scholarly journals Identification of Pro-Fibrotic Macrophage Populations by Single-Cell Transcriptomic Analysis in West Highland White Terriers Affected With Canine Idiopathic Pulmonary Fibrosis

2020 ◽  
Vol 11 ◽  
Author(s):  
Aline Fastrès ◽  
Dimitri Pirottin ◽  
Laurence Fievez ◽  
Alexandru-Cosmin Tutunaru ◽  
Géraldine Bolen ◽  
...  
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Single Cell ◽  
Enrichment Analysis ◽  
Lavage Fluid ◽  
Gene Set Enrichment Analysis ◽  
Cell Populations ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Macrophage Populations

Canine idiopathic pulmonary fibrosis (CIPF) affects old dogs from the West Highland white terrier (WHWT) breed and mimics idiopathic pulmonary fibrosis (IPF) in human. The disease results from deposition of fibrotic tissue in the lung parenchyma causing respiratory failure. Recent studies in IPF using single-cell RNA sequencing (scRNA-seq) revealed the presence of profibrotic macrophage populations in the lung, which could be targeted for therapeutic purpose. In dogs, scRNA-seq was recently validated for the detection of cell populations in bronchoalveolar lavage fluid (BALF) from healthy dogs. Here we used the scRNA-seq to characterize disease-related heterogeneity within cell populations of macrophages/monocytes (Ma/Mo) in the BALF from five WHWTs affected with CIPF in comparison with three healthy WHWTs. Gene set enrichment analysis was also used to assess pro-fibrotic capacities of Ma/Mo populations. Five clusters of Ma/Mo were identified. Gene set enrichment analyses revealed the presence of pro-fibrotic monocytes in higher proportion in CIPF WHWTs than in healthy WHWTs. In addition, monocyte-derived macrophages enriched in pro-fibrotic genes in CIPF compared with healthy WHWTs were also identified. These results suggest the implication of Ma/Mo clusters in CIPF processes, although, further research is needed to understand their role in disease pathogenesis. Overexpressed molecules associated with pulmonary fibrosis processes were also identified that could be used as biomarkers and/or therapeutic targets in the future.

scholarly journals Application of biclustering of gene expression data and gene set enrichment analysis methods to identify potentially disease causing nanomaterials

2015 ◽  
Vol 6 ◽  
pp. 2438-2448 ◽  
Author(s):  
Andrew Williams ◽  
Sabina Halappanavar
Keyword(s):  
Gene Expression ◽  
Pulmonary Fibrosis ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Data Driven ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Analysis Methods ◽  
Gene Sets

Background: The presence of diverse types of nanomaterials (NMs) in commerce is growing at an exponential pace. As a result, human exposure to these materials in the environment is inevitable, necessitating the need for rapid and reliable toxicity testing methods to accurately assess the potential hazards associated with NMs. In this study, we applied biclustering and gene set enrichment analysis methods to derive essential features of altered lung transcriptome following exposure to NMs that are associated with lung-specific diseases. Several datasets from public microarray repositories describing pulmonary diseases in mouse models following exposure to a variety of substances were examined and functionally related biclusters of genes showing similar expression profiles were identified. The identified biclusters were then used to conduct a gene set enrichment analysis on pulmonary gene expression profiles derived from mice exposed to nano-titanium dioxide (nano-TiO2), carbon black (CB) or carbon nanotubes (CNTs) to determine the disease significance of these data-driven gene sets. Results: Biclusters representing inflammation (chemokine activity), DNA binding, cell cycle, apoptosis, reactive oxygen species (ROS) and fibrosis processes were identified. All of the NM studies were significant with respect to the bicluster related to chemokine activity (DAVID; FDR p-value = 0.032). The bicluster related to pulmonary fibrosis was enriched in studies where toxicity induced by CNT and CB studies was investigated, suggesting the potential for these materials to induce lung fibrosis. The pro-fibrogenic potential of CNTs is well established. Although CB has not been shown to induce fibrosis, it induces stronger inflammatory, oxidative stress and DNA damage responses than nano-TiO2 particles. Conclusion: The results of the analysis correctly identified all NMs to be inflammogenic and only CB and CNTs as potentially fibrogenic. In addition to identifying several previously defined, functionally relevant gene sets, the present study also identified two novel genes sets: a gene set associated with pulmonary fibrosis and a gene set associated with ROS, underlining the advantage of using a data-driven approach to identify novel, functionally related gene sets. The results can be used in future gene set enrichment analysis studies involving NMs or as features for clustering and classifying NMs of diverse properties.

scholarly journals Elevated TUBA1A Might Indicate the Clinical Outcomes of Patients with Gastric Cancer, Being Associated with the Infiltration of Macrophages in the Tumor Immune Microenvironment

