scholarly journals Nourin-Associated miRNAs: Novel Inflammatory Monitoring Markers for Cyclocreatine Phosphate Therapy in Heart Failure

2021 ◽  
Vol 22 (7) ◽  
pp. 3575
Author(s):  
Salwa A. Elgebaly ◽  
Robert Todd ◽  
Donald L. Kreutzer ◽  
Robert Christenson ◽  
Nashwa El-Khazragy ◽  
...  
Keyword(s):  
Gene Expression ◽  
Heart Failure ◽  
Myocardial Injury ◽  
Cell Damage ◽  
Expression Profiles ◽  
Preventive Therapy ◽  
Heart Weight ◽  
Serum Samples ◽  
Expression Levels ◽  
Gene Expression Levels

Background: Cyclocreatine phosphate (CCrP) is a potent bioenergetic cardioprotective compound known to preserve high levels of cellular adenosine triphosphate during ischemia. Using the standard Isoproterenol (ISO) rat model of heart failure (HF), we recently demonstrated that the administration of CCrP prevented the development of HF by markedly reducing cardiac remodeling (fibrosis and collagen deposition) and maintaining normal ejection fraction and heart weight, as well as physical activity. The novel inflammatory mediator, Nourin is a 3-KDa formyl peptide rapidly released by ischemic myocardium and is associated with post-ischemic cardiac inflammation. We reported that the Nourin-associated miR-137 (marker of cell damage) and miR-106b-5p (marker of inflammation) are significantly upregulated in unstable angina patients and patients with acute myocardial infarction, but not in healthy subjects. Objectives: To test the hypothesis that Nourin-associated miR-137 and miR-106b-5p are upregulated in ISO-induced “HF rats” and that the administration of CCrP prevents myocardial injury (MI) and reduces Nourin gene expression in “non-HF rats”. Methods: 25 male Wistar rats (180–220 g) were used: ISO/saline (n = 6), ISO/CCrP (0.8 g/kg/day) (n = 5), control/saline (n = 5), and control/CCrP (0.8 g/kg/day) (n = 4). In a limited study, CCrP at a lower dose of 0.4 g/kg/day (n = 3) and a higher dose of 1.2 g/kg/day (n = 2) were also tested. The Rats were injected SC with ISO for two consecutive days at doses of 85 and 170 mg/kg/day, respectively, then allowed to survive for an additional two weeks. CCrP and saline were injected IP (1 mL) 24 h and 1 h before first ISO administration, then daily for two weeks. Serum CK-MB (U/L) was measured 24 h after the second ISO injection to confirm myocardial injury. After 14 days, gene expression levels of miR-137 and miR-106b-5p were measured in serum samples using quantitative real-time PCR (qPCR). Results: While high levels of CK-MB were detected after 24 h in the ISO/saline rats indicative of MI, the ISO/CCrP rats showed normal CK-MB levels, supporting prevention of MI by CCrP. After 14 days, gene expression profiles showed significant upregulation of miR-137 and miR-106b-5p by 8.6-fold and 8.7-fold increase, respectively, in the ISO/saline rats, “HF rats,” compared to the control/saline group. On the contrary, CCrP treatment at 0.8 g/kg/day markedly reduced gene expression of miR-137 by 75% and of miR-106b-5p by 44% in the ISO/CCrP rats, “non-HF rats,” compared to the ISO/Saline rats, “HF rats.” Additionally, healthy rats treated with CCrP for 14 days showed no toxicity in heart, liver, and renal function. Conclusions: Results suggest a role of Nourin-associated miR-137 and miR-106b-5p in the pathogenesis of HF and that CCrP treatment prevented ischemic injury in “non-HF rats” and significantly reduced Nourin gene expression levels in a dose–response manner. The Nourin gene-based mRNAs may, therefore, potentially be used as monitoring markers of drug therapy response in HF, and CCrP—as a novel preventive therapy of HF due to ischemia.

