scholarly journals Transcriptomic Analyses Reveal Gene Expression Profiles and Networks in Nasopharyngeal Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yaqi Zhou ◽  
Weiqiang Yang ◽  
Xueshuang Mei ◽  
Hongyi Hu
Keyword(s):  
Gene Expression ◽  
Nasopharyngeal Carcinoma ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Interaction Network ◽  
Principal Component ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Clinical Samples ◽  
Tissue Samples

Background. Nasopharyngeal carcinoma (NPC) is a rare but highly aggressive tumor that is predominantly encountered in Southeast Asia and China in particular. Aside from radiotherapy, no effective therapy that specifically treats NPC is available, including targeted drugs. Finding more sensitive biomarkers is important for new drug discovery and for evaluating patient prognosis. Methods. mRNA expression datasets from the Gene Expression Omnibus database (GSE53819, GSE64634, and GSE40290) were selected. After all samples in each dataset were subjected to quality control using principal component analyses, the qualified samples were used for additional analyses. The genes that were significantly expressed in each dataset were intersected to identify the most significant of these. Gene functional enrichment analyses were performed on these genes, using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes analyses. The protein–protein interaction network of selected genes was analyzed using the Search Tool for the Retrieval of Interacting Genes database. Significantly, differentially expressed genes were further verified with two RNA-seq datasets (GSE68799 and GSE12452), as well as in clinical samples. Results. In all, 34 (8 upregulated genes and 26 downregulated) genes were identified as significantly differentially expressed. The immune response and the regulation of cell proliferation were the most enriched biological GO terms. Using reverse transcription quantitative real-time PCR (RT-qPCR), the genes MMP1, AQP9, and TNFAIP6 were detected to be upregulated, and FAM3D, CR2, and LTF were downregulated in NPC tissue samples. Conclusion. This study provides information on the genes that may be involved in the development of NPC and suggests possible druggable targets and biomarkers for diagnosing and evaluating the prognosis of NPC.

Differential gene expression profiling in whole blood during acute systemic inflammation in lipopolysaccharide-treated rats

2005 ◽  
Vol 21 (1) ◽  
pp. 92-104 ◽  
Author(s):  
Rick D. Fannin ◽  
J. Todd Auman ◽  
Maribel E. Bruno ◽  
Stella O. Sieber ◽  
Sandra M. Ward ◽  
...  
Keyword(s):  
Gene Expression ◽  
Whole Blood ◽  
Acute Inflammation ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Principal Component ◽  
Differentially Expressed ◽  
Sprague Dawley ◽  
Environmental Health Sciences ◽  
Adaptive Shifts

Microarrays have been used to evaluate the expression of thousands of genes in various tissues. However, few studies have investigated the change in gene expression profiles in one of the most easily accessible tissues, whole blood. We utilized an acute inflammation model to investigate the possibility of using a cDNA microarray to measure the gene expression profile in the cells of whole blood. Blood was collected from male Sprague-Dawley rats at 2 and 6 h after treatment with 5 mg/kg (ip) LPS. Hematology showed marked neutrophilia accompanied by lymphopenia at both time points. TNF-α and IL-6 levels were markedly elevated at 2 h, indicating acute inflammation, but by 6 h the levels had declined. Total RNA was isolated from whole blood and hybridized to the National Institute of Environmental Health Sciences Rat Chip v.3.0. LPS treatment caused 226 and 180 genes to be differentially expressed at 2 and 6 h, respectively. Many of the differentially expressed genes are involved in inflammation and the acute phase response, but differential expression was also noted in genes involved in the cytoskeleton, cell adhesion, oxidative respiration, and transcription. Real-time RT-PCR confirmed the differential regulation of a representative subset of genes. Principal component analysis of gene expression discriminated between the acute inflammatory response apparent at 2 h and the observed recovery underway at 6 h. These studies indicate that, in whole blood, changes in gene expression profiles can be detected that are reflective of inflammation, despite the adaptive shifts in leukocyte populations that accompany such inflammatory processes.

scholarly journals DIFFERENT MORPHOLOGICAL STRUCTURES OF BREAST TUMORS DEMONSTRATE INDIVIDUAL DRUG RESISTANCE GENE EXPRESSION PROFILES

