scholarly journals Development of Biomarker Signatures Associated with Anoikis to Predict Prognosis in Endometrial Carcinoma Patients

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Shan Chen ◽  
Jiamin Gu ◽  
Qinfen Zhang ◽  
Yan Hu ◽  
Yu Ge
Keyword(s):  
Clinical Outcome ◽  
Endometrial Carcinoma ◽  
Molecular Mechanisms ◽  
Immune Status ◽  
Expression Patterns ◽  
Immune Dysfunction ◽  
Survival Outcome ◽  
Biological Pathways ◽  
Hub Genes ◽  
Regression Methods

Purpose. To generate a signature based on anoikis-related genes (ARGs) for endometrial carcinoma (EC) patients and elucidate the molecular mechanisms in EC. Methods. On the basis of TCGA-UCEC dataset, we identified specific anoikis-related genes (ARGs) in EC. Cox-relative regression methods were used to generate an anoikis-related signature (ARS). The possible biological pathways of ARS-related genes were analyzed by GSEA. The clinical potency and immune status of ARS were analyzed by CIBERSORT method, ssGSEA algorithm, Tumor Immune Dysfunction and Exclusion (TIDE) analysis. Moreover, the expression patterns of ARS genes were verified by HPA database. Results. Seven anoikis genes (CDKN2A, E2F1, ENDOG, EZH2, HMGA1, PLK1, and SLC2A1) were determined to develop a prognostic ARS. Both genes of ARS were closely bound up with the prognosis of EC patients. The ARS could accurately classify EC cases with different clinical outcome and mirror the specific immune status of EC. We observed that ARS-high patients could not benefit from immunotherapy. Finally, all the hub genes of ARS were proved to be upregulated in EC tissues by immunohistology. Conclusion. ARS can be used to stratify the risk and forecast the survival outcome of EC patients and provide prominent reference for individualized treatment in EC.

scholarly journals Identification of Hub Genes Correlated With Poor Prognosis for Patients With Uterine Corpus Endometrial Carcinoma by Integrated Bioinformatics Analysis and Experimental Validation

2021 ◽  
Vol 11 ◽  
Author(s):  
Yi Yuan ◽  
Zhengzheng Chen ◽  
Xushan Cai ◽  
Shengxiang He ◽  
Dong Li ◽  
...  
Keyword(s):  
Endometrial Carcinoma ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Female Genital Tract ◽  
Therapeutic Targets ◽  
Public Health Problem ◽  
The Cancer Genome Atlas ◽  
Major Public Health Problem ◽  
Hub Genes ◽  
Uterine Corpus

Uterine Corpus Endometrial Carcinoma (UCEC) is one of the most common malignancies of the female genital tract and there remains a major public health problem. Although significant progress has been made in explaining the progression of UCEC, it is still warranted that molecular mechanisms underlying the tumorigenesis of UCEC are to be elucidated. The aim of the current study was to investigate key modules and hub genes related to UCEC pathogenesis, and to explore potential biomarkers and therapeutic targets for UCEC. The RNA-seq dataset and corresponding clinical information for UCEC patients were obtained from the Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were screened between 23 paired UCEC tissues and adjacent non-cancerous tissues. Subsequently, the co-expression network of DEGs was determined via weighted gene co-expression network analysis (WGCNA). The Blue and Brown modules were identified to be significantly positively associated with neoplasm histologic grade. The highly connected genes of the two modules were then investigated as potential key factors related to tumor differentiation. Additionally, a protein-protein interaction (PPI) network for all genes in the two modules was constructed to obtain key modules and nodes. 10 genes were identified by both WGCNA and PPI analyses, and it was shown by Kaplan-Meier curve analysis that 6 out of the 10 genes were significantly negatively related to the 5-year overall survival (OS) in patients (AURKA, BUB1, CDCA8, DLGAP5, KIF2C, TPX2). Besides, according to the DEGs from the two modules, lncRNA-miRNA-mRNA and lncRNA-TF-mRNA networks were constructed to explore the molecular mechanism of UCEC-related lncRNAs. 3 lncRNAs were identified as being significantly negatively related to the 5-year OS (AC015849.16, DUXAP8 and DGCR5), with higher expression in UCEC tissues compared to non-tumor tissues. Finally, quantitative Real-time PCR was applied to validate the expression patterns of hub genes. Cell proliferation and colony formation assays, as well as cell cycle distribution and apoptosis analysis, were performed to test the effects of representative hub genes. Altogether, this study not only promotes our understanding of the molecular mechanisms for the pathogenesis of UCEC but also identifies several promising biomarkers in UCEC development, providing potential therapeutic targets for UCEC.

