Gene Expression Profiling of Blood in Ruptured Intracranial Aneurysms: in Search of Biomarkers

The molecular mechanisms underlying the systemic response to subarachnoid hemorrhage (SAH) from ruptured intracranial aneurysms (RAs) are not fully understood. We investigated whether the analysis of gene expression in peripheral blood could provide clinically relevant information regarding the biologic consequences of SAH. Transcriptomics were performed using Illumina HumanHT-12v4 microarrays for 43 RA patients and 18 controls (C). Differentially expressed transcripts were analyzed for overrepresented functional groups and blood cell type-specific gene expression. The set of differentially expressed transcripts was validated using quantitative polymerase chain reaction in an independent group of subjects (15 RA patients and 14 C). There were 135 differentially expressed genes (false discovery rate ≤1%, absolute fold change ≤1.7): the abundant levels of 78 mRNAs increased and 57 mRNAs decreased. Among RA patients, transcripts specific to T lymphocyte subpopulations were downregulated, whereas those related to monocytes and neutrophils were upregulated. Expression profiles of a set of 16 genes and lymphocyte-to-monocyte-and-neutrophil gene expression ratios distinguished RA patients from C. These results indicate that SAH from RAs strongly influences the transcription profiles of blood cells. A specific pattern of these changes suggests suppression in lymphocyte response and enhancements in monocyte and neutrophil activities. This is probably related to the immunodepression observed in SAH.

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Insight into Molecular Profile Changes after Skeletal Muscle Contusion Using Microarray and Bioinformatics Analyses

10.21203/rs.3.rs-85830/v1 ◽

2020 ◽

Author(s):

Na Li ◽

Ru-feng Bai ◽

Chun Li ◽

Li-hong Dang ◽

Qiu-xiang Du ◽

...

Keyword(s):

Gene Expression ◽

Network Analysis ◽

Differentially Expressed Genes ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Healing Process ◽

Differentially Expressed ◽

Molecular Profile ◽

Wound Age ◽

Functional Modules

Abstract Background: Muscle trauma frequently occurs in daily life. However, the molecular mechanisms of muscle healing, which partly depend on the extent of the damage, are not well understood. This study aimed to investigate gene expression profiles following mild and severe muscle contusion, and to provide more information about the molecular mechanisms underlying the repair process.Methods: A total of 33 rats were divided randomly into control (n = 3), mild contusion (n = 15), and severe contusion (n = 15) groups; the contusion groups were further divided into five subgroups (1, 3, 24, 48, and 168 h post-injury; n = 3 per subgroup). Then full genome microarray of RNA isolated from muscle tissue was performed to access the gene expression changes during healing process.Results: A total of 2,844 and 2,298 differentially expressed genes were identified in the mild and severe contusion groups, respectively. The analysis of the overlapping differentially expressed genes showed that there are common mechanisms of transcriptomic repair of mild and severe contusion within 48 h post-contusion. This was supported by the results of principal component analysis, hierarchical clustering, and weighted gene co‐expression network analysis of the 1,620 coexpressed genes in mildly and severely contused muscle. From these analyses, we discovered that the gene profiles in functional modules and temporal clusters were similar between the mild and severe contusion groups; moreover, the genes showed time-dependent patterns of expression, which allowed us to identify useful markers of wound age. We then performed an analysis of the functions of genes (including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway annotation, and protein–protein interaction network analysis) in the functional modules and temporal clusters, and the hub genes in each module–cluster pair were identified. Interestingly, we found that genes downregulated within 24−48 h of the healing process were largely associated with metabolic processes, especially oxidative phosphorylation of reduced nicotinamide adenine dinucleotide phosphate, which has been rarely reported. Conclusions: These results improve our understanding of the molecular mechanisms underlying muscle repair, and provide a basis for further studies of wound age estimation.