2018 ◽  
Vol 40 (3) ◽  
pp. 228-234 ◽  
Author(s):  
T S Gerashchenko ◽  
E V Denisov ◽  
N M Novikov ◽  
L A Tashireva ◽  
E V Kaigorodova ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Drug Resistance ◽  
Anticancer Drugs ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Drug Uptake ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Luminal Breast Cancer

Aim: To identify gene expression profiles involved in drug resistance of different morphological structures (tubular, alveolar, solid, trabecular, and discrete) presented in breast cancer. Material and Methods: Ten patients with luminal breast cancer have been included. A laser microdissection-assisted microarrays and qRT-PCR were used to perform whole-transcriptome profiling of different morphological structures, to select differentially expressed drug response genes, and to validate their expression. Results: We found 27 differentially expressed genes (p < 0.05) encoding drug uptake (SLC1A3, SLC23A2, etc.) and efflux (ABCC1, ABCG1, etc.) transporters, drug targets (TOP2A, TYMS, and Tubb3), and proteins that are involved in drug detoxification (NAT1 and ALDH1B1), cell cycle progression (CCND1, AKT1, etc.), apoptosis (CASP3, TXN2, etc.), and DNA repair (BRCA1 and USP11). Each type of structures showed an individual gene expression profile related to resistance and sensitivity to anticancer drugs. However, most of the genes (19/27; p < 0.05) were expressed in alveolar structures. Functional enrichment analysis showed that drug resistance is significantly associated with alveolar structures. Other structures demonstrated the similar number (10–13 out of 27) of expressed genes; however, the spectrum of resistance and sensitivity to different anticancer drugs varied. Conclusion: Different morphological structures of breast cancer show individual expression of drug resistance genes.

scholarly journals Identification of microRNAs and their target genes in the placenta as biomarkers of inflammation

2020 ◽  
Vol 47 (1) ◽  
pp. 42-53 ◽  
Author(s):  
Hee Yeon Jang ◽  
Seung Mook Lim ◽  
Hyun Jung Lee ◽  
Joon-Seok Hong ◽  
Gi Jin Kim
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Differentially Expressed ◽  
Western Blots ◽  
Tissue Samples ◽  
Disease States ◽  
Polymerase Chain ◽  
Lps Treatment

Objective: Recently, microRNA (miRNA) has been identified both as a powerful regulator involved in various biological processes through the regulation of numerous genes and as an effective biomarker for the prediction and diagnosis of various disease states. The objective of this study was to identify and validate miRNAs and their target genes involved in inflammation in placental tissue.Methods: Microarrays were utilized to obtain miRNA and gene expression profiles from placentas with or without inflammation obtained from nine normal pregnant women and 10 preterm labor patients. Quantitative real-time polymerase chain reaction and Western blots were performed to validate the miRNAs and differentially-expressed genes in the placentas with inflammation. Correlations between miRNA and target gene expression were confirmed by luciferase assays in HTR-8/SVneo cells.Results: We identified and validated miRNAs and their target genes that were differentially expressed in placentas with inflammation. We also demonstrated that several miRNAs (miR-371a-5p, miR-3065-3p, miR-519b-3p, and miR-373-3p) directly targeted their target genes (<i>LEF1, LOX, ITGB4</i>, and <i>CD44</i>). However, some miRNAs and their direct target genes showed no correlation in tissue samples. Interestingly, miR-373-3p and miR-3065-3p were markedly regulated by lipopolysaccharide (LPS) treatment, although the expression of their direct targets <i>CD44</i> and <i>LOX</i> was not altered by LPS treatment.Conclusion: These results provide candidate miRNAs and their target genes that could be used as placental biomarkers of inflammation. These candidates may be useful for further miRNA-based biomarker development.

