scholarly journals An evolutionary transcriptomics approach links CD36 to membrane remodeling in replicative senescence

2018 ◽  
Author(s):  
Marie Saitou ◽  
Darleny Y. Lizardo ◽  
Recep Ozgur Taskent ◽  
Alec Millner ◽  
Gunes Ekin Atilla-Gokcumen ◽  
...  
Keyword(s):  
Cell Lines ◽  
Cellular Senescence ◽  
Replicative Senescence ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Core Gene ◽  
Functional Enrichment ◽  
Membrane Remodeling ◽  
Lipid Metabolism Gene ◽  
The Media

SummaryCellular senescence, the irreversible ceasing of cell division, has been associated with organismal aging, prevention of cancerogenesis, and developmental processes. As such, the evolutionary basis and biological features of cellular senescence remain a fascinating area of research. In this study, we conducted comparative RNAseq experiments to detect genes associated with replicative senescence in two different human cell lines and at different time points. We identified 841 and 900 genes (core senescence-associated genes) that are significantly up- and downregulated in senescent cells, respectively, in both cell lines. Our functional enrichment analysis showed that downregulated core genes are primarily involved in cell cycle processes while upregulated core gene enrichment indicated various lipid-related processes. We further demonstrated that downregulated genes are significantly more conserved than upregulated genes. Using both transcriptomics and genetic variation data, we identified one of the upregulated, lipid metabolism gene, CD36 as an outlier. We found that overexpression of CD36 induces a senescence-like phenotype and, further, the media of CD36-overexpressing cells alone can induce a senescence-like phenotype in proliferating young cells. Moreover, we used a targeted lipidomics approach and showed that phosphatidylcholines accumulate during senescence in these cells, suggesting that upregulation of CD36 could contribute to membrane remodeling during senescence. Overall, these results contribute to the understanding of evolution and biology of cellular senescence and identify several targets and questions for future studies.

scholarly journals Identification of Latent Diagnostic Biomarkers and Biological Pathways in Dermatomyositis Based on WGCNA

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Shaxi Ouyang ◽  
Yifang Liu ◽  
Changjuan Xiao ◽  
Qinghua Zeng ◽  
Xun Luo ◽  
...  
Keyword(s):  
Cell Lines ◽  
Differentially Expressed Gene ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Interferon Α ◽  
Pathway Enrichment Analysis ◽  
Oligoadenylate Synthetase

Introduction. Dermatomyositis (DM) is a chronic autoimmune disease of predominantly lymphocytic infiltration mainly involving the transverse muscle. Its pathogenesis is remaining unknown. This research is designed to probe the latent pathogenesis of dermatomyositis, identify potential biomarkers, and reveal the pathogenesis of dermatomyositis through information biology analysis of gene chips. Methods. In this study, we utilised the GSE14287 and GSE11971 datasets rooted in the Gene Expression Omnibus (GEO) databank, which included a total of 62 DM samples and 9 normal samples. The datasets were combined, and the differentially expressed gene sets were subjected to weighted gene coexpression network analysis, and the hub gene was screened using a protein interaction network from genes in modules highly correlated with dermatomyositis progression. Results. A total of 3 key genes—myxovirus resistance-2 (MX2), oligoadenylate synthetase 1 (OAS1), and oligoadenylate synthetase 2 (OAS2)—were identified in combination with cell line samples, and the expressions of the 3 genes were verified separately. The results showed that MX2, OAS1, and OAS2 were highly expressed in LPS-treated cell lines compared to normal cell lines. The results of pathway enrichment analysis of the genes indicated that all 3 genes were enriched in the cytosolic DNA signalling and cytokine and cytokine receptor interaction signalling pathways; the results of functional enrichment analysis showed that all 3 were enriched in interferon-α response and interferon-γ response functions. Conclusions. This is important for the study of the pathogenesis and objective treatment of dermatomyositis and provides important reference information for the targeted therapy of dermatomyositis.

scholarly journals A Novel Metastasis-related Genes Based Signature for Predicting the Progression-free Interval of Patients With Papillary Thyroid Carcinoma

