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Marco M Gottardis

Publications and source records attributed to Marco M Gottardis.

2 recordsLinked to original sources

Inhibition of proliferation and estrogen receptor signaling by peroxisome proliferator-activated receptor gamma ligands in uterine leiomyoma.

Peroxisome proliferator-activated receptor (PPAR) gamma is an important signaling molecule in cells of mesenchymal origin, inducing differentiation and regulating cell proliferation in several cell types such as vascular smooth muscle cells. Leiomyomas arise from smooth muscle cells of the uterine myometrium with an incidence rate as high as 70% in women of reproductive age. PPAR signaling has not been characterized in these tumors, although prostaglandins, natural PPAR ligands, are known effectors of key biological functions in the normal myometrium. Leiomyomas and tumor-derived cells isolated from a rat model for this disease were characterized by Western analysis and found to express all three PPAR isoforms, suggesting that signaling pathways mediated by these receptors were intact in this tumor type. In vitro experiments with a leiomyoma-derived cell line demonstrated that the pan-PPAR ligand cis-4,7,10,13,16,19-docosahexaenoic acid and PPARgamma-specific ligands 15-deoxy-delta(12,14)-prostaglandin J(2), troglitazone, and ciglitazone inhibited 17beta-estradiol-stimulated cell proliferation. This inhibitory effect was not observed with PPARalpha- or PPARbeta-specific ligands. Although both PPAR and estrogen receptor (ER) signaling pathways were intact in leiomyoma cells, in addition to growth inhibition, stimulation of PPARgamma signaling also inhibited ER-mediated gene expression. Human leiomyomas were also found to express all three PPAR isoforms, and primary cultures of these cells were sensitive to the inhibitory effects of PPARgamma ligands. These results suggest that in uterine leiomyomas PPARgamma activation is growth inhibitory and that this inhibition is mediated at least in part by negative cross-talk between ER and PPAR signaling pathways.

Animals↗

Quality indicators increase the reliability of microarray data.

Large-scale gene expression profiling with DNA microarrays opens new dimensions to molecular biology but still lacks the overall precision of traditional low-scale techniques. We developed a novel strategy of data processing linking search stringency to quality indicators for efficient detection of low-level, regulated genes. Using retinoid-induced differentiation of NB-4 promyelocytic cells, the variation of expression profiles between biological duplicates was studied and compared with the changes induced by all-trans retinoic acid (atRA) treatment. An analysis of 4320 genes showed that retinoic acid has mainly geneactivating function in NB-4 cells. Treatment with atRA for 18 hours induced metabolic genes that may be associated with cell differentiation and signaling factors triggering later events leading to apoptosis; cytokine genes were among the highest stimulated by atRA. Notably, we identified a regulatory loop inhibiting MYC action: as MYC was downregulated, a cognate repressor of MYC was upregulated.

Cluster Analysis↗