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Distinct gene regulatory programs define the inhibitory effects of liver X receptors and PPARG on cancer cell proliferation.

Savic D, Ramaker RC, Roberts BS, Dean EC, Burwell TC, Meadows SK, Cooper SJ, Garabedian MJ, Gertz J, Myers RM - Genome Med (2016)

Bottom Line: PPARG generated a rapid and short-term response while maintaining a gene activator role.By contrast, LXR signaling was prolonged, with initial, predominantly activating functions that transitioned to repressive gene regulatory activities at late time points.Through the use of a multi-tiered strategy that integrated various genomic datasets, our data illustrate that distinct gene regulatory programs elicit common phenotypic effects, highlighting the complexity of the genome.

View Article: PubMed Central - PubMed

Affiliation: HudsonAlpha Institute for Biotechnology, Huntsville, AL, 35806, USA.

ABSTRACT

Background: The liver X receptors (LXRs, NR1H2 and NR1H3) and peroxisome proliferator-activated receptor gamma (PPARG, NR1C3) nuclear receptor transcription factors (TFs) are master regulators of energy homeostasis. Intriguingly, recent studies suggest that these metabolic regulators also impact tumor cell proliferation. However, a comprehensive temporal molecular characterization of the LXR and PPARG gene regulatory responses in tumor cells is still lacking.

Methods: To better define the underlying molecular processes governing the genetic control of cellular growth in response to extracellular metabolic signals, we performed a comprehensive, genome-wide characterization of the temporal regulatory cascades mediated by LXR and PPARG signaling in HT29 colorectal cancer cells. For this analysis, we applied a multi-tiered approach that incorporated cellular phenotypic assays, gene expression profiles, chromatin state dynamics, and nuclear receptor binding patterns.

Results: Our results illustrate that the activation of both nuclear receptors inhibited cell proliferation and further decreased glutathione levels, consistent with increased cellular oxidative stress. Despite a common metabolic reprogramming, the gene regulatory network programs initiated by these nuclear receptors were widely distinct. PPARG generated a rapid and short-term response while maintaining a gene activator role. By contrast, LXR signaling was prolonged, with initial, predominantly activating functions that transitioned to repressive gene regulatory activities at late time points.

Conclusions: Through the use of a multi-tiered strategy that integrated various genomic datasets, our data illustrate that distinct gene regulatory programs elicit common phenotypic effects, highlighting the complexity of the genome. These results further provide a detailed molecular map of metabolic reprogramming in cancer cells through LXR and PPARG activation. As ligand-inducible TFs, these nuclear receptors can potentially serve as attractive therapeutic targets for the treatment of various cancers.

No MeSH data available.


Related in: MedlinePlus

Genome-wide binding profiles of LXRs and PPARG. a Normalized sequencing read depth rank correlation (top left) at all ChIP-seq binding sites identified across replicate LXRB (light blue), PPARG (gold), and LXRA (dark blue) ChIP-seq experiments after 2 and 48 h of drug treatment. The top panel shows 2-h drug treatment replicate ChIP-seq comparisons while the bottom panel displays 48-h comparisons. b Enriched canonical LXR and PPARG motif identified in corresponding ChIP-seq data. c Venn diagram comparisons of binding events between 2 and 48 h of drug treatment. Overlapping sites are shown in gray, while sites identified at only 2 or 48 h are shown at the left and right, respectively. The number of sites in each category is presented for each category. d The percentage of all LXRB and PPARG sites that were identified at 2 h only (light green), 48 h only (dark green), and common to both time points (common, gray). e Read depth ratios (x-axis) at all LXRB binding sites. Negative values highlight stronger enrichment after 48 h of GW3965 treatment while positive values denote stronger occupancy after 2 h. f Read depth ratios (x-axis) at all PPARG binding sites. Negative values highlight stronger enrichment after 48 h of rosiglitazone treatment while positive values denote stronger read enrichment after 2 h
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Fig3: Genome-wide binding profiles of LXRs and PPARG. a Normalized sequencing read depth rank correlation (top left) at all ChIP-seq binding sites identified across replicate LXRB (light blue), PPARG (gold), and LXRA (dark blue) ChIP-seq experiments after 2 and 48 h of drug treatment. The top panel shows 2-h drug treatment replicate ChIP-seq comparisons while the bottom panel displays 48-h comparisons. b Enriched canonical LXR and PPARG motif identified in corresponding ChIP-seq data. c Venn diagram comparisons of binding events between 2 and 48 h of drug treatment. Overlapping sites are shown in gray, while sites identified at only 2 or 48 h are shown at the left and right, respectively. The number of sites in each category is presented for each category. d The percentage of all LXRB and PPARG sites that were identified at 2 h only (light green), 48 h only (dark green), and common to both time points (common, gray). e Read depth ratios (x-axis) at all LXRB binding sites. Negative values highlight stronger enrichment after 48 h of GW3965 treatment while positive values denote stronger occupancy after 2 h. f Read depth ratios (x-axis) at all PPARG binding sites. Negative values highlight stronger enrichment after 48 h of rosiglitazone treatment while positive values denote stronger read enrichment after 2 h

