scholarly journals Identification of IL10RA by Weighted Correlation Network Analysis and in vitro Validation of Its Association With Prognosis of Metastatic Melanoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Si Cheng ◽  
Zhe Li ◽  
Wenhao Zhang ◽  
Zhiqiang Sun ◽  
Zhigang Fan ◽  
...  
Keyword(s):  
Network Analysis ◽  
Metastatic Melanoma ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Migration And Invasion

Skin cutaneous melanoma (SKCM) is the major cause of death for skin cancer patients, its high metastasis often leads to poor prognosis of patients with malignant melanoma. However, the molecular mechanisms underlying metastatic melanoma remain to be elucidated. In this study we aim to identify and validate prognostic biomarkers associated with metastatic melanoma. We first construct a co-expression network using large-scale public gene expression profiles from GEO, from which candidate genes are screened out using weighted gene co-expression network analysis (WGCNA). A total of eight modules are established via the average linkage hierarchical clustering, and 111 hub genes are identified from the clinically significant modules. Next, two other datasets from GEO and TCGA are used for further screening of biomarker genes related to prognosis of metastatic melanoma, and identified 11 key genes via survival analysis. We find that IL10RA has the highest correlation with clinically important modules among all identified biomarker genes. Further in vitro biochemical experiments, including CCK8 assays, wound-healing assays and transwell assays, have verified that IL10RA can significantly inhibit the proliferation, migration and invasion of melanoma cells. Furthermore, gene set enrichment analysis shows that PI3K-AKT signaling pathway is significantly enriched in metastatic melanoma with highly expressed IL10RA, indicating that IL10RA mediates in metastatic melanoma via PI3K-AKT pathway.

The Role of PAX2 in Breast Cancer: A Study Based on Bioinformatics Analysis and in Vitro Validation

2021 ◽  
Author(s):  
Shan Yang ◽  
Wei Gao ◽  
Haoqi Wang ◽  
Xi Zhang ◽  
Yunzhe Mi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cell Growth ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Migration And Invasion ◽  
Clinical Samples

Abstract Background: Breast cancer (BC) is the most frequently diagnosed cancer in women and is the second most common cancer among newly diagnosed cancers worldwide. Studies have shown that paired box 2 (PAX2) participates in the tumorigenesis of some cancer cells. However, the functions of PAX2 in the BC context are still unclear.Methods: Transcriptome expression profiles and clinicopathological information of BC were download from the TCGA database. Then the expression level and prognostic value in TCGA database were explored. Gene Set Enrichment Analysis (GSEA) and functional enrichment analysis were performed to investigate the functions and pathways of PAX2. Moreover, RT-qPCR was used to determine the expression of PAX2 in BC tissues, and the predictive value of PAX2 in clinical samples was assessed. CCK-8 assay was used to evaluate cell growth. The migration and invasion capacities of cells were assessed by wound healing assay and Transwell assay.Results: PAX2 was up-regulated in the TCGA-BC datasets. GSEA analysis suggested that PAX2 might be involved in the regulation of MAPK signaling pathways and so on. Moreover, PAX2 was overexpressed in BC tissues, and PAX2 expression was associated with menopause. PAX2 deficiency could inhibit the growth, migration, and invasion of BC cells.Conclusion: This study suggested that PAX2 was up-regulated in BC, which inhibited BC cell growth, migration, and invasion. Thus, PAX2 could be a potential therapeutic target for BC.

scholarly journals Identification of Crucial Genes and Infiltrating Immune Cells Underlying Sepsis-Induced Cardiomyopathy via Weighted Gene Co-Expression Network Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Juexing Li ◽  
Lei Zhou ◽  
Zhenhua Li ◽  
Shangneng Yang ◽  
Liangyue Tang ◽  
...  
Keyword(s):  
Network Analysis ◽  
Immune Cells ◽  
Plasma Cells ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Cardiac Metabolism ◽  
Gene Set Enrichment Analysis ◽  
Hub Genes ◽  
Research Studies