scholarly journals Evaluation of TGF-Beta 2 and VEGFα Gene Expression Levels in Epiretinal Membranes and Internal Limiting Membranes in the Course of Retinal Detachments, Proliferative Diabetic Retinopathy, Macular Holes, and Idiopathic Epiretinal Membranes

2018 ◽  
Vol 2018 ◽  
pp. 1-6
Author(s):  
Joanna Stafiej ◽  
Karolina Kaźmierczak ◽  
Katarzyna Linkowska ◽  
Paweł Żuchowski ◽  
Tomasz Grzybowski ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Rna Extraction ◽  
Retinal Diseases ◽  
Epiretinal Membranes ◽  
Expression Levels ◽  
Macular Holes ◽  
Retinal Disorders ◽  
Pars Plana ◽  
Gene Expression Levels

Purpose. To evaluate the expression profiles of the VEGFα and TGFβ in the ERMs and ILMs in retinal disorders. Methods. In this nonrandomized prospective study, 75 patients (34 females and 41 males) referred to pars plana vitrectomy (PPV) due to different retinal diseases were enrolled to the study. The samples of ERMs and ILMs collected during PPV were immediately put in TRIzol® Reagent (Life Technologies, USA) and stored at −70°C until RNA extraction. Gene expression analysis was done with TaqMan® Gene Expression Assays (Applied Biosystems, USA) following the manufacturer’s instructions. Results. The gene expression levels of VEGFα as well as of TGFβ2 were significantly higher in ERMs than in ILMs in all studied groups. The level of TGFβ2 expression exhibits a significantly lower values in iERMs as compared with the RRD group (p=0.043). There were differences in TGFβ2 expression in ILM in groups studied: DR versus RRD, p=0.003; DR versus iERM, p=0,047; and iERM versus RRD, p=0.004. Conclusions. Our results revealed that factors associated with angiogenesis and wound healing processes in eyes with RRD, PDR, iERM, and MH were more upregulated in ERMs than in ILMs. This may indicate that ILM is not responsible for reproliferation and its peeling should be avoided in routine PPV.

Expression profiles of metamorphosis-related genes during natural transformations in tadpoles of wild Wood Frogs (Lithobates sylvaticus)

2012 ◽  
Vol 90 (9) ◽  
pp. 1059-1071 ◽  
Author(s):  
Laia Navarro-Martín ◽  
Chantal Lanctôt ◽  
Christopher Edge ◽  
Jeff Houlahan ◽  
Vance L. Trudeau
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Rana Sylvatica ◽  
Fold Increase ◽  
Gonadal Development ◽  
Specific Expression ◽  
Wood Frogs ◽  
Lithobates Sylvaticus ◽  
Expression Levels ◽  
Gene Expression Levels

Numerous studies using laboratory-reared tadpoles have shown the importance of thyroid hormones (TH), thyroid receptors (TR), and deiodinase (Dio) enzymes during anuran metamorphosis. Our study focuses on the analysis of thyroid-related genes in tadpoles of wild Wood Frogs ( Lithobates sylvaticus (LeConte, 1825); also known as Rana sylvatica (Cope, 1889)) during metamorphosis. Results showed that, in concordance with laboratory-reared studies, thyroid receptor beta (trb) gene expression profiles presented the most marked changes. At climax and compared with premetamorphic stages, brains, tails, and gonad–mesonephros complex (GMC) tissues increased trb expression levels 5-, 21-, and 41-fold, respectively (p < 0.05). In addition, gene expression levels of brain deiodinase type II and III showed opposite trends, where 3-fold decrease and 10-fold increase were, respectively, found. This finding supports the idea that thyroid hormone, as it has been demonstrated in laboratory-reared tadpoles, is also involved in natural metamorphosis in wild tadpoles. Interestingly, and contrary to our predictions, we observed that whole brain corticotropin-releasing factor (crf) and crf receptor 1 (crfr1) gene expression levels significantly decrease through metamorphosis in wild L. sylvaticus tadpoles. Further analyses are required to determine if a role of TH in the timing of anuran gonadal development exists, as well as the importance of cell-specific and tissue-specific expression of crf and crfr1 to metamorphosis.

