Protein-protein Interaction Network Analysis Research Articles

Role of CENPL, DARS2, and PAICS in determining the prognosis of patients with lung adenocarcinoma.

Non-small cell lung cancer (NSCLC) accounts for about 85% of lung cancers, and is the leading cause of tumor-related death. Lung adenocarcinoma (LUAD) is the most prevalent subtype of NSCLC. Although significant progress of LUAD treatment has been made under multimodal strategies, the prognosis of advanced LUAD is still poor due to recurrence and metastasis. There is still a lack of reliable markers to evaluate the LUAD prognosis. This study aims to explore novel biomarkers and construct a prognostic model to predict the prognosis of LUAD patients. The Genomic Data Commons-The Cancer Genome Atlas-Lung Adenocarcinoma (GDC-TCGA-LUAD) dataset was downloaded from the University of California, Santa Cruz (UCSC) Xena browser. The GSE72094 and GSE13213 datasets and corresponding clinical information were downloaded from the Gene Expression Omnibus (GEO) database. By analyzing these datasets using DESeq2 R package and Limma R package, differentially expressed genes (DEGs) were found. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to analyze possible enrichment pathways. A protein-protein interaction (PPI) network was constructed to explore possible relationship among DEGs by using the STRING database. A survival analysis was performed to identify reliable prognostic genes using the Kaplan-Meier method. A multi-omics analysis was performed using the Gene Set Cancer Analysis (GSCA). The Tumor Immune Estimation Score (TIMER) database was used to analyze the association between prognostic genes and immune infiltration. A Spearman correlation analysis was conducted to examine the correlation between prognostic genes and drug sensitivity. A multivariate Cox regression was used to identify independent prognostic factors. Next, a nomogram was constructed using the rms R package. Finally, the expressions of aspartyl-tRNA synthetase 2 (DARS2) and phosphoribosyl aminoimidazole carboxylase (PAICS) were detected using immunohistochemistry (IHC). We screened out 30 DEGs prior to functional enrichment and PPI network analysis revealing potential enrichment pathways and interactions of these DEGs. Then survival analysis revealed the CENPL, DARS2, and PAICS expression was negatively correlated with LUAD prognosis. Additionally, multi-omics analysis showed CENPL, DARS2, and PAICS expressions were significantly higher in LUAD tissues than normal tissues. CENPL, DARS2, and PAICS were all up-regulated in late stage and M1 stage. Correlation analysis indicated CENPL, DARS2, and PAICS may not be associated with activation or suppression of immune cells. Drug sensitivity analysis revealed many potentially effective drugs and small molecule compounds. Moreover, we successfully constructed a robust and stable nomogram by combining the DARS2 and PAICS expression with other clinicopathological variables. Finally, IHC results showed DARS2 and PAICS were significantly up-regulated in LUAD. The CENPL, DARS2, and PAICS expression was negatively correlated with LUAD prognosis. A prognostic model, which integrated DARS2, PAICS, and other clinicopathological variables, was able to effectively predict LUAD patients prognosis.

HLTF/SERPINE1 Axis Plays a Crucial Pro-Oncogenic Role in the Progression from Cervical Precancerous Lesions to Cervical Carcinoma in vitro

Objectives: Cervical carcinoma (CC) is prevalent among women worldwide with increasing risk. Finding effective methods for treating CC is of utmost importance. The aim of this study was to investigate the effect of SERPINE1 on the progression of cervical precancerous lesions to CC. Design: This study used transcriptome sequencing and in vitro cell line. Participants/Materials: Cervical precancerous lesions and CC samples and human cervical epithelial immortalized cell line H8, human CC cell lines HeLa, and CaSki were involved in this study. Setting and Methods: Next-generation sequencing was applied to identify 100 differentially expressed genes from cervical precancerous lesions and CC samples. With the application of the Search Tool for the Retrieval of Interacting Genes (STRING) database, we carried out the protein-protein interaction network analysis, thus screening out serine protease inhibitor clade E member 1 (SERPINE1) with significant upregulation in CC cells. The helicase-like transcription factor (HLTF) was predicted as the upstream transcription factor using Human Transcription Factor Database (HumanTFDB). The chromatin immunoprecipitation (ChIP) experiment was conducted to validate the interaction between SERPINE1 and HLTF. The immunohistochemistry was employed to determine the expression of SERPINE1 and HLTF in CC tissues. Following the upregulation or downregulation of SERPINE1 and HLTF, the real-time quantitative reverse transcription polymerase chain reaction was carried out to assess mRNA expression levels of SERPINE1 and HLTF in cells. Cell viability, migration, and invasion were evaluated using MTT assay, cell scratch assay, and Transwell assay, respectively. Western blot analysis was conducted to assess changes in the expression levels of matrix metalloproteinases and proteins related to epithelial-mesenchymal transition (EMT). Results: The ChIP experiment confirmed the interaction between HLTF and SERPINE1. HLTF and SERPINE1 were upregulated in CC tissues and cells, and silencing SERPINE1 inhibited the EMT process and viability, migration, and invasion of CC cells. However, overexpression of SERPINE1 in CC cells showed the opposite trend. Rescue experiments demonstrated that silencing HLTF repressed CC cell viability, migration, and invasion, which could be restored by overexpressing SERPINE1. Limitations: The effect of the HLTF/SERPINE1 axis on CC malignant progression has not been confirmed by in vivo experiments. Conclusion: HLTF transcriptionally activates SERPINE1, promoting the progression from cervical precancerous lesions to CC.

