Identification of the molecular subgroups in coronary artery disease by gene expression profiles

Molecular mechanisms of EGCG-CSH/n-HA/CMC in promoting osteogenic differentiation and macrophage polarization

2. This research investigates the impact of the EGCG-CSH/n-HA/CMC composite material on bone defect repair, emphasizing its influence on macrophage polarization and osteogenic differentiation of BMSCs. Comprehensive evaluations of the composite's physical and chemical characteristics were performed. BMSC response to the material was tested in vitro for proliferation, migration, and osteogenic potential. An SD rat model was employed for in vivo assessments of bone repair efficacy. Both transcriptional and proteomic analyses were utilized to delineate the mechanisms influencing macrophage behavior and stem cell differentiation. The material maintained excellent structural integrity and significantly promoted BMSC functions critical to bone healing. In vivo results confirmed accelerated bone repair, and molecular analysis highlighted the role of macrophage M2 polarization, particularly through changes in the SIRPA gene and protein expression. EGCG-CSH/n-HA/CMC plays a significant role in enhancing bone repair, with implications for macrophage and BMSC function. Our findings suggest that targeting SIRPA may offer new therapeutic opportunities for bone regeneration.

Resveratrol suppresses liver cancer progression by downregulating AKR1C3: targeting HCC with HSA nanomaterial as a carrier to enhance therapeutic efficacy

The enzyme AKR1C3 plays a crucial role in hormone and drug metabolism and is associated with abnormal expression in liver cancer, leading to tumor progression and poor prognosis. Nanoparticles modified with HSA can modulate the tumor microenvironment by enhancing photodynamic therapy to induce apoptosis in tumor cells and alleviate hypoxia. Therefore, exploring the potential regulatory mechanisms of resveratrol on AKR1C3 through the construction of HSA-RSV NPs carriers holds significant theoretical and clinical implications for the treatment of liver cancer. The aim of this study is to investigate the targeted regulation of AKR1C3 expression through the loading of resveratrol (RSV) on nanomaterials HSA-RSV NPs (Nanoparticles) in order to alleviate tumor hypoxia and inhibit the progression of hepatocellular carcinoma (HCC), and to explore its molecular mechanism. PubChem database and PharmMapper server were used to screen the target genes of RSV. HCC-related differentially expressed genes (DEGs) were analyzed through the GEO dataset, and relevant genes were retrieved from the GeneCards database, resulting in the intersection of the three to obtain candidate DEGs. GO and KEGG enrichment analyses were performed on the candidate DEGs to analyze the potential cellular functions and molecular signaling pathways affected by the main target genes. The cytohubba plugin was used to screen the top 10 target genes ranked by Degree and further intersected the results of LASSO and Random Forest (RF) to obtain hub genes. The expression analysis of hub genes and the prediction of malignant tumor prognosis were conducted. Furthermore, a pharmacophore model was constructed using PharmMapper. Molecular docking simulations were performed using AutoDockTools 1.5.6 software, and ROC curve analysis was performed to determine the core target. In vitro cell experiments were carried out by selecting appropriate HCC cell lines, treating HCC cells with different concentrations of RSV, or silencing or overexpressing AKR1C3 using lentivirus. CCK-8, clone formation, flow cytometry, scratch experiment, and Transwell were used to measure cancer cell viability, proliferation, migration, invasion, and apoptosis, respectively. Cellular oxygen consumption rate was analyzed using the Seahorse XF24 analyzer. HSA-RSV NPs were prepared, and their characterization and cytotoxicity were evaluated. The biological functional changes of HCC cells after treatment were detected. An HCC subcutaneous xenograft model was established in mice using HepG2 cell lines. HSA-RSV NPs were injected via the tail vein, with a control group set, to observe changes in tumor growth, tumor targeting of NPs, and biological safety. TUNEL, Ki67, and APC-hypoxia probe staining were performed on excised tumor tissue to detect tumor cell proliferation, apoptosis, and hypoxia. Lentivirus was used to silence or overexpress AKR1C3 simultaneously with the injection of HSA-RSV NPs via the tail vein to assess the impact of AKR1C3 on the regulation of HSA-RSV NPs in HCC progression. Bioinformatics analysis revealed that AKR1C3 is an important target gene involved in the regulation of HCC by RSV, which is associated with the prognosis of HCC patients and upregulated in expression. In vitro cell experiments showed that RSV significantly inhibits the respiratory metabolism of HCC cells, suppressing their proliferation, migration, and invasion and promoting apoptosis. Silencing AKR1C3 further enhances the toxicity of RSV towards HCC cells. The characterization and cytotoxicity experiments of nanomaterials demonstrated the successful construction of HSA-RSV NPs, which exhibited stronger inhibitory effects on HCC cells. In vivo, animal experiments further confirmed that targeted downregulation of AKR1C3 by HSA-RSV NPs suppresses the progression of HCC and tumor hypoxia while exhibiting tumor targeting and biological safety. Targeted downregulation of AKR1C3 by HSA-RSV NPs can alleviate HCC tumor hypoxia and inhibit the progression of HCC.

Targeting CSF1R in myeloid-derived suppressor cells: insights into its immunomodulatory functions in colorectal cancer and therapeutic implications

OBJECTIVE

This study aimed to investigate the critical role of MDSCs in CRC immune suppression, focusing on the CSF1R and JAK/STAT3 signaling axis. Additionally, it assessed the therapeutic efficacy of LNCs@CSF1R siRNA and anti-PD-1 in combination.

METHODS

Single-cell transcriptome sequencing data from CRC and adjacent normal tissues identified MDSC-related differentially expressed genes. RNA-seq analysis comprehensively profiled MDSC gene expression in murine CRC tumors. LNCs@CSF1R siRNA nanocarriers effectively targeted and inhibited CSF1R. Flow cytometry quantified changes in MDSC surface markers post-CSF1R inhibition. RNA-seq and pathway enrichment analyses revealed the impact of CSF1R on MDSC metabolism and signaling. The effect of CSF1R inhibition on the JAK/STAT3 signaling axis was validated using Colivelin and metabolic assessments. Glucose and fatty acid uptake were measured via fluorescence-based flow cytometry. The efficacy of LNCs@CSF1R siRNA and anti-PD-1, alone and in combination, was evaluated in a murine CRC model with extensive tumor section analyses.

