An in-silico method leads to recognition of hub genes and crucial pathways in survival of patients with breast cancer

Investigating the potential of Juglans regia phytoconstituents for the treatment of cervical cancer utilizing network biology and molecular docking approach

The fourth most frequent type of cancer in women and the leading cause of mortality for females worldwide is cervical cancer. Traditionally, medicinal plants have been utilized to treat various illnesses and ailments. The molecular docking method is used in the current study to look into the phytoconstituents of Juglans regia's possible anticancer effects on cervical cancer target proteins. This work uses the microarray dataset analysis of GSE63678 from the NCBI Gene Expression Omnibus database to find differentially expressed genes. Furthermore, protein-protein interactions of differentially expressed genes were constructed using network biology techniques. The top five hub genes (IGF1, FGF2, ESR1, MYL9, and MYH11) are then determined by computing topological parameters with Cytohubba. In addition, molecular docking research was performed on Juglans regia phytocompounds that were extracted from the IMPPAT database versus hub genes that had been identified. Utilizing molecular dynamics, simulation confirmed that prioritized docked complexes with low binding energies were stable.

Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer

Background and Objectives: Breast cancer (BC) is one of the major causes of cancer-related death in women globally. Proper identification of BC-causing hub genes (HubGs) for prognosis, diagnosis, and therapies at an earlier stage may reduce such death rates. However, most of the previous studies detected HubGs through non-robust statistical approaches that are sensitive to outlying observations. Therefore, the main objectives of this study were to explore BC-causing potential HubGs from robustness viewpoints, highlighting their early prognostic, diagnostic, and therapeutic performance. Materials and Methods: Integrated robust statistics and bioinformatics methods and databases were used to obtain the required results. Results: We robustly identified 46 common differentially expressed genes (cDEGs) between BC and control samples from three microarrays (GSE26910, GSE42568, and GSE65194) and one scRNA-seq (GSE235168) dataset. Then, we identified eight cDEGs (COL11A1, COL10A1, CD36, ACACB, CD24, PLK1, UBE2C, and PDK4) as the BC-causing HubGs by the protein-protein interaction (PPI) network analysis of cDEGs. The performance of BC and survival probability prediction models with the expressions of HubGs from two independent datasets (GSE45827 and GSE54002) and the TCGA (The Cancer Genome Atlas) database showed that our proposed HubGs might be considered as diagnostic and prognostic biomarkers, where two genes, COL11A1 and CD24, exhibit better performance. The expression analysis of HubGs by Box plots with the TCGA database in different stages of BC progression indicated their early diagnosis and prognosis ability. The HubGs set enrichment analysis with GO (Gene ontology) terms and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways disclosed some BC-causing biological processes, molecular functions, and pathways. Finally, we suggested the top-ranked six drug molecules (Suramin, Rifaximin, Telmisartan, Tukysa Tucatinib, Lynparza Olaparib, and TG.02) for the treatment of BC by molecular docking analysis with the proposed HubGs-mediated receptors. Molecular docking analysis results also showed that these drug molecules may inhibit cancer-related post-translational modification (PTM) sites (Succinylation, phosphorylation, and ubiquitination) of hub proteins. Conclusions: This study's findings might be valuable resources for diagnosis, prognosis, and therapies at an earlier stage of BC.

Integrated analysis of inflammatory mRNAs, miRNAs, and lncRNAs elucidates the molecular interactome behind bovine mastitis