Screening of differential gene expression patterns through survival analysis for diagnosis, prognosis and therapies of clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of kidney cancer. Although there is increasing evidence linking ccRCC to genetic alterations, the exact molecular mechanism behind this relationship is not yet completely known to the researchers. Though drug therapies are the best choice after the metastasis, unfortunately, the majority of the patients progressively develop resistance against the therapeutic drugs after receiving it for almost 2 years. In this case, multi-targeted different variants of therapeutic drugs are essential for effective treatment against ccRCC. To understand molecular mechanisms of ccRCC development and progression, and explore multi-targeted different variants of therapeutic drugs, it is essential to identify ccRCC-causing key genes (KGs). In order to obtain ccRCC-causing KGs, at first, we detected 133 common differentially expressed genes (cDEGs) between ccRCC and control samples based on nine (9) microarray gene-expression datasets with NCBI accession IDs GSE16441, GSE53757, GSE66270, GSE66272, GSE16449, GSE76351, GSE66271, GSE71963, and GSE36895. Then, we filtered these cDEGs through survival analysis with the independent TCGA and GTEx database and obtained 54 scDEGs having significant prognostic power. Next, we used protein-protein interaction (PPI) network analysis with the reduced set of 54 scDEGs to identify ccRCC-causing top-ranked eight KGs (PLG, ENO2, ALDOB, UMOD, ALDH6A1, SLC12A3, SLC12A1, SERPINA5). The pan-cancer analysis with KGs based on TCGA database showed the significant association with different subtypes of kidney cancers including ccRCC. The gene regulatory network (GRN) analysis revealed some crucial transcriptional and post-transcriptional regulators of KGs. The scDEGs-set enrichment analysis significantly identified some crucial ccRCC-causing molecular functions, biological processes, cellular components, and pathways that are linked to the KGs. The results of DNA methylation study indicated the hypomethylation and hyper-methylation of KGs, which may lead the development of ccRCC. The immune infiltrating cell types (CD8+ T and CD4+ T cell, B cell, neutrophil, dendritic cell and macrophage) analysis with KGs indicated their significant association in ccRCC, where KGs are positively correlated with CD4+ T cells, but negatively correlated with the majority of other immune cells, which is supported by the literature review also. Then we detected 10 repurposable drug molecules (Irinotecan, Imatinib, Telaglenastat, Olaparib, RG-4733, Sorafenib, Sitravatinib, Cabozantinib, Abemaciclib, and Dovitinib.) by molecular docking with KGs-mediated receptor proteins. Their ADME/T analysis and cross-validation with the independent receptors, also supported their potent against ccRCC. Therefore, these outputs might be useful inputs/resources to the wet-lab researchers and clinicians for considering an effective treatment strategy against ccRCC.

Bacopa monnieri confers neuroprotection by influencing signaling pathways associated with interleukin 4, 13 and extracellular matrix organization in Alzheimer's disease: A proteomics-based perspective

Alzheimer's disease, a prevalent neurodegenerative disorder in the elderly, is characterized by the accumulation of senile plaques and neurofibrillary tangles, triggering oxidative stress, neuroinflammation, and neuronal apoptosis. Current therapies focus on symptomatic treatment rather than targeting the underlying disease-modifying molecular mechanisms and are often associated with significant side effects. Bacopa monnieri, a traditional Indian herb with nootropic properties, has shown promise in neurological disorder treatment from ancient times. However, its mechanisms of action in Alzheimer's disease remain elusive. In this study, a cellular model for Alzheimer's disease was created by treating differentiated IMR-32 cells with beta-amyloid, 1–42 peptide (Aβ42). Additionally, a recovery model was established through co-treatment with Bacopa monnieri to explore its protective mechanism. Co-treatment with Bacopa monnieri extract recovered Aβ42 induced damage as evidenced by the decreased apoptosis and reduced reactive oxygen species production. Mass spectrometry-based quantitative proteomic analysis identified 21,674 peptides, corresponding to 3626 proteins from the Alzheimer's disease model. The proteins dysregulated by Aβ42 were implicated in cellular functions, such as negative regulation of cell proliferation and microtubule cytoskeleton organization. The enriched pathways include extracellular matrix organization and interleukin-4 and interleukin-13 signaling. Bacopa monnieri co-treatment showed remarkable restoration of Aβ42 altered proteins, including FOSL1, and TDO2. The protein-protein interaction network analysis of Bacopa monnieri restored proteins identified the hub gene involved in Alzheimer's disease. The findings from this study may open up new avenues for creating innovative therapeutic approaches for Alzheimer's disease.