scholarly journals Integrative Transcriptomics Reveals Activation of Innate Immune Responses and Inhibition of Inflammation During Oral Immunotherapy for Egg Allergy in Children

2021 ◽  
Vol 12 ◽  
Author(s):  
Piia Karisola ◽  
Kati Palosuo ◽  
Victoria Hinkkanen ◽  
Lukas Wisgrill ◽  
Terhi Savinko ◽  
...  
Keyword(s):  
Gene Expression ◽  
Clinical Outcome ◽  
Immune Responses ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Oral Immunotherapy ◽  
Innate Immune ◽  
Egg Allergy ◽  
Innate Immune Responses ◽  
Open Label

We previously reported the results of a randomized, open-label trial of egg oral immunotherapy (OIT) in 50 children where 44% were desensitized and 46% were partially desensitized after 8 months of treatment. Here we focus on cell-mediated molecular mechanisms driving desensitization during egg OIT. We sought to determine whether changes in genome-wide gene expression in blood cells during egg OIT correlate with humoral responses and the clinical outcome. The blood cell transcriptome of 50 children receiving egg OIT was profiled using peripheral blood mononuclear cell (PBMC) samples obtained at baseline and after 3 and 8 months of OIT. We identified 467 differentially expressed genes (DEGs) after 3 or 8 months of egg OIT. At 8 months, 86% of the DEGs were downregulated and played a role in the signaling of TREM1, IL-6, and IL-17. In correlation analyses, Gal d 1–4-specific IgG4 antibodies associated positively with DEGs playing a role in pathogen recognition and antigen presentation and negatively with DEGs playing a role in the signaling of IL-10, IL-6, and IL-17. Desensitized and partially desensitized patients had differences in their antibody responses, and although most of the transcriptomic changes were shared, both groups had also specific patterns, which suggest slower changes in partially desensitized and activation of NK cells in the desensitized group. OIT for egg allergy in children inhibits inflammation and activates innate immune responses regardless of the clinical outcome at 8 months. Changes in gene expression patterns first appear as posttranslational protein modifications, followed by more sustained epigenetic gene regulatory functions related to successful desensitization.

scholarly journals Weighted gene co-expression network analysis to identify key modules and hub genes associated with paucigranulocytic asthma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Min Li ◽  
Wenye Zhu ◽  
Chu Wang ◽  
Yuanyuan Zheng ◽  
Shibo Sun ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Differentially Expressed Genes ◽  
Immune Status ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Hub Genes

Abstract Background Asthma is a heterogeneous disease that can be divided into four inflammatory phenotypes: eosinophilic asthma (EA), neutrophilic asthma (NA), mixed granulocytic asthma (MGA), and paucigranulocytic asthma (PGA). While research has mainly focused on EA and NA, the understanding of PGA is limited. In this study, we aimed to identify underlying mechanisms and hub genes of PGA. Methods Based on the dataset from Gene Expression Omnibus(GEO), weighted gene coexpression network analysis (WGCNA), differentially expressed genes (DEGs) analysis and protein–protein interaction (PPI) network analysis were conducted to construct a gene network and to identify key gene modules and hub genes. Functional enrichment analyses were performed to investigate the biological process, pathways and immune status of PGA. The hub genes were validated in a separate dataset. Results Compared to non-PGA, PGA had a different gene expression pattern, in which 449 genes were differentially expressed. One gene module significantly associated with PGA was identified. Intersection between the differentially expressed genes (DEGs) and the genes from the module that were most relevant to PGA were mainly enriched in inflammation and immune response regulation. The single sample Gene Set Enrichment Analysis (ssGSEA) suggested a decreased immune infiltration and function in PGA. Finally six hub genes of PGA were identified, including ADCY2, CXCL1, FPRL1, GPR109B, GPR109A and ADCY3, which were validated in a separate dataset of GSE137268. Conclusions Our study characterized distinct gene expression patterns, biological processes and immune status of PGA and identified hub genes, which may improve the understanding of underlying mechanism and provide potential therapeutic targets for PGA.

scholarly journals Differential Activation of ERK Signaling in HPV-Related Oropharyngeal Squamous Cell Carcinoma

Cancers ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 584 ◽  
Author(s):  
Chao Rong ◽  
Marie Muller ◽  
Christa Flechtenmacher ◽  
Dana Holzinger ◽  
Gerhard Dyckhoff ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Clinical Outcome ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Oropharyngeal Squamous Cell Carcinoma ◽  
Erk Signaling ◽  
Primary Tumors ◽  
The Impact

