scholarly journals FYN, SARS-CoV-2, and IFITM3 in the Neurobiology of Alzheimer’s Disease: A Regulatory Feedback Loop Governing Tau and Aβ Pathology

2020 ◽  
Author(s):  
George Vavougios ◽  
Marianthi Breza ◽  
Sofia Nikou ◽  
Karen Krogfelt
Keyword(s):  
Single Cell ◽  
Biological Networks ◽  
Meta Analysis ◽  
Temporal Cortex ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Gamma Secretase ◽  
Independent Manner

Introduction IFITM3, an innate immune protein linked to COVID-19 severity, has recently been identified as a novel γ-secretase modulator. Independent research has shown that IFITM3 may facilitate SARS-CoV-2 neurotropism in an ACE2-independent manner. In a previous study, we had detected perturbations in IFITM3 networks in both the CNS and peripheral immune cells donated by AD patients.The purpose of this study is to explore the transcriptomic evidence of the SARS-CoV-2 / IFITM3 / AD interplay, validating previous findings from our group. Methods Exploratory analyses involved meta-analysis of bulk and single cell RNA data for IFITM3 and FYN differential expression. For confirmatory analyses, we performed gene set enrichment analysis (GSEA) on an AD gene signature from AD Consensus transcriptomics; using the Enrichr platform, we scrutinized COVID-19 datasets for significant, overlapping enriched biological networks. Results Bulk RNA data analysis revealed that IFITM3 and FYN were differentially expressed in two CNS regions in AD: the temporal cortex (AD vs. Controls, adj.p-value=1.3e-6) and the parahippocampal cortex (AD vs. controls, adj.p-value=0.012). Correspondingly, single cell RNA analysis of IFITM3 and FYN revealed that it was differentially expressed in neuronal cells donated from AD patients (astrocytes, microglia and oligodendrocyte precursor cells), when compared to controls. Discussion IFITM3 and by extent FYN were found as interactors within biological networks overlapping between AD and SARS-CoV-2 infection. SARS-CoV-2 SARS-CoV-2-mediated IFITM3 induction would mechanistically result in increased Aβ production. FYN recruitment by viral processes results in abrogation of both fusion of IFITM3 vesicles with lysosomes; immunoevasion, by FYN-mediated impairment of autophagy would then serve to promote impaired detoxification from Aβ, while propagating Tau pathology in an IFITM3-independent manner.

scholarly journals Learning interpretable cellular and gene signature embeddings from single-cell transcriptomic data

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yifan Zhao ◽  
Huiyu Cai ◽  
Zuobai Zhang ◽  
Jian Tang ◽  
Yue Li
Keyword(s):  
Single Cell ◽  
Large Scale ◽  
Topic Model ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Learning Performance ◽  
Cell Type ◽  
Gene Set Enrichment ◽  
Gene Sets

AbstractThe advent of single-cell RNA sequencing (scRNA-seq) technologies has revolutionized transcriptomic studies. However, large-scale integrative analysis of scRNA-seq data remains a challenge largely due to unwanted batch effects and the limited transferabilty, interpretability, and scalability of the existing computational methods. We present single-cell Embedded Topic Model (scETM). Our key contribution is the utilization of a transferable neural-network-based encoder while having an interpretable linear decoder via a matrix tri-factorization. In particular, scETM simultaneously learns an encoder network to infer cell type mixture and a set of highly interpretable gene embeddings, topic embeddings, and batch-effect linear intercepts from multiple scRNA-seq datasets. scETM is scalable to over 106 cells and confers remarkable cross-tissue and cross-species zero-shot transfer-learning performance. Using gene set enrichment analysis, we find that scETM-learned topics are enriched in biologically meaningful and disease-related pathways. Lastly, scETM enables the incorporation of known gene sets into the gene embeddings, thereby directly learning the associations between pathways and topics via the topic embeddings.

Molecular pathways associated with micro-vascular invasion HCC.

2016 ◽  
Vol 34 (4_suppl) ◽  
pp. 249-249
Author(s):  
Caroline Yun Ling Chia ◽  
Wilson Lek Wen Tan ◽  
Nicholas Brian Shannon ◽  
Roger Sik Yin Foo ◽  
Pierce Kah Hoe Chow
Keyword(s):  
Pathway Analysis ◽  
Cell Metabolism ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Molecular Pathways ◽  
Management Options ◽  
Ampk Signaling ◽  
Cytoskeleton Organization

