Identification and Functional Prediction of Long Non-Coding RNAs in Dilated Cardiomyopathy by Bioinformatics Analysis

Studying relative RNA localization From nucleus to the cytosol

The precise coordination of important biological processes, such as differentiation and development, is highly dependent on the regulation of expression of the genetic information. The flow of the genetic information is tightly regulated on multiple levels. Among them, RNA export to cytosol is an essential step for the production of proteins in eukaryotic cells. Hence, estimating the relative concentration of RNA molecules of a given transcript species in the nucleus and in the cytosol is of major significance as it contributes to the understanding of the dynamics of RNA trafficking between the nucleus and the cytosol. The most efficient way to estimate the levels of RNA species genome-wide is through RNA sequencing (RNAseq). While RNAseq can be performed separately in the nucleus and in the cytosol, because measured transcript levels are relative to the total volume of RNA in these compartments, and because this volume is usually unknown, the transcript levels in the nucleus and in the cytosol cannot be directly compared. Here we show theoretically that if, in addition to nuclear and cytosolic RNA-seq, whole cell RNA-seq is also performed, then accurate estimations of the localization of transcripts can be obtained. Based on this, we designed a method that estimates, first the fraction of the total RNA volume in the cytosol (nucleus), and then, this fraction for every transcript. We evaluate our methodology on simulated data and nuclear and cytosolic single cell data available. Finally, we use our method to investigate the cellular localization of transcripts using bulk RNAseq data from the ENCODE project.

Long non-coding RNA FGD5 antisense RNA 1 targets Baculovirus inhibitor 5 via microRNA-497-5p to alleviate calcific aortic valve disease

Calcific aortic valve disease (CAVD) is featured by thickening and calcification of the aortic valve. Osteoblast differentiation is a crucial step in valve calcification. Long non-coding RNAs (LncRNAs) participate in the osteogenic differentiation of mesenchymal cells. However, the character of lncRNA FGD5 antisense RNA 1 (FGD5-AS1) in CAVD is uncertain. After collection of human aortic valve tissue samples, detection of FGD5-AS1, microRNA (miR)-497-5p and Baculovirus inhibitor 5 (BIRC5) was conducted. Valve mesenchymal cells were isolated from CAVD patients and induced to differentiate to osteoblasts, and transfected with FGD5-AS1, miR-497-5p and BIRC5 plasmids. Detection of the alkaline phosphatase activity was after osteogenic induction of human aortic valve interstitial cells (hAVICs); Detection of the degree of calcium nodules and osteoblast differentiation markers (RUNX2 and OPN) was conducted. After establishment of a mouse model of CAVD, detection of the thickness of aortic valve leaflets, and the degree of calcification of the valve leaflets, and evaluation of echocardiographic parameters were implemented. Experimental data manifested in CAVD patients, lncRNAFGD5-AS1 and BIRC5 were reduced, but miR-497-5p was elevated; Enhancing lncRNA FGD5-AS1 or repressing miR-497-5p mitigated CAVD by restraining osteogenic differentiation; LncRNA FGD5-AS1 sponged miR-497-5p to target BIRC5; Repressive BIRC5 turned around the therapeutic action of elevated FGD5-AS1 or depressed miR-497-5p on hAVICs; Enhancive FGD5-AS1 in vivo was available to reduce ApoE-/- mouse CAVD induced via high cholesterol diet. All in all, lncRNAFGD5-AS1 targets BIRC5 via miR-497-5p to alleviate CAVD.

Mitochondria-related lncRNAs: predicting prognosis, tumor microenvironment and treatment response in lung adenocarcinoma

