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OBJECTIVE: Precancerous lesions of gastric cancer (PLGC) are key pathological stages in the transformation of gastric "inflammation-cancer", and timely and effective intervention at this stage is of great importance in the prevention and treatment of gastric cancer. Zhiwei Fuwei Pills (ZWFW), as a traditional Chinese medicine formulation, has been proven to have good clinical efficacy in the treatment of PLGC, but its specific mechanism of action has not been fully explained. Thus, this study validated the efficacy and explored the potential mechanisms of ZWFW in treating PLGC by integrating network pharmacology analyses and experimental verification. METHODS: The TCMSP database was used to obtain the active ingredients of ZWFW and their corresponding targets, and the GeneCards database was used to retrieve PLGC-related targets. The intersecting targets between ZWFW and PLGC were obtained through mapping, and protein-protein interaction (PPI) networks and "drug-active ingredient-target" networks were constructed by using Cytoscape software. The DAVID database was used for GO functional enrichment analysis and KEGG pathway enrichment analysis. AutoDockTools software was used for molecular docking of key active ingredients and key targets. In order to verify the analysis results of network pharmacology, TEM and H&E were used to observe the effects of different dosage groups of ZWFW on gastric mucosal microvasculature in PLGC rats. Subsequently, the ELISA, IF, IHC, RT-PCR and western blot were used to detected the expression levels of relevant targets in the tissues, so as to verify the potential mechanism of ZWFW in intervening PLGC. RESULTS: After the screening, 258 effective active ingredients and 325 targets were obtained, and 1294 disease-related targets were determined, resulting in 139 intersection targets through mapping. The KEGG enrichment results showed that PI3K/Akt and HIF-1 signaling pathway might play important roles in the treatment mechanism of PLGC. The molecular docking results showed that active ingredients of ZWFW all had a strong affinity and stable structure with key targets, including AKT1 and VEGF. In vivo experiments confirmed that ZWFW could improve gastric mucosal microvascular abnormalities in PLGC, effectively intervene in gastric mucosal pathological grading. Meanwhile, compared with the model group, this formulation could reduce the expression levels of PI3K, Akt, mTOR, HIF-1α, and VEGF in gastric mucosa, showing a dose-effect relationship. CONCLUSION: ZWFW can intervene in the neovascularization and pathological evolution of PLGC, and this mechanism of action may be achieved by inhibiting abnormal activation of the PI3K/Akt/mTOR/HIF-1α/VEGF signaling pathway.

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Medicamentos Herbarios Chinos , Neovascularización Patológica , Farmacología en Red , Lesiones Precancerosas , Neoplasias Gástricas , Neoplasias Gástricas/tratamiento farmacológico , Neoplasias Gástricas/patología , Animales , Medicamentos Herbarios Chinos/farmacología , Medicamentos Herbarios Chinos/uso terapéutico , Neovascularización Patológica/tratamiento farmacológico , Masculino , Lesiones Precancerosas/tratamiento farmacológico , Lesiones Precancerosas/patología , Mapas de Interacción de Proteínas , Factor A de Crecimiento Endotelial Vascular/metabolismo , Ratas Sprague-Dawley , Ratas , Simulación del Acoplamiento Molecular , Angiogénesis

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Crosslinking mass spectrometry (MS) has emerged as an important technique for elucidating the in-solution structures of protein complexes and the topology of protein-protein interaction networks. However, the expanding user community lacked an integrated visualisation tool that helped them make use of the crosslinking data for investigating biological mechanisms. We addressed this need by developing xiVIEW, a web-based application designed to streamline crosslinking MS data analysis, which we present here. xiVIEW provides a user-friendly interface for accessing coordinated views of mass spectrometric data, network visualisation, annotations extracted from trusted repositories like UniProtKB, and available 3D structures. In accordance with recent recommendations from the crosslinking MS community, xiVIEW (i) provides a standards compliant parser to improve data integration and (ii) offers accessible visualisation tools. By promoting the adoption of standard file formats and providing a comprehensive visualisation platform, xiVIEW empowers both experimentalists and modellers alike to pursue their respective research interests. We anticipate that xiVIEW will advance crosslinking MS-inspired research, and facilitate broader and more effective investigations into complex biological systems.

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Reactivos de Enlaces Cruzados , Espectrometría de Masas , Espectrometría de Masas/métodos , Reactivos de Enlaces Cruzados/química , Programas Informáticos , Proteínas/química , Mapeo de Interacción de Proteínas/métodos , Bases de Datos de Proteínas , Interfaz Usuario-Computador , Mapas de Interacción de Proteínas

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Background: T-cell exhaustion (Tex) can be beneficial in autoimmune diseases, but its role in Graves' disease (GD), an autoimmune disorder of the thyroid, remains unknown. This study investigated Tex-related gene expression in GD patients to discern the potential contributions of these genes to GD pathogenesis and immune regulation. Methods: Through gene landscape analysis, a protein-protein interaction network of 40 Tex-related genes was constructed. mRNA expression levels were compared between GD patients and healthy control (HCs). Unsupervised clustering categorized GD cases into subtypes, revealing distinctions in gene expression, immune cell infiltration, and immune responses. Weighted gene co-expression network analysis and differential gene expression profiling identified potential therapeutic targets. RT-qPCR validation of candidate gene expression was performed using blood samples from 112 GD patients. Correlations between Tex-related gene expression and clinical indicators were analyzed. Results: Extensive Tex-related gene interactions were observed, with six genes displaying aberrant expression in GD patients. This was associated with atypical immune cell infiltration and regulation. Cluster analysis delineated two GD subtypes, revealing notable variations in gene expression and immune responses. Screening efforts identified diverse drug candidates for GD treatment. The Tex-related gene CBL was identified for further validation and showed reduced mRNA expression in GD patients, especially in cases of relapse. CBL mRNA expression was significantly lower in patients with moderate-to-severe thyroid enlargement than in those without such enlargement. Additionally, CBL mRNA expression was negatively correlated with the disease-specific indicator thyrotropin receptor antibodies. Conclusion: Tex-related genes modulate GD pathogenesis, and their grouping aids subtype differentiation and exploration of therapeutic targets. CBL represents a potential marker for GD recurrence.

