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.     

NFκB pathway analysis: An approach to analyze gene co-expression networks employing feedback cycles

The genes of the NFκB pathway are involved in the control of a plethora of biological processes ranking from inhibition of apoptosis to metastasis in cancer. It has been described that Gliobastoma multiforme (GBM) patients carry aberrant NFκB activation, but the molecular mechanisms are not completely understood. Here, we present a NFκB pathway analysis in tumor specimens of GBM compared to non-neoplasic brain tissues, based on the different kind of cycles found among genes of a gene co-expression network constructed using quantized data obtained from the microarrays. A cycle is a closed walk with all vertices distinct (except the first and last). Thanks to this way of finding relations among genes, a more robust interpretation of gene correlations is possible, because the cycles are associated with feedback mechanisms that are very common in biological networks. In GBM samples, we could conclude that the stoichiometric relationship between genes involved in NFκB pathway regulation is unbalanced. This can be measured and explained by the identification of a cycle. This conclusion helps to understand more about the biology of this type of tumor.     

Identifying condition specific key genes from basal-like breast cancer gene expression data

Mining patterns of co-expressed genes across the subset of conditions help to narrow down the search space for the analysis of gene expression data. Identifying conditions specific key genes from the large-scale gene expression data is a challenging task. The conditions specific key gene signifies functional behavior of a group of co-expressed genes across the subset of conditions and can be act as biomarkers of the diseases. In this paper, we have propose a novel approach for identification of conditions specific key genes from Basal-Like Breast Cancer (BLBC) disease using biclustering algorithm and Gene Co-expression Network (GCN). The proposed approach is a two-stage approach. In the first stage, significant biclusters have been extracted with the help of ‘runibic’ biclustering algorithm. The second stage identifies conditions specific key genes from the extracted significant biclusters with the help of GCN. By using difference matrix and gene correlation matrix, we have constructed biologically meaningful and statistically strong GCN. Also, presented the proposed approach with the help of a process diagram and demonstrated the procedure with an example of bicluster number 93 (Bic93). From the experimental results, we observed that 95% and 85% of the extracted biclusters are found to be biologically significant at the p-values less than 0.05 and 0.01 respectively. We have compared proposed approach with the Weighted Gene Co-expression Network Analysis (WGCNA) based approach. From the comparison, our approach has performed effectively and extracted biologically significant biclusters. Also, identified conditions specific key genes which cannot be extracted using the WGCNA based approach. Some of the important identified known key genes are PIK3CA, SHC3, ERBB2, SHC4, PTOV1, STAG1, ZNF215 etc. These key genes can be used as a diagnostic and prognostic biomarker for the BLBC disease after the rigorous analysis. The identified conditions specific key genes can be helpful to reduce the analysis time and increase the accuracy of further research such as biomarker identification, drug target discovery etc.     

Investigating ego modules involved in TGFβ3-induced chondrogenesis in mesenchymal stem cells based on ego network

ObjectiveThis paper aimed to investigate ego modules for TGFβ3-induced chondrogenesis in mesenchymal stem cells (MSCs) using ego network algorithm.MethodsThe ego network algorithm comprised three parts, extracting differential expression network (DEN) based on gene expression data and protein-protein interaction (PPI) data; exploring ego genes by reweighting DEN; and searching ego modules by ego gene expansions. Subsequently, permutation test was carried out to evaluate the statistical significance of the ego modules. Finally, pathway enrichment analysis was conducted to investigate ego pathways enriched by the ego modules.ResultsA total of 15 ego genes were obtained from the DEN, such as PSMA4, HNRNPM and WDR77. Starting with each ego genes, 15 candidate modules were gained. When setting the thresholds of the area under the receiver operating characteristics curve (AUC) ≥0.9 and gene size ≥4, three ego modules (Module 3, Module 8 and Module 14) were identified, and all of them had statistical significances between normal and TGFβ3-induced chondrogenesis in MSCs. By mapping module genes to confirmed pathway database, their ego pathways were detected, Cdc20:Phospho-APC/C mediated degradation of Cyclin A for Module 3, Mitotic G1-G1/S phases for Module 8, and mRNA Splicing for Module 14.ConclusionsWe have successfully identified three ego modules, evaluated their statistical significances and investigated their functional enriched ego pathways. The findings might provide potential biomarkers and give great insights to reveal molecular mechanism underlying this process.     