2022 ◽  
Author(s):  
Rui Liu ◽  
Zhen Cao ◽  
Meng-wei Wu ◽  
Xiao-bin Li ◽  
Hong-wei Yuan ◽  
...  
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Cell Lines ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Bioinformatic Analysis ◽  
Functional Enrichment ◽  
Clinical Parameters ◽  
Papillary Thyroid ◽  
Free Interval

Abstract Background: We aimed to build a novel model with metastasis-related genes (MTGs) signature and relevant clinical parameters for predicting progression-free interval (PFI) after surgery for papillary thyroid carcinoma (PTC).Methods: We performed a bioinformatic analysis of integrated PTC datasets with the MTGs to identify differentially expressed MTGs (DE-MTGs). Then we generated PFI-related DE-MTGs and established a novel MTGs based signature. After that, we validated the signature on multiple datasets and PTC cell lines. Further, we carried out uni- and multivariate analysis to identify independent prognostic characters. Finally, we established a signature and clinical parameters-based nomogram for predicting the PFI of PTC. Results: We identified 155 DE-MTGs related to PFI in PTC. The functional enrichment analysis showed that the DE-MTGs were associated with an essential oncogenic process. Consequently, we found a novel 10-gene signature and could distinguish patients with poorer prognoses and predicted PFI accurately. The novel signature had a C-index of 0.76 and the relevant nomogram had a C-index of 0.80. Also, it was closely related to pivotal clinical characters of datasets and invasiveness of cell lines. And the signature was confirmed a significant independent prognostic factor in PTC. Finally, we built a nomogram by including the signature and relevant clinical factors. Validation analysis showed that the nomogram's efficacy was satisfying in predicting PTC’s PFI. Conclusions: The MTG signature and nomogram were closely associated with PTC prognosis and may help clinicians improve the individualized prediction of PFI, especially for high-risk patients after surgery.

scholarly journals Integral Analyses of Competing Endogenous RNA Mechanisms and DNA Methylation Reveal Regulatory Mechanisms in Osteosarcoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Tingrui Wu ◽  
Bo Wei ◽  
Hao Lin ◽  
Boan Zhou ◽  
Tao Lin ◽  
...  
Keyword(s):  
Cell Lines ◽  
Binding Sites ◽  
Control Cell ◽  
Bone Tumour ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Biological Processes ◽  
Survival Times ◽  
Poor Overall Survival

Background: Osteosarcoma (OS) is the most common primary malignant bone tumour in children and adolescents, with rapid growth, frequent metastasis, and a poor prognosis, but its pathogenesis has not been fully elucidated. Exploring the pathogenesis of OS is of great significance for improving diagnoses and finding new therapeutic targets.Methods: Differentially expressed circRNAs (DECs), miRNAs (DEMs), methylated DNA sites (DMSs), and mRNAs (DEGs) were identified between OS and control cell lines. GSEA of DEGs and functional enrichment analysis of methylated DEGs were carried out to further identify potential biological processes. Online tools were used to predict the miRNA binding sites of DECs and the mRNA binding sites of DEMs, and then construct a circRNA-miRNA-mRNA network. Next, an analysis of the interaction between methylated DEGs was performed with a protein-protein interaction (PPI) network, and hub gene identification and survival analysis were carried out. The expression pattern of circRNA-miRNA-mRNA was validated by real-time PCR.Results: GSEA and functional enrichment analysis indicated that DEGs and methylated DEGs are involved in important biological processes in cancer. Hsa_circ_0001753/has_miR_760/CD74 network was constructed and validated in cell lines. Low expression levels of CD74 are associated with poor overall survival times and show good diagnostic ability.Conclusion: Methylated DEGs may be involved in the development of OS, and the hsa_circ_0001753/has_miR_760/CD74 network may serve as a target for the early diagnosis of and targeted therapy for OS.

scholarly journals Identification of Overexpressed Genes in Malignant Pleural Mesothelioma

2021 ◽  
Vol 22 (5) ◽  
pp. 2738
Author(s):  
Federica Morani ◽  
Luisa Bisceglia ◽  
Giulia Rosini ◽  
Luciano Mutti ◽  
Ombretta Melaiu ◽  
...  
Keyword(s):  
Cell Lines ◽  
Malignant Pleural Mesothelioma ◽  
Gene List ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Mitotic Cell ◽  
Functional Enrichment ◽  
Pleural Mesothelioma ◽  
Apoptosis Inhibition ◽  
Tcga Dataset