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Enfermedad de Graves , Humanos , Enfermedad de Graves/genética , Enfermedad de Graves/inmunología , Masculino , Femenino , Adulto , Linfocitos T/inmunología , Linfocitos T/metabolismo , Persona de Mediana Edad , Perfilación de la Expresión Génica , Mapeo Cromosómico , Mapas de Interacción de Proteínas , Estudios de Casos y Controles , Proteínas Proto-Oncogénicas c-cbl/genética , Redes Reguladoras de Genes , Agotamiento de Células T

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Lupus nephritis (LN) is a challenging condition with limited diagnostic and treatment options. In this study, we applied 12 distinct machine learning algorithms along with Non-negative Matrix Factorization (NMF) to analyze single-cell datasets from kidney biopsies, aiming to provide a comprehensive profile of LN. Through this analysis, we identified various immune cell populations and their roles in LN progression and constructed 102 machine learning-based immune-related gene (IRG) predictive models. The most effective models demonstrated high predictive accuracy, evidenced by Area Under the Curve (AUC) values, and were further validated in external cohorts. These models highlight six hub IRGs (CD14, CYBB, IFNGR1, IL1B, MSR1, and PLAUR) as key diagnostic markers for LN, showing remarkable diagnostic performance in both renal and peripheral blood cohorts, thus offering a novel approach for noninvasive LN diagnosis. Further clinical correlation analysis revealed that expressions of IFNGR1, PLAUR, and CYBB were negatively correlated with the glomerular filtration rate (GFR), while CYBB also positively correlated with proteinuria and serum creatinine levels, highlighting their roles in LN pathophysiology. Additionally, protein-protein interaction (PPI) analysis revealed significant networks involving hub IRGs, emphasizing the importance of the interleukin family and chemokines in LN pathogenesis. This study highlights the potential of integrating advanced genomic tools and machine learning algorithms to improve diagnosis and personalize management of complex autoimmune diseases like LN.

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Algoritmos , Nefritis Lúpica , Aprendizaje Automático , Nefritis Lúpica/diagnóstico , Nefritis Lúpica/inmunología , Humanos , Femenino , Biomarcadores , Masculino , Adulto , Mapas de Interacción de Proteínas , Biología Computacional/métodos , Perfilación de la Expresión Génica , Análisis de la Célula Individual/métodos

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Steroid-induced osteonecrosis of the femoral head (SONFH) is a debilitating condition caused by long-term corticosteroid use, leading to impaired blood flow and bone cell death. The disruption of cellular processes and promotion of apoptosis by endoplasmic reticulum stress (ERS) is implicated in the pathogenesis of SONFH. We identified ERS-associated genes in SONFH and investigated their potential as therapeutic targets. We analysed the GSE123568 GEO dataset to identify differentially expressed genes (DEGs) related to ERS in SONFH. We conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, identified hub genes by protein-protein interaction (PPI) analyses, and evaluated their functions by gene set enrichment analysis (GSEA). We constructed mRNA-miRNA networks, identified potential therapeutics, and assessed immune cell infiltration. We performed cross-validation using the GEO dataset GSE74089, qRT-PCR on clinical samples from patients with SONFH and controls, and a receiver operating characteristic (ROC) curve analysis to assess the diagnostic performance of the hub genes. We identified 195 ERS-related genes in SONFH, which were primarily involved in oxidative stress, immune responses, and metabolic pathways. The PPI network suggested CXCL8, STAT3, IL1B, TLR4, PTGS2, TLR2, CASP1, CYBB, CAT, and HOMX1 to be key hub genes, which were shown by GSEA to be involved in biological pathways related to metabolism, immune modulation, and cellular integrity. We also identified 261 microRNAs (miRNAs) as well as drugs such as dibenziodolium and N-acetyl-L-cysteine that modulated inflammatory responses in SONFH. Twenty-two immune cell subtypes showed significant correlations, such as a positive correlation between activated mast cells and Tregs, and patients with SONFH had fewer dendritic cells than controls. The hub genes CYBB and TLR4 showed significant correlations with M1 macrophages and CD8 T cells, respectively. Cross-validation and qRT-PCR confirmed the upregulation of STAT3, IL1B, TLR2, and CASP1 in patients with SONFH, validating the bioinformatics findings. An ROC curve analysis confirmed the diagnostic potential of the hub genes. The top 10 hub genes show promise as ERS-related diagnostic biomarkers for SONFH. We discovered that 261 miRNAs, including hsa-miR-23, influence these genes and identified potential therapeutics such as dibenziodolium and simvastatin. Immune profiling indicated altered immune functions in SONFH, with significant correlations among immune cell types. Validation confirmed the upregulation of STAT3, IL1B, TLR2 and CASP1, which had diagnostic potential. The findings suggest potential diagnostic markers and therapeutic targets for SONFH.

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Estrés del Retículo Endoplásmico , Necrosis de la Cabeza Femoral , Mapas de Interacción de Proteínas , Humanos , Estrés del Retículo Endoplásmico/genética , Necrosis de la Cabeza Femoral/genética , Necrosis de la Cabeza Femoral/inducido químicamente , Mapas de Interacción de Proteínas/genética , MicroARNs/genética , Redes Reguladoras de Genes , Perfilación de la Expresión Génica , Esteroides/efectos adversos , Ontología de Genes , Masculino

