Correlations between glycolysis with clinical traits and immune function in bladder urothelial carcinoma

Abstract Background: Glycolysis was a representative hallmark in the tumor microenvironment (TME), and we aimed to explore the correlations between glycolysis with immune activity and clinical traits in bladder urothelial carcinoma (BLCA). Methods: Our study obtained glycolysis scores for each BLCA samples from TCGA by a single-sample gene set enrichment analysis (ssGSEA) algorithm, based on a glycolytic gene set. The relationship between glycolysis with prognosis, clinical characteristics, and immune function were investigated subsequently. Results: We found that enhanced glycolysis was associated with poor prognosis and metastasis in BLCA. Moreover, glycolysis had a close correlation with immune function, and enhanced glycolysis increased immune activities. In other words, glycolysis had a positive correlation with immune activities. Immune checkpoints such as IDO1, CD274, were up-regulated in high-glycolysis group as well. Conclusion: We speculated that in BLCA, elevated glycolysis enhanced immune function, which caused tumor cells to overexpress immune checkpoints to evade immune surveillance. Inhibition of glycolysis might be a promising assistant for immunotherapy in bladder cancer.

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PVT1 is a prognostic marker associated with immune invasion of bladder urothelial carcinoma

Mathematical Biosciences and Engineering ◽

10.3934/mbe.2022009 ◽

2021 ◽

Vol 19 (1) ◽

pp. 169-190

Author(s):

Peiyuan Li ◽

◽

Gangjie Qiao ◽

Jian Lu ◽

Wenbin Ji ◽

...

Keyword(s):

Urothelial Carcinoma ◽

Immune Cell ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Gene Set Enrichment ◽

Cox Regression Analysis ◽

Gene Set ◽

Bladder Urothelial Carcinoma

<abstract> <p>Plasmacytoma variant translocation 1 (PVT1) is involved in multiple signaling pathways and plays an important regulatory role in a variety of malignant tumors. However, its role in the prognosis and immune invasion of bladder urothelial carcinoma (BLCA) remains unclear. This study investigated the expression of PVT1 in tumor tissue and its relationship with immune invasion, and determined its prognostic role in patients with BLCA. Patients were identified from the cancer genome atlas (TCGA). The enrichment pathway and function of PVT1 were explained by gene ontology (GO) term analysis, gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA), and the degree of immune cell infiltration was quantified. Kaplan–Meier analysis and Cox regression were used to analyze the correlation between PVT1 and survival rate. PVT1-high BLCA patients had a lower 10-year disease-specific survival (DSS P < 0.05) and overall survival (OS P < 0.05). Multivariate Cox regression analysis showed that PVT1 (high vs. low) (P = 0.004) was an independent prognostic factor. A nomogram was used to predict the effect of PVT1 on the prognosis. PVT1 plays an important role in the progression and prognosis of BLCA and can be used as a medium biomarker to predict survival after cystectomy.</p> </abstract>

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Newborn infant skin gene expression: Remarkable differences versus adults

PLoS ONE ◽

10.1371/journal.pone.0258554 ◽

2021 ◽

Vol 16 (10) ◽

pp. e0258554

Author(s):

Marty O. Visscher ◽

Ping Hu ◽

Andrew N. Carr ◽

Charles C. Bascom ◽

Robert J. Isfort ◽

...

Keyword(s):

Ultraviolet Radiation ◽

Immune Function ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Biological Processes ◽

Hair Cycle ◽

Gene Set Enrichment ◽

Gene Set ◽

Adult Skin ◽

Skin Samples

At birth, human infants are poised to survive in harsh, hostile conditions. An understanding of the state of newborn skin development and maturation is key to the maintenance of health, optimum response to injury, healing and disease. The observational study collected full-thickness newborn skin samples from 27 infants at surgery and compared them to skin samples from 43 adult sites protected from ultraviolet radiation exposure, as the standard for stable, mature skin. Transcriptomics profiling and gene set enrichment analysis were performed. Statistical analysis established over 25,000 differentially regulated probe sets, representing 10,647 distinct genes, in infant skin compared to adult skin. Gene set enrichment analysis showed a significant increase in 143 biological processes (adjusted p < 0.01) in infant skin, versus adult skin samples, including extracellular matrix (ECM) organization, cell adhesion, collagen fibril organization and fatty acid metabolic process. ECM organization and ECM structure organization were the biological processes in infant skin with the lowest adjusted P-value. Genes involving epidermal development, immune function, cell differentiation, and hair cycle were overexpressed in adults, representing 101 significantly enriched biological processes (adjusted p < 0.01). The processes with the highest significant difference were skin and epidermal development, e.g., keratinocyte differentiation, keratinization and cornification intermediate filament cytoskeleton organization and hair cycle. Enriched Gene Ontology (GO) biological processes also involved immune function, including antigen processing and presentation. When compared to ultraviolet radiation-protected adult skin, our results provide essential insight into infant skin and its ability to support the newborn’s preparedness to survive and flourish, despite the infant’s new environment laden with microbes, high oxygen tension and potential irritants. This fundamental knowledge is expected to guide strategies to protect and preserve the features of unperturbed, young skin.

