scholarly journals Uncovering Potential Roles of Differentially Expressed Genes, Upstream Regulators, and Canonical Pathways in Endometriosis Using an In Silico Genomics Approach

Diagnostics ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 416
Author(s):  
Zeenat Mirza ◽  
Umama A. Abdel-dayem

Endometriosis is characterized by ectopic endometrial tissue implantation, mostly within the peritoneum, and affects women in their reproductive age. Studies have been done to clarify its etiology, but the precise molecular mechanisms and pathophysiology remain unclear. We downloaded genome-wide mRNA expression and clinicopathological data of endometriosis patients and controls from NCBI’s Gene Expression Omnibus, after a systematic search of multiple independent studies comprising 156 endometriosis patients and 118 controls to identify causative genes, risk factors, and potential diagnostic/therapeutic biomarkers. Comprehensive gene expression meta-analysis, pathway analysis, and gene ontology analysis was done using a bioinformatics-based approach. We identified 1590 unique differentially expressed genes (129 upregulated and 1461 downregulated) mapped by IPA as biologically relevant. The top upregulated genes were FOS, EGR1, ZFP36, JUNB, APOD, CST1, GPX3, and PER1, and the top downregulated ones were DIO2, CPM, OLFM4, PALLD, BAG5, TOP2A, PKP4, CDC20B, and SNTN. The most perturbed canonical pathways were mitotic roles of Polo-like kinase, role of Checkpoint kinase proteins in cell cycle checkpoint control, and ATM signaling. Protein–protein interaction analysis showed a strong network association among FOS, EGR1, ZFP36, and JUNB. These findings provide a thorough understanding of the molecular mechanism of endometriosis, identified biomarkers, and represent a step towards the future development of novel diagnostic and therapeutic options.

2020 ◽  
Vol 40 (11) ◽  
Author(s):  
Lin Zhao ◽  
Yuhui Li ◽  
Zhen Zhang ◽  
Jing Zou ◽  
Jianfu Li ◽  
...  

Abstract Background: Ovarian cancer causes high mortality rate worldwide, and despite numerous attempts, the outcome for patients with ovarian cancer are still not well improved. Microarray-based gene expressional analysis provides with valuable information for discriminating functional genes in ovarian cancer development and progression. However, due to the differences in experimental design, the results varied significantly across individual datasets. Methods: In the present study, the data of gene expression in ovarian cancer were downloaded from Gene Expression Omnibus (GEO) and 16 studies were included. A meta-analysis based gene expression analysis was performed to identify differentially expressed genes (DEGs). The most differentially expressed genes in our meta-analysis were selected for gene expression and gene function validation. Results: A total of 972 DEGs with P-value < 0.001 were identified in ovarian cancer, including 541 up-regulated genes and 431 down-regulated genes, among which 92 additional DEGs were found as gained DEGs. Top five up- and down-regulated genes were selected for the validation of gene expression profiling. Among these genes, up-regulated CD24 molecule (CD24), SRY (sex determining region Y)-box transcription factor 17 (SOX17), WFDC2, epithelial cell adhesion molecule (EPCAM), innate immunity activator (INAVA), and down-regulated aldehyde oxidase 1 (AOX1) were revealed to be with consistent expressional patterns in clinical patient samples of ovarian cancer. Gene functional analysis demonstrated that up-regulated WFDC2 and INAVA promoted ovarian cancer cell migration, WFDC2 enhanced cell proliferation, while down-regulated AOX1 was functional in inducing cell apoptosis of ovarian cancer. Conclusion: Our study shed light on the molecular mechanisms underlying the development of ovarian cancer, and facilitated the understanding of novel diagnostic and therapeutic targets in ovarian cancer.


2020 ◽  
Author(s):  
Lin Zhao ◽  
Yuhui Li ◽  
Zhen Zhang ◽  
Hong Guo ◽  
Jianfu Li ◽  
...  