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Convergent evolution of venom gland transcriptomes across Metazoa

10.1101/2021.07.04.451048 ◽

2021 ◽

Author(s):

Giulia Zancolli ◽

Maarten Reijnders ◽

Robert Waterhouse ◽

Marc Robinson-Rechavi

Keyword(s):

Gene Expression ◽

Regulatory Networks ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Venom Gland ◽

Bioactive Molecules ◽

Specific Gene ◽

Animal Kingdom ◽

Venom Glands

Animals have repeatedly evolved specialized organs and anatomical structures to produce and deliver a cocktail of potent bioactive molecules to subdue prey or predators: venom. This makes it one of the most widespread convergent functions in the animal kingdom. Whether animals have adopted the same genetic toolkit to evolved venom systems is a fascinating question that still eludes us. Here, we performed the first comparative analysis of venom gland transcriptomes from 20 venomous species spanning the main Metazoan lineages, to test whether different animals have independently adopted similar molecular mechanisms to perform the same function. We found a strong convergence in gene expression profiles, with venom glands being more similar to each other than to any other tissue from the same species, and their differences closely mirroring the species phylogeny. Although venom glands secrete some of the fastest evolving molecules (toxins), their gene expression does not evolve faster than evolutionarily older tissues. We found 15 venom gland specific gene modules enriched in endoplasmic reticulum stress and unfolded protein response pathways, indicating that animals have independently adopted stress response mechanisms to cope with mass production of toxins. This, in turns, activates regulatory networks for epithelial development, cell turnover and maintenance which seem composed of both convergent and lineage-specific factors, possibly reflecting the different developmental origins of venom glands. This study represents the first step towards an understanding of the molecular mechanisms underlying the repeated evolution of one of the most successful adaptive traits in the animal kingdom.

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Bioinformatics Analysis Reveals the Potential Diagnostic Biomarkers for Abdominal Aortic Aneurysm

Frontiers in Cardiovascular Medicine ◽

10.3389/fcvm.2021.656263 ◽

2021 ◽

Vol 8 ◽

Author(s):

Xinsheng Xie ◽

En ci Wang ◽

Dandan Xu ◽

Xiaolong Shu ◽

Yu fei Zhao ◽

...

Keyword(s):

Gene Expression ◽

Molecular Mechanisms ◽

Bioinformatics Analysis ◽

Inflammatory Responses ◽

Expression Profiles ◽

Enrichment Analysis ◽

Aortic Aneurysms ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Abdominal Aortic

Objectives: Abdominal aortic aneurysms (AAAs) are associated with high mortality rates. The genes and pathways linked with AAA remain poorly understood. This study aimed to identify key differentially expressed genes (DEGs) linked to the progression of AAA using bioinformatics analysis.Methods: Gene expression profiles of the GSE47472 and GSE57691 datasets were acquired from the Gene Expression Omnibus (GEO) database. These datasets were merged and normalized using the “sva” R package, and DEGs were identified using the limma package in R. The functions of these DEGs were assessed using Cytoscape software. We analyzed the DEGs using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Protein–protein interaction networks were assembled using Cytoscape, and crucial genes were identified using the Cytoscape plugin, molecular complex detection. Data from GSE15729 and GSE24342 were also extracted to verify our findings.Results: We found that 120 genes were differentially expressed in AAA. Genes associated with inflammatory responses and nuclear-transcribed mRNA catabolic process were clustered in two gene modules in AAA. The hub genes of the two modules were IL6, RPL21, and RPL7A. The expression levels of IL6 correlated positively with RPL7A and negatively with RPL21. The expression of RPL21 and RPL7A was downregulated, whereas that of IL6 was upregulated in AAA.Conclusions: The expression of RPL21 or RPL7A combined with IL6 has a diagnostic value for AAA. The novel DEGs and pathways identified herein might provide new insights into the underlying molecular mechanisms of AAA.

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Molecular Phenotype of Malignant CD34+ Hematopoietic Stem and Progenitor Cells in Chronic Myelogenous Leukemia.

