A systemic approach to explore the mechanisms of drug resistance and altered signaling cascades in extensively drug-resistant tuberculosis

Identified S100A9 as a target for diagnosis and treatment of ulcerative colitis by bioinformatics analysis

Ulcerative colitis (UC) is a chronic, recurrent inflammatory bowel disease. UC confronts with severe challenges including the unclear pathogenesis and lack of specific diagnostic markers, demanding for identifying predictive biomarkers for UC diagnosis and treatment. We perform immune infiltration and weighted gene co-expression network analysis on gene expression profiles of active UC, inactive UC, and normal controls to identify UC related immune cell and hub genes. Neutrophils, M1 macrophages, activated dendritic cells, and activated mast cells are significantly enriched in active UC. MMP-9, CHI3L1, CXCL9, CXCL10, CXCR2 and S100A9 are identified as hub genes in active UC. Specifically, S100A9 is significantly overexpressed in mice with colitis. The receiver operating characteristic curve demonstrates the excellent performance of S100A9 expression in diagnosing active UC. Inhibition of S100A9 expression reduces DSS-induced colonic inflammation. These identified biomarkers associated with activity in UC patients enlighten the new insights of UC diagnosis and treatment.

Genomic insights and advanced machine learning: characterizing autism spectrum disorder biomarkers and genetic interactions

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by altered brain connectivity and function. In this study, we employed advanced bioinformatics and explainable AI to analyze gene expression associated with ASD, using data from five GEO datasets. Among 351 neurotypical controls and 358 individuals with autism, we identified 3,339 Differentially Expressed Genes (DEGs) with an adjusted p-value (≤ 0.05). A subsequent meta-analysis pinpointed 342 DEGs (adjusted p-value ≤ 0.001), including 19 upregulated and 10 down-regulated genes across all datasets. Shared genes, pathogenic single nucleotide polymorphisms (SNPs), chromosomal positions, and their impact on biological pathways were examined. We identified potential biomarkers (HOXB3, NR2F2, MAPK8IP3, PIGT, SEMA4D, and SSH1) through text mining, meriting further investigation. Additionally, ‎we shed light on the roles of RPS4Y1 and KDM5D genes in neurogenesis and neurodevelopment. Our analysis detected 1,286 SNPs linked to ASD-related conditions, of which 14 high-risk SNPs were located on chromosomes 10 and X. We highlighted potential missense SNPs associated with FGFR inhibitors, suggesting that it may serve as a promising biomarker for responsiveness to targeted therapies. Our explainable AI model identified the MID2 gene as a potential ASD biomarker. This research unveils vital genes and potential biomarkers, providing a foundation for novel gene discovery in complex diseases.

Structural Optimization of Antimycobacterial Azaaurones Towards Improved Solubility and Metabolic Stability

While N-acetyl azaaurones have already been disclosed for their potential against tuberculosis (TB), their low metabolic stability remains an unaddressed liability. We now report a study designed to improve the metabolic stability and solubility of the azaaurone scaffold and to identify the structural requirements for antimycobacterial activity. Replacing the N-acetyl moiety for a N-carbamoyl group led to analogues with sub- and nanomolar potencies against M. tuberculosis H37Rv, as well as equipotent against drug-susceptible and drug-resistant M. tuberculosis isolates. The new N-carbamoyl azaaurones exhibited improved microsomal stability, compared to their N-acetylated counterparts, with several compounds displaying moderate to high kinetic solubility. The frequency of spontaneous resistance to azaaurones was observed to be in the range of 10-8 , a value that is comparable to current TB drugs in the market. Overall, these results reveal that azaaurones are amenable to structural modifications to improve metabolic and solubility liabilities, and highlight their potential as antimycobacterial agents.

GP, Kumar SU, El Allali A, Alsamman AM, Zayed H. Integrated gene network analysis sheds light on understanding the progression of Osteosarcoma

Introduction

Osteosarcoma is a rare disorder among cancer, but the most frequently occurring among sarcomas in children and adolescents. It has been reported to possess the relapsing capability as well as accompanying collateral adverse effects which hinder the development process of an effective treatment plan. Using networks of omics data to identify cancer biomarkers could revolutionize the field in understanding the cancer. Cancer biomarkers and the molecular mechanisms behind it can both be understood by studying the biological networks underpinning the etiology of the disease.

Methods

In our study, we aimed to highlight the hub genes involved in gene-gene interaction network to understand their interaction and how they affect the various biological processes and signaling pathways involved in Osteosarcoma. Gene interaction network provides a comprehensive overview of functional gene analysis by providing insight into how genes cooperatively interact to elicit a response. Because gene interaction networks serve as a nexus to many biological problems, their employment of it to identify the hub genes that can serve as potential biomarkers remain widely unexplored. A dynamic framework provides a clear understanding of biological complexity and a pathway from the gene level to interaction networks.

