Biological Signaling Pathways Research Articles

Integrative network pharmacology and transcriptomics analysis reveal the mechanism of Tanreqing in the treatment of acne vulgaris

BackgroundAcne vulgaris is a common skin disease that affects the pilosebaceous unit, and inflammation plays an important role. Chinese traditional medicine Tanreqing (TRQ) has been used in the field of dermatology to treat inflammatory diseases and has shown outstanding efficacy. The purpose of this study was to evaluate the potential advantages of TRQ on a mouse model of acne inflammation. Additionally, network pharmacology and transcriptome analysis were utilized to investigate the possible underlying mechanisms. MethodsThe active compounds of TRQ were collected through TCMSP database and literature review, and the predicted targets of active compounds were obtained from Swiss Target Prediction. Acne targets were collected from the Gene Cards database and DisGeNET. Cytoscape v3.7.1 was used to build the "compounds-targets" network and PPI network and to obtain the core network. GO analysis and KEGG pathway annotation were performed on the core genes. The Illumina HiSeq sequencing platform was utilized to sequence mRNA from mouse skin tissue in acne areas. Differential gene expression analysis was conducted to identify genes that were affected by TRQ, and their associated biological functions and signaling pathways were analyzed. The transcriptomic and network pharmacology analyses were integrated to generate predictive results. Additionally, the efficacy of TRQ in treating acne was confirmed through H&E staining, and the predicted outcomes were verified through quantitative real-time PCR (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA). ResultsThe study's results indicate that 37 potential target genes were enriched in multiple signaling pathways, including the atherosclerosis, IL-17, and TNF signaling pathways, according to network pharmacology. In addition, 338 transcriptomic DEGs were found to be involved in various signaling pathways, including Cell adhesion molecules and the IL-17 signaling pathway.The combined analysis of these findings suggests that the IL-17 and TNF signaling pathways are the primary mechanisms by which TRQ exerts its anti-acne effects. H&E staining revealed that TRQ inhibited inflammatory cell infiltration in acne lesions and attenuated the inflammatory response in acne. Moreover, TRQ significantly suppressed key factors such as TNF-α, JNK2, IL-17A, C/EBPβ, IL-6, and IL-1β in the IL-17 and TNF signaling pathways. Furthermore, TRQ also demonstrated a significant inhibition in the expression of TNF-α and IL-1β in the skin tissues of acne vulgaris mice ConclusionOur findings suggest that TRQ may effectively inhibit the IL-17/TNF signaling pathway by suppressing the expression of TNF-α and IL-1β, making it a potential candidate for the treatment of acne

Multi-omics analysis of zebrafish response to tick saliva reveals biological processes associated with alpha-Gal syndrome

The alpha-Gal syndrome (AGS) is a tick-borne allergy. A multi-omics approach was used to determine the effect of tick saliva and mammalian meat consumption on zebrafish gut transcriptome and proteome. Bioinformatics analysis using R software was focused on significant biological and metabolic pathway changes associated with AGS. Ortholog mapping identified highly concordant human ortholog genes for the detection of disease-enriched pathways. Tick saliva treatment increased zebrafish mortality, incidence of hemorrhagic type allergic reactions and changes in behavior and feeding patterns. Transcriptomics analysis showed downregulation of biological and metabolic pathways correlated with anti-alpha-Gal IgE and allergic reactions to tick saliva affecting blood circulation, cardiac and vascular smooth muscle contraction, behavior and sensory perception. Disease enrichment analysis revealed downregulated orthologous genes associated with human disorders affecting nervous, musculoskeletal, and cardiovascular systems. Proteomics analysis revealed suppression of pathways associated with immune system production of reactive oxygen species and cardiac muscle contraction. Underrepresented proteins were mainly linked to nervous and metabolic human disorders. Multi-omics data revealed inhibition of pathways associated with adrenergic signaling in cardiomyocytes, and heart and muscle contraction. Results identify tick saliva-related biological pathways supporting multisystemic organ involvement and linking α-Gal sensitization with other illnesses for the identification of potential disease biomarkers.

Secreted proteins in plasma and placenta as novel non-invasive biomarkers for intrahepatic cholestasis of pregnancy: A case-control study