Characterizing mutation–expression network relationships in multiple cancers

BackgroundData made available through large cancer consortia like The Cancer Genome Atlas make for a rich source of information to be studied across and between cancers. In recent years, network approaches have been applied to such data in uncovering the complex interrelationships between mutational and expression profiles, but lack direct testing for expression changes via mutation. In this pan-cancer study we analyze mutation and gene expression information in an integrative manner by considering the networks generated by testing for differences in expression in direct association with specific mutations. We relate our findings among the 19 cancers examined to identify commonalities and differences as well as their characteristics.ResultsUsing somatic mutation and gene expression information across 19 cancers, we generated mutation–expression networks per cancer. On evaluation we found that our generated networks were significantly enriched for known cancer-related genes, such as skin cutaneous melanoma (p < 0.01 using Network of Cancer Genes 4.0). Our framework identified that while different cancers contained commonly mutated genes, there was little concordance between associated gene expression changes among cancers. Comparison between cancers showed a greater overlap of network nodes for cancers with higher overall non-silent mutation load, compared to those with a lower overall non-silent mutation load.ConclusionsThis study offers a framework that explores network information through co-analysis of somatic mutations and gene expression profiles. Our pan-cancer application of this approach suggests that while mutations are frequently common among cancer types, the impact they have on the surrounding networks via gene expression changes varies. Despite this finding, there are some cancers for which mutation-associated network behaviour appears to be similar: suggesting a potential framework for uncovering related cancers for which similar therapeutic strategies may be applicable. Our framework for understanding relationships among cancers has been integrated into an interactive R Shiny application, PAn Cancer Mutation Expression Networks (PACMEN), containing dynamic and static network visualization of the mutation–expression networks. PACMEN also features tools for further examination of network topology characteristics among cancers.     

Enhancement of O-GlcNAcylation on Mitochondrial Proteins with 2-(4-Methoxyphenyl)ethyl-2-acetamido-2-deoxy-β-d-pyranoside,Contributes to the Mitochondrial Network,Cellular Bioenergetics and Stress Response in Neuronal Cells under Ischemic-like Conditions

O-GlcNAcylation is a nutrient-driven post-translational modification known as a metabolic sensor that links metabolism to cellular function. Recent evidences indicate that the activation of O-GlcNAc pathway is a potential pro-survival pathway and that acute enhancement of this response is conducive to the survival of cells and tissues. 2-(4-Methoxyphenyl)ethyl-2-acetamido-2-deoxy-β-d-pyranoside (SalA-4g), is a salidroside analogue synthesized in our laboratory by chemical structure-modification, with a phenyl ring containing a para-methoxy group and a sugar ring consisting of N-acetylglucosamine. We have previously shown that SalA-4g elevates levels of protein O-GlcNAc and improves neuronal tolerance to ischemia. However, the specific target of SalA-4g regulating O-GlcNAcylation remains unknown. To address these questions, in this study, we have focused on mitochondrial network homeostasis mediated by O-GlcNAcylation in SalA-4g’s neuroprotection in primary cortical neurons under ischemic-like conditions. O-GlcNAc-modified mitochondria induced by SalA-4g demonstrated stronger neuroprotection under oxygen glucose deprivation and reoxygenation stress, including the improvement of mitochondrial homeostasis and bioenergy, and inhibition of mitochondrial apoptosis pathway. Blocking mitochondrial protein O-GlcNAcylation with OSMI-1 disrupted mitochondrial network homeostasis and antagonized the protective effects of SalA-4g. Collectively, these data demonstrate that mitochondrial homeostasis mediated by mitochondrial protein O-GlcNAcylation is critically involved in SalA-4g neuroprotection.     

The gene network determining development of Drosophila melanogaster mechanoreceptors

Macrochaetes (large bristles), functioning as mechanoreceptors, are located in an orderly fashion on the drosophila head and body forming a species-specific bristle pattern. A simple organization of each bristle organ, comprising only four specialized cells, and conservation of bristle pattern make macrochaetes a convenient model for studying the development patterns of spatial structures with a fixed number of elements at certain positions and the mechanisms of cell differentiation.In this work, we systematize the experimental data on the main genes and their products that are involved in the control of proneural clusters in the ectoderm of imaginal discs and determination of the sensory organ precursor (SOP) cell within the proneural clusters. The computer system GeneNet was used to reconstruct the gene network controlling these stages of macrochaete development, which are critical for the formation of a correct bristle pattern. The role of achaete–scute complex and EGFR and Notch signaling pathways and the regulatory mechanisms acting in this gene network are discussed.     