Results

Our study revealed various hub genes viz. TP53, CCND1, CDK4, STAT3, and VEGFA by analyzing various topological parameters of the network, such as highest number of interactions, average shortest path length, high cluster density, etc. Their involvement in key signaling pathways, such as the FOXM1 transcription factor network, FAK-mediated signaling events, and the ATM pathway, makes them significant candidates for studying the disease. The study also highlighted significant enrichment in GO terms (Biological Processes, Molecular Function, and Cellular Processes), such as cell cycle signal transduction, cell communication, kinase binding, transcription factor activity, nucleoplasm, PML body, nuclear body, etc.

Conclusion

To develop better therapeutics, a specific approach toward the disease targeting the hub genes involved in various signaling pathways must have opted to unravel the complexity of the disease. Our study has highlighted the candidate hub genes viz. TP53, CCND1 CDK4, STAT3, VEGFA. Their involvement in the major signaling pathways of Osteosarcoma makes them potential candidates to be targeted for drug development. The highly enriched signaling pathways include FOXM1 transcription pathway, ATM signal-ling pathway, FAK mediated signaling events, Arf6 signaling events, mTOR signaling pathway, and Integrin family cell surface interactions. Targeting the hub genes and their associated functional partners which we have reported in our studies may be efficacious in developing novel therapeutic targets.

Identification of potential circadian genes and associated pathways in colorectal cancer progression and prognosis using microarray gene expression analysis

Colorectal cancer (CRC) is third cancer causing death in the world. CRC is associated with disrupting the circadian rhythm (CR), closely associating the CRC progression and the dysregulation of genes involved in the biological clock. In this study, we aimed to understand the circadian rhythm changes in patients diagnosed with CRC. We used the GEO database with the ID GSE46549 for our analysis, which consists of 32 patients with CRC and one as normal control. Our study has identified five essential genes involved in CRC, HAPLN1, CDH12, IGFBP5, DCHS2, and DOK5, and had different enriched pathways, such as the Wnt-signaling pathway, at different time points of study. As a part of our study, we also identified various related circadian genes, such as CXCL12, C1QTNF2, MRC2, and GLUL, from the Circadian Gene Expression database, that played a role in circadian rhythm and CRC development. As circadian timing can influence the host tissue's ability to tolerate anticancer medications, the genes reported can serve as a potential drug target for treating CRC and become beneficial to translational settings.

Elucidating the mechanism of antimicrobial resistance in Mycobacterium tuberculosis using gene interaction networks

Antimicrobial resistance (AMR) in microorganisms is an urgent global health threat. AMR of Mycobacterium tuberculosis is associated with significant morbidity and mortality. It is of great importance to underpin the resistance pathways involved in the mechanisms of AMR and identify the genes that are directly involved in AMR. The focus of the current study was the bacteria M. tuberculosis, which carries AMR genes that give resistance that lead to multidrug resistance. We, therefore, built a network of 43 genes and examined for potential gene-gene interactions. Then we performed a clustering analysis and identified three closely related clusters that could be involved in multidrug resistance mechanisms. Through the bioinformatics pipeline, we consistently identified six-hub genes (dnaN, polA, ftsZ, alr, ftsQ, and murC) that demonstrated the highest number of interactions within the clustering analysis. This study sheds light on the multidrug resistance of MTB and provides a protocol for discovering genes that might be involved in multidrug resistance, which will improve the treatment of resistant strains of TB.

Molecular characterization of circadian gene expression and its correlation with survival percentage in colorectal cancer patients

Colorectal cancer (CRC) is a form of cancer characterized by many symptoms and readily metastasizes to different organs in the body. Circadian rhythm is one of the many processes that is observed to be dysregulated in CRC-affected patients. In this study, we aim to identify the dysregulated physiological processes in CRC-affected patients and correlate the expression profiles of the circadian clock genes with CRC-patients' survival rates. We performed an extensive microarray gene expression pipeline, whereby 471 differentially expressed genes (DEGs) were identified, following which, we streamlined our search to 43 circadian clock affecting DEGs. The Circadian Gene Database was accessed to retrieve the circadian rhythm-specific genes. The DEGs were then subjected to multi-level functional annotation, i.e., preliminary analysis using ClueGO/CluePedia and pathway enrichment using DAVID. The findings of our study were interesting, wherein we observed that the survival percentage of CRC-affected patients dropped significantly around the 100th-month mark. Furthermore, we identified hormonal activity, xenobiotic metabolism, and PI3K-Akt signaling pathway to be frequently dysregulated cellular functions. Additionally, we detected that the ZFYVE family of genes and the two genes, namely MYC and CDK4 were the significant DEGs that are linked to the pathogenesis and progression of CRC. This study sheds light on the importance of bioinformatics to simplify our understanding of the interactions of different genes that control different phenotypes.