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It is estimated that there are 544.9 million people suffering from chronic respiratory diseases in the world, which is the third largest chronic disease. Although there are various clinical treatment methods, there is no specific drug for chronic pulmonary diseases, including chronic obstructive pulmonary disease (COPD), interstitial lung disease (ILD) and idiopathic pulmonary fibrosis (IPF). Therefore, it is urgent to clarify the pathological mechanism and medication development. Single-cell transcriptome data of human and mouse from GEO database were integrated by "Harmony" algorithm. The data was standardized and normalized by using "Seurat" package, and "SingleR" algorithm was used for cell grouping annotation. The "Findmarker" function is used to find differentially expressed genes (DEGs), which were enriched and analyzed by using "clusterProfiler", and a protein interaction network was constructed for DEGs, and four algorithms are used to find the hub genes. The expression of hub genes were analyzed in independent human and mouse single-cell transcriptome data. Bulk RNA data were used to integrate by the "SVA" function, verify the expression levels of hub genes and build a diagnostic model. The L1000FWD platform was used to screen potential drugs. Through exploring the similarities and differences by integrated single-cell atlas, we found that the lung parenchymal cells showed abnormal oxidative stress, cell matrix adhesion and ubiquitination in COPD, corona virus disease 2019 (COVID-19), ILD and IPF. Meanwhile, the lung resident immune cells showed abnormal Toll-like receptor signals, interferon signals and ubiquitination. However, unlike acute pneumonia (COVID-19), chronic pulmonary disease shows enhanced ubiquitination. This phenomenon was confirmed in independent external human single-cell atlas, but unfortunately, it was not confirmed in mouse single-cell atlas of bleomycin-induced pulmonary fibrosis model and influenza virus-infected mouse model, which means that the model needs to be optimized. In addition, the bulk RNA-Seq data of COVID-19, ILD and IPF was integrated, and we found that the immune infiltration of lung tissue was enhanced, consistent with the single-cell level, UBA52, UBB and UBC were low expressed in COVID-19 and high expressed in ILD, and had a strong correlation with the expression of cell matrix adhesion genes. UBA52 and UBB have good diagnostic efficacy, and salermide and SSR-69071 can be used as their candidate drugs. Our study found that the disorder of protein ubiquitination in chronic pulmonary diseases is an important cause of pathological phenotype of pulmonary fibrosis by integrating scRNA-Seq and bulk RNA-Seq, which provides a new horizons for clinicopathology, diagnosis and treatment.

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RNA-Seq , Ubiquitina , Humanos , Animales , Ratones , Ubiquitina/metabolismo , Ubiquitina/genética , Análisis de la Célula Individual/métodos , Transcriptoma , Fibrosis Pulmonar/genética , Fibrosis Pulmonar/metabolismo , Fibrosis Pulmonar/patología , COVID-19/genética , COVID-19/metabolismo , COVID-19/virología , Perfilación de la Expresión Génica , Mapas de Interacción de Proteínas , Enfermedad Crónica , Fibrosis Pulmonar Idiopática/genética , Fibrosis Pulmonar Idiopática/patología , Fibrosis Pulmonar Idiopática/metabolismo , SARS-CoV-2/genética , Enfermedad Pulmonar Obstructiva Crónica/genética , Enfermedad Pulmonar Obstructiva Crónica/metabolismo , Análisis de Expresión Génica de una Sola Célula

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OBJECTIVE: To explore the mechanism underlying the therapeutic effect of Bufei Yishen Formula III combined with exercise rehabilitation (ECC-BYF III + ER) on chronic obstructive pulmonary disease (COPD) and further identify hub genes. MATERIALS AND METHODS: Gene Set Enrichment Analysis was used to identify the COPD-associated pathways and reversal pathways after ECC-BYF III + ER treatment. Protein-protein interaction network analysis and cytoHubba were used to identify the hub genes. These genes were verified using independent datasets, molecular docking and quantitative real-time polymerase chain reaction experiment. RESULTS: Using the high-throughput sequencing data of COPD rats from our laboratory, 49 significantly disturbed pathways were identified in COPD model compared with control group via gene set enrichment analysis (false discovery rate < 0.05). The 34 pathways were reversed after ECC-BYF III + ER treatment. In the 2306 genes of these 34 pathways, 121 of them were differentially expressed in COPD rats compared with control samples. A protein-protein interaction network comprising 111 nodes and 274 edges was created, and 34 candidate genes were identified. Finally, seven COPD hub genes (Il1b, Ccl2, Cxcl1, Apoe, Ccl7, Ccl12, and Ccl4) were well identified and verified in independent COPD rat data from our laboratory and the public dataset GSE178513. The area under the receiver operating characteristic curve values ranged from 0.86 to 1 and from 0.67 to 1, respectively. The reliability of the mentioned genes, which can bind to the active ingredients of ECC-BYF III through molecular docking, were further verified through qRT-PCR experiments. CONCLUSION: Thirty-four COPD-related pathways and seven hub genes that may be regulated by ECC-BYF III + ER were identified and well verified. The findings of this study may provide insights into the treatment and mechanism underlying COPD.

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GSEA method can circumvent the limitations of the preacquisition of DEGs for ORA and is suitable for small sample data.34 COPD-related pathways that can be regulated by ECC-BYF III + ER were identified.Seven COPD hub genes were identified and well verified in independent RNA-seq data and PCR experiment, and they may play a crucial role in TCM treatment.

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Medicamentos Herbarios Chinos , Simulación del Acoplamiento Molecular , Mapas de Interacción de Proteínas , Enfermedad Pulmonar Obstructiva Crónica , Enfermedad Pulmonar Obstructiva Crónica/genética , Enfermedad Pulmonar Obstructiva Crónica/rehabilitación , Animales , Medicamentos Herbarios Chinos/farmacología , Medicamentos Herbarios Chinos/uso terapéutico , Ratas , Masculino , Modelos Animales de Enfermedad , Terapia por Ejercicio/métodos , Condicionamiento Físico Animal , Ratas Sprague-Dawley , Terapia Combinada

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BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal and rapidly progressive motoneuron degenerative disorder. There are still no drugs capable of slowing disease evolution or improving life quality of ALS patients. Thus, autologous stem cell therapy has emerged as an alternative treatment regime to be investigated in clinical ALS. METHOD: Using Proteomics and Protein-Protein Interaction Network analyses combined with bioinformatics, the possible cellular mechanisms and molecular targets related to mesenchymal stem cells (MSCs, 1 × 106 cells/kg, intrathecally in the lumbar region of the spine) were investigated in cerebrospinal fluid (CSF) of ALS patients who received intrathecal infusions of autologous bone marrow-derived MSCs thirty days after cell therapy. Data are available via ProteomeXchange with identifier PXD053129. RESULTS: Proteomics revealed 220 deregulated proteins in CSF of ALS subjects treated with MSCs compared to CSF collected from the same patients prior to MSCs infusion. Bioinformatics enriched analyses highlighted events of Extracellular matrix and Cell adhesion molecules as well as related key targets APOA1, APOE, APP, C4A, C5, FGA, FGB, FGG and PLG in the CSF of cell treated ALS subjects. CONCLUSIONS: Extracellular matrix and cell adhesion molecules as well as their related highlighted components have emerged as key targets of autologous MSCs in CSF of ALS patients. TRIAL REGISTRATION: Clinicaltrial.gov identifier NCT0291768. Registered 28 September 2016.