Transcriptome analysis reveals key signature genes involved in the oncogenesis of lung cancer

2020 ◽  
Vol 29 (4) ◽  
pp. 475-482
Author(s):  
Fanlu Meng ◽  
Linlin Zhang ◽  
Yaoyao Ren ◽  
Qing Ma
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Gene Expression Profiles ◽  
Interaction Network ◽  
Functional Enrichment ◽  
Sequencing Platform ◽  
Signature Genes ◽  
Regulated Expression

Previous studies have suggested potential signature genes for lung cancer, however, due to factors such as sequencing platform, control, data selection and filtration conditions, the results of lung cancer-related gene expression analysis are quite different. Here, we performed a meta-analysis on existing lung cancer gene expression results to identify Meta-signature genes without noise. In this study, functional enrichment, protein-protein interaction network, the DAVID, String, TfactS, and transcription factor binding were performed based on the gene expression profiles of lung adenocarcinoma and non-small cell lung cancer deposited in the GEO database. As a result, a total of 574 differentially expressed genes (DEGs) affecting the pathogenesis of lung cancer were identified (207 up-regulated expression and 367 down-regulated expression in lung cancer tissues). A total of 5,093 interactions existed among the 507 (88.3%) proteins, and 10 Meta-signatures were identified: AURKA, CCNB1, KIF11, CCNA2, TOP2A, CENPF, KIF2C, TPX2, HMMR, and MAD2L1. The potential biological functions of Meta-signature DEGs were revealed. In summary, this study identified key genes involved in the process of lung cancer. Our results would help the developing of novel biomarkers for lung cancer.

scholarly journals Comprehensive Comparison of Amnion Stromal Cells and Chorion Stromal Cells by RNA-Seq

2021 ◽  
Vol 22 (4) ◽  
pp. 1901
Author(s):  
Brielle Jones ◽  
Chaoyang Li ◽  
Min Sung Park ◽  
Anne Lerch ◽  
Vimal Jacob ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stromal Cells ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Principal Component ◽  
Differentially Expressed ◽  
Inflammatory Factor ◽  
Next Generation Sequencing Technology ◽  
Angiogenic Potential ◽  
Anti Inflammatory

Mesenchymal stromal cells derived from the fetal placenta, composed of an amnion membrane, chorion membrane, and umbilical cord, have emerged as promising sources for regenerative medicine. Here, we used next-generation sequencing technology to comprehensively compare amniotic stromal cells (ASCs) with chorionic stromal cells (CSCs) at the molecular and signaling levels. Principal component analysis showed a clear dichotomy of gene expression profiles between ASCs and CSCs. Unsupervised hierarchical clustering confirmed that the biological repeats of ASCs and CSCs were able to respectively group together. Supervised analysis identified differentially expressed genes, such as LMO3, HOXA11, and HOXA13, and differentially expressed isoforms, such as CXCL6 and HGF. Gene Ontology (GO) analysis showed that the GO terms of the extracellular matrix, angiogenesis, and cell adhesion were significantly enriched in CSCs. We further explored the factors associated with inflammation and angiogenesis using a multiplex assay. In comparison with ASCs, CSCs secreted higher levels of angiogenic factors, including angiogenin, VEGFA, HGF, and bFGF. The results of a tube formation assay proved that CSCs exhibited a strong angiogenic function. However, ASCs secreted two-fold more of an anti-inflammatory factor, TSG-6, than CSCs. In conclusion, our study demonstrated the differential gene expression patterns between ASCs and CSCs. CSCs have superior angiogenic potential, whereas ASCs exhibit increased anti-inflammatory properties.

4 Molecularly guided multiplexed digital spatial analysis reveals differential gene expression profiles in the WNT-β-catenin pathway between melanoma and prostate tumors

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A4-A4
Author(s):  
Anushka Dikshit ◽  
Dan Zollinger ◽  
Karen Nguyen ◽  
Jill McKay-Fleisch ◽  
Kit Fuhrman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Single Molecule ◽  
Spatial Information ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Fluorescence Assay ◽  
Differentially Expressed ◽  
Tumor Type ◽  
Prostate Tumors

