Muscle miRNAs are influenced by sex at baseline and in response to exercise
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE242861 | GEO | 2023/10/05
REPOSITORIES: GEO
Similar Datasets
Project description:iPSC-derived neurons were treated with mimics and inhibitors of the miRNAs miR-150-5p, hsa-mir-193a-3p and hsa-miR-19b-3p.
RNA-sequencing was then performed to examine the effects of miRNA up-regulation and inhibition.
| EGAD00001006844 | EGA
Project description:Background: Laryngeal squamous cell carcinoma (LSCC) is the most common type in head and neck squamous cell carcinoma (HNSCC), and the development of LSCC are multistep processes accompanied by changes of molecular biology. Objective: The purpose of this study was to investigate the miRNAs basis of tumorigenesis in LSCC, and analyze the microRNAs dysregulation related with the six targeted genes (CDK1,CDK2, CDK4, MCM2, MCM3, MCM4) which were related to tumorigenesis from the screened miRNAs. Methods: A total number of 5 patients who underwent surgery for primary laryngeal squamous cell carcinoma were recruited for miRNA array analysis. LSCC tissues compared with corresponding adjacent non-neoplastic tissues were analysed by the Affymetrix GeneChip miRNA Array 3.0 to screen effective miRNAs, then mirfocus 3.0 database (http://mirfocus.org/index.php) was adopted to select putative regulated miRNAs of the six targeted genes. Moreover, the selected putative regulated miRNAs were also validated by qRT-PCR in another 36 patients diagnosed for LSCC. Results: Analysed by the miRNAs arrays, there were 127 miRNAs significantly related to tumorigenesis ,and 78 showed a higher expression in tumor than in non-tumor tissue while 49 presented the contrasting pattern(P<0.01).Then analyzed by mirfocus 3.0 database, there were 2 putative regulated miRNAs, hsa-miR-24-3p and hsa-miR-183-5p, corresponding to three of the six targeted genes. Among the 2 putative miRNAs, hsa-miR-24-3p regulated MCM4,CDK1 and CDK4,while hsa-miR-183-5p regulated MCM4 only. Another miRNA we should focus on is hsa-miR-30a-5p, a tumor-suppressive factor, which was down-expressed obviously analysed by the miRNAs arrays. The expression of the 3 putative regulated miRNAs were also validated by qRT-PCR in another 36 patients (P<0.05). Conclusions: The research revealed 127 miRNAs expression signature of tumorigenesis in laryngeal squamous cell carcinoma,and analyzed 3 putative regulated miRNAs, hsa-miR-24-3p, hsa-miR-183-5p and hsa-miR-30a-5p, as potential diagnostic and therapeutic markers in LSCC. The result will contribute to the understanding of the molecular basis of LSCC and help to improve the treatment.
2014-10-30 | GSE62819 | GEO
Project description:Cancer cachexia is a multifactorial metabolic syndrome defined by the rapid loss of skeletal muscle mass and the loss of fat mass. Up 80% of cancer patients at the late stage with cachexia suffer from progressive atrophy of adipose tissue. Unlike studies on skeletal muscle wasting, there is limited research on fat loss in cachexia. It was noted that most patients suffer from fat loss as cancer progress. Fat loss precedes muscle loss, is associated with shorter survival, and is variable to timing and intensity in various cancer populations. Increased lipolysis may be the leading cause of fat loss in cancer cachexia. miRNAs are a class of non-coding RNAs of 19~25 nucleotides that regulate gene silencing by interacting with the 3’ untranslated region (UTR) of target mRNA to cause mRNA degradation and translational repression. miRNAs play multifaceted roles in pancreatic cancer proliferation, survival, metastasis, and chemoresistance. Aberrant expression of miRNA in circulating exosomes may play potential roles in modulating fat loss in cancer cachexia. We identified 2 miRNAs, miR-16 and miR-29, which have 2-fold higher expression existed in at PDAC cells. To explore which genes in adipogenesis and lipolysis were directly affected by miR-16-5p or/and miR-29a-3p, we analyzed the targets which were down-regulated in both miR-16-5p and miR-29a-3p-transfected 3T3-L1 cells by mass analysis.