2020 ◽  
Vol 29 (4) ◽  
pp. 509-522
Author(s):  
Dazhi Wang ◽  
Zheng Jiao ◽  
Yinghui Ji ◽  
Shuyu Zhang
Keyword(s):  
Gastric Cancer ◽  
Tumor Microenvironment ◽  
Single Cell ◽  
Single Cells ◽  
Enrichment Analysis ◽  
Clinicopathological Features ◽  
Gene Set Enrichment Analysis ◽  
Regulation Mechanism ◽  
Gene Set Enrichment ◽  
Gene Set

Background and Aims: TUBA1A belongs to the tubulin superfamily, and its role in gastric cancer (GC) remains unclear. This study assessed the expression and effect of TUBA1A in GC, as well as its association with survival and clinicopathological features. Gene set enrichment analysis (GSEA) results revealed that high TUBA1A expression was associated with multiple pathways, including those that contributed to the infiltration of macrophages in the tumor microenvironment. Since increased infiltration of macrophages can lead to oxaliplatin resistance, we analyzed the association between TUBA1A, the infiltration of macrophages to the tumor microenvironment, and the inhibitory concentration 50% (IC50) of oxaliplatin. In addition, we analyzed the possible epigenetic regulation mechanism. Methods: A total of 1,881 samples, including 1,618 patients with GC and 263 normal samples, were examined. The associations between clinicopathological features and TUBA1A were assessed by chi-square test, survival was assessed by Kaplan-Meier analysis, and gene set enrichment analysis (GSEA) was performed to explore the potential mechanisms. The associations between TUBA1A and immune infiltration of M0-, M1-, and M2- polarized macrophages were examined by applying deconvolution’s quantification and Pearson’s correlation analysis. The association of TUBA1A with the IC50 of oxaliplatin was analyzed by Pearson correlation test. The mechanisms of TUBA1A dysregulation were studied by analyzing methylation data. A single-cell TUBA1A mRNA expression map of the stomach was drawn from the analysis of stomach single-cell RNA sequencing data that included more than 13,000 single cells of 17 stomach cell types. Results: TUBA1A expression was elevated in GC (p<0.01) and indicated poorer overall survival (p<0.001), first progression survival (p<0.001), and post-progression survival (p<0.01). High TUBA1A expression was significantly correlated with more aggressive clinicopathological features of GC patients (p<0.001). Elevated TUBA1A contributes to the infiltration of macrophages to the tumor microenvironment (p<0.001) and increased the IC50 of oxaliplatin in vitro (p<0.05), while hypomethylation was shown to contribute to the upregulation of TUBA1A (p<0.05). Conclusions: TUBA1A might be a potential prognostic marker and therapeutic target in GC. TUBA1A is significantly associated with the infiltration of M2-polarized macrophages in GC, and the IC50 of oxaliplatin. Hypomethylation contributes to the upregulation of TUBA1A in GC.

scholarly journals Higher Acid-Base Imbalance Associated with Respiratory Failure Could Decrease the Survival of Patients with Scrub Typhus during Intensive Care Unit Stay: A Gene Set Enrichment Analysis

2019 ◽  
Vol 8 (10) ◽  
pp. 1580 ◽  
Author(s):  
Kyoung Min Moon ◽  
Kyueng-Whan Min ◽  
Mi-Hye Kim ◽  
Dong-Hoon Kim ◽  
Byoung Kwan Son ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Respiratory Failure ◽  
Scrub Typhus ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Acid Base ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Gene Sets

Ninety percent of patients with scrub typhus (SC) with vasculitis-like syndrome recover after mild symptoms; however, 10% can suffer serious complications, such as acute respiratory failure (ARF) and admission to the intensive care unit (ICU). Predictors for the progression of SC have not yet been established, and conventional scoring systems for ICU patients are insufficient to predict severity. We aimed to identify simple and robust indicators to predict aggressive behaviors of SC. We evaluated 91 patients with SC and 81 non-SC patients who were admitted to the ICU, and 32 cases from the public functional genomics data repository for gene expression analysis. We analyzed the relationships between several predictors and clinicopathological characteristics in patients with SC. We performed gene set enrichment analysis (GSEA) to identify SC-specific gene sets. The acid-base imbalance (ABI), measured 24 h before serious complications, was higher in patients with SC than in non-SC patients. A high ABI was associated with an increased incidence of ARF, leading to mechanical ventilation and worse survival. GSEA revealed that SC correlated to gene sets reflecting inflammation/apoptotic response and airway inflammation. ABI can be used to indicate ARF in patients with SC and assist with early detection.

scholarly journals Drug perturbation gene set enrichment analysis (dpGSEA): a new transcriptomic drug screening approach