Mastitis is known as intramammary inflammation, which has a multifactorial complex phenotype. However, the underlying molecular pathogenesis of mastitis remains poorly understood. In this study, we utilized a combination of RNA-seq and miRNA-seq techniques, along with computational systems biology approaches, to gain a deeper understanding of the molecular interactome involved in mastitis. We retrieved and processed one hundred transcriptomic libraries, consisting of 50 RNA-seq and 50 matched miRNA-seq data, obtained from milk-isolated monocytes of Holstein-Friesian cows, both infected with Streptococcus uberis and non-infected controls. Using the weighted gene co-expression network analysis (WGCNA) approach, we constructed co-expressed RNA-seq-based and miRNA-seq-based modules separately. Module-trait relationship analysis was then performed on the RNA-seq-based modules to identify highly-correlated modules associated with clinical traits of mastitis. Functional enrichment analysis was conducted to understand the functional behavior of these modules. Additionally, we assigned the RNA-seq-based modules to the miRNA-seq-based modules and constructed an integrated regulatory network based on the modules of interest. To enhance the reliability of our findings, we conducted further analyses, including hub RNA detection, protein-protein interaction (PPI) network construction, screening of hub-hub RNAs, and target prediction analysis on the detected modules. We identified a total of 17 RNA-seq-based modules and 3 miRNA-seq-based modules. Among the significant highly-correlated RNA-seq-based modules, six modules showed strong associations with clinical characteristics of mastitis. Functional enrichment analysis revealed that the turquoise module was directly related to inflammation persistence and mastitis development. Furthermore, module assignment analysis demonstrated that the blue miRNA-seq-based module post-transcriptionally regulates the turquoise RNA-seq-based module. We also identified a set of different RNAs, including hub-hub genes, hub-hub TFs (transcription factors), hub-hub lncRNAs (long non-coding RNAs), and hub miRNAs within the modules of interest, indicating their central role in the molecular interactome underlying the pathogenic mechanisms of S. uberis infection. This study provides a comprehensive insight into the molecular crosstalk between immunoregulatory mRNAs, miRNAs, and lncRNAs during S. uberis infection. These findings offer valuable directions for the development of molecular diagnosis and biological therapies for mastitis.

TGM2, HMGA2, FXYD3, and LGALS4 genes as biomarkers in acquired oxaliplatin resistance of human colorectal cancer: A systems biology approach

Acquired resistance to oxaliplatin is considered as the primary reason for failure in colorectal cancer (CRC) therapy. Identifying the underlying resistance mechanisms may improve CRC treatment. The present study aims to identify the key genes involved in acquired oxaliplatin-resistant in CRC by confirming the oxaliplatin resistance index (OX-RI). To this aim, two public microarray datasets regarding oxaliplatin-resistant CRC cells with different OX-RI, GSE42387, and GSE76092 were downloaded from GEO database to identify differentially expressed genes (DEGs). The results indicated that the OX-RI affects the gene expression pattern significantly. Then, 54 common DEGs in both datasets including 18 up- and 36 down-regulated genes were identified. Protein-protein interaction (PPI) analysis revealed 13 up- (MAGEA6, TGM2, MAGEA4, SCHIP1, ECI2, CD33, AKAP12, MAGEA12, CALD1, WFDC2, VSNL1, HMGA2, and MAGEA2B) and 12 down-regulated (PDZK1IP1, FXYD3, ALDH2, CEACAM6, QPRT, GRB10, TM4SF4, LGALS4, ALDH3A1, USH1C, KCNE3, and CA12) hub genes. In the next step, two novel up-regulated hub genes including ECI2 and SCHIP1 were identified to be related to oxaliplatin resistance. Functional enrichment and pathway analysis indicated that metabolic pathways, proliferation, and epithelial-mesenchymal transition may play dominant roles in CRC progression and oxaliplatin resistance. In the next procedure, two in vitro oxaliplatin-resistant sub-lines including HCT116/OX-R4.3 and HCT116/OX-R10 cells with OX-IR 3.93 and 10.06 were established, respectively. The results indicated the up-regulation of TGM2 and HMGA2 in HCT116/OX-R10 cells with high OX-RI and down-regulation of FXYD3, LGALS4, and ECI2 in both cell types. Based on the results, TGM2, HMGA2, FXYD3, and LGALS4 genes are related to oxaliplatin-resistant CRC and may serve as novel therapeutic targets.