BackgroundThe canonical WNT-β-catenin signaling pathway is vital for development and tissue homeostasis but becomes strongly tumorigenic when dysregulated. and alter the transcriptional signature of a cell to promote malignant transformation. However, thorough characterization of these transcriptomic signatures has been challenging because traditional methods lack either spatial information, multiplexing, or sensitivity/specificity. To overcome these challenges, we developed a novel workflow combining the single molecule and single cell visualization capabilities of the RNAscope in situ hybridization (ISH) assay with the highly multiplexed spatial profiling capabilities of the GeoMx™ Digital Spatial Profiler (DSP) RNA assays. Using these methods, we sought to spatially profile and compare gene expression signatures of tumor niches with high and low CTNNB1 expression.MethodsAfter screening 120 tumor cores from multiple tumors for CTNNB1 expression by the RNAscope assay, we identified melanoma as the tumor type with the highest CTNNB1 expression while prostate tumors had the lowest expression. Using the RNAscope Multiplex Fluorescence assay we selected regions of high CTNNB1 expression within 3 melanoma tumors as well as regions with low CTNNB1 expression within 3 prostate tumors. These selected regions of interest (ROIs) were then transcriptionally profiled using the GeoMx DSP RNA assay for a set of 78 genes relevant in immuno-oncology. Target genes that were differentially expressed were further visualized and spatially assessed using the RNAscope Multiplex Fluorescence assay to confirm GeoMx DSP data with single cell resolution.ResultsThe GeoMx DSP analysis comparing the melanoma and prostate tumors revealed that they had significantly different gene expression profiles and many of these genes showed concordance with CTNNB1 expression. Furthermore, immunoregulatory targets such as ICOSLG, CTLA4, PDCD1 and ARG1, also demonstrated significant correlation with CTNNB1 expression. On validating selected targets using the RNAscope assay, we could distinctly visualize that they were not only highly expressed in melanoma compared to the prostate tumor, but their expression levels changed proportionally to that of CTNNB1 within the same tumors suggesting that these differentially expressed genes may be regulated by the WNT-β-catenin pathway.ConclusionsIn summary, by combining the RNAscope ISH assay and the GeoMx DSP RNA assay into one joint workflow we transcriptionally profiled regions of high and low CTNNB1 expression within melanoma and prostate tumors and identified genes potentially regulated by the WNT- β-catenin pathway. This novel workflow can be fully automated and is well suited for interrogating the tumor and stroma and their interactions.GeoMx Assays are for RESEARCH ONLY, not for diagnostics.

scholarly journals LncGSEA: a versatile tool to infer lncRNA associated pathways from large-scale cancer transcriptome sequencing data

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yanan Ren ◽  
Ting-You Wang ◽  
Leah C. Anderton ◽  
Qi Cao ◽  
Rendong Yang
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Clinical Samples ◽  
Sequencing Data ◽  
Multiple Cancer ◽  
Regulatory Pathways ◽  
Cancer Transcriptome ◽  
Versatile Tool

Abstract Background Long non-coding RNAs (lncRNAs) are a growing focus in cancer research. Deciphering pathways influenced by lncRNAs is important to understand their role in cancer. Although knock-down or overexpression of lncRNAs followed by gene expression profiling in cancer cell lines are established approaches to address this problem, these experimental data are not available for a majority of the annotated lncRNAs. Results As a surrogate, we present lncGSEA, a convenient tool to predict the lncRNA associated pathways through Gene Set Enrichment Analysis of gene expression profiles from large-scale cancer patient samples. We demonstrate that lncGSEA is able to recapitulate lncRNA associated pathways supported by literature and experimental validations in multiple cancer types. Conclusions LncGSEA allows researchers to infer lncRNA regulatory pathways directly from clinical samples in oncology. LncGSEA is written in R, and is freely accessible at https://github.com/ylab-hi/lncGSEA.

scholarly journals Integrative transcriptome data mining for identification of core lncRNAs in breast cancer

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7821 ◽  
Author(s):  
Xiaoming Zhang ◽  
Jing Zhuang ◽  
Lijuan Liu ◽  
Zhengguo He ◽  
Cun Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Prognostic Value ◽  
Early Stage ◽  
Expression Profiles ◽  
Diagnostic Value ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Data Set

