Identification of miR-29a-mediated target transcriptome in human pancreatic stellate cells (hPSCs) using RNAseq approach
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE144767 | GEO | 2020/07/20
REPOSITORIES: GEO
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Project description:In this study, we aim to understand the regulatory role of miR-29a in differential expression of genes and pathways associated with PDAC. Functional validation of the top candidate miR-29a targets identified from the RNASeq data delineates novel PDAC pathways paving the way for the development of de novo therapeutic strategies for PDAC treatment.
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Project description:To confirm the mechanism of miR-29a in liver fibrosis healing, we have employed whole genome microarray expression profiling as a discovery platform to identify genes. CCl4 and TAA liver fibrosis model mouse were used for this experiment. After five weeks liver fibrosis induction period, mouse have been observed for one week (1w) or two weeks (2w) and negative control nucleotide (N.C) or miR-29a were injected every 3 days on this period. We used CCl4 1w N.C (n = 1), 1w miR-29a (n = 1), 2w N.C (n = 1), 2w miR-29a (n = 1), and also used TAA model mouse (total n = 8) liver samples for microarray analysis. We can get only one gene (PDGF-c) as a target of miR-29a which relate to liver fibrosis and down-regulated more than 1.5 times in common miR-29a injected group than N.C group. CCl4 and TAA liver fibrosis model mouse were used for this experiment. After five weeks liver fibrosis induction period, mouse have been obserbed for one week (1w) or two weeks (2w) and negative control nucleotide (N.C) or miR-29a were injected every 3 days on this period. We used CCl4 1w N.C (n = 1), 1w miR-29a (n = 1), 2w N.C (n = 1), 2w miR-29a (n = 1), and also used TAA model mouse (total n = 8) liver samples for microarray analysis.
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Project description:The miR-29 family is an important player in the molecular pathophysiology of distinct types of cancer, with roles that seems to depend on cellular context. Reduced miR-29 levels are associated with more aggressive disease and its overexpression in cancer and leukemic cell lines inhibits proliferation. In contrast, its overexpression in hematopoietic progenitors, promotes leukemogenesis. We explored the potential roles of miR-29a in the molecular pathophysiology of T-cell acute lymphoblastic leukemia (T-ALL). As compared to normal T-cells, miR-29a levels are extremely reduced in T-ALL and in the Jurkat cell line. Microarrays analysis in Jurkat cells, following the introduction of synthetic miR-29a mimics, revealed the down-regulation of several predicted targets, including previously described targets (DNMT3a/b, CDK6, PXDN, MCL1, PIK3R1 and CXXC6), and novel targets with roles in active DNA demethylation, such as members of the ten-eleven-translocation (TET) family and TDG. Reduced miR-29a levels contribute to altered epigenetics, as its introduction in Jurkat cells, promotes the demethylation of the AHR gene (commonly methylated in T-ALL). In T-ALL patients, miR-29a levels are significantly associated with blast counts and disease free survival. Our results highlight the relevance of miR-29 in T-ALL physiopathology, and may help to clarify some contrasting findings reported in the literature. In order to identify potential miR-29a targets in T-cell lymphoblastic leukemia, Jurkat cells were electroporated with synthetic RNA molecules corresponding to miR-29a mimics (pre-miR) or inhibitors (anti-miR); and microarray profiles were compared to the profiles of Jurkat cells eletroporated with the corresponding negative controls. Transcripts with levels reduced following the introduction of the pre-miR-29a (as compared to pre-miR-Control), or transcripts acumulated folowing introduction of the anti-miR-29a inhibitor (as compared to anti-miR-Control), were considered potential targets; and were further compared to microRNA target prediction databases. Two paired samples were used for this analysis.
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Project description:Identification of miR-29a-mediated target transcriptome in human pancreatic stellate cells (hPSCs) using RNAseq approach
| PRJNA604801 | ENA