Sepsis-induced cardiomyopathy (SIC), with a possibly reversible cardiac dysfunction, is a potential complication of septic shock. Despite quite a few mechanisms including the inflammatory mediator, exosomes, and mitochondrial dysfunction, having been confirmed in the existing research studies we still find it obscure about the overall situation of gene co-expression that how they can affect the pathological process of SIC. Thus, we intended to find out the crucial hub genes, biological signaling pathways, and infiltration of immunocytes underlying SIC. It was weighted gene co-expression network analysis that worked as our major method on the ground of the gene expression profiles: hearts of those who died from sepsis were compared to hearts donated by non-failing humans which could not be transplanted for technical reasons (GSE79962). The top 25 percent of variant genes were abstracted to identify 10 co-expression modules. In these modules, brown and green modules showed the strongest negative and positive correlation with SIC, which were primarily enriched in the bioenergy metabolism, immunoreaction, and cell death. Next, nine genes (LRRC39, COQ10A, FSD2, PPP1R3A, TNFRSF11B, IL1RAP, DGKD, POR, and THBS1) including two downregulated and seven upregulated genes which were chosen as hub genes that meant the expressive level of which was higher than the counterparts in control groups. Then, the gene set enrichment analysis (GSEA) demonstrated a close relationship of hub genes to the cardiac metabolism and the necroptosis and apoptosis of cells in SIC. Concerning immune cells infiltration, a higher level of neutrophils and B cells native and a lower level of mast cells resting and plasma cells had been observed in patients with SIC. In general, nine candidate biomarkers were authenticated as a reliable signature for deeper exploration of basic and clinical research studies on SIC.

scholarly journals Transcriptome Research of Key Modules and Hub Genes Associated with Primary Myelofibrosis by Weighted Co-expression Network Analysis.

2020 ◽  
Author(s):  
Weihang Li ◽  
Bin Yuan ◽  
Shilei Zhang ◽  
Ziyi Ding ◽  
Yingjing Zhao ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Network Analysis ◽  
Early Stage ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Primary Myelofibrosis ◽  
Gene Set Enrichment Analysis ◽  
Hub Genes

Abstract Background: This study aimed to identify novel targets of diagnosis, therapy as well as prognosis for primary myelofibrosis (PMF).Methods: The gene expression profiles of GSE26049 was obtained from GEO dataset, weighted gene co-expression network analysis (WGCNA) was then performed to identify the most related modules with PMF. Subsequently, GO (Gene Ontology), KEGG (Kyoto Encyclopedia Genes and Genomes), GSEA (Gene Set Enrichment Analysis) and PPI (Protein-Protein Interaction) network were conducted to fully understand the detailed information of the green module.Results: Green module was strongly correlated with PMF disease after WGCNA analysis. 20 genes in green module were identified as hub genes responsible for the progression of PMF. Functional annotation and pathway analysis revealed that these hub genes were primarily enriched in erythrocyte differentiation, transcription factor binding, hemoglobin complex, transcription factor complex and cell cycle et al. Of which, EPB42, CALR, SLC4A1 and MPL had the most correlations with PMF.Conclusions: This study elucidated that genes EPB42, CALR, SLC4A1 and MPL were significantly more highly expressed in PMF samples than in normal samples. These four genes may be considered candidate prognostic biomarkers and potential therapeutic targets for early stage of PMF. Meanwhile, EPB42 and SLC4A1 were firstly found to be highly correlated with the progression of PMF.

scholarly journals Connectivity Map Analysis Indicates PI3K/Akt/mTOR Inhibitors as Potential Anti-Hypoxia Drugs in Neuroblastoma

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2809
Author(s):  
Paolo Uva ◽  
Maria Carla Bosco ◽  
Alessandra Eva ◽  
Massimo Conte ◽  
Alberto Garaventa ◽  
...  
Keyword(s):  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Drug Repurposing ◽  
Enrichment Analysis ◽  
Mtor Inhibitors ◽  
Gene Set Enrichment Analysis ◽  
Low Oxygen ◽  
Connectivity Map ◽  
Hypoxic Conditions ◽  
Connectivity Score

