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

Wang, Guangying; Shen, Dayue; Zhang, Xilan; Ferrini, Mónica G.; Li, Yuanping; Liao, Hui

doi:10.1097/md.0000000000027508

Cited by 3 publications

(6 citation statements)

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“…Finally, GSE2457 was selected as the research object, including five normal penile tissues and five DMED penile tissues 16 . Gene expression matrix of DMED was standardized as previously described 15,17 . Differently expressed genes (DEGs) were determined by p ‐value and fold change (FC) and the thresholds were set as p < 0.05 and |log2 FC| ≥1 in this article.…”

Section: Methodsmentioning

confidence: 99%

“…16 Gene expression matrix of DMED was standardized as previously described. 15,17 Differently expressed genes (DEGs) were determined by p-value and fold change (FC) and the thresholds were set as p < 0.05 and |log2 FC| ≥1 in this article.…”

Section: Data Downloading and Processingmentioning

confidence: 99%

“…12,13 By means of bioinformatics, we found that genetic changes between different biological states could serve as potential therapeutic measures for DMED. 14,15 In this article, transcriptome data of normal and DMED rats were obtained from gene expression omnibus (GEO; https://www.ncbi.nlm.nih.gov/gds) GSE2457 dataset.…”

Section: Introductionmentioning

confidence: 99%

“…With the development of bioinformatics technology, studying the function and regulation mechanism of genes to find drug targets has become the mainstream direction of medical treatment now 12,13 . By means of bioinformatics, we found that genetic changes between different biological states could serve as potential therapeutic measures for DMED 14,15 . In this article, transcriptome data of normal and DMED rats were obtained from gene expression omnibus (GEO; https://www.ncbi.nlm.nih.gov/gds) GSE2457 dataset.…”

Section: Introductionmentioning

confidence: 99%

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Identification of hub biomarkers and exploring the roles of immunity, M6A, ferroptosis, or cuproptosis in rats with diabetic erectile dysfunction

et al. 2022

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Background: Currently, patients with diabetic erectile dysfunction (DMED) were not satisfied with the effects of first-line phosphodiesterase type 5 inhibitors (PDE5Is).Hence, this paper was designed to mine hub biomarkers in DMED and explore its potential mechanisms.Methods: Gene expression matrix of DMED was downloaded from the gene expression omnibus (GEO; GSE2457) dataset. The top 20 genes were selected based on the connectivity degrees in protein-protein interaction (PPI) network. Functional enrichment analysis was utilized to reveal DMED-related signaling pathways. We also explored the roles of immunity, m6A, ferroptosis, or cuproptosis in DMED and constructed Sprague Dawley (SD) rats DMED model to verify gene expressions by quantitative real-time polymerase chain reaction (qRT-PCR).Results: Based on the threshold, a total of 122 differently expressed genes (DEGs) were identified in DMED, including 39 up-regulated and 83 down-regulated genes.Functional enrichment analysis implied that these DEGs were significantly enriched in peroxisome proliferator-activated receptors, ferroptosis, hypoxia-inducible factor 1 signaling pathways, and so on. SD rats DMED model was also successfully established by us and validated by intracavernous pressure/mean arterial pressure, Masson's trichrome staining, and immunohistochemical analysis. We further verified the expression of these top 20 genes from the PPI network by qRT-PCR in the SD rats DMED model and finally identified Sparc, Lox, Srebf1, and Mmp3 as hub biomarkers (all p < 0.05). As for immunity and cuproptosis, our analysis indicated that DMED had nothing to do with them (all p > 0.05). Actually, DMED was markedly associated with m6A regulators and ferroptosis. Conclusions:We identified Sparc, Lox, Srebf1, and Mmp3 as potential hub biomarkers in the SD rats DMED model for future drug development and found its significant associations with m6A regulators and ferroptosis, but not with immunity or cuproptosis.

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Section: Methodsmentioning

confidence: 99%

Section: Data Downloading and Processingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Identification of hub biomarkers and exploring the roles of immunity, M6A, ferroptosis, or cuproptosis in rats with diabetic erectile dysfunction

et al. 2022

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“…The STRING software ( Szklarczyk et al, 2019 ) was adopted to construct PPI network of DEIRGs, which was visualized by Cytoscape software 3.8.1 ( Shannon et al, 2003 ). According to previously published studies, we chose the confidence value of 0.9 and the maximum number of connections of 3 to screen out relatively reliable protein interaction relationships on the basis of preserving protein correlations as much as possible ( Wang et al, 2021 ; Ramadhani et al, 2022 ; Yadalam et al, 2022 ). Cytohubba is a plug-in of Cytoscape software for identifying hub gene nodes ( Chin et al, 2014 ).…”

Section: Methodsmentioning

confidence: 99%

Integrated identification of key immune related genes and patterns of immune infiltration in calcified aortic valvular disease: A network based meta-analysis

Xiao

Sun

et al. 2022

Front. Genet.