BackgroundIntrahepatic cholestasis of pregnancy (ICP) is likely to lead to unfavorable consequences. Total bile acid (TBA) is thought to be the sole ICP indicator available as of now, but it comes with some kind of restrictions in terms of sensitivity and specificity. We were endeavoring to find potential diagnostic biomarkers for ICP in this investigation. MethodsThis case-control study with a prospective nature included 40 females in the stage of pregnancy who were diagnosed with ICP. It also included another 20 females who were also pregnant but with sound physical condition(control). Placental and plasma samples were collected from all females that were in the stage of pregnancy, except for 20 ICP patients, in which only plasma was collected. We used four-dimensional data-independent acquisition followed by enzyme-linked immunosorbent assay and immunohistochemistry to identify and validate plasma and placental profiles in ICP patients and controls. Bioinformatics was adopted in an effort to demonstrate the relevant biological processes and signalling pathways. Correlation analysis was used to analyse the consistency of tissue and plasma protein expression and the correlation between sequencing and experimental results. ResultsThe expression levels of nectin-1 (NECTIN1), Kunitz-type protease inhibitor 1 (SPINT1), and inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3) were remarkably higher in ICP patients than in controls. However, heparin cofactor 2 (SERPIND1) expression levels in female participants in the stage of pregnancy who were diagnosed with ICP were remarkably lower than those pregnant females with good physical fitness. In addition to the negative correlation between SERPIND1 and TBA, NECTIN1, SPINT1, and ITIH3 expression positively correlated with TBA. Area under the receiver operating characteristic curve (AUC) values of 0.7925, 0.8313, 0.8163, and 0.9025, respectively, were used to assess the diagnostic accuracies of NECTIN1, SPINT1, ITIH3, and SERPIND1. AUC (0.9438) was considerably greater when NECTIN1, SPINT1, and SERPIND1 were integrated, according to binary logistic regression. The AUC of the ROC curve for various combinations of SERPIND1 and other indicators was higher than itself, thus providing a more reliable ICP diagnosis. Furthermore, according to the bioinformatics analysis, the NECTIN1, SPINT1, ITIH3, and SERPIND1 were identified as secreted proteins because they were localized in the extracellular region. ConclusionsThis research discovered new non-invasive ICP indicators. On top of this, it sheds new light on the crucial diagnostic function of secreted proteins in ICP.

Ferroptosis-related gene MTF-1 as a novel prognostic biomarker in low-grade glioma and its correlation with immune infiltration

BackgroundMetal-responsive transcription factor-1 performs a necessary position in a range of cancers. It is unknown, though, how the prognosis of patients with low-grade gliomas is related to immune infiltration. MethodThe Cancer Genome Atlas database was used in this investigation to evaluate MTF-1 transcription in low-grade glioma and healthy brain tissues, and immunohistochemistry was used to confirm MTF-1 levels. By using functional enrichment analysis and R software, the putative biological roles and signaling pathways connected to MTF-1 in LGG as well as its prognostic significance were investigated. Further research was done on the connection involving MTF-1 and tumor mutational burden in LGG. Finally, the research evaluated how MTF-1 and immune cell infiltration are related. ResultsWe noticed that the WHO grade, 1p/19q codeletion, and older age were all substantially linked with MTF-1 overexpression in low-grade gliomas. OS and disease-specific survival were significantly lowered as a result of MTF-1 transcription. MTF-1 was recognized as an independent OS prognostic predictor with a poor prognosis by multifactorial Cox analysis. Functional enrichment analysis revealed that the primary enrichment pathways were chemical carcinogenesis—receptor activation and the generation of miRNAs implicated in gene suppression by miRNA. Additionally, there was a negative correlation between MTF-1 overexpression and the degree of immune cell infiltration in neutrophils and DC. ConclusionMTF-1 may be a novel prognostic biomarker.

Network pharmacology-based and molecular docking-based analysis of You-Gui-Yin for the treatment of osteonecrosis of the femoral head.

You-Gui-Yin (YGY) is a classic prescription for warming up kidney-Yang and filling in kidney essence in traditional Chinese medicine, and has been used to treat osteonecrosis of the femoral head (ONFH) effectively. However, the underlying mechanisms are still unknown. This study is aimed at exploring the possible mechanisms of action of the YGY in the treatment of ONFH based on network pharmacology and molecular docking. TCMSP was used to screen the active components and targets of YGY. The disease targets of ONFH were collected in several public databases. The protein-protein interaction (PPI) Network was constructed using the STRING platform. The Metascape database platform was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The key active components and core target proteins of YGY in the treatment of ONFH were verified by the molecular docking. 120 active components were obtained from YGY, among which 73 components were hit by the 117 drug-disease intersection targets. Key effective components included quercetin, kaempferol, beta-sitosterol, glycitein, beta-carotene, and so on. Core target proteins included ALB, AKT1, TNF, IL6, TP53, and so on. According to GO and KEGG analyses, there were 1762 biological processes, 94 cellular component, 138 molecular function and 187 signaling pathways involved. we selected the top 20 biological processes (BP), cellular components (CC), molecular functions (MF) and signaling pathways to draw the heat maps, showing that Lipid and atherosclerosis signaling pathway, IL-17 signaling pathway, HIF-1 signaling pathway, relaxin signaling pathway and MAPK signaling pathway and other pathways may play a key role in the treatment of ONFH by YGY. The results of molecular docking showed that key effective components and corresponding core target proteins exhibited the good binding activity. YGY can treat ONFH through multicomponents, multitargets, and multipathways, which provides a reference for the subsequent research, development of targeted drugs and clinical application.

