LINC02381 contributes to cell proliferation and hinders cell apoptosis in glioma by transcriptionally enhancing CBX5

T2DB: A Web Database for Long Non-Coding RNA Genes in Type II Diabetes

Type II diabetes (T2D) is a growing health problem worldwide due to increased levels of obesity and can lead to other life-threatening diseases, such as cardiovascular and kidney diseases. As the number of individuals diagnosed with T2D rises, there is an urgent need to understand the pathogenesis of the disease in order to prevent further harm to the body caused by elevated blood glucose levels. Recent advances in long non-coding RNA (lncRNA) research may provide insights into the pathogenesis of T2D. Although lncRNAs can be readily detected in RNA sequencing (RNA-seq) data, most published datasets of T2D patients compared to healthy donors focus only on protein-coding genes, leaving lncRNAs to be undiscovered and understudied. To address this knowledge gap, we performed a secondary analysis of published RNA-seq data of T2D patients and of patients with related health complications to systematically analyze the expression changes of lncRNA genes in relation to the protein-coding genes. Since immune cells play important roles in T2D, we conducted loss-of-function experiments to provide functional data on the T2D-related lncRNA USP30-AS1, using an in vitro model of pro-inflammatory macrophage activation. To facilitate lncRNA research in T2D, we developed a web application, T2DB, to provide a one-stop-shop for expression profiling of protein-coding and lncRNA genes in T2D patients compared to healthy donors or subjects without T2D.

Non-coding regions of nuclear-DNA-encoded mitochondrial genes and intergenic sequences are targeted by autoantibodies in breast cancer

Autoantibodies against mitochondrial-derived antigens play a key role in chronic tissue inflammation in autoimmune disorders and cancers. Here, we identify autoreactive nuclear genomic DNA (nDNA)-encoded mitochondrial gene products (GAPDH, PKM2, GSTP1, SPATA5, MFF, TSPOAP1, PHB2, COA4, and HAGH) recognized by breast cancer (BC) patients’ sera as nonself, supporting a direct relationship of mitochondrial autoimmunity to breast carcinogenesis. Autoreactivity of multiple nDNA-encoded mitochondrial gene products was mapped to protein-coding regions, 3’ untranslated regions (UTRs), as well as introns. In addition, autoantibodies in BC sera targeted intergenic sequences that may be parts of long non-coding RNA (lncRNA) genes, including LINC02381 and other putative lncRNA neighbors of the protein-coding genes ERCC4, CXCL13, SOX3, PCDH1, EDDM3B, and GRB2. Increasing evidence indicates that lncRNAs play a key role in carcinogenesis. Consistent with this, our findings suggest that lncRNAs, as well as mRNAs of nDNA-encoded mitochondrial genes, mechanistically contribute to BC progression. This work supports a new paradigm of breast carcinogenesis based on a globally dysfunctional genome with altered function of multiple mitochondrial and non-mitochondrial oncogenic pathways caused by the effects of autoreactivity-induced dysregulation of multiple genes and their products. This autoimmunity-based model of carcinogenesis will open novel avenues for BC treatment.

Inhibition of ox‐LDL‐induced endothelial cell injury by LINC02381 knockdown through the microRNA‐491‐5p/transcription factor 7 axis

Atherosclerosis (AS) is a complex multifactorial and chronic inflammatory vascular disease that contributes to the development of cardiovascular diseases. Abnormal cellular proliferation in human umbilical vein endothelial cells (HUVECs) is a crucial element in AS development. In this study, we investigated the potential role of the long noncoding RNA LINC02381/microRNA (miR)‐491‐5p/transcription factor 7 (TCF7) axis in regulating HUVEC injury in 30 participants suffering from AS and 30 healthy control participants. We established an in vitro model of AS in HUVECs using oxidized low‐density lipoprotein (ox‐LDL), and measured cellular mRNA and protein levels of LINC02381, miR‐491‐5p, and TCF7 in serum samples using reverse transcription‐quantitative polymerase chain reaction and Western blotting assays. We evaluated cell viability, apoptosis, and inflammation using Cell Counting Kit‐8, flow cytometry, and enzyme‐linked immunosorbent assays, respectively. Moreover, we analyzed apoptosis‐related protein expression using western blotting analysis and determined the association between miR‐491‐5p and LINC02381 or TCF7 using dual‐luciferase reporter assay, RNA pull‐down, and rescue experiments. We observed that LINC02381 was elevated, while miR‐491‐5p was downregulated in serum samples from participants with AS and in ox‐LDL‐treated HUVECs. LINC02381 knockdown was protective against HUVEC injury via miR‐491‐5p inhibition, which is its downstream target. Rescue experiments further demonstrated that miR‐491‐5p alleviated HUVEC injury by modulating TCF7. Thus, LINC02381 knockdown ameliorated HUVEC injury by regulating the miR‐491‐5p/TCF7 axis, which provides new insights into AS treatment strategies.

