scholarly journals Transcriptomic Mapping of Neural Diversity, Differentiation and Functional Trajectory in iPSC-Derived 3D Brain Organoid Models

Cells ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 3422
Author(s):  
Kiavash Kiaee ◽  
Yasamin A. Jodat ◽  
Nicole J. Bassous ◽  
Navneet Matharu ◽  
Su Ryon Shin
Keyword(s):  
Principal Component ◽  
Enrichment Analysis ◽  
Experimental Models ◽  
Developmental Trajectory ◽  
Gene Set Enrichment Analysis ◽  
Functional Genes ◽  
Specific Gene ◽  
Regulatory Pathways ◽  
Brain Organoid

Experimental models of the central nervous system (CNS) are imperative for developmental and pathophysiological studies of neurological diseases. Among these models, three-dimensional (3D) induced pluripotent stem cell (iPSC)-derived brain organoid models have been successful in mitigating some of the drawbacks of 2D models; however, they are plagued by high organoid-to-organoid variability, making it difficult to compare specific gene regulatory pathways across 3D organoids with those of the native brain. Single-cell RNA sequencing (scRNA-seq) transcriptome datasets have recently emerged as powerful tools to perform integrative analyses and compare variability across organoids. However, transcriptome studies focusing on late-stage neural functionality development have been underexplored. Here, we combine and analyze 8 brain organoid transcriptome databases to study the correlation between differentiation protocols and their resulting cellular functionality across various 3D organoid and exogenous brain models. We utilize dimensionality reduction methods including principal component analysis (PCA) and uniform manifold approximation projection (UMAP) to identify and visualize cellular diversity among 3D models and subsequently use gene set enrichment analysis (GSEA) and developmental trajectory inference to quantify neuronal behaviors such as axon guidance, synapse transmission and action potential. We showed high similarity in cellular composition, cellular differentiation pathways and expression of functional genes in human brain organoids during induction and differentiation phases, i.e., up to 3 months in culture. However, during the maturation phase, i.e., 6-month timepoint, we observed significant developmental deficits and depletion of neuronal and astrocytes functional genes as indicated by our GSEA results. Our results caution against use of organoids to model pathophysiology and drug response at this advanced time point and provide insights to tune in vitro iPSC differentiation protocols to achieve desired neuronal functionality and improve current protocols.

Epithelial Organotypic Cultures: A Viable Model to Address Mechanisms of Carcinogenesis by Epitheliotropic Viruses

2018 ◽  
Vol 18 (4) ◽  
pp. 246-255 ◽  
Author(s):  
Lara Termini ◽  
Enrique Boccardo
Keyword(s):  
Three Dimensional ◽  
Cell Types ◽  
Experimental Models ◽  
Biological Research ◽  
Specific Gene ◽  
Specific Cell ◽  
Organotypic Cultures ◽  
Skin Physiology

In vitro culture of primary or established cell lines is one of the leading techniques in many areas of basic biological research. The use of pure or highly enriched cultures of specific cell types obtained from different tissues and genetics backgrounds has greatly contributed to our current understanding of normal and pathological cellular processes. Cells in culture are easily propagated generating an almost endless source of material for experimentation. Besides, they can be manipulated to achieve gene silencing, gene overexpression and genome editing turning possible the dissection of specific gene functions and signaling pathways. However, monolayer and suspension cultures of cells do not reproduce the cell type diversity, cell-cell contacts, cell-matrix interactions and differentiation pathways typical of the three-dimensional environment of tissues and organs from where they were originated. Therefore, different experimental animal models have been developed and applied to address these and other complex issues in vivo. However, these systems are costly and time consuming. Most importantly the use of animals in scientific research poses moral and ethical concerns facing a steadily increasing opposition from different sectors of the society. Therefore, there is an urgent need for the development of alternative in vitro experimental models that accurately reproduce the events observed in vivo to reduce the use of animals. Organotypic cultures combine the flexibility of traditional culture systems with the possibility of culturing different cell types in a 3D environment that reproduces both the structure and the physiology of the parental organ. Here we present a summarized description of the use of epithelial organotypic for the study of skin physiology, human papillomavirus biology and associated tumorigenesis.