2024-06-13 | PXD037862 | Pride
Project description:Cancer cachexia is a multifactorial metabolic syndrome defined by the rapid loss of skeletal muscle mass and the loss of fat mass. Up 80% of cancer patients at the late stage with cachexia suffer from progressive atrophy of adipose tissue. Unlike studies on skeletal muscle wasting, there is limited research on fat loss in cachexia. It was noted that most patients suffer from fat loss as cancer progress. Fat loss precedes muscle loss, is associated with shorter survival, and is variable to timing and intensity in various cancer populations. Increased lipolysis may be the leading cause of fat loss in cancer cachexia. miRNAs are a class of non-coding RNAs of 19~25 nucleotides that regulate gene silencing by interacting with the 3’ untranslated region (UTR) of target mRNA to cause mRNA degradation and translational repression. miRNAs play multifaceted roles in pancreatic cancer proliferation, survival, metastasis, and chemoresistance. Aberrant expression of miRNA in circulating exosomes may play potential roles in modulating fat loss in cancer cachexia. We identified 2 miRNAs, miR-16 and miR-29, which have 2-fold higher expression existed in at PDAC cells. To explore which genes in adipogenesis and lipolysis were directly affected by miR-16-5p or/and miR-29a-3p, we analyzed the targets which were down-regulated in both miR-16-5p and miR-29a-3p-transfected 3T3-L1 cells by mass analysis.
2024-06-13 | PXD037998 | Pride
Project description:Microglia were derived from iPSCs and treated with mimics and inhibitors of the miRNAs hsa-miR-150-5p, hsa-miR-193a-3p and hsa-miR-19b-3p. RNA-sequencing was then performed to examine the effects of up- and down-regulation of the respective miRNAs.
| EGAD00001006842 | EGA
Project description:Background. Human Metapneumovirus (HMPV) and Respiratory Syncytial Virus (RSV), are responsible for respiratory diseases mostly in children. In spite of the resemblance between these two pneumoviruses, they elicit a different extent of immune response. miRNAs are small non coding RNAs that regulate gene expression and are involved in numerous cellular processes including the immune system. Methodology. Human monocyte-derived dendritic cells (moDC) were differentiated from peripheral blood mononuclear cells and infected at an MOI of 3 for 24h. RNA was isolated to analyze the miRNAs transcription by high throughput sequencing using illumina technology. Principal findings. Infection with HMPV up-regulated the expression of hsa-miR-4448, while RSV infection induced significant expression of hsa-miR-30a-5p, hsa-miR-182-5p, hsa-miR-1913, hsa37, miR-4448 and hsa-miR-4634. Conclusions/Significance. In human monocyte derived dendritic cells (moDC), RSV and HMPV induced different profiles of miRNA expression. Understanding the changes of miRNA expression profiles by RSV and HMPV in immune cells will further our understanding of the differential immune response induced by these respiratory viruses
2018-12-10 | GSE111732 | GEO
Project description:Applying Next Generation Sequencing technique we compared the miRNA expression pattern of tumor tissue sample of 6 GPs and peritumoral region of 6 lower grade (I-II) Glioma patients, serving as control group. To determine the difference on miRNA expresion level between GBM and control cases, we performed cluster analysis on the NGS dataset of 6 replicates for each of the two goups of samples with iDEP 96 software. In order to characterize the extent of up- or downregulation, log2FC values were calculated using the iDEP.96 web tool applying the DESeq2 algorithm. On the base of that 117 known miRNAs were identified to be differentially expressed using a threshold of false discovery rate (FDR) <0.05 and fold-change> 2 during the analysis. Among them, 35 miRNAs were upregulated (log2FC > 2) and 82 miRNAs were downregulated (log2FC < -2) with biological revelance in tissue samples comparing with the control samples. To validate our results obtained by NGS, five upregulated miRNAs: hsa-miR-196a-5p, hsa-miR-21-3p, hsa-miR-92b-5p, hsa-miR-10b-3p, hsa-miR-503-5p and three downregulated miRNAs: hsa-mir-383-5p, hsa-mir-490-3p, hsa-mir-1224-3p were chosen for RT-qPCR analysis. As the result of that hsa-miR-196a-5p, hsa-miR-21-3p, and hsa-miR-10b-3p was significantly upregulated while hsa-mir-383-5p and hsa-mir-490-3p was significantly downregulated, compared with those in the control samples. The other three miRNAs: hsa-miR-1224-3p, hsa-miR-92b-5p, hsa-miR-503-5p did not show significant difference between the control group and GPs.
2024-10-31 | GSE244332 | GEO
Project description:Proctor2017 - Identifying microRNA for muscle
regeneration during ageing (Mirs_in_muscle)
This model is described in the article:
Using computer simulation
models to investigate the most promising microRNAs to improve
muscle regeneration during ageing
Carole J. Proctor & Katarzyna
Goljanek-Whysall
Nature Scientific Reports
Abstract:
MicroRNAs (miRNAs) regulate gene expression through
interactions with target sites within mRNAs, leading to
enhanced degradation of the mRNA or inhibition of translation.