249 Background: Microvascular invasion (MVI) in hepatocellular carcinoma (HCC) has a reported incidence of 15-57%. It is associated with decreased overall and recurrence free survival in post-surgical resection and transplant patients. Currently, the biology of MVI+ HCC remains unknown and the absence of effective adjuvant therapy limits management options to prevent recurrence. Aim: To correlate gene signatures observed at the transcriptomic level with the presence of MVI in HCC, analyze molecular pathways with gene expression tools and validate with TCGA database. Methods: Whole genome expression was studied in two groups of Asian resected HCC tumour specimens: (i) MVI present (MVI+) (n = 14) and (ii) MVI absent (MVI-) (n = 33) both without macrovascular invasion on radiological imaging. 2 distinct pathway analysis tools – gene set enrichment analysis (GSEA) and ingenuity pathway analysis (IPA) were performed to identify significantly enriched pathways potentially explaining the observed MVI+ HCC phenotype. Selected gene sets from the identified pathways were subjected to in-silico validation with TCGA data to confirm their enrichment within MVI+ HCC. Results: Within 14 MVI+ and 33 MVI- HCC studied, we have found a total of 1401 significantly differentially expressed genes between them; 766 genes were up-regulated and 635 genes were down-regulated in MVI+ HCC. At p < 0.05 and FDR < 0.25, GSEA and IPA analyses identified enrichment of PI3K/AKT/mTOR, HIF1α, AMPK signaling and actin-mediated cell kinetics pathways: actiny, Cdc42 signaling and actin pathways regulated by Rho. A 90 gene signature derived from these enriched pathways, created on the basis of biological function was used to compare between average expression within the MVI+ vs MVI- HCCs in the TCGA Asian cohort. Genes found differentially expressed at p < 0.05 corresponded with the enriched pathways: actiny, AMPK signaling and PI3K/AKT/mTOR. Conclusions: These pathways underscore functions in regulation of cell metabolism, growth, proliferation, survival, protein synthesis and cytoskeleton organization in MVI+ HCC. Further studies in these pathways may assist in development of molecular targeted therapies for MVI+ HCC. We propose to carry out a prospective study to validate this.

scholarly journals Cyclin B1 acts as a tumor microenvironment-related cancer promoter and prognostic biomarker in hepatocellular carcinoma

2021 ◽  
Vol 49 (5) ◽  
pp. 030006052110162
Author(s):  
Yangming Hou ◽  
Xin Wang ◽  
Junwei Wang ◽  
Xuemei Sun ◽  
Xinbo Liu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Tumor Microenvironment ◽  
Proportional Hazards ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Cyclin B1 ◽  
Cox Proportional Hazards ◽  
Gene Set Enrichment Analysis ◽  
Tumor Promoter ◽  
Protein Protein Interaction

Objectives The present study aimed to develop a gene signature based on the ESTIMATE algorithm in hepatocellular carcinoma (HCC) and explore possible cancer promoters. Methods The ESTIMATE and CIBERSORT algorithms were applied to calculate the immune/stromal scores and the proportion of tumor-infiltrating immune cells (TICs) in a cohort of HCC patients. The differentially expressed genes (DEGs) were screened by Cox proportional hazards regression analysis and protein–protein interaction (PPI) network construction. Cyclin B1 (CCNB1) function was verified using experiments. Results The stromal and immune scores were associated with clinicopathological factors and recurrence-free survival (RFS) in HCC patients. In total, 546 DEGs were up-regulated in low score groups, 127 of which were associated with RFS. CCNB1 was regarded as the most predictive factor closely related to prognosis of HCC and could be a cancer promoter. Gene Set Enrichment Analysis (GSEA) and CIBERSORT analyses indicated that CCNB1 levels influenced HCC tumor microenvironment (TME) immune activity. Conclusions The ESTIMATE signature can be used as a prognosis tool in HCC. CCNB1 is a tumor promoter and contributes to TME status conversion.

scholarly journals Key pathways involved in prostate cancer based on gene set enrichment analysis and meta analysis

2011 ◽  
Vol 10 (4) ◽  
pp. 3856-3887 ◽  
Author(s):  
Q.Y. Ning ◽  
J.Z. Wu ◽  
N. Zang ◽  
J. Liang ◽  
Y.L. Hu ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Key Pathways

scholarly journals Development of a Novel Prognostic Signature Based on Antigen Processing and Presentation in Patients with Breast Cancer

2021 ◽  
Vol 27 ◽  
Author(s):  
Aoshuang Qi ◽  
Mingyi Ju ◽  
Yinfeng Liu ◽  
Jia Bi ◽  
Qian Wei ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Antigen Processing ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Prognostic Indicators ◽  
Gene Set ◽  
Antigen Processing And Presentation