scholarly journals TNF-α Triggers RIP1/FADD/Caspase-8-Mediated Apoptosis of Astrocytes and RIP3/MLKL-Mediated Necroptosis of Neurons Induced by Angiostrongylus cantonensis Infection

2021 ◽  
Author(s):  
Hongli Zhou ◽  
Minyu Zhou ◽  
Yue Hu ◽  
Yanin Limpanon ◽  
Yubin Ma ◽  
...  
Keyword(s):  
Cell Death ◽  
Enrichment Analysis ◽  
Angiostrongylus Cantonensis ◽  
Gene Set Enrichment Analysis ◽  
Caspase 8 ◽  
Cns Injury ◽  
Vitro Assay ◽  
Tnf Α

AbstractAngiostrongylus cantonensis (AC) can cause severe eosinophilic meningitis or encephalitis in non-permissive hosts accompanied by apoptosis and necroptosis of brain cells. However, the explicit underlying molecular basis of apoptosis and necroptosis upon AC infection has not yet been elucidated. To determine the specific pathways of apoptosis and necroptosis upon AC infection, gene set enrichment analysis (GSEA) and protein–protein interaction (PPI) analysis for gene expression microarray (accession number: GSE159486) of mouse brain infected by AC revealed that TNF-α likely played a central role in the apoptosis and necroptosis in the context of AC infection, which was further confirmed via an in vivo rescue assay after treating with TNF-α inhibitor. The signalling axes involved in apoptosis and necroptosis were investigated via immunoprecipitation and immunoblotting. Immunofluorescence was used to identify the specific cells that underwent apoptosis or necroptosis. The results showed that TNF-α induced apoptosis of astrocytes through the RIP1/FADD/Caspase-8 axis and induced necroptosis of neurons by the RIP3/MLKL signalling pathway. In addition, in vitro assay revealed that TNF-α secretion by microglia increased upon LSA stimulation and caused necroptosis of neurons. The present study provided the first evidence that TNF-α was secreted by microglia stimulated by AC infection, which caused cell death via parallel pathways of astrocyte apoptosis (mediated by the RIP1/FADD/caspase-8 axis) and neuron necroptosis (driven by the RIP3/MLKL complex). Our research comprehensively elucidated the mechanism of cell death after AC infection and provided new insight into targeting TNF-α signalling as a therapeutic strategy for CNS injury.

Transmembrane p24 Trafficking Protein 2 Regulates Inflammation Through the TLR4/NF-κB Signaling Pathway in Lung Adenocarcinoma

2021 ◽  
Author(s):  
Longhua Feng ◽  
Pengjiang Cheng ◽  
Zhengyun Feng ◽  
Xiaoyu Zhang
Keyword(s):  
Lung Adenocarcinoma ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Inflammatory Factors ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
New Strategy

Abstract Background: To investigate the role of transmembrane p24 trafficking protein 2 (TMED2) in lung adenocarcinoma (LUAD) and determine whether TMED2 knockdown could inhibit LUAD in vitro and in vivo.Methods: TIMER2.0, Kaplan-Meier plotter, gene set enrichment analysis (GSEA), Target Gene, and pan-cancer systems were used to predict the potential function of TMED2. Western blotting and immunohistochemistry were performed to analyze TMED2 expression in different tissues or cell lines. The proliferation, development, and apoptosis of LUAD were observed using a lentivirus-mediated TMED2 knockdown. Bioinformatics and western blot analysis of TMED2 against inflammation via the TLR4/NF-κB signaling pathway were conducted. Results: TMED2 expression in LUAD tumor tissues was higher than that in normal tissues and positively correlated with poor survival in lung cancer and negatively correlated with apoptosis in LUAD. The expression of TMED2 was higher in tumors or HCC827 cells. TMED2 knockdown inhibited LUAD development in vitro and in vivo and increased the levels of inflammatory factors via the TLR4/NF-κB signaling pathway. TMED2 was correlated with TME, immune score, TME-associated immune cells, their target markers, and some mechanisms and pathways, as determined using the TIMER2.0, GO, and KEGG assays.Conclusions: TMED2 may regulate inflammation in LUAD through the TLR4/NF-κB signaling pathway, and enhance the proliferation, development, and prognosis of LUAD by regulating inflammation, which provide a new strategy for treating LUAD by regulating inflammation.

