scholarly journals Screening and identification of key candidate genes and pathways in myelodysplastic syndrome by bioinformatic analysis

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e8162
Author(s):  
Ying Le
Keyword(s):  
Gene Expression ◽  
Myelodysplastic Syndrome ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Hematologic Malignancy ◽  
Expression Profiles ◽  
Interaction Network ◽  
Functional Enrichment ◽  
Hematopoietic Stem ◽  
Diagnosis And Prognosis

Myelodysplastic syndrome (MDS) is a heterogeneous hematologic malignancy derived from hematopoietic stem cells and the molecular mechanism of MDS remains unclear. This study aimed to elucidate potential markers of diagnosis and prognosis of MDS. The gene expression profiles GSE19429 and GSE58831 were obtained and downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in MDS were screened using GEO2R and overlapped DEGs were obtained with Venn Diagrams. Then, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway functional enrichment analyses, protein–protein interaction network establishment and survival analyses were performed. Functional enrichment analysis indicated that these DEGs were significantly enriched in the interferon signaling pathway, immune response, hematopoietic cell lineage and the FOXO signaling pathway. Four hub genes and four significant modules including 25 module genes were obtained via Cytoscape MCODE. Survival analysis showed that the overall survival of MDS patients having BLNK, IRF4, IFITM1, IFIT1, ISG20, IFI44L alterations were worse than that without alterations. In conclusion, the identification of these genes and pathways helps understand the underlying molecular mechanisms of MDS and provides candidate targets for the diagnosis and prognosis of MDS.

scholarly journals Modulation of the Immune Response by Deferasirox in Myelodysplastic Syndrome Patients

2021 ◽  
Vol 14 (1) ◽  
pp. 41
Author(s):  
Hana Votavova ◽  
Zuzana Urbanova ◽  
David Kundrat ◽  
Michaela Dostalova Merkerova ◽  
Martin Vostry ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Blood Cell ◽  
Myelodysplastic Syndrome ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Adaptive Immune Response ◽  
Gene Expression Profiles ◽  
Iron Chelator ◽  
Multiple Cancer

Deferasirox (DFX) is an oral iron chelator used to reduce iron overload (IO) caused by frequent blood cell transfusions in anemic myelodysplastic syndrome (MDS) patients. To study the molecular mechanisms by which DFX improves outcome in MDS, we analyzed the global gene expression in untreated MDS patients and those who were given DFX treatment. The gene expression profiles of bone marrow CD34+ cells were assessed by whole-genome microarrays. Initially, differentially expressed genes (DEGs) were determined between patients with normal ferritin levels and those with IO to address the effect of excessive iron on cellular pathways. These DEGs were annotated to Gene Ontology terms associated with cell cycle, apoptosis, adaptive immune response and protein folding and were enriched in cancer-related pathways. The deregulation of multiple cancer pathways in iron-overloaded patients suggests that IO is a cofactor favoring the progression of MDS. The DEGs between patients with IO and those treated with DFX were involved predominantly in biological processes related to the immune response and inflammation. These data indicate DFX modulates the immune response mainly via neutrophil-related genes. Suppression of negative regulators of blood cell differentiation essential for cell maturation and upregulation of heme metabolism observed in DFX-treated patients may contribute to the hematopoietic improvement.

Analysis of Expression Profiles of mRNA and lncRNA in Oviduct During Estrus Phase of Sheep (Ovis Aries) with Two Fecundity (FecB Gene) Genotypes

2021 ◽  
Author(s):  
Weihao Chen ◽  
Zhifeng Li ◽  
Wei Sun ◽  
Mingxing Chu
Keyword(s):  
Embryo Development ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Ovis Aries ◽  
Functional Enrichment ◽  
Saga Complex ◽  
Rna Seq ◽  
Estrus Phase

