Proteomic Analysis of the Secretome and Exosomes of Feline Adipose-Derived Mesenchymal Stem Cells

Mesenchymal stem cells (MSCs) have been shown to have therapeutic efficacy in different complex pathologies in feline species. This effect is attributed to the secretion of a wide variety of bioactive molecules and extracellular vesicles, such as exosomes, with significant paracrine activity, encompassed under the concept of the secretome. However, at present, the exosomes from feline MSCs have not yet been studied in detail. The objective of this study is to analyze and compare the protein profiles of the secretome as a whole and its exosomal fraction from feline adipose-derived MSCs (fAd-MSCs). For this, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Protein–Protein Interaction Networks Functional Enrichment Analysis (STRING) were utilized. A total of 239 proteins were identified in the secretome, and 228 proteins specific to exosomes were identified, with a total of 133 common proteins. The proteins identified in the secretome were located in the extracellular regions and in the cytoplasm, while the exosomal proteins were located mainly in the membrane, cytoplasm and cytosol. Regarding function, in the secretome, proteins involved in different metabolic pathways, in pathways related to the immune system and the endocrine system and in the processing of proteins in the endoplasmic reticulum predominated. In contrast, proteins specific to exosomes were predominantly associated with endocytosis, cell junctions, platelet activation and other cell signaling pathways. The possible future use of the secretome, or some of its components, such as exosomes, would provide a non-cell-based therapeutic strategy for the treatment of different diseases that would avoid the drawbacks of cell therapy.

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Investigation and Functional Enrichment Analysis of the Human Host Interaction Network with Common Gram-Negative Respiratory Pathogens Predicts Possible Association with Lung Adenocarcinoma

Pathophysiology ◽

10.3390/pathophysiology28010003 ◽

2021 ◽

Vol 28 (1) ◽

pp. 20-33

Author(s):

Lydia-Eirini Giannakou ◽

Athanasios-Stefanos Giannopoulos ◽

Chrissi Hatzoglou ◽

Konstantinos I. Gourgoulianis ◽

Erasmia Rouka ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Cell Junctions ◽

Respiratory Pathogens ◽

Gram Negative ◽

Human Proteins ◽

Apoptotic Pathways

Haemophilus influenzae (Hi), Moraxella catarrhalis (MorCa) and Pseudomonas aeruginosa (Psa) are three of the most common gram-negative bacteria responsible for human respiratory diseases. In this study, we aimed to identify, using the functional enrichment analysis (FEA), the human gene interaction network with the aforementioned bacteria in order to elucidate the full spectrum of induced pathogenicity. The Human Pathogen Interaction Database (HPIDB 3.0) was used to identify the human proteins that interact with the three pathogens. FEA was performed via the ToppFun tool of the ToppGene Suite and the GeneCodis database so as to identify enriched gene ontologies (GO) of biological processes (BP), cellular components (CC) and diseases. In total, 11 human proteins were found to interact with the bacterial pathogens. FEA of BP GOs revealed associations with mitochondrial membrane permeability relative to apoptotic pathways. FEA of CC GOs revealed associations with focal adhesion, cell junctions and exosomes. The most significantly enriched annotations in diseases and pathways were lung adenocarcinoma and cell cycle, respectively. Our results suggest that the Hi, MorCa and Psa pathogens could be related to the pathogenesis and/or progression of lung adenocarcinoma via the targeting of the epithelial cellular junctions and the subsequent deregulation of the cell adhesion and apoptotic pathways. These hypotheses should be experimentally validated.