Background Cumulative evidence suggests that long non-coding RNAs (lncRNAs) play an important role in tumorigenesis. This study aims to identify lncRNAs that can serve as new biomarkers for breast cancer diagnosis or screening. Methods First, the linear fitting method was used to identify differentially expressed genes from the breast cancer RNA expression profiles in The Cancer Genome Atlas (TCGA). Next, the diagnostic value of all differentially expressed lncRNAs was evaluated using a receiver operating characteristic (ROC) curve. Then, the top ten lncRNAs with the highest diagnostic value were selected as core genes for clinical characteristics and prognosis analysis. Furthermore, core lncRNA-mRNA co-expression networks based on weighted gene co-expression network analysis (WGCNA) were constructed, and functional enrichment analysis was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). The differential expression level and diagnostic value of core lncRNAs were further evaluated by using independent data set from Gene Expression Omnibus (GEO). Finally, the expression status and prognostic value of core lncRNAs in various tumors were analyzed based on Gene Expression Profiling Interactive Analysis (GEPIA). Results Seven core lncRNAs (LINC00478, PGM5-AS1, AL035610.1, MIR143HG, RP11-175K6.1, AC005550.4, and MIR497HG) have good single-factor diagnostic value for breast cancer. AC093850.2 has a prognostic value for breast cancer. AC005550.4 and MIR497HG can better distinguish breast cancer patients in early-stage from the advanced-stage. Low expression of MAGI2-AS3, LINC00478, AL035610.1, MIR143HG, and MIR145 may be associated with lymph node metastasis in breast cancer. Conclusion Our study provides candidate biomarkers for the diagnosis and prognosis of breast cancer, as well as a bioinformatics basis for the further elucidation of the molecular pathological mechanism of breast cancer.

scholarly journals A Study of Gene Expression Changes in Human Spinal and Oculomotor Neurons; Identifying Potential Links to Sporadic ALS

Genes ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 448
Author(s):  
Aayan N. Patel ◽  
Dennis Mathew
Keyword(s):  
Gene Expression ◽  
Disease Progression ◽  
Motor Neurons ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Tissue Samples ◽  
Disease Symptoms ◽  
Sporadic Als ◽  
Oculomotor Neurons ◽  
Als Patients

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease that causes compromised function of motor neurons and neuronal death. However, oculomotor neurons are largely spared from disease symptoms. The underlying causes for sporadic ALS as well as for the resistance of oculomotor neurons to disease symptoms remain poorly understood. In this bioinformatic-analysis, we compared the gene expression profiles of spinal and oculomotor tissue samples from control individuals and sporadic ALS patients. We show that the genes GAD2 and GABRE (involved in GABA signaling), and CALB1 (involved in intracellular Ca2+ ion buffering) are downregulated in the spinal tissues of ALS patients, but their endogenous levels are higher in oculomotor tissues relative to the spinal tissues. Our results suggest that the downregulation of these genes and processes in spinal tissues are related to sporadic ALS disease progression and their upregulation in oculomotor neurons confer upon them resistance to ALS symptoms. These results build upon prevailing models of excitotoxicity that are relevant to sporadic ALS disease progression and point out unique opportunities for better understanding the progression of neurodegenerative properties associated with sporadic ALS.

scholarly journals PCA-based unsupervised feature extraction for gene expression analysis of COVID-19 patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kota Fujisawa ◽  
Mamoru Shimo ◽  
Y.-H. Taguchi ◽  
Shinya Ikematsu ◽  
Ryota Miyata
Keyword(s):  
Gene Expression ◽  
Feature Extraction ◽  
Target Genes ◽  
Gene Selection ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Principal Component ◽  
Data Set ◽  
Immune Related Genes ◽  
Unsupervised Feature Extraction

AbstractCoronavirus disease 2019 (COVID-19) is raging worldwide. This potentially fatal infectious disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the complete mechanism of COVID-19 is not well understood. Therefore, we analyzed gene expression profiles of COVID-19 patients to identify disease-related genes through an innovative machine learning method that enables a data-driven strategy for gene selection from a data set with a small number of samples and many candidates. Principal-component-analysis-based unsupervised feature extraction (PCAUFE) was applied to the RNA expression profiles of 16 COVID-19 patients and 18 healthy control subjects. The results identified 123 genes as critical for COVID-19 progression from 60,683 candidate probes, including immune-related genes. The 123 genes were enriched in binding sites for transcription factors NFKB1 and RELA, which are involved in various biological phenomena such as immune response and cell survival: the primary mediator of canonical nuclear factor-kappa B (NF-κB) activity is the heterodimer RelA-p50. The genes were also enriched in histone modification H3K36me3, and they largely overlapped the target genes of NFKB1 and RELA. We found that the overlapping genes were downregulated in COVID-19 patients. These results suggest that canonical NF-κB activity was suppressed by H3K36me3 in COVID-19 patient blood.

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