Identification of key genes and expression profiles in osteoarthritis by co-expressed network analysis

BackgroundThe underlying molecular characteristics of osteoarthritis (OA), a common age-related joint disease, remains elusive. Here, we aimed to identify potential early diagnostic biomarkers and elucidate underlying mechanisms of OA using weighted gene co-expression network analysis (WGCNA).Material and methodsWe obtained the gene expression profile dataset GSE55235, GSE55457, and GSE55584, from the Gene Expression Omnibus. WGCNA was used to investigate the changes in co-expressed genes between normal and OA synovial membrane samples. Modules that were highly correlated to OA were subjected to functional enrichment analysis using the R clusterProfiler package. Differentially expressed genes (DEGs) between the two samples were screened using the “limma” package in R. A Venn diagram was constructed to intersect the genes in significant modules and DEGs. RT -PCR was used to further verify the hub gene expression levels between normal and OA samples.ResultsThe preserved significant module was found to be highly associated with OA development and progression (P < 1e-200, correlation = 0.92). Functional enrichment analysis suggested that the antiquewhite4 module was highly correlated to FoxO signaling pathway, and the metabolism of fatty acids and 2-oxocarboxylic acid. A total of 13 hub genes were identified based on significant module network topology and DEG analysis, and RT-PCR confirmed that these genes were significantly increased in OA samples compared with that in normal samples.ConclusionsWe identified 13 hub genes correlated to the development and progression of OA, which may provide new biomarkers and drug targets for OA.     

Down regulation of lactotransferrin enhanced radio-sensitivity of nasopharyngeal carcinoma

IntroductionIt is reported that LTF had a radiation resistance effect, and its expression in nasopharyngeal carcinoma (NPC) was significantly down-regulated. However, the mechanism of down-regulated LTF affecting the sensitivity of radiotherapy has remained elusive.MethodsWe re-analyzed the microarray data GSE36972 and GSE48503 to find differentially expressed genes (DEGs) in NPC cell line 5−8 F transfected with LTF or vector control, and the DEGs between radio-resistant and radio-sensitive NPC cell lines. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment and protein-protein interaction network (PPI) analysis of DEGs were performed to obtain the node genes. The target genes of miR-214 were also predicted to complement the mechanism associated with radiotherapy resistance because it could directly target LTF.ResultsThis study identified 1190 and 1279 DEGs, respectively. GO and KEGG analysis showed that apoptotic process and proliferation, PI3K-Akt signaling pathway were significantly enriched pathways. Four nodes (DUSP1, PPARGC1A, FOS and SMARCA1) associated with LTF were screened. And 42 target genes of miR-214 were cross-linked to radiotherapy sensitivity.ConclusionsThe present study demonstrates the possible molecular mechanism that the down-regulated LTF enhances the radiosensitivity of NPC cells through interaction with DUSP1, PPARGC1A, FOS and SMARCA1, and miR-214 as its superior negative regulator may play a role in regulating the radiotherapy effect.     

Screening disrupted molecular functions and pathways associated with clear cell renal cell carcinoma using Gibbs sampling

ObjectiveTo explore the disturbed molecular functions and pathways in clear cell renal cell carcinoma (ccRCC) using Gibbs sampling.MethodsGene expression data of ccRCC samples and adjacent non-tumor renal tissues were recruited from public available database. Then, molecular functions of expression changed genes in ccRCC were classed to Gene Ontology (GO) project, and these molecular functions were converted into Markov chains. Markov chain Monte Carlo (MCMC) algorithm was implemented to perform posterior inference and identify probability distributions of molecular functions in Gibbs sampling. Differentially expressed molecular functions were selected under posterior value more than 0.95, and genes with the appeared times in differentially expressed molecular functions ≥5 were defined as pivotal genes. Functional analysis was employed to explore the pathways of pivotal genes and their strongly co-regulated genes.ResultsIn this work, we obtained 396 molecular functions, and 13 of them were differentially expressed. Oxidoreductase activity showed the highest posterior value. Gene composition analysis identified 79 pivotal genes, and survival analysis indicated that these pivotal genes could be used as a strong independent predictor of poor prognosis in patients with ccRCC. Pathway analysis identified one pivotal pathway − oxidative phosphorylation.ConclusionsWe identified the differentially expressed molecular functions and pivotal pathway in ccRCC using Gibbs sampling. The results could be considered as potential signatures for early detection and therapy of ccRCC.     