Integrating Network Pharmacology and Transcriptomic Strategies to Explore the Pharmacological Mechanism of Paeoniflorin Exerts Antidepressant Effects

Background:: Paeoniflorin has been proven to have neuroprotective and antidepressant effects in several studies. However, there is currently no comprehensive elaboration of its antidepressant effects through network pharmacology combined with transcriptomics analysis. The purpose of this study is to explore the potential mechanisms by which paeoniflorin exerts its antidepressant effects using network pharmacology and transcriptomics sequencing approaches. Methods:: We utilized metascape to enrich the intersecting targets for paeoniflorin and depression for enrichment analyses. Additionally, we employed Cytoscape software to construct target pathway networks. For the screening of differentially expressed genes (DEGs) altered by paeoniflorin, we sequenced mRNA from the hippocampal tissue of CUMS model mice using the BMKCloud platform. We further enriched their biological functions and signaling pathways by using the Omishare database. The study utilized a combination of network pharmacology and transcriptomics analysis to evaluate the interactions between paeoniflorin and key targets. The results were then verified through a molecular docking process and a subsequent Western blot experiment. Results:: According to a comprehensive analysis, paeoniflorin has 19 key targets that are closely related to its therapeutic effect. Molecular docking revealed that paeoniflorin has a high affinity for HIF-1α, VEGFA, and other targets. Furthermore, protein expression and immunofluorescence staining analysis showed that paeoniflorin significantly increased the expression level of HIF-1α and VEGFA in the hippocampus of depression model mice. Conclusion:: These findings suggest that paeoniflorin may have therapeutic potential in depression through the activation of the HIF-1α-VEGFA pathway.

SNORD3A acts as a potential prognostic and therapeutic biomarker in gastric cancer

BackgroundAlthough SNORD3A has been implicated in cancer progression, its specific roles and underlying mechanisms in gastric cancer (GC) remain poorly understood. We analysed SNORD3A expression using TCGA data and evaluated patient survival via Kaplan‒Meier curves. Additionally, we conducted GO-KEGG enrichment analysis to identify relevant biological processes and signaling pathways, while ssGSEA was used to assess the correlation between SNORD3A and cancer immune infiltrates. Furthermore, we explored the relationship between SNORD3A and immunotherapy response through TIDE. We verified SNORD3A expression using real-time qPCR and assessed cell proliferation, migration, and invasion via CCK8 and Transwell migration and invasion assays. ResultsOur results revealed that SNORD3A was significantly upregulated in GC, with high expression correlating with poor survival. SNORD3A and related genes were primarily enriched in the insulin/insulin-related growth factor signaling pathway. We also observed negative associations between SNORD3A expression and several immune cells, including activated dendritic cells, CD56bright natural killer cells, central memory CD8 T cells, effector memory CD8 T cells, effector memory CD4 T cells, eosinophils, immature dendritic cells, macrophages, mast cells, MDSCs, memory B cells, monocytes, neutrophil cells, plasmacytoid dendritic cells, regulatory T cells, and T follicular helper cells. High SNORD3A expression also correlated with a poorer response to immunotherapy. Finally, inhibition of SNORD3A suppressed cell proliferation, migration, and invasion. ConclusionsOur findings suggest that SNORD3A plays a catalytic role in the proliferation, migration and invasiveness of GC and may have potential as a diagnostic biomarker and therapeutic target for GC.How to cite: Wang Q, Li Y, Niu X, et al. SNORD3A acts as a potential prognostic and therapeutic biomarker in gastric cancer. Electron J Biotechnol 2023; 67. https://doi.org/10.1016/j.ejbt.2023.08.004.

Organotypic 3D Cell-Architecture Impacts the Expression Pattern of miRNAs-mRNAs Network in Breast Cancer SKBR3 Cells.

