Immune landscape of periodontitis unveils alterations of infiltrating immunocytes and molecular networks-aggregating into an interactive web-tool for periodontitis related immune analysis and visualization

Abstract Background Immunity reaction plays an essential role in periodontitis progress and we aim to investigate the underlying regulatory network of immune reactions in periodontitis. Methods CIBERSORT was used to estimate immunocyte fractions in different clinical statuses. Logistic regression was used to assess the immunocyte weight in periodontitis. Immune-related periodontitis subtypes were identified by the Nonnegative Matrix Factorization algorithm. Gene-set enrichment analysis and Gene-set variation analysis were conducted to analyze pathway activities. Immunocytes related gene modules were identified by Weighted gene co-expression network analysis. Results Altered immunocytes in healthy versus periodontitis, aggressive versus chronic, male versus female and age were identified. Immunocytes enriched in periodontitis were calculated, and their correlation was also explored. Two distinct immune-related periodontitis subtypes were identified and one is characterized by B cell reactions and the other is IL-6 cytokine reactions. 463 statistically significant correlations between 22 immunocytes and pathways were revealed. Immunocytes and clinical phenotypes matched their gene modules, and their functions were annotated. Last, an easy-to-use and user-friendly interactive web-tool were developed for periodontitis related immune analysis and visualization (https://118.24.100.193:3838/tool-PIA/). Conclusions This study systematically investigated periodontitis immune atlas and caught a glimpse of the underlying mechanism of periodontitis from gene-pathway-immunocyte networks, which can not only inspire researchers but also help them in periodontitis related immune researches.

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Immune landscape of periodontitis unveils alterations of infiltrating immunocytes and molecular networks-aggregating into an interactive web-tool for periodontitis related immune analysis and visualization

10.21203/rs.3.rs-37931/v2 ◽

2020 ◽

Author(s):

Xiaoqi Zhang ◽

Qingxuan Wang ◽

Xinyu Yan ◽

Yue Shan ◽

Lu Xing ◽

...

Keyword(s):

Nonnegative Matrix ◽

Enrichment Analysis ◽

Underlying Mechanism ◽

Gene Set Enrichment Analysis ◽

Molecular Networks ◽

Web Tool ◽

Gene Set ◽

Gene Pathway ◽

Gene Modules ◽

User Friendly

Abstract Background: Immunity reaction plays an essential role in periodontitis progress and we aim to investigate the underlying regulatory network of immune reactions in periodontitis. Methods: CIBERSORT was used to estimate immunocyte fractions in different clinical statuses. Logistic regression was used to assess the immunocyte enrichment in periodontitis. Immune-related periodontitis subtypes were identified by the Nonnegative Matrix Factorization algorithm. Gene-set enrichment analysis and Gene-set variation analysis were conducted to analyze pathway activities. Immunocytes related gene modules were identified by Weighted gene co-expression network analysis. Results: Altered immunocytes in healthy-vs-periodontitis, aggressive-vs-chronic, male-vs-female and age were identified. Immunocytes enriched in periodontitis were calculated, and their correlation was also explored. Two distinct immune-related periodontitis subtypes were identified and one is characterized by B cell reaction and the other is IL-6 cytokine reactions. 463 statistically significant correlations between 22 immunocytes and pathways were revealed. Immunocytes and clinical phenotypes matched their gene modules, and their functions were annotated. Last, an easy-to-use and user-friendly interactive web-tool were developed for periodontitis related immune analysis and visualization (http://118.24.100.193:3838/tool-PIA/).Conclusions: This study systematically investigated periodontitis immune atlas and caught a glimpse of the underlying mechanism of periodontitis from gene-pathway-immunocyte networks, which can not only inspire researchers but also help them in periodontitis related immune researches.

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Immune Landscape of Periodontitis Unveils Alterations of Infiltrating Immunocytes and Molecular Networks-Aggregating into an Interactive Web-Tool for Periodontitis Related Immune Analysis and Visualization

10.21203/rs.3.rs-37931/v1 ◽

2020 ◽

Author(s):

Xiaoqi Zhang ◽

Qingxuan Wang ◽

Xinyu Yan ◽

Yue Shan ◽

Lu Xing ◽

...