Mentions: To interrogate LXR and PPARG TF occupancy during our drug treatment regime, we performed replicate ChIP-seq experiments for LXRA (NR1H3), LXRB (NR1H2), and PPARG (NR1C3). We used an early (2-h) and a late (48-h) time point for these experiments to further preserve temporal information. These two datasets spanned the entire temporal molecular characterization and allowed for an examination of the immediate effects of drugs on their direct protein targets. We obtained high-quality antibodies for LXRB and PPARG; however, because we could not identify a suitable commercial ChIP-seq grade antibody for LXRA, we engineered HT29 cells to express a C-terminal Flag-tagged LXRA transgene protein and used a Flag antibody for ChIP-seq experiments. Importantly, normalized sequencing read depth at identified LXRA/B or PPARG binding sites was highly concordant across replicate ChIP-seq experiments for both time points (Fig. 3a). Additionally, for all datasets, the canonical LXR and PPARG motifs were significantly enriched, supporting the notion that our cistromes are identifying true nuclear receptor binding events (Fig. 3b). Collectively, we identified 18,653, 3,900 and 14,360 binding sites at 2 h and 17,576, 9,335 and 8463 binding sites at 48 h for LXRA, LXRB, and PPARG, respectively. Moreover, ~80 % of the endogenous LXRB binding sites were identified by the Flag-tagged LXRA protein at both time points, suggesting substantial redundancy between both LXR proteins.Fig. 3


Distinct gene regulatory programs define the inhibitory effects of liver X receptors and PPARG on cancer cell proliferation.

Savic D, Ramaker RC, Roberts BS, Dean EC, Burwell TC, Meadows SK, Cooper SJ, Garabedian MJ, Gertz J, Myers RM - Genome Med (2016)