Blood ◽

10.1182/blood.v106.11.2863.2863 ◽

2005 ◽

Vol 106 (11) ◽

pp. 2863-2863

Author(s):

Ralf Kronenwett ◽

Elena Diaz-Blanco ◽

Thorsten Graef ◽

Ulrich Steidl ◽

Slawomir Kliszewski ◽

...

Keyword(s):

Gene Expression ◽

Fatty Acid ◽

Expression Profiles ◽

Expression Patterns ◽

Gene Expression Pattern ◽

Leukemic Cell ◽

Differentially Expressed ◽

Specific Gene ◽

Hematopoietic Stem ◽

Cd34 Cells

Abstract In this study, we examined gene expression profiles of immunomagnetically enriched CD34+ cells from bone marrow (BM) of 9 patients with untreated CML in chronic phase and from 8 healthy volunteers using Affymetrix GeneChips. Additionally, in 3 patients CD34+ from peripheral blood (PB) were compared with those from BM. Differential expression of 12 candidate genes was corroborated by quantitative real-time RT-PCR. Following hybridization of labelled cRNA to Affymetrix GeneChips covering 8793 genes we used the statistical scripting language “R” for data analysis. For normalization a method of variance stabilization transformations was used. To identify significantly differentially expressed genes we used the Significance Analysis of Microarrays (SAM) algorithm. The intraindividual comparison of CD34+ cells from BM and PB in CML showed no differentially expressed genes which is different to normal CD34+ cells which had distinct gene expression patterns comparing circulating and sedentary CD34+ cells (Steidl et al., Blood, 2002). Comparing malignant BM CD34+ cells from CML with normal BM CD34+ cells 792 genes were significantly differentially expressed (fold change: >1.3; q-value: <0.03). 735 genes had a higher and 57 genes a lower expression in CML. Gene expression patterns reflected BCR-ABL-induced functional alterations such as increased cell-cycle and proteasome activity as well as decreased apoptosis. Downregulation of several genes involved in DNA repair and detoxification in CML might be the basis for DNA instability and progression to blast crisis. An interesting finding was an upregulation of fetal hemoglobin (Hb) components such as Hb gamma A and G in leukemic progenitor cells whereas no difference in adult Hb expression was observed suggesting an induction of fetal Hb synthesis in CML. Looking at genes involved in stem cell maintenance we found an upregulation of GATA2 and a reduced expression of proteins from the Wnt signalling pathway suggesting an increased self-renewal of CML hematopoietic stem cells compared to the normal counterpart. Moreover, several genes playing a role in ubiquitin-dependent protein catabolism and in fatty acid biosynthesis such as fatty acid synthase (FAS) were stronger expressed in CML. The functional role of FAS for leukemic cell growth was assessed in cell culture experiments. Incubation of the leukemic cell line K562 with the FAS inhibitor cerulenin (10 μg/ml) for 3 days resulted in death of 99% of cells suggesting that survival of leukemic cells depends upon endogenous fatty acid synthesis. In an attempt to find a specific gene expression pattern associated with response to imatinib therapy we divided the patients included in this study into two groups: maximal reduction of BCR-ABL transcript level <3-log vs. >3-log (major molecular remission) during therapy. Comparing pretherapeutic gene expression profiles of both groups we could not identify a pattern predictive for major molecular response. In conclusion, malignant CD34+ cells in CML have a specific gene expression pattern which seems not to be predictive for response to imatinib therapy.

