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Reconstruction of nuclear receptor network reveals that NR2E3 is a novel upstream regulator of ESR1 in breast cancer.

Park YY, Kim K, Kim SB, Hennessy BT, Kim SM, Park ES, Lim JY, Li J, Lu Y, Gonzalez-Angulo AM, Jeong W, Mills GB, Safe S, Lee JS - EMBO Mol Med (2011)

Bottom Line: By applying systems-level re-analysis of publicly available gene expression data, we uncovered a potential regulator of ESR1.Moreover, expression of NR2E3 was significantly associated with recurrence-free survival and a favourable response to tamoxifen treatment in women with ER-positive breast cancer.Our results provide mechanistic insights on the regulation of ESR1 by NR2E3 and the clinical relevance of NR2E3 in breast cancer.

View Article: PubMed Central - PubMed

Affiliation: Department of Systems Biology, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.

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NR2E3-specific gene expression signaturesGene expression signature specific to loss of NR2E3 or ESR1 expression by shRNA or siRNA in MCF-7 cells. Genes in the Venn diagram were selected by applying a two-sample Student's t-test (p < 0.005). The green and blue circles represent genes whose expression patterns are significantly associated with loss of NR2E3 or ESR1, respectively.Overall scheme of generation of prediction models and evaluation of predicted outcome based on shared gene expression signature of NR2E3 and ESR1 in MCF-7. A shared gene expression signature was used to form a series of classifiers that estimated the probability of how much the expression pattern of a particular patient with breast cancer was similar to the shared signature; control (Con.) vs. knock down (KD).Kaplan–Meier plots of RFS of breast cancer patients in the NKI cohort were predicted by using the ESR1-independent NR2E3 gene expression signature as a classifier. The differences between groups were significant as indicated (log-rank test). CCP, compound covariate predictor; 1NN, one nearest neighbor; 3NN, three nearest neighbors; NC, nearest centroid; SVM, support vector machines; and LDA, linear discriminator analysis.
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fig08: NR2E3-specific gene expression signaturesGene expression signature specific to loss of NR2E3 or ESR1 expression by shRNA or siRNA in MCF-7 cells. Genes in the Venn diagram were selected by applying a two-sample Student's t-test (p < 0.005). The green and blue circles represent genes whose expression patterns are significantly associated with loss of NR2E3 or ESR1, respectively.Overall scheme of generation of prediction models and evaluation of predicted outcome based on shared gene expression signature of NR2E3 and ESR1 in MCF-7. A shared gene expression signature was used to form a series of classifiers that estimated the probability of how much the expression pattern of a particular patient with breast cancer was similar to the shared signature; control (Con.) vs. knock down (KD).Kaplan–Meier plots of RFS of breast cancer patients in the NKI cohort were predicted by using the ESR1-independent NR2E3 gene expression signature as a classifier. The differences between groups were significant as indicated (log-rank test). CCP, compound covariate predictor; 1NN, one nearest neighbor; 3NN, three nearest neighbors; NC, nearest centroid; SVM, support vector machines; and LDA, linear discriminator analysis.

Mentions: We next examined gene networks shared between NR2E3 and ESR1 by comparing gene expression signatures specific to silencing expression of each gene in MCF-7 cells. The Venn diagram (Fig 8A) shows that a substantial number of gene features were identified as downstream targets of both NR2E3 and ESR1, suggesting that a significant part of NR2E3-mediated biological activity is dependent on ESR1. We next tested the clinical relevance of the shared signature by applying a previously established prediction strategy that employs multiple different algorithms (Fig 8B and Method 1 of Supporting Information; Lee et al, 2004, 2006). As expected, the shared gene expression signature was significantly associated with disease recurrence in breast cancer patients (Figs S8 and S9 of Supporting Information) when judged by predicted outcomes of various classifiers. Of interest, the NR2E3-specific gene expression signature (1847 gene features; Gene list on Table 1 of Supporting Information) that was independent of ESR1 was also significantly associated with disease recurrence (Fig 8C), suggesting that NR2E3 activity, that is independent of ESR1 might have important functional roles and prognostic significance in breast cancer. Gene network analysis revealed several interesting features that may contribute to prognostic features of NR2E3 in breast cancer (Fig S10 of Supporting Information).