Neuroblastoma (NB) is one of the deadliest pediatric cancers, accounting for 15% of deaths in childhood. Hypoxia is a condition of low oxygen tension occurring in solid tumors and has an unfavorable prognostic factor for NB. In the present study, we aimed to identify novel promising drugs for NB treatment. Connectivity Map (CMap), an online resource for drug repurposing, was used to identify connections between hypoxia-modulated genes in NB tumors and compounds. Two sets of 34 and 21 genes up- and down-regulated between hypoxic and normoxic primary NB tumors, respectively, were analyzed with CMap. The analysis reported a significant negative connectivity score across nine cell lines for 19 compounds mainly belonging to the class of PI3K/Akt/mTOR inhibitors. The gene expression profiles of NB cells cultured under hypoxic conditions and treated with the mTORC complex inhibitor PP242, referred to as the Mohlin dataset, was used to validate the CMap findings. A heat map representation of hypoxia-modulated genes in the Mohlin dataset and the gene set enrichment analysis (GSEA) showed an opposite regulation of these genes in the set of NB cells treated with the mTORC inhibitor PP242. In conclusion, our analysis identified inhibitors of the PI3K/Akt/mTOR signaling pathway as novel candidate compounds to treat NB patients with hypoxic tumors and a poor prognosis.

scholarly journals Transcriptome profiling of peanut (Arachis hypogaea) gynophores in gravitropic response

2013 ◽  
Vol 40 (12) ◽  
pp. 1249 ◽  
Author(s):  
Hai-fen Li ◽  
Xiao-Ping Chen ◽  
Fang-he Zhu ◽  
Hai-Yan Liu ◽  
Yan-Bin Hong ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Arachis Hypogaea ◽  
Molecular Mechanisms ◽  
Carbon Fixation ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Pentose Phosphate ◽  
Differentially Expressed ◽  
Pcr Analysis

Peanut (Arachis hypogaea L.) produces flowers aerially, but the fruit develops underground. This process is mediated by the gynophore, which always grows vertically downwards. The genetic basis underlying gravitropic bending of gynophores is not well understood. To identify genes related to gynophore gravitropism, gene expression profiles of gynophores cultured in vitro with tip pointing upward (gravitropic stimulation sample) and downward (control) at both 6 and 12 h were compared through a high-density peanut microarray. After gravitropic stimulation, there were 174 differentially expressed genes, including 91 upregulated and 83 downregulated genes at 6 h, and 491 differentially expressed genes including 129 upregulated and 362 downregulated genes at 12 h. The differentially expressed genes identified were assigned to 24 functional categories. Twenty pathways including carbon fixation, aminoacyl-tRNA biosynthesis, pentose phosphate pathway, starch and sucrose metabolism were identified. The quantitative real-time PCR analysis was performed for validation of microarray results. Our study paves the way to better understand the molecular mechanisms underlying the peanut gynophore gravitropism.

Connecting gene expression subtypes of colorectal cancer (CRC) with cell lines and drug resistance.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. e14544-e14544
Author(s):  
Eva Budinska ◽  
Jenny Wilding ◽  
Vlad Calin Popovici ◽  
Edoardo Missiaglia ◽  
Arnaud Roth ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Line ◽  
Clinical Significance ◽  
Cell Lines ◽  
Drug Response ◽  
Drug Sensitivity ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis

e14544 Background: We identified CRC gene expression subtypes (ASCO 2012, #3511), which associate with established parameters of outcome as well as relevant biological motifs. We now substantiate their biological and potentially clinical significance by linking them with cell line data and drug sensitivity, primarily attempting to identify models for the poor prognosis subtypes Mesenchymal and CIMP-H like (characterized by EMT/stroma and immune-associated gene modules, respectively). Methods: We analyzed gene expression profiles of 35 publicly available cell lines with sensitivity data for 82 drug compounds, and our 94 cell lines with data on sensitivity for 7 compounds and colony morphology. As in vitro, stromal and immune-associated genes loose their relevance, we trained a new classifier based on genes expressed in both systems, which identifies the subtypes in both tissue and cell cultures. Cell line subtypes were validated by comparing their enrichment for molecular markers with that of our CRC subtypes. Drug sensitivity was assessed by linking original subtypes with 92 drug response signatures (MsigDB) via gene set enrichment analysis, and by screening drug sensitivity of cell line panels against our subtypes (Kruskal-Wallis test). Results: Of the cell lines 70% could be assigned to a subtype with a probability as high as 0.95. The cell line subtypes were significantly associated with their KRAS, BRAF and MSI status and corresponded to our CRC subtypes. Interestingly, the cell lines which in matrigel created a network of undifferentiated cells were assigned to the Mesenchymal subtype. Drug response studies revealed potential sensitivity of subtypes to multiple compounds, in addition to what could be predicted based on their mutational profile (e.g. sensitivity of the CIMP-H subtype to Dasatinib, p<0.01). Conclusions: Our data support the biological and potentially clinical significance of the CRC subtypes in their association with cell line models, including results of drug sensitivity analysis. Our subtypes might not only have prognostic value but might also be predictive for response to drugs. Subtyping cell lines further substantiates their significance as relevant model for functional studies.