Bioinformatics Identification and Validation of Angiogenesis-Related Genes in Myocardial Ischemic Reperfusion Injury.

Angiogenesis plays a critical protective role in myocardial ischemia-reperfusion injury (MIRI); however, therapeutic targeting of associated genes remains constrained. To bridge this gap, we conducted bioinformatics analysis to identify pivotal angiogenesis-related genes in MIRI, potentially applicable for preventive and therapeutic interventions. We collected two mouse heart I/R expression datasets (GSE61592 and GSE83472) from Gene Expression Omnibus, utilizing the Limma package to identify differentially expressed genes (DEGs). Angiogenesis-related genes (ARGs) were extracted from GeneCards, and their overlap with DEGs produced differentially expressed ARGs (ARDEGs). Further analyses included Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and disease ontology to explore biological functions. Weighted gene correlation network analysis (WGCNA) was used to investigate molecular modules linked to MIRI. Additionally, a protein-protein interaction (PPI) network was constructed to pinpoint hub genes relevant to MIRI. Receiver operating characteristic curves were used to assess the diagnostic efficacy of these hub genes for MIRI. An ischemia-reperfusion injury model was established using human cardiac microvascular endothelial cells (HCMECs), with the expression of hub genes validated within this experimental framework. We identified 47 ARDEGs, 41 upregulated and 6 downregulated. PPI network analysis revealed suppressor of cytokine signaling 3 (Socs3), C-X-C motif chemokine ligand 1 (Cxcl1), interleukin 1 beta (Il1b), and matrix metallopeptidase 9 (Mmp9) as hub genes. Receiver operating characteristic (ROC) curve analysis demonstrated strong diagnostic potential for Socs3, Cxcl1, Il1b, and Mmp9. In vitro validation corroborated the mRNA and protein expression predictions. Our study highlights the pivotal role of Socs3, Cxcl1, Il1b, and Mmp9 in MIRI development, their significance in immune cell infiltration, and their diagnostic accuracy. These findings offer valuable insights for MIRI diagnosis and treatment, presenting potential molecular targets for future research.

Secreted protein TNA: a promising biomarker for understanding the adipose-bone axis and its impact on bone metabolism

BackgroundOsteoporosis (OP) is a systemic bone disease characterized by reduced bone mass and deterioration of bone microstructure, leading to increased bone fragility. Platelets can take up and release cytokines, and a high platelet count has been associated with low bone density. Obesity is strongly associated with OP, and adipose tissue can influence platelet function by secreting adipokines. However, the biological relationship between these factors remains unclear.MethodsWe conducted differential analysis to identify OP platelet-related plasma proteins. And, making comprehensive analysis, including functional enrichment, protein-protein interaction network analysis, and Friends analysis. The key protein, Tetranectin (TNA/CLEC3B), was identified through screening. Then, we analyzed TNA’s potential roles in osteogenic and adipogenic differentiation using multiple RNA-seq data sets and validated its effect on osteoclast differentiation and bone resorption function through in vitro experiments.ResultsSix OP-platelet-related proteins were identified via differential analysis. Then, we screened the key protein TNA, which was found to be highly expressed in adipose tissue. RNA-seq data suggested that TNA may promote early osteoblast differentiation. In vitro experiments showed that knockdown of TNA expression significantly increased the expression of osteoclast markers, thereby promoting osteoclast differentiation and bone resorption.ConclusionsWe identified TNA as a secreted protein that inhibits osteoclast differentiation and bone resorption. While, it potentially promoted early osteoblast differentiation from bioinformatic results. TNA may play a role in bone metabolism through the adipose-bone axis.