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Esclerosis Amiotrófica Lateral , Trasplante de Células Madre Mesenquimatosas , Células Madre Mesenquimatosas , Proteómica , Trasplante Autólogo , Humanos , Esclerosis Amiotrófica Lateral/líquido cefalorraquídeo , Esclerosis Amiotrófica Lateral/terapia , Esclerosis Amiotrófica Lateral/metabolismo , Células Madre Mesenquimatosas/metabolismo , Proteómica/métodos , Trasplante de Células Madre Mesenquimatosas/métodos , Masculino , Femenino , Persona de Mediana Edad , Apolipoproteínas E/metabolismo , Apolipoproteínas E/genética , Apolipoproteínas E/líquido cefalorraquídeo , Anciano , Apolipoproteína A-I/líquido cefalorraquídeo , Apolipoproteína A-I/metabolismo , Adulto , Células de la Médula Ósea/metabolismo , Mapas de Interacción de Proteínas

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Background: Proliferative diabetic retinopathy (PDR) is a severe complication of diabetes, and understanding its molecular mechanisms is crucial. Endoplasmic reticulum (ER) stress has been implicated in various diseases, including diabetic complications. This study aims to elucidate ER stress-related biomarkers in PDR, providing insights into the underlying molecular pathways. Methods: We analyzed two independent PDR datasets, GSE102485 and GSE60436. The GSE102485 dataset (22 PDR and 3 normal samples) was the primary dataset for comprehensive analyses, including differential expression, functional enrichment, PPI network construction, immune cell infiltration, and drug prediction. The GSE60436 dataset (6 PDR and 3 normal samples) was used for validation. In vitro experiments using human umbilical vein endothelial cells (HUVECs) in a high-glucose environment were conducted to validate key bioinformatics outcomes. Western blotting assessed protein levels of ER stress markers (TRAM1 and TXNIP). Results: Differential expression analysis identified 2451 genes, including 328 ER stress-related genes. Functional analysis revealed enrichment in ER stress-related processes and pathways. Hub genes (BCL2, CCL2, IL-1ß, TLR4, TNF, TP53) were identified, and immune infiltration analysis showed altered immune cell proportions. Validation in GSE60436 and in vitro confirmed ER stress gene dysregulation. Drug prediction suggested potential small molecules targeting ER stress markers. Conclusion: This study provides a comprehensive molecular characterization of ER stress in PDR, highlighting altered biological processes, immune changes, and potential therapeutic targets. The identified hub genes and small molecules offer avenues for further investigation and therapy development, enhancing understanding of PDR pathogenesis and aiding targeted intervention creation.

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Biología Computacional , Retinopatía Diabética , Estrés del Retículo Endoplásmico , Humanos , Estrés del Retículo Endoplásmico/genética , Retinopatía Diabética/genética , Retinopatía Diabética/metabolismo , Retinopatía Diabética/patología , Retinopatía Diabética/inmunología , Biología Computacional/métodos , Células Endoteliales de la Vena Umbilical Humana/metabolismo , Masculino , Femenino , Perfilación de la Expresión Génica , Biomarcadores/metabolismo , Persona de Mediana Edad , Mapas de Interacción de Proteínas

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Introduction: Infantile Hemangioma (IH) is a prevalent benign vascular tumor affecting approximately 5-10% of infants. Its underlying pathogenesis remains enigmatic, and current therapeutic approaches show limited effectiveness. Our study aimed to discover potential IH-associated therapeutics through a transcriptomic, computational drug repurposing methodology. Methods: Utilizing the IH-specific dataset GSE127487 from the Gene Expression Omnibus, we identified differentially expressed genes (DEGs) and conducted weighted gene coexpression network analysis (WGCNA). Subsequently, a protein-protein interaction (PPI) network was constructed to obtain the top 100 hub genes. Drug candidates were sourced from the Connectivity Map (CMap) and Comparative Toxicogenomics Database (CTD). Results: Our analysis revealed 1203 DEGs and a significant module of 1780 mRNAs strongly correlated with IH. These genes were primarily enriched in the PI3K/AKT/MTOR, RAS/MAPK, and CGMP/PKG signaling pathway. After creating a PPI network of overlapping genes, we filtered out the top 100 hub genes. Ultimately, 44 non-toxic drugs were identified through the CMap and CTD databases. Twelve molecular-targeting agents (belinostat, chir 99021, dasatinib, entinostat, panobinostat, sirolimus, sorafenib, sunitinib, thalidomide, U 0126, vorinostat, and wortmannin) may be potential candidates for IH therapy. Moreover, in vitro experiments demonstrated that entinostat, sorafenib, dasatinib, and sirolimus restricted the proliferation and migration and initiated apoptosis in HemEC cells, thereby underscoring their potential therapeutic value. Conclusion: Our investigation revealed that the pathogenic mechanism underlying IH might be closely associated with the PI3K/AKT/MTOR, RAS/MAPK, and CGMP/PKG signaling pathways. Furthermore, we identified twelve molecular-targeting agents among the predicted drugs that show promise as therapeutic candidates for IH.

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Transcriptomic analysis used to discover potential therapeutics for Infantile Hemangioma (IH). Key IH-related pathways: PI3K/AKT/MTOR, RAS/MAPK, and CGMP/PKG signaling identified. Identified 44 non-toxic drugs as potential IH therapies via CMap and CTD. Twelve molecular agents show potential as IH therapy candidates. In vitro studies confirmed entinostat, sorafenib, dasatinib, and sirolimus inhibit HemEC cell proliferation and induce apoptosis.