Abstract Background Ovarian cancer causes high mortality rate worldwide, and despite numerous attempts, the outcome for patients with ovarian cancer are still not well improved. Microarray based gene expressional analysis provides with valuable information for discriminating functional genes in ovarian cancer development and progression. However, due to the differences in experimental design, the results varied significantly across individual datasets. Methods In the present study, the data of gene expression in ovarian cancer was downloaded from Gene Expression Omnibus and 16 studies were included. A meta-analysis based gene expression analysis was performed to identify differentially expressed genes (DEGs). The most differentially expressed genes in our meta-analysis were selected for gene expression and gene function validation. Results A total of 972 DEGs with P -value<0.001 were identified in ovarian cancer, including 541 up-regulated genes and 431 down-regulated genes, among which 92 additional DEGs were found as gained DEGs. Top five up-and down-regulated genes were selected for the validation of gene expressional profiling. Among these genes, up-regulated CD24 , SOX17 , WFDC2 , EPCAM , INAVA , and down-regulated AOX1 were revealed to be with consistent expressional patterns in clinical patient samples of ovarian cancer. Gene functional analysis demonstrated that up-regulated WFCD2 and INAVA promoted ovarian cancer cell migration, WFDC2 enhanced cell proliferation, while down-regulated AOX1 was functional in inducing cell apoptosis of ovarian cancer. Interestingly. Conclusion Our study shed light on the molecular mechanisms underlying the development of ovarian cancer, and facilitated the understanding of novel diagnostic and therapeutic targets in ovarian cancer.


Viruses ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 244 ◽  
Author(s):  
Antonio Victor Campos Coelho ◽  
Rossella Gratton ◽  
João Paulo Britto de Melo ◽  
José Leandro Andrade-Santos ◽  
Rafael Lima Guimarães ◽  
...  

HIV-1 infection elicits a complex dynamic of the expression various host genes. High throughput sequencing added an expressive amount of information regarding HIV-1 infections and pathogenesis. RNA sequencing (RNA-Seq) is currently the tool of choice to investigate gene expression in a several range of experimental setting. This study aims at performing a meta-analysis of RNA-Seq expression profiles in samples of HIV-1 infected CD4+ T cells compared to uninfected cells to assess consistently differentially expressed genes in the context of HIV-1 infection. We selected two studies (22 samples: 15 experimentally infected and 7 mock-infected). We found 208 differentially expressed genes in infected cells when compared to uninfected/mock-infected cells. This result had moderate overlap when compared to previous studies of HIV-1 infection transcriptomics, but we identified 64 genes already known to interact with HIV-1 according to the HIV-1 Human Interaction Database. A gene ontology (GO) analysis revealed enrichment of several pathways involved in immune response, cell adhesion, cell migration, inflammation, apoptosis, Wnt, Notch and ERK/MAPK signaling.


2020 ◽  
Author(s):  
Na Li ◽  
Ru-feng Bai ◽  
Chun Li ◽  
Li-hong Dang ◽  
Qiu-xiang Du ◽  
...  

Abstract Background: Muscle trauma frequently occurs in daily life. However, the molecular mechanisms of muscle healing, which partly depend on the extent of the damage, are not well understood. This study aimed to investigate gene expression profiles following mild and severe muscle contusion, and to provide more information about the molecular mechanisms underlying the repair process.Methods: A total of 33 rats were divided randomly into control (n = 3), mild contusion (n = 15), and severe contusion (n = 15) groups; the contusion groups were further divided into five subgroups (1, 3, 24, 48, and 168 h post-injury; n = 3 per subgroup). Then full genome microarray of RNA isolated from muscle tissue was performed to access the gene expression changes during healing process.Results: A total of 2,844 and 2,298 differentially expressed genes were identified in the mild and severe contusion groups, respectively. The analysis of the overlapping differentially expressed genes showed that there are common mechanisms of transcriptomic repair of mild and severe contusion within 48 h post-contusion. This was supported by the results of principal component analysis, hierarchical clustering, and weighted gene co‐expression network analysis of the 1,620 coexpressed genes in mildly and severely contused muscle. From these analyses, we discovered that the gene profiles in functional modules and temporal clusters were similar between the mild and severe contusion groups; moreover, the genes showed time-dependent patterns of expression, which allowed us to identify useful markers of wound age. We then performed an analysis of the functions of genes (including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway annotation, and protein–protein interaction network analysis) in the functional modules and temporal clusters, and the hub genes in each module–cluster pair were identified. Interestingly, we found that genes downregulated within 24−48 h of the healing process were largely associated with metabolic processes, especially oxidative phosphorylation of reduced nicotinamide adenine dinucleotide phosphate, which has been rarely reported. Conclusions: These results improve our understanding of the molecular mechanisms underlying muscle repair, and provide a basis for further studies of wound age estimation.