RESULTS

CSF1R played a significant role in MDSC-mediated immune suppression. LNCs@CSF1R siRNA nanocarriers effectively targeted MDSCs and inhibited CSF1R. CSF1R regulated MDSC fatty acid metabolism and immune suppression through the JAK/STAT3 signaling axis. Inhibition of CSF1R reduced STAT3 activation and target gene expression, which was rescued by Colivelin. Combined treatment with LNCs@CSF1R siRNA and anti-PD-1 significantly slowed tumor growth and reduced MDSC abundance within CRC tumors.

CONCLUSION

CSF1R via the JAK/STAT3 axis critically regulates MDSCs, particularly in fatty acid metabolism and immune suppression. Combined therapy with LNCs@CSF1R siRNA and anti-PD-1 enhances therapeutic efficacy in a murine CRC model, providing a strong foundation for future clinical applications.

Delivery of miR-15b-5p via magnetic nanoparticle-enhanced bone marrow mesenchymal stem cell-derived extracellular vesicles mitigates diabetic osteoporosis by targeting GFAP

Diabetic osteoporosis (DO) presents significant clinical challenges. This study aimed to investigate the potential of magnetic nanoparticle-enhanced extracellular vesicles (GMNPE-EVs) derived from bone marrow mesenchymal stem cells (BMSCs) to deliver miR-15b-5p, thereby targeting and downregulating glial fibrillary acidic protein (GFAP) expression in rat DO models. Data was sourced from DO-related RNA-seq datasets combined with GEO and GeneCards databases. Rat primary BMSCs, bone marrow-derived macrophages (BMMs), and osteoclasts were isolated and cultured. EVs were separated, and GMNPE targeting EVs were synthesized. Bioinformatic analysis revealed a high GFAP expression in DO-related RNA-seq and GSE26168 datasets for disease models. Experimental results confirmed elevated GFAP in rat DO bone tissues, promoting osteoclast differentiation. miR-15b-5p was identified as a GFAP inhibitor, but was significantly downregulated in DO and enriched in BMSC-derived EVs. In vitro experiments showed that GMNPE-EVs could transfer miR-15b-5p to osteoclasts, downregulating GFAP and inhibiting osteoclast differentiation. In vivo tests confirmed the therapeutic potential of this approach in alleviating rat DO. Collectively, GMNPE-EVs can effectively deliver miR-15b-5p to osteoclasts, downregulating GFAP expression, and hence, offering a therapeutic strategy for rat DO.

Molecular mechanisms of Codonopsis pilosula in inhibiting hepatocellular carcinoma growth and metastasis

BACKGROUND

Liver cancer, one of the most common types of cancer worldwide, accounts for millions of cases annually. With its multi-target and wide-ranging therapeutic effects, traditional Chinese medicine has emerged as a potential approach for treating various tumors. Codonopsis pilosula, a traditional herb, is known for its anti-inflammatory and antioxidant properties. In this study, we investigated the potential molecular mechanisms of Codonopsis pilosula in regulating the inhibition of CDK1 and the modulation of PDK1/β-catenin, which are involved in hepatocellular carcinoma growth and metastasis.

STUDY DESIGN/METHODS

Firstly, we screened the active chemical constituents of Codonopsis pilosula and identified their respective target proteins using the Herb database. Then, we applied the GeneCards database and transcriptome sequencing analysis to screen for critical genes associated with the occurrence and development of liver cancer. The intersection of the target proteins and disease-related genes was used to determine the potential targets of Codonopsis pilosula in hepatocellular carcinoma. Protein-protein interaction analysis and GO/KEGG analysis were subsequently performed to uncover the pathways through which Codonopsis pilosula acts on liver cancer. The Huh-7 cell line, exhibiting the highest sensitivity to Codonopsis pilosula polysaccharide solution (CPP) intervention, was chosen for subsequent studies. Cell viability was evaluated using the CCK-8 assay, colony formation assay was conducted to determine cell proliferation capacity, flow cytometry was used to analyze cell cycle, TUNEL staining was performed to assess cell apoptosis, scratch assay was carried out to evaluate cell migration ability, the expression of EMT-related proteins was detected and analyzed, and cell sphere formation assay was conducted to investigate cell stemness. Finally, a liver cancer animal model was established, and different doses of CPP were administered via gavage the next day. The expression levels of CDK1, PDK1, and β-catenin in mouse liver tissues were detected and analyzed, immunohistochemistry staining was performed to assess the expression of tumor cell proliferation-related proteins Ki67 and PCNA in mouse xenografts, and TUNEL staining was carried out to evaluate cell apoptosis in mouse liver tissues. After intervention with CDK1 expression, the expression levels of CDK1, PDK1, and β-catenin proteins and mRNA in each group of cells were detected using Western blot and RT-qPCR.

RESULTS

Through network pharmacology analysis, transcriptome sequencing, and bioinformatics analysis, 35 target genes through which Codonopsis pilosula acts on liver cancer were identified. Among them, CDK1, with the highest degree in the PPI network, was considered an essential target protein for Codonopsis pilosula in treating liver cancer. In vitro cell experiments revealed that CPP could inhibit the expression of CDK1/PDK1/β-catenin signaling axis factors, suppress cell proliferation, decrease cell migration ability, influence the EMT process, and reduce cell stemness by inhibiting CDK1 and affecting the PDK1/β-catenin signaling axis. Similarly, in vivo experiments demonstrated that CPP could regulate the CDK1/PDK1/β-catenin signaling axis, inhibit tumor growth, and induce cell apoptosis.

CONCLUSION

Codonopsis pilosula may inhibit hepatocellular carcinoma growth by suppressing CDK1 and affecting the PDK1/β-catenin signaling axis, limiting cell EMT and reducing cell stemness. These findings provide insights into the potential therapeutic role of Codonopsis pilosula in liver cancer.