Human papillomavirus (HPV)-related oropharyngeal squamous cell carcinoma (OPSCC) forms a distinct tumor entity with better survival clinical outcome. Numerous underlying molecular mechanisms have been postulated for differences in treatment response, but the impact of MEK/ERK signaling, a main driver of carcinogenesis in various cancers including OPSCC and key player mediating therapy resistance remains elusive. In a retrospective experimental cohort study, primary tumor samples from OPSCC patients (n = 124) were available on tissue microarrays (TMAs) and expression levels of phosphorylated ERK1/2 (pERK1/2) were detected by immunohistochemical staining. Correlations of pERK1/2 expression patterns with clinicopathological features and clinical outcome were evaluated by statistical analysis. A low pERK1/2 expression was strongly associated with HPV-related OPSCC, while primary tumors with high pERK1/2 staining showed a distinctly worse survival outcome and were associated with higher cellular differentiation. Co-activation of both ERK1/2 and AKT was a common event and was associated with unfavorable prognosis in our cohort. However, the combinatorial analysis of pAKT (Ser473) and pERK1/2 did not strengthen the predictive power of pERK1/2, suggesting that pERK1/2 plays a more significant function in OPSCC. In summary, our data provide a compelling experimental and statistical evidence that low levels of tumor cell intrinsic ERK1/2 activation contribute at least in part to the favorable outcome of HPV-related OPSCC. On the other hand, presented findings indicate that non-HPV-related OPSCC with elevated ERK phosphorylation are at high risk for treatment failure and might benefit from targeted therapy of MEK/ERK signaling.

scholarly journals Genetics Responses to Hypoxia and Reoxygenation Stress in Larimichthys crocea Revealed via Transcriptome Analysis and Weighted Gene Co-Expression Network

Animals ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 3021
Author(s):  
Yibo Zhang ◽  
Jie Ding ◽  
Cheng Liu ◽  
Shengyu Luo ◽  
Xinming Gao ◽  
...  
Keyword(s):  
Gene Network ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Hypoxia Tolerance ◽  
Large Yellow Croaker ◽  
Larimichthys Crocea ◽  
Hub Genes ◽  
Gsk 3Β ◽  
Different Tissues

The large yellow croaker (Larimichthys crocea) is an important marine economic fish in China; however, its intolerance to hypoxia causes widespread mortality. To understand the molecular mechanisms underlying hypoxia tolerance in L. crocea, the transcriptome gene expression profiling of three different tissues (blood, gills, and liver) of L. crocea exposed to hypoxia and reoxygenation stress were performed. In parallel, the gene relationships were investigated based on weighted gene co-expression network analysis (WGCNA). Accordingly, the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis showed that several pathways (e.g., energy metabolism, signal transduction, oxygen transport, and osmotic regulation) may be involved in the response of L. crocea to hypoxia and reoxygenation stress. In addition, also, four key modules (darkorange, magenta, saddlebrown, and darkolivegreen) that were highly relevant to the samples were identified by WGCNA. Furthermore, some hub genes within the association module, including RPS16, EDRF1, KCNK5, SNAT2, PFKL, GSK-3β, and PIK3CD, were found. This is the first study to report the co-expression patterns of a gene network after hypoxia stress in marine fish. The results provide new clues for further research on the molecular mechanisms underlying hypoxia tolerance in L. crocea.

scholarly journals Hub microRNAs and genes in the development of atrial fibrillation identified by weighted gene co-expression network analysis

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Qiang Qu ◽  
Jin-Yu Sun ◽  
Zhen-Ye Zhang ◽  
Yue Su ◽  
Shan-Shan Li ◽  
...  
Keyword(s):  
Network Analysis ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Expression Patterns ◽  
Mirna Gene ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Interaction Patterns ◽  
Hub Genes ◽  
Key Genes

AbstractCo-expression network may contribute to better understanding molecular interaction patterns underlying cellular processes. To explore microRNAs (miRNAs) expression patterns correlated with AF, we performed weighted gene co-expression network analysis (WGCNA) based on the dataset GSE28954. Thereafter, we predicted target genes using experimentally verified databases (ENOCRI, miRTarBase, and Tarbase), and overlapped genes with differentially expressed genes (DEGs) from GSE79768 were identified as key genes. Integrated analysis of association between hub miRNAs and key genes was conducted to screen hub genes. In general, we identified 3 differentially expressed miRNAs (DEMs) and 320 DEGs, predominantly enriched in inflammation-related functional items. Two significant modules (red and blue) and hub miRNAs (hsa-miR-146b-5p and hsa-miR-378a-5p), which highly correlated with AF-related phenotype, were detected by WGCNA. By overlapping the DEGs and predicted target genes, 38 genes were screened out. Finally, 9 genes (i.e. ATP13A3, BMP2, CXCL1, GABPA, LIF, MAP3K8, NPY1R, S100A12, SLC16A2) located at the core region in the miRNA-gene interaction network were identified as hub genes. In conclusion, our study identified 2 hub miRNAs and 9 hub genes, which may improve the understanding of molecular mechanisms and help to reveal potential therapeutic targets against AF.