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Mike Fang ◽  
Brian Richardson ◽  
Cheryl M. Cameron ◽  
Jean-Eudes Dazard ◽  
Mark J. Cameron
Keyword(s):  
Drug Targets ◽  
T Regulatory Cells ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Regulatory Cells ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Gene Sets ◽  
Gastroenteropancreatic Neuroendocrine Tumor ◽  
Public Datasets

Abstract Background In this study, we demonstrate that our modified Gene Set Enrichment Analysis (GSEA) method, drug perturbation GSEA (dpGSEA), can detect phenotypically relevant drug targets through a unique transcriptomic enrichment that emphasizes biological directionality of drug-derived gene sets. Results We detail our dpGSEA method and show its effectiveness in detecting specific perturbation of drugs in independent public datasets by confirming fluvastatin, paclitaxel, and rosiglitazone perturbation in gastroenteropancreatic neuroendocrine tumor cells. In drug discovery experiments, we found that dpGSEA was able to detect phenotypically relevant drug targets in previously published differentially expressed genes of CD4+T regulatory cells from immune responders and non-responders to antiviral therapy in HIV-infected individuals, such as those involved with virion replication, cell cycle dysfunction, and mitochondrial dysfunction. dpGSEA is publicly available at https://github.com/sxf296/drug_targeting. Conclusions dpGSEA is an approach that uniquely enriches on drug-defined gene sets while considering directionality of gene modulation. We recommend dpGSEA as an exploratory tool to screen for possible drug targeting molecules.

scholarly journals Key pathways involved in prostate cancer based on gene set enrichment analysis and meta analysis

2011 ◽  
Vol 10 (4) ◽  
pp. 3856-3887 ◽  
Author(s):  
Q.Y. Ning ◽  
J.Z. Wu ◽  
N. Zang ◽  
J. Liang ◽  
Y.L. Hu ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Key Pathways

scholarly journals A Novel Prognostic Model Based On Cytosolic DNA Sensing-Related Gene Signature for Pancreatic Cancer

2021 ◽  
Author(s):  
Chuan-Qi Xu ◽  
Kui-Sheng Yang ◽  
Shu-Xian Zhao ◽  
Jian Lv
Keyword(s):  
Pancreatic Cancer ◽  
Prognostic Factor ◽  
Prognostic Model ◽  
Risk Group ◽  
Enrichment Analysis ◽  
Independent Prognostic Factor ◽  
Gene Set Enrichment Analysis ◽  
Dna Sensing ◽  
Gene Set Enrichment ◽  
Gene Set

Abstract Objective: Pancreatic cancer (PC) is one of the most malignant tumors. Cytosolic DNA sensing have been found to play an essential role in tumor. In this study, a cytosolic DNA sensing-related genes (CDSRGs) signature was constructed and the potential mechanisms also been discussed.Methods: The RNA expression and clinical data of PC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Subsequently, univariate (UCR) and multivariate Cox regression (MCR) analyses were conducted to establish a prognostic model in the TCGA patients, which was verified by GEO patients. Cancer immune infiltrates were investigated via single sample gene set enrichment analysis (ssGSEA) and Tumor Immune Estimation Resource (TIMER). Finally, Gene Set Enrichment Analysis (GSEA) was used to investigate the related signaling pathways.Results: A prognostic model comprising four genes (POLR2E,IL18, MAVS, and FADD) was established. The survival rate of patients in the low-risk group was significantly higher than that of patients in the high-risk group. In addition, CDSRGs-risk score was proved as an independent prognostic factor in PC. Immune infiltrates and drug sensitivity are associated with POLR2E,IL18, MAVS, and FADD expression.Conclusions: In summary, we present and validated a CDSRGs risk model that is an independent prognostic factor and indicates the immune characteristics of PC. This prognostic model may facilitate the personalized treatment and monitoring.

scholarly journals Kalirin-RAC controls nucleokinetic migration in ADRN-type neuroblastoma

2021 ◽  
Vol 4 (5) ◽  
pp. e201900332
Author(s):  
Elena A Afanasyeva ◽  
Moritz Gartlgruber ◽  
Tatsiana Ryl ◽  
Bieke Decaesteker ◽  
Geertrui Denecker ◽  
...  
Keyword(s):  
Enrichment Analysis ◽  
Time Lapse ◽  
Dna Methyltransferases ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Risk Characteristics ◽  
Weak Points ◽  
Treatment Research ◽  
Time Lapse Imaging