Expression analysis of Rho GTPase-related lncRNAs in breast cancer

The Rho GTPases have prominent roles in cell cycle transition and cell migration. Some members of this family have been found to be mutated in cancers. Moreover, alterations in expression levels and/or activity of these proteins have been reported in many types of cancers. Thus, Rho GTPases are involved in the carcinogenesis. Rho GTPases regulate growth, motility, invasiveness and metastatic ability of breast cancer cells. Long non-coding RNAs (lncRNAs) have been revealed to exert significant effect in the regulation of these proteins via direct routes or through sequestering microRNAs that inhibit Rho GTPases. We aimed to assess expression levels of four Rho GTPase-related lncRNAs, namely NORAD, RAD51-AS1, NRAV and DANCR in breast cancer samples versus non-cancerous specimens from the same individuals. Expression levels of NORAD were shown to be elevated in tumoral tissues compared with non-tumoral tissues (Expression ratio (95% CI)= 5.85 (3.16-10.83), Standard error of mean (SEM)= 0.44, P value< 0.0001). NRAV expression was also higher in tumoral tissues compared with control tissues (Expression ratio=2.85 (1.52-5.35), SEM= 0.45, P value= 0.0013). Similar to these lncRNAs, RHOA was demonstrated to be up-regulated in malignant tissues (Expression ratio=6.58 (3.17-13.63), SEM= 0.52, P value< 0.0001). Although expression ratio values showed up-regulation of RAD51-AS1 and DANCR in cancerous tissues (Expression ratio (95% CI)= 2.2 (1.05-4.6) and 1.35 (0.72-2.53), respectively), P values did not reach significance level (P values=0.0706 and 0.3746, respectively). There were significant associations between expression level of NRAV gene in tumor tissues and a number of parameters including age, histological tumor grade and tubule formation. Taken together, the current study shows dysregulation of a number of RHOA-related lncRNAs in breast cancer in association with abnormal up-regulation of this member of Rho GTPase family and suggests conduction of additional functional studies to unravel their mode of participation in the breast carcinogenesis.

Phytocompounds From Edible Oil Seeds Target Hub Genes To Control Breast Cancer

Breast cancer is one of the most commonly diagnosed cancers in woman which accounts for more than 1 in 10 new cancers in the entire world. The recently found four new potential hub genes that show a strong expression in breast cancer are CCNA2, CCNB1, MAD2L1, and RAD51. Nowadays, food habits and lifestyle of an individual are one of the factors for causing cancers. Consumption of seeds on a regular basis is the key factor for leading a good health. Sesame seeds and Sunflower seeds are few examples of cancer fighting seeds. Sesame (Sesamum indicum) is one of the earliest oil seed plant with various phytocompounds present which include lignans, tocopherols, phenolics, polyunsaturated fatty acids, and phytosterols. Sunflower (Helianthus annuus L.) is primarily harvested as an oil seed plant with various phytocompounds present which include flavonoids, phenolic acids, tocopherols, and vitamin B3. These are the few seeds that help women to prevent and also to fight against Breast cancer with its potential anti-cancer activity. The main objective of the current study is to identify the potential phytocompounds present in the cancer fighting seeds using molecular docking and dynamic simulation approach which can further help pharmaceuticals industries in producing targeted drugs against breast cancer hub genes as well as food industries in producing products combining the potential phytocompounds present in the seeds.

Comparative transcriptomic analysis of long noncoding RNAs in Leishmania-infected human macrophages

