding RNAs (lncRNAs) play a significant role in mediating drug resistance in GC. Therefore, there is an imperative to explore novel molecular mechanisms underlying drug resistance in order to overcome this challenging issue. With advancements in deep transcriptome sequencing technology, lncRNAs-once considered transcriptional noise-have garnered widespread attention as potential regulators of carcinogenesis, including tumor cell proliferation, metastasis, and sensitivity to chemo- or radiotherapy through multiple regulatory mechanisms. In light of these findings, we aim to review the mechanisms by which lncRNAs contribute to drug therapy resistance in GC with the goal of providing new insights and breakthroughs toward overcoming this formidable obstacle.

The Mechanisms of Long Non-coding RNA-XIST in Ischemic Stroke: Insights into Functional Roles and Therapeutic Potential

Ischemic stroke, which occurs due to the occlusion of cerebral arteries, is a common type of stroke. Recent research has highlighted the important role of long non-coding RNAs (lncRNAs) in the development of cerebrovascular diseases, specifically ischemic stroke. Understanding the functional roles of lncRNAs in ischemic stroke is crucial, given their potential contribution to the disease pathology. One noteworthy lncRNA is X-inactive specific transcript (XIST), which exhibits downregulation during the early stages of ischemic stroke and subsequent upregulation in later stages. XIST exert its influence on the development of ischemic stroke through interactions with multiple miRNAs and transcription factors. These interactions play a significant role in the pathogenesis of the condition. In this review, we have provided a comprehensive summary of the functional roles of XIST in ischemic stroke. By investigating the involvement of XIST in the disease process, we aim to enhance our understanding of the mechanisms underlying ischemic stroke and potentially identify novel therapeutic targets.

Mechanistic insights into DNA damage recognition and checkpoint control in plants

The plant DNA damage response (DDR) pathway safeguards genomic integrity by rapid recognition and repair of DNA lesions that, if unrepaired, may cause genome instability. Most frequently, DNA repair goes hand in hand with a transient cell cycle arrest, which allows cells to repair the DNA lesions before engaging in a mitotic event, but consequently also affects plant growth and yield. Through the identification of DDR proteins and cell cycle regulators that react to DNA double-strand breaks or replication defects, it has become clear that these proteins and regulators form highly interconnected networks. These networks operate at both the transcriptional and post-transcriptional levels and include liquid-liquid phase separation and epigenetic mechanisms. Strikingly, whereas the upstream DDR sensors and signalling components are well conserved across eukaryotes, some of the more downstream effectors are diverged in plants, probably to suit unique lifestyle features. Additionally, DDR components display functional diversity across ancient plant species, dicots and monocots. The observed resistance of DDR mutants towards aluminium toxicity, phosphate limitation and seed ageing indicates that gaining knowledge about the plant DDR may offer solutions to combat the effects of climate change and the associated risk for food security.

Chloroprocaine antagonizes progression of breast cancer by regulating LINC00494/miR-3619-5p/MED19 axis

Breast cancer, as the most prevalent female malignancy, leads the cancer-related death in women worldwide. Local anesthetic chloroprocaine exhibits antitumor potential, but its specific functions and underlying molecular mechanisms in breast cancer remain unclear. Here, we demonstrated chloroprocaine significantly inhibited proliferation, invasion and induced apoptosis of breast cancer cells in vitro. Tumor growth and pulmonary metastasis were also suppressed in BABL/c nude mice model with chloroprocaine treatment. LINC00494 was identified as one of the most downregulated long noncoding RNAs in chloroprocaine-treated breast cancer cells by high-throughput sequencing. Futhermore, high level of LINC00494 was positively associated with poor outcome of breast cancer patients. LINC00494 acted as a "miRNAs sponge" to compete with MED19 for the biding of miR-3619-5p, led to the upregulation of MED19. LINC00494/miR-3619-5p/MED19 axis participated in chloroprocaine-mediated inhibition of proliferation, invasion and promotion of apoptosis of breast cancer cells. Consequently, our finding suggested local anesthetic chloroprocaine attenuated breast cancer aggressiveness through LINC00494-mediated signaling pathway, which detailly revealed the clinical value of chloroprocaine during breast cancer treatment.

The long non-coding RNA LINDA restrains cellular collapse following DNA damage in Arabidopsis thaliana

The genomic integrity of every organism is endangered by various intrinsic and extrinsic stresses. To maintain genomic integrity, a sophisticated DNA damage response (DDR) network is activated rapidly after DNA damage. Notably, the fundamental DDR mechanisms are conserved in eukaryotes. However, knowledge about many regulatory aspects of the plant DDR is still limited. Important, yet little understood, regulatory factors of the DDR are the long non-coding RNAs (lncRNAs). In humans, 13 lncRNAs functioning in DDR have been characterized to date, whereas no such lncRNAs have been characterized in plants yet. By meta-analysis, we identified the putative long intergenic non-coding RNA induced by DNA damage (LINDA) that responds strongly to various DNA double-strand break-inducing treatments, but not to replication stress induced by mitomycin C. After DNA damage, LINDA is rapidly induced in an ATM- and SOG1-dependent manner. Intriguingly, the transcriptional response of LINDA to DNA damage is similar to that of its flanking hypothetical protein-encoding gene. Phylogenetic analysis of putative Brassicales and Malvales LINDA homologs indicates that LINDA lncRNAs originate from duplication of a flanking small protein-encoding gene followed by pseudogenization. We demonstrate that LINDA is not only needed for the regulation of this flanking gene but also fine-tuning of the DDR after the occurrence of DNA double-strand breaks. Moreover, Δlinda mutant root stem cells are unable to recover from DNA damage, most likely due to hyper-induced cell death.