scholarly journals Bioinformatics-based Screening of Key Genes for Saponin Metabolism in Quinoa

2021 ◽  
Author(s):  
Chengang Guo ◽  
Zhimin wei ◽  
Wei Lyu ◽  
Yanlou Geng
Keyword(s):  
Differentially Expressed Genes ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Hierarchical Cluster ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Differential Analysis ◽  
Rna Seq ◽  
Protein Coding ◽  
Key Genes

Abstract Quinoa saponins have complex, diverse and evident physiologic activities. However, the key regulatory genes for quinoa saponin metabolism are not yet well studied. The purpose of this study was to explore genes closely related to quinoa saponin metabolism. In this study, the significantly differentially expressed genes in yellow quinoa were firstly screened based on RNA-seq technology. Then, the key genes for saponin metabolism were selected by gene set enrichment analysis (GSEA) and principal component analysis (PCA) statistical methods. Finally, the specificity of the key genes was verified by hierarchical clustering. The results of differential analysis showed that 1654 differentially expressed genes were achieved after pseudogenes deletion. Therein, there were 142 long non-coding genes and 1512 protein-coding genes. Based on GSEA analysis, 116 key candidate genes were found to be significantly correlated with quinoa saponin metabolism. Through PCA dimension reduction analysis, 57 key genes were finally obtained. Hierarchical cluster analysis further demonstrated that these key genes can clearly separate the four groups of samples. The present results could provide references for the breeding of sweet quinoa and would be helpful for the rational utilization of quinoa saponins.

scholarly journals Benchmarking substrate-based kinase activity inference using phosphoproteomic data

2016 ◽  
Author(s):  
Claudia Hernandez-Armenta ◽  
David Ochoa ◽  
Emanuel Gonçalves ◽  
Julio Saez-Rodriguez ◽  
Pedro Beltrao
Keyword(s):  
Kinase Activity ◽  
Multiple Linear Regression Model ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Target Sequence ◽  
Sequence Specificity ◽  
Gold Standard Dataset ◽  
Kolmogorov Smirnov

AbstractMotivationPhosphoproteomic experiments are increasingly used to study the changes in signalling occurring across different conditions. It has been proposed that changes in phosphorylation of kinase target sites can be used to infer when a kinase activity is under regulation. However, these approaches have not yet been benchmarked due to a lack of appropriate benchmarking strategies.ResultsWe curated public phosphoproteomic experiments to identify a gold standard dataset containing a total of 184 kinase-condition pairs where regulation is expected to occur. A list of kinase substrates was compiled and used to estimate changes in kinase activities using the following methods: Z-test, Kolmogorov Smirnov test, Wilcoxon rank sum test, gene set enrichment analysis (GSEA), and a multiple linear regression model (MLR). We also tested weighted variants of the Z-test, and GSEA that include information on kinase sequence specificity as proxy for affinity. Finally, we tested how the number of known substrates and the type of evidence (in vivo, in vitro or in silico) supporting these influence the predictions.ConclusionsMost models performed well with the Z-test and the GSEA performing best as determined by the area under the ROc curve (Mean AUC=0.722). Weighting kinase targets by the kinase target sequence preference improves the results only marginally. However, the number of known substrates and the evidence supporting the interactions has a strong effect on the predictions.

scholarly journals Prognostic value of an immune long non-coding RNA signature in liver hepatocellular carcinoma

2019 ◽  
Author(s):  
rui kong ◽  
Nan Wang ◽  
Wei Han ◽  
Yuejuan Zheng ◽  
Jie Lu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Risk Groups ◽  
Gene Set Enrichment Analysis ◽  
Kaplan Meier ◽  
Non Coding Rna ◽  
Liver Hepatocellular Carcinoma ◽  
Long Non Coding Rna

