scholarly journals A pan-cancer analysis of the glutaminase and their association with prognosis, tumor microenvironment, and therapeutic targets

2021 ◽  
Author(s):  
Sheng-Jie Jin ◽  
Lian-bao Kong
Keyword(s):  
Drug Sensitivity ◽  
Cancer Metabolism ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Glutamine Metabolism ◽  
Gene Set Enrichment ◽  
Normal Tissues ◽  
Checkpoint Genes ◽  
Pan Cancer ◽  
Cancer Bioinformatics

Abstract BackgroundGlutamine metabolism plays a key role in various biological processes of tumor. Glutaminase (GLS) is involved in Glutamine metabolism and plays a conserved regulatory role in the process. Nevertheless, there is no comprehensively analysis of GLS in pan-cancer.MaterialsComprehensive bioinformatics analysis was adopted to investigate the expression level, prognostic values, and association between expression of GLS and TME, immune cells' infiltration, immune checkpoint genes, TMB, MSI, drug sensitivity in pan-cancer. Bioinformatics tools including CCLE, immunophenoscore (IPS), Tumor Immune Dysfunction and Exclusion (TIDE), GSEA, and TIMER databases were used.ResultsDifferently expressed GLS between tumor and normal tissues were analyzed, and the clinical prognoses, MMR, MSI, and TMB in multiple types of cancer were associated with GLS expression. Furthermore, GLS closely correlated with tumor immunity and drug sensitivity, and found GLS were predicted to be involved in cancer metabolism and immunity pathways, through gene set enrichment analysis (GSEA).ConclusionThe GLS expression could be used as a prognostic biomarker for determining prognosis and provide further insights into anti-glutamine metabolism for cancer.

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 H2A Histone Family Member X (H2AX) Is Upregulated in Ovarian Cancer and Demonstrates Utility as a Prognostic Biomarker in Terms of Overall Survival

2020 ◽  
Vol 9 (9) ◽  
pp. 2844
Author(s):  
Sayeh Saravi ◽  
Eriko Katsuta ◽  
Jeyarooban Jeyaneethi ◽  
Hasnat A. Amin ◽  
Matthias Kaspar ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Overall Survival ◽  
Prognostic Biomarker ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Nucleotide Polymorphisms ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Normal Tissues

Background: H2AX can be of prognostic value in breast cancer, since in advanced stage patients with high levels, there was an association with worse overall survival (OS). However, the clinical relevance of H2AX in ovarian cancer (OC) remains to be elucidated. Methods: OC H2AX expression studied using the TCGA/GTEX datasets. Subsequently, patients were classified as either high or low in terms of H2AX expression to compare OS and perform gene set enrichment. qRT-PCR validated in-silico H2AX findings followed by immunohistochemistry on a tissue microarray. The association between single nucleotide polymorphisms in the area of H2AX; prevalence and five-year OC survival was tested in samples from the UK Biobank. Results: H2AX was significantly overexpressed in OCs compared to normal tissues, with higher expression associated with better OS (p = 0.010). Gene Set Enrichment Analysis demonstrated gene sets involved in G2/M checkpoint, DNA repair mTORC1 signalling were enriched in the H2AX highly expressing OCs. Polymorphisms in the area around the gene were associated with both OC prevalence (rs72997349-C, p = 0.005) and worse OS (rs10790282-G, p = 0.011). Finally, we demonstrated that H2AX gene expression correlated with γ-H2AX staining in vitro. Conclusions: Our findings suggest that H2AX can be a novel prognostic biomarker for OC.

scholarly journals Comprehensive Analysis of Immune Correlation of KIF20A in Pan-cancer

2020 ◽  
Author(s):  
Xiao-Han Cui ◽  
Qiu-Ju Peng ◽  
Peng Gao ◽  
Xu-Dong Zhang ◽  
Ren-Zhi Li ◽  
...  
Keyword(s):  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Rna Seq ◽  
Gene Set Enrichment ◽  
Related Information ◽  
Common Causes ◽  
Cancer Genome Atlas ◽  
Pan Cancer