Currently, most of the research on breast cancer has been carried out in conventional two-dimensional (2D) cell cultures due to its practical benefits, however, the three-dimensional (3D) cell culture is becoming the model of choice in cancer research because it allows cell-cell and cell-extracellular matrix (ECM) interactions, mimicking the native microenvironment of tumors in vivo. In this work, we evaluated the effect of 3D cell organization on the expression pattern of miRNAs (by Small-RNAseq) and mRNAs (by microarrays) in the breast cancer SKBR3 cell line and analyzed the biological processes and signaling pathways regulated by the differentially expressed protein-coding genes (DE-mRNAs) and miRNAs (DE-microRNAs) found in the organoids. We obtained well-defined cell-aggregated organoids with a grape cluster-like morphology with a size up to 9.2 × 105 μm3. The transcriptomic assays showed that cell growth in organoids significantly affected (all p < 0.01) the gene expression patterns of both miRNAs, and mRNAs, finding 20 upregulated and 19 downregulated DE-microRNAs, as well as 49 upregulated and 123 downregulated DE-mRNAs. In silico analysis showed that a subset of 11 upregulated DE-microRNAs target 70 downregulated DE-mRNAs. These genes are involved in 150 gene ontology (GO) biological processes such as regulation of cell morphogenesis, regulation of cell shape, regulation of canonical Wnt signaling pathway, morphogenesis of epithelium, regulation of cytoskeleton organization, as well as in the MAPK and AGE-RAGE signaling KEGG-pathways. Interestingly, hsa-mir-122-5p (Fold Change (FC) = 15.4), hsa-mir-369-3p (FC = 11.4), and hsa-mir-10b-5p (FC = 20.1) regulated up to 81% of the 70 downregulated DE-mRNAs. The organotypic 3D cell-organization architecture of breast cancer SKBR3 cells impacts the expression pattern of the miRNAs-mRNAs network mainly through overexpression of hsa-mir-122-5p, hsa-mir-369-3p, and hsa-mir-10b-5p. All these findings suggest that the interaction between cell-cell and cell-ECM as well as the change in the culture architecture impacts gene expression, and, therefore, support the pertinence of migrating breast cancer research from conventional cultures to 3D models.

New gene signature from the dominant infiltration immune cell type in osteosarcoma predicts overall survival

The immune microenvironment of osteosarcoma (OS) has been reported to play an important role in disease progression and prognosis. However, owing to tumor heterogeneity, it is not ideal to predict OS prognosis by examining only infiltrating immune cells. This work aimed to build a prognostic gene signature based on similarities in the immune microenvironments of OS patients. Public datasets were used to examine the correlated genes, and the most consistent dominant infiltrating immune cell type was identified. The LASSO Cox regression model was used to establish a multiple-gene risk prediction signature. A nine-gene prognostic signature was generated from the correlated genes for M0 macrophages and then proven to be effective and reliable in validation cohorts. Signature comparison indicated the priority of the signature. Multivariate Cox regression models indicated that the signature risk score is an independent prognostic factor for OS patients regardless of the Huvos grade in all datasets. In addition, the results of the association between the signature risk score and chemotherapy sensitivity also showed that there was no significant difference in the sensitivity of any drugs between the low- and high-risk groups. A GSEA of GO and KEGG pathways found that antigen processing- and presentation-related biological functions and olfactory transduction receptor signaling pathways have important roles in signature functioning. Our findings showed that M0 macrophages were the dominant infiltrating immune cell type in OS and that the new gene signature is a promising prognostic model for OS patients.

Ovarian follicle transcriptome dynamics reveals enrichment of immune system process during transition from small to large follicles in cyclic Indian Ghoongroo pigs

Ovarian follicular development is a critical determinant of reproductive performance in litter bearing species like pigs, wherein economic gains depend on litter size. The study aimed to gain insight into the differentially expressed genes (DEGs) and signalling pathways regulating follicular growth and maturation in Ghoongroo pigs. Transcriptome profiling of porcine small follicles (SF) and large follicles (LF) was conducted using NovaSeq600 sequencing platform and DEGs were identified using DESeq2 with threshold of Padj. < 0.05 and log2 fold change cut off 0.58 (LF vs. SF). Functional annotations and bioinformatics analysis of DEGs were performed to find out biological functions, signalling pathways and hub genes regulating follicular dynamics. Transcriptome analysis revealed 709 and 479 genes unique to SF and LF stages, respectively, and 11,993 co-expressed genes in both the groups. In total, 507 DEGs (284 upregulated and 223 downregulated) were identified, which encoded for diverse proteins including transcription factors (TFs). These DEGs were functionally linked to response to stimulus, lipid metabolic process, developmental process, extracellular matrix organisation along with the immune system process, indicating wide-ranging mechanisms associated with follicular transition. The enriched KEGG pathways in LF stage consisted of ovarian steroidogenesis, cholesterol and retinol metabolism, cell adhesion molecules, cytokine receptor interaction and immune signalling pathways, depicting intra-follicular control of varied ovarian function. The hub gene analysis revealed APOE, SCARB1, MMP9, CYP17A1, TYROBP as key regulators of follicular development. This study identified candidate genes and TFs providing steroidogenic advantage to LFs which makes them fit for selection into the ovulatory pool of follicles.

Validation of a Novel Cuproptosis-Related Prognostic Gene Marker and Differential Expression Associated with Lung Adenocarcinoma.