Insights regarding novel biomarkers and the pathogenesis of primary colorectal carcinoma based on bioinformatic analysis

BackgroundBiomarkers are important in the study of tumor processes for early detection and precise treatment. The biomarkers that have been previously detected are not useful for clinical application for primary colorectal carcinoma (PCRC). The aim of this study was to explore clinically valuable biomarkers of PCRC based on integrated bioinformatic analysis.Material and methodsGene expression data were acquired from the GSE41258 dataset, and the differentially expressed genes were determined between PCRC and normal colorectal samples. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were implemented via Gene Set Enrichment Analysis. A protein-protein interaction (PPI) network was constructed. The significant modules and hub genes were screened and identified in the PPI network.ResultsA total of 202 DEGs were identified, including 58 upregulated and 144 downregulated genes in PCRC samples compared to those in normal colorectal samples. Enrichment analysis demonstrated that the gene sets enriched in PCRC were significantly related to bicarbonate transport, regulation of sodium ion transport, potassium ion homeostasis, regulation of telomere maintenance, and other processes. A total of 10 hub genes was identified by cytoHubba: PYY, CXCL3, CXCL11, CXCL8, CXCL12, CCL20, MMP3, P2RY14, NPY1R, and CXCL1.ConclusionThe hub genes, such as NPY1R, P2RY14, and CXCL12, and the electrolyte disequilibrium resulting from the differential expression of genes, especially bicarbonate imbalance, may provide novel insights and evidence for the future diagnosis and targeted therapy of PCRC.     

The protective effect of icariin on glucocorticoid-damaged BMECs explored by microfluidic organ chip

Osteonecrosis of the femoral head(ONFH) is a devastating musculoskeletal disease characterized by the impaired circulation of bone. The purpose of this study was to explore the underlying mechanisms of the protective effect of icariin on the glucocorticoid-induced injury of bone microvascular endothelial cells(BMECs). Normal BMECs were extracted from the femoral heads by enzymatic isolation and magneticactivated cell sorting methods. Dexamethasone and icariin were used to intervene BMECs in micr...     

MiR-330-3p and miR-485-5p as biomarkers for glioblastoma: An integrated bioinformatics and experimental study

Glioblastoma Multiforme (GBM) is the most common, invasive, and malignant primary brain tumor with a poor prognosis and a median survival of 12–15 months. This study tried to identify the most significant miRNA biomarkers in both tissue and serum samples of GBM. GSE25632 was employed from gene expression omnibus and using WGCNA package, association of miRNA networks and clinical data was explored and brown and green modules identified as the most relevant modules. Independently, Limma package was utilized to identify differentially expressed miRNAs (DEMs) in GSE25632 by cutoff $\left|\text{l}\text{o}\text{g}\text{F}\text{C}\right|$ > 2 and P.value < 0.05. By merging the results of Limma and WGCNA, the miRNAs that were in brown and green modules and had mentioned cutoff were selected as hub miRNAs. Performing enrichment analysis, Pathways in cancer, Prostate cancer, Glioma, p53 signaling pathway, and Focal adhesion were identified as the most important signaling pathways. Based on miRNA- target genes, has-mir-330−3p and has-mir-485−5p were identified as core miRNAs. The expression level of core miRNAs was validated by GSE90604, GSE42657, and GSE93850. We evaluated the expression level of common target genes of two detected core genes based on GSE77043, GSE42656, GSE22891, GSE15824, and GSE122498. The ability of detected miRNAs to discriminate GBM from healthy controls was assessed by area under the curve (AUC) using the ROC curve analysis. Based on TCGA database, we tested the prognostic significance of miRNAs using overall survival analysis. We evaluated the expression level of the miRNAs in tissue of 83 GBM patients and also non-tumoral adjacent (as control) tissues. We used serum samples of 34 GBM patients to evaluate the expression levels of the hub miRNAs compare to the controls. Our results showed that has-mir-330−3p and has-mir-485−5p could be potential biomarkers in GBM.     

Clinicopathological value and underlying molecular mechanism of annexin A2 in 992 cases of thyroid carcinoma

BackgroundThyroid carcinoma (THCA) is one of the most frequent endocrine cancers and has increasing morbidity. Annexin A2 (ANXA2) has been found to be highly expressed in various cancers; however, its expression level and potential mechanism in THCA remain unknown. This study investigated the clinicopathological value and primary molecular machinery of ANXA2 in THCA.Material and MethodsPublic RNA-sequencing and microarray data were obtained and analyzed with ANXA2 expression in THCA and corresponding non-cancerous thyroid tissue. A Pearson correlation coefficient calculation was used for the acquisition of ANXA2 coexpressed genes, while edgR, limma, and Robust Rank Aggregation were employed for differentially expressed gene (DEG) in THCA. The probable mechanism of ANXA2 in THCA was predicted by gene ontology and pathway enrichment. A dual-luciferase reporter assay was employed to confirm the targeting relationships between ANXA2 and its predicted microRNA (miRNA).ResultsExpression of ANXA2 was significantly upregulated in THCA tissues with a summarized standardized mean difference of 1.09 (P < 0.0001) based on 992 THCA cases and 589 cases of normal thyroid tissue. Expression of ANXA2 was related to pathologic stage. Subsequently, 1442 genes were obtained when overlapping 4542 ANXA2 coexpressed genes with 2248 DEGs in THCA; these genes were mostly enriched in pathways of extracellular matrix-receptor interaction, cell adhesion molecules, and complement and coagulation cascades. MiR-23b-3p was confirmed to target ANXA2 by dual-luciferase reporter assay.ConclusionsUpregulated expression of ANXA2 may promote the malignant biological behavior of THCA by affecting the involving pathways or being targeted by miR-23b-3p.     