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Antineoplásicos , Proliferación Celular , Ensayos de Selección de Medicamentos Antitumorales , Hemangioma , Humanos , Antineoplásicos/farmacología , Antineoplásicos/química , Hemangioma/tratamiento farmacológico , Hemangioma/patología , Hemangioma/genética , Proliferación Celular/efectos de los fármacos , Lactante , Simulación por Computador , Apoptosis/efectos de los fármacos , Mapas de Interacción de Proteínas/efectos de los fármacos , Reposicionamiento de Medicamentos , Relación Dosis-Respuesta a Droga

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Glioblastoma multiforme (GBM) is a malignant tumour with a poor prognosis. Therefore, potential treatment strategies and novel therapeutic targets have gained increased attention. Our data showed that the ethanol extract of Vanilla planifolia stem (VAS) significantly decreased the viability and the colony formation of GBM cells. Moreover, VAS induced the cleavage of MAP1LC3, a marker of autophagy. Further RNA-seq and bioinformatic analysis revealed 4248 differentially expressed genes (DEGs) between VAS-treated GBM cells and the control cells. Protein-protein interactions between DEGs with fold changes less than -3 and more than 5 were further analysed, and we found that 16 and 9 hub DEGs, respectively, were correlated with other DEGs. Further qPCR experiments confirmed that 14 hub DEGs was significantly downregulated and 9 hub DEGs was significantly upregulated. In addition, another significantly downregulated DEG, p21-activated kinase 6 (PAK6), was correlated with the overall survival of GBM patients. Further validation experiments confirmed that VAS significantly reduced the mRNA and protein expression of PAK6, which led to the abolition of cell viability and colony formation. These findings demonstrated that VAS reduced cell viability, suppressed colony formation and induced autophagy and revealed PAK6 and other DEGs as potential therapeutic targets for GBM treatment.

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Autofagia , Regulación Neoplásica de la Expresión Génica , Glioblastoma , Extractos Vegetales , Quinasas p21 Activadas , Glioblastoma/metabolismo , Glioblastoma/patología , Glioblastoma/tratamiento farmacológico , Glioblastoma/genética , Humanos , Quinasas p21 Activadas/metabolismo , Quinasas p21 Activadas/genética , Extractos Vegetales/farmacología , Regulación Neoplásica de la Expresión Génica/efectos de los fármacos , Línea Celular Tumoral , Autofagia/efectos de los fármacos , Supervivencia Celular/efectos de los fármacos , Tallos de la Planta/química , Etanol , Proliferación Celular/efectos de los fármacos , Mapas de Interacción de Proteínas/efectos de los fármacos , Muerte Celular/efectos de los fármacos

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BACKGROUND: The bone is among the most frequently chosen sites for the metastatic spread of breast cancer. The prediction of biomarkers for BM (Bone Metastasis) and PDB (Paget's disease of bone) initiated from breast cancer could be critically important in categorizing individuals with a higher risk and providing targeted treatment for PDB and BM. AIMS: This research aims to investigate the common key candidate biomarkers that contribute to BM-BCa (Bone metastasis of breast cancer) and PDB by employing network decomposition and functional enrichment studies. METHODS AND RESULTS: This research analyzed high-throughput transcriptome sequencing (RNA-Seq). For this work, the dataset (GSE121677) was downloaded from GEO (Gene Expression Omnibus), and DEGs were identified using Galaxy and R script 4.3. Using STRING (Search Tool for the Retrieval of Interacting Genes), high-throughput research created a protein-protein interaction network (PPIN). The BM-PDB-interactome was created using Cytoscape 3.9.1 and PDB biomarkers, with the top 3% DEGs from BM-BCa. Functional Enrichment Analysis (Funrich 3.1.3) and DAVID 6.8 performed functional and gene set enrichment analysis (GSEA) of putatively essential biomarkers. TCGA (The Cancer Genome Atlas) validated the discovered genes. Based on our research, we identified 1262 DEGs; among these DEGs, 431 genes were upregulated, and 831 genes were downregulated. During the third growth of the interactome, 20 more genes were pinned to the BM-PDB interactome. RAC2, PIAS1, EP300, EIF2S1, and LRP6 are among the additional 25% of genes identified to interact with the BM-PDB interactome. To corroborate the findings of the research presented, additional functional and gene set enrichment analyses have been performed. CONCLUSION: Of the five reported genes (RAC2, PIAS1, EP300, EIF2S1, and LRP6), RAC2 was identified to function as the common key potential biomarker in the BM-PDB interactome analysis and validated by TCGA in the study presented.

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Biomarcadores de Tumor , Neoplasias Óseas , Neoplasias de la Mama , Osteítis Deformante , Mapas de Interacción de Proteínas , Humanos , Neoplasias de la Mama/patología , Neoplasias de la Mama/genética , Femenino , Neoplasias Óseas/secundario , Neoplasias Óseas/genética , Biomarcadores de Tumor/genética , Biomarcadores de Tumor/metabolismo , Osteítis Deformante/genética , Osteítis Deformante/patología , Perfilación de la Expresión Génica , Regulación Neoplásica de la Expresión Génica , Redes Reguladoras de Genes , Transcriptoma , Secuenciación de Nucleótidos de Alto Rendimiento