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Background: As the most prevalent valvular heart disease, calcific aortic valve disease (CAVD) has become a primary cause of aortic valve stenosis and insufficiency. We aim to illustrate the roles of immune related genes (IRGs) and immune cells infiltration in the occurrence of CAVD.Methods: Integrative meta-analysis of expression data (INMEX) was adopted to incorporate multiple gene expression datasets of CAVD from Gene Expression Omnibus (GEO) database. By matching the differentially expressed genes (DEGs) to IRGs from “ImmPort” database, differentially expressed immune related genes (DEIRGs) were screened out. We performed enrichment analysis and found that DEIRGs in CAVD were closely related to inflammatory response and immune cells infiltration. We also constructed protein–protein interaction (PPI) network of DEIRGs and identified 5 key DEIRGs in CAVD according to the mixed character calculation results. Moreover, CIBERSORT algorithm was used to explore the profile of infiltrating immune cells in CAVD. Based on Spearman’s rank correlation method, correlation analysis between key DEIRGs and infiltrating immune cells was performed.Results: A total of 220 DEIRGs were identified and the enrichment analysis of DEIRGs showed that they were significantly enriched in inflammatory responses. PPI network was constructed and PTPN11, GRB2, SYK, PTPN6 and SHC1 were identified as key DEIRGs. Compared with normal aortic valve tissue samples, the proportion of neutrophils, T cells CD4 memory activated and macrophages M0 was elevated in calcified aortic valves tissue samples, as well as reduced infiltration of macrophages M2 and NK cells activated. Furthermore, key DEIRGs identified in the present study, including PTPN11, GRB2, PTPN6, SYK, and SHC1, were all significantly correlated with infiltration of various immune cells.Conclusion: This meta-analysis suggested that PTPN11, GRB2, PTPN6, SYK, and SHC1 might be key DEIRGs associated with immune cells infiltration, which play a pivotal role in pathogenesis of CAVD.

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Adipocyte‐specific FAK deletion promotes pancreatic β‐cell apoptosis via adipose inflammatory response to exacerbate diabetes mellitus

Ding,

Zheng,

Fang

et al. 2024

Clinical & Translational Med

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BackgroundWhite adipose tissue (WAT) has a key role in maintaining energy balance throughout the body, and their dysfunction take part in the regulation of diabetes mellitus. However, the internal regulatory mechanisms underlying are still unknown.Methods and resultsWe generated adipocyte‐specific FAK KO (FAK‐AKO) mice and investigated their phenotype. The cascade of adipocyte, macrophage in adipocyte tissues, and pancreatic β‐cells were proposed in FAK‐AKO mice and validated by cell line studies using 3T3‐L1, Raw264.7 and Min6. The FAK‐AKO mice exhibited glucose intolerance, reduced adipose tissue mass and increased apoptosis, lipolysis and inflammatory response in adipose tissue. We further demonstrate that adipocyte FAK deletion increases β cell apoptosis and inflammatory infiltrates into islets, which is potentiated if mice were treated with STZ. In the STZ‐induced diabetes model, FAK AKO mice exhibit less serum insulin content and pancreatic β cell area. Moreover, serum pro‐inflammatory factors increased and insulin levels decreased after glucose stimulation in FAK AKO mice. In a parallel vitro experiment, knockdown or inhibition of FAK during differentiation also increased apoptosis, lipolysis and inflammatory in 3T3‐L1 adipocytes, whereas the opposite was observed upon overexpression of FAK. Moreover, coculturing LPS‐treated RAW264.7 macrophages with knockdown FAK of 3T3‐L1 adipocytes increased macrophage pro‐inflammatory response. Furthermore, conditioned medium from above stimulated Min6 cells apoptosis (with or without STZ), whereas the opposite was observed upon overexpression of FAK. Mechanistically, FAK protein interact with TRAF6 in adipocytes and knockdown or inhibition of FAK activated TRAF6/TAK1/NF‐κB signaling, which exacerbates inflammation of adipocytes themselves.ConclusionAdipocyte FAK deletion promotes both adipocyte apoptosis and adipose tissue inflammation. Pro‐inflammatory factors released by the FAK‐null adipose tissue further trigger apoptosis in pancreatic islets induced by the administration of STZ, thereby exacerbating the diabetes mellitus. This study reveals a link between FAK‐mediated adipose inflammation and diabetes mellitus, a mechanism that has not been previously recognized.

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

Abstract: Supplemental Digital Content is available in the text

Cited by 3 publications

References 68 publications

Identification of hub biomarkers and exploring the roles of immunity, M6A, ferroptosis, or cuproptosis in rats with diabetic erectile dysfunction

Identification of hub biomarkers and exploring the roles of immunity, M6A, ferroptosis, or cuproptosis in rats with diabetic erectile dysfunction

Integrated identification of key immune related genes and patterns of immune infiltration in calcified aortic valvular disease: A network based meta-analysis

Adipocyte‐specific FAK deletion promotes pancreatic β‐cell apoptosis via adipose inflammatory response to exacerbate diabetes mellitus

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