scholarly journals Transcriptional Profiling Reveals Kidney Neutrophil Heterogeneity in Both Healthy People and ccRCC Patients

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Yiliang Meng ◽  
Kai Cai ◽  
Jingjie Zhao ◽  
Keyu Huang ◽  
Xiumei Ma ◽  
...  
Keyword(s):  
Transcriptional Profiling ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Other ◽  
Renal Diseases ◽  
Gene Set Enrichment ◽  
Cell Renal Cell Carcinoma ◽  
Tumor Pathology ◽  
Healthy Donors ◽  
Immune Therapies

Neutrophil is known to critically impact the development of renal diseases (e.g., the clear cell renal cell carcinoma (ccRCC)), whereas the heterogeneity of neutrophils in ccRCC remains unclear. In the present study, kidney biopsies from healthy donors and ccRCC tissues were collected for single-cell RNA sequencing (scRNA-seq). In addition, the subpopulations of neutrophils in a healthy kidney and in the tumor microenvironment (TME) of ccRCC were expressed and then analyzed. The genes reported previously were mapped to all subpopulations identified here. On that basis, biological theme comparison and Gene Set Enrichment Analysis (GSEA) were employed to reveal and compare relevant biological functions. In a healthy kidney, neutrophils exhibit two subpopulations: one is more associated with renal autoimmunity, probably acting as therapeutic target; the other is suggested to resist infectious microorganisms. It is noteworthy that six subpopulations were identified in ccRCC biopsy, and two were more relevant to autoimmunity, while the other four are more relevant to the tumor pathology. Besides, ccRCC neutrophil could resist anticancer immune therapies of ipilimumab and pembrolizumab for their low/no expressions of CTLA-4, PD-1, and PD-L1. Thus, this study can help understand the heterogeneity and pathological significance of neutrophils in renal diseases.

Next Generation Sequencing reveals profound transcriptomic differences between reticulated and non-reticulated platelets from healthy donors, CCS- and STEMI patients

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
L Hille ◽  
T.G Nuehrenberg ◽  
L Hein ◽  
F.J Neumann ◽  
D Trenk
Keyword(s):  
Healthy Subjects ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Gene Set Enrichment ◽  
Reticulated Platelets ◽  
Gene Sets ◽  
Healthy Donors ◽  
Go Terms ◽  
Generation Sequencing

Abstract Background The youngest circulating platelets – so called reticulated platelets (RP) – represent a highly prothrombotic platelet subpopulation. Previous studies showed that patients with chronic coronary syndrome (CCS) as well as patients with ST-elevation myocardial infarction (STEMI) have higher amounts of RP compared to healthy subjects. It has been suggested that intrinsic properties of RP impact on cardiovascular risk. However, it is unknown if transcriptomic alterations contribute to the prothrombotic properties of RP. Purpose This study sought to investigate differences in the transcriptomic landscape of sorted RP versus non-RP, i.e. young and old platelets, in healthy subjects, CCS- and STEMI-patients. Methods Blood samples were obtained from healthy subjects as well as from patients with CCS/STEMI (n=8 each) the day after PCI. After staining with SYTO 13, platelets from each donor were sorted into a RP and a non-RP fraction based on their RNA-content. Next Generation Sequencing (NGS) was applied to generate sequencing reads for sorted RP and non-RP from the 3 cohorts. Data was analyzed by use of the Freiburg bioinformatics platform “Galaxy”. Results Investigation of transcriptomic alterations in non-RP versus RP by differential gene expression analysis revealed a total number of 2,476 transcripts that were differentially expressed in platelets from healthy donors, 2,075 in CCS-patients and 1,852 in STEMI patients, respectively (adj. p<0.05 in all analyses). Comparison of these transcripts revealed a large overlap of 500 mRNAs which were downregulated and 660 mRNAs which were upregulated in RP in all 3 cohorts. However, there are also distinct groups of transcripts that are differentially expressed in only one of the 3 cohorts. Gene ontology (GO)-analysis of the 500 uniformly enriched transcripts in RP yielded 38 overrepresented GO-terms. A large group was related to cytoskeleton and shape change. Furthermore, GO-terms associated to the platelet activation cascade were overrepresented. Upregulated transcripts included well-known examples like GP6 and GP9, P-selectin, integrin β3, integrin a-IIb, and tubulin α4a. GO-analysis of enriched transcripts in non-RP showed a large group associated to mitosis and cell nucleus/DNA which is surprising since platelets neither contain DNA nor a nucleus. Gene set enrichment analysis (GSEA) determined higher normalized enrichment scores for several gene sets associated to platelet degranulation, aggregation and activation in the STEMI-cohort. Gene sets affecting cell adhesion and platelet calcium homeostasis were overexpressed in particular in CCS-patients. Conclusion NGS-results indicate a highly prothrombotic transcriptome of RP from each cohort with high amounts of differentially expressed transcripts overlapping. However, GSEA identified gene sets that are particularly overexpressed in CCS- or STEMI-patients which might contribute to platelet hyperreactivity in these cohorts. Gene set enrichment analysis Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): PharmCompNet Baden-Wuerttemberg: Kompetenznetzwerk Pharmakologie Baden-Wuerttemberg - Wirkstoffnetzwerke als Grundlagen der individualisierten Arzneistofftherapie