Analysis of signaling cascades from myeloma cells treated with pristimerin

Multiple myeloma (MM) is the 2nd most frequently diagnosed blood cancer after non-Hodgkin's lymphoma. The present study aimed to identify the differentially expressed genes (DEGs) between the control and pristimerin-treated MM cell lines. We examined the GSE14011 microarray dataset and screened DEGs with GEO2R statistical tool using the inbuilt limma package. We used a bioinformatics pipeline to identify the differential networks, signaling cascades, and the survival of the hub genes. We implemented two different enrichment analysis including ClueGO and Metacore™, to get accurate annotation for most significant DEGs. We screened the most significant 408 DEGs from the dataset based on p-values and logFC values. Using protein network analysis, we found the genes UBC, HSP90AB1, HSPH1, HSPA1B, HSPA1L, HSPA6, HSPD1, DNAJB1, HSPE1, DNAJC10, BAG3, and DNAJC7 had higher node degree distribution. In contrast, the functional annotation provided that the DEGs were predominantly enriched in B-cell receptor signaling, unfolded protein response, positive regulation of phagocytosis, HSP70, and HSP40-dependent folding, and ubiquitin-proteasomal proteolysis. Using network algorithms, and comparing enrichment analysis, we found the hub genes enriched were INHBE, UBC, HSPA1A, HSP90AB1, IKBKB, and BAG3. These DEGs were further validated with overall survival and gene expression analysis between the tumor and control groups. Finally, pristimerin effects were validated independently in a cell line model consisting of IM9 and U266 MM cells. Pristimerin induced in vitro cytotoxicity in MM cells in a dose-dependent manner. Pristimerin inhibited NF-κB, induced accumulation of ubiquitinated proteins and inhibited HSP60 in the validation of bioinformatics findings, while pristimerin-induced caspase-3 and PARP cleavage confirmed cell death. Taken together, we found that the identified DEGs were strongly associated with the apoptosis induced in MM cell lines due to pristimerin treatment, and combinatorial therapy derived from pristimerin could act as novel anti-myeloma multifunctional agents.

Upregulation of SERPINE2 Results in Poor Prognosis of Hepatoblastoma via Promoting Invasion Abilities

Background

Hepatoblastoma (HB) is the most common malignant liver tumor in children. High-risk patients, especially those with tumor metastasis, have poor prognosis. Serpin family E member 2 (SERPINE2) is overexpressed in a variety of tumors, especially adenocarcinoma, and promotes tumor invasion and metastasis. The function and mechanism of SERPINE2 in HB are still unclear. The purpose of this study was to investigate the potential clinical prognostic value and molecular mechanism of SERPINE2 in HB.

Methods

We performed bioinformatics analyses on HB microarray data GSE131329 to study the role of SERPINE2. The expression level of SERPINE2 in HB and its clinical significance were further analyzed by quantitative real-time polymerase chain reaction (qRT-PCR), Western blot, and immunohistochemistry. After constructing the SERPINE2 overexpression and knockdown in HepG2 and HUH6 cells, the 5-ethynyl-29-deoxyuridine (EdU) assay, wound healing assay, Transwell experiment, and apoptosis assay were performed to explore the role of SERPINE2 in HB progress.

Results

Upregulation of SERPINE2 was found in HB tissues and was associated with a poor prognosis. Moreover, the SERPINE2 expression was related to tumor size, vascular invasion, and tumor metastasis. The Cox regressions show that high SERPINE2 expression is an independent risk factor for HB. SERPINE2 overexpression remarkably enhanced HB cell migration and invasion and suppressed apoptosis, while knockdown of SERPINE2 exerted the opposite effect. In addition, SERPINE2 facilitated the epithelial to mesenchymal transformation (EMT) phenotype of HB cells in vitro.

Conclusion

Our findings indicated that SERPINE2 accelerates HB progression, suggesting that SERPINE2 may be a potential prognostic biomarker and an underlying therapeutic target for HB.

Molecular Insight into Mycobacterium tuberculosis Resistance to Nitrofuranyl Amides Gained through Metagenomics-like Analysis of Spontaneous Mutants

We performed synthesis of new nitrofuranyl amides and investigated their anti-TB activity and primary genetic response of mycobacteria through whole-genome sequencing (WGS) of spontaneous resistant mutants. The in vitro activity was assessed on reference strain Mycobacterium tuberculosis H37Rv. The most active compound 11 was used for in vitro selection of spontaneous resistant mutants. The same mutations in six genes were detected in bacterial cultures grown under increased concentrations of 11 (2×, 4×, 8× MIC). The mutant positions were presented as mixed wild type and mutant alleles while increasing the concentration of the compound led to the semi-proportional and significant increase in mutant alleles. The identified genes belong to different categories and pathways. Some of them were previously reported as mediating drug resistance or drug tolerance, and counteracting oxidative and nitrosative stress, in particular: Rv0224c, fbiC, iniA, and Rv1592c. Gene-set interaction analysis revealed a certain weak interaction for gene pairs Rv1592–Rv1639c and Rv1592–Rv0224c. To conclude, this study experimentally demonstrated a multifaceted primary genetic response of M. tuberculosis to the action of nitrofurans. All three 11-treated subcultures independently presented the same six SNPs, which suggests their non-random occurrence and likely causative relationship between compound action and possible resistance mechanism.