Cuproptosis induction is seen as a promising alternative for immunotherapies and targeted therapies in breast cancer. The objective of this research was to examine the prognostic and biological importance of cuproptosis-related genes (CRGs) in lung adenocarcinoma (LUAD). The following methods were used: GSE10072 dataset and TCGA database analysis, differential expression analysis of CRGs, and biological function (BP) and signaling pathway enrichment analysis, prognostic analysis and clinical analysis of CRGs, construction of the prognostic signature and RNA modified genes and miRNA analysis of CRGs in LUAD, immunoinfiltration analysis and immunohistochemical staining of DβH, UBE2D3, SOD1, UBE2D1 and LOXL2. AOC1, ATOX1, CCL8, CCS, COX11, CP, LOXL2, MAP2K2, PDK1, SCO2, SOD1, UBE2D1, UBE2D3 and VEGFA showed significantly higher expression, while ATP7B, DβH, PDE3B, SLC31A2, UBE2D2, UBE2D4 and ULK2 showed lower expression in LUAD tissues than normal tissues. We also found that ATP7B (4%), AOC1 (3%) PDE3B (2%), DβH (2%), CP (1%), ULK2 (1%), PDK1 (1%), LOXL2 (1%) and UBE2D3 (1%) showed higher mutation frequencies. The univariate Cox analysis was used to identify CRGs that have prognostic value. It identified 21 genes that showed significant prognostic value, containing DβH, UBE2D3, SOD1, UBE2D1 and LOXL2. Patients with DβH up-expression have a longer survival time and patients with UBE2D3, SOD1, UBE2D1 and LOXL2 down-expression also have a longer survival time. hsa-miR-29c-3p, hsa-miR-29a-3p, hsa-miR-181c-5p, hsa-miR-1245a, etc., play an important role in the miRNA regulatory network, and in LUAD, miR-29a, miR-29c and miR-181c high expression survival was longer, and miR-1245a low expression survival was longer. We also performed an analysis to examine the relationships between DβH, LOXL2, SOD1, UBE2D1 and UBE2D3 and immune infiltration in LUAD, including B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils and DCs. DβH, UBE2D3, SOD1, UBE2D1, and LOXL2 are potential candidates implicated in LUAD and can be further explored for their application as diagnostic, prognostic, and therapeutic biomarkers for LUAD.

Exploring the mechanism of action of Qian Lie Xing Fang during the treatment of benign prostatic hyperplasia via network pharmacology and molecular dynamics simulation analyses.

This study aimed to explore the historical research progress on benign prostatic hyperplasia from the perspective of traditional Chinese medicine theory and the treatment of benign prostatic hyperplasia (BPH) with Qian Lie Xing Fang (QLXF) via the warming and tonifying of kidney yang, promotion of blood circulation, and clearing of meridians. First, network pharmacology analysis was used to screen and identify possible pathways for BPH treatment with QLXF. Subsequently, molecular docking analysis helped explore the mechanism of action by which the components of QLXF affected androgen receptor (AR) and type 5 phosphodiesterase inhibitor (PDE-5) levels. Targets for treatment with QLXF were identified from the online Mendelian inheritance in man and DisGeNET databases. BPH-related genes were identified using GeneCards and online Mendelian inheritance in man databases, and their intersection was used to construct a protein-protein interaction network analysis graph. Subsequently, gene ontology and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses were performed. The semiflexible docking of the ingredients of QLXF acting on the 2 targets was performed via molecular docking and molecular dynamics simulation, to elucidate the mechanism of action by which the active ingredients affect AR and PDE-5 levels further. This enabled us to explore the pattern of interactions between small active ingredient molecules, the target protein, and the stability after binding at the microscopic level. Gene ontology enrichment analysis showed that QLXF affected several processes, such as DNA transcription factor binding, kinase binding, protein homodimerization activity, protein structure domain-specific binding, and protein-coupled amine receptor activity in BPH patients. KEGG results showed that chemical carcinogenic reactive oxidative species and the JAK-STAT, Pl3k-Akt, FoxO, NF-κB, and other pathways were significantly enriched. Conducting molecular docking studies to investigate the interaction of active components from QLXF with AR and PDE-5, it was found that MOL002260 may possess the potential to inhibit PDE-5 activity, while MOL010578 may exhibit the capability to inhibit AR activity. QLXF is closely associated with various biological processes and KEGG signaling pathways related to BPH. The active ingredients of QLXF were investigated for their interactions with AR and PDE-5, with a primary focus on the small molecules MOL002260 and MOL010578.

Pathway-driven analysis of synthetic lethal interactions in cancer using perturbation screens.