Keyword(s):

Regulatory Network ◽

Clinical Status ◽

Underlying Mechanism ◽

Molecular Networks ◽

Related Gene ◽

Web Tool ◽

Gene Pathway ◽

Immune Alterations ◽

Gene Modules ◽

User Friendly

Abstract Background: Immunity and immunocyte reaction play an essential role in periodontitis progress and we aim to investigate the underlying regulatory network of periodontitis immune alterations. Methods: CIBERSORT was used to estimated immunocyte fractions in different clinical status. Logistic regression was used to assess the immunocyte weight to periodontitis. Immune-related periodontitis subtypes were identified by the NMF algorithm. GSEA and GSVA were conducted to analyze pathway activity. Immunocytes related gene modules were identified by WGCNA. Results: Altered immunocytes in healthy-vs-periodontitis, aggressive-vs-chronic, male-vs-female and age were identified. Contributing for periodontitis of immunocytes was calculated and their correlation was also done. Two distinct immune-related periodontitis subtypes were identified and one is characterized by B cell reaction and the other is IL-6 cytokine reactions. 463 statistically significant correlations between 22 immunocytes and pathways were revealed. Immunocytes and clinical phenotypes matched their gene modules, and their functions were annotated. Last, an easy-to-use and user-friendly interactive web-tool were developed for periodontitis related immune analysis and visualization (http://118.24.100.193:3838/tool-PIA/).Conclusions: This study systematically investigated periodontitis immune atlas and glimpse the underlying mechanism of periodontitis from gene-pathway-immunocyte networks, which can not only inspire researchers but also help them in periodontitis related immune researches.

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massiveGenesetsTest: a web tool to run enrichment analysis

10.1101/2021.02.15.431228 ◽

2021 ◽

Author(s):

Luigi Cerulo ◽

Stefano Maria Pagnotta

Keyword(s):

Test Procedure ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Supplementary Information ◽

Web Tool ◽

Test Statistic ◽

Gene Set ◽

Gene Sets ◽

Prioritization Method ◽

The Web

AbstractMotivationInferring biological phenotypes from genomic data and sample clusters is a routinely task usually performed with Gene-Set Enrichment Analysis (GSEA), a tool that queries gene-profiles. In previous work, we scrutinized the approach based on Mann-Witney for Gene-Sets test. We highlighted the Mann-Witney test-statistics sensitivity to uncover weak signals and the drastic decreasing of time complexity.ResultsWe propose web implementation of the Gene-sets testing based on the Mann-Witney procedure. The test-procedure has reshaped to decrease the computational expense, now about tens of seconds, even if a large collection of gene-sets queries the same gene-profile. The probabilistic interpretation of the normalized test-statistic has been investigated to a better understanding of the enrichment results. A novel prioritization method across enrichment-scores, gene-set dimensions, and p-values, draws attention to relevant gene-sets. The web tool provides both tabular and graphical enrichment results. A complimentary R function allows integrating the enrichment procedure in a complex [email protected] informationExample data and guidelines are included in the supporting material of the web-site.

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Cancer-associated fibroblasts promote the survival of irradiated nasopharyngeal carcinoma cells via the NF-κB pathway

Journal of Experimental & Clinical Cancer Research ◽

10.1186/s13046-021-01878-x ◽

2021 ◽

Vol 40 (1) ◽

Cited By ~ 1

Author(s):

Weiqiang Huang ◽

Longshan Zhang ◽

Mi Yang ◽

Xixi Wu ◽

Xiaoqing Wang ◽

...

Keyword(s):