Dexmedetomidine enhances Mitophagy via PINK1 to alleviate hippocampal neuronal Pyroptosis and improve postoperative cognitive dysfunction in elderly rat

Postoperative cognitive dysfunction (POCD) is a common complication in elderly surgical patients, significantly affecting their quality of life. Dexmedetomidine (Dex), an anesthetic, has shown promise in alleviating POCD, but its underlying mechanism remains unclear. This study aims to explore how Dex improves POCD in aged rats by targeting the PINK1-mediated mitochondrial autophagy pathway, reducing caspase-1/11-GSDMD-induced hippocampal neuronal pyroptosis. Transcriptome sequencing identified 300 differentially expressed genes enriched in the mitochondrial autophagy pathway in Dex-treated POCD rat hippocampal tissue, with Pink1 as a key candidate. In a POCD rat model, Dex treatment upregulated hippocampal PINK1 expression. In vitro experiments using H19-7 rat hippocampal neurons revealed that Dex enhanced mitochondrial autophagy and suppressed neuronal pyroptosis by upregulating PINK1. Further mechanistic validation demonstrated that Dex activated PINK1-mediated mitochondrial autophagy, inhibiting caspase-1/11-GSDMD-induced neuronal pyroptosis. In vivo experiments confirmed Dex's ability to reduce caspase-1/11-GSDMD-dependent hippocampal neuronal pyroptosis and improve postoperative cognitive function in aged rats. Dexmedetomidine improves postoperative cognitive dysfunction in elderly rats by enhancing mitochondrial autophagy via PINK1 upregulation, mitigating caspase-1/11-GSDMD-induced neuronal pyroptosis.

HIF-1α Pathway Orchestration by LCN2: A Key Player in Hypoxia-Mediated Colitis Exacerbation

In this study, we investigated the role of hypoxia in the development of chronic inflammatory bowel disease (IBD), focusing on its impact on the HIF-1α signaling pathway through the upregulation of lipocalin 2 (LCN2). Using a murine model of colitis induced by sodium dextran sulfate (DSS) under hypoxic conditions, transcriptome sequencing revealed LCN2 as a key gene involved in hypoxia-mediated exacerbation of colitis. Bioinformatics analysis highlighted the involvement of crucial pathways, including HIF-1α and glycolysis, in the inflammatory process. Immune infiltration analysis demonstrated the polarization of M1 macrophages in response to hypoxic stimulation. In vitro studies using RAW264.7 cells further elucidated the exacerbation of inflammation and its impact on M1 macrophage polarization under hypoxic conditions. LCN2 knockout cells reversed hypoxia-induced inflammatory responses, and the HIF-1α pathway activator dimethyloxaloylglycine (DMOG) confirmed LCN2's role in mediating inflammation via the HIF-1α-induced glycolysis pathway. In a DSS-induced colitis mouse model, oral administration of LCN2-silencing lentivirus and DMOG under hypoxic conditions validated the exacerbation of colitis. Evaluation of colonic tissues revealed altered macrophage polarization, increased levels of inflammatory factors, and activation of the HIF-1α and glycolysis pathways. In conclusion, our findings suggest that hypoxia exacerbates colitis by modulating the HIF-1α pathway through LCN2, influencing M1 macrophage polarization in glycolysis. This study contributes to a better understanding of the mechanisms underlying IBD, providing potential therapeutic targets for intervention.

Identification of metabolism-related key genes as potential biomarkers for pathogenesis of immune thrombocytopenia

Immune thrombocytopenia (ITP), an acquired autoimmune disease, is characterized by immune-mediated platelet destruction. A biomarker is a biological entity that contributes to disease pathogenesis and reflects disease activity. Metabolic alterations are reported to be associated with the occurrence of various diseases. As metabolic biomarkers for ITP have not been identified. This study aimed to identify metabolism-related differentially expressed genes as potential biomarkers for pathogenesis of ITP using bioinformatic analyses.The microarray expression data of the peripheral blood mononuclear cells were downloaded from the Gene Expression Omnibus database (GSE112278 download link: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE112278 ). Key module genes were intersected with metabolism-related genes to obtain the metabolism-related key candidate genes. The hub genes were screened based on the degree function in the coytoscape sofware. The key ITP-related genes were subjected to functional enrichment analysis. Immune infiltration analysis was performed using a single-sample gene set enrichment analysis algorithm to evaluate the differential infiltration levels of immune cell types between ITP patient and control. Molecular subtypes were identified based on the expression of hub genes. The expression of hub genes in the ITP patients was validated using quantitative real-time polymerase chain reaction analysis. This study identified five hub genes (ADH4, CYP7A1, CYP1A2, CYP8B1, and NR1H4), which were be associated with the pathogenesis of ITP, and two molecular subtypes of ITP. Among these hub genes, CYP7A1 and CYP8B1 involved in cholesterol metabolism,were further verified in clinical samples.

circRNA-PTPN4 mediated regulation of FOXO3 and ZO-1 expression: implications for blood-brain barrier integrity and cognitive function in uremic encephalopathy

Uremic encephalopathy (UE) poses a significant challenge in neurology, leading to the need to investigate the involvement of non-coding RNA (ncRNA) in its development. This study employed ncRNA-seq and RNA-seq approaches to identify fundamental ncRNAs, specifically circRNA and miRNA, in the pathogenesis of UE using a mouse model. In vitro and in vivo experiments were conducted to explore the circRNA-PTPN4/miR-301a-3p/FOXO3 axis and its effects on blood-brain barrier (BBB) function and cognitive abilities. The research revealed that circRNA-PTPN4 binds to and inhibits miR-301a-3p, leading to an increase in FOXO3 expression. This upregulation results in alterations in the transcriptional regulation of ZO-1, affecting the permeability of human brain microvascular endothelial cells (HBMECs). The axis also influences the growth, proliferation, and migration of HBMECs. Mice with UE exhibited cognitive deficits, which were reversed by overexpression of circRNA-PTPN4, whereas silencing FOXO3 exacerbated these deficits. Furthermore, the uremic mice showed neuronal loss, inflammation, and dysfunction in the BBB, with the expression of circRNA-PTPN4 demonstrating therapeutic effects. In conclusion, circRNA-PTPN4 plays a role in promoting FOXO3 expression by sequestering miR-301a-3p, ultimately leading to the upregulation of ZO-1 expression and restoration of BBB function in mice with UE. This process contributes to the restoration of cognitive abilities.

TIE2 expression in hypertensive ICH and its therapeutic modulation with AKB-9778: Implications for brain vascular health

Hypertensive intracerebral hemorrhage (ICH) is a devastating condition, the molecular underpinnings of which remain not fully understood. By leveraging high-throughput transcriptome sequencing and network pharmacology analysis, this study unveils the significant role of the tyrosine kinase with immunoglobulin-like and EGF-like domains 2 (TIE2) in ICH pathogenesis. Compared to controls, a conspicuous downregulation of TIE2 was observed in the cerebral blood vessels of hypertensive ICH mice. In vitro assays with human brain microvascular endothelial cells (HBMEC), HBEC-5i revealed that modulation of TIE2 expression significantly influences cellular proliferation, migration, and angiogenesis, mediated via the Rap1/MEK/ERK signaling pathway. Notably, the small molecule AKB-9778 was identified to target and activate TIE2, affecting the functional attributes of HBEC-5i. In vivo experiments further demonstrated that combining AKB-9778 with antihypertensive drugs could mitigate the incidence and volume of bleeding in hypertensive ICH mouse models, suggesting potential therapeutic implications.