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Tumor-specific and Proliferation-specific Gene Expression Typifies Murine Transgenic B Cell Lymphomagenesis

Journal of Biological Chemistry ◽

10.1074/jbc.m605870200 ◽

2006 ◽

Vol 282 (7) ◽

pp. 4803-4811 ◽

Cited By ~ 27

Author(s):

Marc E. Lenburg ◽

Anupama Sinha ◽

Douglas V. Faller ◽

Gerald V. Denis

Keyword(s):

Gene Expression ◽

Cell Cycle ◽

B Cell ◽

Cell Cycle Progression ◽

Cellular Proliferation ◽

Expression Profiles ◽

Expression Patterns ◽

B Cell Lymphoma ◽

Specific Pattern ◽

Specific Gene

The dual bromodomain protein Brd2 is closely related to the basal transcription factor TAFII250, which is essential for cyclin A transactivation and mammalian cell cycle progression. In transgenic mice, constitutive lymphoid expression of Brd2 causes a malignancy most similar to human diffuse large B cell lymphoma. We compare the genome-wide transcriptional expression profiles of these lymphomas with those of proliferating and resting normal B cells. Transgenic tumors reproducibly show differential expression of a large number of genes important for cell cycle control and lymphocyte biology; expression patterns are either tumor-specific or proliferation-specific. Several of their human orthologs have been implicated in human lymphomagenesis. Others correlate with human disease survival time. BRD2 is underexpressed in some subtypes of human lymphoma and these subtypes display a number of similarities to the BRD2-mediated murine tumors. We illustrate with a high degree of detail that cancer is more than rampant cellular proliferation, but involves the additional transcriptional mobilization of many genes, some of them poorly characterized, which show a tumor-specific pattern of gene expression.

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Vertical sleeve gastrectomy induces distinctive transcriptomic responses in liver, fat and muscle

Scientific Reports ◽

10.1038/s41598-021-81866-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Chang Ho Ahn ◽

Eun Hye Choi ◽

Hyunjung Lee ◽

Woochan Lee ◽

Jong-Il Kim ◽

...

Keyword(s):

Gene Expression ◽

Sleeve Gastrectomy ◽

Molecular Mechanisms ◽

Sham Group ◽

Expression Profiles ◽

Transcriptomic Analysis ◽

High Rate ◽

Liver Fat ◽

Specific Gene ◽

Vertical Sleeve Gastrectomy

AbstractVertical sleeve gastrectomy (VSG) is the most commonly performed bariatric/metabolic surgery, exhibiting a high rate of diabetes remission in humans. To elucidate the molecular mechanisms of VSG, we performed transcriptomic analysis of the liver, fat, and muscle in VSG mice. C57BL/6 mice fed a high-fat diet were randomly assigned to sham or VSG surgery. The sham-operated mice were fed ad libitum (sham group) or pair-fed (sham-PF group) matching their food intake to the VSG-operated mice. Comparative transcriptomic analysis of the liver, fat, and muscle using RNA sequencing was performed. VSG reduced body weight and improved glucose tolerance compared to the sham group, but not more than the sham-PF group. Improvement in fatty liver and adipose tissue inflammation was comparable between VSG and sham-PF. However, global gene expression profiles showed distinctive changes in the liver, fat, and muscle of the VSG group compared to both the sham or sham-PF groups. The liver showed the most prominent gene expression changes. Immune response-related pathways were commonly upregulated in the three organs of the VSG group compared to the sham or sham-PF. VSG induces organ-specific gene expression changes in the liver, fat, and muscle, which may play critical roles in metabolic improvements after VSG.

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Construction and analysis of mRNA, miRNA, lncRNA, and TF regulatory networks reveal the key genes in prostate cancer

10.1101/323543 ◽

2018 ◽

Author(s):

Su-Liang Li ◽

Yun Ye ◽

Sheng-Yu Wang

Keyword(s):