Genome-wide binding profiles of LXRs and PPARG. a Normalized sequencing read depth rank correlation (top left) at all ChIP-seq binding sites identified across replicate LXRB (light blue), PPARG (gold), and LXRA (dark blue) ChIP-seq experiments after 2 and 48 h of drug treatment. The top panel shows 2-h drug treatment replicate ChIP-seq comparisons while the bottom panel displays 48-h comparisons. b Enriched canonical LXR and PPARG motif identified in corresponding ChIP-seq data. c Venn diagram comparisons of binding events between 2 and 48 h of drug treatment. Overlapping sites are shown in gray, while sites identified at only 2 or 48 h are shown at the left and right, respectively. The number of sites in each category is presented for each category. d The percentage of all LXRB and PPARG sites that were identified at 2 h only (light green), 48 h only (dark green), and common to both time points (common, gray). e Read depth ratios (x-axis) at all LXRB binding sites. Negative values highlight stronger enrichment after 48 h of GW3965 treatment while positive values denote stronger occupancy after 2 h. f Read depth ratios (x-axis) at all PPARG binding sites. Negative values highlight stronger enrichment after 48 h of rosiglitazone treatment while positive values denote stronger read enrichment after 2 h
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Fig3: Genome-wide binding profiles of LXRs and PPARG. a Normalized sequencing read depth rank correlation (top left) at all ChIP-seq binding sites identified across replicate LXRB (light blue), PPARG (gold), and LXRA (dark blue) ChIP-seq experiments after 2 and 48 h of drug treatment. The top panel shows 2-h drug treatment replicate ChIP-seq comparisons while the bottom panel displays 48-h comparisons. b Enriched canonical LXR and PPARG motif identified in corresponding ChIP-seq data. c Venn diagram comparisons of binding events between 2 and 48 h of drug treatment. Overlapping sites are shown in gray, while sites identified at only 2 or 48 h are shown at the left and right, respectively. The number of sites in each category is presented for each category. d The percentage of all LXRB and PPARG sites that were identified at 2 h only (light green), 48 h only (dark green), and common to both time points (common, gray). e Read depth ratios (x-axis) at all LXRB binding sites. Negative values highlight stronger enrichment after 48 h of GW3965 treatment while positive values denote stronger occupancy after 2 h. f Read depth ratios (x-axis) at all PPARG binding sites. Negative values highlight stronger enrichment after 48 h of rosiglitazone treatment while positive values denote stronger read enrichment after 2 h
Mentions: To interrogate LXR and PPARG TF occupancy during our drug treatment regime, we performed replicate ChIP-seq experiments for LXRA (NR1H3), LXRB (NR1H2), and PPARG (NR1C3). We used an early (2-h) and a late (48-h) time point for these experiments to further preserve temporal information. These two datasets spanned the entire temporal molecular characterization and allowed for an examination of the immediate effects of drugs on their direct protein targets. We obtained high-quality antibodies for LXRB and PPARG; however, because we could not identify a suitable commercial ChIP-seq grade antibody for LXRA, we engineered HT29 cells to express a C-terminal Flag-tagged LXRA transgene protein and used a Flag antibody for ChIP-seq experiments. Importantly, normalized sequencing read depth at identified LXRA/B or PPARG binding sites was highly concordant across replicate ChIP-seq experiments for both time points (Fig. 3a). Additionally, for all datasets, the canonical LXR and PPARG motifs were significantly enriched, supporting the notion that our cistromes are identifying true nuclear receptor binding events (Fig. 3b). Collectively, we identified 18,653, 3,900 and 14,360 binding sites at 2 h and 17,576, 9,335 and 8463 binding sites at 48 h for LXRA, LXRB, and PPARG, respectively. Moreover, ~80 % of the endogenous LXRB binding sites were identified by the Flag-tagged LXRA protein at both time points, suggesting substantial redundancy between both LXR proteins.Fig. 3

Bottom Line: PPARG generated a rapid and short-term response while maintaining a gene activator role.By contrast, LXR signaling was prolonged, with initial, predominantly activating functions that transitioned to repressive gene regulatory activities at late time points.Through the use of a multi-tiered strategy that integrated various genomic datasets, our data illustrate that distinct gene regulatory programs elicit common phenotypic effects, highlighting the complexity of the genome.

View Article: PubMed Central - PubMed

Affiliation: HudsonAlpha Institute for Biotechnology, Huntsville, AL, 35806, USA.

ABSTRACT

Background: The liver X receptors (LXRs, NR1H2 and NR1H3) and peroxisome proliferator-activated receptor gamma (PPARG, NR1C3) nuclear receptor transcription factors (TFs) are master regulators of energy homeostasis. Intriguingly, recent studies suggest that these metabolic regulators also impact tumor cell proliferation. However, a comprehensive temporal molecular characterization of the LXR and PPARG gene regulatory responses in tumor cells is still lacking.

Methods: To better define the underlying molecular processes governing the genetic control of cellular growth in response to extracellular metabolic signals, we performed a comprehensive, genome-wide characterization of the temporal regulatory cascades mediated by LXR and PPARG signaling in HT29 colorectal cancer cells. For this analysis, we applied a multi-tiered approach that incorporated cellular phenotypic assays, gene expression profiles, chromatin state dynamics, and nuclear receptor binding patterns.

Results: Our results illustrate that the activation of both nuclear receptors inhibited cell proliferation and further decreased glutathione levels, consistent with increased cellular oxidative stress. Despite a common metabolic reprogramming, the gene regulatory network programs initiated by these nuclear receptors were widely distinct. PPARG generated a rapid and short-term response while maintaining a gene activator role. By contrast, LXR signaling was prolonged, with initial, predominantly activating functions that transitioned to repressive gene regulatory activities at late time points.

Conclusions: Through the use of a multi-tiered strategy that integrated various genomic datasets, our data illustrate that distinct gene regulatory programs elicit common phenotypic effects, highlighting the complexity of the genome. These results further provide a detailed molecular map of metabolic reprogramming in cancer cells through LXR and PPARG activation. As ligand-inducible TFs, these nuclear receptors can potentially serve as attractive therapeutic targets for the treatment of various cancers.

No MeSH data available.


Related in: MedlinePlus