Relationship Between San-Huang-Xie-Xin-Tang and Its Herbal Components on the Gene Expression Profiles in HepG2 Cells

2008 ◽  
Vol 36 (04) ◽  
pp. 783-797 ◽  
Author(s):  
Wen-Yu Cheng ◽  
Shih-Lu Wu ◽  
Chien-Yun Hsiang ◽  
Chia-Cheng Li ◽  
Tung-Yuan Lai ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepg2 Cells ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Major Effect ◽  
Gene Set Enrichment Analysis ◽  
P53 Signaling ◽  
The Relationship ◽  
Herbal Components

Traditional Chinese medicine (TCM) has been used for thousands of years. Most Chinese herbal formulae consist of several herbal components and have been used to treat various diseases. However, the mechanisms of most formulae and the relationship between formulae and their components remain to be elucidated. Here we analyzed the putative mechanism of San-Huang-Xie-Xin-Tang (SHXXT) and defined the relationship between SHXXT and its herbal components by microarray technique. HepG2 cells were treated with SHXXT or its components and the gene expression profiles were analyzed by DNA microarray. Gene set enrichment analysis indicated that SHXXT and its components displayed a unique anti-proliferation pattern via p53 signaling, p53 activated, and DNA damage signaling pathways in HepG2 cells. Network analysis showed that most genes were regulated by one molecule, p53. In addition, hierarchical clustering analysis showed that Rhizoma Coptis shared a similar gene expression profile with SHXXT. These findings may explain why Rhizoma Coptis is the principle herb that exerts the major effect in the herbal formula, SHXXT. Moreover, this is the first report to reveal the relationship between formulae and their herbal components in TCM by microarray and bioinformatics tools.

scholarly journals Stromal genes discriminate preinvasive from invasive disease, predict outcome, and highlight inflammatory pathways in digestive cancers

2010 ◽  
Vol 107 (5) ◽  
pp. 2177-2182 ◽  
Author(s):  
Amel Saadi ◽  
Nicholas B. Shannon ◽  
Pierre Lao-Sirieix ◽  
Maria O’Donovan ◽  
Elaine Walker ◽  
...  
Keyword(s):  
Expression Profiles ◽  
Enrichment Analysis ◽  
Invasive Disease ◽  
Gene Set Enrichment Analysis ◽  
In Vitro Assays ◽  
Stromal Compartment ◽  
Inflammatory Pathways ◽  
Digestive Cancers ◽  
Stromal Signature

The stromal compartment is increasingly recognized to play a role in cancer. However, its role in the transition from preinvasive to invasive disease is unknown. Most gastrointestinal tumors have clearly defined premalignant stages, and Barrett’s esophagus (BE) is an ideal research model. Supervised clustering of gene expression profiles from microdissected stroma identified a gene signature that could distinguish between BE metaplasia, dysplasia, and esophageal adenocarcinoma (EAC). EAC patients overexpressing any of the five genes (TMEPAI, JMY, TSP1, FAPα, and BCL6) identified from this stromal signature had a significantly poorer outcome. Gene ontology analysis identified a strong inflammatory component in BE disease progression, and key pathways included cytokine–cytokine receptor interactions and TGF-β. Increased protein levels of inflammatory-related genes significantly up-regulated in EAC compared with preinvasive stages were confirmed in the stroma of independent samples, and in vitro assays confirmed functional relevance of these genes. Gene set enrichment analysis of external datasets demonstrated that the stromal signature was also relevant in the preinvasive to invasive transition of the stomach, colon, and pancreas. These data implicate inflammatory pathways in the genesis of gastrointestinal tract cancers, which can affect prognosis.