Phloretin alleviates palmitic acid-induced oxidative stress in HUVEC cells by suppressing the expression of LncBAG6-AS

Oxidative stress (OS) is an important trigger of vascular endothelial injury (VEI), which then leads to cardiovascular disease (CVDs). Phloretin was previously investigated to alleviate OS in human umbilical vein endothelial cells (HUVECs) by activating the AMPK/Nrf2 pathway; however, whether phloretin exerts cardiovascular health benefits by targeting non-coding RNAs (ncRNAs) remains unclear. Herein, the whole transcriptome sequencing and lncRNA library building were performed on HUVECs, a commonly used cell line for CVDs study, from different groups in control (CK), palmitic acid (PA, 100 μM), and PA + phloretin (50 μM, G50). KEGG analysis demonstrated that DE-lncRNAs regulated the pathway related to OS and metabolism in HUVECs. LncBAG6-AS was highly expressed under OS stimulation, which was reversed by phloretin co-treatment. Moreover, the MMP, activities of SOD, GSH-Px, T-AOC and GR were significantly ameliorated after interference of LncBAG6-AS, which were consistent with phloretin recover group. Furthermore, the expression of DE-genes from previously reported mRNA sequencing, including MAPK10, PIK3R1, ATP2B4, AKT2, and ADCY9, were significantly changed with LncBAG6-AS interference, indicating that LncBAG6-AS may participate in the process of OS attenuation by phloretin through regulating gene expression. So, the transcriptome sequencing of HUVECs with LncBAG6-AS knockdown was subsequently performed and DE-genes for "NC vs. si-ASO-LncBAG6-AS" were significantly enriched with GO terms, such as apoptosis, response to OS, ferroptosis, and others, which were similar to those observed from KEGG analysis. Overall, this study provides new insights into the molecular mechanisms by which bioactive substances alleviate OS and potential targets for the early prevention and treatment of VEI.

The Emerging Role of Long Non-Coding RNAs in Development and Function of Gilthead Sea Bream (Sparus aurata) Fast Skeletal Muscle

Long non-coding RNAs (lncRNAs) are an emerging group of ncRNAs that can modulate gene expression at the transcriptional or translational levels. In the present work, previously published transcriptomic data were used to identify lncRNAs expressed in gilthead sea bream skeletal muscle, and their transcription levels were studied under different physiological conditions. Two hundred and ninety lncRNAs were identified and, based on transcriptomic differences between juveniles and adults, a total of seven lncRNAs showed potential to be important for muscle development. Our data suggest that the downregulation of most of the studied lncRNAs might be linked to increased myoblast proliferation, while their upregulation might be necessary for differentiation. However, with these data, as it is not possible to propose a formal mechanism to explain their effect, bioinformatic analysis suggests two possible mechanisms. First, the lncRNAs may act as sponges of myoblast proliferation inducers microRNAs (miRNAs) such as miR-206, miR-208, and miR-133 (binding energy MEF < -25.0 kcal). Secondly, lncRNA20194 had a strong predicted interaction towards the myod1 mRNA (ndG = -0.17) that, based on the positive correlation between the two genes, might promote its function. Our study represents the first characterization of lncRNAs in gilthead sea bream fast skeletal muscle and provides evidence regarding their involvement in muscle development.

GreeNC 2.0: a comprehensive database of plant long non-coding RNAs

The Green Non-Coding Database (GreeNC) is one of the reference databases for the study of plant long non-coding RNAs (lncRNAs). Here we present our most recent update where 16 species have been updated, while 78 species have been added, resulting in the annotation of more than 495 000 lncRNAs. Moreover, sequence clustering was applied providing information about sequence conservation and gene families. The current version of the database is available at: http://greenc.sequentiabiotech.com/wiki2/Main_Page.

Long non-coding RNA ASMTL-AS1 deteriorates the oncogenicity of osteosarcoma by decoying microRNA-342-3p and consequently raising ADAM9 expression

BACKGROUND

Till now, little is known regarding expression pattern and specific roles of lncRNA ASMTL antisense RNA 1 (ASMTL-AS1) in osteosarcoma (OS). Therefore, our current research measured the expression of ASMTL-AS1 in OS, unveiled the roles of ASMTL-AS1 in the modulation of malignant characteristics of OS, and identified the downstream mechanism.

METHODS

The regulatory actions of ASMTL-AS1 ablation in OS cells were explored utilizing loss-of-function experiments. Mechanistic studies were implemented utilizing bioinformatics analysis, luciferase reporter assay, RNA immunoprecipitation and rescue experiments.