Detecting early-warning biomarkers associated with heart-exosome genetic-signature for acute myocardial infarction: A source-tracking study of exosome

The genetic information of plasma total-exosomes originating from tissues have already proven useful to assess the severity of coronary artery diseases (CAD). However, plasma total-exosomes include multiple sub-populations secreted by various tissues. Only analysing the genetic information of plasma total-exosomes is perturbed by exosomes derived from other organs except the heart. We aim to detect early-warning biomarkers associated with heart-exosome genetic-signatures for acute myocardial infarction (AMI) by a source-tracking analysis of plasma exosome. The source-tracking of AMI plasma total-exosomes was implemented by deconvolution algorithm. The final early-warning biomarkers associated with heart-exosome genetic-signatures for AMI was identified by integration with single-cell sequencing, weighted gene correction network and machine learning analyses. The correlation between biomarkers and clinical indicators was validated in impatient cohort. A nomogram was generated using early-warning biomarkers for predicting the CAD progression. The molecular subtypes landscape of AMI was detected by consensus clustering. A higher fraction of exosomes derived from spleen and blood cells was revealed in plasma exosomes, while a lower fraction of heart-exosomes was detected. The gene ontology revealed that heart-exosomes genetic-signatures was associated with the heart development, cardiac function and cardiac response to stress. We ultimately identified three genes associated with heart-exosomes defining early-warning biomarkers for AMI. The early-warning biomarkers mediated molecular clusters presented heterogeneous metabolism preference in AMI. Our study introduced three early-warning biomarkers associated with heart-exosome genetic-signatures, which reflected the genetic information of heart-exosomes carrying AMI signals and provided new insights for exosomes research in CAD progression and prevention.

A precise molecular subtyping of ulcerative colitis reveals the immune heterogeneity and predicts clinical drug responses

BACKGROUND AND AIMS

We sought to identify novel molecular subtypes of ulcerative colitis (UC) based on large-scale cohorts and establish a clinically applicable subtyping system for the precision treatment of the disease.

METHODS

Eight microarray profiles containing colon samples from 357 patients were utilized. Expression heterogeneity was screened out and stable subtypes were identified among UC patients. Immune infiltration pattern and biological agent response were compared among subtypes to assess the value in guiding treatment. The relationship between PRLR and TNFSF13B genes with the highest predictive value was further validated by functional experiments.

RESULTS

Three stable molecular subtypes were successfully identified. Immune cell infiltration analysis defined three subtypes as innate immune activated UC (IIA), whole immune activated UC (WIA), and immune homeostasis like UC (IHL). Notably, the response rate towards biological agents (infliximab/vedolizumab) in WIA patients was the lowest (less than 10%), while the response rate in IHL patients was the highest, ranging from 42 to 60%. Among the featured genes of subtypes, the ratio of PRLR to TNFSF13B could effectively screen for IHL UC subtype suitable for biological agent therapies (Area under curve: 0.961-0.986). Furthermore, we demonstrated that PRLR expressed in epithelial cells could inhibit the expression of TNFSF13B in monocyte-derived macrophages through the CXCL1-NF-κB pathway.

CONCLUSIONS

We identified three stable UC subtypes with a heterogeneous immune pattern and different response rates towards biological agents for the first time. We also established a precise molecular subtyping system and classifier to predict clinical drug response and provide individualized treatment strategies for UC patients.

Phenomics and Robust Multiomics Data for Cardiovascular Disease Subtyping

The complex landscape of cardiovascular diseases encompasses a wide range of related pathologies arising from diverse molecular mechanisms and exhibiting heterogeneous phenotypes. This variety of manifestations poses significant challenges in the development of treatment strategies. The increasing availability of precise phenotypic and multiomics data of cardiovascular disease patient populations has spurred the development of a variety of computational disease subtyping techniques to identify distinct subgroups with unique underlying pathogeneses. In this review, we outline the essential components of computational approaches to select, integrate, and cluster omics and clinical data in the context of cardiovascular disease research. We delve into the challenges faced during different stages of the analysis, including feature selection and extraction, data integration, and clustering algorithms. Next, we highlight representative applications of subtyping pipelines in heart failure and coronary artery disease. Finally, we discuss the current challenges and future directions in the development of robust subtyping approaches that can be implemented in clinical workflows, ultimately contributing to the ongoing evolution of precision medicine in health care.

Aging and obesity prime the methylome and transcriptome of adipose stem cells for disease and dysfunction

The epigenome of stem cells occupies a critical interface between genes and environment, serving to regulate expression through modification by intrinsic and extrinsic factors. We hypothesized that aging and obesity, which represent major risk factors for a variety of diseases, synergistically modify the epigenome of adult adipose stem cells (ASCs). Using integrated RNA- and targeted bisulfite-sequencing in murine ASCs from lean and obese mice at 5- and 12-months of age, we identified global DNA hypomethylation with either aging or obesity, and a synergistic effect of aging combined with obesity. The transcriptome of ASCs in lean mice was relatively stable to the effects of age, but this was not true in obese mice. Functional pathway analyses identified a subset of genes with critical roles in progenitors and in diseases of obesity and aging. Specifically, Mapt, Nr3c2, App, and Ctnnb1 emerged as potential hypomethylated upstream regulators in both aging and obesity (AL vs. YL and AO vs. YO), and App, Ctnnb1, Hipk2, Id2, and Tp53 exhibited additional effects of aging in obese animals. Furthermore, Foxo3 and Ccnd1 were potential hypermethylated upstream regulators of healthy aging (AL vs. YL), and of the effects of obesity in young animals (YO vs. YL), suggesting that these factors could play a role in accelerated aging with obesity. Finally, we identified candidate driver genes that appeared recurrently in all analyses and comparisons undertaken. Further mechanistic studies are needed to validate the roles of these genes capable of priming ASCs for dysfunction in aging- and obesity-associated pathologies.