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Background: Bladder cancer, a highly fatal disease, poses a significant threat to patients. Positioned at 19q13.2-13.3, LIG1, one of the four DNA ligases in mammalian cells, is frequently deleted in tumour cells of diverse origins. Despite this, the precise involvement of LIG1 in BLCA remains elusive. This pioneering investigation delves into the uncharted territory of LIG1's impact on BLCA. Our primary objective is to elucidate the intricate interplay between LIG1 and BLCA, alongside exploring its correlation with various clinicopathological factors. Methods: We retrieved gene expression data of para-carcinoma tissues and bladder cancer (BLCA) from the GEO repository. Single-cell sequencing data were processed using the "Seurat" package. Differential expression analysis was then performed with the "Limma" package. The construction of scale-free gene co-expression networks was achieved using the "WGCNA" package. Subsequently, a Venn diagram was utilized to extract genes from the positively correlated modules identified by WGCNA and intersect them with differentially expressed genes (DEGs), isolating the overlapping genes. The "STRINGdb" package was employed to establish the protein-protein interaction (PPI) network.Hub genes were identified through the PPI network using the Betweenness Centrality (BC) algorithm. We conducted KEGG and GO enrichment analyses to uncover the regulatory mechanisms and biological functions associated with the hub genes. A machine-learning diagnostic model was established using the R package "mlr3verse." Mutation profiles between the LIG1^high and LIG1^low groups were visualized using the BEST website. Survival analyses within the LIG1^high and LIG1^low groups were performed using the BEST website and the GENT2 website. Finally, a series of functional experiments were executed to validate the functional role of LIG1 in BLCA. Results: Our investigation revealed an upregulation of LIG1 in BLCA specimens, with heightened LIG1 levels correlating with unfavorable overall survival outcomes. Functional enrichment analysis of hub genes, as evidenced by GO and KEGG enrichment analyses, highlighted LIG1's involvement in critical function such as the DNA replication, cellular senescence, cell cycle and the p53 signalling pathway. Notably, the mutational landscape of BLCA varied significantly between LIG1high and LIG1low groups.Immune infiltrating analyses suggested a pivotal role for LIG1 in immune cell recruitment and immune regulation within the BLCA microenvironment, thereby impacting prognosis. Subsequent experimental validations further underscored the significance of LIG1 in BLCA pathogenesis, consolidating its functional relevance in BLCA samples. Conclusions: Our research demonstrates that LIG1 plays a crucial role in promoting bladder cancer malignant progression by heightening proliferation, invasion, EMT, and other key functions, thereby serving as a potential risk biomarker.

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Biomarcadores de Tumor , ADN Ligasa (ATP) , Aprendizaje Automático , Análisis de la Célula Individual , Neoplasias de la Vejiga Urinaria , Neoplasias de la Vejiga Urinaria/genética , Neoplasias de la Vejiga Urinaria/mortalidad , Neoplasias de la Vejiga Urinaria/patología , Humanos , Análisis de la Célula Individual/métodos , Biomarcadores de Tumor/genética , ADN Ligasa (ATP)/genética , ADN Ligasa (ATP)/metabolismo , Pronóstico , Masculino , Regulación Neoplásica de la Expresión Génica , Femenino , Redes Reguladoras de Genes , Mapas de Interacción de Proteínas , Persona de Mediana Edad , Perfilación de la Expresión Génica , Biología Computacional/métodos , Línea Celular Tumoral , Anciano

RESUMEN

BACKGROUND: Rapid proliferation and outgrowth of tumor cells frequently result in localized hypoxia, which has been implicated in the progression of lung cancer. The present study aimed to identify key long non-coding RNAs (lncRNAs) and messenger RNAs (mRNAs) involved in hypoxia-induced A549 lung cancer cells, and to investigate their potential underlying mechanisms of action. METHODS: High-throughput sequencing was utilized to obtain the expression profiles of lncRNA and mRNA in both hypoxia-induced and normoxia A549 lung cancer cells. Subsequently, a bioinformatics analysis was conducted on the differentially expressed molecules, encompassing functional enrichment analysis, protein-protein interaction (PPI) network analysis, and competitive endogenous RNA (ceRNA) analysis. Finally, the alterations in the expression of key lncRNAs and mRNAs were validated using real-time quantitative PCR (qPCR). RESULTS: In the study, 1155 mRNAs and 215 lncRNAs were identified as differentially expressed between the hypoxia group and the normoxia group. Functional enrichment analysis revealed that the differentially expressed mRNAs were significantly enriched in various pathways, including the p53 signaling pathway, DNA replication, and the cell cycle. Additionally, key lncRNA-miRNA-mRNA relationships, such as RP11-58O9.2-hsa-miR-6749-3p-XRCC2 and SNAP25-AS1-hsa-miR-6749-3p-TENM4, were identified. Notably, the qPCR assay demonstrated that the expression of SNAP25-AS1, RP11-58O9.2, TENM4, and XRCC2 was downregulated in the hypoxia group compared to the normoxia group. Conversely, the expression of LINC01164, VLDLR-AS1, RP11-14I17.2, and CDKN1A was upregulated. CONCLUSION: Our findings suggest a potential involvement of SNAP25-AS1, RP11-58O9.2, TENM4, XRCC2, LINC01164, VLDLR-AS1, RP11-14I17.2, and CDKN1A in the development of hypoxia-induced lung cancer. These key lncRNAs and mRNAs exert their functions through diverse mechanisms, including the competitive endogenous RNA (ceRNA) pathway.

Asunto(s)

Regulación Neoplásica de la Expresión Génica , Secuenciación de Nucleótidos de Alto Rendimiento , Neoplasias Pulmonares , ARN Largo no Codificante , ARN Mensajero , Humanos , ARN Largo no Codificante/genética , ARN Largo no Codificante/metabolismo , ARN Mensajero/genética , ARN Mensajero/metabolismo , Células A549 , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patología , Neoplasias Pulmonares/metabolismo , Redes Reguladoras de Genes , Perfilación de la Expresión Génica , Mapas de Interacción de Proteínas/genética , Biología Computacional/métodos , Hipoxia de la Célula/genética , MicroARNs/genética , MicroARNs/metabolismo