Synthetic lethality offers a promising approach for developing effective therapeutic interventions in cancer when direct targeting of driver genes is impractical. In this study, we comprehensively analyzed large-scale CRISPR, shRNA, and PRISM screens to identify potential synthetic lethal (SL) interactions in pan-cancer and 12 individual cancer types, using a new computational framework that leverages the biological function and signaling pathway information of key driver genes to mitigate the confounding effects of background genetic alterations in different cancer cell lines. This approach has successfully identified several putative SL interactions, including KRAS-MAP3K2 and APC-TCF7L2 in pan cancer, and CCND1-METTL1, TP53-FRS3, SMO-MDM2, and CCNE1-MTOR in liver, blood, skin, and gastric cancers, respectively. In addition, we proposed several FDA-approved cancer-targeted drugs for various cancer types through PRISM drug screens, such as cabazitaxel for VHL-mutated kidney cancer and alectinib for lung cancer with NRAS or KRAS mutations. Leveraging pathway information can enhance the concordance of shRNA and CRISPR screens and provide clinically relevant findings such as the potential efficacy of dasatinib, an inhibitor of SRC, for colorectal cancer patients with mutations in the WNT signaling pathway. These analyses revealed that taking signaling pathway information into account results in the identification of more promising SL interactions.

Effect and molecular mechanism of Sulforaphane alleviates brain damage caused by acute carbon monoxide poisoning:Network pharmacology analysis, molecular docking, and experimental evidence.

Sulforaphane (SFN) has attracted much attention due to its ability on antioxidant, anti-inflammatory, and anti-apoptotic properties, while its functional targets and underlying mechanism of action on brain injury caused by acute carbon monoxide poisoning (ACOP) have not been fully elucidated. Herein, we used a systematic network pharmacology approach to explore the mechanism of SFN in the treatment of brain damage after ACOP. In this study, the results of network pharmacology demonstrated that there were a total of 81 effective target genes of SFN and 36 drug-disease targets, which were strongly in connection with autophagy-animal signaling pathway, drug metabolism, and transcription disorders in cancer. Upon the further biological function and KEGG signaling pathway enrichment analysis, a large number of them were involved in neuronal death, reactive oxygen metabolic processes and immune functions. Moreover, based on the results of bioinformatics prediction associated with multiple potential targets and pathways, the AMP-activated protein kinase (AMPK) signaling pathway was selected to elucidate the molecular mechanism of SFN in the treatment of brain injury caused by ACOP. The following molecular docking analysis also confirmed that SFN can bind to AMPKα well through chemical bonds. In addition, an animal model of ACOP was established by exposure to carbon monoxide in a hyperbaric oxygen chamber to verify the predicted results of network pharmacology. We found that the mitochondrial ultrastructure of neurons in rats with ACOP was seriously damaged, and apoptotic cells increased significantly. The histopathological changes were obviously alleviated, apoptosis of cortical neurons was inhibited, and the number of Nissl bodies was increased in the SFN group as compared with the ACOP group (p < .05). Besides, the administration of SFN could increase the expressions of phosphorylated P-AMPK and MFN2 proteins and decrease the levels of DRP1, Caspase3, and Casapase9 proteins in the brain tissue of ACOP rats. These findings suggest that network pharmacology is a useful tool for traditional Chinese medicine (TCM) research, SFN can effectively inhibit apoptosis, protect cortical neurons from the toxicity of carbon monoxide through activating the AMPK pathway and may become a potential therapeutic strategy for brain injury after ACOP.

Over-representation analysis of angiogenic factors in immunosuppressive mechanisms in neoplasms and neurological conditions during COVID-19

BackgroundRecent studies emphasized the necessity to identify key (human) biological processes and pathways targeted by the Coronaviridae family of viruses, especially Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Coronavirus Disease (COVID-19) caused up to 33–55 % death rates in COVID-19 patients with malignant neoplasms and Alzheimer's disease. Given this scenario, we identified biological processes and pathways involved in various diseases which are most likely affected by COVID-19. MethodsThe COVID-19 DisGeNET data set (v4.0) contains the associations between various diseases and human genes known to interact with viruses from Coronaviridae family and were obtained from the IntAct Coronavirus data set annotated with DisGeNET data. We constructed the disease-gene network to identify genes that are involved in various comorbid diseased states. Communities from the disease-gene network were identified using Louvain method and functional enrichment through over-representation analysis methodology was used to discover significant biological processes and pathways shared between COVID-19 and other diseases. ResultThe COVID-19 DisGeNET data set (v4.0) comprised of 828 human genes and 10,473 diseases (including various phenotypes) that together constituted nodes in the disease-gene network. Each of the 70,210 edges connects a human gene with an associated disease. The top 10 genes linked to most number of diseases were VEGFA, BCL2, CTNNB1, ALB, COX2, AGT, HLA-A, HMOX1, FGF2 and COMT. The most vulnerable group of patients thus discovered had comorbid conditions such as carcinomas, malignant neoplasms and Alzheimer's disease. Finally, we identified 15 potentially useful biological processes and pathways for improved therapies. Vascular endothelial growth factor (VEGF) is the key mediator of angiogenesis in cancer. It is widely distributed in the brain and plays a crucial role in brain inflammation regulating the level of angiopoietins. With a degree of 1899, VEGFA was associated with maximum number of diseases in the disease-gene network. Previous studies have indicated that increased levels of VEGFA in the blood results in dyspnea, Pulmonary Edema (PE), Acute Lung Injury (ALI) and Acute Respiratory Distress Syndrome (ARDS). In case of COVID-19 patients with neoplasms and other neurological symptoms, our results indicate VEGFA as a therapeutic target for inflammation suppression. As VEGFs are known to disproportionately affect cancer patients, improving endothelial permeability and vasodilation with anti-VEGF therapy could lead to suppression of inflammation and also improve oxygenation. As an outcome of our study, we make case for clinical investigations towards anti-VEGF therapies for such comorbid conditions affected by COVID-19 for better therapeutic outcomes.