Myeloid- and hepatocyte-specific deletion of group VIA calcium-independent phospholipase A2 leads to dichotomous opposing phenotypes during MCD diet-induced NASH

Polymorphisms of phospholipase A2VIA (iPLA2β or PLA2G6) are associated with body weights and blood C-reactive protein. The role of iPLA2β/PLA2G6 in non-alcoholic steatohepatitis (NASH) is still elusive because female iPla2β-null mice showed attenuated hepatic steatosis but exacerbated hepatic fibrosis after feeding with methionine- and choline-deficient diet (MCDD). Herein, female mice with myeloid- (MPla2g6^-/-) and hepatocyte- (LPla2g6^-/-) specific PLA2G6 deletion were generated and phenotyped after MCDD feeding. Without any effects on hepatic steatosis, MCDD-fed MPla2g6^-/- mice showed further exaggeration of liver inflammation and fibrosis as well as elevation of plasma TNFα, CCL2, and circulating monocytes. Bone-marrow-derived macrophages (BMDMs) from MPla2g6^-/- mice displayed upregulation of PPARγ and CEBPα proteins, and elevated release of IL6 and CXCL1 under LPS stimulation. LPS-stimulated BMDMs from MCDD-fed MPla2g6^-/- mice showed suppressed expression of M1 Tnfa and Il6, but marked upregulation of M2 Arg1, Chil3, IL10, and IL13 as well as chemokine receptors Ccr2 and Ccr5. This in vitro shift was associated with exaggeration of hepatic M1/M2 cytokines, chemokines/chemokine receptors, and fibrosis genes. Contrarily, MCDD-fed LPla2g6^-/- mice showed a complete protection which was associated with upregulation of Ppara/PPARα and attenuated expression of Pparg/PPARγ, fatty-acid uptake, triglyceride synthesis, and de novo lipogenesis genes. Interestingly, LPla2g6^-/- mice fed with chow or MCDD displayed an attenuation of blood monocytes and elevation of anti-inflammatory lipoxin A4 in plasma and liver. Thus, PLA2G6 inactivation specifically in myeloid cells and hepatocytes led to opposing phenotypes in female mice undergoing NASH. Hepatocyte-specific PLA2G6 inhibitors may be further developed for treatment of this disease.

Identification of molecular subtypes of coronary artery disease based on ferroptosis- and necroptosis-related genes

Aim: Coronary artery disease (CAD) is a heterogeneous disorder with high morbidity, mortality, and healthcare costs, representing a major burden on public health. Here, we aimed to improve our understanding of the genetic drivers of ferroptosis and necroptosis and the clustering of gene expression in CAD in order to develop novel personalized therapies to slow disease progression.

Methods: CAD datasets were obtained from the Gene Expression Omnibus. The identification of ferroptosis- and necroptosis-related differentially expressed genes (DEGs) and the consensus clustering method including the classification algorithm used km and distance used spearman were performed to differentiate individuals with CAD into two clusters (cluster A and cluster B) based expression matrix of DEGs. Next, we identified four subgroup-specific genes of significant difference between cluster A and B and again divided individuals with CAD into gene cluster A and gene cluster B with same methods. Additionally, we compared differences in clinical information between the subtypes separately. Finally, principal component analysis algorithms were constructed to calculate the cluster-specific gene score for each sample for quantification of the two clusters.

Results: In total, 25 ferroptosis- and necroptosis-related DEGs were screened. The genes in cluster A were mostly related to the neutrophil pathway, whereas those in cluster B were mostly related to the B-cell receptor signaling pathway. Moreover, the subgroup-specific gene scores and CAD indices were higher in cluster A and gene cluster A than in cluster B and gene cluster B. We also identified and validated two genes showing upregulation between clusters A and B in a validation dataset.

Conclusion: High expression of CBS and TLR4 was related to more severe disease in patients with CAD, whereas LONP1 and HSPB1 expression was associated with delayed CAD progression. The identification of genetic subgroups of patients with CAD may improve clinician knowledge of disease pathogenesis and facilitate the development of methods for disease diagnosis, classification, and prognosis.

Lipid metabolism patterns and relevant clinical and molecular features of coronary artery disease patients: an integrated bioinformatic analysis

Background

Hyperlipidaemia is an important factor that induces coronary artery disease (CAD). This study aimed to explore the lipid metabolism patterns and relevant clinical and molecular features of coronary artery disease patients.

Methods

In the current study, datasets were fetched from the Gene Expression Omnibus (GEO) database and nonnegative matrix factorization clustering was used to establish a new CAD classification based on the gene expression profile of lipid metabolism genes. In addition, this study carried out bioinformatics analysis to explore intrinsic biological and clinical characteristics of the subgroups.

Results

Data for a total of 615 samples were extracted from the Gene Expression Omnibus database and were associated with clinical information. Then, this study used nonnegative matrix factorization clustering for RNA sequencing data of 581 lipid metabolism relevant genes, and the 296 patients with CAD were classified into three subgroups (NMF1, NMF2, and NMF3). Subjects in subgroup NMF2 tended to have an increased severity of CAD. The CAD index and age of group NMF1 were similar to those of group NMF3, but their intrinsic biological characteristics exhibited significant differences. In addition, weighted gene coexpression network analysis (WGCNA) was used to determine the most important modules and screen lipid metabolism related genes, followed by further analysis of the DEGs in which the significant genes were identified based on clinical information. The progression of coronary atherosclerosis may be influenced by genes such as PTGDS and DGKE.

Conclusion

Different CAD subgroups have their own intrinsic biological characteristics, indicating that more personalized treatment should be provided to patients in each subgroup, and some lipid metabolism related genes (PDGTS, DGKE and so on) were related significantly with clinical characteristics.

Identification of Key Genes as Early Warning Signals of Acute Myocardial Infarction Based on Weighted Gene Correlation Network Analysis and Dynamic Network Biomarker Algorithm

Purpose

The specific mechanisms and biomarkersunderlying the progression of stable coronary artery disease (CAD) to acute myocardial infarction (AMI) remain unclear. The current study aims to explore novel gene biomarkers associated with CAD progression by analyzing the transcriptomic sequencing data of peripheral blood monocytes in different stages of CAD.