Gene Expression ◽

Prostate Cancer ◽

Large Scale ◽

Molecular Mechanisms ◽

Scale Effects ◽

Expression Profiles ◽

Differentially Expressed ◽

Regulation Of Transcription ◽

Normal Prostate ◽

Ppi Networks

AbstractPurpose: Prostate cancer (PCa) causes a common male urinary system malignant tumour, and the molecular mechanisms of PCa remain poorly understood. This study aims to investigate the underlying molecular mechanisms of PCa with bioinformatics.Methods: Original gene expression profiles were obtained from the GSE64318 and GSE46602 datasets in the Gene Expression Omnibus (GEO). We conducted differential screens of the expression of genes (DEGs) between two groups using the R software limma package. The interactions between the differentially expressed miRNAs, mRNAs and lncRNAs were predicted and merged with the target genes. Co-expression of the miRNAs, lncRNAs and mRNAs were selected to construct the mRNA-miRNA and-lncRNA interaction networks. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed for the DEGs. The protein-protein interaction (PPI) networks were constructed, and the transcription factors were annotated. The expression of hub genes in the TCGA datasets was verified to improve the reliability of our analysis.Results: The results demonstrated that 60 miRNAs, 1578 mRNAs and 61 lncRNAs were differentially expressed in PCa. The mRNA-miRNA-lncRNA networks were composed of 5 miRNA nodes, 13 lncRNA nodes, and 45 mRNA nodes. The DEGs were mainly enriched in the nuclei and cytoplasm and were involved in the regulation of transcription, related to sequence-specific DNA binding, and participated in the regulation of the PI3K-Akt signalling pathway. These pathways are related to cancer and focal adhesion signalling pathways. Furthermore, we found that 5 miRNAs, 6 lncRNAs, 6 mRNAs and 2 TFs play important regulatory roles in the interaction network. The expression levels of EGFR, VEGFA, PIK3R1, DLG4, TGFBR1 and KIT were significantly different between PCa and normal prostate tissue.Conclusion: Based on the current study, large-scale effects of interrelated mRNAs, miRNAs, lncRNAs, and TFs were revealed and a model for predicting the mechanism of PCa was provided. This study provides new insight for the exploration of the molecular mechanisms of PCa and valuable clues for further research.

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What Do Machines Tell us About Dementia? Machine Learning Applied to Aging, Dementia and Traumatic Brain Injury Study

10.21203/rs.3.rs-840907/v1 ◽

2021 ◽

Author(s):

Denis Arthur Pinheiro Moura ◽

Joao Ricardo Mendes de Oliveira

Keyword(s):

Gene Expression ◽

Machine Learning ◽

Traumatic Brain Injury ◽

Brain Injury ◽

Expression Profiles ◽

Brain Regions ◽

Machine Learning Algorithms ◽

Differentially Expressed ◽

Classification Model ◽

Specific Gene

Abstract Dementia, a syndrome characterized by the progressive deterioration of memory and cognition, arises from different pathologies, with Alzheimer's Disease (AD) its most common cause. Patterns of gene expression during dementia of different etiologies may function as generalist biomarkers of the condition. We used RNA-Seq data from the Allen Dementia and Traumatic Brain Injury Study (ADTBI) to identify differentially expressed genes in brains with dementia. Machine Learning algorithms Decision Trees (DT) and Random Forest (RF) were used to create models to identify dementia samples based on their gene expression profile. Importance analyses were conducted to identify the most relevant genes in each classification model. A total of 1629 differentially expressed (DE) genes were found in brains with the condition. Gene PAN3-AS1 was the only DE gene across more than three brain regions. The artificial intelligence models were capable of identifying correctly up to 92.85% of dementia samples. Our analyses provide interesting insights regarding using brain-specific gene expression profiles as biomarkers of dementia, identifying genes possibly involved with dementia, and guiding future studies in prediction and early identification of the syndrome.