The migrational propensity of neuroblastoma is affected by cell identity, but the mechanisms behind the divergence remain unknown. Using RNAi and time-lapse imaging, we show that ADRN-type NB cells exhibit RAC1- and kalirin-dependent nucleokinetic (NUC) migration that relies on several integral components of neuronal migration. Inhibition of NUC migration by RAC1 and kalirin-GEF1 inhibitors occurs without hampering cell proliferation and ADRN identity. Using three clinically relevant expression dichotomies, we reveal that most of up-regulated mRNAs in RAC1- and kalirin–GEF1–suppressed ADRN-type NB cells are associated with low-risk characteristics. The computational analysis shows that, in a context of overall gene set poverty, the upregulomes in RAC1- and kalirin–GEF1–suppressed ADRN-type cells are a batch of AU-rich element–containing mRNAs, which suggests a link between NUC migration and mRNA stability. Gene set enrichment analysis–based search for vulnerabilities reveals prospective weak points in RAC1- and kalirin–GEF1–suppressed ADRN-type NB cells, including activities of H3K27- and DNA methyltransferases. Altogether, these data support the introduction of NUC inhibitors into cancer treatment research.

scholarly journals DPYSL2 as potential diagnostic and prognostic biomarker linked to immune infiltration in lung adenocarcinoma

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Yang-Jie Wu ◽  
Ai-Tao Nai ◽  
Gui-Cheng He ◽  
Fei Xiao ◽  
Zhi-Min Li ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Roc Curve ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
List Type ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract Background Dihydropyrimidinase like 2 (DPYSL2) has been linked to tumor metastasis. However, the function of DPSY2L in lung adenocarcinoma (LUAD) is yet to be explored. Methods Herein, we assessed DPYSL2 expression in various tumor types via online databases such as Oncomine and Tumor Immune Estimation Resource (TIMER). Further, we verified the low protein and mRNA expressions of DPYSL2 in LUAD via the ULCAN, The TCGA and GEPIA databases. We applied the ROC curve to examine the role of DPYSL2 in diagnosis. The prognostic significance of DPYSL2 was established through the Kaplan–Meier plotter and the Cox analyses (univariate and multivariate). TIMER was used to explore DPYSL2 expression and its connection to immune infiltrated cells. Through Gene Set Enrichment Analysis, the possible mechanism of DPYSL2 in LUAD was investigated. Results In this study, database analysis revealed lower DPYSL2 expression in LUAD than in normal tissues. The ROC curve suggested that expression of DPYSL2 had high diagnostic efficiency in LUAD. The DPYSL2 expression had an association with the survival time of LUAD patients in the Kaplan–Meier plotter and the Cox analyses. The results from TIMER depicted a markedly positive correlation of DPYSL2 expression with immune cells infiltrated in LUAD, such as macrophages, dendritic cells, CD4+ T cells, and neutrophils. Additionally, many gene markers for the immune system had similar positive correlations in the TIMER analysis. In Gene Set Enrichment Analysis, six immune-related signaling pathways were associated with DPYSL2. Conclusions In summary, DPYSL2 is a novel biomarker with diagnostic and prognostic potential for LUAD as well as an immunotherapy target. Highlights Expression of DPYSL2 was considerably lower in LUAD than in normal tissues. Investigation of multiple databases showed a high diagnostic value of DPYSL2 in LUAD. DPYSL2 can independently predict the LUAD outcomes. Immune-related mechanisms may be potential ways for DPYSL2 to play a role in LUAD.

scholarly journals Arkas: Rapid reproducible RNAseq analysis

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 586 ◽  
Author(s):  
Anthony R. Colombo ◽  
Timothy J. Triche Jr ◽  
Giridharan Ramsingh
Keyword(s):  
De Novo ◽  
Transcriptome Assembly ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Special Focus ◽  
Gene Set Enrichment ◽  
Cloud Computing Environment ◽  
Gene Set ◽  
Structured Information ◽  
Computing Platforms

The recently introduced Kallisto pseudoaligner has radically simplified the quantification of transcripts in RNA-sequencing experiments.  We offer cloud-scale RNAseq pipelines Arkas-Quantification, which deploys Kallisto for parallel cloud computations, and Arkas-Analysis, which annotates the Kallisto results by extracting structured information directly from source FASTA files with per-contig metadata and calculates the differential expression and gene-set enrichment analysis on both coding genes and transcripts. The biologically informative downstream gene-set analysis maintains special focus on Reactome annotations while supporting ENSEMBL transcriptomes. The Arkas cloud quantification pipeline includes support for custom user-uploaded FASTA files, selection for bias correction and pseudoBAM output. The option to retain pseudoBAM output for structural variant detection and annotation provides a middle ground between de novo transcriptome assembly and routine quantification, while consuming a fraction of the resources used by popular fusion detection pipelines.  Illumina's BaseSpace cloud computing environment, where these two applications are hosted, offers a massively parallel distributive quantification step for users where investigators are better served by cloud-based computing platforms due to inherent efficiencies of scale.

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