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Co-expression network analysis identifies specific hub genes in association with developmental neuronal remodeling in Drosophila melanogaster

10.7287/peerj.preprints.27586v1 ◽

2019 ◽

Author(s):

Yunze Liu ◽

Xiaojie Sun ◽

Aijun Qu

Keyword(s):

Drosophila Melanogaster ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Pathway Enrichment Analysis ◽

Hub Genes ◽

Protein Protein Interaction ◽

Neuronal Remodeling ◽

Gene Modules

As an evolutionarily conserved mechanism, developmental neuronal remodeling is needed for the proper wiring of the nervous system and is critical for understanding the neurodevelopment mechanisms. Previous studies have shown that during metamorphosis lots of Drosophila melanogaster mushroom body neurons experience stereotypic remodeling. However, the related regulators and downstream executors of pathways are yet unclear, especially studies of transcriptional gene co-expression analysis of nervous systems remain insufficient. In this study, we develop a weighted gene co-expression network (WGCNA) to classify gene modules associated with neuronal remodeling. Moreover, functional and pathway enrichment analysis with protein-protein network construction is applied to detect high informative hub genes in the targeted gene module. Thus, we select a total of five hub genes that play critical roles in neuronal remodeling and identify them with functional enrichment analysis and protein-protein interaction network. Overall, this study provides insight into the underlying molecular mechanism of developmental neuronal remodeling in Drosophila melanogaster.

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Apolipoprotein B Is Associated With the Microenvironment of Cholangiocarcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.654689 ◽

2021 ◽

Vol 11 ◽

Author(s):

Xiaofeng Xu ◽

Diyu Chen ◽

Xiaode Feng ◽

Jiating Hu ◽

Jiangzhen Ge ◽

...

Keyword(s):

Immune Cells ◽

Apolipoprotein B ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Abundance Ratio ◽

Functional Enrichment ◽

Score System ◽

Protein Protein Interaction ◽

New Ideas ◽

Differential Expressed Genes

BackgroundCholangiocarcinoma (CCA) is a kind of devastating malignancy, which is correlated with the extremely high mortality. Due to the occult pathogenesis of CCA, most patients are diagnosed in the advanced stage. However, the efficacy of chemotherapy and immunotherapy is limited for these patients. The cause for this phenomenon is unclear, the recent researches indicate that it could be related to predisposing genetic factors and tumor microenvironment (TME) changes. The TME is created by the tumor and dominated by tumor-induced interactions. And the tumor prognosis could be influenced by the extent of infiltrating immune cells and stromal cells in TME.Materials and methodsThe abundance ratio of immune cells for each sample was obtained via the CIBERSORT algorithm, and we used ESTIMATE score system to calculate the immune and stromal scores in CCA. The CCA cases in TCGA database were categorized into high and low score groups according to their immune/stromal scores. And then, we identified the differential expressed genes (DEGs) in two groups. Functional enrichment analysis and protein‐protein interaction networks were carried out for DEGs. Interestingly, we found out that apolipoprotein B (APOB) is the most down-regulated among these genes. Then we performed the immunohistochemistry staining of APOB in a CCA tumor microarray which contained 100 CCA cases, APOB was down-regulated in CCA samples. Thus, we evaluated the APOB function in the TME of CCA through TIMER.Results and ConclusionThe results demonstrate that the infiltration degree of immune cells in CCA could be influenced by the expression of APOB, and the APOB expression could be mediated by DNA methylation. Our study not only indicates APOB is a potential target for CCA immunotherapy but also provides new ideas for researchers to explore the immunotherapy of various tumors.

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Co-expression network analysis identifies specific hub genes in association with developmental neuronal remodeling in Drosophila melanogaster

10.7287/peerj.preprints.27586 ◽

2019 ◽

Author(s):

Yunze Liu ◽

Xiaojie Sun ◽

Aijun Qu

Keyword(s):

Drosophila Melanogaster ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Pathway Enrichment Analysis ◽

Hub Genes ◽

Protein Protein Interaction ◽

Neuronal Remodeling ◽

Gene Modules

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Gene Clusters Based on OLIG2 and CD276 Could Distinguish Molecular Profiling in Glioblastoma

10.21203/rs.3.rs-599543/v1 ◽

2021 ◽

Author(s):

Minjie Fu ◽

Jinsen Zhang ◽

Weifeng Li ◽

Shan He ◽

Jingwen Zhang ◽

...