scholarly journals Transcriptome profiling of human pluripotent stem cell-derived cerebellar organoids reveals faster commitment under dynamic conditions

2021 ◽  
Author(s):  
Teresa P. Silva ◽  
Rui Sousa-Luís ◽  
Tiago G. Fernandes ◽  
Evguenia P. Bekman ◽  
Carlos A. V. Rodrigues ◽  
...  
Keyword(s):  
Large Scale ◽  
Disease Modeling ◽  
Dynamic Condition ◽  
Expression Profiles ◽  
Continuous Process ◽  
Gene Expression Profiles ◽  
Brain Diseases ◽  
Scale Production ◽  
Large Scale Production

AbstractHuman induced pluripotent stem cells (iPSCs) have great potential for disease modeling. However, generating iPSC-derived models to study brain diseases remains a challenge. In particular, the ability to recapitulate cerebellar development in vitro is still limited. We presented a reproducible and scalable production of cerebellar organoids by using the novel Vertical-Wheel single-use bioreactors, in which functional cerebellar neurons were obtained. Here, we evaluate the global gene expression profiles by RNA sequencing (RNA-seq) across cerebellar differentiation, demonstrating a faster cerebellar commitment in this novel dynamic differentiation protocol. Furthermore, transcriptomic profiles suggest a significant enrichment of extracellular matrix (ECM) in dynamic-derived cerebellar organoids, which can better mimic the neural microenvironment and support a consistent neuronal network. Thus, an efficient generation of organoids with cerebellar identity was achieved for the first time in a continuous process using a dynamic system without the need of organoids encapsulation in ECM-based hydrogels, allowing the possibility of large-scale production and application in high-throughput processes. The presence of factors that favors angiogenesis onset was also detected in dynamic condition, which can enhance functional maturation of cerebellar organoids. We anticipate that large-scale production of cerebellar organoids may help developing models for drug screening, toxicological tests and studying pathological pathways involved in cerebellar degeneration.

scholarly journals DDX10 Promotes the Proliferation and Metastasis of Colorectal Cancer Cells via Splicing RPL35

2021 ◽  
Author(s):  
Xin Zhou ◽  
Zhihong Liu ◽  
Cuifeng Zhang ◽  
Manman Jiang ◽  
Yuxiao Jin ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Migration And Invasion ◽  
Ppi Network ◽  
Interacting Protein ◽  
Network Analyses ◽  
Potential Biomarker

Abstract Background: Colorectal cancer (CRC) has become the second deadliest cancer in the world and severely threatens human health. An increasing number of studies have focused on the role of the RNA helicase DEAD-box (DDX) family in CRC. However, the mechanism of DDX10 in CRC has not been elucidated.Methods: In our study, we analysed the expression data of CRC samples from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Subsequently, we performed cytological experiments and animal experiments to explore the role of DDX10 in CRC cells. Furthermore, we performed Gene Ontology (GO)/ Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and protein-protein interaction (PPI) network analyses. Finally, we predicted the interacting protein of DDX10 by LC-MS/MS and verified it by coimmunoprecipitation (Co-IP) and qPCR.Results: In the present study, we identified that DDX10 mRNA was extremely highly expressed in CRC tissues compared with normal colon tissues in the TCGA and GEO databases. The protein expression of DDX10 was measured by immunochemistry (IHC) in 17 CRC patients. The biological roles of DDX10 were explored via cell and molecular biology experiments in vitro and in vivo and cell cycle assays. We found that DDX10 knockdown markedly reduced CRC cell proliferation, migration and invasion. Then, we constructed a PPI network with the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). GO and KEGG enrichment analysis and gene set enrichment analysis (GSEA) showed that DDX10 was closely related to RNA splicing and E2F targets. Using LC-MS/MS and Co-IP assays, we discovered that RPL35 is the interacting protein of DDX10. In addition, we hypothesize that RPL35 is related to the E2F pathway and the immune response in CRC.Conclusions: In conclusion, provides a better understanding of the molecular mechanisms of DDX10 in CRC and provides a potential biomarker for the diagnosis and treatment of CRC.

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