The role of matrix stiffness in breast cancer progression: a review.

The significance of matrix stiffness in cancer development has been investigated in recent years. The gradual elastic force the extracellular matrix imparts to cells, known as matrix stiffness, is one of the most important types of mechanical stimulation. Increased matrix stiffness alters the biological activity of cells, which promotes the growth of numerous malignancies, including breast cancer. Comprehensive studies have demonstrated that increasing matrix stiffness activates molecular signaling pathways that are closely linked to breast cancer progression. There are many articles exploring the relationship between mechanism hardness and breast cancer, so we wanted to provide a systematic summary of recent research advances. In this review, we briefly introduce the mechanism of matrix stiffness in breast cancer, elaborate on the effect of extracellular matrix stiffness on breast cancer biological behavior and signaling pathways, and finally, we will talk about breast cancer treatment that focuses on matrix stiffness.

Pan-cancer analysis identifies RNF43 as a prognostic, therapeutic and immunological biomarker

BackgroundRING finger protein 43 (RNF43), an E3 ubiquitin ligase, is a homologous gene mutated in several cancers. However, the pan-cancer panoramic picture of RNF43 and its predictive value for tumor immune phenotypes and immunotherapeutic efficacy are still largely unclear. Our study aims to clarify the functions of RNF43 in predicting the prognosis, immune signature, and immunotherapeutic efficacy in pan-cancer.MethodsBy using RNA-seq, mutation, and clinical data from the TCGA database, the expression levels and prognostic significance of RNF43 in pan-cancer were analyzed. The genetic alteration characteristics of RNF43 were displayed by the cBioPortal database. Gene Set Enrichment Analysis (GSEA) was performed to investigate the potential biological functions and signaling pathways modulated by RNF43 in cancers. The relationship of RNF43 expression with immune cell infiltration, and immune modulators expression was interpreted by the ESTIMATE algorithm, CIBERSORT algorithm, and TISIDB database. The correlations between RNF43, microsatellite instability (MSI), and tumor mutation burden (TMB) were also investigated. Furthermore, the predictive value of RNF43 for immunotherapeutic efficacy and drug sensitivity was further illustrated. Besides, immunohistochemistry (IHC) was employed to validate the expression of the RNF43 in different cancer types by our clinical cohorts, including patients with lung cancer, sarcoma, breast cancer, and kidney renal clear cell carcinoma.ResultsThe results demonstrated that RNF43 was abnormally expressed in multiple cancers, and RNF43 is a critical prognosis-related factor in several cancers. RNF43 was frequently mutated in several cancers with a high frequency of 4%, and truncating mutation was the most frequent RNF43 mutation type. RNF43 expression was linked to the abundance of several immune cell types, including CD8+ T cells, B cells, and macrophages within the tumor immune microenvironment. Furthermore, RNF43 expression was significantly correlated with the efficacy of anti-PD-1/PD-L1 treatment, and it could predict the sensitivity of various anti-cancer drugs. Finally, IHC explored and validated the different expression levels of RNF43 in different cancers by our clinical samples.ConclusionOur results first present the expression pattern and the mutation signature of RNF43, highlighting that RNF43 is an important prognostic biomarker in pan-cancer. Furthermore, RNF43 seems to be a critical modulator in the tumor immune microenvironment and can function as a promising biomarker for predicting the immunotherapeutic efficacy of anti-PD-1/PD-L1 treatment, and drug sensitivity in cancer treatment.

Identification of oxidative stress-related biomarkers associated with the development of acute-on-chronic liver failure using bioinformatics

Acute-on-chronic liver failure (ACLF) is a serious stage of chronic liver disease with high short-term mortality and no definitely effective treatment. Oxidative stress (OS) is involved in the development of ACLF. OS-related genes targeted therapy may provide additional assistance for the treatment of ACLF. ACLF related gene sets and oxidative stress-related genes (OSGs) were respectively downloaded from gene expression omnibus (GEO) database and GeneCards database for integrated bioinformatics analyses (functional enrichment, weighted gene co-expression network and immune cells infiltration). Immune-related differentially expressed oxidative stress-related genes (DEOSGs) in ACLF were used for construction of protein–protein interaction (PPI) network in which hub genes were screened out. Hub genes with consistently good diagnostic or prognostic value for ACLF in four gene sets were named as key genes. DEOSGs were significantly enriched in biological process and signaling pathways related to inflammation, immune response and oxidative stress. Six key genes (MPO, CCL5, ITGAM, TLR2, TLR4, and TIMP1) were identified and found to be highly correlated with immune response and metabolic process. This study deepened our understanding of the impact of oxidative stress on the pathogenesis and prognosis of ACLF and provided more insights into the prediction of prognosis and molecular targeted therapy in ACLF.