Identification of Aberrantly Regulated Genes through Comparison of Genome-Wide Expression Profiles and Karyotype in Hyperdiploid >50 Chromosomes Pediatric Acute Lymphoblastic Leukemia.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 420-420
Author(s):  
Christian Flotho ◽  
Susana C. Raimondi ◽  
James R. Downing
Keyword(s):  
Gene Expression ◽  
Copy Number ◽  
Expression Profiles ◽  
Chromosome 21 ◽  
Small Subset ◽  
Specific Gene ◽  
Expression Levels ◽  
Number Of Genes ◽  
The Mean ◽  
Gene Expression Levels

Abstract We have demonstrated that expression profiling of leukemic blasts can accurately identify the known prognostic subtypes of ALL, including T-ALL, E2A-PBX1, TEL-AML1, MLL rearrangements, BCR-ABL, and hyperdiploid &gt;50 chromosomes (HD&gt;50). Interestingly, almost 70% of the genes that defined HD&gt;50 ALL localized to chromosome 21 or X. To further explore the relationship between gene expression and chromosome dosage, we compared the expression profiles obtained using the Affymetrix U133A&B microarrays of 17 HD&gt;50 ALLs to 78 diploid or pseudodiploid ALLs. Our analysis demonstrated that the average expression level for all genes on a chromosome could be used to predict chromosome copy numbers. Specifically, the copy number for each chromosome calculated by gene expression profiling predicted the numerical chromosomal abnormalities detected by standard cytogenetics. For chromosomes that were trisomic in HD&gt;50 ALL, the mean chromosome-specific gene expression level was increased approximately 1.5-fold compared to that observed in diploid or pseudodiploid ALL cases. Similarly, for chromosome 21 and X, the mean chromosome-specific gene expression levels were increased approximately 2-fold, consistent with a duplication of the active X chromosome and tetrasomy of chromosome 21, a finding verified by standard cytogenetics in &gt;90% of the HD&gt;50 cases. These finding indicate that the aberrant gene expression levels seen in HD&gt;50 ALL primarily reflect gene dosages. Importantly, we did not observe any clustering of aberrantly expressed genes across the duplicated chromosomes, making regional gain or loss of genomic material unlikely. Paradoxically, however, a more detailed analysis revealed a small but statistically significant number of genes on the trisomic/tetrasomic chromosomes whose expression levels were markedly reduced when compared to that seen in diploid or pseudodiploid leukemic samples. Using the Statistical Analysis of Microarrays (SAM) algorithm we identified 20 genes whose expression was reduced &gt;2-fold despite having an increase in copy number. Interestingly, included within this group are several known tumor suppressors, including AKAP12, which is specifically silenced by methylation in fos-transformed cells, and IGF2R and IGFBP7, negative regulators of insulin-like growth factor signaling. In addition to the silencing of a small subset of genes, we also identified 21 genes on these chromosomes whose expression levels were markedly higher (&gt;3-fold) than would be predicted solely based on copy number. Although the mechanism responsible for their increased expression remains unknown, included in this group are four genes involved in signal transduction (IL3RA, IL13RA1, SNX9, and GASP) and a novel cytokine, C17, whose expression is normally limited to CD34+ hematopoietic progenitors. Taken together, these data suggest that aberrant growth in HD&gt;50 ALL is in part driven by increased expression of a large number of genes secondary to chromosome duplications, coupled with a further enhanced expression of a limited number of growth promoting genes, and the specific silencing of a small subset of negative growth regulatory genes. Understanding the mechanisms responsible for the non-dosage related changes in gene expression should provide important insights into the pathology of HD&gt;50 ALL.