Material and Methods

A total of 24 age- and sex- matched patients at different CAD stages who received coronary angiography were enrolled, which included 8 patients with normal coronary angiography, 8 patients with angiographic intermediate lesion, and 8 patients with AMI. The RNA from peripheral blood monocytes was extracted and transcriptome sequenced to analyze the gene expression and the differentially expressed genes (DEG). A Gene Oncology (GO) enrichment analysis was performed to analyze the biological function of genes. Weighted gene correlation network analysis (WGCNA) was performed to classify genes into several gene modules with similar expression profiles, and correlation analysis was carried out to explore the association of each gene module with a clinical trait. The dynamic network biomarker (DNB) algorithm was used to calculate the key genes that promote disease progression. Finally, the overlapping genes between different analytic methods were explored.

Results

WGCNA analysis identified a total of nine gene modules, of which two modules have the highest positive association with CAD stages. GO enrichment analysis indicated that the biological function of genes in these two gene modules was closely related to inflammatory response, which included T-cell activation, cell response to inflammatory stimuli, lymphocyte activation, cytokine production, and the apoptotic signaling pathway. DNB analysis identified a total of 103 genes that may play key roles in the progression of atherosclerosis plaque. The overlapping genes between DEG/WGCAN and DNB analysis identified the following 13 genes that may play key roles in the progression of atherosclerosis disease: SGPP2, DAZAP2, INSIG1, CD82, OLR1, ARL6IP1, LIMS1, CCL5, CDK7, HBP1, PLAU, SELENOS, and DNAJB6.

Conclusions

The current study identified a total of 13 genes that may play key roles in the progression of atherosclerotic plaque and provides new insights for early warning biomarkers and underlying mechanisms underlying the progression of CAD.

Identification of Potential Molecular Mechanism Related to Infertile Endometriosis

Objectives

In this research, we aim to explore the bioinformatic mechanism of infertile endometriosis in order to identify new treatment targets and molecular mechanism.

Methods

The Gene Expression Omnibus (GEO) database was used to download MRNA sequencing data from infertile endometriosis patients. The “limma” package in R software was used to find differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA) was used to classify genes into modules, further obtained the correlation coefficient between the modules and infertility endometriosis. The intersection genes of the most disease-related modular genes and DEGs are called gene set 1. To clarify the molecular mechanisms and potential therapeutic targets for infertile endometriosis, we used Gene Ontology (GO), Kyoto Gene and Genome Encyclopedia (KEGG) enrichment, Protein-Protein Interaction (PPI) networks, and Gene Set Enrichment Analysis (GSEA) on these intersecting genes. We identified lncRNAs and miRNAs linked with infertility and created competing endogenous RNAs (ceRNA) regulation networks using the Human MicroRNA Disease Database (HMDD), mirTarBase database, and LncRNA Disease database.

Results

Firstly, WGCNA enrichment analysis was used to examine the infertile endometriosis dataset GSE120103, and we discovered that the Meorangered1 module was the most significantly related with infertile endometriosis. The intersection genes were mostly enriched in the metabolism of different amino acids, the cGMP-PKG signaling pathway, and the cAMP signaling pathway according to KEGG enrichment analysis. The Meorangered1 module genes and DEGs were then subjected to bioinformatic analysis. The hub genes in the PPI network were performed KEGG enrichment analysis, and the results were consistent with the intersection gene analysis. Finally, we used the database to identify 13 miRNAs and two lncRNAs linked to infertility in order to create the ceRNA regulatory network linked to infertile endometriosis.

Conclusion

In this study, we used a bioinformatics approach for the first time to identify amino acid metabolism as a possible major cause of infertility in patients with endometriosis and to provide potential targets for the diagnosis and treatment of these patients.

Molecular Subgroup Classification in Alzheimer's Disease by Transcriptomic Profiles

Alzheimer's disease (AD) is a progressive cognitive disorder that occurs worldwide, and the lack of disease-modifying targets and pathways is a pressing issue. This study aimed to provide new targets and pathways by performing molecular subgroup classification. After normalizing the collected data, the subgroup number was confirmed with consensus clustering. Comparisons of clinical features among subgroups were conducted to clarify the clinical traits of each subgroup. Subgroup-specific genes were identified to perform weighted gene coexpression analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were carried out. Next, gene set enrichment analysis (GSEA) was performed. Protein-protein interaction networks were built to screen core genes and in each subgroup to perform Spearman correlation analysis with clinical traits. Sequencing profiles of 1068 AD samples collected from 2 datasets were classified into 3 subgroups. Clinical comparisons revealed that patients in subgroup III tended to be younger, while their pathological grades were the most severe. WGCNA detected four gene modules, and the turquoise module, where the dopaminergic synapse pathway was enriched, was related to subgroup I. The neurotrophin signaling pathway and TGF-beta signaling pathway were robustly enriched in the blue and brown modules, respectively, in subgroup III. Moreover, 3 hub genes in subgroup I were negatively correlated with the sum of neurofibrillary tangle (Nft) density. Conversely, hub genes in subgroups II and III exhibited positive correlations with the sum of Nft density. These results provide new pathways and targets for AD treatment.

Identification of Molecular Subgroups in Liver Cirrhosis by Gene Expression Profiles

Background: Liver cirrhosis is characterized by high mortality, bringing a serious health and economic burden to the world. The clinical manifestations of liver cirrhosis are complex and heterogeneous. According to subgroup characteristics, identifying cirrhosis has become a challenge. Objectives: The purpose of this study was to evaluate the difference between different subgroups of cirrhosis. The ultimate goal of research on these different phenotypes was to discover groups of patients with unique treatment characteristics, and formulate targeted treatment plans that improve the prognosis of the disease and improve the patients’ quality of life. Methods: We obtained the relevant gene chip by searching the gene expression omnibus (GEO) database. According to the gene expression profile, 79 patients with liver cirrhosis were divided into four subgroups, which showed different expression patterns. Therefore, we used weighted gene coexpression network analysis (WGCNA) to find differences between subgroups. Results: The characteristics of the WGCNA module indicated that subjects in subgroup I might exhibit inflammatory characteristics; subjects in subgroup II might exhibit metabolically active characteristics; arrhythmogenic right ventricular cardiomyopathy and neuroactive ligand-receptive somatic interaction pathways were significantly enriched in subgroup IV. We did not find a significantly upregulated pathway in the third subgroup. Conclusions: In this study, a new type of clinical phenotype classification of liver cirrhosis was derived by consensus clustering. This study found that patients in different subgroups may have unique gene expression patterns. This new classification method helps researchers explore new treatment strategies for cirrhosis based on clinical phenotypic characteristics.

