Identification of hub genes and pathways associated with cellular senescence in diabetic foot ulcers via comprehensive transcriptome analysis.

This research aimed to find important genes and pathways related to cellular senescence (CS) in diabetic foot ulcers (DFU) and to estimate the possible pathways through which CS affects diabetic foot healing. The GSE80178 dataset was acquired from the Gene Expression Omnibus (GEO) database, containing six DFU and three diabetic foot skin (DFS) samples. The limma package was used to identify differentially expressed genes (DEGs). At the same time, DEGs associated with CS (CS-DEGs) were found using the CellAge database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted on the CS-DEGs. A protein-protein interaction (PPI) network was built using the String database, and the cytoHubba plug-in within Cytoscape helped identify hub genes. Lastly, the miRNA-TF-mRNA regulatory network for these hub genes was established. In total, 66 CS-DEGs were obtained. These genes mainly focus on CS, Kaposi sarcoma-associated herpesvirus infection and Toll-like receptor signalling pathway. Eight hub genes were identified to regulate cell senescence in DFU, including TP53, SRC, SIRT1, CCND1, EZH2, CXCL8, AR and CDK4. According to miRNA-TF-mRNA regulatory network, hsa-mir-132-3p/SIRT1/EZH2 axis is involved in senescence cell accumulation in DFU.

Identification of prostate cancer bone metastasis related genes and potential therapy targets by bioinformatics and in vitro experiments.

The aetiology of bone metastasis in prostate cancer (PCa) remains unclear. This study aims to identify hub genes involved in this process. We utilized machine learning, GO, KEGG, GSEA, Single-cell analysis, ROC methods to identify hub genes for bone metastasis in PCa using the TCGA and GEO databases. Potential drugs targeting these genes were identified. We validated these results using 16 specimens from patients with PCa and analysed the relationship between the hub genes and clinical features. The impact of APOC1 on PCa was assessed through in vitro experiments. Seven hub genes with AUC values of 0.727-0.926 were identified. APOC1, CFH, NUSAP1 and LGALS1 were highly expressed in bone metastasis tissues, while NR4A2, ADRB2 and ZNF331 exhibited an opposite trend. Immunohistochemistry further confirmed these results. The oxidative phosphorylation pathway was significantly enriched by the identified genes. Aflatoxin B1, benzo(a)pyrene, cyclosporine were identified as potential drugs. APOC1 expression was correlated with clinical features of PCa metastasis. Silencing APOC1 significantly inhibited PCa cell proliferation, clonality, and migration in vitro. This study identified 7 hub genes that potentially facilitate bone metastasis in PCa through mitochondrial metabolic reprogramming. APOC1 emerged as a promising therapeutic target and prognostic marker for PCa with bone metastasis.

Contribution of FOS in neutrophils to venous thromboembolism via miR-144 based on bioinformatic prediction and validation.

The Finkel-Biskis-Jinkins Osteosarcoma (c-Fos; encoded by FOS) plays an important role in several cardiovascular diseases, including atherosclerosis and stroke. However, the relationship between FOS and venous thromboembolism (VTE) remains unknown. We identified differentially expressed genes in Gene Expression Omnibus dataset, GSE48000, comprising VTE patients and healthy individuals, and analysed them using CIBERSORT and weighted co-expression network analysis (WGCNA). FOS and CD46 expressions were significantly downregulated (FOS p = 2.26E-05, CD64 p = 8.83E-05) and strongly linked to neutrophil activity in VTE. We used GSE19151 and performed PCR to confirm that FOS and CD46 had diagnostic potential for VTE; however, only FOS showed differential expression by PCR and ELISA in whole blood samples. Moreover, we found that hsa-miR-144 which regulates FOS expression was significantly upregulated in VTE. Furthermore, FOS expression was significantly downregulated in neutrophils of VTE patients (p = 0.03). RNA sequencing performed on whole blood samples of VTE patients showed that FOS exerted its effects in VTE via the leptin-mediated adipokine signalling pathway. Our results suggest that FOS and related genes or proteins can outperform traditional clinical markers and may be used as diagnostic biomarkers for VTE.

Network visualization of genes involved in skeletal muscle myogenesis in livestock animals.