Keyword(s):

Gene Cluster ◽

Efficient Method ◽

Enrichment Analysis ◽

Gene Clusters ◽

Functional Enrichment Analysis ◽

Molecular Classification ◽

Functional Enrichment ◽

Protein Protein Interaction ◽

Dna Elements

Abstract BackgroundThe molecular classification of glioblastoma (GBM) based on transcriptomic analysis could provide precise treatment and prognosis. However, current subtyping (Classic, Mesenchymal, Neural, Proneural) is a time-consuming and cost-intensive process, which hinders its clinical application. A simple and efficient method for classification was imperative.MethodsRandom forest algorithm was applied to conduct a gene cluster featured with hub genes, OLIG2 and CD276. Functional enrichment analysis and Protein-protein interaction were performed using the genes in this gene cluster. The classification efficiency of the gene cluster was validated by WGCNA and LASSO algorithms, and tested in GSE84010 and Gravandeel’s GBM datasets. ResultsThe gene cluster (n = 26) could distinguish mesenchymal and proneural excellently (AUC = 0.92), which could be validated by multiple algorithms (WGCNA, LASSO) and datasets (GSE84010 and Gravandeel’s GBM dataset). The gene cluster could be functionally enriched in DNA elements and T cell associated pathways. Additionally, five genes in the signature could predict the prognosis well (p = 0.0051 for training cohort, p = 0.065 for test cohort). ConclusionsThis study proved the accuracy and efficiency of random forest classifier for GBM subtyping and provided a convenient and efficient method for subtyping Proneural and Mesenchymal GBM.

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Role of COL3A1 and POSTN on Pathologic Stages of Esophageal Cancer

Technology in Cancer Research & Treatment ◽

10.1177/1533033820977489 ◽

2020 ◽

Vol 19 ◽

pp. 153303382097748

Author(s):

Shao-wei Zhang ◽

Nan Zhang ◽

Na Wang

Keyword(s):

Gene Expression ◽

Esophageal Cancer ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Gene Expression Omnibus ◽

Functional Enrichment ◽

Protein Protein Interaction ◽

And Control ◽

The Impact

Background: Esophageal cancer (EC) is a primary malignant tumor originating from the esophageal of the epithelium. Surgical resection is a potential treatment for EC, but this is only appropriate for patients who have locally resectable lesions suitable for surgery. However, most patients with EC are at a late stage when diagnosed. Therefore, there is an urgent need to further explore the pathogenesis of EC to enable early diagnosis and treatment. Methods: Our study downloaded 2 expression spectrum datasets (GSE92396 and GSE100942) in the Gene Expression Omnibus (GEO) database. GEO2 R was used to identify the Differentially expressed genes (DEGs) between the samples of EC and control. Using the DAVID tool to make the Functional enrichment analysis. Constructing A protein–protein interaction (PPI) network. Identifying the Hub genes. The impact of hub gene expression on overall survival and their expression based on immunohistochemistry were analyzed. Associated microRNAs were also predicted. Results: There were 36 common DEGs identified. The analysis of GO and KEGG results shown that the variations were predominantly concentrated in the extracellular matrix (ECM), ECM organization, DNA binding, platelet activation, and ECM-receptor interactions. COL3A1 and POSTN had high expression in EC tissues which was compared with their expression in healthy tissues. Analysis of pathologic stages showed that when COL3A1 and POSTN were highly expressed, the stage of the pathologic of EC patients was relatively high (P < 0.005). Conclusions: COL3A1 and POSTN may play an important role in the advancement and occurrence of EC. These genes could provide some novel ideas and basis for the diagnosis and targeted treatment of EC.

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Bioinformatics analysis of prognostic value genes in colorectal cancer microenvironment

10.21203/rs.2.16191/v1 ◽

2019 ◽

Author(s):

Taohua Yue ◽

Jing Zhu ◽

Xin Wang ◽

Yisheng Pan ◽

Yucun Liu ◽

...