Malignant pleural mesothelioma (MPM) is a fatal tumor lacking effective therapies. The characterization of overexpressed genes could constitute a strategy for identifying drivers of tumor progression as targets for novel therapies. Thus, we performed an integrated gene-expression analysis on RNAseq data of 85 MPM patients from TCGA dataset and reference samples from the GEO. The gene list was further refined by using published studies, a functional enrichment analysis, and the correlation between expression and patients’ overall survival. Three molecular signatures defined by 15 genes were detected. Seven genes were involved in cell adhesion and extracellular matrix organization, with the others in control of the mitotic cell division or apoptosis inhibition. Using Western blot analyses, we found that ADAMTS1, PODXL, CIT, KIF23, MAD2L1, TNNT1, and TRAF2 were overexpressed in a limited number of cell lines. On the other hand, interestingly, CTHRC1, E-selectin, SPARC, UHRF1, PRSS23, BAG2, and MDK were abundantly expressed in over 50% of the six MPM cell lines analyzed. Thus, these proteins are candidates as drivers for sustaining the tumorigenic process. More studies with small-molecule inhibitors or silencing RNAs are fully justified and need to be undertaken to better evaluate the cancer-driving role of the targets herewith identified.

scholarly journals Downregulation of microRNA-376a in Gastric Cancer and Association with Poor Prognosis

2018 ◽  
Vol 51 (5) ◽  
pp. 2010-2018 ◽  
Author(s):  
Cheng Zhang ◽  
Yu Liang ◽  
Ming-Hui Ma ◽  
Kun-Zhe Wu ◽  
Chun-Dong Zhang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cell Lines ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Control Group ◽  
Mesenchymal Transition ◽  
Tumorigenesis And Progression ◽  
The Common

Background/Aims: MicroRNAs have a significant role in the tumorigenesis and progression of cancers, including gastric cancer (GC). Our study aimed to identify a novel biomarker to predict the prognosis of patients with GC. Methods: The GC microarray dataset, GSE28700, was downloaded from the Gene Expression Omnibus (GEO) database and screened for differentially expressed miRNAs (DEMs). The downregulation of miR-376a expression was verified in GC cell lines and 82 paired GC tissues by performing RT-qPCR and the correlation between its expression and clinicopathological characteristics was also explored. The target genes of miR-376a were predicted using TargetScan7.1, miRDB, and DIANA website tools. A functional enrichment analysis was performed to explore the biological role of the common target genes. Results: Bioinformatics analysis found that miR-376a was downregulated in GC tissues. Compared with the control group, RT-qPCR results showed that the expression of miR-376a in GC cell lines and tissues were also significantly decreased. The expression of miR-376a was statistically associated with T and N stage. Survival analysis with Kaplan–Meier showed that GC patients in the low expression group had a poorer prognosis than those in the high expression group (median survival of 26.4 and 46.9 months, respectively). Univariate and multivariate analysis demonstrated that low miR-376a expression was an independent prognostic marker for poor survival. Functional enrichment analysis indicated that the common targets genes were involved in cell–cell communication, VEGF and mTOR1-mediated signaling, and epithelial-to-mesenchymal transition (EMT). Conclusion: The results suggest that miR-376a could play an important role in the tumorigenesis and progression of GC and act as a novel therapeutic target and prognostic indicator in patients with GC.

scholarly journals Enrichment analysis on regulatory subspaces: a novel direction for the superior description of cellular responses to SARS-CoV-2

2021 ◽  
Author(s):  
Pedro P. Rodrigues ◽  
Rafael S. Costa ◽  
Rui Henriques
Keyword(s):  
Machine Learning ◽  
Cell Lines ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Learning Approaches ◽  
Transcriptional Responses ◽  
Kegg Pathways ◽  
Regulatory Processes