BACKGROUND: Muscle growth post-birth relies on muscle fiber number and size. Myofibre number, metabolic and contractile capacities are established pre-birth during prenatal myogenesis. The aim of this study was to identify genes involved in skeletal muscle development in cattle, sheep, and pigs - livestock. RESULTS: The cattle analysis showed significant differences in 5043 genes during the 135-280 dpc period. In sheep, 444 genes differed significantly during the 70-120 dpc period. Pigs had 905 significantly different genes for the 63-91 dpc period.The biological processes and KEGG pathway enrichment results in each species individually indicated that DEGs in cattle were significantly enriched in regulation of cell proliferation, cell division, focal adhesion, ECM-receptor interaction, and signaling pathways (PI3K-Akt, PPAR, MAPK, AMPK, Ras, Rap1); in sheep - positive regulation of fibroblast proliferation, negative regulation of endothelial cell proliferation, focal adhesion, ECM-receptor interaction, insulin resistance, and signaling pathways (PI3K-Akt, HIF-1, prolactin, Rap1, PPAR); in pigs - regulation of striated muscle tissue development, collagen fibril organization, positive regulation of insulin secretion, focal adhesion, ECM-receptor interaction, and signaling pathways (PPAR, FoxO, HIF-1, AMPK). Among the DEGs common for studied animal species, 45 common genes were identified. Based on these, a protein-protein interaction network was created and three significant modules critical for skeletal muscle myogenesis were found, with the most significant module A containing four recognized hub genes - EGFR, VEGFA, CDH1, and CAV1. Using the miRWALK and TF2DNA databases, miRNAs (bta-miR-2374 and bta-miR-744) and transcription factors (CEBPB, KLF15, RELA, ZNF143, ZBTB48, and REST) associated with hub genes were detected. Analysis of GO term and KEGG pathways showed that such processes are related to myogenesis and associated with module A: positive regulation of MAP kinase activity, vascular endothelial growth factor receptor, insulin-like growth factor binding, focal adhesion, and signaling pathways (PI3K-Akt, HIF-1, Rap1, Ras, MAPK). CONCLUSIONS: The identified genes, common to the prenatal developmental period of skeletal muscle in livestock, are critical for later muscle development, including its growth by hypertrophy. They regulate valuable economic characteristics. Enhancing and breeding animals according to the recognized genes seems essential for breeders to achieve superior gains in high-quality muscle mass.

Key gene modules and hub genes associated with pyrethroid and organophosphate resistance in Anopheles mosquitoes: a systems biology approach.

Indoor residual spraying (IRS) and insecticide-treated nets (ITNs) are the main methods used to control mosquito populations for malaria prevention. The efficacy of these strategies is threatened by the spread of insecticide resistance (IR), limiting the success of malaria control. Studies of the genetic evolution leading to insecticide resistance could enable the identification of molecular markers that can be used for IR surveillance and an improved understanding of the molecular mechanisms associated with IR. This study used a weighted gene co-expression network analysis (WGCNA) algorithm, a systems biology approach, to identify genes with similar co-expression patterns (modules) and hub genes that are potential molecular markers for insecticide resistance surveillance in Kenya and Benin. A total of 20 and 26 gene co-expression modules were identified via average linkage hierarchical clustering from Anopheles arabiensis and An. gambiae, respectively, and hub genes (highly connected genes) were identified within each module. Three specific genes stood out: serine protease, E3 ubiquitin-protein ligase, and cuticular proteins, which were top hub genes in both species and could serve as potential markers and targets for monitoring IR in these malaria vectors. In addition to the identified markers, we explored molecular mechanisms using enrichment maps that revealed a complex process involving multiple steps, from odorant binding and neuronal signaling to cellular responses, immune modulation, cellular metabolism, and gene regulation. Incorporation of these dynamics into the development of new insecticides and the tracking of insecticide resistance could improve the sustainable and cost-effective deployment of interventions.

Spatiotemporal transcriptomic plasticity in barley roots: unravelling water deficit responses in distinct root zones.