Integrating network pharmacology, molecular docking and experimental verification to explore the therapeutic effect and potential mechanism of nomilin against triple-negative breast cancer

BackgroundNomilin is a limonoid compound known for its multiple biological activities, but its role in triple negative breast cancer (TNBC) remains unclear. This study aims to uncover the potential therapeutic effect of nomilin on TNBC and elucidate the specific mechanism of its action.MethodsWe employed weighted gene co-expression network analysis (WGCNA), differential expression analysis, and the GeneCards database to identify potential targets for TNBC. Simultaneously, we utilized the Swiss Target Prediction, ChEMBL, and STITCH databases to identify potential targets of nomilin. The core targets and mechanisms of nomilin against TNBC were predicted through protein-protein interaction (PPI) network analysis, molecular docking, and enrichment analysis. The results of the network pharmacology were corroborated by conducting experiments.ResultsA total of 17,204 TNBC targets were screened, and 301 potential targets of nomilin were identified. Through the PPI network, eight core targets of nomilin against TNBC were pinpointed, namely BCL2, Caspase3, CyclinD1, EGFR, HSP90AA1, KRAS, PARP1, and TNF. Molecular docking, molecular dynamics simulation and proteome microarray revealed that nomilin exhibits strong binding activity to these core proteins. Enrichment analysis results indicated that the anti-TNBC effect of nomilin is associated with PI3K/Akt pathway. In vitro and in vivo experiments have demonstrated that nomilin inhibits TNBC cell proliferation and migration while promoting cell apoptosis through the PI3K/Akt pathway.ConclusionFor the first time, the research effectively discovered the objectives and mechanisms of nomilin in combating TNBC using network pharmacology, molecular docking, molecular dynamics simulation, proteome microarray and experimental confirmation, presenting a hopeful approach for treating TNBC.Graphical

Determination of key hub genes in Leishmaniasis as potential factors in diagnosis and treatment based on a bioinformatics study.

Leishmaniasis is an infectious disease caused by protozoan parasites from different species of leishmania. The disease is transmitted by female sandflies that carry these parasites. In this study, datasets on leishmaniasis published in the GEO database were analyzed and summarized. The analysis in all three datasets (GSE43880, GSE55664, and GSE63931) used in this study has been performed on the skin wounds of patients infected with a clinical form of leishmania (Leishmania braziliensis), and biopsies have been taken from them. To identify differentially expressed genes (DEGs) between leishmaniasis patients and controls, the robust rank aggregation (RRA) procedure was applied. We performed gene functional annotation and protein-protein interaction (PPI) network analysis to demonstrate the putative functionalities of the DEGs. The study utilized Molecular Complex Detection (MCODE), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) to detect molecular complexes within the protein-protein interaction (PPI) network and conduct analyses on the identified functional modules. The CytoHubba plugin's results were paired with RRA analysis to determine the hub genes. Finally, the interaction between miRNAs and hub genes was predicted. Based on the RRA integrated analysis, 407 DEGs were identified (263 up-regulated genes and 144 down-regulated genes). The top three modules were listed after creating the PPI network via the MCODE plug. Seven hub genes were found using the CytoHubba app and RRA: CXCL10, GBP1, GNLY, GZMA, GZMB, NKG7, and UBD. According to our enrichment analysis, these functional modules were primarily associated with immune pathways, cytokine activity/signaling pathways, and inflammation pathways. However, a UBD hub gene is interestingly involved in the ubiquitination pathways of pathogenesis. The mirNet database predicted the hub gene's interaction with miRNAs, and results revealed that several miRNAs, including mir-146a-5p, crucial in fighting pathogenesis. The key hub genes discovered in this work may be considered as potential biomarkers in diagnosis, development of agonists/antagonist, novel vaccine design, and will greatly contribute to clinical studies in the future.

High expression of ARHGEF5 predicts unfavorable prognosis in acute myeloid leukemia

Acute myeloid leukemia (AML) is a highly heterogeneous hematological neoplasm, highlighting the need for new molecular markers to improve prognosis prediction and therapeutic strategies. While Rho guanine nucleotide exchange factor 5 (ARHGEF5) is known to be overexpressed in various cancers, its role in AML is not well understood. This study investigates the correlation between ARHGEF5 expression and AML using data from the Cancer Genome Atlas (TCGA). ARHGEF5 expression levels in AML patients and normal samples were compared using the Wilcoxon rank-sum test. The Kaplan–Meier method and Cox regression analysis (CRA) assessed the association between ARHGEF5 expression and patient survival. A prognostic nomogram was constructed using CRA, incorporating patient age and cytogenetic risk.Our findings indicate significant overexpression of ARHGEF5 in AML compared to normal samples. Elevated ARHGEF5 levels were associated with poor prognosis, particularly in patients ≤ 60 years, those with NPM1 mutations, FLT3 mutation-positive, and wild-type RAS (P < 0.05). CRA confirmed that high ARHGEF5 expression independently predicts poor prognosis. Additionally, 412 differentially expressed genes (DEGs) were identified between high and low ARHGEF5 expression groups, with 216 genes upregulated and 196 downregulated. Pathway enrichment analyses using GO and KEGG, along with protein–protein interaction network and single sample gene set enrichment analyses, revealed key pathways and immune cell associations linked to ARHGEF5. These findings suggest that ARHGEF5 overexpression could serve as a biomarker for unfavorable outcomes in AML, providing insights into the underlying mechanisms of AML onset and progression.