Abstract Background: Cancer is one of the most common causes of death, and the morbidity and mortality are gradually increasing in the world. KIF20A plays an important role in tumors, but its immune relevance in pan-cancer needs to be further studied.Methods: KIF20A-related information was download from The Cancer Genome Atlas (TCGA). Collecting RNA-seq data is fragments per kilobase million (FPKM) style data. The ESTIMATE algorithm was used for estimating the stromal and immune scores for 33 tumors. Then, we analyzed the correlation between KIF20A in pan-cancer and immune checkpoints and performed gene set enrichment analysis (GSEA) analysis on the co-expressed genes of KIF20A in pan-cancer.Results: We have confirmed that the expression of KIF20A has a intensive correlation with prognosis in 33 kinds of tumors. Its expression of KIF20A was related to a variety of immune cells and immune checkpoints. Based on the results of GSEA for further analysis, in multiple tumors, KIF20A is related to immune-related pathways.Conclusion: We have demonstrated that KIF20A played an important role in pan-cancer and could affect the occurrence or development of a variety of tumors. Moreover, KIF20A was related to immunity, and KIF20A- related immune research in pan-cancer also needs to be further demonstrate.

scholarly journals Identification and analysis of immune-related subtypes of hepatocellular carcinoma

2020 ◽  
pp. 153537022097013
Author(s):  
Qimeng Wang ◽  
Jin Huang ◽  
Huihua Zhang ◽  
Huan Liu ◽  
Min Yu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Immune Cells ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Expression Data ◽  
Ppi Network ◽  
Gene Set Enrichment ◽  
Genes Expression ◽  
Connectivity Degree ◽  
Checkpoint Genes

Hepatocellular carcinoma is a malignance that remains difficult to cure. Immunotherapy has shown its potential application in a variety of refractory malignancies. Due to the complexity of immune microenvironment of hepatocellular carcinoma, the efficacy of immunotherapy for hepatocellular carcinoma is not as effective as expected. Expression data of hepatocellular carcinoma from the TCGA and ICGC databases were used for classification and verification of hepatocellular carcinoma subtypes. The immune-related functions and pathways were identified via gene set enrichment analysis, while the sections denoting the subsets of the immune cells were estimated using the CIBERSORT algorithm. Immunity low (Immunity_L), immunity medium (Immunity_M), and immunity high (Immunity_H) were specified as the three immune-related subtypes of hepatocellular carcinoma. The quantity of stromal and immune cells was the most substantial in Immunity_H, compared to the other subtypes. Interestingly, the proportion of M0 macrophages decreased from Immunity_L to Immunity_H, while the proportion of CD8 T cells increased. Furthermore, the HLA genes expression levels, as well as those of six immune checkpoint genes were substantially lower in Immunity_L than in Immunity_H. Functional analysis was performed for 1512 differentially expressed genes between Immunity_L and Immunity_H. Finally, the PPI network was constructed with 118 nodes. The highest connectivity degree nodes were B2M, HLA-DRA, and HLA-DRB1. The above results were verified in ICGC-JP and ICGC-FR databases with a consistent trend. In this study, we divided hepatocellular carcinoma into three subtypes and explored the immune-related characteristics of these subtypes. These results may provide new insights for immunotherapy of hepatocellular carcinoma.

Identification of key mRNAs, miRNAs, and mRNA-miRNA network involved in papillary thyroid carcinoma

2020 ◽  
Vol 15 ◽  
Author(s):  
Wei Han ◽  
Dongchen Lu ◽  
Chonggao Wang ◽  
Mengdi Cui ◽  
Kai Lu
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Differential Expression Analysis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Integrated Analysis ◽  
Papillary Thyroid ◽  
Gene Set Enrichment ◽  
Mirna Expression Data

Background: In the past decades, the incidence of thyroid cancer (TC) has been gradually increasing, owing to the widespread use of ultrasound scanning devices. However, the key mRNAs, miRNAs, and mRNA-miRNA network in papillary thyroid carcinoma (PTC) has not been fully understood. Material and Methods: In this study, multiple bioinformatics methods were employed, including differential expression analysis, gene set enrichment analysis, and miRNA-mRNA interaction network construction. Results: First, we investigated the key miRNAs that regulated significantly more differentially expressed genes based on GSEA method. Second, we searched for the key miRNAs based on the mRNA-miRNA interaction subnetwork involved in PTC. We identified hsa-mir-1275, hsa-mir-1291, hsa-mir-206 and hsa-mir-375 as the key miRNAs involved in PTC pathogenesis. Conclusion: The integrated analysis of the gene and miRNA expression data not only identified key mRNAs, miRNAs, and mRNA-miRNA network involved in papillary thyroid carcinoma, but also improved our understanding of the pathogenesis of PTC.