Abstract Background: In recent years, long non-coding RNAs (lncRNAs) are emerging as crucial regulators in the immunological process of liver hepatocellular carcinoma (LIHC). Increasing studies have found that some lncRNAs could be used as a diagnostic or therapeutic target for clinical management, but little research has investigated the role of immune-related lncRNA in tumor prognosis. In this study, we aimed to develop an immune lncRNA signature for the precise diagnosis and prognosis of liver hepatocellular carcinoma. Methods: Gene expression profiles of LIHC samples obtained from TCGA were screened for immune-related genes using two reference gene sets. The optimal immune-related lncRNA signature was built via correlational analysis, univariate and multivariate cox analysis. Then the Kaplan-Meier plot, ROC curve, clinical analysis, gene set enrichment analysis, and principal component analysis were carried out to evaluate the capability of immune lncRNA signature as a prognostic indicator. Results: Six long non-coding RNA MSC−AS1, AC009005.1, AL117336.3, AL031985.3, AL365203.2, AC099850.3 were identified via correlation analysis and cox regression analysis considering their interactions with immune genes. Next, tumor samples were separated into two risk groups by the signature with different clinical outcomes. Stratification analysis showed the prognostic ability of this signature acted as an independent factor. The AUC value of ROC curve was 0.779. The Kaplan-Meier method was used in survival analysis and results showed a statistical difference between the two risk groups. The predictive performance of this signature was validated by principal component analysis (PCA). Data from gene set enrichment analysis (GSEA) further unveiled several potential biological processes of these biomarkers may involve in. Conclusion: In summary, the study demonstrated the potential role of the six-lncRNA signature served as an independent prognostic factor for LIHC patients.

scholarly journals Norepinephrine exposure restrains endometrial decidualization in early pregnancy

2021 ◽  
Author(s):  
Jiju Wang ◽  
Yuhui Tang ◽  
Songcun Wang ◽  
Liyuan Cui ◽  
Da-Jin Li ◽  
...  
Keyword(s):  
Stromal Cells ◽  
Adrenergic Receptor ◽  
Enrichment Analysis ◽  
Normal Pregnancy ◽  
Receptor Expression ◽  
Gene Set Enrichment Analysis ◽  
Endometrial Stromal Cells ◽  
Significant Enrichment

Previous studies have focused on the role of norepinephrine on arrhythmias, generalized anxiety disorder, and cancer. This study aimed to investigate the effect of norepinephrine on endometrial decidualization. Artificial decidualization and norepinephrine-treated mice were established in vivo. In vitro, human endometrial stromal cells were treated with MPA and cAMP to induce decidualization. Decidual markers and important signaling molecules during decidualization were detected using quantitative real-time polymerase chain reaction and Western blot. RNA sequencing was performed to determine related signaling pathways. Exposure of excess norepinephrine significantly restricted the induced expression of decidualized markers Dtprp, BMP2, WNT4, and Hand2 in mice. In vitro, 10 µM norepinephrine markedly downregulated the expressions of prolactin, IGFBP1, and PLZF, which are the specifical markers of decidual stromal cells during decidualization. The gene set enrichment analysis showed that a significant enrichment in neuroactive ligand–receptor interactions of norepinephrine treatment group. The α1b-adrenergic receptor expression was upregulated by norepinephrine. Interestingly, norepinephrine did not inhibit the expression of IGFBP1 in endometrial stromal cells after silencing α1b-adrenergic receptor, while significantly suppressed the induced decidualization with overexpression of α1b-adrenergic receptor. When α1b-adrenergic receptor was activated, endometrial p-PKC was significantly increased under post-treatment with norepinephrine in vivo and in vitro. In addition, norepinephrine treatment inhibited embryo and fetal development using a normal pregnancy model. Therefore, norepinephrine exposure inhibited endometrial decidualization through the activation of the PKC signaling pathway by upregulating α1b-adrenergic receptor. Our study could explain some female reproductive problems due to stress and provide some novel strategies for this disorder.