Abstract Background:In sheep, FecB is the essential biomarker of the fertility, previous researches have provided a detailed insight on the regulation involved estrus phase and FecB in the reproductive-related tissues including hypothalamus, pituitary, and ovary. However, as the host of embryo development and connection between the ovary and the uterus, little is known about the interaction between mRNAs and lncRNAs in sheep oviduct. In the present study, RNA-Seq was performed to identify the transcriptomic profiles of mRNAs and lncRNAs in oviduct during estrus phase of sheep with FecBBB/++ genotypes.Results:In total, 21,863 lncRNAs and 43,674 mRNAs were identified, 57 DE lncRNAs and 637 DE mRNAs were revealed in the comparisons between follicular phase and luteal phase, 26 DE lncRNAs and 421 DE lncRNAs were revealed in the comparisons between FecB BB genotype and FecB ++ genotype. Functional enrichment analysis suggested that GO and KEGG terms related to reproduction such as SAGA complex, ATP-binding cassette (ABC), Nestin, and Hippo signalling pathway. DE-interaction network suggested that LNC_018420 maybe the key regulators related to embryo development in sheep oviduct.Conclusion:This was the first study to reveal the transcriptomic profiles of mRNAs and lncRNAs in the oviduct of FecB BB/++ sheep at estrus phase using RNA-Seq. Our findings can provide new understanding on the molecular mechanisms of mRNAs and lncRNAs underlying sheep embryo development and also opening new lines of investigation in sheep reproduction.

Differential gene expression profiling of adult murine hematopoietic stem cells

Blood ◽  
2002 ◽  
Vol 99 (2) ◽  
pp. 488-498 ◽  
Author(s):  
In-Kyung Park ◽  
Yaqin He ◽  
Fangming Lin ◽  
Ole D. Laerum ◽  
Qiang Tian ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Hematopoietic Stem Cells ◽  
Differential Gene Expression ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Cdna Clones ◽  
Self Renewal ◽  
Hematopoietic Stem ◽  
Differential Gene

Abstract Hematopoietic stem cells (HSCs) have self-renewal capacity and multilineage developmental potentials. The molecular mechanisms that control the self-renewal of HSCs are still largely unknown. Here, a systematic approach using bioinformatics and array hybridization techniques to analyze gene expression profiles in HSCs is described. To enrich mRNAs predominantly expressed in uncommitted cell lineages, 54 000 cDNA clones generated from a highly enriched population of HSCs and a mixed population of stem and early multipotent progenitor (MPP) cells were arrayed on nylon membranes (macroarray or high-density array), and subtracted with cDNA probes derived from mature lineage cells including spleen, thymus, and bone marrow. Five thousand cDNA clones with very low hybridization signals were selected for sequencing and further analysis using microarrays on glass slides. Two populations of cells, HSCs and MPP cells, were compared for differential gene expression using microarray analysis. HSCs have the ability to self-renew, while MPP cells have lost the capacity for self-renewal. A large number of genes that were differentially expressed by enriched populations of HSCs and MPP cells were identified. These included transcription factors, signaling molecules, and previously unknown genes.

Acquired α-thalassemia in association with myelodysplastic syndrome and other hematologic malignancies

Blood ◽  
2005 ◽  
Vol 105 (2) ◽  
pp. 443-452 ◽  
Author(s):  
David P. Steensma ◽  
Richard J. Gibbons ◽  
Douglas R. Higgs
Keyword(s):  
Gene Expression ◽  
Myelodysplastic Syndrome ◽  
Molecular Mechanisms ◽  
Hematologic Malignancy ◽  
Globin Gene ◽  
Molecular Genetic ◽  
Hematologic Malignancies ◽  
Genetic Features ◽  
Diagnostic Confusion ◽  
Hematologic Neoplasia

AbstractAbnormalities of hemoglobin synthesis are usually inherited but may also arise as a secondary manifestation of another disease, most commonly hematologic neoplasia. Acquired hemoglobin disorders can be seen in any population and are not restricted to areas of the world with high incidences of inherited hemoglobinopathies. In fact, the acquired hemoglobinopathies may be more readily recognized where inherited hemoglobin abnormalities are rare and less likely to cause diagnostic confusion. Acquired α-thalassemia is the best characterized of the acquired red blood cell disorders in patients with hematologic malignancy, and it is almost always associated with a myelodysplastic syndrome (MDS). At least 2 molecular mechanisms for acquired α-thalassemia are now recognized: acquired deletion of the α-globin gene cluster limited to the neoplastic clone and, more commonly, inactivating somatic mutations of the trans-acting chromatin-associated factor ATRX, which cause dramatic down-regulation of α-globin gene expression. Here we review the clinical, hematologic, and molecular genetic features of α-thalassemia arising in a clonal myeloid disorder, and we discuss howATRX might affect gene expression in normal and abnormal hematopoiesis through epigenetic mechanisms.