Porphyromonas gingivalis Outer Membrane Vesicles Promote Apoptosis via msRNA-Regulated DNA Methylation in Periodontitis

The outer membrane vesicles (OMVs) produced by Porphyromonas gingivalis contain a variety of bioactive molecules that may be involved in the progression of periodontitis. However, the participation of P. gingivalis OMVs in the development of periodontitis has not been elucidated. Here, we isolated P. gingivalis OMVs and confirmed their participation in periodontitis both in vivo and in vitro. Microcomputed tomography (micro-CT) and histological analysis showed that under stimulation with P. gingivalis OMVs, the alveolar bone of rats was significantly resorbed in vivo. We found that P. gingivalis OMVs were taken up by human periodontal ligament cells ([hPDLCs]) in vitro, which subsequently resulted in apoptosis and inflammatory cytokine release, which was accomplished by the microRNA-size small RNA (msRNA) sRNA45033 in the P. gingivalis OMVs. Through bioinformatics analysis and screening of target genes, chromobox 5 (CBX5) was identified as the downstream target of screened-out sRNA45033. Using a dual-luciferase reporter assay, overexpression, and knockdown methods, sRNA45033 was confirmed to target CBX5 to regulate hPDLC apoptosis. In addition, CUT&Tag (cleavage under targets and tagmentation) analysis confirmed the mechanism that CBX5 regulates apoptosis through the methylation of p53 DNA. Collectively, these findings indicate that the role of P. gingivalis OMVs is immunologically relevant and related to bacterial virulence during the development of periodontitis. IMPORTANCE P. gingivalis is a bacterium often associated with periodontitis. This study demonstrates that (i) sRNA45033 in P. gingivalis OMVs targets CBX5, (ii) CBX5 regulates the methylation of p53 DNA and its expression, which is associated with apoptosis, and (iii) a novel mechanism of interaction between hosts and pathogens is mediated by OMVs in the occurrence of periodontitis.

Machine learning for the micropeptide encoded by LINC02381 regulates ferroptosis through the glucose transporter SLC2A10 in glioblastoma

Glioblastoma (GBM) is the most common primary intracranial tumor in the central nervous system, and resistance to temozolomide is an important reason for the failure of GBM treatment. We screened out that Solute Carrier Family 2 Member 10 (SLC2A10) is significantly highly expressed in GBM with a poor prognosis, which is also enriched in the NF-E2 p45-related factor 2 (NRF2) signalling pathway. The NRF2 signalling pathway is an important defence mechanism against ferroptosis. SLC2A10 related LINC02381 is highly expressed in GBM, which is localized in the cytoplasm/exosomes, and LINC02381 encoded micropeptides are localized in the exosomes. The micropeptide encoded by LINC02381 may be a potential treatment strategy for GBM, but the underlying mechanism of its function is not precise yet. We put forward the hypothesis: “The micropeptide encoded by LINC02381 regulates ferroptosis through the glucose transporter SLC2A10 in GBM.” This study innovatively used machine learning for micropeptide to provide personalized diagnosis and treatment plans for precise treatment of GBM, thereby promoting the development of translational medicine. The study aimed to help find new disease diagnoses and prognostic biomarkers and provide a new strategy for experimental scientists to design the downstream validation experiments.

Identification of Autophagy-Related LncRNA to Predict the Prognosis of Colorectal Cancer

Objective: To establish a prediction model based on autophagy-related lncRNAs and investigate the functional enrichment of autophagy-related lncRNAs in colorectal cancer.

Methods: TCGA database was used to extract the transcriptome data and clinical features of colorectal cancer patients. HADb was used to obtain autophagy-related genes. Pearson correlation analysis was performed to identify autophagy-related lncRNAs. The autophagy-related lncRNAs with prognostic values were selected. Based on the selected lncRNAs, the risk score model and nomogram were constructed, respectively. Calibration curve, concordance index, and ROC curve were performed to evaluate the predictive efficacy of the prediction model. GSEA was performed to figure out the functional enrichment of autophagy-related lncRNAs.

Results: A total of 13413 lncRNAs and 938 autophagy-related genes were obtained. A total of 709 autophagy-related genes were identified in colon cancer tissues, and 11 autophagy-related lncRNAs (AL138756.1, LINC01063, CD27-AS1, LINC00957, EIF3J-DT, LINC02474, SNHG16, AC105219.1, AC068580.3, LINC02381, and LINC01011) were finally selected and set as prognosis-related lncRNAs. According to the risk score, patients were divided into the high-risk and low-risk groups, respectively. The survival K–M (Kaplan–Meier) curve showed the low-risk group exhibits better overall survival than the high-risk group. The AUCs under the ROC curves were 0.72, 0.814, and 0.83 at 1, 3, and 5 years, respectively. The C-index (concordance index) of the model was 0.814. The calibration curves at 1, 3, and 5 years showed the predicting values were consistent with the actual values. Functional enrichment analysis showed that autophagy-related lncRNAs were enriched in several pathways.

Conclusions: A total of 11 specific autophagy-related lncRNAs were identified to own prognostic value in colon cancer. The predicting model based on the lncRNAs and clinical features can effectively predict the OS. Furthermore, functional enrichment analysis showed that autophagy-related genes were enriched in various biological pathways.