Keyword(s):

Colorectal Cancer ◽

Large Scale ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Previous Literature ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Gastrointestinal Malignancies ◽

Protein Protein Interaction ◽

Cancer Genome Atlas

Abstract Colorectal cancer (CRC) is one of the most deadly gastrointestinal malignancies. The openness of the Cancer Genome Atlas (TCGA) allows us to perform correlation analysis between large-scale transcriptome data and overall survival (OS) of multiple malignancies. Previous literature reports that the infiltration of immune cells and stromal cells in the tumor microenvironment (TME) significantly associate with the prognosis of cancers. Based on the ESTIMATE algorithm, the immune and stromal components in TME can be quantified by immune and stromal scores. To determine the effects of immune and stromal cell associated genes on CRC prognosis, we divided the CRC cases into high- and low-groups based on the immune/stromal scores and identified 999 differentially expressed genes (DEGs). Heatmaps, functional enrichment analysis and protein‐protein interaction (PPIs) networks further indicated that 999 DEGs mainly participated in stromal composition and immune response. Finally, we obtained 56 genes that were significantly associated with CRC prognosis from 999 DEGs and identified the PPIs networks. The role of 41 genes in CRC has been reported in previous literature, and the other 15 genes have never been reported. Therefore, we found 15 novel TME genes associated with CRC prognosis waiting for more researches.

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Integrative Analysis of four miRNA prognostic signatures of prostate cancer

10.21203/rs.3.rs-34448/v1 ◽

2020 ◽

Author(s):

Chen Chi ◽

Xianwu Chen ◽

Liping Yao ◽

Min Li ◽

Lanting Xiang ◽

...

Keyword(s):

Prostate Cancer ◽

Overall Survival ◽

Target Genes ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Differentially Expressed ◽

Protein Protein Interaction ◽

Cellular Processes ◽

Relationship Of

Abstract Background Prostate cancer (PCa) is the most common urological cancer among men, having a poor prognosis, which is hard to accurately evaluate based on the present methods. MicroRNAs (miRNAs), a class of internal non-coding small RNA, can involve in the regulation of tumor biological function. So far, many researchers have tried to explore the relationship of malignant progress of PCa with miRNA, while there are just limited studies conducting the comprehensive analysis of miRNA in PCa clinical significance. Methods The data of miRNA and mRNA expressions in PCa were downloaded from TCGA database, and were performed the overall survival (OS) analysis using Survival package of R software to harvest the differentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs). The bioinformatics tools such as TargetScan, miRDB, and miRanda were also conducted to forecast the desired target genes related with prognostic DEMs. In addition, both GO and KEGG analyses were used to uncover the fundamental signaling pathways and cellular processes in PCa as well as the protein-protein interaction (PPI) network was constructed through STRING and Cytoscape software. Results Firstly, 4 DEMs (miR-19a-3p, miR-144-3p, miR-223-5p, and miR-483-3p) were found having significantly associated with overall survival in PCa. Based on the criteria with FDR < 0.05 and |log2FC| > 1, 33 genes were screened out as DEGs. Besides, the functional enrichment analysis revealed that these DEGs of 4 miRNAs may participate in cancer-related pathways like FoxO and PI3K-Akt signaling pathway. Lastly, the low expression of CD177 may be potentially associated with poor survival of patients in PCa. Conclusion This study systematically analyzed multiple PCa prognostic DEMs (miR-19a-3p, miR-144-3p, miR-223-5p, and miR-483-3p), and verified a novel DEG signature (CD177) that can be used to effectively assess the prognosis of PCa patients.