Background: Complex antigen processing and presentation processes are involved in the development and progression of breast cancer (BC). A single biomarker is unlikely to adequately reflect the complex interplay between immune cells and cancer; however, there have been few attempts to find a robust antigen processing and presentation-related signature to predict the survival outcome of BC patients with respect to tumor immunology. Therefore, we aimed to develop an accurate gene signature based on immune-related genes for prognosis prediction of BC.Methods: Information on BC patients was obtained from The Cancer Genome Atlas. Gene set enrichment analysis was used to confirm the gene set related to antigen processing and presentation that contributed to BC. Cox proportional regression, multivariate Cox regression, and stratified analysis were used to identify the prognostic power of the gene signature. Differentially expressed mRNAs between high- and low-risk groups were determined by KEGG analysis.Results: A three-gene signature comprising HSPA5 (heat shock protein family A member 5), PSME2 (proteasome activator subunit 2), and HLA-F (major histocompatibility complex, class I, F) was significantly associated with OS. HSPA5 and PSME2 were protective (hazard ratio (HR) &lt; 1), and HLA-F was risky (HR &gt; 1). Risk score, estrogen receptor (ER), progesterone receptor (PR) and PD-L1 were independent prognostic indicators. KIT and ACACB may have important roles in the mechanism by which the gene signature regulates prognosis of BC.Conclusion: The proposed three-gene signature is a promising biomarker for estimating survival outcomes in BC patients.

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 Identification of a five-gene signature in association with overall survival for hepatocellular carcinoma

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11273
Author(s):  
Lei Yang ◽  
Weilong Yin ◽  
Xuechen Liu ◽  
Fangcun Li ◽  
Li Ma ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
Overall Survival ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Enrichment Score ◽  
Hub Genes ◽  
Cox Regression Analysis

Background Hepatocellular carcinoma (HCC) is considered to be a malignant tumor with a high incidence and a high mortality. Accurate prognostic models are urgently needed. The present study was aimed at screening the critical genes for prognosis of HCC. Methods The GSE25097, GSE14520, GSE36376 and GSE76427 datasets were obtained from Gene Expression Omnibus (GEO). We used GEO2R to screen differentially expressed genes (DEGs). A protein-protein interaction network of the DEGs was constructed by Cytoscape in order to find hub genes by module analysis. The Metascape was performed to discover biological functions and pathway enrichment of DEGs. MCODE components were calculated to construct a module complex of DEGs. Then, gene set enrichment analysis (GSEA) was used for gene enrichment analysis. ONCOMINE was employed to assess the mRNA expression levels of key genes in HCC, and the survival analysis was conducted using the array from The Cancer Genome Atlas (TCGA) of HCC. Then, the LASSO Cox regression model was performed to establish and identify the prognostic gene signature. We validated the prognostic value of the gene signature in the TCGA cohort. Results We screened out 10 hub genes which were all up-regulated in HCC tissue. They mainly enrich in mitotic cell cycle process. The GSEA results showed that these data sets had good enrichment score and significance in the cell cycle pathway. Each candidate gene may be an indicator of prognostic factors in the development of HCC. However, hub genes expression was weekly associated with overall survival in HCC patients. LASSO Cox regression analysis validated a five-gene signature (including CDC20, CCNB2, NCAPG, ASPM and NUSAP1). These results suggest that five-gene signature model may provide clues for clinical prognostic biomarker of HCC.

scholarly journals Identification and Validation of an 6-Metabolism-Related Gene Signature and Its Correlation With Immune Checkpoint in Hepatocellular Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
He Ren ◽  
Wanjing Li ◽  
Xin Liu ◽  
Shuliang Li ◽  
Hao Guo ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Immune Checkpoint ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Clinicopathological Characteristics ◽  
Gene Set Enrichment Analysis ◽  
Operating Characteristics ◽  
Kaplan Meier ◽  
Characteristics Analysis

Hepatocellular carcinoma (HCC) is a common malignant tumor with relatively high malignancy and rapid disease progression. Metabolism-related genes (MRGs) are involved in the pathogenesis of HCC. This study explored potential key MRGs and their effect on T-cell immune function in the tumor immune microenvironment to provide new insight for the treatment of HCC. Of 456 differentially expressed MRGs identified from TCGA database, 21 were screened by MCODE and cytoHubba algorithms. From the key module, GAD1, SPP1, WFS1, GOT2, EHHADH, and APOA1 were selected for validation. The six MRGs were closely correlated with survival outcomes and clinicopathological characteristics in HCC. Receiver operating characteristics analysis and Kaplan-Meier plots showed that these genes had good prognostic value for HCC. Gene set enrichment analysis of the six MRGs indicated that they were associated with HCC development. TIMER and GEPIA databases revealed that WFS1 was significantly positively correlated and EHHADH was negatively correlated with tumor immune cell infiltration and immune checkpoint expression. Finally, quantificational real-time polymerase chain reaction (qRT-PCR) confirmed the expression of WFS1 and EHHADH mRNA in our own patients’ cohort samples and four HCC cell lines. Collectively, the present study identified six potential MRG biomarkers associated with the prognosis and tumor immune infiltration of HCC, thus providing new insight into the pathogenesis and treatment of HCC.

