Placental Transcriptome Adaptations to Maternal Nutrient Restriction in 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.

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

Current Bioinformatics ◽

10.2174/1574893615999200608125427 ◽

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.

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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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Protein–protein interaction network analysis and gene set enrichment analysis in epilepsy patients with brain cancer

Journal of Clinical Neuroscience ◽

10.1016/j.jocn.2013.06.026 ◽

2014 ◽

Vol 21 (2) ◽

pp. 316-319 ◽

Cited By ~ 7

Author(s):

Bin Kong ◽

Tao Yang ◽

Lin Chen ◽

Yong-qin Kuang ◽

Jian-wen Gu ◽

...

Keyword(s):

Network Analysis ◽

Protein Interaction ◽

Brain Cancer ◽

Protein Interaction Network ◽

Interaction Network ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Protein Protein Interaction ◽

Protein Protein Interaction Network

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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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A Six-Gene Prognostic Risk Prediction Model In Hepatitis B Virus-Associated Hepatocellular Carcinoma

Clinical & Investigative Medicine ◽

10.25011/cim.v44i3.37124 ◽

2021 ◽

Vol 44 (3) ◽

pp. E32-44

Author(s):

Jia Shen ◽

Ming Shu ◽

Shujie Xie ◽

Jia Yan ◽

Kaile Pan ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Prognostic Model ◽

Prognostic Score ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Training Set ◽

Gene Set Enrichment ◽

B Virus ◽

Score Model ◽

Normal Controls

Purpose: This study aimed to screen hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC)-related feature ribonucleic acids (RNAs) and to establish a prognostic model. Methods: The transcriptome expression data of HBV-associated HCC were downloaded from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus database. Differential RNAs between HBV-associated HCC and normal controls were identified by a meta-analysis of TCGA, GSE55092 and GSE121248. Weighted gene co-expression network analysis was performed to identify key RNAs and modules. A prognostic score model was established using TCGA as a training set by Cox regression analysis and was validated in E-TABM-36 dataset. Additionally, independent prognostic clinical factors were screened, and the function of lncRNAs waspredicted through Gene Set Enrichment Analysis. Results: A total of 710 consistent differential RNAs between HBV-associated HCC and normal controls were obtained, including five lncRNAs and 705 mRNAs. An optimized combination of six differential RNAs (DSCR4, DBH, ECM1, GDAP1, MATR3 and RFC4) was selected and a prognostic score model was constructed. Kaplan-Meier analysis demonstrated that the prognosis of the high-risk and low-risk groups separated by this model was significantly different in the training set and the validation set. Gene Set Enrichment Analysis showed that the co-expression genes of DSCR4 were significantly correlated with neuroactive ligand receptor interactionpathway. Conclusion: A prognostic model based on DSCR4, DBH, ECM1, GDAP1, MATR3 and RFC4 was developed that can accurately predict the prognosis of patients with HBV-associated HCC. These genes, as well as histologic grade, may serve as independent prognostic factors in HBV-associated HCC.

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A Hypoxia-related LncRNA Signature Predicts Survival of Primary Lower-grade glioma

10.21203/rs.3.rs-335140/v1 ◽

2021 ◽

Author(s):

Yanjia Hu ◽

Jing Zhang ◽

Jing Chen

Keyword(s):

High Risk ◽

Risk Score ◽

Cox Regression ◽

Risk Group ◽

Enrichment Analysis ◽

High Risk Group ◽

Gene Set Enrichment Analysis ◽

Lower Grade ◽

Prognostic Signature ◽

Gene Set Enrichment

Abstract Background Hypoxia-related long non-coding RNAs (lncRNAs) have been proven to play a role in multiple cancers and can serve as prognostic markers. Lower-grade gliomas (LGGs) are characterized by large heterogeneity. Methods This study aimed to construct a hypoxia-related lncRNA signature for predicting the prognosis of LGG patients. Transcriptome and clinical data of LGG patients were obtained from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). LGG cohort in TCGA was chosen as training set and LGG cohorts in CGGA served as validation sets. A prognostic signature consisting of fourteen hypoxia-related lncRNAs was constructed using univariate and LASSO Cox regression. A risk score formula involving the fourteen lncRNAs was developed to calculate the risk score and patients were classified into high- and low-risk groups based on cutoff. Kaplan-Meier survival analysis was used to compare the survival between two groups. Cox regression analysis was used to determine whether risk score was an independent prognostic factor. A nomogram was then constructed based on independent prognostic factors and assessed by C-index and calibration plot. Gene set enrichment analysis and immune cell infiltration analysis were performed to uncover further mechanisms of this lncRNA signature. Results LGG patients with high risk had poorer prognosis than those with low risk in both training and validation sets. Recipient operating characteristic curves showed good performance of the prognostic signature. Univariate and multivariate Cox regression confirmed that the established lncRNA signature was an independent prognostic factor. C-index and calibration plots showed good predictive performance of nomogram. Gene set enrichment analysis showed that genes in the high-risk group were enriched in apoptosis, cell adhesion, pathways in cancer, hypoxia etc. Immune cells were higher in high-risk group. Conclusion The present study showed the value of the 14-lncRNA signature in predicting survival of LGGs and these 14 lncRNAs could be further investigated to reveal more mechanisms involved in gliomas.