Whole-transcriptome analyses of ovine lung microvascular endothelial cells infected with bluetongue virus

Bluetongue virus (BTV) infection induces profound and intricate changes in the transcriptional profile of the host to facilitate its survival and replication. However, there have been no whole-transcriptome studies on ovine lung microvascular endothelial cells (OLMECs) infected with BTV. In this study, we comprehensively analysed the whole-transcriptome sequences of BTV-1 serotype-infected and mock-infected OLMECs and subsequently performed bioinformatics differential analysis. Our analysis revealed 1215 differentially expressed mRNA transcripts, 82 differentially expressed long noncoding RNAs (lncRNAs) transcripts, 63 differentially expressed microRNAs (miRNAs) transcripts, and 42 differentially expressed circular RNAs (circRNAs) transcripts. Annotation from Gene Ontology, enrichment from the Kyoto Encyclopedia of Genes and Genomes, and construction of endogenous competing RNA network analysis revealed that the differentially expressed RNAs primarily participated in viral sensing and signal transduction pathways, antiviral and immune responses, inflammation, and extracellular matrix (ECM)-related pathways. Furthermore, protein‒protein interaction network analysis revealed that BTV may regulate the conformation of ECM receptor proteins and change their biological activity through a series of complex mechanisms. Finally, on the basis of real-time fluorescence quantitative polymerase chain reaction results, the expression trends of the differentially expressed RNA were consistent with the whole-transcriptome sequencing data, such as downregulation of the expression of COL4A1, ITGA8, ITGB5, and TNC and upregulation of the expression of CXCL10, RNASEL, IRF3, IRF7, and IFIHI. This study provides a novel perspective for further investigations of the mechanism of the ECM in the BTV-host interactome and the pathogenesis of lung microvascular endothelial cells.

Molecular profiling of a rat model of vascular dementia: Evidences from proteomics, metabolomics and experimental validations

Decrease of cerebral blood flow is the primary cause of vascular dementia (VD), but its pathophysiological mechanisms are still not known. This study aims to profile the molecular changes of a rat model of VD induced by bilateral common carotid artery ligation. The Morris water maze and new object recognition tasks were used to test the cognitive function of rats. Hematoxylin and Eosin (HE) staining was used to detect pathological changes in the hippocampus. After confirming the model, proteomics was used to detect differentially expressed proteins in the hippocampus, and metabolomics was used to detect differential metabolites in rat serum. Thereafter, bioinformatics were used to integrate and analyze the potential molecular profile. The results showed that compared with the sham control group, the spatial and recognition memory of the rats were significantly reduced, and pathological changes were observed in the hippocampal CA1 region of the model group. Proteomic analysis suggested 206 differentially expressed proteins in the hippocampus of VD rats, with 117 proteins upregulated and 89 downregulated. Protein-protein interaction network analysis suggested that those differentially expressed proteins might play crucial roles in lipid metabolism, cell adhesion, intracellular transport, and signal transduction. Metabolomics analysis identified 103 differential metabolites, and comparison with the human metabolome database revealed 22 common metabolites, which predicted 265 potential targets. Afterwards, by intersecting the predicted results from metabolomics with the differentially expressed proteins from proteomics, we identified five potential targets, namely ACE, GABBR1, Rock1, Abcc1 and Mapk10. Furthermore, western blotting confirmed that compared with control group, hippocampal GABBR1 and Rock1 were enhanced in the model group. Together, this study showed the molecular profile of VD rats through a combination of proteomics, metabolomics, and experimental confirmation methods, offering crucial molecular targets for the diagnosis and treatment of VD.

Potential mechanisms of ZiGongDing in treating HPV-induced cervical intraepithelial neoplasia: a network pharmacology and experimental verification study.