Lung cancer is the most common type of malignant tumor that affects people in China and even across the globe, as it exhibits the highest rates of morbidity and mortality. Lung adenocarcinoma (LUAD) is a type of lung cancer with a very high incidence. The purpose of this study was to identify potential biomarkers that could be used to forecast the prognosis and improve the existing therapy options for treating LUAD. Clinical and RNA sequencing data of LUAD patients were retrieved from the TCGA database, while the mitochondria-associated gene sets were acquired from the MITOMAP database. Thereafter, Pearson correlation analysis was carried out to screen mitochondria-associated lncRNAs. Furthermore, univariate Cox and Lasso regression analyses were used for the initial screening of the target lncRNAs for prognostic lncRNAs before they could be incorporated into a multivariate Cox Hazard ratio model. Then, the clinical data, concordance index, Kaplan-Meier (K-M) curves, and the clinically-relevant subjects that were approved by the Characteristic Curves (ROC) were employed for assessing the model's predictive value. Additionally, the differences in immune-related functions and biological pathway enrichment between high- and low-risk LUAD groups were examined. Nomograms were developed to anticipate the OS rates of the patients within 1-, 3-, and 5 years, and the differences in drug sensitivity and immunological checkpoints were compared. In this study, 2175 mitochondria-associated lncRNAs were screened. Univariate, multivariate, and Lasso Cox regression analyses were carried out to select 13 lncRNAs with an independent prognostic significance, and a prognostic model was developed. The OS analysis of the established prognostic prediction model revealed significant variations between the high- and low-risk patients. The AUC-ROC values after 1, 3, and 5 years were seen to be 0.746, 0.692, and 0.726, respectively. The results suggested that the prognostic model riskscore could be used as an independent prognostic factor that differed from the other clinical characteristics. After analyzing the findings of the study, it was noted that both the risk groups showed significant differences in their immune functioning, immunological checkpoint genes, and drug sensitivity. The prognosis of patients with LUAD could be accurately and independently predicted using a risk prediction model that included 13 mitochondria-associated lncRNAs.

A concise review on the role of MIR100HG in human disorders

MIR100HG is a long non-coding RNA (lncRNA) encoded by a locus on chr11:122,028,203-122,556,721. This gene can regulate cell proliferation, apoptosis, cell cycle transition and cell differentiation. MIR100HG was firstly identified through a transcriptome analysis and found to regulate differentiation of human neural stem cells. It is functionally related with a number of signalling pathways such as TGF-β, Wnt, Hippo and ERK/MAPK signalling pathways. Dysregulation of MIR100HG has been detected in a diversity of cancers in association with clinical outcomes. Moreover, it has a role in the pathophysiology of dilated cardiomyopathy, intervertebral disk degeneration and pulmonary fibrosis. The current study summarizes the role of these lncRNAs in human disorders.

Integrated bioinformatics analysis for identifying key genes and pathways in female and male patients with dilated cardiomyopathy

Dilated cardiomyopathy (DCM) is a common cause of heart failure, and males are more likely to suffer from DCM than females. This research aimed at exploring possible DCM-associated genes and their latent regulatory effects in female and male patients. WGCNA analysis found that in the yellow module, 341 and 367 key DEGs were identified in females and males, respectively. A total of 22 hub genes in females and 17 hub genes in males were identified from the PPI networks of the key DEGs based on Metascape database. And twelve and eight potential TFs of the key DEGs were also identified in females and males, respectively. Eight miRNAs of 15 key DEGs were screened in both females and males, which may be differentially expressed in females and males. Dual-luciferase reporter assay demonstrated that miR-21-5P could directly target the key gene MATN2. Furthermore, Sex differences in KEGG pathways were identified. Both KOBAS and GSEA analysis identified 19 significantly enriched pathways related to immune response in both females and males, and the TGF-β signaling pathway was exclusively identified in males. Network pharmacology analysis revealed that seven key DEGs were potential targets for the treatment of DCM, of which the OLR1 gene was only identified in males, the expression levels of the seven genes were verified by RT-PCR. The above results could offer a novel understanding of sex differences in key genes and pathways in DCM progression.

Establishment of a prognostic signature for lung adenocarcinoma using cuproptosis-related lncRNAs

OBJECTIVE

To establish a prognostic signature for lung adenocarcinoma (LUAD) based on cuproptosis-related long non-coding RNAs (lncRNAs), and to study the immune-related functions of LUAD.