It is well established that infection with Leishmania alters the host cell's transcriptome. Since mammalian cells have multiple mechanisms to control gene expression, different molecules, such as noncoding RNAs, can be involved in this process. MicroRNAs have been extensively studied upon Leishmania infection, but whether long noncoding RNAs (lncRNAs) are also altered in macrophages is still unexplored. We performed RNA-seq from THP-1-derived macrophages infected with Leishmania amazonensis (La), L. braziliensis (Lb), and L. infantum (Li), investigating a previously unappreciated fraction of macrophage transcriptome. We found that more than 24% of the total annotated transcripts and 30% of differentially expressed (DE) RNAs in Leishmania-infected macrophage correspond to lncRNAs. LncRNAs and protein coding RNAs with altered expression are similar among macrophages infected with the Leishmania species. Still, some species-specific alterations could occur due to distinct pathophysiology in which Li infection led to a more significant number of exclusively DE RNAs. The most represented classes among DE lncRNAs were intergenic and antisense lncRNAs. We also found enrichment for immune response-related pathways in the DE protein coding RNAs, as well as putative targets of the lncRNAs. We performed a coexpression analysis to explore potential cis regulation of coding and antisense noncoding transcripts. We identified that antisense lncRNAs are similarly regulated as its neighbor protein coding genes, such as the BAALC/BAALC-AS1, BAALC/BAALC-AS2, HIF1A/HIF1A-AS1, HIF1A/HIF1A-AS3 and IRF1/IRF1-AS1 pairs, which can occur as a species-specific modulation. These findings are a novelty in the field because, to date, no study has focused on analyzing lncRNAs in Leishmania-infected macrophage. Our results suggest that lncRNAs may account for a novel mechanism by which Leishmania can control macrophage function. Further research must validate putative lncRNA targets and provide additional prospects in lncRNA function during Leishmania infection.

Integrated bioinformatic analysis to understand the association between phthalate exposure and breast cancer progression

Phthalates have been extensively used as plasticizers while manufacturing plastic-based consumer products. Estradiol mimicking properties and association studies suggest phthalates may contribute to breast cancer (BC). We performed an in-silico analysis and functional studies to understand the association between phthalate exposure and BC progression. Search for phthalate-responsive genes using the comparative toxicogenomics database identified 20 genes as commonly altered in response to multiple phthalates exposure. Of the 20 genes, 12 were significantly differentially expressed between normal and BC samples. In BC samples, 9 out of 20 genes showed a negative correlation between promoter methylation and its expression. AHR, BAX, BCL2, CAT, ESR2, IL6, and PTGS2 expression differed significantly between metastatic and non-metastatic BC samples. Gene set enrichment analysis identified metabolism, ATP-binding cassette transporters, insulin signaling, and type II diabetes as highly enriched pathways. The diagnostic assessment based on 20 genes expression suggested a sensitivity and a specificity >0.91. The aberrantly expressed phthalate interactive gene influenced the overall survival of BC patients. Drug-gene interaction analysis identified 14 genes and 523 candidate drugs, including 19 BC treatment-approved drugs. Di(2-ethylhexyl) phthlate (DEHP) exposure increased the growth, proliferation, and migration of MCF-7 and MDA-MB-231 cells in-vitro. DEHP exposure induced morphological changes, actin cytoskeletal remodeling, increased ROS content, reduced basal level lipid peroxidation, and induced epithelial to mesenchymal transition (EMT). The present approach can help to explore the potentially damaging effects of environmental agents on cancer risk and understand the underlined pathways and molecular mechanisms.

Integrative ontology and pathway-based approach identifies distinct molecular signatures in transcriptomes of esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) remains a serious concern globally due to many factors that including late diagnosis, lack of an ideal biomarker for diagnosis and prognosis, and high rate of mortality. In this study, we aimed to identify the essential dysregulated genes and molecular signatures associated with the progression and development of ESCC. The dataset with 15 ESCCs and the 15 adjacent normal tissue samples from the surrounding histopathologically tumor-free mucosa was selected. We applied bioinformatics pipelines including various topological parameters from MCODE, CytoNCA, and cytoHubba to prioritize the most significantly associated DEGs with ESCC. We performed functional enrichment annotation for the identified DEGs using DAVID and MetaCore™ GeneGo platforms. Furthermore, we validated the essential core genes in TCGA and GTEx datasets between the normal mucosa and ESCC for their expression levels. These DEGs were primarily enriched in positive regulation of transferase activity, negative regulation of organelle organization, cell cycle mitosis/S-phase transition, spindle organization/assembly, development, and regulation of angiogenesis. Subsequently, the DEGs were associated with the pathways such as oocyte meiosis, cell cycle, and DNA replication. Our study identified the eight-core genes (AURKA, AURKB, MCM2, CDC20, TPX2, PLK1, FOXM1, and MCM7) that are highly expressed among the ESCC, and TCGA dataset. The multigene comparison and principal component analysis resulted in elevated signals for the AURKA, MCM2, CDC20, TPX2, PLK1, and FOXM1. Overall, our study reported GO profiles and molecular signatures that might help researchers to grasp the pathological mechanisms underlying ESCC development and eventually provide novel therapeutic and diagnostic strategies.