RESUMEN

BACKGROUND: Rheumatoid arthritis (RA) is an autoimmune, inflammatory joint disease. There is growing evidence that ferroptosis is involved in the pathogenesis of RA. This study aimed to search for diagnostic markers of ferroptosis in RA and to analyse the potential mechanisms and clinical value. MATERIALS AND METHODS: RA-associated datasets were used from the publicly available GEO database. Three methods of machine learning were applied to screen biomarkers. The diagnostic efficacy of the results was also verified by receiver operating characteristic (ROC) curve, external dataset, qRT-PCR and Western blot. Enrichment analysis was performed in this process, while protein-protein interaction (PPI) analysis and immune infiltration correlation analysis were performed using biomarkers, and competing endogenous RNA (ceRNA) networks were constructed to search for prospective therapeutic targets. RESULTS: MMP13 and GABARAPL1 can be used as ferroptosis diagnostic genes in RA. The ROC curve and PPI result demonstrated that MMP13 and GABARAPL1 had an excellent diagnostic value. The results of signature genes in the external dataset, qRT-PCR and Western blot further confirm our findings. The enrichment analysis showed that p53, MAPK and NOD-like receptor signalling pathways may be involved in the process of ferroptosis in RA. In addition, two ferroptosis diagnostic genes in RA participate in the occurrence of ferroptosis in RA via oxidative stress, metabolism and immune response. Immune infiltration analysis showed that RA extensively infiltrated B cells, T cells, macrophages and other immune cells. Persistent immune activation may be an essential reason for the progression of ferroptosis in RA. We also obtained five potential therapeutic agents for RA and some long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) regulating ferroptosis diagnostic genes. CONCLUSIONS: Our study suggests that MMP13 and GABARAPL1, which are closely linked with oxidative stress and immunological modulation, can be used as ferroptosis-related potential diagnostic markers in RA and provide new clues regarding the diagnostic and therapeutic targets of ferroptosis in RA.

Asunto(s)

Artritis Reumatoide , Biomarcadores , Ferroptosis , Metaloproteinasa 13 de la Matriz , Ferroptosis/genética , Artritis Reumatoide/genética , Artritis Reumatoide/diagnóstico , Artritis Reumatoide/inmunología , Artritis Reumatoide/metabolismo , Humanos , Biomarcadores/metabolismo , Metaloproteinasa 13 de la Matriz/metabolismo , Metaloproteinasa 13 de la Matriz/genética , Mapas de Interacción de Proteínas/genética , Curva ROC , Aprendizaje Automático

RESUMEN

The dolichyl-diphosphooligosaccharide-protein glycosyltransferase non-catalytic subunit (DDOST) is a key component of the oligosaccharyltransferase complex catalyzing N-linked glycosylation in the endoplasmic reticulum lumen. DDOST is associated with several cancers and congenital disorders of glycosylation. However, its role in pancreatic cancer remains elusive, despite its enriched pancreatic expression. Using quantitative mass spectrometry, we identify 30 differentially expressed proteins and phosphopeptides (DEPs) after DDOST knockdown in the pancreatic ductal adenocarcinoma (PDAC) cell line PA-TU-8988T. We evaluated DDOST / DEP protein-protein interaction networks using STRING database, correlation of mRNA levels in pancreatic cancer TCGA data, and biological processes annotated to DEPs in Gene Ontology database. The inferred DDOST regulated phenotypes were experimentally verified in two PDAC cell lines, PA-TU-8988T and BXPC-3. We found decreased proliferation and cell viability after DDOST knockdown, whereas ER-stress, ROS-formation and apoptosis were increased. In conclusion, our results support an oncogenic role of DDOST in PDAC by intercepting cell stress events and thereby reducing apoptosis. As such, DDOST might be a potential biomarker and therapeutic target for PDAC.

Asunto(s)

Apoptosis , Estrés del Retículo Endoplásmico , Técnicas de Silenciamiento del Gen , Estrés Oxidativo , Neoplasias Pancreáticas , Humanos , Apoptosis/genética , Neoplasias Pancreáticas/genética , Neoplasias Pancreáticas/patología , Neoplasias Pancreáticas/metabolismo , Línea Celular Tumoral , Hexosiltransferasas/metabolismo , Hexosiltransferasas/genética , Proliferación Celular , Especies Reactivas de Oxígeno/metabolismo , Carcinoma Ductal Pancreático/genética , Carcinoma Ductal Pancreático/patología , Carcinoma Ductal Pancreático/metabolismo , Regulación Neoplásica de la Expresión Génica , Mapas de Interacción de Proteínas , Supervivencia Celular/genética , Proteínas de la Membrana

RESUMEN

BACKGROUND: Glucose fluctuations may be involved in the pathophysiological process of cardiomyocyte apoptosis, but the exact mechanism remains elusive. This study focused on exploring the mechanisms related to glucose fluctuation-induced cardiomyocyte apoptosis. METHODS: Diabetic rats established via an injection of streptozotocin were randomized to five groups: the controlled diabetic (CD) group, the uncontrolled diabetic (UD) group, the glucose fluctuated diabetic (GFD) group, the GFD group rats with the injection of 0.9% sodium chloride (NaCl) (GFD + NaCl) and the GFD group rats with the injection of N-acetyl-L-cysteine (NAC) (GFD + NAC). Twelve weeks later, cardiac function and apoptosis related protein expressions were tested. Proteomic analysis was performed to further analyze the differential protein expression pattern of CD and GFD. RESULTS: The left ventricular ejection fraction levels and fractional shortening levels were decreased in the GFD group, compared with those in the CD and UD groups. Positive cells tested by DAB-TUNEL were increased in the GFD group, compared with those in the CD group. The expression of Bcl-2 was decreased, but the expressions of Bax, cleaved caspase-3 and cleaved caspase-9 were increased in response to glucose fluctuations. Compared with CD, there were 527 upregulated and 152 downregulated proteins in GFD group. Txnip was one of the differentially expressed proteins related to oxidative stress response. The Txnip expression was increased in the GFD group, while the Akt phosphorylation level was decreased. The interaction between Txnip and Akt was enhanced when blood glucose fluctuated. Moreover, the application of NAC partially reversed glucose fluctuations-induced cardiomyocyte apoptosis. CONCLUSIONS: Glucose fluctuations lead to cardiomyocyte apoptosis by up-regulating Txnip expression and enhancing Txnip-Akt interaction.