Establishment and Analysis of a Prognostic Model of Autophagy-Related lncRNAs in ESCA

Esophageal cancer (ESCA) is a malignant tumor of the upper gastrointestinal tract, with a high mortality rate and poor prognosis. Long noncoding RNAs (lncRNAs) play a role in the malignant progression of tumors by regulating autophagy. This study is aimed at establishing a prognostic model of autophagy-related lncRNAs in ESCA and provide a theoretical basis to determine potential therapeutic targets for ESCA. The transcriptome expression profiles were downloaded from The Cancer Genome Atlas (TCGA). We identified autophagy-related mRNAs and lncRNAs in ESCA using differential expression analysis and the Human Autophagy Database (HADb). Four differentially expressed autophagy-related lncRNAs with a prognostic value were identified using Cox regression and survival analyses. Furthermore, the combination of the selected lncRNAs was able to predict the prognosis of patients with ESCA more accurately than any of the four lncRNAs individually. Finally, we constructed a coexpression network of autophagy-related mRNAs and lncRNAs. This study showed that autophagy-related lncRNAs play an important role in the occurrence and development of ESCA and could become a new target for the diagnosis and treatment of this disease.

LINC02381-ceRNA exerts its oncogenic effect through regulation of IGF1R signaling pathway in glioma

PURPOSE

LncRNAs play essential roles in the cellular and molecular biology of glioma. Some LncRNAs exert their role through sponging miRNAs and regulating multiple signaling pathways. LINC02381 is involved in several cancer types as either oncogene or tumor suppressor. Here, we intended to find the molecular mechanisms of the LINC02381 effect during the glioma progression in related cell lines.

METHODS AND RESULTS

RNA-seq data analysis indicated the oncogenic characteristics of LINC02381, and RT-qPCR results confirmed its upregulation compared to normal tissues. Besides its expression was relatively stronger in invasive glioma cell lines. Furthermore, in silico analysis revealed LINC02381 is concentrated in the cytoplasm and predicted its sponging effect against miR-128 and miR-150, which was verified through dual luciferase assay. When LINC02381 was overexpressed in 1321N1, U87, and A172 cell lines, IGF1R and TrkC receptors as well as their downstream pathways (PI3K and RAS/MAPK), were upregulated, detected by RT-qPCR, and verified by western analysis. Consistently, LINC02381 overexpression was followed by an increased proliferation rate of transfected glioma cell lines, detected by flow cytometry and MTT assay, and RT-qPCR. It also resulted in elevated EMT and stemness markers expression level, increased migration rate, and reduced apoptosis rate, detected by RT-qPCR, western analysis, scratch test, and Annexin/PI flow cytometry analysis, respectively.

CONCLUSION

The overall results indicated that LINC02381 exerts its oncogenic effect in glioma cells through sponging miR-128 and miR-150 to upregulate the IGF1R signaling pathway. Our results introduce LINC02381 and miR-128, and miR-150 as potential prognosis and therapy targets for the treatment of glioma.

Comprehensive Analysis of RNA-Seq in Endometriosis Reveals Competing Endogenous RNA Network Composed of circRNA, lncRNA and mRNA

Although long non coding RNAs (lncRNAs) and circular RNAs (circRNAs) play important roles in the pathogenesis of diseases, endometriosis related lncRNAs and circRNAs are still rarely reported. This study focused on the potential molecular mechanism of endometriosis related competitive endogenous RNA (ceRNA) composed of lncRNAs and circRNAs. We performed high-throughout sequencing of six normal endometria, six eutopic endometria and six ectopic endometria for the first time to describe and analyze the expression profile of lncRNA, circRNA and mRNA. Our results showed that 140 lncRNAs, 107 circRNAs and 1,206 mRNAs were differentially expressed in the ectopic group, compared with the normal and eutopic groups. We established an lncRNA/circRNA-mRNA co-expression network using pearson correlation test. Meanwhile, the results of Gene set enrichment analysis analysis showed that the 569 up-regulated differentially expressed mRNA (DEmRNA) were mainly related to the epithelial-mesenchymal transition, regulation of immune system process and immune effector process. Subsequently, we established a DElncRNA-miRNA and DEcircRNA-miRNA network using the starbase database, identified the common miRNAs and constructed DElncRNA/DEcircRNA-miRNA pairs. miRDB, Targetscan, miRwalk and circRNA/lncRNA-mRNA pairs jointly determined the miRNA-mRNA portion of the circRNA/lncRNA-miRNA-mRNA co-expression network. RT-qPCR results of 15 control samples and 25 ectopic samples confirmed that circGLIS2, circFN1, LINC02381, IGFL2-AS1, CD84, LYPD1 and FAM163A were significantly overexpressed in ectopic tissues. In conclusion, this is the first study to illustrate ceRNA composed of differentially expressed circRNA, lncRNA and mRNA in endometriosis. We also found that lncRNA and circRNA exerted a pivotal function on the pathogenesis of endometriosis, which can provide new insights for further exploring the pathogenesis of endometriosis and identifying new targets.