Phytocompounds of Onion Target Heat Shock Proteins (HSP70s) to Control Breast Cancer Malignancy

Globally, breast cancer is one of the leading invasive cancers in women. Moreover, the use of chemotherapeutic drugs for treating cancer produces toxic side effects and has even led to drug resistance. This research paper focuses on targeting three heat shock proteins belonging to 70 kDa subfamily (HSP70s), predominantly, Mortalin, Binding Immunoglobulin Protein (BiP), and Stress Inducible HSP70 (Stress Inducible Heat Shock Protein 70) involved in breast cancer malignancy using different phytocompounds of onion. Phytocompounds of onion (ligands) obtained from different literature sources and the conventional drug, Tamoxifen (standard ligand), used for treating breast cancer are docked against three HSP70s (target proteins) through molecular docking. Molecular docking helps to determine protein-ligand interactions with minimum binding affinity. A comparative analysis revealed that fourteen phytocompounds of onion have lesser binding affinity and formed more stable complexes with the target proteins compared to that of the conventional drug. This evidence can be used and confirmed further through in vitro (cell culture) and in vivo (animal models) studies, and then, these phytocompounds can be modulated efficiently as potential therapeutics for treating breast cancer with less or nearly no side effects. In Silico work represented here targets three heat shock proteins belonging to 70 kDa subfamily (HSP70s)-Mortalin, Binding Immunoglobulin Protein (BiP), and Stress Inducible HSP70 involved in breast cancer malignancy using different phytocompounds of onion to identify potential phytocompounds that can treat breast cancer with nearly no side effects.

Frankincense myrrh attenuates hepatocellular carcinoma by regulating tumor blood vessel development through multiple epidermal growth factor receptor-mediated signaling pathways

BACKGROUND

In traditional Chinese medicine (TCM), frankincense and myrrh are the main components of the antitumor drug Xihuang Pill. These compounds show anticancer activity in other biological systems. However, whether frankincense and/or myrrh can inhibit the occurrence of hepatocellular carcinoma (HCC) is unknown, and the potential molecular mechanism(s) has not yet been determined.

AIM

To predict and determine latent anti-HCC therapeutic targets and molecular mechanisms of frankincense and myrrh in vivo.

METHODS

In the present study, which was based on the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (http://tcmspw.com/tcmsp.php), Universal Protein database (http://www.uniprot.org), GeneCards: The Human Gene Database (http://www.genecards.org/) and Comparative Toxicogenomics Database (http://www.ctdbase.org/), the efficacy of and mechanism by which frankincense and myrrh act as anti-HCC compounds were predicted. The core prediction targets were screened by molecular docking. In vivo, SMMC-7721 human liver cancer cells were transplanted as xenografts into nude mice to establish a subcutaneous tumor model, and two doses of frankincense plus myrrh or one dose of an EGFR inhibitor was administered to these mice continuously for 14 d. The tumors were collected and evaluated: the tumor volume and growth rate were gauged to evaluate tumor growth; hematoxylin-eosin staining was performed to estimate histopathological changes; immunofluorescence (IF) was performed to detect the expression of CD31, α-SMA and collagen IV; transmission electron microscopy (TEM) was conducted to observe the morphological structure of vascular cells; enzyme-linked immunosorbent assay (ELISA) was performed to measure the levels of secreted HIF-1α and TNF-α; reverse transcription-polymerase chain reaction (RT-qPCR) was performed to measure the mRNA expression of HIF-1α, TNF-α, VEGF and MMP-9; and Western blot (WB) was performed to determine the levels of proteins expressed in the EGFR-mediated PI3K/Akt and MAPK signaling pathways.