Dna Damage ◽

Nasopharyngeal Carcinoma ◽

Enrichment Analysis ◽

Underlying Mechanism ◽

Gene Set Enrichment Analysis ◽

Cancer Associated Fibroblasts ◽

Western Blot Assay ◽

Damage Level ◽

Radiation Resistant

Abstract Background Irradiation has emerged as a valid tool for nasopharyngeal carcinoma (NPC) in situ treatment; however, NPC derived from tissues treated with irradiation is a main cause cancer-related death. The purpose of this study is to uncover the underlying mechanism regarding tumor growth after irradiation and provided potential therapeutic strategy. Methods Fibroblasts were extracted from fresh NPC tissue and normal nasopharyngeal mucosa. Immunohistochemistry was conducted to measure the expression of α-SMA and FAP. Cytokines were detected by protein array chip and identified by real-time PCR. CCK-8 assay was used to detect cell proliferation. Radiation-resistant (IRR) 5-8F cell line was established and colony assay was performed to evaluate tumor cell growth after irradiation. Signaling pathways were acquired via gene set enrichment analysis (GSEA). Comet assay and γ-H2AX foci assay were used to measure DNA damage level. Protein expression was detected by western blot assay. In vivo experiment was performed subcutaneously. Results We found that radiation-resistant NPC tissues were constantly infiltrated with a greater number of cancer-associated fibroblasts (CAFs) compared to radiosensitive NPC tissues. Further research revealed that CAFs induced the formation of radioresistance and promoted NPC cell survival following irradiation via the IL-8/NF-κB pathway to reduce irradiation-induced DNA damage. Treatment with Tranilast, a CAF inhibitor, restricted the survival of CAF-induced NPC cells and attenuated the of radioresistance properties. Conclusions Together, these data demonstrate that CAFs can promote the survival of irradiated NPC cells via the NF-κB pathway and induce radioresistance that can be interrupted by Tranilast, suggesting the potential value of Tranilast in sensitizing NPC cells to irradiation.

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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

Journal of Clinical Medicine ◽

10.3390/jcm8101580 ◽

2019 ◽

Vol 8 (10) ◽

pp. 1580 ◽

Cited By ~ 1

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.

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Gene set enrichment analysis for genome-wide DNA methylation data

Genome Biology ◽

10.1186/s13059-021-02388-x ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Jovana Maksimovic ◽

Alicia Oshlack ◽

Belinda Phipson

Keyword(s):

Dna Methylation ◽

Enrichment Analysis ◽

R Package ◽

Gene Set Enrichment Analysis ◽

Methylation Array ◽

Gene Set ◽

Genome Wide ◽

Genome Methylation ◽

Unbiased Gene ◽

Gene Set Testing

AbstractDNA methylation is one of the most commonly studied epigenetic marks, due to its role in disease and development. Illumina methylation arrays have been extensively used to measure methylation across the human genome. Methylation array analysis has primarily focused on preprocessing, normalization, and identification of differentially methylated CpGs and regions. GOmeth and GOregion are new methods for performing unbiased gene set testing following differential methylation analysis. Benchmarking analyses demonstrate GOmeth outperforms other approaches, and GOregion is the first method for gene set testing of differentially methylated regions. Both methods are publicly available in the missMethyl Bioconductor R package.

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IKBIP is a novel EMT-related biomarker and predicts poor survival in glioma

Translational Neuroscience ◽

10.1515/tnsci-2021-0002 ◽

2021 ◽

Vol 12 (1) ◽

pp. 009-019

Author(s):

Ying Yang ◽

Jin Wang ◽

Shihai Xu ◽

Wen Lv ◽

Fei Shi ◽

...

Keyword(s):

Epithelial To Mesenchymal Transition ◽

Molecular Subtype ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Transcriptional Level ◽

Who Grade ◽

Interacting Protein ◽

Mesenchymal Transition ◽

Gene Set ◽

Substrate Adhesion

Abstract Background In cancer, kappa B-interacting protein (IKBIP) has rarely been reported. This study aimed at investigating its expression pattern and biological function in brain glioma at the transcriptional level. Methods We selected 301 glioma patients with microarray data from CGGA database and 697 glioma patients with RNAseq data from TCGA database. Transcriptional data and clinical data of 998 samples were analyzed. Statistical analysis and figure generating were performed with R language. Results We found that IKBIP expression showed positive correlation with WHO grade of glioma. IKBIP was increased in isocitrate dehydrogenase (IDH) wild type and mesenchymal molecular subtype of glioma. Gene ontology analysis demonstrated that IKBIP was profoundly associated with extracellular matrix organization, cell–substrate adhesion and response to wounding in both pan-glioma and glioblastoma. Subsequent gene set enrichment analysis revealed that IKBIP was particularly correlated with epithelial-to-mesenchymal transition (EMT). To further elucidate the relationship between IKBIP and EMT, we performed gene set variation analysis to screen the EMT-related signaling pathways and found that IKBIP expression was significantly associated with PI3K/AKT, hypoxia and TGF-β pathway. Moreover, IKBIP expression was found to be synergistic with key biomarkers of EMT, especially with N-cadherin, vimentin, snail, slug and TWIST1. Finally, higher IKBIP indicated significantly shorter survival for glioma patients. Conclusions IKBIP was associated with more aggressive phenotypes of gliomas. Furthermore, IKBIP was significantly involved in EMT and could serve as an independent prognosticator in glioma.

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

BMC Bioinformatics ◽

10.1186/s12859-020-03929-0 ◽

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.

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