Functional enrichment analysis of mutated genes in children with hyperthyroidism.

Hyperthyroidism in Chinese children is relatively high and has been increasing in recent years, which has a significant impact on their healthy development. Hyperthyroidism is a polygenic disorder that presents greater challenges in terms of prediction and treatment than monogenic diseases. This study aims to elucidate the associated functions and gene sets of mutated genes in children with hyperthyroidism in terms of the gene ontology through GO enrichment analysis and in terms of biological signaling pathways through KEGG enrichment analysis, thereby enhancing our understanding of the expected effects of multiple mutated genes on hyperthyroidism in children. Whole-exome sequencing was performed on the DNA samples of children with hyperthyroidism. Screening for pathogenic genes related to hyperthyroidism in affected children was performed using the publicly available disease databases Malacards, MutationView, and Clinvar, and the functions and influences of the identified pathogenic genes were analyzed using statistical analysis and the gene enrichment approach. Through GO enrichment analysis, it was found that the most significant gene ontology enrichment was the function "hormone activity" in terms of gene ontology molecular function. The corresponding mutated genes set that has common effects on hyperthyroidism in children included TG, CALCA, POMC, CGA, PTH, GHRL, FBN1, TRH, PRL, LEP, ADIPOQ, INS, GH1. The second most significant gene ontology enrichment was the function "response to peptide hormone" in terms of biological process. The corresponding mutated genes set that has common effects on hyperthyroidism in children included LRP6, TSC2, KANK1, COL1A1, CDKN1B, POMC, STAT1, MEN1, APC, GHRL, TSHR, GJB2, FBN1, GPT, LEP, ADIPOQ, INS, GH1. Through KEGG enrichment analysis, it was found that the most significant biological signaling pathway enrichment was the pathway "Thyroid hormone signaling pathway" function. The corresponding mutated genes set that has common effects on hyperthyroidism in children included NOTCH3, MYH7, TSC2, STAT1, MED13L, MAP2K2, SLCO1C1, SLC16A2, and THRB. The second most significant biological signaling pathway enrichment was the pathway "Hypertrophic cardiomyopathy" in terms of biological process. The corresponding mutated genes set that has common effects on hyperthyroidism in children included IGF1, CACNA1S, MYH7, IL6, TTN, CACNB2, LAMA2, and DMD. The mutated genes in children with hyperthyroidism were closely linked to function involved in "hormone activity" and "response to peptide hormone" in terms of the biological signaling pathway, and to the functional pathways involved in "Thyroid hormone signaling pathway" and "Hypertrophic cardiomyopathy" in terms of the biological signaling pathway.

Identification of the potential regulatory interactions in rheumatoid arthritis through a comprehensive analysis of lncRNA-related ceRNA networks

ObjectiveThis study aimed at constructing a network of competing endogenous RNA (ceRNA) in the synovial tissues of rheumatoid arthritis (RA). It seeks to discern potential biomarkers and explore the long non-coding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) axes that are intricately linked to the pathophysiological mechanisms underpinning RA, and providing a scientific basis for the pathogenesis and treatment of RA.MethodsMicroarray data pertaining to RA synovial tissue, GSE103578, GSE128813, and GSE83147, were acquired from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo). Conducted to discern both differentially expressed lncRNAs (DELncRNAs) and differentially expressed genes (DEGs). A ceRNA network was obtained through key lncRNAs, key miRNAs, and key genes. Further investigations involved co-expression analyses to uncover the lncRNA-miRNA-mRNA axes contributing to the pathogenesis of RA. To delineate the immune-relevant facets of this axis, we conducted an assessment of key genes, emphasizing those with the most substantial immunological correlations, employing the GeneCards database. Finally, gene set enrichment analysis (GSEA) was executed on the identified key lncRNAs to elucidate their functional implications in RA.ResultsThe 2 key lncRNAs, 7 key miRNAs and 6 key genes related to the pathogenesis of RA were obtained, as well as 2 key lncRNA-miRNA-mRNA axes (KRTAP5-AS1-hsa-miR-30b-5p-PNN, XIST-hsa-miR-511-3p/hsa-miR-1277-5p-F2RL1). GSEA of two key lncRNAs obtained biological processes and signaling pathways related to RA synovial lesions.ConclusionThe findings of this investigation hold promise in furnishing a foundational framework and guiding future research endeavors aimed at comprehending the etiology and therapeutic interventions for RA.