The onset of cervical intraepithelial neoplasia (CIN) is strongly associated with persistent infection caused by high-risk human papillomavirus (HPV). ZiGongDing (ZGD), a traditional Chinese medicine, has progressed to clinical application in HPV-induced CIN treatment, yet the underlying mechanism remains unclear. The objective of this paper is to explore the mechanism of ZGD in treating HPV-induced CIN by integrating a combination of network pharmacology and experimental validation. The active ingredients and targets of ZGD were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database. CIN-related targets were sourced from GeneCards and the Online Mendelian Inheritance in Man (OMIM) database. Protein-protein interaction (PPI) and functional enrichment analyses were conducted to determine the potential molecular mechanism. The herb-active ingredient-target network was constructed by Cytoscape software. To further validate the therapeutic mechanism, molecular docking and in vitro experiments were performed. In this study, we identified 60 active ingredients in ZGD and 46 common targets in of CIN treatment. The PPI network analysis revealed estrogen receptor 1 (ESR1) as a pivotal target in ZGD against CIN. Functional enrichment analysis showed that the estrogen signaling pathway was mostly enriched, and ESR1 was involved. The herb-active ingredient-target network and relative literature identified cnidimol B as the primary active ingredient. Molecular docking demonstrated a strong binding affinity between ESR1 and cnidimol B. Cellular experiments revealed that cnidimol B could significantly decrease the viability of HeLa and CaSki cells. Moreover, the expression of ESR1 was notably upregulated in HeLa and CaSki cells after treatment with cnidimol B. Our study proposes a novel mechanism underlying ZGD against CIN, which involves the modulation of ESR1. This insight lays a solid foundation for further exploring and optimizing ZGD's therapeutic potential.

Integrating network pharmacology, molecular docking and non-targeted serum metabolomics to illustrate pharmacodynamic ingredients and pharmacologic mechanism of Haizao Yuhu Decoction in treating hyperthyroidism.

To explore the pharmacodynamic ingredients and pharmacologic mechanism of Haizao Yuhu Decoction (HYD) in treating hyperthyroidism via an analysis integrating network pharmacology, molecular docking, and non-targeted serum metabolomics. Therapeutic targets of hyperthyroidism were searched through multi-array analyses in the Gene Expression Omnibus (GEO) database. Hub genes were subjected to the construction of a protein-protein interaction (PPI) network, and GO and KEGG enrichment analyses. Targets of active pharmaceutical ingredients (APIs) in HYD and those of hyperthyroidism were intersected to yield hub genes, followed by validations via molecular docking and non-targeted serum metabolomics. 112 hub genes were identified by intersecting APIs of HYD and therapeutic targets of hyperthyroidism. Using ultra-high performance liquid chromatography with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) in both negative and positive ion polarity modes, 279 compounds of HYD absorbed in the plasma were fingerprinted. Through summarizing data yielded from network pharmacology and non-targeted serum metabolomics, 214 common targets were identified from compounds of HYD absorbed in the plasma and therapeutic targets of hyperthyroidism, including PTPN11, PIK3CD, EGFR, HRAS, PIK3CA, AKT1, SRC, PIK3CB, and PIK3R1. They were mainly enriched in the biological processes of positive regulation of gene expression, positive regulation of MAPK cascade, signal transduction, protein phosphorylation, negative regulation of apoptotic process, positive regulation of protein kinase B signaling and positive regulation of MAP kinase activity; and molecular functions of identical protein binding, protein serine/threonine/tyrosine kinase activity, protein kinase activity, RNA polymerase II transcription factor activity, ligand-activated sequence-specific DNA binding and protein binding. A total of 185 signaling pathways enriched in the 214 common targets were associated with cell proliferation and angiogenesis. HYD exerts a pharmacological effect on hyperthyroidism via inhibiting pathological angiogenesis in the thyroid and rebalancing immunity.

The inhibitory effect of type V transforming growth factor-β receptor antagonist on the proliferation of keloid fibroblasts by suppressing insulin-like growth factor-binding protein 3-interleukin-6 signaling

Abstract Background: Hyperplasia of fibroblasts is critical in keloid pathogenesis. Insulin-like growth factor-binding protein 3 (IGFBP3) is an important factor in the regulation of cell growth and type V transforming growth factor-β receptor (TβR-V) is a specific receptor of IGFBP3. However, the role of IGFBP3 in keloid development has not been reported. Objectives: This study aimed to investigate the role of IGFBP3 in keloid pathogenesis and evaluate the effects of TβR-V antagonist on keloid fibroblasts (KFs) activities. Methods: IGFBP3 expression in keloids and its impact on KF proliferation were examined. The effects of TβR-V antagonist on KF cell proliferation, migration, and invasion were also investigated. Differentially expressed genes (DEGs) between TβR-V antagonist treated and nontreated KFs were identified through RNA-sequencing (RNA-seq), followed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein–protein interaction (PPI) network analyses. Results: IGFBP3 was overexpressed in keloids and could promote KF proliferation. TβR-V antagonist suppressed KFs proliferation, migration, and invasion. GO and KEGG analyses showed that the downregulated DEGs revealed by RNA-seq were significantly enriched in terms related to cell proliferation. Interleukin-6 (IL-6) was identified as the only gene interacting with IGFBP3 in the PPI network and was associated with nine hub genes. In vitro assay confirmed the suppression of IL-6 by TβR-V antagonist in KFs. Conclusion: Our study demonstrated that TβR-V antagonist could inhibit keloid growth likely through suppressing IGFBP3-IL-6 signaling activation. These findings suggest that targeting TβR-V could be a potential therapeutic strategy for keloid treatment.