RESULTS

ASMTL-AS1 expression in OS was elevated in both TCGA database and our own cohort. Interfering with ASMTL-AS1 restricted cell proliferation, migration and invasion while increasing cell apoptosis in vitro. Additionally, silencing ASMTL-AS1 blocked tumour growth in vivo. Mechanistically, ASMTL-AS1 could act as a competing endogenous RNA for microRNA-342-3p (miR-342-3p) and inhibit its activity in OS cells, consequently causing an increase in ADAM metallopeptidase domain 9 (ADAM9) levels. Furthermore, inhibiting miR-342-3p or upregulating ADAM9 abated silenced ASMTL-AS1-induced antitumour activity in OS cells.

CONCLUSION

ASMTL-AS1 aggravated OS progression by regulating the miR-342-3p/ADAM9 axis.

Mechanisms of Long Non-Coding RNAs in Biological Characteristics and Aerobic Glycolysis of Glioma

Glioma is the most common and aggressive tumor of the central nervous system. The uncontrolled proliferation, cellular heterogeneity, and diffusive capacity of glioma cells contribute to a very poor prognosis of patients with high grade glioma. Compared to normal cells, cancer cells exhibit a higher rate of glucose uptake, which is accompanied with the metabolic switch from oxidative phosphorylation to aerobic glycolysis. The metabolic reprogramming of cancer cell supports excessive cell proliferation, which are frequently mediated by the activation of oncogenes or the perturbations of tumor suppressor genes. Recently, a growing body of evidence has started to reveal that long noncoding RNAs (lncRNAs) are implicated in a wide spectrum of biological processes in glioma, including malignant phenotypes and aerobic glycolysis. However, the mechanisms of diverse lncRNAs in the initiation and progression of gliomas remain to be fully unveiled. In this review, we summarized the diverse roles of lncRNAs in shaping the biological features and aerobic glycolysis of glioma. The thorough understanding of lncRNAs in glioma biology provides opportunities for developing diagnostic biomarkers and novel therapeutic strategies targeting gliomas.

Genome-Wide Analysis of LncRNA in Bovine Mammary Epithelial Cell Injuries Induced by Escherichia Coli and Staphylococcus Aureus

Escherichia coli and Staphylococcus aureus are two common pathogenic microorganisms that cause mastitis in dairy cows. They can cause clinical mastitis and subclinical mastitis. In recent studies, lncRNAs have been found to play an important role in the immune responses triggered by microbial inducers. However, the actions of lncRNAs in bovine mastitis remain unclear. The purpose of this study was to investigate the effects of bovine mammary epithelial cell injuries induced by treatment with E. coli and S. aureus, and to explore the lncRNA profile on cell injuries. The lncRNA transcriptome analysis showed a total of 2597 lncRNAs. There were 2234 lncRNAs differentially expressed in the E. coli group and 2334 in the S. aureus group. Moreover, we found that the E. coli and S. aureus groups of maternal genes targeted signaling pathways with similar functions according to KEGG and GO analyses. Two lncRNA-miRNA-mRNA interaction networks were constructed in order to predict the potential molecular mechanisms of regulation in the cell injuries. We believe that this is the first report demonstrating the dysregulation of lncRNAs in cells upon E. coli and S. aureus infections, suggesting that they have the potential to become important diagnostic markers and to provide novel insights into controlling and preventing mastitis.

Advances in Computational Methodologies for Classification and Sub-Cellular Locality Prediction of Non-Coding RNAs

Apart from protein-coding Ribonucleic acids (RNAs), there exists a variety of non-coding RNAs (ncRNAs) which regulate complex cellular and molecular processes. High-throughput sequencing technologies and bioinformatics approaches have largely promoted the exploration of ncRNAs which revealed their crucial roles in gene regulation, miRNA binding, protein interactions, and splicing. Furthermore, ncRNAs are involved in the development of complicated diseases like cancer. Categorization of ncRNAs is essential to understand the mechanisms of diseases and to develop effective treatments. Sub-cellular localization information of ncRNAs demystifies diverse functionalities of ncRNAs. To date, several computational methodologies have been proposed to precisely identify the class as well as sub-cellular localization patterns of RNAs). This paper discusses different types of ncRNAs, reviews computational approaches proposed in the last 10 years to distinguish coding-RNA from ncRNA, to identify sub-types of ncRNAs such as piwi-associated RNA, micro RNA, long ncRNA, and circular RNA, and to determine sub-cellular localization of distinct ncRNAs and RNAs. Furthermore, it summarizes diverse ncRNA classification and sub-cellular localization determination datasets along with benchmark performance to aid the development and evaluation of novel computational methodologies. It identifies research gaps, heterogeneity, and challenges in the development of computational approaches for RNA sequence analysis. We consider that our expert analysis will assist Artificial Intelligence researchers with knowing state-of-the-art performance, model selection for various tasks on one platform, dominantly used sequence descriptors, neural architectures, and interpreting inter-species and intra-species performance deviation.