BACKGROUND: Drought poses a major threat to agricultural production and thus food security. Understanding the processes shaping plant responses to water deficit is essential for global food safety. Though many studies examined the effect of water deficit on the whole-root level, the distinct functions of each root zone and their specific stress responses remain masked by this approach. RESULTS: In this study, we investigated the effect of water deficit on root development of the spring barley (Hordeum vulgare L.) cultivar Morex and examined transcriptomic responses at the level of longitudinal root zones. Water deficit significantly reduced root growth rates after two days of treatment. RNA-sequencing revealed root zone and temporal gene expression changes depending on the duration of water deficit treatment. The majority of water deficit-regulated genes were unique for their respective root zone-by-treatment combination, though they were associated with commonly enriched gene ontology terms. Among these, we found terms associated with transport, detoxification, or cell wall formation affected by water deficit. Integration of weighted gene co-expression analyses identified differential hub genes, that highlighted the importance of modulating energy and protein metabolism and stress response. CONCLUSION: Our findings provide new insights into the highly dynamic and spatiotemporal response cascade triggered by water deficit and the underlying genetic regulations on the level of root zones in the barley cultivar Morex, providing potential targets to enhance plant resilience against environmental constraints. This study further emphasizes the importance of considering spatial and temporal resolution when examining stress responses.

RNA sequencing of olfactory bulb in Parkinson's disease reveals gene alterations associated with olfactory dysfunction.

The olfactory bulb is involved early in the pathophysiology of Parkinson's disease (PD), which is consistent with the early onset of olfactory dysfunction. Identifying the molecular mechanisms through which PD affects the olfactory bulb could lead to a better understanding of the pathophysiology and etiology of olfactory dysfunction in PD. We specifically aimed to assess gene expression changes, affected pathways and co-expression network by whole transcriptomic profiling of the olfactory bulb in subjects with clinicopathologically defined PD. Bulk RNA sequencing was performed on frozen human olfactory bulbs of 20 PD and 20 controls without dementia or any other neurodegenerative disorder, from the Arizona Study of Aging and Neurodegenerative disorders and the Brain and Body Donation Program. Differential expression analysis (19 PD vs 19 controls) revealed 2164 significantly differentially expressed genes (1090 upregulated and 1074 downregulated) in PD. Pathways enriched in downregulated genes included oxidative phosphorylation, olfactory transduction, metabolic pathways, and neurotransmitters synapses while immune and inflammatory responses as well as cellular death related pathways were enriched within upregulated genes. An overrepresentation of microglial and astrocyte-related genes was observed amongst upregulated genes, and excitatory neuron-related genes were overrepresented amongst downregulated genes. Co-expression network analysis revealed significant modules highly correlated with PD and olfactory dysfunction that were found to be involved in the MAPK signaling pathway, cytokine-cytokine receptor interaction, cholinergic synapse, and metabolic pathways. LAIR1 (leukocyte associated immunoglobulin like receptor 1) and PPARA (peroxisome proliferator activated receptor alpha) were identified as hub genes with a high discriminative power between PD and controls reinforcing an important role of neuroinflammation in the olfactory bulb of PD subjects. Olfactory identification test score positively correlated with expression of genes coding for G-coupled protein, glutamatergic, GABAergic, and cholinergic receptor proteins and negatively correlated with genes for proteins expressed in glial olfactory ensheathing cells. In conclusion, this study reveals gene alterations associated with neuroinflammation, neurotransmitter dysfunction, and disruptions of factors involved in the initiation of olfactory transduction signaling that may be involved in PD-related olfactory dysfunction.

Weighted gene co-expression network analysis reveals hub genes regulating response to salt stress in peanut.

Peanut (Arachis hypogaea L.) is an important oilseed crop worldwide. However, soil salinization becomes one of the main limiting factors of peanut production. Therefore, developing salt-tolerant varieties and understanding the molecular mechanisms of salt tolerance is important to protect peanut yield in saline areas. In this study, we selected four peanut varieties with contrasting response to salt challenges with T1 and T2 being tolerance and S1 and S2 being susceptible. High-throughput RNA sequencing resulted in more than 314.63 Gb of clean data from 48 samples. We identified 12,057 new genes, 7,971of which have functional annotations. KEGG pathway enrichment analysis of uniquely expressed genes in salt-tolerant peanut revealed that upregulated genes in the root are involved in the MAPK signaling pathway, fatty acid degradation, glycolysis/gluconeogenesis, and upregulated genes in the shoot were involved in plant hormone signal transduction and the MAPK signaling pathway. Na+ content, K+ content, K+/ Na+, and dry mass were measured in root and shoot tissues, and two gene co-expression networks were constructed based on weighted gene co-expression network analysis (WGCNA) in root and shoot. In this study, four key modules that are highly related to peanut salt tolerance in root and shoot were identified, plant hormone signal transduction, phenylpropanoid biosynthesis, starch and sucrose metabolism, flavonoid biosynthesis, carbon metabolism were identified as the key biological processes and metabolic pathways for improving peanut salt tolerance. The hub genes include genes encoding ion transport (such as HAK8, CNGCs, NHX, NCL1) protein, aquaporin protein, CIPK11 (CBL-interacting serine/threonine-protein kinase 11), LEA5 (late embryogenesis abundant protein), POD3 (peroxidase 3), transcription factor, and MAPKKK3. There were some new salt-tolerant genes identified in peanut, including cytochrome P450, vinorine synthase, sugar transport protein 13, NPF 4.5, IAA14, zinc finger CCCH domain-containing protein 62, beta-amylase, fatty acyl-CoA reductase 3, MLO-like protein 6, G-type lectin S-receptor-like serine/threonine-protein kinase, and kinesin-like protein KIN-7B. The identification of key modules, biological pathways, and hub genes in this study enhances our understanding of the molecular mechanisms underlying salt tolerance in peanuts. This knowledge lays a theoretical foundation for improving and innovating salt-tolerant peanut germplasm.