Investigation of differentially expressed genes and dysregulated pathways involved in multiple sclerosis

Multiple Sclerosis (MS) is a neurodegenerative autoimmune and organ-specific demyelinating disorder, known to affect the central nervous system (CNS). While genetic studies have revealed several critical genes and diagnostic biomarkers associated with MS, the etiology of the disease remains poorly understood. This study is aimed at screening and identifying the key genes and canonical pathways associated with MS. Gene expression profiling of the microarray dataset GSE38010 was used to analyze two control brain samples (control 1; GSM931812, control 2; GSM931813), active inflammation stage samples (CAP1; GSM931815, CAP2; GSM931816) and late subsided stage samples (CP1; GSM931817, CP2; GSM931818) collected from patients ranging between 23 and 54years and both genders. This analysis yielded a list of 58,866 DEGs (29,433 for active-inflammation stage and 29,433 for late-subsided Stage). The interactions between the DEGs were then studied using STRING, Cytoscape software, and MCODE was employed to find the genes that form clusters. Functional enrichment and integrative analysis were performed using ClueGO/CluePedia and MetaCore™. Our data revealed dysregulated key canonical pathways in MS patients. In addition, we identified three hub genes (SCN2A, HTR2A, and HCN1) that may serve as potential biomarkers for the prognosis of MS. Furthermore, the expression patterns of HPCA and PLCB1 provide insights into the progressive stages of MS, indicating that these genes could be used in predicting MS progression. We were able to map potential biomarkers that could be used for the prognosis and diagnosis of MS.

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.

A review of bioinformatics tools and web servers in different microarray platforms used in cancer research

Over the past decade, conventional lab work strategies have gradually shifted from being limited to a laboratory setting towards a bioinformatics era to help manage and process the vast amounts of data generated by omics technologies. The present work outlines the latest contributions of bioinformatics in analyzing microarray data and their application to cancer. We dissect different microarray platforms and their use in gene expression in cancer models. We highlight how computational advances empowered the microarray technology in gene expression analysis. The study on protein-protein interaction databases classified into primary, derived, meta-database, and prediction databases describes the strategies to curate and predict novel interaction networks in silico. In addition, we summarize the areas of bioinformatics where neural graph networks are currently being used, such as protein functions, protein interaction prediction, and in silico drug discovery and development. We also discuss the role of deep learning as a potential tool in the prognosis, diagnosis, and treatment of cancer. Integrating these resources efficiently, practically, and ethically is likely to be the most challenging task for the healthcare industry over the next decade; however, we believe that it is achievable in the long term.

The macrophage-associated microRNA-4715-3p / Gasdermin D axis potentially indicates fibrosis progression in nonalcoholic fatty liver disease: evidence from transcriptome and biological data

Nonalcoholic fatty liver disease (NAFLD) is highly possible to progress to cirrhosis, malignancy, and liver failure through fibrogenesis. The enormous potential of pathogenetic and therapeutic targets in NAFLD has been revealed. This study aimed to explore novel factors potentially indicating or mediating NAFLD progression. Multiple bulk and single-cell RNA sequencing datasets were used, in which landscapes of cell populations were clarified to characterize immune cell infiltration. Significantly high infiltration of macrophages (MPs) was discovered during NAFLD progression. Samples in bulk NASH datasets were regrouped by MP level. Highly differentially expressed genes (DEGs) were identified in the Ctrl vs. NASH comparison, low MP vs. high MP comparison, and the weighted gene co-expression network analysis (WGCNA) clusters. Eight hub genes were identified as promising targets by protein–protein interaction analysis and validated in fibrosis progression, microRNA (miR)–protein interactions were predicted, and the hub genes were verified in a free fatty acid (FFA)-induced macrophage injury model. The results showed that Gasdermin D (GSDMD) was upregulated with fibrosis progression in NAFLD and was associated with macrophage infiltration. In addition, a potential regulator (miR-4715-3p) was correlated with GSDMD. The miR-4715-3p/GSDMD axis potentially modulates macrophage-associated immunity and indicates fibrosis progression in NAFLD.

Functional deficiency of succinate dehydrogenase promotes tumorigenesis and development of clear cell renal cell carcinoma through weakening of ferroptosis

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal carcinomas, with high mortality and poor prognoses worldwide. Succinate dehydrogenase (SDH) consists of four nuclear-encoded subunits and it is the only complex involved in both the tricarboxylic acid (TCA) cycle and oxidative phosphorylation (OXPHOS). Previous studies have shown decreased SDH activity in ccRCC. However, the role and underlying molecular mechanisms of SDH in ccRCC initiation and development remain unclear. In the present study, pan-cancer analysis of SDH gene expression was analyzed and the relationship between SDH gene expression and clinicopathological parameters was assessed using different databases. cBioPortal, UACLAN, and Tumor Immune Estimation Resource (TIMER) were subsequently utilized to analyze genetic alterations, methylation, and immune cell infiltration of SDH genes in ccRCC patients. We found SDHs were significantly downregulated in ccRCC tissues and correlated with ccRCC progression. Increased methylation and high SDH promoter mutation rates may be the cause of reduced expression of SDHs in ccRCC. Moreover, the interaction network showed that SDH genes were correlated with ferroptosis-related genes. We further demonstrated that SDH inhibition dampened oxidative phosphorylation, reduced ferroptotic events, and restored ferroptotic cell death, characterized by eliminated mitochondrial ROS levels, decreased cellular ROS and diminished peroxide accumulation. Collectively, this study provides new insights into the regulatory role of SDH in the carcinogenesis and progression of ccRCC, introducing a potential target for advanced antitumor therapy through ferroptosis.