RESULTS

The results of the network pharmacology analysis showed that there were 35 active components in the frankincense and myrrh extracts targeting 151 key targets. The molecular docking analysis showed that both boswellic acid and stigmasterol showed strong affinity for the targets, with the greatest affinity for EGFR. Frankincense and myrrh treatment may play a role in the treatment of HCC by regulating hypoxia responses and vascular system-related pathological processes, such as cytokine-receptor binding, and pathways, such as those involving serine/threonine protein kinase complexes and MAPK, HIF-1 and ErbB signaling cascades. The animal experiment results were verified. First, we found that, through frankincense and/or myrrh treatment, the volume of subcutaneously transplanted HCC tumors was significantly reduced, and the pathological morphology was attenuated. Then, IF and TEM showed that frankincense and/or myrrh treatment reduced CD31 and collagen IV expression, increased the coverage of perivascular cells, tightened the connection between cells, and improved the shape of blood vessels. In addition, ELISA, RT-qPCR and WB analyses showed that frankincense and/or myrrh treatment inhibited the levels of hypoxia-inducible factors, inflammatory factors and angiogenesis-related factors, namely, HIF-1α, TNF-α, VEGF and MMP-9. Furthermore, mechanistic experiments illustrated that the effect of frankincense plus myrrh treatment was similar to that of an EGFR inhibitor with regard to controlling EGFR activation, thereby inhibiting the phosphorylation activity of its downstream targets: the PI3K/Akt and MAPK (ERK, p38 and JNK) pathways.

CONCLUSION

In summary, frankincense and myrrh treatment targets tumor blood vessels to exert anti-HCC effects via EGFR-activated PI3K/Akt and MAPK signaling pathways, highlighting the potential of this dual TCM compound as an anti-HCC candidate.

Long non-coding RNA-associated competing endogenous RNA axes in the olfactory epithelium in schizophrenia: a bioinformatics analysis

The etiology of schizophrenia (SCZ), as a serious mental illness, is unknown. The significance of genetics in SCZ pathophysiology is yet unknown, and newly identified mechanisms involved in the regulation of gene transcription may be helpful in determining how these changes affect SCZ development and progression. In the current work, we used a bioinformatics approach to describe the role of long non-coding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs) in the olfactory epithelium (OE) samples in order to better understand the molecular regulatory processes implicated in SCZ disorders in living individuals. The Gene Expression Omnibus database was used to obtain the OE microarray dataset (GSE73129) from SCZ sufferers and control subjects, which contained information about both lncRNAs and mRNAs. The limma package of R software was used to identify the differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs). RNA interaction pairs were discovered using the Human MicroRNA Disease Database, DIANA-LncBase, and miRTarBase databases. In this study, the Pearson correlation coefficient was utilized to find positive correlations between DEmRNAs and DElncRNAs in the ceRNA network. Eventually, lncRNA-associated ceRNA axes were developed based on co-expression relations and DElncRNA-miRNA-DEmRNA interactions. This work found six potential DElncRNA-miRNA-DEmRNA loops in SCZ pathogenesis, including, SNTG2-AS1/hsa-miR-7-5p/SLC7A5, FLG-AS1/hsa-miR-34a-5p/FOSL1, LINC00960/hsa-miR-34a-5p/FOSL1, AQP4-AS1/hsa-miR-335-5p/FMN2, SOX2-OT/hsa-miR-24-3p/NOS3, and CASC2/hsa-miR-24-3p/NOS3. According to the findings, ceRNAs in OE might be promising research targets for studying SCZ molecular mechanisms. This could be a great opportunity to examine different aspects of neurodevelopment that may have been hampered early in SCZ patients.