Genome-wide analysis of the potato GRF gene family and their expression profiles in response to hormone and Ralstonia solanacearum infection.

Potato (Solanum tuberosum L.) is one of the most economically significant crops globally. Nevertheless, potato cultivation is becoming increasingly susceptible to a multitude of diseases, including bacterial wilt, which is caused by Ralstonia solanacearum. To identify the GRF gene family in potatoes and to examine their expression profiles in response to hormones and R. solanacearum infection. A comprehensive genome-wide analysis was conducted to identify the GRF gene family in the potato genome. A total of 13 GRF genes were identified from the latest potato genome, including five StGRFs belonging to the ɛ group and eight of the non-ɛ group. The transcriptional responses of the StGRFs to two biotic stress-related phytohormones (SA and MeJA) were defined, as well as the response to infection with R. solanacearum in a bacterial wilt-sensitive cultivar, S. tuberosum 'Qingshu 9'. Many StGRF genes exhibited high induction levels in response to R. solanacearum infection and SA treatment while displaying a marked decline in expression in the presence of MeJA. Furthermore, protein interaction network analysis revealed that the StGRF proteins interact with several candidate target proteins, indicating that GRF proteins are ubiquitous regulators in potatoes. However, the associations between two type III effectors (T3Es) RipAC/RipH2 from R. solanacearum isolates and StGRF7 were not detectable in a yeast two-hybrid assay. This study provides comprehensive information on the GRF gene family and lays a foundation for further research on the molecular mechanism of potato biotic stress adaptation.

Exercise and tumor proteome: insights from a neuroblastoma model.

The impact of exercise on pediatric tumor biology is essentially unknown. We explored the effects of regular exercise on tumor proteome profile (as assessed with liquid chromatography with tandem mass spectrometry) in a mouse model of one of the most aggressive childhood malignancies, high-risk neuroblastoma (HR-NB). Tumor samples of 14 male mice (aged 6-8 wk) that were randomly allocated into an exercise (5-wk combined aerobic and resistance training) or nonexercise control group (6 and 8 mice/group, respectively) were analyzed. The Search Tool for the Retrieval of Interacting Genes/Proteins database was used to generate a protein-protein interaction (PPI) network and enrichment analyses. The Systems Biology Triangle (SBT) algorithm was applied for analyses at the functional category level. Tumors of exercised mice showed a higher and lower abundance of 101 and 150 proteins, respectively, than controls [false discovery rate (FDR) < 0.05]. These proteins were enriched in metabolic pathways, amino acid metabolism, regulation of hormone levels, and peroxisome proliferator-activated receptor signaling (FDR < 0.05). The SBT algorithm indicated that 184 and 126 categories showed a lower and higher abundance, respectively, in the tumors of exercised mice (FDR < 0.01). Categories with lower abundance were involved in energy production, whereas those with higher abundance were related to transcription/translation, apoptosis, and tumor suppression. Regular exercise altered the abundance of hundreds of intratumoral proteins and molecular pathways, particularly those involved in energy metabolism, apoptosis, and tumor suppression. These findings provide preliminary evidence of the molecular mechanisms underlying the potential effects of exercise in HR-NB.NEW & NOTEWORTHY We used liquid chromatography with tandem mass spectrometry to explore the impact of a 5-wk exercise intervention on the tumor proteome profile in a mouse model of one of the most aggressive childhood malignancies, high-risk neuroblastoma. Exercise altered the abundance of hundreds of proteins and pathways, particularly those involved in energy metabolism and tumor suppression. These molecular changes could mediate, at least partly, the potential antitumorigenic effects of exercise.

Unveiling the role of IGF1R in autism spectrum disorder: a multi-omics approach to decipher common pathogenic mechanisms in the IGF signaling pathway.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition marked by impairments in social interaction, communication, and repetitive behaviors. Emerging evidence suggests that the insulin-like growth factor (IGF) signaling pathway plays a critical role in ASD pathogenesis; however, the precise pathogenic mechanisms remain elusive. This study utilizes multi-omics approaches to investigate the pathogenic mechanisms of ASD susceptibility genes within the IGF pathway. Whole-exome sequencing (WES) revealed a significant enrichment of rare variants in key IGF signaling components, particularly the IGF receptor 1 (IGF1R), in a cohort of Chinese Han individuals diagnosed with ASD, as well as in ASD patients from the SFARI SPARK WES database. Subsequent single-cell RNA sequencing (scRNA-seq) of cortical tissues from children with ASD demonstrated elevated expression of IGF receptors in parvalbumin (PV) interneurons, suggesting a substantial impact on their development. Notably, IGF1R appears to mediate the effects of IGF2R on these neurons. Additionally, transcriptomic analysis of brain organoids derived from ASD patients indicated a significant association between IGF1R and ASD. Protein-protein interaction (PPI) and gene regulatory network (GRN) analyses further identified ASD susceptibility genes that interact with and regulate IGF1R expression. In conclusion, IGF1R emerges as a central node within the IGF signaling pathway, representing a potential common pathogenic mechanism and therapeutic target for ASD. These findings highlight the need for further investigation into the modulation of this pathway as a strategy for ASD intervention.