Bioinformatics and Functional Analyses Implicate Potential Roles for EOGT and L-fringe in Pancreatic Cancers

Notch signaling receptors, ligands, and their downstream target genes are dysregulated in pancreatic ductal adenocarcinoma (PDAC), suggesting a role of Notch signaling in pancreatic tumor development and progression. However, dysregulation of Notch signaling by post-translational modification of Notch receptors remains poorly understood. Here, we analyzed the Notch-modifying glycosyltransferase involved in the regulation of the ligand-dependent Notch signaling pathway. Bioinformatic analysis revealed that the expression of epidermal growth factor (EGF) domain-specific O-linked N-acetylglucosamine (EOGT) and Lunatic fringe (LFNG) positively correlates with a subset of Notch signaling genes in PDAC. The lack of EOGT or LFNG expression inhibited the proliferation and migration of Panc-1 cells, as observed by the inhibition of Notch activation. EOGT expression is significantly increased in the basal subtype, and low expression of both EOGT and LFNG predicts better overall survival in PDAC patients. These results imply potential roles for EOGT- and LFNG-dependent Notch signaling in PDAC.     

Global expression analysis of CESA and CSL genes in Arabidopsis

We have used Affymetrix gene chips to measure the expression of 10 CESA and 29 CSL genes of Arabidopsis in different developmental stages or organs. These measurements reveal that many of the genes exhibit different levels of expression in the various organs. While several CESA genes are highly expressed in all the tissues examined, very few CSL genes approach such high levels of expression. This suggests that the CSL genes either encode enzymes for the synthesis of minor components of cell walls or are expressed only in specific cell types. The expression data also highlights the potential importance of the CESA genes for primary and secondary cell wall formation during different developmental stages and in the different organs examined.     

Genetic and expression alterations in association with the sarcomatous change of cholangiocarcinoma cells

Cholangiocarcinoma (CC) is an intrahepatic bile duct carcinoma with a high mortality rate and a poor prognosis. Sarcomatous change/epithelial mesenchymal transition (EMT) of CC frequently leads to aggressive intrahepatic spread and metastasis. The aim of this study was to identify the genetic alterations and gene expression pattern that might be associated with the sarcomatous change in CC. Previously, we established 4 human CC cell lines (SCK, JCK1, Cho-CK, and Choi-CK). In the present study, we characterized a typical sarcomatoid phenotype of SCK, and classified the other cell lines according to tumor cell differentiation (a poorly differentiated JCK, a moderately differentiated Cho-CK, and a well differentiated Choi-CK cells), both morphologically and immunocytologically. We further analyzed the genetic alterations of two tumor suppressor genes (p53 and FHIT) and the expression of Fas/FasL gene, well known CC-related receptor and its ligand, in these four CC cell lines. The deletion mutation of p53 was found in the sarcomatoid SCK cells. These cells expressed much less Fas/FasL mRNAs than did the other ordinary CC cells. We further characterize the gene expression pattern that is involved in the sarcomatous progression of CC, using cDNA microarrays that contained 18,688 genes. Comparison of the expression patterns between the sarcomatoid SCK cells and the differentiated Choi-CK cells enabled us to identify 260 genes and 247 genes that were significantly over-expressed and under-expressed, respectively. Northern blotting of the 14 randomly selected genes verified the microarray data, including the differential expressions of the LGALS1, TGFBI, CES1, LDHB, UCHL1, ASPH, VDAC1, VIL2, CCND2, S100P, CALB1, MAL2, GPX1, and ANXA8 mRNAs. Immunohistochemistry also revealed in part the differential expressions of these gene proteins. These results suggest that those genetic and gene expression alterations may be relevant to the sarcomatous change/EMT in CC cells.     