scholarly journals Identification of Potential Key Genes and Molecular Mechanisms of Medulloblastoma Based on Integrated Bioinformatics Approach

2022 ◽  
Vol 2022 ◽  
pp. 1-17
Author(s):  
Md. Rakibul Islam ◽  
Lway Faisal Abdulrazak ◽  
Mohammad Khursheed Alam ◽  
Bikash Kumar Paul ◽  
Kawsar Ahmed ◽  
...  
Keyword(s):  
Gene Expression ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Clinical Information ◽  
Gene Expression Omnibus ◽  
Hub Genes ◽  
New Treatments

Background. Medulloblastoma (MB) is the most occurring brain cancer that mostly happens in childhood age. This cancer starts in the cerebellum part of the brain. This study is designed to screen novel and significant biomarkers, which may perform as potential prognostic biomarkers and therapeutic targets in MB. Methods. A total of 103 MB-related samples from three gene expression profiles of GSE22139, GSE37418, and GSE86574 were downloaded from the Gene Expression Omnibus (GEO). Applying the limma package, all three datasets were analyzed, and 1065 mutual DEGs were identified including 408 overexpressed and 657 underexpressed with the minimum cut-off criteria of ∣ log   fold   change ∣ > 1 and P < 0.05 . The Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and WikiPathways enrichment analyses were executed to discover the internal functions of the mutual DEGs. The outcomes of enrichment analysis showed that the common DEGs were significantly connected with MB progression and development. The Search Tool for Retrieval of Interacting Genes (STRING) database was used to construct the interaction network, and the network was displayed using the Cytoscape tool and applying connectivity and stress value methods of cytoHubba plugin 35 hub genes were identified from the whole network. Results. Four key clusters were identified using the PEWCC 1.0 method. Additionally, the survival analysis of hub genes was brought out based on clinical information of 612 MB patients. This bioinformatics analysis may help to define the pathogenesis and originate new treatments for MB.

scholarly journals Identification of Key Genes and Pathways Associated with Mast Cells Resting in Meningioma

2020 ◽  
Author(s):  
Hui Xie ◽  
Xiao-hui Ding ◽  
Ce Yuan ◽  
Jin-jiang Li ◽  
Zhao-yang Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Mast Cells ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Immune Cell ◽  
Risk Model ◽  
Kegg Pathway ◽  
Expression Profiles ◽  
Receptor Interaction ◽  
Key Genes

Abstract Background: To identify candidate key genes and pathways related to mast cells resting in meningioma and the underlying molecular mechanisms of meningioma.Methods: Gene expression profiles of GSE43290 and GSE16581 datasets were obtained from the Gene Expression Omnibus (GEO) database. GO and KEGG pathway enrichments of DEGs were analyzed using the ClusterProfiler package in R. The protein-protein interaction network (PPI), and TF-miRNA- mRNA co-expression networks were constructed. Further, the difference in immune infiltration was investigated using the CIBERSORT algorithm.Results: A total of 1499 DEGs were identified between tumor and normal controls. The analysis of the immune cell infiltration landscape showed that the probability of distribution of memory B cells, regulatory T cells (Tregs), and resting mast cells in tumor samples were significantly higher than those in the controls. Moreover, through WGCNA analysis, the module related to mast cells resting contained 158 DEGs, and KEGG pathway analysis revealed that the DEGs were dominant in the TNF signaling pathway, cytokine-cytokine receptor interaction, and IL-17 signaling pathway. Survival analysis of hub genes related to mast cells resting showed that the risk model was constructed based on 9 key genes. The TF-miRNA- mRNA co-regulation network, including MYC-miR-145-5p, TNFAIP3-miR-29c-3p, and TNFAIP3-hsa-miR-335-3p, were obtained. Further, 36 nodes and 197 interactions in the PPI network were identified. Conclusions: The results of this study revealed candidate key genes, miRNAs, and pathways related to mast cells resting involved in meningioma development, providing potential therapeutic targets for meningioma treatment.