Gene set enrichment analysis and ingenuity pathway analysis of metastatic clear cell renal cell carcinoma cell line

2016 ◽  
Vol 311 (2) ◽  
pp. F424-F436 ◽  
Author(s):  
Mohammed I. Khan ◽  
Konrad J. Dębski ◽  
Michał Dabrowski ◽  
Anna M. Czarnecka ◽  
Cezary Szczylik
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Cell Line ◽  
Pathway Analysis ◽  
Renal Cell ◽  
Clear Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Cell Renal Cell Carcinoma

In recent years, genome-wide RNA expression analysis has become a routine tool that offers a great opportunity to study and understand the key role of genes that contribute to carcinogenesis. Various microarray platforms and statistical approaches can be used to identify genes that might serve as prognostic biomarkers and be developed as antitumor therapies in the future. Metastatic renal cell carcinoma (mRCC) is a serious, life-threatening disease, and there are few treatment options for patients. In this study, we performed one-color microarray gene expression (4×44K) analysis of the mRCC cell line Caki-1 and the healthy kidney cell line ASE-5063. A total of 1,921 genes were differentially expressed in the Caki-1 cell line (1,023 upregulated and 898 downregulated). Gene Set Enrichment Analysis (GSEA) and Ingenuity Pathway Analysis (IPA) approaches were used to analyze the differential-expression data. The objective of this research was to identify complex biological changes that occur during metastatic development using Caki-1 as a model mRCC cell line. Our data suggest that there are multiple deregulated pathways associated with metastatic clear cell renal cell carcinoma (mccRCC), including integrin-linked kinase (ILK) signaling, leukocyte extravasation signaling, IGF-I signaling, CXCR4 signaling, and phosphoinositol 3-kinase/AKT/mammalian target of rapamycin signaling. The IPA upstream analysis predicted top transcriptional regulators that are either activated or inhibited, such as estrogen receptors, TP53, KDM5B, SPDEF, and CDKN1A. The GSEA approach was used to further confirm enriched pathway data following IPA.

scholarly journals Pyroptosis Regulators and Tumor Microenvironment Infiltration Characterization in Clear Cell Renal Cell Carcinoma

2022 ◽  
Vol 11 ◽  
Author(s):  
Xi Zhang ◽  
Xiyi Wei ◽  
Yichun Wang ◽  
Shuai Wang ◽  
Chengjian Ji ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Gene Set Enrichment ◽  
Cell Renal Cell Carcinoma ◽  
Gene Set

BackgroundIt is well known that chronic inflammation can promote the occurrence and progression of cancer. As a type of proinflammatory death, pyroptosis can recast a suitable microenvironment to promote tumor growth. However, the potential role of pyroptosis in clear cell renal cell carcinoma (ccRCC) remains unclear.MethodsThe transcriptome expression profile and mutation profile data of ccRCC with clinical characteristics included in this study were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Consensus clustering was used for clustering. Gene set enrichment analysis (GSEA) analysis were applied to evaluate the biological mechanisms. Single sample gene set enrichment analysis (ssGSEA) was applied for evaluating the proportion of various immune infiltrating cells. The ESTIMATE algorithm was involved to compute the immune microenvironment scores.ResultsAmong the 17 pyroptosis regulators, a total of 15 pyroptosis regulators were differential expressed between tumor and normal tissues, in which 12 of them emerged strong correlations with prognoses. According to the pyroptosis components, the ccRCC patients were divided into four pyroptosis subtypes with different clinical, molecular, and pathway characteristics. Compared with other clusters, cluster B showed the pyroptosis heat phenotype, while cluster D represented the pyroptosis cold phenotype with poor overall survival. In addition, we performed principal component analysis (PCA) on the differential genes between clusters to construct the pyroptosis index. Furthermore, the pyroptosis index was significantly correlated with survival in different tumor mutation statuses and different grades and stages. Besides, the expression of pyroptosis-related regulators was related to the infiltration of immune cells and the expression of immune checkpoints, among which AIM2 was considered as the most significant immune-related pyroptosis regulator. Ultimately, we found that AIM2 was related to the immune activation pathway and was significantly overexpressed in tumor tissues.ConclusionThis study revealed that pyroptosis regulators and pyroptosis index played an important role in the development and prognoses of ccRCC. Moreover, AIM2 can be used as a predictor of the response of immunotherapy. Assessing the pyroptosis patterns may help evaluate the tumor status and guide immunotherapy strategies.

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 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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