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BDNF Acts as a Prognostic Factor Associated with Tumor-Infiltrating Th2 Cells in Pancreatic Adenocarcinoma

Disease Markers ◽

10.1155/2021/7842035 ◽

2021 ◽

Vol 2021 ◽

pp. 1-22

Author(s):

Yanan Zhu ◽

Cangang Zhang ◽

Dongyu Zhao ◽

Wenhua Li ◽

Zhe Zhao ◽

...

Keyword(s):

Pancreatic Adenocarcinoma ◽

Chemokine Receptors ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Th2 Cells ◽

Immune Checkpoints ◽

Bdnf Expression ◽

Gene Set Enrichment ◽

Gene Set ◽

Patient Prognosis

Pancreatic adenocarcinoma (PAAD) is an extremely lethal disease worldwide. Brain-derived neurotrophic factor (BDNF) is a critical member of the neurotrophin polypeptide superfamily that plays an important role in multiple cancers. However, the association among BDNF expression, tumor immunity, and PAAD prognosis remains unclear. BDNF expression and its influence on patient prognosis were explored based on The Cancer Genome Atlas, Cancer Cell Line Encyclopedia, Genotype-Tissue Expression, and Kaplan-Meier plotter. Gene set enrichment analysis was performed to understand the biological roles of BDNF. The role of BDNF in tumor-infiltrating immune cells was determined using the Tumor Immune Estimation Resource database and the single-sample gene set enrichment analysis and xCell algorithm. The correlation among BDNF and chemokines, chemokine receptors, chemotherapeutic efficacy, and immune checkpoints was analyzed based on RStudio. BDNF expression was remarkably higher in PAAD compared to their paired normal tissues, and high BDNF expression was associated with unfavorable prognosis. Enrichment analysis revealed that BDNF was significantly enriched in major oncogenic pathways in PAAD. BDNF expression was positively correlated with immune infiltration, especially Th2 cells. Moreover, BDNF expression was positively correlated with Th2 cell-related chemokine/chemokine receptors, indicating that BDNF might modulate the migration of Th2 cells in PAAD. We also found that BDNF expression was correlated with high chemotherapeutics sensitivity and highly expressed immune checkpoints, making it a valuable biomarker in predicting the therapeutic benefits for chemotherapy and immunotherapy in cancer patients. In summary, BDNF might affect patient prognosis by interacting with tumor-infiltrating Th2 cells, thus serving as a potential prognostic biomarker in PAAD.

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Elevated GAS2L3 Expression Correlates With Poor Prognosis in Patients With Glioma: A Study Based on Bioinformatics and Immunohistochemical Analysis

Frontiers in Genetics ◽

10.3389/fgene.2021.649270 ◽

2021 ◽

Vol 12 ◽

Author(s):

Yan Zhou ◽

Limin Zhang ◽

Sirong Song ◽

Lixia Xu ◽

Yan Yan ◽

...

Keyword(s):

T Cell ◽

Immune Cell ◽

Enrichment Analysis ◽

Immunohistochemical Analysis ◽

Gene Set Enrichment Analysis ◽

Immune Checkpoints ◽

Gene Set Enrichment ◽

Bioinformatics Analyses ◽

Gene Set

BackgroundGrowth arrest–specific 2 like 3 (GAS2L3) is a cytoskeleton-associated protein that interacts with actin filaments and tubulin. Abnormal GAS2L3 expression has been reported to be associated with carcinogenesis. However, the biological role of GAS2L3 in glioma remains to be determined.MethodsThe transcriptome level of GAS2L3 and its relationship with clinicopathological characteristics were analyzed among multiple public databases and clinical specimens. Bioinformatics analyses were conducted to explore biological functions and prognostic value of GAS2L3 in glioma.ResultsGAS2L3 was substantially expressed in glioma, and high GAS2L3 expression correlated with shorter overall survival time and poor clinical variables. Gene set enrichment analysis (GSEA), single-sample gene-set enrichment analysis, and CIBERSORT algorithm analyses showed that GAS2L3 expression was closely linked to immune-related pathways, inflammatory activities, and immune cell infiltration. Moreover, GAS2L3 was synergistic with T cell–inflamed gene signature, immune checkpoints, T-cell receptor diversities, and neoantigen numbers.ConclusionThis study suggests that GAS2L3 is a prognostic biomarker for glioma, providing a reference for further study of the potential role of GAS2L3 in the immunomodulation of glioma.

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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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