Identifying the key hub genes linked with lung squamous cell carcinoma by examining the differentially expressed and survival genes.

Lung Squamous Cell Carcinoma is characterised by significant alterations in RNA expression patterns, and a lack of early symptoms and diagnosis results in poor survival rates. Our study aimed to identify the hub genes involved in LUSC by differential expression analysis and their influence on overall survival rates in patients. Thus, identifying genes with the potential to serve as biomarkers and therapeutic targets. RNA sequence data for LUSC was obtained from TCGA and analysed using R Studio. Survival analysis was performed on DE genes. PPI network and hub gene analysis was performed on survival-relevant genes. Enrichment analysis was conducted on the PPI network to elucidate the functional roles of hub genes. Our analysis identified 2774 DEGs in LUSC patient datasets. Survival analysis revealed 511 genes with a significant impact on patient survival. Among these, 20 hub genes-FN1, ACTB, HGF, PDGFRB, PTEN, SNAI1, TGFBR1, ESR1, SERPINE1, THBS1, PDGFRA, VWF, BMP2, LEP, VTN, PXN, ABL1, ITGA3 and ANXA5-were found to have lower expression levels associated with better patient survival, whereas high expression of SOX2 correlated with longer survival. Enrichment analysis indicated that these hub genes are involved in critical cellular and cancer-related pathways. Our study has identified six key hub genes that are differentially expressed and exhibit significant influence over LUSC patient survival outcomes. Further, in vitro and in vivo studies must be conducted on the key genes for their utilisation as therapeutic targets and biomarkers in LUSC.

Pyroptosis is involved in the immune microenvironment regulation of unexplained recurrent miscarriage.

Unexplained recurrent miscarriage (URM) is a common pregnancy complication with few effective therapies. Moreover, little is known regarding the role of pyroptosis in the regulation of the URM immune microenvironment. To address this issue, gene expression profiles of publicly available placental datasets GSE22490 and GSE76862 were downloaded from the Gene Expression Omnibus database. Pyroptosis-related differentially expressed genes were identified and a total of 16 differentially expressed genes associated with pyroptosis were detected, among which 1 was upregulated and 15 were downregulated. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses indicated that the functionally enriched modules and pathways of these genes are closely related to immune and inflammatory responses. Four hub genes were identified: BTK, TLR8, NLRC4, and TNFSF13B. BTK, TLR8, and TNFSF13B were highly connected with immune cells, according to the correlation analysis of four hub genes and 20 different types of immune cells (p < 0.05). The four hub genes were used as research objects to construct the interaction networks. Chorionic villus tissue was used for quantitative real-time polymerase chain reaction and western blot to confirm the expression levels of hub genes, and the results showed that the expression of the four hub genes was significantly decreased in the chorionic villus tissue in the URM group. Collectively, the present study indicates that perhaps pyroptosis is essential to the diversity and complexity of the URM immune microenvironment, and provides a theoretical basis and research ideas for subsequent target gene verification and mechanism research.

Genes related to microglia polarization and immune infiltration in Alzheimer's Disease.