2020 ◽  
pp. 153537022096732
Author(s):  
Lille Kurvits ◽  
Freddy Lättekivi ◽  
Ene Reimann ◽  
Liis Kadastik-Eerme ◽  
Kristjan M Kasterpalu ◽  
...  

Transcriptomics in Parkinson’s disease offers insights into the pathogenesis of Parkinson’s disease but obtaining brain tissue has limitations. In order to bypass this issue, we profile and compare differentially expressed genes and enriched pathways (KEGG) in two peripheral tissues (blood and skin) of 12 Parkinson’s disease patients and 12 healthy controls using RNA-sequencing technique and validation with RT-qPCR. Furthermore, we compare our results to previous Parkinson’s disease post mortem brain tissue and blood results using the robust rank aggregation method. The results show no overlapping differentially expressed genes or enriched pathways in blood vs. skin in our sample sets (25 vs. 1068 differentially expressed genes with an FDR ≤ 0.05; 1 vs. 9 pathways in blood and skin, respectively). A meta-analysis from previous transcriptomic sample sets using either microarrays or RNA-Seq yields a robust rank aggregation list of cortical gene expression changes with 43 differentially expressed genes; a list of substantia nigra changes with 2 differentially expressed genes and a list of blood changes with 1 differentially expressed gene being statistically significant at FDR ≤ 0.05. In cortex 1, KEGG pathway was enriched, four in substantia nigra and two in blood. None of the differentially expressed genes or pathways overlap between these tissues. When comparing our previously published skin transcription analysis, two differentially expressed genes between the cortex robust rank aggregation and skin overlap. In this study, for the first time a meta-analysis is applied on transcriptomic sample sets in Parkinson’s disease. Simultaneously, it explores the notion that Parkinson’s disease is not just a neuronal tissue disease by exploring peripheral tissues. The comparison of different Parkinson’s disease tissues yields surprisingly few significant differentially expressed genes and pathways, suggesting that divergent gene expression profiles in distinct cell lineages, metabolic and possibly iatrogenic effects create too much transcriptomic noise for detecting significant signal. On the other hand, there are signs that point towards Parkinson’s disease-specific changes in non-neuronal peripheral tissues in Parkinson’s disease, indicating that Parkinson’s disease might be a multisystem disorder.


2018 ◽  
Vol 1 (3) ◽  
Author(s):  
Li Gao ◽  
Yong Jie Yang ◽  
En Qi Li ◽  
Jia Ning Mao

Objective Evidence indicates that physical activity influence bone health. However, the molecular mechanisms mediating the beneficial adaptations to exercise are not well understood. The purpose of this study was to examine the differentially expressed genes in PBMC between athletes and healthy controls, and to analyze the important functional genes and signal pathways that cause increased bone mineral density in athletes, in order to further reveal the molecular mechanisms of exercise promoting bone health. Methods Five professional trampoline athletes and five age-matched untrained college students participated in this study. Used the human expression Microarray V4.0 expression profiling chip to detect differentially expressed genes in the two groups, and performed KEGG Pathway analysis and application of STRING database to construct protein interaction Network; Real-Time PCR technology was used to verify the expression of some differential genes.  Results Compared with healthy controls, there were significant improvement in lumbar spine bone mineral density, and 236 up-regulated as well as 265 down-regulated in serum samples of athletes. The differentially expressed genes involved 28 signal pathways, such as cell adhesion molecules. Protein interaction network showed that MYC was at the core node position. Real-time PCR results showed that the expression levels of CD40 and ITGα6 genes in the athletes were up-regulated compared with the healthy controls, the detection results were consistent with that of the gene chip. Conclusions The findings highlight that long-term high-intensity trampoline training could induce transcriptional changes in PBMC of the athletes. These data suggest that gene expression fingerprints can serve as a powerful research tool to design novel strategies for monitoring exercise. The findings of the study also provide support for the notion that PBMC could be used as a substitute to study exercise training that affects bone health.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Aimin Hu ◽  
Zheng Wei ◽  
Zuxiang Zheng ◽  
Bichao Luo ◽  
Jieming Yi ◽  
...  