Long Non-Coding RNA- Associated Competing Endogenous RNA Axes in T-Cells in Multiple Sclerosis

Multiple sclerosis (MS) is an immune-mediated demyelinating and degenerative disease with unknown etiology. Inappropriate response of T-cells to myelin antigens has an essential role in the pathophysiology of MS. The clinical and pathophysiological complications of MS necessitate identification of potential molecular targets to understand the pathogenic events of MS. Since the functions and regulatory mechanisms of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in MS are yet uncertain, we conducted a bioinformatics analysis to explain the lncRNA-associated ceRNA axes to clarify molecular regulatory mechanisms involved in T-cells responses in MS. Two microarray datasets of peripheral blood T-cell from subjects with relapsing-remitting MS and matched controls containing data about miRNAs (GSE43590), mRNAs and lncRNAs (GSE43591) were downloaded from the Gene Expression Omnibus database. Differentially expressed miRNAs (DEmiRNAs), mRNAs (DEmRNAs), and lncRNAs (DElncRNAs) were identified by the limma package of the R software. Protein-protein interaction (PPI) network and module were developed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and the Molecular Complex Detection (MCODE) Cytoscape plugin, respectively. Using DIANA-LncBase and miRTarBase, the lncRNA-associated ceRNA axes was constructed. We conducted a Pearson correlation analysis and selected the positive correlations among the lncRNAs and mRNAs in the ceRNA axes. Lastly, DEmRNAs pathway enrichment was conducted by the Enrichr tool. A ceRNA regulatory relationship among Small nucleolar RNA host gene 1 (SNHG1), hsa-miR-197-3p, YOD1 deubiquitinase (YOD1) and zinc finger protein 101 (ZNF101) and downstream connected genes was identified. Pathway enrichment analysis showed that DEmRNAs were enriched in “Protein processing in endoplasmic reticulum” and “Herpes simplex virus 1 infection” pathways. To our knowledge, this would be the first report of a possible role of SNHG1/hsa-miR-197-3p/YOD1/ZNF101 axes in the pathogenesis of MS. This research remarks on the significance of ceRNAs and prepares new perceptions for discovering the molecular mechanism of MS.

Bioinformatics analysis of long non-coding RNA-associated competing endogenous RNA network in schizophrenia

Schizophrenia (SCZ) is a serious psychiatric condition with a 1% lifetime risk. SCZ is one of the top ten global causes of disabilities. Despite numerous attempts to understand the function of genetic factors in SCZ development, genetic components in SCZ pathophysiology remain unknown. The competing endogenous RNA (ceRNA) network has been demonstrated to be involved in the development of many kinds of diseases. The ceRNA hypothesis states that cross-talks between coding and non-coding RNAs, including long non-coding RNAs (lncRNAs), via miRNA complementary sequences known as miRNA response elements, creates a large regulatory network across the transcriptome. In the present study, we developed a lncRNA-related ceRNA network to elucidate molecular regulatory mechanisms involved in SCZ. Microarray datasets associated with brain regions (GSE53987) and lymphoblasts (LBs) derived from peripheral blood (sample set B from GSE73129) of SCZ patients and control subjects containing information about both mRNAs and lncRNAs were downloaded from the Gene Expression Omnibus database. The GSE53987 comprised 48 brain samples taken from SCZ patients (15 HPC: hippocampus, 15 BA46: Brodmann area 46, 18 STR: striatum) and 55 brain samples taken from control subjects (18 HPC, 19 BA46, 18 STR). The sample set B of GSE73129 comprised 30 LB samples (15 patients with SCZ and 15 controls). Differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified using the limma package of the R software. Using DIANA-LncBase, Human MicroRNA Disease Database (HMDD), and miRTarBase, the lncRNA- associated ceRNA network was generated. Pathway enrichment of DEmRNAs was performed using the Enrichr tool. We developed a protein-protein interaction network of DEmRNAs and identified the top five hub genes by the use of STRING and Cytoscape, respectively. Eventually, the hub genes, DElncRNAs, and predictive miRNAs were chosen to reconstruct the subceRNA networks. Our bioinformatics analysis showed that twelve key DEmRNAs, including BDNF, VEGFA, FGF2, FOS, CD44, SOX2, NRAS, SPARC, ZFP36, FGG, ELAVL1, and STARD13, participate in the ceRNA network in SCZ. We also identified DLX6-AS1, NEAT1, MINCR, LINC01094, DLGAP1-AS1, BABAM2-AS1, PAX8-AS1, ZFHX4-AS1, XIST, and MALAT1 as key DElncRNAs regulating the genes mentioned above. Furthermore, expression of 15 DEmRNAs (e.g., ADM and HLA-DRB1) and one DElncRNA (XIST) were changed in both the brain and LB, suggesting that they could be regarded as candidates for future biomarker studies. The study indicated that ceRNAs could be research candidates for investigating SCZ molecular pathways.