METHODS

First, transcriptome data and clinical data related to LUAD were downloaded from the Cancer Genome Atlas (TCGA), and cuproptosis-related genes were analyzed to identify cuproptosis-related lncRNAs. Univariate COX analysis, least absolute shrinkage and selection operator (LASSO) analysis, and multivariate COX analysis were performed to analyze the cuproptosis-related lncRNAs, and a prognostic signature was established. Second, univariate COX analysis and multivariate COX analysis were performed for independent prognostic analyses. Receiver operating characteristic (ROC) curves, C index, survival curve, nomogram, and principal component analysis (PCA) were performed to evaluate the results of the independent prognostic analyses. Finally, gene enrichment analyses and immune-related function analyses were also carried out.

RESULTS

(1) A total of 1,297 cuproptosis-related lncRNAs were screened. (2) A LUAD prognostic signature containing 13 cuproptosis-related lncRNAs was constructed (NIFK-AS1, AC026355.2, SEPSECS-AS1, AL360270.1, AC010999.2, ABCA9-AS1, AC032011.1, AL162632.3, LINC02518, LINC0059, AL031600.2, AP000346.1, AC012409.4). (3) The area under the multi-indicator ROC curves at 1, 3, and 5 years were AUC1 = 0.742, AUC2 = 0.708, and AUC3 = 0.762, respectively. The risk score of the prognostic signature could be used as an independent prognostic factor that was independent of other clinical indicators. (4) The results of gene enrichment analyses showed that 13 biomarkers were primarily related to amoebiasis, the wnt signaling pathway, hematopoietic cell lineage. The ssGSEA volcano map showed significant differences between high- and low-risk groups in immune-related functions, such as human leukocyte antigen (HLA), Type_II_IFN_Reponse, MHC_class_I, and Parainflammation (P < 0.001).

CONCLUSIONS

Thirteen cuproptosis-related lncRNAs may be clinical molecular biomarkers for the prognosis of LUAD.

Maternal Serum tRNA-Derived Fragments (tRFs) as Potential Candidates for Diagnosis of Fetal Congenital Heart Disease

BACKGROUND

Congenital heart disease (CHD) is one of the most predominant birth defects that causes infant death worldwide. The timely and successful surgical treatment of CHD on newborns after delivery requires accurate detection and reliable diagnosis during pregnancy. However, there are no biomarkers that can serve as an early diagnostic factor for CHD patients. tRNA-derived fragments (tRFs) have been reported to play an important role in the occurrence and progression of numerous diseases, but their roles in CHD remains unknown.

METHODS

High-throughput sequencing was performed on the peripheral blood of pregnant women with an abnormal fetal heart and a normal fetal heart, and 728 differentially expressed tRFs/tiRNAs were identified, among which the top 18 tRFs/tiRNAs were selected as predictive biomarkers of CHD. Then, a quantitative reverse transcriptase polymerase chain reaction verified the expression of tRFs/tiRNAs in more clinical samples, and the correlation between tRFs/tiRNAs abnormalities and CHD was analyzed.

RESULTS

tRF-58:74-Gly-GCC-1 and tiRNA-1:35-Leu-CAG-1-M2 may be promising biomarkers. Through further bioinformatics analysis, we predicted that TRF-58:744-GLy-GCC-1 could induce CHD by influencing biological metabolic processes.

CONCLUSIONS

Our results provide a theoretical basis for the abnormally expressed tRF-58:74-Gly-GCC-1 in maternal peripheral blood as a new potential biomarker for the accurate diagnosis of CHD during pregnancy.

Identification of crucial lncRNAs and mRNAs in liver regeneration after portal vein ligation through weighted gene correlation network analysis

BACKGROUND

Portal vein ligation (PVL)-induced liver hypertrophy increases future liver remnant (FLR) volume and improves resectability of large hepatic carcinoma. However, the molecular mechanism by which PVL facilitates liver hypertrophy remains poorly understood.

METHODS

To gain mechanistic insight, we established a rat PVL model and carried out a comprehensive transcriptome analyses of hepatic lobes preserving portal blood supply at 0, 1, 7, and 14-day after PVL. The differentially expressed (DE) long-non coding RNAs (lncRNAs) and mRNAs were applied to conduct weighted gene co-expression network analysis (WGCNA). LncRNA-mRNA co-expression network was constructed in the most significant module. The modules and genes associated with PVL-induced liver hypertrophy were assessed through quantitative real-time PCR.