Abstract 12596: Manipulation of Gut Microbiota Influences Myocardial Mass in Mice

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Takehiro Kamo
Keyword(s):  
Gene Expression ◽  
Heart Failure ◽  
Body Weight ◽  
Gut Microbiota ◽  
Expression Profiles ◽  
Oral Treatment ◽  
Regulation Of Gene Expression ◽  
Heart Weight ◽  
Myocardial Mass ◽  
Antibiotic Cocktail

Introduction: Gut microbiota have developed a close relationship with human host during the co-evolutionary process for millions of years, and they play an essential role in the maintenance of host homeostasis. There is accumulating evidence that an imbalance in the gut microbial communities, referred to as dysbiosis, is associated with human pathologies including cardiovascular diseases. We and others have recently demonstrated that heart failure is associated with gut microbiota dysbiosis using 16S ribosomal RNA gene sequencing of fecal samples from patients with heart failure. This finding suggests a potential significance of gut microbiota in the pathophysiology of heart failure. However, the link between the gut microbiota and the heart remains largely unclear. Hypothesis: We hypothesized that manipulation of gut microbiota influences the structure of the heart. Methods: To determine the effects of gut microbiota depletion, cardiac structure and gene expression were evaluated in mice following treatment with orally administered broad-spectrum antibiotic cocktail. We subsequently explored the effects of administration of a single antibiotic agent on myocardial structure. Results: Antibiotic cocktail-treated mice showed a remarkable decrease in myocardial mass and cardiomyocyte size as compared with untreated mice (mean [±SD] ratio of heart weight to body weight, 3.87±0.25 mg/g in 44 antibiotic-treated mice vs. 4.38±0.21 mg/g in 45 untreated mice). The decrease in myocardial mass was associated with substantial changes in gene expression profiles in the heart, including the expression of genes encoding sarcomere proteins and extracellular matrix proteins. In addition, oral treatment with ampicillin alone led to a significant decrease in myocardial mass (mean [±SD] ratio of heart weight to body weight, 3.52±0.24 mg/g in 11 ampicillin-treated mice vs. 4.10±0.24 mg/g in 12 untreated mice). Conclusions: These results suggest that gut microbiota may modulate myocardial mass through the remote regulation of gene expression in the heart. Our study indicates an intimate relationship between the gut microbiota and the heart, and suggests the potential efficacy of manipulating gut microbiota in the prevention and treatment of heart failure.

scholarly journals CellExpress: a comprehensive microarray-based cancer cell line and clinical sample gene expression analysis online system

Database ◽  
2018 ◽  
Vol 2018 ◽  
Author(s):  
Yi-Fang Lee ◽  
Chien-Yueh Lee ◽  
Liang-Chuan Lai ◽  
Mong-Hsun Tsai ◽  
Tzu-Pin Lu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Lines ◽  
Cancer Cell ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Comprehensive Analysis ◽  
Next Generation Sequencing Data ◽  
Clinical Samples ◽  
Expression Levels ◽  
Gene Expression Levels

Abstract With the advancement of high-throughput technologies, gene expression profiles in cell lines and clinical samples are widely available in the public domain for research. However, a challenge arises when trying to perform a systematic and comprehensive analysis across independent datasets. To address this issue, we developed a web-based system, CellExpress, for analyzing the gene expression levels in more than 4000 cancer cell lines and clinical samples obtained from public datasets and user-submitted data. First, a normalization algorithm can be utilized to reduce the systematic biases across independent datasets. Next, a similarity assessment of gene expression profiles can be achieved through a dynamic dot plot, along with a distance matrix obtained from principal component analysis. Subsequently, differentially expressed genes can be visualized using hierarchical clustering. Several statistical tests and analytical algorithms are implemented in the system for dissecting gene expression changes based on the groupings defined by users. Lastly, users are able to upload their own microarray and/or next-generation sequencing data to perform a comparison of their gene expression patterns, which can help classify user data, such as stem cells, into different tissue types. In conclusion, CellExpress is a user-friendly tool that provides a comprehensive analysis of gene expression levels in both cell lines and clinical samples. The website is freely available at http://cellexpress.cgm.ntu.edu.tw/. Source code is available at https://github.com/LeeYiFang/Carkinos under the MIT License. Database URL: http://cellexpress.cgm.ntu.edu.tw/

scholarly journals Comparability of reference-based and reference-free transcriptome analysis approaches at the gene expression level