Alzheimer's Disease (AD) remains a significant challenge due to its complex etiology and socio-economic burden. In this study, we investigated the roles of macrophage polarization-related hub genes in AD pathology, focusing on their impact on immune infiltration and gene regulation in distinct brain regions. Using Gene Expression Omnibus (GEO) datasets GSE110226 (choroid plexus) and GSE1297 (hippocampal CA1), we identified key genes-EDN1, HHLA2, KL, TREM2, and WWTR1-associated with AD mechanisms and immune responses. Based on these findings, we developed a diagnostic model demonstrating favorable calibration and clinical applicability. Furthermore, we explored molecular interactions within mRNA-transcription factor and mRNA-miRNA regulatory networks, providing deeper insights into AD progression and identifying potential therapeutic targets. The novel identification of WWTR1 and HHLA2 as biomarkers expands the diagnostic toolkit for AD, offering new perspectives on the disease's underlying immune dynamics. However, external dataset validation and further in vitro and in vivo studies are required to confirm these results and their clinical relevance.

Identification and experimental validation of KMO as a critical immune-associated mitochondrial gene in unstable atherosclerotic plaque.

BACKGROUND: The heightened risk of cardiovascular and cerebrovascular events is associated with the increased instability of atherosclerotic plaques. However, the lack of effective diagnostic biomarkers has impeded the assessment of plaque instability currently. This study was aimed to investigate and identify hub genes associated with unstable plaques through the integration of various bioinformatics tools, providing novel insights into the detection and treatment of this condition. METHODS: Weighted Gene Co-expression Network Analysis (WGCNA) combined with two machine learning methods were used to identify hub genes strongly associated with plaque instability. The cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) method was utilized to assess immune cell infiltration patterns in atherosclerosis patients. Additionally, Gene Set Variation Analysis (GSVA) was conducted to investigate the potential biological functions, pathways, and mechanisms of hub genes associated with unstable plaques. To further validate the diagnostic efficiency and expression of the hub genes, immunohistochemistry (IHC), quantitative real-time polymerase chain reaction (RT-qPCR), and enzyme-linked immunosorbent assay (ELISA) were performed on collected human carotid plaque and blood samples. Immunofluorescence co-staining was also utilized to confirm the association between hub genes and immune cells, as well as their colocalization with mitochondria. RESULTS: The CIBERSORT analysis demonstrated a significant decrease in the infiltration of CD8 T cells and an obvious increase in the infiltration of M0 macrophages in patients with atherosclerosis. Subsequently, two highly relevant modules (blue and green) strongly associated with atherosclerotic plaque instability were identified. Through intersection with mitochondria-related genes, 50 crucial genes were identified. Further analysis employing least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine recursive feature elimination (SVM-RFE) algorithms revealed six hub genes significantly associated with plaque instability. Among them, NT5DC3, ACADL, SLC25A4, ALDH1B1, and MAOB exhibited positive correlations with CD8 T cells and negative correlations with M0 macrophages, while kynurenine 3-monooxygenas (KMO) demonstrated a positive correlation with M0 macrophages and a negative correlation with CD8 T cells. IHC and RT-qPCR analyses of human carotid plaque samples, as well as ELISA analyses of blood samples, revealed significant upregulation of KMO and MAOB expression, along with decreased ALDH1B1 expression, in both stable and unstable samples compared to the control samples. However, among the three key genes mentioned above, only KMO showed a significant increase in expression in unstable plaque samples compared to stable plaque samples. Furthermore, the expression patterns of KMO in human carotid unstable plaque tissues and cultured mouse macrophage cell lines were assessed using immunofluorescence co-staining techniques. Finally, lentivirus-mediated KMO silencing was successfully transduced into the aortas of high-fat-fed ApoE-/- mice, with results indicating that KMO silencing attenuated plaque formation and promoted plaque stability in ApoE-/- mice. CONCLUSIONS: The results suggest that KMO, a mitochondria-targeted gene associated with macrophage cells, holds promise as a valuable diagnostic biomarker for assessing the instability of atherosclerotic plaques.

Decoding plant-induced transcriptomic variability and consistency in two related polyphagous mites differing in host ranges.

The diet breadth of generalist herbivores when compared to specialists tends to be associated with greater transcriptional plasticity. Here, we consider whether it may also contribute to variation in host range among two generalists with different levels of polyphagy. We examined two related polyphagous spider mites with different host ranges, Tetranychus urticae (1200 plants) and Tetranychus truncatus (90 plants). Data from multiple populations of both species domesticated on common beans and transferred to new plant hosts (cotton, cucumber, eggplant) were used to investigate transcriptional plasticity relative to population-based variation in gene expression. Compared to T. truncatus, T. urticae exhibited much higher transcriptional plasticity. Populations of this species also showed much more variable expression regulation in response to a plant host, particularly for genes related to detoxification, transport, and transcriptional factors. In response to the different plant hosts, both polyphagous species showed enriched processes of drug/xenobiotics metabolism, with T. urticae orchestrating a relatively broader array of biological pathways. Through co-expression network analysis, we identified gene modules associated with host plant response, revealing shared hub genes primarily involved in detoxification metabolism when both mites fed on the same plants. After silencing a shared hub CYP gene related to eggplant exposure, the performance of both species on the original bean host improved, but the fecundity of T. truncatus decreased when feeding on eggplant. The extensive transcriptomic variation shown by T. urticae might serve as a potential compensatory mechanism for a deficiency of hub genes in this species. This research points to nuanced differences in transcriptomic variability between generalist herbivores.