A computational model revealing the immune-related hub genes and key pathways involved in rheumatoid arthritis (RA)

Rheumatoid arthritis (RA) has one of the highest disability rates among inflammatory joint disorders. However, the reason and possible molecular events are still unclear. There are various treatment options available, but no complete cure. To obtain early diagnosis and successful medication in RA, it is necessary to explore gene susceptibility and pathogenic factors. The main intend of our work is to explore the immune-related hub genes with similar functions that are differentially expressed in RA patients. Three datasets such as GSE21959, GSE55457, and GSE77298, were taken to analyze the differently expressed genes (DEGs) among 55 RA and 33 control samples. We obtained 331 upregulated and 275 downregulated DEGs from three Gene Expression Omnibus (GEO) datasets using the R package. Furthermore, a protein-protein interaction network was built for upregulated and downregulated DEGs using Cytoscape. Subsequently, MCODE analysis was performed and obtained the top two modules in each DEG's upregulated and downregulated protein-protein interactions (PPIs) network. CytoNCA and cytoHubba were performed and identified overlapping DEGs. In addition, we narrowed down DEGs by filtering with immune-related genes and identified DE-IRGs. Gene ontology (GO) and KEGG pathway analysis in upregulated and downregulated DEGs were executed with the DAVID platform. Our study obtained the nine most significant DE-IRGs in RA such as CXCR4, CDK1, BUB1, BIRC5, AGTR1, EGFR, EDNRB, KALRN, and GHSR. Among them, CXCR4, CDK1, BUB1, and BIRC5 are overexpressed in RA and may contribute to the pathophysiology of the disease. Similarly, AGTR1, EGFR, EDNRB, KALRN, and GHSR are all low expressed in RA and may have a contribution to pathogenesis. GO, KEGG functional enrichment, and GeneMANIA showed that the dysregulated process of DE-IRGs causes RA development and progression. These findings may be helpful in future studies in RA diagnosis and therapy.

Long non-coding RNAs PGM5-AS1 upregulates Decorin (DCN) to inhibit cervical cancer progression by sponging miR-4284

Long non-coding RNAs (lncRNAs) have been widely studied and play crucial roles in cervical cancer (CC) progression. Here, we investigated the function and mechanism of lncRNA PGM5-AS1 action in CC cells. Using real-time quantitative polymerase chain reaction or western blotting, PGM5-AS1 and decorin (DCN) were downregulated in CC tissues and cells, whereas miR-4284 was upregulated. Luciferase assay, RNA pull-down assay, and western blotting showed that PGM5-AS1 could sponge miR-4284 to upregulate DCN expression in CC cells. Additionally, cell functional experiments showed that PGM5-AS1 overexpression led to decreased proliferation, migration, and invasion of CC cells. However, the inhibitory effect of PGM5-AS1 overexpression on CC cells was partly relieved by DCN knockdown because of the targeting interaction between PGM5-AS1, miR-4284, and DCN. In summary, this study identified that PGM5-AS1 negatively regulates CC cell malignancy by targeting miR-4284/DCN.

Identification of differential microRNAs and messenger RNAs resulting from ASXL transcriptional regulator 3 knockdown during during heart development

Congenital heart disease (CHD) is the most common birth defect. Although ASXL transcriptional regulator 3 (ASXL3) has been reported to cause hereditary CHD, ASXL3-mediated mechanisms in heart development remain unclear. In this study, we used dimethyl sulfoxide (DMSO) to induce differentiation in P19 cells, observed cell morphology using light microscopy after ASXL3 knockdown, and determined the levels of associated myocardial cell markers using reverse transcription-quantitative polymerase chain reaction and western blotting. Subsequently, we used microRNA sequencing, messenger RNA (mRNA) sequencing, and bioinformatics to initially identify the possible mechanisms through which ASXL3-related microRNAs and mRNAs affect heart development. The results indicated that DMSO induced P19 cell differentiation, which could be inhibited by ASXL3 knockdown. We screened 1214 and 1652 differentially expressed microRNAs and mRNAs, respectively, through ASXL3 knockdown and sequencing; these differentially expressed miRNAs were largely enriched in PI3K-Akt, mitogen-activated protein kinase, and Rap1 signaling pathways. Additionally, 11 miRNAs associated with heart development were selected through a literature review. Our analysis indicated the involvement of mmu-miR-323-3p in P19 cell differentiation through the PI3K-Akt pathway. In conclusion, ASXL3 may be involved in the regulation of heart development. This comprehensive study of differentially expressed microRNAs and mRNAs through ASXL3 knockdown in P19 cells provides new insights that may aid the prevention and treatment of CHD.