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The Important Role of Perituberal Tissue in Epileptic Patients with Tuberous Sclerosis Complex by the Transcriptome Analysis

BioMed Research International ◽

10.1155/2020/4980609 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11

Author(s):

Shuqiang Li ◽

Huijie Shao ◽

Liansheng Chang

Keyword(s):

Tuberous Sclerosis ◽

Tuberous Sclerosis Complex ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Receptor Interaction ◽

Ppi Network ◽

Hub Genes ◽

R Language ◽

Protein Protein Interaction

Epilepsy is most common in patients with tuberous sclerosis complex (TSC). However, in addition to the challenging treatment, the pathogenesis of epilepsy is still controversial. To determine the transcriptome characteristics of perituberal tissue (PT) and clarify its role in the pathogenesis of epilepsy, GSE16969 was downloaded from the GEO database for further study by comprehensive bioinformatics analysis. Identification of differentially expressed genes (DEGs), functional enrichment analysis, construction of protein-protein interaction (PPI) network, and selection of Hub genes were performed using R language, Metascape, STRING, and Cytoscape, respectively. Comparing with cortical tuber (CT), 220 DEGs, including 95 upregulated and 125 downregulated genes, were identified in PT and mainly enriched in collagen-containing extracellular matrix and positive regulation of receptor-mediated endocytosis, as well as the pathways of ECM-receptor interaction and neuroactive ligand-receptor interaction. As for normal cortex (NC), 1549 DEGs, including 30 upregulated and 1519 downregulated genes, were identified and mainly enriched in presynapse, dendrite and axon, and also the pathways of dopaminergic synapse and oxytocin signaling pathway. In the PPI network, 4 hub modules were found between PT and CT, and top 5 hub modules were selected between PT and NC. C3, APLNR, ANXA2, CD44, CLU, CP, MCHR2, HTR1E, CTSG, APP, and GNG2 were identified as Hub genes, of which, C3, CD44, ANXA2, HTR1E, and APP were identified as Hub-BottleNeck genes. In conclusion, PT has the unique characteristics different from CT and NC in transcriptome and makes us further understand its importance in the TSC-associated epilepsy.

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Network Pharmacology Prediction: The Possible Mechanisms of Cinobufotalin against Osteosarcoma

Computational and Mathematical Methods in Medicine ◽

10.1155/2022/3197402 ◽

2022 ◽

Vol 2022 ◽

pp. 1-9

Author(s):

Riyu Chen ◽

Zeyi Guan ◽

Xianxing Zhong ◽

Wenzheng Zhang ◽

Ya Zhang

Keyword(s):

Survival Curve ◽

Therapeutic Targets ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Network Pharmacology ◽

Hub Genes ◽

Survival Prognosis ◽

Active Compounds ◽

Protein Protein Interaction

Objective. To explore the active compounds and targets of cinobufotalin (huachansu) compared with the osteosarcoma genes to obtain the potential therapeutic targets and pharmacological mechanisms of action of cinobufotalin on osteosarcoma through network pharmacology. Methods. The composition of cinobufotalin was searched by literature retrieval, and the target was selected from the CTD and TCMSP databases. The osteosarcoma genes, found from the GeneCards, OMIM, and other databases, were compared with the cinobufotalin targets to obtain potential therapeutic targets. The protein-protein interaction (PPI) network of potential therapeutic targets, constructed through the STRING database, was inputted into Cytoscape software to calculate the hub genes, using the NetworkAnalyzer. The hub genes were inputted into the Kaplan-Meier Plotter online database for exploring the survival curve. Functional enrichment analysis was identified using the DAVID database. Results. 28 main active compounds of cinobufotalin were explored, including bufalin, adenosine, oleic acid, and cinobufagin. 128 potential therapeutic targets on osteosarcoma are confirmed among 184 therapeutic targets form cinobufotalin. The hub genes included TP53, ACTB, AKT1, MYC, CASP3, JUN, TNF, VEGFA, HSP90AA1, and STAT3. Among the hub genes, TP53, ACTB, MYC, TNF, VEGFA, and STAT3 affect the patient survival prognosis of sarcoma. Through function enrichment analysis, it is found that the main mechanisms of cinobufotalin on osteosarcoma include promoting sarcoma apoptosis, regulating the cell cycle, and inhibiting proliferation and differentiation. Conclusion. The possible mechanisms of cinobufotalin against osteosarcoma are preliminarily predicted through network pharmacology, and further experiments are needed to prove these predictions.

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