scholarly journals Placental Transcriptome Adaptations to Maternal Nutrient Restriction in Sheep

2021 ◽  
Vol 22 (14) ◽  
pp. 7654
Author(s):  
Chelsie B. Steinhauser ◽  
Colleen A. Lambo ◽  
Katharine Askelson ◽  
Gregory W. Burns ◽  
Susanta K. Behura ◽  
...  
Keyword(s):  
Mhc Class Ii ◽  
Killer Cell ◽  
National Research Council ◽  
Enrichment Analysis ◽  
Nutrient Utilization ◽  
Gene Set Enrichment Analysis ◽  
Nutrient Restriction ◽  
Placental Development ◽  
Gene Set Enrichment ◽  
Pregnant Sheep

Placental development is modified in response to maternal nutrient restriction (NR), resulting in a spectrum of fetal growth rates. Pregnant sheep carrying singleton fetuses and fed either 100% (n = 8) or 50% (NR; n = 28) of their National Research Council (NRC) recommended intake from days 35–135 of pregnancy were used to elucidate placentome transcriptome alterations at both day 70 and day 135. NR fetuses were further designated into upper (NR NonSGA; n = 7) and lower quartiles (NR SGA; n = 7) based on day 135 fetal weight. At day 70 of pregnancy, there were 22 genes dysregulated between NR SGA and 100% NRC placentomes, 27 genes between NR NonSGA and 100% NRC placentomes, and 22 genes between NR SGA and NR NonSGA placentomes. These genes mediated molecular functions such as MHC class II protein binding, signaling receptor binding, and cytokine activity. Gene set enrichment analysis (GSEA) revealed significant overrepresentation of genes for natural-killer-cell-mediated cytotoxicity in NR SGA compared to 100% NRC placentomes, and alterations in nutrient utilization pathways between NR SGA and NR NonSGA placentomes at day 70. Results identify novel factors associated with impaired function in SGA placentomes and potential for placentomes from NR NonSGA pregnancies to adapt to nutritional hardship.

scholarly journals Comprehensive Analysis of ESRRA in Endometrial Cancer

2021 ◽  
Vol 20 ◽  
pp. 153303382199208
Author(s):  
Shufang Wang ◽  
Xinlong Huo
Keyword(s):  
Endometrial Cancer ◽  
Protein Expression ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Expression Level ◽  
Operating Characteristics ◽  
Protein Expression Level ◽  
Normal Tissues

Background: Estrogen-related receptor alpha (ESRRA) was reported to play an important role in multiple biological processes of neoplastic diseases. The roles of ESRRA in endometrial cancer have not been fully investigated yet. Methods: Expression data and clinicopathological data of patients with uteri corpus endometrial carcinoma (UCEC) were obtained from The Cancer Genome Atlas (TCGA). Comprehensive bioinformatics analysis was performed, including receiver operating characteristics (ROC) curve analysis, Kaplan-Meier survival analysis, gene ontology (GO) enrichment analysis, and Gene Set Enrichment Analysis (GSEA). Immunohistochemistry was used to detect the protein expression level of ESRRA and CCK-8 assay was performed to evaluate the effect of ESRRA on the proliferation ability. Results: A total of 552 UCEC tissues and 35 normal tissues were obtained from the TCGA database. The mRNA and protein expression level of ESRRA was highly elevated in UCEC compared with normal tissues, and was closely associated with poor prognosis. ROC analysis indicated a very high diagnostic value of ESRRA for patients with UCEC. GO and GSEA functional analysis showed that ESRRA might be mainly involved in cellular metabolism processes, in turn, tumorigenesis and progression of UCEC. Knockdown of ESRRA inhibited the proliferation of UCEC cells in vitro. Further immune cell infiltration demonstrated that ESRRA enhanced the infiltration level of neutrophil cell and reduced that of T cell (CD4+ naïve), NK cell, and cancer associated fibroblast (CAF). The alteration of immune microenvironment will greatly help in developing immune checkpoint therapy for UCEC. Conclusions: Our study comprehensively analyzed the expression level, clinical value, and possible mechanisms of action of ESRRA in UCEC. These findings showed that ESRRA might be a potential diagnostic and therapeutic target.

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.

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