Expression characteristics of long noncoding RNA and messenger RNA in human traumatic brain injury

OBJECTIVES

The role of long noncoding RNAs has attracted significant attention in diseases. However, their expression characteristics in human traumatic brain injury are unclear.

METHODS

The brain contusion tissues and tissues adjacent to the brain contusion from 6 server traumatic brain injury patients were used to analyze differential expression signatures of long noncoding RNAs and mRNAs via full-length transcriptome sequencing, Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis and establishment of a long noncoding RNA/mRNA coexpression network.

RESULTS

We identified 1720 long noncoding RNAs and 1632 mRNAs differential expression. Microarray analysis showed that 874 long noncoding RNAs and 1405 mRNAs were upregulated, 846 long noncoding RNAs and 227 mRNAs were downregulated. Subsequently, we used Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses to reveal signaling pathways that were associated with target genes. Then, a long noncoding RNA/mRNA coexpression network was generated, which showed an absolute correlation coefficient value >0.99 for 559 long noncoding RNA-mRNA pairs. Finally, we comprehensive analyzed long noncoding RNA/mRNA coexpression network and Kyoto Encyclopedia of Genes and Genomes pathway and found the top five pairs of long noncoding RNA/ mRNA. Accordingly, we identified that long noncoding RNA tubulin beta 6 class V/nuclear factor E2-related factor 2 was most closely related to the pathological process after traumatic brain injury.

CONCLUSIONS

Our results indicated that the expression profiles of long noncoding RNAs and mRNAs were different after traumatic brain injury, providing new insight regarding long noncoding RNAs in human traumatic brain injury.

Mechanistic Insight Into the Regulation of Immune-Related Genes Expression in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder featuring impairment in verbal and non-verbal interactions, defects in social interactions, stereotypic behaviors as well as restricted interests. In recent times, the incidence of ASD is growing at a rapid pace. In spite of great endeavors devoted to explaining ASD pathophysiology, its precise etiology remains unresolved. ASD pathogenesis is related to different phenomena associated with the immune system; however, the mechanisms behind these immune phenomena as well as the potential contributing genes remain unclear. In the current work, we used a bioinformatics approach to describe the role of long non-coding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs) in the peripheral blood (PB) samples to figure out the molecular regulatory procedures involved in ASD better. The Gene Expression Omnibus database was used to obtain the PB microarray dataset (GSE89594) from the subjects suffering from ASD and control subjects, containing the data related to both mRNAs and lncRNAs. The list of immune-related genes was obtained from the ImmPort database. In order to determine the immune-related differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs), the limma package of R software was used. A protein-protein interaction network was developed for the immune-related DEmRNAs. By employing the Human MicroRNA Disease Database, DIANA-LncBase, and DIANA-TarBase databases, the RNA interaction pairs were determined. We used the Pearson correlation coefficient to discover the positive correlations between DElncRNAs and DEmRNAs within the ceRNA network. Finally, the lncRNA-associated ceRNA network was created based on DElncRNA-miRNA-DEmRNA interactions and co-expression interactions. In addition, the KEGG enrichment analysis was conducted for immune-related DEmRNAs found within the constructed network. This work found four potential DElncRNA-miRNA-DEmRNA axes in ASD pathogenesis, including, LINC00472/hsa-miR-221-3p/PTPN11, ANP32A-IT1/hsa-miR-182-5p/S100A2, LINC00472/hsa-miR-132-3p/S100A2, and RBM26-AS1/hsa-miR-182-5p/S100A2. According to pathway enrichment analysis, the immune-related DEmRNAs were enriched in the "JAK-STAT signaling pathway" and "Adipocytokine signaling pathway." An understanding of regulatory mechanisms of ASD-related immune genes would provide novel insights into the molecular mechanisms behind ASD pathogenesis.