2021 ◽  
Vol 22 (S11) ◽  
Author(s):  
Sung-Gwon Lee ◽  
Dokyun Na ◽  
Chungoo Park
Keyword(s):  
Gene Expression ◽  
De Novo ◽  
Expression Profiles ◽  
Gene Families ◽  
Cell Types ◽  
Model Organisms ◽  
Expression Levels ◽  
Large Gene ◽  
Gene Expression Quantification ◽  
Gene Expression Levels

Abstract Background Lately, high-throughput RNA sequencing has been extensively used to elucidate the transcriptome landscape and dynamics of cell types of different species. In particular, for most non-model organisms lacking complete reference genomes with high-quality annotation of genetic information, reference-free (RF) de novo transcriptome analyses, rather than reference-based (RB) approaches, are widely used, and RF analyses have substantially contributed toward understanding the mechanisms regulating key biological processes and functions. To date, numerous bioinformatics studies have been conducted for assessing the workflow, production rate, and completeness of transcriptome assemblies within and between RF and RB datasets. However, the degree of consistency and variability of results obtained by analyzing gene expression levels through these two different approaches have not been adequately documented. Results In the present study, we evaluated the differences in expression profiles obtained with RF and RB approaches and revealed that the former tends to be satisfactorily replaced by the latter with respect to transcriptome repertoires, as well as from a gene expression quantification perspective. In addition, we urge cautious interpretation of these findings. Several genes that are lowly expressed, have long coding sequences, or belong to large gene families must be validated carefully, whenever gene expression levels are calculated using the RF method. Conclusions Our empirical results indicate important contributions toward addressing transcriptome-related biological questions in non-model organisms.

Targeting FOXM1 Transcription Factor In T-Cell Acute Lymphoblastic Leukemia

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 4974-4974 ◽  
Author(s):  
Özlem Tüfekçi ◽  
Melis Kartal Yandım ◽  
Hale Ören ◽  
Gülersu Irken ◽  
Yusuf Baran
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Cell Proliferation ◽  
Cell Line ◽  
Expression Profiles ◽  
Jurkat Cells ◽  
Pcr Array ◽  
Expression Levels ◽  
Siomycin A ◽  
Gene Expression Levels