scholarly journals Identification of a Novel Epithelial-Mesenchymal Transition Gene Signature Regulated by KEAP1-NRF2 Pathway in Esophageal Carcinoma

2020 ◽  
Author(s):  
Mohamed Elshaer ◽  
Ahmed Hammad ◽  
Xiu Jun Wang ◽  
Xiuwen Tang
Keyword(s):  
Cell Lines ◽  
Epithelial Mesenchymal Transition ◽  
Cancer Cell Line ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Mesenchymal Transition ◽  
Gene Set ◽  
Over Expression

Abstract BackgroundKEAP1-NRF2 pathway alterations were identified in many cancers including, esophageal cancer (ESCA). Identifying biomarkers that are associated with mutations in this pathway will aid in defining this cancer subset; and hence in supporting precision and personalized medicine. MethodsIn this study, 182 tumor samples from the Cancer Genome Atlas (TCGA)-ESCA RNA-Seq V2 level 3 data were segregated into two groups KEAP1-NRF2-mutated (22) and wild-type (160).The two groups were subjected to differential gene expression analysis, and we performed Gene Set Enrichment Analysis (GSEA) to determine all significantly affected biological pathways. Then, the enriched gene set was integrated with the differentially expressed genes (DEGs) to identify a gene signature regulated by the KEAP1-NRF2 pathway in ESCA. Furthermore, we validated the gene signature using mRNA expression data of ESCA cell lines provided by the Cancer Cell Line Encyclopedia (CCLE). The identified signature was tested in 3 independent ESCA datasets to assess its prognostic value.ResultsWe identified 11 epithelial-mesenchymal transition (EMT) genes regulated by the KEAP1-NRF2 pathway in ESCA patients. Five of the 11 genes showed significant over-expression in KEAP1-NRF2-mutated ESCA cell lines. In addition, the over-expression of these five genes was significantly associated with poor survival in 3 independent ESCA datasets, including the TCGA-ESCA dataset.ConclusionAltogether, we identified a novel EMT 5-gene signature regulated by the KEAP1-NRF2 axis and this signature is strongly associated with metastasis and drug resistance in ESCA. These 5-genes are potential biomarkers and therapeutic targets for ESCA patients in whom the KEAP1-NRF2 pathway is altered.

Age-Dependent Transcriptional Alterations in Cardiac Endothelial Cells

2021 ◽  
Author(s):  
Uchenna Emechebe ◽  
Jonathan William Nelson ◽  
Nabil J. Alkayed ◽  
Sanjiv Kaul ◽  
Andrew C Adey ◽  
...  
Keyword(s):  
Endothelial Cells ◽  
Endothelial Cell ◽  
Single Cell ◽  
Significant Risk ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Mouse Heart ◽  
Age Related ◽  
Organ Systems ◽  
Transcriptional Alterations

Aging is a significant risk factor for cardiovascular disease. Despite the fact that endothelial cells play critical roles in cardiovascular function and disease, the molecular impact of aging on this cell population in many organ systems remains unknown. In this study, we sought to determine age-associated transcriptional alterations in cardiac endothelial cells. Highly enriched populations of endothelial cells (ECs) isolated from the heart, brain and kidney of young (3 months) and aged (24 months) C57/BL6 mice were profiled for RNA expression via bulk RNA sequencing. Approximately 700 cardiac endothelial transcripts significantly differ by age. Gene set enrichment analysis indicated similar patterns for cellular pathway perturbations. Receptor-ligand comparisons indicated parallel alterations in age-affected circulating factors and cardiac endothelial-expressed receptors. Single-cell RNA-seq analysis identified 9 distinct endothelial cell subtypes in the heart with an age-associated population shift observed for the Aplnr-enriched endothelial cell clusters. Gene and pathway enrichment analyses show that age-related transcriptional response of cardiac endothelial cells is distinct from that of endothelial cells derived from the brain or kidney vascular bed. Furthermore, single-cell analysis identified 9 distinct EC subtypes, and shows that the Aplnr-enriched subtype is reduced with age in mouse heart. Finally, we identify age-dysregulated genes in specific aged cardiac endothelial subtypes.

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