Identification of Key Candidate Genes Involved in the Progression of Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a lethal, agnogenic interstitial lung disease with limited therapeutic options. To investigate vital genes involved in the development of IPF, we integrated and compared four expression profiles ({"type":"entrez-geo","attrs":{"text":"GSE110147","term_id":"110147"}}GSE110147, {"type":"entrez-geo","attrs":{"text":"GSE53845","term_id":"53845"}}GSE53845, {"type":"entrez-geo","attrs":{"text":"GSE24206","term_id":"24206"}}GSE24206, and {"type":"entrez-geo","attrs":{"text":"GSE10667","term_id":"10667"}}GSE10667), including 87 IPF samples and 40 normal samples. By reanalyzing these datasets, we managed to identify 62 upregulated genes and 20 downregulated genes in IPF samples compared with normal samples. Differentially expressed genes (DEGs) were analyzed by gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis to illustrate relevant pathways of IPF, biological processes, molecular function, and cell components. The DEGs were then subjected to protein–protein interaction (PPI) for network analysis, serving to find 11 key candidate genes (ANXA3, STX11, THBS2, MMP1, MMP9, MMP7, MMP10, SPP1, COL1A1, ITGB8, IGF1). The result of RT-qPCR and immunohistochemical staining verified our finding as well. In summary, we identified 11 key candidate genes related to the process of IPF, which may contribute to novel treatments of IPF.     

Network pharmacology analysis of pharmacological mechanisms underlying the anti-type 2 diabetes mellitus effect of guava leaf

The current study aimed to explore the anti-type 2 diabetes mellitus (T2DM) mechanism of guava leaf based on network pharmacology. The compounds contained in guava leaf was summarized from the literature, and a series of databases was used to identify the active components and corresponding potential targets. The intersection between diabetes-associated genes searched in the GeneCard database and the predicted targets of guava leaf active components was defined as target genes, which were then used to construct a “compound-active components-target genes” pharmacological network. The biological functions and pathway enrichment analyses of target genes were performed in KOBAS 3.0. The differential expression analysis of GSE76894 was performed to obtain the differential expressed genes (DEGs) in T2DM patients by comparing non-diabetic controls. Finally, the intersection between DEGs and target genes were named key genes, and the representative pathways in which these genes were involved were drawn through KEGG Mapper. We found that the active components of guava leaf may regulate the PI3K-AKT signaling pathway, T2DM regulation process, and insulin resistance pathway, which was evidenced by KEGG pathway analysis of key genes. These results implied that guava leaf has a potential anti-T2DM property and its mode of action may be exerted via regulating insulin secretion and reducing blood sugar level.     

Transcriptome Profiling of HCT-116 Colorectal Cancer Cells with RNA Sequencing Reveals Novel Targets for Polyphenol Nano Curcumin

Colorectal cancer is one of the leading causes of cancer-related deaths worldwide. The gemini nanoparticle formulation of polyphenolic curcumin significantly inhibits the viability of cancer cells. However, the molecular mechanisms and pathways underlying its toxicity in colon cancer are unclear. Here, we aimed to uncover the possible novel targets of gemini curcumin (Gemini-Cur) on colorectal cancer and related cellular pathways. After confirming the cytotoxic effect of Gemini-Cur by MTT and apoptotic assays, RNA sequencing was employed to identify differentially expressed genes (DEGs) in HCT-116 cells. On a total of 3892 DEGs (padj < 0.01), 442 genes showed a log2 FC >|2| (including 244 upregulated and 198 downregulated). Gene ontology (GO) enrichment analysis was performed. Protein–protein interaction (PPI) and gene-pathway networks were constructed by using STRING and Cytoscape. The pathway analysis showed that Gemini-Cur predominantly modulates pathways related to the cell cycle. The gene network analysis revealed five central genes, namely GADD45G, ATF3, BUB1B, CCNA2 and CDK1. Real-time PCR and Western blotting analysis confirmed the significant modulation of these genes in Gemini-Cur-treated compared to non-treated cells. In conclusion, RNA sequencing revealed novel potential targets of curcumin on cancer cells. Further studies are required to elucidate the molecular mechanism of action of Gemini-Cur regarding the modulation of the expression of hub genes.     

Analysis of Renal Cell Carcinoma as a First Step for Developing Mass Spectrometry-Based Diagnostics

Immediate diagnosis of human specimen is an essential prerequisites in medical routines. This study aimed to establish a novel cancer diagnostics system based on probe electrospray ionization-mass spectrometry (PESI-MS) combined with statistical data processing. PESI-MS uses a very fine acupuncture needle as a probe for sampling as well as for ionization. To demonstrate the applicability of PESI-MS for cancer diagnosis, we analyzed nine cases of clear cell renal cell carcinoma (ccRCC) by PESI-MS and processed the data by principal components analysis (PCA). Our system successfully delineated the differences in lipid composition between non-cancerous and cancerous regions. In this case, triacylglycerol (TAG) was reproducibly detected in the cancerous tissue of nine different individuals, the result being consistent with well-known profiles of ccRCC. Moreover, this system enabled us to detect the boundaries of cancerous regions based on the expression of TAG. These results strongly suggest that PESI-MS will be applicable to cancer diagnosis, especially when the number of data is augmented.