Hepatocellular carcinoma (HCC) is one of the most common and lethal malignancies worldwide. Although there have been extensive studies on the molecular mechanisms of its carcinogenesis, FDA-approved drugs for HCC are rare. Side effects, development time, and cost of these drugs are the major bottlenecks, which can be partially overcome by drug repositioning. In this study, we developed a computational framework to study the mechanisms of HCC carcinogenesis, in which drug perturbation-induced gene expression signatures were utilized for repositioning of potential drugs. Specifically, we first performed differential expression analysis and coexpression network module analysis on the HCC dataset from The Cancer Genome Atlas database. Differential gene expression analysis identified 1,337 differentially expressed genes between HCC and adjacent normal tissues, which were significantly enriched in functions related to various pathways, including α-adrenergic receptor activity pathway and epinephrine binding pathway. Weighted gene correlation network analysis (WGCNA) suggested that the number of coexpression modules was higher in HCC tissues than in normal tissues. Finally, by correlating differentially expressed genes with drug perturbation-related signatures, we prioritized a few potential drugs, including nutlin and eribulin, for the treatment of hepatocellular carcinoma. The drugs have been reported by a few experimental studies to be effective in killing cancer cells.


2020 ◽  
Author(s):  
Takuma Sakamoto ◽  
Maaya Nishiko ◽  
Hidemasa Bono ◽  
Takeru Nakazato ◽  
Jin Yoshimura ◽  
...  

Abstract Background: Polyembryony is defined as the formation of several embryos from a single egg. This phenomenon can occur in humans, armadillo, and some endoparasitoid insects. However, the mechanism underlying polyembryogenesis in animals remains to be elucidated. The polyembryonic parasitoid wasp Copidosoma floridanum oviposits its egg into an egg of the host insect; eventually, over 2,000 individuals will arise from one egg. Previously, we reported that polyembryogenesis is enhanced when the juvenile hormone (JH) added to the culture medium in the embryo culture. Hence, in the present study, we performed RNA sequencing (RNA-Seq) analysis to investigate the molecular mechanisms controlling polyembryogenesis of C. floridanum . Functional annotation of genes is not fully available for C.floridanum ; however, whole genome assembly has been archived. Hence, we constructed a pipeline for gene functional annotation in C. floridanum and performed molecular network analysis. We analyzed differentially expressed genes between control and JH-treated molura after 48 h of culture, then used the tblastx program to assign whole C. floridanum transcripts to human gene. Results: We obtained 11,117 transcripts in the JH treatment group and identified 217 differentially expressed genes compared with the control group. As a result, 76% of C. floridanum transcripts were assigned to human genes. Gene enrichment analysis revealed genes associated with platelet degranulation, fatty acid biosynthesis, cell morphogenesis in the differentiation and integrin signaling pathways were fluctuated following JH treatment. Furthermore, Cytoscape analysis revealed a molecular interaction that was possibly associated with polyembryogenesis . Conclusions: We have constructed a pipeline for gene functional annotation of C. floridanum , and identified transcripts with high similarity to human genes during early embryo developmental. Additionally, this study reveals new molecular interactions associated with polyembryogenesis; these interactions could indicate the molecular mechanisms underlying polyembryony. Our results highlight the potential utility of molecular interaction analysis in human twins.


Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 3671-3671
Author(s):  
Michael Getman ◽  
Jeffrey Malik ◽  
James Palis ◽  
Laurie A Steiner