Transcriptional Profiling and Deriving a Seven-Gene Signature That Discriminates Active and Latent Tuberculosis: An Integrative Bioinformatics Approach

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (M.tb.). Our integrative analysis aims to identify the transcriptional profiling and gene expression signature that distinguish individuals with active TB (ATB) disease, and those with latent tuberculosis infection (LTBI). In the present study, we reanalyzed a microarray dataset (GSE37250) from GEO database and explored the data for differential gene expression analysis between those with ATB and LTBI derived from Malawi and South African cohorts. We used BRB array tool to distinguish DEGs (differentially expressed genes) between ATB and LTBI. Pathway enrichment analysis of DEGs was performed using DAVID bioinformatics tool. The protein–protein interaction (PPI) network of most upregulated genes was constructed using STRING analysis. We have identified 375 upregulated genes and 152 downregulated genes differentially expressed between ATB and LTBI samples commonly shared among Malawi and South African cohorts. The constructed PPI network was significantly enriched with 76 nodes connected to 151 edges. The enriched GO term/pathways were mainly related to expression of IFN stimulated genes, interleukin-1 production, and NOD-like receptor signaling pathway. Downregulated genes were significantly enriched in the Wnt signaling, B cell development, and B cell receptor signaling pathways. The short-listed DEGs were validated in a microarray data from an independent cohort (GSE19491). ROC curve analysis was done to assess the diagnostic accuracy of the gene signature in discrimination of active and latent tuberculosis. Thus, we have derived a seven-gene signature, which included five upregulated genes FCGR1B, ANKRD22, CARD17, IFITM3, TNFAIP6 and two downregulated genes FCGBP and KLF12, as a biomarker for discrimination of active and latent tuberculosis. The identified genes have a sensitivity of 80–100% and specificity of 80–95%. Area under the curve (AUC) value of the genes ranged from 0.84 to 1. This seven-gene signature has a high diagnostic accuracy in discrimination of active and latent tuberculosis.

Utilizing network pharmacology and experimental validation to explore the potential molecular mechanisms of BanXia-YiYiRen in treating insomnia

BanXia-YiYiRen (Pinellia Ternata and Coix Seed, BX-YYR) has been clinically proven to be an effective Chinese medicine compatible with the treatment of insomnia. However, the underlying mechanism of BX-YYR against insomnia remains unclear. This study aimed to explore the pharmacological mechanisms of BX-YYR in treating insomnia based on network pharmacology and experimental validation. The drug-disease targets were obtained using publicly available databases. The analysis revealed 21 active compounds and 101 potential targets of BX-YYR from the pharmacological database of Chinese medicine system and analysis platform (TCMSP) and 1020 related targets of insomnia from the GeneCards and Online Mendelian Inheritance in Man (OMIM) databases. Furthermore, 38 common targets of BX-YYR against insomnia were identified, and these common targets were used to construct a protein–protein interaction (PPI) network. The visual PPI network was constructed by Cytoscape software. The top three genes from PPI according to degree value are FOS, AKT1, and CASP3. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were applied to reveal the potential targets and signaling pathways involved in BX-YYR against insomnia, especially the serotonergic pathway. In addition, molecular docking revealed that baicalein, beta-sitosterol, and stigmasterol displayed strong binding to AKT1, FOS, PRKCA, and VEGFA. Experimental study found that BX-YYR against insomnia might play a role in improving sleep by modulating the serotonergic pathway. In summary, our findings revealed the underlying mechanism of BX-YYR against insomnia and provided an objective basis for further experimental study and clinical application.

Screening differentially expressed genes between endometriosis and ovarian cancer to find new biomarkers for endometriosis

AIM

Endometriosis is one of the most common reproductive system diseases, but the mechanisms of disease progression are still unclear. Due to its high recurrence rate, searching for potential therapeutic biomarkers involved in the pathogenesis of endometriosis is an urgent issue.

METHODS

Due to the similarities between endometriosis and ovarian cancer, four endometriosis datasets and one ovarian cancer dataset were downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified, followed by gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interaction (PPI) analyses. Then, we validated gene expression and performed survival analysis with ovarian serous cystadenocarcinoma (OV) datasets in TCGA/GTEx database, and searched for potential drugs in the Drug-Gene Interaction Database. Finally, we explored the miRNAs of key genes to find biomarkers associated with the recurrence of endometriosis.

RESULTS

In total, 104 DEGs were identified in the endometriosis datasets, and the main enriched GO functions included cell adhesion, extracellular exosome and actin binding. Fifty DEGs were identified between endometriosis and ovarian cancer datasets including 11 consistently regulated genes, and nine DEGs with significant expression in TCGA/GTEx. Only IGHM had both significant expression and an association with survival, three module DEGs and two significantly expressed DEGs had drug associations, and 10 DEGs had druggability.