scholarly journals Transcriptomic Analysis Exploring the Molecular Mechanisms of Hanchuan Zupa Granules in Alleviating Asthma in Rat

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Hailong Yin ◽  
Yanbo Fan ◽  
Dandan Mu ◽  
Fei Song ◽  
Fang Tian ◽  
...  
Keyword(s):  
Protein Expression ◽  
Wall Thickness ◽  
Molecular Mechanisms ◽  
Group Discussion ◽  
Expression Patterns ◽  
Muscle Layer ◽  
Sprague Dawley ◽  
Hub Genes ◽  
Activated T Cells ◽  
Asthma Model

Context. Hanchuan Zupa granule (HCZP), as a Chinese traditional medicine, is used to treat asthma. Objective. To investigate the molecular mechanisms of HCZP treatment of asthma. Materials and Methods. Thirty Sprague Dawley (SD) rats were divided into normal, asthma, and HCZP groups (n = 10). The asthma model was sensitized by 1 mg ovalbumin (OVA)/aluminum hydroxide Al(OH)3mixture and then challenged with 1% aerosolized OVA for four weeks. Rats in the HCZP group received 10.08 g/kg/d HCZP for four weeks during OVA challenge. Then, lung tissues of rats in each group were collected for RNA sequencing. Moreover, the expression level of some core genes was detected by using western blotting and immunohistochemistry. Results. Inflammatory cell infiltration and pathological damage of the lungs improved in the HCZP group. Compared with the asthma group (0.049 ± 0.002 mm2/mm; 0.036 ± 0.006 mm2/mm; and 0.014 ± 0.001 mm2/mm), total wall thickness (0.042 ± 0.001 mm2/mm), inner wall thickness (0.013 ± 0.001 mm2/mm), and smooth muscle layer thickness (0.012 ± 0.001 mm2/mm) significantly decreased in the HCZP group. Bioinformatics analysis showed that hub genes such as bradykinin receptor B2 (Bdkrb2) and CD4 molecule (Cd4) had different expression patterns between model and HCZP groups. Two transcription factors, forkhead box Q1 (Foxq1) and nuclear factor of activated T cells 2 (Nfatc2), served important regulatory roles in asthma. Compared with the model group, Bdkrb2 protein expression increased and Nfatc2 protein expression decreased in the HCZP group. Discussion and Conclusion. HCZP could alleviate asthma via regulating the expression of several hub genes, which might serve as therapeutic targets for asthma. However, the mechanism of these genes will be studied in the future.

Screening and identification of key biomarkers and related transcription factors in ovarian cancer by integrated bioinformatics analysis

2020 ◽  
Author(s):  
Wenqiong Qin ◽  
Qiang Yuan ◽  
Yi Liu ◽  
Ying Zeng ◽  
Dandan Ke ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Molecular Mechanisms ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Transcriptional Factor ◽  
Ppi Network ◽  
Hub Genes

Abstract Background Ovarian tumors are the most malignant tumors of all gynecological tumors, and although multiple efforts have been made to elucidate the pathogenesis, the molecular mechanisms of ovarian cancer remain unclear. Methods In this study, we used bioinformatics to identify genes involved in the carcinogenesis and progression of ovarian cancer. Three microarray datasets (GSE14407, GSE29450, and GSE54388) were downloaded from Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) were identified. For a more in-depth understanding of the DEGs, functional and pathway enrichment analyses were performed and a protein-protein interaction (PPI) network was constructed. The associated transcriptional factor (TFs) regulation network of the DEGs was also constructed. Kaplan Meier-plotter, Gene Expression Profiling Interactive Analysis (GEPIA), the Human Protein Atlas (HPA) database and the Oncomine database were implemented to validated hub genes. Results A total of 514 DEGs were detected after the analysis of the three gene expression profiles, including 171 upregulated and 343 downregulated genes. Nine hub genes ( CCNB1, CDK1, BUB1, CDC20, CCNA2, BUB1B, AURKA, RRM2, TTK) were obtained from the PPI network. Survival analysis showed that high expression levels of seven hub genes ( CCNB1, BUB1, BUB1B, CCNA2, AURKA, CDK1, and RRM2) were associated with worse overall survival (OS). All of seven hub genes were discovered highly expressed in ovarian cancer samples compared to normal ovary samples in GEPIA. Immunostaining results from the HPA database suggested that the expressions of CCNB1, CCNA2, AURKA, and CDK1 proteins were increased in ovarian cancer tissues, and Oncomine analysis indicated that the expression patterns of BUB1B, CCNA2, AURKA, CCNB1, CDK1, and BUB1 have associated with patient clinicopathological information. From the gene-transcriptional factor network, key transcriptional factors, such as POLR2A, ZBTB11, KLF9, and ELF1, were identified with close interactions with these hub genes. Conclusion We identified six significant DEGs with poor prognosis in ovarian cancer, which could be of potential biomarkers for ovarian cancer patients.