Skeletal muscle expresses many different miRNAs with important
roles in adulthood myogenesis (regeneration) and myofibre
hypertrophy and atrophy, processes associated with muscle
ageing. However, the large number of miRNAs and their targets
mean that a complex network of pathways exists, making it
difficult to predict the effect of selected miRNAs on
age-related muscle wasting. Computational modelling has the
potential to aid this process as it is possible to combine
models of individual miRNA:target interactions to form an
integrated network. As yet, no models of these interactions in
muscle exist. We created the first model of miRNA:target
interactions in myogenesis based on experimental evidence of
individual miRNAs which were next validated and used to make
testable predictions. Our model confirms that miRNAs regulate
key interactions during myogenesis and can act by promoting the
switch between quiescent/proliferating/differentiating
myoblasts and by maintaining the differentiation process. We
propose that a threshold level of miR-1 acts in the initial
switch to differentiation, with miR-181 keeping the switch on
and miR-378 maintaining the differentiation and miR-143
inhibiting myogenesis.
This model is hosted on
BioModels Database
and identified by:
MODEL1704110004.
To cite BioModels Database, please use:
Chelliah V et al. BioModels: ten-year
anniversary. Nucl. Acids Res. 2015, 43(Database
issue):D542-8.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2017-09-26 | MODEL1704110004 | BioModels
Project description:Proctor2017 - Identifying microRNA for muscle regeneration during ageing (Mir1_in_muscle)
This model is described in the article:
Using computer simulation
models to investigate the most promising microRNAs to improve
muscle regeneration during ageing
Carole J. Proctor & Katarzyna
Goljanek-Whysall
Nature Scientific Reports
Abstract:
MicroRNAs (miRNAs) regulate gene expression through
interactions with target sites within mRNAs, leading to
enhanced degradation of the mRNA or inhibition of translation.
Skeletal muscle expresses many different miRNAs with important
roles in adulthood myogenesis (regeneration) and myofibre
hypertrophy and atrophy, processes associated with muscle
ageing. However, the large number of miRNAs and their targets
mean that a complex network of pathways exists, making it
difficult to predict the effect of selected miRNAs on
age-related muscle wasting. Computational modelling has the
potential to aid this process as it is possible to combine
models of individual miRNA:target interactions to form an
integrated network. As yet, no models of these interactions in
muscle exist. We created the first model of miRNA:target
interactions in myogenesis based on experimental evidence of
individual miRNAs which were next validated and used to make
testable predictions. Our model confirms that miRNAs regulate
key interactions during myogenesis and can act by promoting the
switch between quiescent/proliferating/differentiating
myoblasts and by maintaining the differentiation process. We
propose that a threshold level of miR-1 acts in the initial
switch to differentiation, with miR-181 keeping the switch on
and miR-378 maintaining the differentiation and miR-143
inhibiting myogenesis.
This model is hosted on
BioModels Database
and identified by:
MODEL1704110000.
To cite BioModels Database, please use:
Chelliah V et al. BioModels: ten-year
anniversary. Nucl. Acids Res. 2015, 43(Database
issue):D542-8.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2017-09-26 | MODEL1704110000 | BioModels
Project description:Proctor2017 - Identifying microRNA for muscle
regeneration during ageing (Mir181_in_muscle)
This model is described in the article:
Using computer simulation
models to investigate the most promising microRNAs to improve
muscle regeneration during ageing
Carole J. Proctor & Katarzyna
Goljanek-Whysall
Scientific Reports
Abstract:
MicroRNAs (miRNAs) regulate gene expression through
interactions with target sites within mRNAs, leading to
enhanced degradation of the mRNA or inhibition of translation.
Skeletal muscle expresses many different miRNAs with important
roles in adulthood myogenesis (regeneration) and myofibre
hypertrophy and atrophy, processes associated with muscle
ageing. However, the large number of miRNAs and their targets
mean that a complex network of pathways exists, making it
difficult to predict the effect of selected miRNAs on
age-related muscle wasting. Computational modelling has the
potential to aid this process as it is possible to combine
models of individual miRNA:target interactions to form an
integrated network. As yet, no models of these interactions in
muscle exist. We created the first model of miRNA:target
interactions in myogenesis based on experimental evidence of
individual miRNAs which were next validated and used to make
testable predictions. Our model confirms that miRNAs regulate
key interactions during myogenesis and can act by promoting the
switch between quiescent/proliferating/differentiating
myoblasts and by maintaining the differentiation process. We
propose that a threshold level of miR-1 acts in the initial
switch to differentiation, with miR-181 keeping the switch on
and miR-378 maintaining the differentiation and miR-143
inhibiting myogenesis.
This model is hosted on
BioModels Database
and identified by:
MODEL1704110001.
To cite BioModels Database, please use:
Chelliah V et al. BioModels: ten-year
anniversary. Nucl. Acids Res. 2015, 43(Database
issue):D542-8.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2017-09-26 | MODEL1704110001 | BioModels