Rps3 Attenuates Gastric Precancerous Lesions by Promoting Dendritic Cells Maturation via AKT/β-Catenin Pathway.

This study aimed to investigate the dysregulated proteins and the underlying mechanisms of gastric precancerous lesions. Proteomic and phosphoproteomic methods were used to characterize the proteome and phosphoproteome profiles of N-methyl-N-nitro-N-nitrosoguanidine (MNNG)-induced gastric precancerous lesions. The hub differentially expressed proteins (DEPs) and phosphoproteins (DEPPs) were identified by using differential expression and protein-protein interaction network analyses. Western blot assay, quantitative reverse transcription (qRT)-PCR, and CCK-8 assays detected the expression of Rps3, N-cadherin, E-cadherin, AKT, p-AKT, and β-catenin and verified the roles of Rps3 on the MNNG-induced human gastric epithelial cell line (GES-1) cells. Hub DEPs and phosphoproteins Rps3, Akt1, and Ctnnb1 were significantly correlated with five dendritic cells (DCs) pathways, and Akt1 and Ctnnb1 were significantly negatively correlated with Rps3. MNNG administration markedly reduced the Rps3 mRNA and protein expression levels (all P < 0.05). Overexpression of Rps3 significantly inhibited tumorigenesis of MNNG-induced GES-1 cells (all P < 0.01) and changed the protein levels of N-cadherin, E-cadherin, AKT, p-AKT, and β-catenin. Similarly, SC79 treatment substantially increased the expression of interleukin (IL)-6, IL-10, and vascular endothelial growth factor (all P < 0.05). Rps3 was poorly expressed in precancerous gastric lesions. Correspondingly, overexpression of Rps3 promoted DC maturation via the AKT/β-catenin pathway, inhibiting the progression of gastric precancerous lesions.

Decoding the duration of fertility of laying chicken through phenotypic and proteomic evaluation

ABSTRACT 1. This study determined the effective indicators and proteins involved in long-duration fertility (DF) in chickens. 2. Three lines of Chinese Xinhua chickens (900) were compared using seven phenotypic trait indicators, and the best was determined based on repeatability value. Subsequently, differential expression analysis, functional annotation and protein-protein interaction (PPI) network analyses were performed to investigate the pathways and hub proteins. Finally, qPCR analysis was conducted to validate the expression of identified hub proteins, and functional annotation with previously published genes was performed to explain how hub proteins work to maintain the trait. 3. The study found that the number of fertilised eggs (FN) and maximum fertilised eggs (MCF) were the most repeatable among the seven indicators. It identified 231 differentially expressed proteins, with 144 being down-regulated and 87 being up-regulated. The differentially expressed proteins exhibited high clustering within various cellular compartments, including the cytosol and cytoplasm and GTP binding. Multiple pathways were identified, including tight and adherens junctions, TGF-beta signalling, autophagy-animal, regulation of actin cytoskeleton and the ribosome that may regulate the trait. Three hub proteins, KRAS, RPL5 (p < 0.001), and HSPA4 (p < 0.01), were significantly differentially expressed between high and low DF groups. 4. This study identified FN and MCF as effective indicators for addressing DF. As it is a quantitative trait, KRAS, HSPA4, and RPL5 are potential hub proteins that work with other genes to maintain the trait.

Proteomic analysis illustrates the potential involvement of motor proteins in cleft palate development

Cleft palate (CP) is a congenital condition characterized by a complex etiology and limited diagnostic and therapeutic options. In this study, we delved into the molecular mechanisms associated with retinoic acid (RA)-induced CP in Kun Ming mice. Proteomic analysis of control and RA-induced CP samples at embryonic day 15.5 revealed 25 upregulated and 19 downregulated proteins. Further analysis identified these differentially expressed proteins (DEPs) as being involved in extracellular matrix organization, actin cytoskeleton, and myosin complex. Moreover, these DEPs were found to be enriched in pathways related to motor protein activity and extracellular matrix-receptor interaction. Protein-protein interaction network analysis identified 10 hub proteins, including motor proteins and ECM-related proteins, which exhibited higher expression levels in CP compared to control tissues. These findings provide insights into the molecular mechanisms underlying CP and highlight potential targets for diagnostic and therapeutic purposes.