RESULTS

A total of 4213 DElncRNAs and 6809 DEmRNAs probesets, identified by transcriptome analyses, were used to carry out WGCNA, by which 10 modules were generated. The largest and most significant module (marked in black_M6) was selected for further analysis. Gene Ontology (GO) analysis of the module exhibited several key biological processes associated with liver regeneration such as complement activation, IL-6 production, Wnt signaling pathway, autophagy, etc. Sixteen mRNAs (Notch1, Grb2, IL-4, Cops4, Stxbp1, Khdrbs2, Hdac2, Gnb3, Gng10, Tlr2, Sod1, Gosr2, Rbbp5, Map3k3, Golga2, and Rev3l) and ten lncRNAs (BC092620, AB190508, EF076772, BC088302, BC158675, BC100646, BC089934, L20987, BC091187, and M23890) were identified as hub genes in accordance with gene significance value, module membership value, protein-protein interaction (PPI) and lncRNA-mRNA co-expression network. Furthermore, the overexpression of 3 mRNAs (Notch1, Grb2 and IL-4) and 4 lncRNAs (BC089934, EF076772, BC092620, and BC088302) was validated in hypertrophic liver lobe tissues from PVL rats and patients undergoing hepatectomy after portal vein embolization (PVE).

CONCLUSIONS

Microarray and WGCNA analysis revealed that the 3 mRNAs (Notch1, Grb2 and IL-4) and the 4 lncRNAs (BC089934, EF076772, BC092620 and BC088302) may be promising targets for accelerating liver regeneration before extensive hepatectomy.

Identification of Immune-Related lncRNAs for Predicting Prognosis and Immune Landscape Characteristics of Uveal Melanoma

Immune-related genes and long noncoding RNAs (lncRNAs) have a significant impact on the prognostic value and immunotherapeutic response of uveal melanoma (UM). Therefore, we tried to develop a prognostic model on the basis of irlncRNAs for predicting prognosis and response on immunotherapy of UM patients. We identified 1,664 immune-related genes and 2,216 immune-related lncRNAs (irlncRNAs) and structured a prognostic model with 3 prognostic irlncRNAs by co-expression analysis, univariable Cox, LASSO, and multivariate Cox regression analyses. The Kaplan–Meier analysis indicated that patients in the high-risk group had a shorter survival time than patients in the low-risk group. The ROC curves demonstrated the high sensitivity and specificity of the signature for survival prediction, and the one-, three-, and five-year AUC values, respectively, were 0.974, 0.929, and 0.941 in the entire set. Cox regression analysis, C-index, DCA, PCA analysis, and nomogram were also applied to assess the validity and accuracy of the risk model. The GO and KEGG enrichment analyses indicated that this signature is significantly related to immune-related pathways and molecules. Finally, we investigated the immunological characteristics and immunotherapy of the model and identified various novel potential compounds in the model for UM. In summary, we constructed a new model on the basis of irlncRNAs that can accurately predict prognosis and response on immunotherapy of UM patients, which may provide valuable clinical applications in antitumor immunotherapy.

Construction of Immune-Related ceRNA Network in Dilated Cardiomyopathy: Based on Sex Differences

Background: Immune targeted therapy has become an attractive therapeutic approach for patients with dilated cardiomyopathy (DCM) recently. Genetic predisposition and gender play a critical role in immune-related responses of DCM. This study aimed to perform a bioinformatics analysis of molecular differences between male and female samples and identify immune-related ceRNA network in DCM.

Methods: The gene expression microarray and clinical features dataset of GSE19303 was downloaded from the GEO. The raw data were preprocessed, followed by identification of differentially expressed genes (DEGs) between male and female DCM samples. Crucial functions and pathway enrichment analysis of DEGs were investigated through GO analysis and KEGG pathway analysis, respectively. A lncRNA–miRNA–mRNA network was constructed and a central module was extracted from the ceRNA network.

