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Overexpression of the microRNA miR-433 promotes resistance to paclitaxel through the induction of cellular senescence in ovarian cancer cells.

Weiner-Gorzel K, Dempsey E, Milewska M, McGoldrick A, Toh V, Walsh A, Lindsay S, Gubbins L, Cannon A, Sharpe D, O'Sullivan J, Murphy M, Madden SF, Kell M, McCann A, Furlong F - Cancer Med (2015)

Bottom Line: Mechanistically, we demonstrate that downregulation of p-Rb is attributable to a miR-433-dependent downregulation of CDK6, establishing it as a novel miR-433 associated gene.Interestingly, we show that high miR-433 expressing cells release miR-433 into the growth media via exosomes which in turn can induce a senescence bystander effect.Furthermore, in relation to a chemotherapeutic response, quantitative real-time polymerase chain reaction (qRT-PCR) analysis revealed that only PEO1 and PEO4 OC cells with the highest miR-433 expression survive paclitaxel treatment.

View Article: PubMed Central - PubMed

Affiliation: UCD School of Medicine and Medical Science (SMMS), UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin 4, Ireland.

No MeSH data available.


Related in: MedlinePlus

Bioinformatic analysis highlights miR-433 potential influence on cellular senescence. (A) Venn diagram showing overlapping genes (CDK6, MAPK14, CDKN2B, and E2F3) between senescence-associated genes and miR-433 target genes. (B) Overview of the interaction between miR-433 target genes (blue nodes) and senescence-associated genes (blue nodes), overlapping nodes are colored yellow. (C) Focus on overlapping genes (yellow nodes) and first degree neighbors in both the senescence-associated genes (green nodes) or predicted miR-433 targets (blue nodes). Blue edges indicate experimentally validated protein–protein interactions, magenta edges indicate predicted interactions with miR-433 (red node).
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fig02: Bioinformatic analysis highlights miR-433 potential influence on cellular senescence. (A) Venn diagram showing overlapping genes (CDK6, MAPK14, CDKN2B, and E2F3) between senescence-associated genes and miR-433 target genes. (B) Overview of the interaction between miR-433 target genes (blue nodes) and senescence-associated genes (blue nodes), overlapping nodes are colored yellow. (C) Focus on overlapping genes (yellow nodes) and first degree neighbors in both the senescence-associated genes (green nodes) or predicted miR-433 targets (blue nodes). Blue edges indicate experimentally validated protein–protein interactions, magenta edges indicate predicted interactions with miR-433 (red node).

Mentions: Having identified candidate miR-433 target genes, we next wanted to determine the potential for these genes to impact on cellular senescence. Well-established genes associated with cellular senescence were identified from the literature, yielding a list of approximately 86 genes (Table S3). Next, we constructed an overlap with the 1204 putative miR-433 target genes and identified four overlapping genes including CDK6, MAPK14, E2F3, and CDKN2A (Fig.2A). To further investigate the interaction between potential miR-433 targets and senescence-associated genes, we built an interaction network in Cytoscape using both ClueGo and Cluepedia apps. Only previously experimentally validated PPIs were included in the construction of the network. From this analysis, we identify a significant number of interactions between well-established cellular senescence genes and our list of miR-433 target genes (Fig.2B). By focusing in on the first degree neighbors of the four overlapping genes we identified a number of possible miR-433 targets which regulate the function of key cellular senescence genes such as Rb (Fig.2C). Overall, this indicated the possible role of miR-433 regulating the induction of cellular senescence in our stably transfected cells.


Overexpression of the microRNA miR-433 promotes resistance to paclitaxel through the induction of cellular senescence in ovarian cancer cells.

Weiner-Gorzel K, Dempsey E, Milewska M, McGoldrick A, Toh V, Walsh A, Lindsay S, Gubbins L, Cannon A, Sharpe D, O'Sullivan J, Murphy M, Madden SF, Kell M, McCann A, Furlong F - Cancer Med (2015)

Bioinformatic analysis highlights miR-433 potential influence on cellular senescence. (A) Venn diagram showing overlapping genes (CDK6, MAPK14, CDKN2B, and E2F3) between senescence-associated genes and miR-433 target genes. (B) Overview of the interaction between miR-433 target genes (blue nodes) and senescence-associated genes (blue nodes), overlapping nodes are colored yellow. (C) Focus on overlapping genes (yellow nodes) and first degree neighbors in both the senescence-associated genes (green nodes) or predicted miR-433 targets (blue nodes). Blue edges indicate experimentally validated protein–protein interactions, magenta edges indicate predicted interactions with miR-433 (red node).
© Copyright Policy - open-access
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4430267&req=5

fig02: Bioinformatic analysis highlights miR-433 potential influence on cellular senescence. (A) Venn diagram showing overlapping genes (CDK6, MAPK14, CDKN2B, and E2F3) between senescence-associated genes and miR-433 target genes. (B) Overview of the interaction between miR-433 target genes (blue nodes) and senescence-associated genes (blue nodes), overlapping nodes are colored yellow. (C) Focus on overlapping genes (yellow nodes) and first degree neighbors in both the senescence-associated genes (green nodes) or predicted miR-433 targets (blue nodes). Blue edges indicate experimentally validated protein–protein interactions, magenta edges indicate predicted interactions with miR-433 (red node).
Mentions: Having identified candidate miR-433 target genes, we next wanted to determine the potential for these genes to impact on cellular senescence. Well-established genes associated with cellular senescence were identified from the literature, yielding a list of approximately 86 genes (Table S3). Next, we constructed an overlap with the 1204 putative miR-433 target genes and identified four overlapping genes including CDK6, MAPK14, E2F3, and CDKN2A (Fig.2A). To further investigate the interaction between potential miR-433 targets and senescence-associated genes, we built an interaction network in Cytoscape using both ClueGo and Cluepedia apps. Only previously experimentally validated PPIs were included in the construction of the network. From this analysis, we identify a significant number of interactions between well-established cellular senescence genes and our list of miR-433 target genes (Fig.2B). By focusing in on the first degree neighbors of the four overlapping genes we identified a number of possible miR-433 targets which regulate the function of key cellular senescence genes such as Rb (Fig.2C). Overall, this indicated the possible role of miR-433 regulating the induction of cellular senescence in our stably transfected cells.

Bottom Line: Mechanistically, we demonstrate that downregulation of p-Rb is attributable to a miR-433-dependent downregulation of CDK6, establishing it as a novel miR-433 associated gene.Interestingly, we show that high miR-433 expressing cells release miR-433 into the growth media via exosomes which in turn can induce a senescence bystander effect.Furthermore, in relation to a chemotherapeutic response, quantitative real-time polymerase chain reaction (qRT-PCR) analysis revealed that only PEO1 and PEO4 OC cells with the highest miR-433 expression survive paclitaxel treatment.

View Article: PubMed Central - PubMed

Affiliation: UCD School of Medicine and Medical Science (SMMS), UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin 4, Ireland.

No MeSH data available.


Related in: MedlinePlus