Subgroup Identification with Gene Expression Profiles of Adipose Tissue in Patients with Coronary Artery Disease

Among many diseases, coronary artery disease (CAD) is the primary cause of mortality and morbidity worldwide. With the aim of revealing the underlying genetic characteristics of the CAD subtypes, we recruited patients with CAD and categorized them into subgroups according to the transcriptome expression profiles of the adipose tissue.With the removal of the batch effect, consensus clustering was employed to determine the subgroup numbers. Subgroup-specific genes were determined to conduct analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Weighted gene co-expression network analysis (WGCNA) revealed the subgroup-specific WGCNA modules. Moreover, gene set enrichment analysis (GSEA) was conducted. Overrepresentation enrichment analysis (OEA) of subgroup-specific signatures was also conducted to reveal the significant gene module associated with the corresponding clinical characteristics.After the removal of the batch effect, 77 CAD objects were divided into three subgroups. It was observed that the patients in subgroup III tended to be fat. After analyzing the dominant pathways of each subgroup, we discovered that the protein digestion and absorption pathway was specifically upregulated in subgroup I, which might result from the lowest proportion of the epicardial adipose tissue (EAT) sample. Moreover, subgroup II patients had genetic characteristics of high expression of complement and coagulation cascades and TNF signaling pathway. Furthermore, Th17 cell differentiation was significantly upregulated in subgroup III, indicating that Th17 cell differentiation is related to the clinical characteristics of body mass index (BMI).In conclusion, the genetic classification of CAD subjects indicated that subjects from different subgroups may exhibit specific gene expression patterns, suggesting that more personalized treatment should be applied to patients in each subgroup.

Identification of the Molecular Subgroups in Idiopathic Pulmonary Fibrosis by Gene Expression Profiles

Background

Idiopathic Pulmonary Fibrosis (IPF) is one of the most common idiopathic interstitial pneumonia, which can occur all over the world. The median survival time of patients is about 3-5 years, and the mortality is relatively high.

Objective

To reveal the potential molecular characteristics of IPF and deepen the understanding of the molecular mechanism of IPF. In order to provide some guidance for the clinical treatment, new drug development, and prognosis judgment of IPF. Although the preliminary conclusion of this study has certain guiding significance for the treatment of IPF and so on, it needs more accurate analytical approaches and large sample clinical trials to verify.

Methods

220 patients with IPF were divided into different subgroups according to the gene expression profiles, which were obtained from the Gene Expression Omnibus (GEO) database. In addition, these subgroups present different expression forms and clinical features. Therefore, weighted gene coexpression analysis (WGCNA) was used to seek the differences between subtypes. And six subgroup-specific WGCNA modules were identified.

Results

Combined with the characteristics of WGCNA and KEGG enrichment modules, the autophagic pathway was only upregulated in subgroup I and enriched significantly. The differentiation pathways of Th1 and Th2 cells were only upregulated and enriched in subgroup II. At the same time, combined with clinical information, IPF patients in subgroup II were older and more serious, which may be closely related to the differentiation of Th1 and Th2 cells. In contrast, the neuroactive ligand-receptor interaction pathway and Ca⁺ signaling pathway were significantly upregulated and enriched in subgroup III. Although there was no significant difference in prognosis between subgroup I and subgroup III, their intrinsic biological characteristics were very different. These results suggest that the subtypes may represent risk factors of age and intrinsic biological characteristics and may also partly reflect the severity of the disease.

Conclusion

In conclusion, current studies have improved our understanding of IPF-related molecular mechanisms. At the same time, because the results show that patients from different subgroups may have their own unique gene expression patterns, it reminds us that patients in each subgroup should receive more personalized treatment.

Construction of the gene expression subgroups of patients with coronary artery disease through bioinformatics approach

Coronary artery disease (CAD) is a heterogeneous disease that has placed a heavy burden on public health due to its considerable morbidity, mortality and high costs. Better understanding of the genetic drivers and gene expression clustering behind CAD will be helpful for the development of genetic diagnosis of CAD patients. The transcriptome of 352 CAD patients and 263 normal controls were obtained from the Gene Expression Omnibus (GEO) database. We performed a modified unsupervised machine learning algorithm to group CAD patients. The relationship between gene modules obtained through weighted gene co-expression network analysis (WGCNA) and clinical features was identified by the Pearson correlation analysis. The annotation of gene modules and subgroups was done by the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Three gene expression subgroups with the clustering score of greater than 0.75 were constructed. Subgroup I may experience coronary artery disease of an in-creased severity, while subgroup III is milder. Subgroup I was found to be closely related to the upregulation of the mitochondrial autophagy pathway, whereas the genes of subgroup II were shown to be related to the upregulation of the ribosome pathway. The high expression of APOE, NOS1 and NOS3 in the subgroup I suggested that the patients had more severe coronary artery disease. The construction of genetic subgroups of CAD patients has enabled clinicians to improve their understanding of CAD pathogenesis and provides potential tools for disease diagnosis, classification and assessment of prognosis.

Bioinformatic identification of hub genes and related transcription factors in low shear stress treated endothelial cells

Background

Recent evidences indicated that shear stress is critical in orchestrating gene expression in cardiovascular disease. It is necessary to identify the mechanism of shear stress influencing gene expression in physiology and pathophysiology conditions. This paper aimed to identify candidate hub genes and its transcription factors with bioinformatics.

Methods

We analyzed microarray expression profile of GSE16706 to identify differentially expressed genes (DEGs) in low shear stress (1 dyne/cm²) treated human umbilical vein endothelial cells (HUVECs) compared with static condition for 24 h.

Results

652 DEGs, including 333 up-regulated and 319 down-regulated DEGs, were screen out. Functional enrichment analysis indicated enrichment items mainly included cytokine-cytokine receptor interaction and cell cycle. Five hub genes (CDC20, CCNA2, KIF11, KIF2C and PLK1) and one significant module (score = 17.39) were identified through protein–protein interaction (PPI) analysis. Key transcriptional factor FOXC1 displayed close interaction with all the hub genes via gene-transcriptional factor network. Single-gene GSEA analysis indicated that CDC20 was linked to the G2M_CHECKPOINT pathway and cell cycle pathway.

Conclusions

By using integrated bioinformatic analysis, a new transcriptional factor and hub-genes network related to HUVECs treated with low shear stress were identified. The new regulation mechanism we discovered may be a promising potential therapeutic target for cardiovascular disease.