scholarly journals Comprehensive Analysis of Differentially Expressed Profiles of mRNA, lncRNA, and circRNA in the Uterus of Seasonal Reproduction Sheep

Genes ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 301 ◽  
Author(s):  
Yongfu La ◽  
Xiaoyun He ◽  
Liping Zhang ◽  
Ran Di ◽  
Xiangyu Wang ◽  
...  
Keyword(s):  
Thyroid Hormone ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Seasonal Reproduction ◽  
Hormone Synthesis ◽  
Long Photoperiod

Photoperiod is one of the important factors leading to seasonal reproduction of sheep. However, the molecular mechanisms underlying the photoperiod regulation of seasonal reproduction remain poorly understood. In this study, we compared the expression profiles of mRNAs, lncRNAs, and circRNAs in uterine tissues from Sunite sheep during three different photoperiods, namely, the short photoperiod (SP), short transfer to long photoperiod (SLP), and long photoperiod (LP). The results showed that 298, 403, and 378 differentially expressed (DE) mRNAs, 171, 491, and 499 DE lncRNAs, and 124, 270, and 400 DE circRNAs were identified between SP and LP, between SP and SLP, and between LP and SLP, respectively. Furthermore, functional enrichment analysis showed that the differentially expressed RNAs were mainly involved in the GnRH signaling pathway, thyroid hormone synthesis, and thyroid hormone signaling pathway. In addition, co-expression networks of lncRNA–mRNA were constructed based on the correlation analysis between the differentially expressed RNAs. Our study provides new insights into the expression changes of RNAs in different photoperiods, which might contribute to understanding the molecular mechanisms of seasonal reproduction in sheep.

Microarray-Based Gene Expression Analysis Identifies Potential Diagnostic and Prognostic Biomarkers for Waldenström Macroglobulinemia

2018 ◽  
Vol 140 (2) ◽  
pp. 87-96
Author(s):  
Haitao Xu ◽  
Fusheng Yao
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Mitogen Activated Protein Kinase ◽  
Ppi Network ◽  
Waldenström Macroglobulinemia ◽  
Waldenstrom Macroglobulinemia

Waldenström macroglobulinemia (WM), also known as lymphoplasmacytic lymphoma, is rare but a clinicopathologically distinct B-cell malignancy. This study assessed differentially expressed genes (DEGs) to identify potential WM biomarkers and uncover the underlying the molecular mechanisms of WM progression using gene expression profiles from the Gene Expression Omnibus database. DEGs were identified using the LIMMA package and their potential functions were then analyzed by using the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and the protein-protein interaction (PPI) network analysis by using the Search Tool for the Retrieval of Interacting Genes/Proteins database. Data showed that among 1,756 DEGs, 926 were upregulated and 830 were downregulated by comparing WM BM CD19+ with normal PB CD19+ B cell samples, whereas 241 DEGs (95 upregulated and 146 downregulated) were identified by comparing WM BM CD138+ with normal BM CD138+ plasma cell samples. The DEGs were enriched in different GO terms and pathways, including the apoptotic process, cell cycle arrest, immune response, cell adhesion, mitogen-activated protein kinase signaling pathway, toll-like receptor signaling pathway, and the gonadotropin-releasing hormone signaling pathway. Hub nodes in the PPI network included CDK1, JUN, CREBBP, EP300, CAD, CDK2, and MAPK14. Bioinformatics analysis of the GSE9656 dataset identified 7 hub genes that might play an important role in WM development and progression. Some of the candidate genes and pathways may serve as promising therapeutic targets for WM.