Asunto(s)

Proteínas Reguladoras de la Apoptosis , Apoptosis , Glucemia , Proteínas Portadoras , Diabetes Mellitus Experimental , Miocitos Cardíacos , Proteínas Proto-Oncogénicas c-akt , Ratas Sprague-Dawley , Transducción de Señal , Animales , Miocitos Cardíacos/patología , Miocitos Cardíacos/metabolismo , Miocitos Cardíacos/efectos de los fármacos , Apoptosis/efectos de los fármacos , Proteínas Proto-Oncogénicas c-akt/metabolismo , Diabetes Mellitus Experimental/metabolismo , Masculino , Proteínas Portadoras/metabolismo , Glucemia/metabolismo , Proteínas Reguladoras de la Apoptosis/metabolismo , Fosforilación , Función Ventricular Izquierda/efectos de los fármacos , Tiorredoxinas/metabolismo , Cardiomiopatías Diabéticas/metabolismo , Cardiomiopatías Diabéticas/patología , Cardiomiopatías Diabéticas/fisiopatología , Cardiomiopatías Diabéticas/etiología , Proteómica , Ratas , Mapas de Interacción de Proteínas , Proteínas de Ciclo Celular

RESUMEN

Plasma protein biomarkers have been considered promising tools for diagnosing dementia subtypes due to their low variability, cost-effectiveness, and minimal invasiveness in diagnostic procedures. Machine learning (ML) methods have been applied to enhance accuracy of the biomarker discovery. However, previous ML-based studies often overlook interactions between proteins, which are crucial in complex disorders like dementia. While protein-protein interactions (PPIs) have been used in network models, these models often fail to fully capture the diverse properties of PPIs due to their local awareness. This drawback increases the chance of neglecting critical components and magnifying the impact of noisy interactions. In this study, we propose a novel graph-based ML model for dementia subtype diagnosis, the graph propagational network (GPN). By propagating the independent effect of plasma proteins on PPI network, the GPN extracts the globally interactive effects between proteins. Experimental results showed that the interactive effect between proteins yielded to further clarify the differences between dementia subtype groups and contributed to the performance improvement where the GPN outperformed existing methods by 10.4% on average.

Asunto(s)

Biomarcadores , Proteínas Sanguíneas , Demencia , Aprendizaje Automático , Mapas de Interacción de Proteínas , Humanos , Demencia/metabolismo , Demencia/diagnóstico , Proteínas Sanguíneas/metabolismo , Mapeo de Interacción de Proteínas/métodos , Algoritmos , Biología Computacional/métodos

RESUMEN

Emerging evidence demonstrates that curcumin has an inhibitory effect on non-small cell lung cancer (NSCLC), and its targets and mechanism of action need further exploration. The goal of this study was to explore the potential targets and mechanism of curcumin against NSCLC by network pharmacology, bioinformatics, and experimental validation, thereby providing more insight into combination treatment with curcumin for NSCLC in preclinical and clinical research. Curcumin targets against NSCLC were predicted based on HIT2.0, STD, CTD, and DisGeNET, and the core targets were analyzed via protein-protein interaction network construction (PPI), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and molecular docking. The gene expression levels of samples in A549 cells, NCI-H460, and curcumin treated groups were detected by real-time quantitative PCR. A total of 67 common targets between curcumin and NSCLC were collected by screening public databases. GO and KEGG analysis suggested that curcumin treatment of NSCLC mainly involves cancer-related pathways, such as PI3K-AKT signaling pathway, Foxo signaling pathway, microRNAs, MAPK signaling pathway, HIF-1 signaling pathway, etc. The targets with the highest degree were identified through the PPI network, namely CASP3, CTNNB1, JUN, IL6, MAPK3, HIF1A, STAT3, AKT1, TP53, CCND1, VEGFA, and EGFR. The results of the in vitro experiments showed that curcumin treatment of NSCLC down-regulated the gene expressions of CCND1, CASP3, HIF1A, IL-6, MAPK3, STAT3, AKT1, and TP53. Our findings revealed that curcumin functions as a potential therapeutic candidate for NSCLC by suppressing multiple signaling pathways and interacting with multiple gene targets.

Asunto(s)

Carcinoma de Pulmón de Células no Pequeñas , Biología Computacional , Curcumina , Neoplasias Pulmonares , Simulación del Acoplamiento Molecular , Carcinoma de Pulmón de Células no Pequeñas/tratamiento farmacológico , Carcinoma de Pulmón de Células no Pequeñas/genética , Humanos , Curcumina/farmacología , Curcumina/uso terapéutico , Neoplasias Pulmonares/tratamiento farmacológico , Neoplasias Pulmonares/genética , Mapas de Interacción de Proteínas/efectos de los fármacos , Antineoplásicos/farmacología , Antineoplásicos/uso terapéutico , Transducción de Señal/efectos de los fármacos , Línea Celular Tumoral , Regulación Neoplásica de la Expresión Génica/efectos de los fármacos , Reacción en Cadena en Tiempo Real de la Polimerasa

RESUMEN

Patients with severe COVID-19 and those with sepsis have similar clinical manifestations. We used bioinformatics methods to identify the common hub genes in these 2 diseases. Two RNA-seq datasets from the Gene Expression Omnibus were used to identify common differentially expressed genes (DEGs) in COVID-19 and sepsis. These common genes were used for analysis of functional enrichment; pathway analysis; identification of associated transcription factors, metabolites, and miRNAs; and mapping of protein-protein interaction networks. The major hub genes of COVID-19 and sepsis were identified, and validation datasets were used to assess the value of these hub genes using receiver operating characteristic (ROC) curves. Analysis of the 800 common DEGs for COVID-19 and sepsis, as well as common transcription factors, miRNAs, and metabolites, demonstrated that the immune response had a key role in both diseases. DLGAP5, BUB1, CDK1, CCNB1, and BUB1B were the most important common hub genes. Analysis of a validation cohort indicated these 5 genes had significantly higher expression in COVID-19 patients and sepsis patients than in corresponding controls, and the area under the ROC curves ranged from 0.832 to 0.981 for COVID-19 and 0.840 to 0.930 for sepsis. We used bioinformatics tools to identify common DEGs, miRNAs, and transcription factors for COVID-19 and sepsis. The 5 identified hub genes had higher expression in validation cohorts of COVID-19 and sepsis. These genes had good or excellent diagnostic performance based on ROC analysis, and therefore have potential use as novel markers or therapeutic targets.

Asunto(s)

COVID-19 , Biología Computacional , Sepsis , Humanos , COVID-19/genética , Sepsis/genética , Biología Computacional/métodos , Mapas de Interacción de Proteínas/genética , SARS-CoV-2/genética , MicroARNs/genética , Curva ROC , Genes Reguladores , Perfilación de la Expresión Génica/métodos