CONCLUSIONS

ITGA7, ITGBL1 and SORBS1 may help us understand the invasive nature of endometriosis, and IGHM might be related to recurrence; moreover, these genes all may be potential therapeutic targets.KEY MESSAGEThis manuscript used a bioinformatics approach to find target genes for the treatment of endometriosis.This manuscript used a new approach to find target genes by drawing on common characteristics between ovarian cancer and endometriosis.We screened relevant therapeutic agents for target genes in the drug database, and performed histological validation of target genes with both expression and survival analysis difference in cancer databases.

Identification of key molecular markers of acute coronary syndrome using peripheral blood transcriptome sequencing analysis and mRNA-lncRNA co-expression network construction

Acute coronary syndrome (ACS) is a term used to describe major cardiovascular diseases, and treatment of in-stent restenosis in patients with ACS remains a major clinical challenge. Further investigation into molecular markers of ACS may aid early diagnosis, and the treatment of ACS and post-treatment recurrence. In the present study, total RNA was extracted from the peripheral blood samples of 3 patients with ACS, 3 patients with percutaneous coronary intervention (PCI)_non-restenosis, 3 patients with PCI_restenosis and 3 healthy controls. Subsequently, RNA library construction and high-throughput sequencing were performed. DESeq2 package in R was used to screen genes that were differentially expressed between the different samples. Moreover, the intersection of the differentially expressed mRNAs (DEmRNAs) and differentially expressed long noncoding RNAs (DElncRNAs) obtained. GeneCodis4.0 was used to perform function enrichment for DEmRNAs, and lncRNA-mRNA co-expression network was constructed. The GSE60993 dataset was utilized for diagnostic analysis, and the aforementioned investigations were verified using in vitro studies. Results of the present study revealed a large number of DEmRNAs and DElncRNAs in the different groups. We selected genes in the top 10 of differential expression and also involved in the co-expression of lncRNA-mRNA for diagnostic analysis in the GSE60993 dataset. The area under curve (AUC) of PDZK1IP1 (0.747), PROK2 (0.769) and LAMP3 (0.725) were all >0.7. These results indicated that the identified mRNAs and lncRNAs may act as potential clinical biomarkers, and more specifically, PDZK1IP1, PROK2 and LAMP3 may act as potential biomarkers for the diagnosis of ACS.

Analysis of Factors Influencing Multidrug-Resistant Tuberculosis and Validation of Whole-Genome Sequencing in Children with Drug-Resistant Tuberculosis

Objective

Pediatric tuberculosis (TB) is one of the top ten causes of death in children. Our study was to analyze influencing factors of multidrug-resistant tuberculosis (MDR-TB) and validation of whole-genome sequencing (WGS) used in children with drug-resistant TB (DR-TB).

Methods

All Mycobacterium tuberculosis (Mtb) strains were isolated from patients aged below 18 years old of Children’s Hospital of Chongqing Medical University, China. A total of 208 Mtb isolates were tested for eight anti-TB drugs with phenotypic drug susceptibility test (DST) and for genetic prediction of the susceptible profile with WGS. The patients corresponding to each strain were grouped according to drug resistance and genotype. Influencing factors of MDR-TB and DR-TB were analyzed.

Results

According to the phenotypic DST and WGS, 82.2% of Mtb strains were susceptible to all eight drugs, and 6.3% were MDR-TB. Using the phenotypic DSTs as the gold standard, the kappa value of WGS to predict isoniazid, rifampin, ethambutol, rifapentine, prothionamide, levofloxacin, moxifloxacin and amikacin was 0.84, 0.89, 0.59, 0.86, 0.89, 0.82, 0.88 and 1.00, respectively. There was significant difference in the distribution of severe TB, diagnosis, treatment and outcome between MDR and drug-susceptible group (P<0.05). The distribution of severe TB and treatment between DR and drug-susceptible group was statistically different (P<0.05). The results of binary logistic regression showed that Calmette–Guérin bacillus (BCG) vaccine is the protective factor for MDR-TB (OR=0.19), and MDR-TB is the risk factor for PTB and EPTB (OR=17.98).

Conclusion

The BCG vaccine is a protective factor for MDR-TB, and MDR-TB might not be confined to pulmonary infection, spreading to extrapulmonary organs in children. MDR-TB had more severe cases and a lower recovery rate than drug-susceptible TB. WGS could provide an accurate prediction of drug susceptibility test results for anti-TB drugs, which are needed for the diagnosis and precise treatment of TB in children.

Comparison of critical biomarkers in 2 erectile dysfunction models based on GEO and NOS-cGMP-PDE5 pathway

BACKGROUND

Erectile dysfunction is a disease commonly caused by diabetes mellitus (DMED) and cavernous nerve injury (CNIED). Bioinformatics analyses including differentially expressed genes (DEGs), enriched functions and pathways (EFPs), and protein-protein interaction (PPI) networks were carried out in DMED and CNIED rats in this study. The critical biomarkers that may intervene in nitric oxide synthase (NOS, predominantly nNOS, ancillary eNOS, and iNOS)-cyclic guanosine monophosphate (cGMP)-phosphodiesterase 5 enzyme (PDE5) pathway, an important mechanism in erectile dysfunction treatment, were then explored for potential clinical applications.