scholarly journals Identification of potential specific biomarkers and key signaling pathways between osteogenic and adipogenic differentiation of hBMSCs for osteoporosis therapy

2020 ◽  
Author(s):  
Jianjun Wu ◽  
Peian Cai ◽  
Zhenhui Lu ◽  
Zhi Zhang ◽  
Xixi He ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Signaling Pathway ◽  
Expression Profiles ◽  
Adipogenic Differentiation ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Pathological Feature ◽  
Osteoporosis Therapy ◽  
Bone Mesenchymal Stem Cells

Abstract Background: The differentiation of bone mesenchymal stem cells (BMSCs) into adipogenesis (AD) rather than osteogenesis (OS) is an important pathological feature of osteoporosis. Illuminating the detailed mechanisms of the differentiation of BMSCs into OS and AD would contribute to the interpretation of osteoporosis pathology.Methods: To identify the regulated mechanism in lineage commitment of the BMSCs into OS and AD in the early-stages, the gene expression profiles with temporal series were downloaded to reveal the distinct fates when BMSCs adopt a committed lineage. For both OS and AD lineages, the profiles of day 2–4 were compared with day 0 to screen the differentially expressed genes (DEGs), respectively. Next, the functional enrichment analysis was utilized to find out the biological function, and Protein-Protein Interaction network to predict the central genes. Finally, experiments were performed to verify our finding.Results: FoxO signaling pathway with central genes like FoxO3, IL6 and CAT, is the crucial mechanism of OS, while Rap1 signaling pathway of VEGFA and FGF2 enrichment is more significant for AD. Besides, PI3K-Akt signaling pathway might serves as the latent mechanism about the initiation of differentiation of BMSCs into multiple lineages.Conclusion: Above hub genes and early-responder signaling pathways control osteogenic and adipogenic fates of BMSCs, which maybe mechanistic models clarifying the changes of bone metabolism in the clinical progress of osteoporosis. The findings provide a crucial reference for the prevention and therapy of osteoporosis.

scholarly journals Hub Genes of Stroke Identified by Weighted Gene Co-expression Network Analysis

2020 ◽  
Author(s):  
Junhong Li ◽  
Yang Zhai ◽  
Peng Wu ◽  
Yueqiang Hu ◽  
Wei Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Common Disease ◽  
Hub Genes ◽  
Neuron Death ◽  
Roc Curve Analysis

Abstract BACKGROUD: Microarray-based gene expression profiling is widely used in biomedical research. Weighted gene co-expression network analysis (WGCNA) links microarray data directly to clinical traits and identifies rules for predicting pathological stage and prognosis of disease.WGCNA is useful in understandingmany biological processes. Stroke is a common disease worldwide, however, molecular mechanisms of its pathogenesis are largely unknown. The aim of this study was to construct gene co-expression networks for identification of key modules and hub genes associated with stroke pathogenesis.METHODS: Gene microarray expression profiles of stroke samples were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened by the limma package in R software. WGCNA was used to construct free-scale gene co-expression networks to explore the associations between gene sets and clinical features, and to identify key modules and hub genes. Subsequently, functional enrichment analyses were performed. Further, receiver operating characteristic (ROC) curve analysis was carried out to validate expression of hub genes and literature validation was performed as well.RESULTS: A total of 11,747 most variant genes were used for co-expression network construction. Pink and yellow modules were significantly correlated to stroke pathogenesis. Functional enrichment analysis showed that the pink module was mainly involved in regulation of neuron regeneration, and repair of DNA damage.On the other hand, yellow module was mainly enriched in ion transport system dysfunction which was correlated with neuron death. A total of eight hub genes (PRR11, NEDD9, Notch2, RUNX1-IT1, ANP32A-IT1, ASTN2, SAMHD1 and STIM1) were identified and validated at transcriptional levels and through existing literature.CONCLUSION: The eight hub genes (PRR11, NEDD9, Notch2, RUNX1-IT1, ANP32A-IT1, ASTN2, SAMHD1 and STIM1) identified in the study are potentialbiomarkers and therapeutic targets for effective diagnosis and treatment of stroke.

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