The Role of PAX2 in Breast Cancer: A Study Based on Bioinformatics Analysis and in Vitro Validation

2021 ◽  
Author(s):  
Shan Yang ◽  
Wei Gao ◽  
Haoqi Wang ◽  
Xi Zhang ◽  
Yunzhe Mi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cell Growth ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Migration And Invasion ◽  
Clinical Samples

Abstract Background: Breast cancer (BC) is the most frequently diagnosed cancer in women and is the second most common cancer among newly diagnosed cancers worldwide. Studies have shown that paired box 2 (PAX2) participates in the tumorigenesis of some cancer cells. However, the functions of PAX2 in the BC context are still unclear.Methods: Transcriptome expression profiles and clinicopathological information of BC were download from the TCGA database. Then the expression level and prognostic value in TCGA database were explored. Gene Set Enrichment Analysis (GSEA) and functional enrichment analysis were performed to investigate the functions and pathways of PAX2. Moreover, RT-qPCR was used to determine the expression of PAX2 in BC tissues, and the predictive value of PAX2 in clinical samples was assessed. CCK-8 assay was used to evaluate cell growth. The migration and invasion capacities of cells were assessed by wound healing assay and Transwell assay.Results: PAX2 was up-regulated in the TCGA-BC datasets. GSEA analysis suggested that PAX2 might be involved in the regulation of MAPK signaling pathways and so on. Moreover, PAX2 was overexpressed in BC tissues, and PAX2 expression was associated with menopause. PAX2 deficiency could inhibit the growth, migration, and invasion of BC cells.Conclusion: This study suggested that PAX2 was up-regulated in BC, which inhibited BC cell growth, migration, and invasion. Thus, PAX2 could be a potential therapeutic target for BC.

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.

Connecting gene expression subtypes of colorectal cancer (CRC) with cell lines and drug resistance.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. e14544-e14544
Author(s):  
Eva Budinska ◽  
Jenny Wilding ◽  
Vlad Calin Popovici ◽  
Edoardo Missiaglia ◽  
Arnaud Roth ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Line ◽  
Clinical Significance ◽  
Cell Lines ◽  
Drug Response ◽  
Drug Sensitivity ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis

e14544 Background: We identified CRC gene expression subtypes (ASCO 2012, #3511), which associate with established parameters of outcome as well as relevant biological motifs. We now substantiate their biological and potentially clinical significance by linking them with cell line data and drug sensitivity, primarily attempting to identify models for the poor prognosis subtypes Mesenchymal and CIMP-H like (characterized by EMT/stroma and immune-associated gene modules, respectively). Methods: We analyzed gene expression profiles of 35 publicly available cell lines with sensitivity data for 82 drug compounds, and our 94 cell lines with data on sensitivity for 7 compounds and colony morphology. As in vitro, stromal and immune-associated genes loose their relevance, we trained a new classifier based on genes expressed in both systems, which identifies the subtypes in both tissue and cell cultures. Cell line subtypes were validated by comparing their enrichment for molecular markers with that of our CRC subtypes. Drug sensitivity was assessed by linking original subtypes with 92 drug response signatures (MsigDB) via gene set enrichment analysis, and by screening drug sensitivity of cell line panels against our subtypes (Kruskal-Wallis test). Results: Of the cell lines 70% could be assigned to a subtype with a probability as high as 0.95. The cell line subtypes were significantly associated with their KRAS, BRAF and MSI status and corresponded to our CRC subtypes. Interestingly, the cell lines which in matrigel created a network of undifferentiated cells were assigned to the Mesenchymal subtype. Drug response studies revealed potential sensitivity of subtypes to multiple compounds, in addition to what could be predicted based on their mutational profile (e.g. sensitivity of the CIMP-H subtype to Dasatinib, p<0.01). Conclusions: Our data support the biological and potentially clinical significance of the CRC subtypes in their association with cell line models, including results of drug sensitivity analysis. Our subtypes might not only have prognostic value but might also be predictive for response to drugs. Subtyping cell lines further substantiates their significance as relevant model for functional studies.

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