Results: Compared with the female group, the male group benefits more from IA/IgG immunotherapy. Male patients of DCM had a significant positive correlation with the abundance of inflammatory cells (B cells, memory B cells, CD8⁺ Tem cells, and NK cells). Sex difference DEGs had a widespread impact on the signaling transduction, transcriptional regulation, and metabolism in DCM. Subsequently, we constructed an immune-related ceRNA network based on sex differences in DCM, including five lncRNAs, six miRNAs, and 29 mRNAs. Furthermore, we extracted a central module from the ceRNA network, including two lncRNAs (XIST and LINC00632), three miRNAs (miR-1-3p, miR-17-5p, and miR-22-3p), and six mRNAs (CBL, CXCL12, ESR1, IGF1R, IL6ST, and STC1). Among these DEGs, CBL, CXCL12, and IL6ST expression was considered to be associated with inflammatory cell infiltration in DCM.

Conclusions: The identified ceRNA network and their enriched pathways may provide genetic insights into the phenotypic diversity of female and male patients with DCM and may provide a basis for development of sex-related individualization of immunotherapy.

Oxidative Stress-Related lncRNAs Are Potential Biomarkers for Predicting Prognosis and Immune Responses in Patients With LUAD

Lung adenocarcinoma is increasingly harmful to society and individuals as cancer with an inferior prognosis and insensitive to chemotherapy. Previous studies have demonstrated that oxidative stress and lncRNAs play a vital role in many biological processes. Therefore, we explored the role of lncRNAs associated with oxidative stress in the prognosis and survival of LUAD patients. We examined the expression profiles of lncRNAs and oxidative stress genes in this study. A prognosis prediction model and a nomogram were built based on oxidative stress-related lncRNAs. Functional and drug sensitivity analyses were also performed depending on oxidative stress-related lncRNA signature. Moreover, we investigated the relationship between immune response and immunotherapy. The results showed that a risk scoring model based on 16 critical oxidative stress lncRNAs was able to distinguish the clinical status of LUAD and better predict the prognosis and survival. Additionally, the model demonstrated a close correlation with the tumor immune system, and these key lncRNAs also revealed the relationship between LUAD and chemotherapeutic drug sensitivity. Our work aims to provide new perspectives and new ideas for the treatment and management of LUAD.

Diagnostic significance of serum FGD5-AS1 and its predictive value for the development of cardiovascular diseases in patients with type 2 diabetes

BACKGROUND

As a result of the continuous rise in the incidence of type 2 diabetes mellitus (T2DM), related cardiovascular diseases (CVDs) have been a main healthy burden worldwide. This study aimed to investigate the potential role of FGD5-AS1 as a biomarker for the diagnosis of T2DM and predicting cardiovascular complications in T2DM.

METHODS

Three hundred subjects were recruited in this study, including 100 T2DM patients without CVDs, 100 T2DM patients with CVDs as well as 100 healthy subjects. Plasma FGD5-AS1 level was quantified using RT-qPCR assay. The correlation of FGD5-AS1 level with other key variables was assessed using Pearson correlation analysis. ROC curve analysis was performed to evaluate the diagnostic value of FGD5-AS1 for T2DM and related CVDs. The effect of FGD5-AS1 on AC16 and HA-VSMCs was determined.

RESULTS

FGD5-AS1 level showed a stepwise decrease in individuals with T2DM and CVDs compared to healthy persons. FGD5-AS1 was associated with BMI, systolic blood pressure, diastolic blood pressure, fasting glucose, 2-h postprandial blood glucose, HbA1c, triglycerides, usCRP, and HDL-cholesterol. The ROC analysis indicated FGD5-AS1 had a significant overall predictive ability to diagnose T2DM, T2DM with CVDs, and the combination of both. FGD5-AS1 increases the growth but alleviates apoptosis and fibrosis of high glucose-induced AC16 cells. FGD5-AS1 attenuate the growth and calcification but induced apoptosis of high glucose-treated HA-VSMC cells.

CONCLUSIONS

These results suggest that FGD5-AS1 are associated with T2DM and measuring FGD5-AS1 could potentially contribute to T2DM screening and prediction for risk of cardiovascular complication.