Abstract The Forkhead box protein M1(FoxM1) is an important  transcriptional factor that takes play in regulation of cell cyle, proliferation, DNA repair, apoptosis, and angiogenesis. FoxM1 overexpression has been reported to be related with many types of cancer. Since many studies have reported that FOXM1 is an important target for cancer therapy, many researchers are studying on the identification of FOXM1 inhibitors. Siomycin A, a thiazol antibiotic, is known to inhibit FoxM1 transcriptional activity. Dexamethasone is a glucocorticoid  that is very important in treatment of acute lymphoblastic leukemia (ALL) and is known to be more potent compared to other steroids in the treatment of T-cell ALL. In this study, our aims were to determine the gene expression levels of FoxM1 in Jurkat cells (T-ALL cell line), to find out the possible synergistic and apoptotic effects of siomycin A and dexamethasone on this cell line and to investigate the changes in expression profiles of some important genes that have vital roles in cellular processes by targeting FoxM1 with siomycin A and dexamethasone on Jurkat cells. The gene expression levels of FoxM1 were studied with reverse transcriptase polymerase chain reaction (RT-PCR). The cytotoxic effects of siomycin  A and dexamethasone on Jurkat cells were assesed by MTT cell proliferation test.  The possible synergistic, additive, neutral, and antagonistic effect of combination of  dexamethasone and siomycin A was determined with isobologram analysis.  The apoptotic effects of these two agents were evaluated by  Caspase-3 activity, loss of mitochondrial membrane potential and localisation of phosphatidilserine on plasma membrane. For this purpose, Caspase-3 calorimetric assay kit, JC-1 mitochondrial membrane potential assay kit, and Annexin V-FITC apoptosis detection kit were used, respectively. For cell cycle analysis, Jurkat cells treated with siomycin A alone or in combination with dexamethasone were stained by propidium iodide and then analyzed by flow cytometry. Expression profiles of Jurkat cells treated with siomycin A alone or in combination with dexamethasone were determined by Cancer Pathway Finder PCR Array. We found that FoxM1 gene is overexpressed in T-ALL cell line and dexamethasone and siomycin A caused a reduction in gene expression levels of FoxM1 in Jurkat cells. 8% to 13% decrease in proliferation of Jurkat cells were observed when these cells were treated with 1 and 10 µM doses of dexamethasone for 72 hours, respectively. The same doses of dexamethasone combined with siomycin A caused 74% and 75% decrease in proliferation of Jurkat cells. Isobologram analysis revealed very strong synergy between dexamethasone and siomycin A. Apoptotic tests showed no apoptotic activity of dexamethasone and siomycin A on Jurkat cells. Cell cycle analysis demonstrated that, reduction of FOXM1 expression by combination of dexamethasone and siomycin A in Jurkat cells inhibited cell proliferation through induction of G1 phase arrest. PCR Array results showed that apoptotic CASPASE-2, CASPASE-7, and CASPASE-9 genes and XIAP and CYCLIN D3 genes were upregulated in response to the treatment. ETS2 gene, which is known as a protooncogene and shown to be involved in regulation of telomerase, was downregulated in response to siomycin A and dexamethosone alone and in combined treatment. TERF1 gene, which inhibits telomerase activity, was upregulated by the treatment. Combination of Siomycin A and dexamethasone downregulated the MCM-2 gene, which is a key component of the pre-replication complex and involved in the formation of DNA replication fork. Moreover, combined treatment resulted in the downregulation of MKI67 gene encoding a nuclear protein associated with  cellular proliferation. WEE1 gene, which inhibits G2/M phase transition in cell cycle, was also upregulated. These data indicate that FoxM1 gene is strongly overexpressed in T-ALL cell line and targeting FoxM1 by siomycin A and dexamethasone causes a significant decrease in T-ALL cell proliferation through induction of  G1 cell cycle arrest. Importantly, PCR array analyses also showed that siomycin A and dexamethasone treatment affects Jurkat cells via upregulating or downregulating the key genes of cell cycle, apoptosis, cell proliferation, telomere, and telomerase function. All these findings suggest a possible role for FoxM1 in T-ALL pathogenesis and represent FoxM1 as an attractive target for T-ALL therapy. Disclosures: No relevant conflicts of interest to declare.

scholarly journals A Sparse and Low-Rank Regression Model for Identifying the Relationships Between DNA Methylation and Gene Expression Levels in Gastric Cancer and the Prediction of Prognosis

Genes ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 854
Author(s):  
Yishu Wang ◽  
Lingyun Xu ◽  
Dongmei Ai
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Dna Methylation ◽  
Regression Model ◽  
The Cancer Genome Atlas ◽  
Low Rank ◽  
Expression Levels ◽  
Rank Regression ◽  
Prediction Of Prognosis ◽  
Gene Expression Levels

DNA methylation is an important regulator of gene expression that can influence tumor heterogeneity and shows weak and varying expression levels among different genes. Gastric cancer (GC) is a highly heterogeneous cancer of the digestive system with a high mortality rate worldwide. The heterogeneous subtypes of GC lead to different prognoses. In this study, we explored the relationships between DNA methylation and gene expression levels by introducing a sparse low-rank regression model based on a GC dataset with 375 tumor samples and 32 normal samples from The Cancer Genome Atlas database. Differences in the DNA methylation levels and sites were found to be associated with differences in the expressed genes related to GC development. Overall, 29 methylation-driven genes were found to be related to the GC subtypes, and in the prognostic model, we explored five prognoses related to the methylation sites. Finally, based on a low-rank matrix, seven subgroups were identified with different methylation statuses. These specific classifications based on DNA methylation levels may help to account for heterogeneity and aid in personalized treatments.

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