A network-based pharmacology study of active compounds and targets of Fritillaria thunbergii against influenza

Seasonal and pandemic influenza infections are serious threats to public health and the global economy. Since antigenic drift reduces the effectiveness of conventional therapies against the virus, herbal medicine has been proposed as an alternative. Fritillaria thunbergii (FT) have been traditionally used to treat airway inflammatory diseases such as coughs, bronchitis, pneumonia, and fever-based illnesses. Herein, we used a network pharmacology-based strategy to predict potential compounds from Fritillaria thunbergii (FT), target genes, and cellular pathways to better combat influenza and influenza-associated diseases. We identified five compounds, and 47 target genes using a compound-target network (C-T). Two compounds (beta-sitosterol and pelargonidin) and nine target genes (BCL2, CASP3, HSP90AA1, ICAM1, JUN, NOS2, PPARG, PTGS1, PTGS2) were identified using a compound-influenza disease target network (C-D). Protein-protein interaction (PPI) network was constructed and we identified eight proteins from nine target genes formed a network. The compound-disease-pathway network (C-D-P) revealed three classes of pathways linked to influenza: cancer, viral diseases, and inflammation. Taken together, our systems biology data from C-T, C-D, PPI and C-D-P networks predicted potent compounds from FT and new therapeutic targets and pathways involved in influenza.     

Cool Temperature Enhances Growth,Ferulic Acid and Flavonoid Biosynthesis While Inhibiting Polysaccharide Biosynthesis in Angelica sinensis

Angelica sinensis, a perennial herb that produces ferulic acid and phthalides for the treatment of cardio-cerebrovascular diseases, prefers growing at an altitude of 1800–3000 m. Geographical models have predicted that high altitude, cool temperature and sunshade play determining roles in geo-authentic formation. Although the roles of altitude and light in yield and quality have been investigated, the role of temperature in regulating growth, metabolites biosynthesis and gene expression is still unclear. In this study, growth characteristics, metabolites contents and related genes expression were investigated by exposing A. sinensis to cooler (15 °C) and normal temperatures (22 °C). The results showed that plant biomass, the contents of ferulic acid and flavonoids and the expression levels of genes related to the biosynthesis of ferulic acid (PAL1, 4CLL4, 4CLL9, C3H, HCT, CCOAMT and CCR) and flavonoids (CHS and CHI) were enhanced at 15 °C compared to 22 °C. The contents of ligustilide and volatile oils exhibited slight increases, while polysaccharide contents decreased in response to cooler temperature. Based on gene expression levels, ferulic acid biosynthesis probably depends on the CCOAMT pathway and not the COMT pathway. It can be concluded that cool temperature enhances plant growth, ferulic acid and flavonoid accumulation but inhibits polysaccharide biosynthesis in A. sinensis. These findings authenticate that cool temperature plays a determining role in the formation of geo-authentic and also provide a strong foundation for regulating metabolites production of A. sinensis.     

Cellulose synthesis in maize: isolation and expression analysis of the cellulose synthase (CesA) gene family

Stalk lodging in maize results in significant yield losses. We have determined that cellulose per unit length of the stalk is the primary determinant of internodal strength. An increase in cellulose concentration in the wall might allow simultaneous improvements in stalk strength and harvest index. Cellulose formation in plants can be perturbed by mutations in the genes involved in cellulose synthesis, post-synthetic cellulose alteration or deposition, N-glycosylation, and some other genes with as yet unknown functions. We have isolated 12 members of the cellulose synthase (CesA) gene family from maize. The genes involved in primary wall formation appear to have duplicated relatively independently in dicots and monocots. The deduced amino acid sequences of three of the maize genes, ZmCesA10–12, cluster with the Arabidopsis CesA sequences that have been shown to be involved in secondary wall formation. Based on their expression patterns across multiple tissues, these three genes appear to be coordinately expressed. The remaining genes show overlapping expression to varying degrees with ZmCesA1, 7, and 8 forming one group, ZmCesA3 and 5 a second group, and ZmCesA2 and 6 exhibiting independent expression of any other gene. This suggests that the varying levels of coexpression may just be incidental except in the case of ZmCesA10–12, which may interact with each other to form a functional enzyme complex. Isolation of the expressed CesA genes from maize and their association with primary or secondary wall formation has made it possible to test their respective roles in cellulose synthesis through mutational genetics or transgenic approaches. This information would be useful in improving stalk strength.