Exploring the molecular mechanism of sepsis-associated encephalopathy by integrated analysis of multiple datasets.

BACKGROUND: We aim to deal with the Hub-genes and signalling pathways connected with Sepsis-associated encephalopathy (SAE). METHODS: The raw datasets were acquired from the Gene Expression Omnibus (GEO) database (GSE198861 and GSE167610). R software filtered the differentially expressed genes (DEGs) for hub genes exploited for Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Hub genes were identified from the intersection of DEGs via protein-protein interaction (PPI) network. And the single-cell dataset (GSE101901) was used to authenticate where the hub genes express in hippocampus cells. Cell-cell interaction analysis and Gene Set Variation Analysis (GSVA) analysis of the whole transcriptome validated the interactions between hippocampal cells. RESULTS: A total of 161 DEGs were revealed in GSE198861 and GSE167610 datasets. Biological function analysis showed that the DEGs were primarily involved in the phagosome pathway and significantly enriched. The PPI network extracted 10 Hub genes. The M2 Macrophage cell decreased significantly during the acute period, and the hub gene may play a role in this biological process. The hippocampal variation pathway was associated with the MAPK signaling pathway. CONCLUSION: Hub genes (Pecam1, Cdh5, Fcgr, C1qa, Vwf, Vegfa, C1qb, C1qc, Fcgr4 and Fcgr2b) may paticipate in the biological process of SAE.

Identification of differentially expressed ER stress-related genes and their association with pulmonary arterial hypertension.

BACKGROUND: Pulmonary arterial hypertension (PAH) is a complex and progressive illness that has a multifaceted origin, significant fatality rates, and profound effects on health. The pathogenesis of PAH is poorly defined due to the insufficient understanding of the combined impact of endoplasmic reticulum (ER) stress and immune infiltration, both of which play vital roles in PAH development. This study aims to identify potential ER stress-related biomarkers in PAH and investigate their involvement in immune infiltration. METHODS: The GEO database was used to download gene expression profiles. Genes associated with ER stress were obtained from the MSigDB database. Weighted gene co-expression network analysis (WGCNA), GO, KEGG, and protein-protein interaction (PPI) were utilized to conduct screening of hub genes and explore potential molecular mechanisms. Furthermore, the investigation also delved into the presence of immune cells in PAH tissues and the correlation between hub genes and the immune system. Finally, we validated the diagnostic value and expression levels of the hub genes in PAH using subject-workup characterization curves and real-time quantitative PCR. RESULTS: In the PAH and control groups, a total of 31 genes related to ER stress were found to be differentially expressed. The enrichment analysis revealed that these genes were primarily enriched in reacting to stress in the endoplasmic reticulum, dealing with unfolded proteins, transporting proteins, and processing proteins within the endoplasmic reticulum. EIF2S1, NPLOC4, SEC61B, SYVN1, and DERL1 were identified as the top 5 hub genes in the PPI network. Immune infiltration analysis revealed that these hub genes were closely related to immune cells. The receiver operating characteristic (ROC) curves revealed that the hub genes exhibited excellent diagnostic efficacy for PAH. The levels of SEC61B, NPLOC4, and EIF2S1 expression were in agreement with the findings of bioinformatics analysis in the PAH group. CONCLUSIONS: Potential biomarkers that could be utilized are SEC61B, NPLOC4, and EIF2S1, as identified in this study. The infiltration of immune cells was crucial to the development and advancement of PAH. This study provided new potential therapeutic targets for PAH.

Identification of key genes associated with cervical cancer based on bioinformatics analysis.