Statement: The enrichment analysis of discriminative cell transcriptional responses to SARS-CoV-2 infection using biclustering produces a broader set of superiorly enriched GO terms and KEGG pathways against alternative state-of-the-art machine learning approaches, unraveling novel knowledge. Motivation and methods: The comprehensive understanding of the impacts of the SARS-CoV-2 virus on infected cells is still incomplete. This work identifies and analyses the main cell regulatory processes affected and induced by SARS-CoV-2, using transcriptomic data from several infectable cell lines available in public databases and in vivo samples. We propose a new class of statistical models to handle three major challenges, namely the scarcity of observations, the high dimensionality of the data, and the complexity of the interactions between genes. Additionally, we analyse the function of these genes and their interactions within cells to compare them to ones affected by IAV (H1N1), RSV and HPIV3 in the target cell lines. Results: Gathered results show that, although clustering and predictive algorithms aid classic functional enrichment analysis, recent pattern-based biclustering algorithms significantly improve the number and quality of the detected biological processes. Additionally, a comparative analysis of these processes is performed to identify potential pathophysiological characteristics of COVID-19. These are further compared to those identified by other authors for the same virus as well as related ones such as SARS-CoV-1. This approach is particularly relevant due to a lack of other works utilizing more complex machine learning tools within this context.

Systems Biology Approaches Reveal a Multi-stress Responsive WRKY Transcription Factor and Stress Associated Gene Co-expression Networks in Chickpea

2019 ◽  
Vol 14 (7) ◽  
pp. 591-601 ◽  
Author(s):  
Aravind K. Konda ◽  
Parasappa R. Sabale ◽  
Khela R. Soren ◽  
Shanmugavadivel P. Subramaniam ◽  
Pallavi Singh ◽  
...  
Keyword(s):  
Expression Pattern ◽  
Gene Networks ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Wrky Transcription Factor ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Callose Deposition ◽  
Significant Probability

Background: Chickpea is a nutritional rich premier pulse crop but its production encounters setbacks due to various stresses and understanding of molecular mechanisms can be ascribed foremost importance. Objective: The investigation was carried out to identify the differentially expressed WRKY TFs in chickpea in response to herbicide stress and decipher their interacting partners. Methods: For this purpose, transcriptome wide identification of WRKY TFs in chickpea was done. Behavior of the differentially expressed TFs was compared between other stress conditions. Orthology based cofunctional gene networks were derived from Arabidopsis. Gene ontology and functional enrichment analysis was performed using Blast2GO and STRING software. Gene Coexpression Network (GCN) was constructed in chickpea using publicly available transcriptome data. Expression pattern of the identified gene network was studied in chickpea-Fusarium interactions. Results: A unique WRKY TF (Ca_08086) was found to be significantly (q value = 0.02) upregulated not only under herbicide stress but also in other stresses. Co-functional network of 14 genes, namely Ca_08086, Ca_19657, Ca_01317, Ca_20172, Ca_12226, Ca_15326, Ca_04218, Ca_07256, Ca_14620, Ca_12474, Ca_11595, Ca_15291, Ca_11762 and Ca_03543 were identified. GCN revealed 95 hub genes based on the significant probability scores. Functional annotation indicated role in callose deposition and response to chitin. Interestingly, contrasting expression pattern of the 14 network genes was observed in wilt resistant and susceptible chickpea genotypes, infected with Fusarium. Conclusion: This is the first report of identification of a multi-stress responsive WRKY TF and its associated GCN in chickpea.

scholarly journals Structural variations in papaya genomes

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Zhenyang Liao ◽  
Xunxiao Zhang ◽  
Shengcheng Zhang ◽  
Zhicong Lin ◽  
Xingtan Zhang ◽  
...  
Keyword(s):  
Agronomic Traits ◽  
Enrichment Analysis ◽  
Copy Number Variant ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Structural Variations ◽  
Reproduction Traits ◽  
Depth Study ◽  
Environmental Adaptability ◽  
The Impact

Abstract Background Structural variations (SVs) are a type of mutations that have not been widely detected in plant genomes and studies in animals have shown their role in the process of domestication. An in-depth study of SVs will help us to further understand the impact of SVs on the phenotype and environmental adaptability during papaya domestication and provide genomic resources for the development of molecular markers. Results We detected a total of 8083 SVs, including 5260 deletions, 552 tandem duplications and 2271 insertions with deletion being the predominant, indicating the universality of deletion in the evolution of papaya genome. The distribution of these SVs is non-random in each chromosome. A total of 1794 genes overlaps with SV, of which 1350 genes are expressed in at least one tissue. The weighted correlation network analysis (WGCNA) of these expressed genes reveals co-expression relationship between SVs-genes and different tissues, and functional enrichment analysis shows their role in biological growth and environmental responses. We also identified some domesticated SVs genes related to environmental adaptability, sexual reproduction, and important agronomic traits during the domestication of papaya. Analysis of artificially selected copy number variant genes (CNV-genes) also revealed genes associated with plant growth and environmental stress. Conclusions SVs played an indispensable role in the process of papaya domestication, especially in the reproduction traits of hermaphrodite plants. The detection of genome-wide SVs and CNV-genes between cultivated gynodioecious populations and wild dioecious populations provides a reference for further understanding of the evolution process from male to hermaphrodite in papaya.