Abstract The molecular mechanisms that drive the maturation of a committed erythroid progenitor to a functional red blood cell are incompletely understood. LSD1 (Lysine-Specific Histone Demethylase 1) is a widely expressed histone demethylase that plays an important role in erythroid maturation (Kereyni, elife, 2013). Although LSD1 is important for a number of biologic processes ranging from embryonic development to leukemogenesis, the molecular mechanisms underlying the influence of LSD1 on gene expression are incompletely understood. The goal of our study is to elucidate the molecular mechanisms by which LSD1 regulates erythroid gene expression and influences erythroid maturation. We hypothesize that LSD1 promotes specific patterns of histone and DNA methylation that facilitate gene expression changes necessary for normal erythroid maturation to occur. To address this hypothesis, the functional and molecular consequences of LSD1 knockdown were assessed in Extensively Self Renewing Erythroblasts (ESREs), a non-transformed, karyotypically normal model of terminal erythroid maturation (England, Blood, 2011). Primary fetal liver was cultured in the presence of EPO, SCF, IGF1 and dexamethasone to derive ESREs. The ESREs were capable of extensive ex-vivo expansion, doubling daily at the proerythroblast phase, however when matured, >90% of cells became benzidine positive and >65% enucleated within 3 days. Lentiviral-mediated shRNA was used to knock down LSD1 in expanding ESREs. Imaging flow cytometry done on maturation day 3 demonstrated that the knockdown cells had impairments in multiple facets of maturation, with larger cell and nuclear areas, higher kit expression, and lower rates of enucleation than the scramble control. LSD1 knockdown was also associated with impaired hemoglobin accumulation (78% vs. 95% benzidine positive; p<0.005). Treatment of ESREs with an inhibitor to LSD1 (Tranylcypromine; TCP) resulted in similar abnormalities in cell and nuclear size, kit expression, hemoglobin accumulation, and enucleation (40% vehicle vs.1% TCP). The functional deficits in maturation, including abnormal kit expression and low rates of enucleation, persisted on maturation day 4. To delineate the molecular mechanisms underlying this maturation impairment, RNA-seq was done in LSD1 knockdown and scramble control samples, and 230 differentially expressed genes (FDR<0.01) were identified using cuffdiff (Trapnell, Nat Biotech, 2013). Consistent with LSD1’s role in erythroid maturation, Ingenuity Pathway Analysis identified multiple networks involving hemoglobin synthesis, and GATA1, EPO, and KLF1 were all predicted as upstream regulators (p-values of 8.24e10-11, 7.25 e10-6, and 3.86e10-4, respectively). To better understand how LSD1 influences gene expression, chromatin immunoprecipitation coupled with high throughput sequencing was used to identify sites of H3K4me2 binding in the differentially expressed genes. 214/230 differentially expressed genes were associated with sites of H3K4me2 occupancy. Quantitative ChIP demonstrated that LSD1 inhibition was associated with increases in H3K4me2 levels at a subset of these sites, however consistent with previous studies, global levels of H3K4me2, determined by Enzyme Linked Immunosorbent Assay (ELIZA), did not change significantly. Although it is known that LSD1 demethylates and stabilizes the maintenance DNA methyltransferase DNMT1 (Wang, Nat Genet 2009), the consequences of LSD1 loss on DNA methylation (5-methyl cytosine; 5-mC) have yet to be investigated. To gain a comprehensive understanding of how LSD1 regulates erythroid gene expression, changes in the level of 5-mC were assessed after knockdown or inhibition of LSD1. Global 5-mC levels, determined by ELIZA assay, were ∼30% lower in TCP treated samples than vehicle treated control (p<0.02) and western blot demonstrated a 3-fold decrease in DNMT1 protein in the TCP treated samples. Both methyl binding domain pull-down coupled with quantitative PCR and genome-wide bisulfite sequencing were utilized to assess changes in 5-mC levels in the differentially expressed genes. Loss of LSD1 was associated with significantly lower levels of 5-mC at several differentially expressed, erythroid-specific genes, such as bh1. Taken together, these data support the hypothesis that LSD1 influences both histone and DNA methylation at genes important for erythroid maturation. Disclosures: No relevant conflicts of interest to declare.


2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Siying He ◽  
Hui Sun ◽  
Yifang Huang ◽  
Shiqi Dong ◽  
Chen Qiao ◽  
...  

Purpose. MiRNAs have been widely analyzed in the occurrence and development of many diseases, including pterygium. This study aimed to identify the key genes and miRNAs in pterygium and to explore the underlying molecular mechanisms. Methods. MiRNA expression was initially extracted and pooled by published literature. Microarray data about differentially expressed genes was downloaded from Gene Expression Omnibus (GEO) database and analyzed with the R programming language. Functional and pathway enrichment analyses were performed using the database for Annotation, Visualization and Integrated Discovery (DAVID). The protein-protein interaction network was constructed with the STRING database. The associations between chemicals, differentially expressed miRNAs, and differentially expressed genes were predicted using the online resource. All the networks were constructed using Cytoscape. Results. We found that 35 miRNAs and 301 genes were significantly differentially expressed. Functional enrichment analysis showed that upregulated genes were significantly enriched in extracellular matrix (ECM) organization, while downregulated genes were mainly involved in cell death and apoptotic process. Finally, we concluded the chemical-gene affected network, miRNA-mRNA interacted networks, and significant pathway network. Conclusion. We identified lists of differentially expressed miRNAs and genes and their possible interaction in pterygium. The networks indicated that ECM breakdown and EMT might be two major pathophysiological mechanisms and showed the potential significance of PI3K-Akt signalling pathway. MiR-29b-3p and collagen family (COL4A1 and COL3A1) might be new treatment target in pterygium.


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