Reconstruction of nuclear receptor network reveals that NR2E3 is a novel upstream regulator of ESR1 in breast cancer.

Park YY, Kim K, Kim SB, Hennessy BT, Kim SM, Park ES, Lim JY, Li J, Lu Y, Gonzalez-Angulo AM, Jeong W, Mills GB, Safe S, Lee JS - EMBO Mol Med (2011)

NR2E3-specific gene expression signaturesGene expression signature specific to loss of NR2E3 or ESR1 expression by shRNA or siRNA in MCF-7 cells. Genes in the Venn diagram were selected by applying a two-sample Student's t-test (p < 0.005). The green and blue circles represent genes whose expression patterns are significantly associated with loss of NR2E3 or ESR1, respectively.Overall scheme of generation of prediction models and evaluation of predicted outcome based on shared gene expression signature of NR2E3 and ESR1 in MCF-7. A shared gene expression signature was used to form a series of classifiers that estimated the probability of how much the expression pattern of a particular patient with breast cancer was similar to the shared signature; control (Con.) vs. knock down (KD).Kaplan–Meier plots of RFS of breast cancer patients in the NKI cohort were predicted by using the ESR1-independent NR2E3 gene expression signature as a classifier. The differences between groups were significant as indicated (log-rank test). CCP, compound covariate predictor; 1NN, one nearest neighbor; 3NN, three nearest neighbors; NC, nearest centroid; SVM, support vector machines; and LDA, linear discriminator analysis.
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Related In: Results  -  Collection

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fig08: NR2E3-specific gene expression signaturesGene expression signature specific to loss of NR2E3 or ESR1 expression by shRNA or siRNA in MCF-7 cells. Genes in the Venn diagram were selected by applying a two-sample Student's t-test (p < 0.005). The green and blue circles represent genes whose expression patterns are significantly associated with loss of NR2E3 or ESR1, respectively.Overall scheme of generation of prediction models and evaluation of predicted outcome based on shared gene expression signature of NR2E3 and ESR1 in MCF-7. A shared gene expression signature was used to form a series of classifiers that estimated the probability of how much the expression pattern of a particular patient with breast cancer was similar to the shared signature; control (Con.) vs. knock down (KD).Kaplan–Meier plots of RFS of breast cancer patients in the NKI cohort were predicted by using the ESR1-independent NR2E3 gene expression signature as a classifier. The differences between groups were significant as indicated (log-rank test). CCP, compound covariate predictor; 1NN, one nearest neighbor; 3NN, three nearest neighbors; NC, nearest centroid; SVM, support vector machines; and LDA, linear discriminator analysis.
Mentions: We next examined gene networks shared between NR2E3 and ESR1 by comparing gene expression signatures specific to silencing expression of each gene in MCF-7 cells. The Venn diagram (Fig 8A) shows that a substantial number of gene features were identified as downstream targets of both NR2E3 and ESR1, suggesting that a significant part of NR2E3-mediated biological activity is dependent on ESR1. We next tested the clinical relevance of the shared signature by applying a previously established prediction strategy that employs multiple different algorithms (Fig 8B and Method 1 of Supporting Information; Lee et al, 2004, 2006). As expected, the shared gene expression signature was significantly associated with disease recurrence in breast cancer patients (Figs S8 and S9 of Supporting Information) when judged by predicted outcomes of various classifiers. Of interest, the NR2E3-specific gene expression signature (1847 gene features; Gene list on Table 1 of Supporting Information) that was independent of ESR1 was also significantly associated with disease recurrence (Fig 8C), suggesting that NR2E3 activity, that is independent of ESR1 might have important functional roles and prognostic significance in breast cancer. Gene network analysis revealed several interesting features that may contribute to prognostic features of NR2E3 in breast cancer (Fig S10 of Supporting Information).

Bottom Line: By applying systems-level re-analysis of publicly available gene expression data, we uncovered a potential regulator of ESR1.Moreover, expression of NR2E3 was significantly associated with recurrence-free survival and a favourable response to tamoxifen treatment in women with ER-positive breast cancer.Our results provide mechanistic insights on the regulation of ESR1 by NR2E3 and the clinical relevance of NR2E3 in breast cancer.

View Article: PubMed Central - PubMed

Affiliation: Department of Systems Biology, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.

Show MeSH
Related in: MedlinePlus