BACKGROUND: Cervical cancer has extremely high morbidity and mortality, and its pathogenesis is still in the exploratory stage. This study aimed to screen and identify differentially expressed genes (DEGs) related to cervical cancer through bioinformatics analysis. METHODS: GSE63514 and GSE67522 were selected from the GEO database to screen DEGs. Then GO and KEGG analysis were performed on DEGs. PPI network of DEGs was constructed through STRING website, and the hub genes were found through 12 algorithms of Cytoscape software. Meanwhile, GSE30656 was selected from the GEO database to screen DEMs. Target genes of DEMs were screened through TagetScan, miRTarBase and miRDB. Next, the hub genes screened from DEGs were merged with the target genes screened from DEMs. Finally, ROC curve and nomogram analysis were performed to assess the predictive capabilities of the hub genes. The expression of these hub genes were verified through TCGA, GEPIA, qRT-PCR, and immunohistochemistry. RESULTS: Six hub genes, TOP2A, AURKA, CCNA2, IVL, KRT1, and IGFBP5, were mined through the protein-protein interaction network. The expression of these hub genes were verified through TCGA, GEPIA, qRT-PCR, and immunohistochemistry, and it was found that TOP2A, AURKA as well as CCNA2 were overexpressed and IGFBP5 was low expression in cervical cancer. CONCLUSIONS: This study showed that TOP2A, AURKA, CCNA2 and IGFBP5 screened through bioinformatics analysis were significantly differentially expressed in cervical cancer samples compared with normal samples, which might be biomarkers of cervical cancer.

ANK1 inhibits malignant progression of osteosarcoma by promoting ferroptosis.

PURPOSE: Osteosarcoma (OS) is a primary bone tumor with high malignancy and poor prognosis. Ferroptosis plays a crucial role in OS. This study aimed to evaluate the effects of Ankyrin 1 (ANK1) on OS and to investigate its specific mechanisms. METHODS: Microarray datasets related to "osteosarcoma" were selected for this study. Relevant hub genes in OS were identified through bioinformatics analysis. Transfected U-2OS and MG-63 cells were used for in vitro experiments. The effects of ANK1 overexpression on cell viability, migration, and invasion were determined through CCK-8, wound healing, and transwell assays. An OS mouse model was established for the in vivo experiments. Hematoxylin-eosin staining and immunohistochemistry were conducted to observe the histological effects of ANK1 overexpression on mouse tumors. TUNEL staining was performed to evaluate apoptosis in mouse. RESULTS: There were 159 common differentially expressed genes in the GSE16088 and GSE19276 datasets. The hub genes ANK1, AHSP, GYPB, GYPA, KEL, and ALAS2 were identified. Pan-cancer analysis verified that ANK1 was closely associated with cancer prognosis and immune infiltration. Furthermore, ANK1 overexpression inhibited the proliferation, migration, and invasion of OS cells and promoted ferroptosis, while ferroptosis inhibitor (fer-1) weakened these effects. Moreover, ANK1 overexpression suppressed tumor growth, promoted apoptosis, reduced the number of Ki67 positive cells, and elevated the number of caspase-3 positive cells in vivo. CONCLUSIONS: ANK1 is a prognosis biomarker of OS that can alleviate the progression of OS by promoting ferroptosis.

Identification of Pyroptosis-Related Genes Regulating the Progression of Chronic Rhinosinusitis with Nasal Polyps.

INTRODUCTION: Chronic rhinosinusitis with nasal polyps (CRSwNP) is an immunologic disease, and pyroptosis, an inflammation-based cellular death, strictly modulates CRSwNP pathology, whereas the pyroptosis genes and mechanisms involved in CRSwNP remain unclear. Herein, we explored disease biomarkers and potential therapeutic targets for pyroptosis and immune regulation in CRSwNP using bioinformatics analysis and tissue-based verification. METHODS: We retrieved the transcriptional profiles of the high-throughput dataset GSE136825 from the Gene Expression Omnibus database, as well as 170 pyroptosis-related gene expressions from GeneCards. Using R, we identified differentially expressed pyroptosis-related genes and examined the potential biological functions of the aforementioned genes using Gene Ontology, Kyoto Encyclopedia of the Genome pathway, immune infiltration, and protein-protein interaction (PPI) network analyses, thereby generating a list of hub genes. The hub genes were, in turn, verified using real-time quantitative polymerase chain reaction (qRT-PCR), immunohistochemistry (IHC), and Western blotting (WB). Ultimately, using the StarBase and miRTarBase databases, we estimated the targeting microRNAs and long chain non-coding RNAs. RESULTS: We demonstrated that the identified pyroptosis-related genes primarily modulated bacterial defense activities, as well as inflammasome immune response and assembly. Moreover, they were intricately linked to neutrophil and macrophage infiltration. Furthermore, we validated the tissue contents of hub genes AIM2, NLPR6, and CASP5 and examined potential associations with clinical variables. We also developed a competitive endogenous RNA (ceRNA) modulatory axis to examine possible underlying molecular mechanisms. CONCLUSION: We found AIM2, CASP5, and NLRP6, three hub genes for pyroptosis in chronic rhinosinusitis with nasal polyps, by biological analysis, experimental validation, and clinical variable validation.