Comprehensive Analysis of the Immune Infiltrates and Aberrant Pathways Activation in Atherosclerotic Plaque

Atherosclerosis is the pathological basis of many cardiovascular and cerebrovascular diseases. The development of gene chip and high-throughput sequencing technologies revealed that the immune microenvironment of coronary artery disease (CAD) in high-risk populations played an important role in the formation and development of atherosclerotic plaques. Three gene expression datasets related to CAD were assessed using high-throughput profiling. CIBERSORT analysis revealed significant differences in five types of immune cells: activated dendritic cells (DCs), T follicular helper cells (Tfhs), resting CD4+ T cells, regulatory T cells (Tregs), and γδ T cells. Immune transcriptome analysis indicated higher levels of inflammatory markers (cytolytic activity, antigen presentation, chemokines, and cytokines) in the cases than in the controls. The level of activated DCs and the lipid clearance signaling score were negatively correlated. We observed a positive correlation between the fraction of Tfhs and lipid biosynthesis. Resting CD4+ T cells and the activity of pathways related to ossification in bone remodeling and glutathione synthesis showed a negative correlation. Gamma delta T cells negatively correlated with IL-23 signaling activity. GSEA revealed a close association with the inflammatory immune microenvironment. The present study revealed that CAD patients may have an inflammatory immune microenvironment and provides a timely update on anti-inflammatory therapies under current investigation.

Rescue of Hepatic Phospholipid Remodeling Defectin iPLA2β-Null Mice Attenuates Obese but Not Non-Obese Fatty Liver

Polymorphisms of group VIA calcium-independent phospholipase A2 (iPLA₂β or PLA2G6) are positively associated with adiposity, blood lipids, and Type-2 diabetes. The ubiquitously expressed iPLA₂β catalyzes the hydrolysis of phospholipids (PLs) to generate a fatty acid and a lysoPL. We studied the role of iPLA₂β on PL metabolism in non-alcoholic fatty liver disease (NAFLD). By using global deletion iPLA₂β-null mice, we investigated three NAFLD mouse models; genetic Ob/Ob and long-term high-fat-diet (HFD) feeding (representing obese NAFLD) as well as feeding with methionine- and choline-deficient (MCD) diet (representing non-obese NAFLD). A decrease of hepatic PLs containing monounsaturated- and polyunsaturated fatty acids and a decrease of the ratio between PLs and cholesterol esters were observed in all three NAFLD models. iPLA₂β deficiency rescued these decreases in obese, but not in non-obese, NAFLD models. iPLA₂β deficiency elicited protection against fatty liver and obesity in the order of Ob/Ob › HFD » MCD. Liver inflammation was not protected in HFD NAFLD, and that liver fibrosis was even exaggerated in non-obese MCD model. Thus, the rescue of hepatic PL remodeling defect observed in iPLA₂β-null mice was critical for the protection against NAFLD and obesity. However, iPLA₂β deletion in specific cell types such as macrophages may render liver inflammation and fibrosis, independent of steatosis protection.

Weighted correlation network bioinformatics uncovers a key molecular biosignature driving the left-sided heart failure

BACKGROUND

Left-sided heart failure (HF) is documented as a key prognostic factor in HF. However, the relative molecular mechanisms underlying left-sided HF is unknown. The purpose of this study is to unearth significant modules, pivotal genes and candidate regulatory components governing the progression of left-sided HF by bioinformatical analysis.

METHODS

A total of 319 samples in GSE57345 dataset were used for weighted gene correlation network analysis (WGCNA). ClusterProfiler package in R was used to conduct functional enrichment for genes uncovered from the modules of interest. Regulatory networks of genes were built using Cytoscape while Enrichr database was used for identification of transcription factors (TFs). The MCODE plugin was used for identifying hub genes in the modules of interest and their validation was performed based on GSE1869 dataset.

RESULTS

A total of six significant modules were identified. Notably, the blue module was confirmed as the most crucially associated with left-sided HF, ischemic heart disease (ISCH) and dilated cardiomyopathy (CMP). Functional enrichment conveyed that genes belonging to this module were mainly those driving the extracellular matrix-associated processes such as extracellular matrix structural constituent and collagen binding. A total of seven transcriptional factors, including Suppressor of Zeste 12 Protein Homolog (SUZ12) and nuclear factor erythroid 2 like 2 (NFE2L2), adrenergic receptor (AR), were identified as possible regulators of coexpression genes identified in the blue module. A total of three key genes (OGN, HTRA1 and MXRA5) were retained after validation of their prognostic value in left-sided HF. The results of functional enrichment confirmed that these key genes were primarily involved in response to transforming growth factor beta and extracellular matrix.

CONCLUSION

We uncovered a candidate gene signature correlated with HF, ISCH and CMP in the left ventricle, which may help provide better prognosis and therapeutic decisions and in HF, ISCH and CMP patients.

Weighted Gene Co-Expression Network Analysis Identified Cancer Cell Proliferation as a Common Phenomenon During Perineural Invasion

Purpose

Perineural invasion (PNI) is the neoplastic invasion of nerves by cancer cells, a process that may prove to be another metastatic route besides direct invasion, lymphatic spread, and vascular dissemination. Given the increasing incidence and association with poor prognosis, revealing the pathogenesis of perineural invasion is of great importance.

Materials and methods

Four datasets related to PNI were downloaded from the Gene Expression Omnibus database and used to construct weighted gene co-expression network analysis (WGCNA). The intersection of potential pathways obtained from further correlation and enrichment analyses of different datasets was validated by the coculture model of Schwann cells (SCs), flow cytometry and immunohistochemistry (IHC).

Results

GSE7055 and GSE86544 datasets were brought into the analysis for there were some significant modules related to PNI, while GSE103479 and GSE102238 datasets were excluded for insignificant differences. In total, 13,841 genes from GSE86544 and 10,809 genes from GSE7055 were used for WGCNA. As a consequence, 19 and 26 modules were generated, respectively. The purple module of GSE86544 and the dark gray module of GSE7055 were positively correlated with perineural invasion. Further correlation and enrichment analyses of genes from the two modules suggested that these genes were mainly enriched in cell cycle processes; especially, the terms S/G2/M phase were enriched. Three kinds of cells grew vigorously after coculture with SCs ex vivo. The Ki67 staining of the cervical cancer samples revealed that the Ki67 index of cancer cells surrounding nerves was higher than of those distant ones.

Conclusion

Our work has identified cancer cell proliferation as a common response to neural cancerous microenvironments, proving a foundation for cancer cell colonization and metastasis.