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CBIO-20. HIGH LEVELS OF TERT CONFER SENSITIVITY TO THE DNA HYPOMETHYLATING AGENT DECITABINE (DAC) IN GLIOMAS

Neuro-Oncology ◽

10.1093/neuonc/noab196.120 ◽

2021 ◽

Vol 23 (Supplement_6) ◽

pp. vi31-vi31

Author(s):

Jong-Whi Park ◽

Felix Sahm ◽

Bianca Steffl ◽

Isabel Arrillaga-Romany ◽

Daniel Cahill ◽

...

Keyword(s):

Enrichment Analysis ◽

Soft Agar ◽

Gene Set Enrichment Analysis ◽

Preclinical Model ◽

Gene Set Enrichment ◽

Chromosome 1P ◽

Activating Mutations ◽

Molecular Determinants ◽

Tert Expression ◽

Mutant Chromosome

Abstract BACKGROUND Decitabine (DAC)-incorporated DNA binds DNMT1 enzyme and subsequently triggers DNMT1 degradation. Previously, we showed that DAC can mediate the anti-tumor effect in a preclinical model of IDH-mutant gliomas. Here, we further investigate molecular determinants of response to DAC in gliomas. METHODS DAC response was assessed by soft agar anchorage independent growth assays and cell proliferation measurements. Patient-derived IDH-mutant chromosome 1p/19q codeleted (codel) and non-codel glioma lines upon vehicle and DAC treatment were used for RNA sequencing and Gene Set Enrichment Analysis (GSEA). RESULTS We found that DAC treatment is effective in high TERT-expressing gliomas including IDH-mutant and IDH-wildtype glioma lines. In contrast, pharmacological inhibition of TERT reduces DAC response in glioma lines. Interestingly, transcriptomic profiling showed that DAC reduces the expression of TERT, along with increased CDKN1A/p21 expression. We experimentally validated that TERT expression depends on CDKN1A/p21. Furthermore, p53 is required for DAC-mediated CDKN1A/p21 induction. Importantly, DAC-mediated proliferation defects in TERT-proficient glioma cells are abolished by DNMT1 knockdown, indicative of an expected DAC mechanism. CONCLUSIONS DAC could elicit the pronounced anti-tumor response in IDH-mutant codel oligodendroglioma and IDH-wildtype glioblastoma with TERT activating mutations.

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Effects of Pseudorabies Virus Infection on the Tracheobronchial Lymph Node Transcriptome

Bioinformatics and Biology Insights ◽

10.4137/bbi.s30522 ◽

2015 ◽

Vol 9s2 ◽

pp. BBI.S30522 ◽

Cited By ~ 2

Author(s):

Laura C. Miller ◽

Darrell O. Bayles ◽

Eraldo L. Zanella ◽

Kelly M. Lager

Keyword(s):

Pseudorabies Virus ◽

Statistical Tests ◽

Digital Gene Expression ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Post Inoculation ◽

Gene Set Enrichment ◽

Tracheobronchial Lymph Node ◽

Base Sequences ◽

Tracheobronchial Lymph Nodes

This study represents the first swine transcriptome hive plots created from gene set enrichment analysis (GSEA) data and provides a novel insight into the global transcriptome changes occurring in tracheobronchial lymph nodes (TBLN) and spanning the swine genome. RNA isolated from draining TBLN from 5-week-old pigs, either clinically infected with a feral isolate of Pseudorabies virus or uninfected, was interrogated using Illumina Digital Gene Expression Tag Profiling. More than 100 million tag sequences were observed, representing 4,064,189 unique 21-base sequences collected from TBLN at time points 1, 3, 6, and 14 days post-inoculation (dpi). Multidimensional statistical tests were applied to determine the significant changes in tag abundance, and then the tags were annotated. Hive plots were created to visualize the differential expression within the swine transcriptome defined by the Broad Institute's GSEA reference datasets between infected and uninfected animals, allowing us to directly compare different conditions.

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