METHODS

GSE2457 and GSE31247 were downloaded. Their DEGs with a |logFC (fold change)| > 0 were screened out. Database for Annotation, Visualization and Integrated Discovery (DAVID) online database was used to analyze the EFPs in Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes networks based on down-regulated and up-regulated DEGs respectively. PPI analysis of 2 datasets was performed in Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Cytoscape. Interactions with an average score greater than 0.9 were chosen as the cutoff for statistical significance.

RESULTS

From a total of 1710 DEGs in GSE2457, 772 were down-regulated and 938 were up-regulated, in contrast to the 836 DEGs in GSE31247, from which 508 were down-regulated and 328 were up-regulated. The 25 common EFPs such as aging and response to hormone were identified in both models. PPI results showed that the first 10 hub genes in DMED were all different from those in CNIED.

CONCLUSIONS

The intervention of iNOS with the hub gene complement component 3 in DMED and the aging process in both DMED and CNIED deserves attention.

Biomarkers of Blood from Patients with Atherosclerosis Based on Bioinformatics Analysis

Atherosclerosis is a multifaceted disease characterized by the formation and accumulation of plaques that attach to arteries and cause cardiovascular disease and vascular embolism. A range of diagnostic techniques, including selective coronary angiography, stress tests, computerized tomography, and nuclear scans, assess cardiovascular disease risk and treatment targets. However, there is currently no simple blood biochemical index or biological target for the diagnosis of atherosclerosis. Therefore, it is of interest to find a biochemical blood marker for atherosclerosis. Three datasets from the Gene Expression Omnibus (GEO) database were analyzed to obtain differentially expressed genes (DEG) and the results were integrated using the Robustrankaggreg algorithm. The genes considered more critical by the Robustrankaggreg algorithm were put into their own data set and the data set system with cell classification information for verification. Twenty-one possible genes were screened out. Interestingly, we found a good correlation between RPS4Y1, EIF1AY, and XIST. In addition, we know the general expression of these genes in different cell types and whole blood cells. In this study, we identified BTNL8 and BLNK as having good clinical significance. These results will contribute to the analysis of the underlying genes involved in the progression of atherosclerosis and provide insights for the discovery of new diagnostic and evaluation methods.

Bio-informatics and in Vitro Experiments Reveal the Mechanism of Schisandrin A Against MDA-MB-231 cells

Schisandrin A (SchA) has been reported to have good anti-cancer effects. However, its anti-cancer mechanism in breast cancer remains unknown. This study aimed to explore the mechanism of SchA in breast cancer treatment using bio-informatics analysis and in vitro experiments. The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Gene Cards, and PharmMapper databases were used to screen the candidate targets of SchA against MDA-MB-231 cells selected as the tested cell line through MTT analysis. The functions and pathways of the targets were identified using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and further analyzed using DAVID 6.8.1 database. Network pharmacology analysis revealed 77 candidate targets, 31 signal pathways, and 208 GO entries (P < 0.05). The targets regulated serine-type endopeptidase and protein tyrosine kinase activities, thereby promoting the migration and inhibiting the apoptosis of MDA-MB-231 cells. Comprehensive analysis of the ‘Protein–Protein Interaction’ (PPI) and ‘Component-Targets-Pathways’ (C-T-P) networks constructed using Cytoscape 3.7.1 software revealed four core targets: EGFR, PIK3R1, MMP9 and Caspase 3. Their docking scores with SchA were subsequently investigated through molecular docking. The wound healing, Hoechst 33342/PI, and western blot assays confirmed that SchA significantly down-regulated EGFR, PIK3R1, and MMP9, but up-regulated cleaved-caspase 3, thus inhibiting the migration and promoting the apoptosis of MDA-MB-231 cells. Reckoning the findings of the study, SchA is a potential adjuvant treatment for breast cancer.

Identification of the correlations between interleukin-27 (IL-27) and immune-inflammatory imbalance in preterm birth

Preterm birth (PTB) is an immune-inflammatory disease that needs to be resolved. This study aimed to identify the role of interleukin-27 (IL-27), an immunomodulatory factor, in PTB and its associated mechanisms. Here, we analyzed the high-throughput of samples data from the maternal-fetal interface to the peripheral circulation obtained from public databases and reported that the elevated IL-27 was involved with the onset of PTB. Further bioinformatics analyses (e.g. GeneMANIA and GSEA) revealed that IL-27 overexpression in the peripheral circulation as well as maternal-fetal interface is related to the activation of the immune-inflammatory process represented by IFN-γ signaling, etc. In addition, IL-27 and immune infiltration correlation analysis demonstrated that IL-27 mediates this immune-inflammatory imbalance, plausibly mainly through monocyte-macrophage and neutrophils. This finding was further validated by analyzing additional datasets. Overall, this is the first study to elaborate on the role of IL-27-mediated immuno-inflammation in PTB from the perspective of bioinformatics, which may provide a novel strategy for the prevention and treatment of PTB.