scholarly journals CCTs as new biomarkers for the prognosis of head and neck squamous cancer

Open Medicine ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. 672-688
Author(s):  
Yanbo Dong ◽  
Siyu Lu ◽  
Zhenxiao Wang ◽  
Liangfa Liu
Keyword(s):  
Head And Neck ◽  
Survival Data ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Advanced Tumor Stage ◽  
Expression Levels ◽  
T Complex ◽  
Advanced Tumor ◽  
Squamous Cancer

AbstractThe chaperonin-containing T-complex protein 1 (CCT) subunits participate in diverse diseases. However, little is known about their expression and prognostic values in human head and neck squamous cancer (HNSC). This article aims to evaluate the effects of CCT subunits regarding their prognostic values for HNSC. We mined the transcriptional and survival data of CCTs in HNSC patients from online databases. A protein–protein interaction network was constructed and a functional enrichment analysis of target genes was performed. We observed that the mRNA expression levels of CCT1/2/3/4/5/6/7/8 were higher in HNSC tissues than in normal tissues. Survival analysis revealed that the high mRNA transcriptional levels of CCT3/4/5/6/7/8 were associated with a low overall survival. The expression levels of CCT4/7 were correlated with advanced tumor stage. And the overexpression of CCT4 was associated with higher N stage of patients. Validation of CCTs’ differential expression and prognostic values was achieved by the Human Protein Atlas and GEO datasets. Mechanistic exploration of CCT subunits by the functional enrichment analysis suggests that these genes may influence the HNSC prognosis by regulating PI3K-Akt and other pathways. This study implies that CCT3/4/6/7/8 are promising biomarkers for the prognosis of HNSC.

scholarly journals Investigation and Functional Enrichment Analysis of the Human Host Interaction Network with Common Gram-Negative Respiratory Pathogens Predicts Possible Association with Lung Adenocarcinoma

2021 ◽  
Vol 28 (1) ◽  
pp. 20-33
Author(s):  
Lydia-Eirini Giannakou ◽  
Athanasios-Stefanos Giannopoulos ◽  
Chrissi Hatzoglou ◽  
Konstantinos I. Gourgoulianis ◽  
Erasmia Rouka ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Cell Junctions ◽  
Respiratory Pathogens ◽  
Gram Negative ◽  
Human Proteins ◽  
Apoptotic Pathways

Haemophilus influenzae (Hi), Moraxella catarrhalis (MorCa) and Pseudomonas aeruginosa (Psa) are three of the most common gram-negative bacteria responsible for human respiratory diseases. In this study, we aimed to identify, using the functional enrichment analysis (FEA), the human gene interaction network with the aforementioned bacteria in order to elucidate the full spectrum of induced pathogenicity. The Human Pathogen Interaction Database (HPIDB 3.0) was used to identify the human proteins that interact with the three pathogens. FEA was performed via the ToppFun tool of the ToppGene Suite and the GeneCodis database so as to identify enriched gene ontologies (GO) of biological processes (BP), cellular components (CC) and diseases. In total, 11 human proteins were found to interact with the bacterial pathogens. FEA of BP GOs revealed associations with mitochondrial membrane permeability relative to apoptotic pathways. FEA of CC GOs revealed associations with focal adhesion, cell junctions and exosomes. The most significantly enriched annotations in diseases and pathways were lung adenocarcinoma and cell cycle, respectively. Our results suggest that the Hi, MorCa and Psa pathogens could be related to the pathogenesis and/or progression of lung adenocarcinoma via the targeting of the epithelial cellular junctions and the subsequent deregulation of the cell adhesion and apoptotic pathways. These hypotheses should be experimentally validated.

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