Identification and evaluation of candidate COVID-19 critical genes and medicinal drugs related to plasma cells.

The ongoing COVID-19 pandemic, caused by the SARS-CoV-2 virus, represents one of the most significant global health crises in recent history. Despite extensive research into the immune mechanisms and therapeutic options for COVID-19, there remains a paucity of studies focusing on plasma cells. In this study, we utilized the DESeq2 package to identify differentially expressed genes (DEGs) between COVID-19 patients and controls using datasets GSE157103 and GSE152641. We employed the xCell algorithm to perform immune infiltration analyses, revealing notably elevated levels of plasma cells in COVID-19 patients compared to healthy individuals. Subsequently, we applied the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm to identify COVID-19 related plasma cell module genes. Further, positive cluster biomarker genes for plasma cells were extracted from single-cell RNA sequencing data (GSE171524), leading to the identification of 122 shared genes implicated in critical biological processes such as cell cycle regulation and viral infection pathways. We constructed a robust protein-protein interaction (PPI) network comprising 89 genes using Cytoscape, and identified 20 hub genes through cytoHubba. These genes were validated in external datasets (GSE152418 and GSE179627). Additionally, we identified three potential small molecules (GSK-1070916, BRD-K89997465, and idarubicin) that target key hub genes in the network, suggesting a novel therapeutic approach. These compounds were characterized by their ability to down-regulate AURKB, KIF11, and TOP2A effectively, as evidenced by their low free binding energies determined through computational analyses using cMAP and AutoDock. This study marks the first comprehensive exploration of plasma cells' role in COVID-19, offering new insights and potential therapeutic targets. It underscores the importance of a systematic approach to understanding and treating COVID-19, expanding the current body of knowledge and providing a foundation for future research.

Single-cell RNA sequencing reveals hub genes of myocardial infarction-associated endothelial cells.

BACKGROUND: Myocardial infarction (MI) is a cardiovascular disease that seriously threatens human health. Dysangiogenesis of endothelial cells (ECs) primarily inhibits recovery from MI, but the specific mechanism remains to be further elucidated. METHODS: In this study, the single-cell RNA-sequencing data from both MI and Sham mice were analyzed by the Seurat Package (3.2.2). The number of ECs in MI and Sham groups were compared by PCA and tSNE algorithm. FindMarkers function of Seurat was used to analyze the DEGs between the MI and Sham groups. Then, the ECs was further clustered into 8 sub-clusters for trajectory analysis. The BEAM was used to analyze the branch point 3 and cluster the results. In addition, the DEGs in the microarray data set of MI and Sham mice were cross-linked, and the cross-linked genes were used to construct PPI networks. The key genes with the highest degree were identified and analyzed for functional enrichment. Finally, this study cultured human umbilical vein endothelial cells (HUVECs), established hypoxia models, and interfered with hub gene expression in cells. The impact of hub genes on the migration and tube formation of hypoxic-induced HUVECs were verified by Wound healing assays and tubule formation experiments. RESULTS: The number and proportion of ECs in the MI group were significantly lower than those in the Sham group. Meantime, 225 DEGs were found in ECs between the MI and Sham groups. Through trajectory analysis, EC4 was found to play an important role in MI. Then, by using BEAM to analyze the branch point 3, and clustering the results, a total of 495 genes were found to be highly expressed in cell Fate2 (mainly EC4). In addition, a total of 194 DEGs were identified in Micro array dataset containing both MI and Sham mice. The hub genes (Timp1 and Fn1) with the highest degree were identified. Inhibiting Timp1 and Fn1 expression promoted the migration and tube formation of HUVECs. CONCLUSIONS: Our data highlighted the non-linear dynamics of ECs in MI, and provided a foothold for analyzing cardiac homeostasis and pro-angiogenesis in MI.