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Network Pharmacology of Red Ginseng (Part I): Effects of Ginsenoside Rg5 at Physiological and Sub-Physiological Concentrations

Pharmaceuticals ◽

10.3390/ph14100999 ◽

2021 ◽

Vol 14 (10) ◽

pp. 999

Author(s):

Alexander Panossian ◽

Sara Abdelfatah ◽

Thomas Efferth

Keyword(s):

Gene Expression ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Differentially Expressed ◽

Network Pharmacology ◽

Pharmacokinetic Studies ◽

Red Ginseng ◽

Toxic Concentration ◽

Wide Range ◽

Ginsenoside Rg5

Numerous in vitro studies on isolated cells have been conducted to uncover the molecular mechanisms of action of Panax ginseng Meyer root extracts and purified ginsenosides. However, the concentrations of ginsenosides and the extracts used in these studies were much higher than those detected in pharmacokinetic studies in humans and animals orally administered with ginseng preparations at therapeutic doses. Our study aimed to assess: (a) the effects of ginsenoside Rg5, the major “rare” ginsenoside of Red Ginseng, on gene expression in the murine neuronal cell line HT22 in a wide range of concentrations, from 10−4 to 10−18 M, and (b) the effects of differentially expressed genes on cellular and physiological functions in organismal disorders and diseases. Gene expression profiling was performed by transcriptome-wide mRNA microarray analyses in HT22 cells after treatment with ginsenoside Rg5. Ginsenoside Rg5 exhibits soft-acting effects on gene expression of neuronal cells in a wide range of physiological concentrations and strong reversal impact at high (toxic) concentration: significant up- or downregulation of expression of about 300 genes at concentrations from 10−6 M to 10−18 M, and dramatically increased both the number of differentially expressed target genes (up to 1670) and the extent of their expression (fold changes compared to unexposed cells) at a toxic concentration of 10−4 M. Network pharmacology analyses of genes’ expression profiles using ingenuity pathway analysis (IPA) software showed that at low physiological concentrations, ginsenoside Rg5 has the potential to activate the biosynthesis of cholesterol and to exhibit predictable effects in senescence, neuroinflammation, apoptosis, and immune response, suggesting soft-acting, beneficial effects on organismal death, movement disorders, and cancer.

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Network Pharmacology of Red Ginseng (Part I): Effects of Ginsenoside Rg5 at Physiological and Sub-Physiological Concentrations

10.20944/preprints202109.0281.v1 ◽

2021 ◽

Author(s):

Alexander Panossian ◽

Sara Abdelfatah ◽

Thomas Efferth

Keyword(s):

Gene Expression ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Differentially Expressed ◽

Network Pharmacology ◽

Pharmacokinetic Studies ◽

Red Ginseng ◽

Toxic Concentration ◽

Wide Range ◽

Ginsenoside Rg5

Numerous in vitro studies on isolated cells have been conducted to uncover the molecular mechanisms of action of Panax ginseng Meyer root extracts and purified ginsenosides. However, the concentrations of ginsenosides and the extracts used in these studies were much higher than detected in pharmacokinetic studies in humans and animals orally administered with ginseng preparations at therapeutic doses. Our study aimed to assess: (a) the effects of ginsenoside Rg5, the major "rare" ginsenoside of Red Ginseng, on gene expression in the murine neuronal cell line HT22 in a wide range of concentrations, from 10-4 to 10-18 M, and (b) the effects of differentially expressed genes on cellular and physiological functions in organismal disorders and diseases. Gene expression profiling was performed by transcriptome-wide mRNA microarray analyses in HT22 cells after treatment with ginsenoside Rg5. Ginsenoside Rg5 exhibits soft-acting effects on gene expression of neuronal cells in a wide range of physiological concentrations and strong reversal impact at high (toxic) concentration: significant up- or downregulation of expression of about 300 genes at concentrations from 10-6 M to 10-18 M, and dramatically increased both the number of differentially expressed target genes (up to 1670) and the extent of their expression (fold changes compared to unexposed cells) at a toxic concentration of 10-4 M. Network pharmacology analyses of genes expression profiles using Ingenuity pathway analysis (IPA) software showed that at low physiological concentrations, ginsenoside Rg5 has the potential to activate the biosynthesis of cholesterol and to exhibit predictable effects in senescence, neuroinflammation, apoptosis, and immune response, suggesting soft-acting, beneficial effects on organismal death, movement disorders, and cancer.

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