scholarly journals Rewired Pathways and Disrupted Pathway Crosstalk in Schizophrenia Transcriptomes by Multiple Differential Coexpression Methods

Genes ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 665
Author(s):  
Hui Yu ◽  
Yan Guo ◽  
Jingchun Chen ◽  
Xiangning Chen ◽  
Peilin Jia ◽  
...  
Keyword(s):  
Gene Expression ◽  
Focal Adhesion ◽  
Biological Pathways ◽  
Postmortem Brain ◽  
Rna Seq ◽  
Hub Genes ◽  
Differential Coexpression ◽  
Pathway Crosstalk ◽  
Microarray Datasets ◽  
Transcriptomic Studies

Transcriptomic studies of mental disorders using the human brain tissues have been limited, and gene expression signatures in schizophrenia (SCZ) remain elusive. In this study, we applied three differential co-expression methods to analyze five transcriptomic datasets (three RNA-Seq and two microarray datasets) derived from SCZ and matched normal postmortem brain samples. We aimed to uncover biological pathways where internal correlation structure was rewired or inter-coordination was disrupted in SCZ. In total, we identified 60 rewired pathways, many of which were related to neurotransmitter, synapse, immune, and cell adhesion. We found the hub genes, which were on the center of rewired pathways, were highly mutually consistent among the five datasets. The combinatory list of 92 hub genes was generally multi-functional, suggesting their complex and dynamic roles in SCZ pathophysiology. In our constructed pathway crosstalk network, we found “Clostridium neurotoxicity” and “signaling events mediated by focal adhesion kinase” had the highest interactions. We further identified disconnected gene links underlying the disrupted pathway crosstalk. Among them, four gene pairs (PAK1:SYT1, PAK1:RFC5, DCTN1:STX1A, and GRIA1:MAP2K4) were normally correlated in universal contexts. In summary, we systematically identified rewired pathways, disrupted pathway crosstalk circuits, and critical genes and gene links in schizophrenia transcriptomes.

scholarly journals Screen Key Genes Associated with Distraction-Induced Osteogenesis of Stem Cells Using Bioinformatics Methods

2021 ◽  
Vol 22 (12) ◽  
pp. 6505
Author(s):  
Jishizhan Chen ◽  
Jia Hua ◽  
Wenhui Song
Keyword(s):  
Stem Cells ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Negative Control ◽  
Gene Set Enrichment Analysis ◽  
Venn Diagram ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Two Samples ◽  
Key Genes

Applying mesenchymal stem cells (MSCs), together with the distraction osteogenesis (DO) process, displayed enhanced bone quality and shorter treatment periods. The DO guides the differentiation of MSCs by providing mechanical clues. However, the underlying key genes and pathways are largely unknown. The aim of this study was to screen and identify hub genes involved in distraction-induced osteogenesis of MSCs and potential molecular mechanisms. Material and Methods: The datasets were downloaded from the ArrayExpress database. Three samples of negative control and two samples subjected to 5% cyclic sinusoidal distraction at 0.25 Hz for 6 h were selected for screening differentially expressed genes (DEGs) and then analysed via bioinformatics methods. The Gene Ontology (GO) terms and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment were investigated. The protein–protein interaction (PPI) network was visualised through the Cytoscape software. Gene set enrichment analysis (GSEA) was conducted to verify the enrichment of a self-defined osteogenic gene sets collection and identify osteogenic hub genes. Results: Three hub genes (IL6, MMP2, and EP300) that were highly associated with distraction-induced osteogenesis of MSCs were identified via the Venn diagram. These hub genes could provide a new understanding of distraction-induced osteogenic differentiation of MSCs and serve as potential gene targets for optimising DO via targeted therapies.

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