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Genetic variation of ESR1 and its co-activator PPARGC1B is synergistic in augmenting the risk of estrogen receptor-positive breast cancer

Authors: Li, Yuqing; Li, Yi; Wedrén, Sara; Li, Guoliang; Charn, Tze Howe; Desai, Kartiki Vasant; Bonnard, Carine; +12 Authors

Genetic variation of ESR1 and its co-activator PPARGC1B is synergistic in augmenting the risk of estrogen receptor-positive breast cancer

Abstract

Abstract Introduction Given the role of estrogen in breast carcinogenesis and the modification of estrogen receptor (ER) activity by its biochemical cofactors, we hypothesize that genetic variation within ER cofactor genes alters cellular response to estrogen exposure and consequently modifies the risk for ER-positive breast cancer. Methods We genotyped 790 tagging SNPs within 60 ER cofactor genes in 1,257 cases and 1,464 controls from Sweden and in 2,215 cases and 1,265 controls from Finland, and tested their associations with either ER-positive or ER-negative breast cancer. Results Seven SNPs showed consistent association with ER-positive breast cancer in the two independent samples, and six of them were located within PPARGC1B, encoding an ER co-activator, with the strongest association at rs741581 (odds ratio = 1.41, P = 4.84 × 10-5) that survived Bonferroni correction for multiple testing in the combined ER-positive breast cancer sample (Pcorrected = 0.03). Moreover, we also observed significant synergistic interaction (P interaction = 0.008) between the genetic polymorphisms within PPARGC1B and ESR1 in ER-positive breast cancer. By contrast, no consistent association was observed in ER-negative breast cancer. Furthermore, we found that administration of estrogen in the MCF-7 cell line induced PPARGC1B expression and enhanced occupancies of ER and RNA polymerase II within the region of SNP association, suggesting the upregulation of PPARGC1B expression by ESR1 activation. Conclusions Our study revealed that DNA polymorphisms of PPARGC1B, coding a bona fide ER co-activator, are associated with ER-positive breast cancer risk. The feed-forward transcriptional regulatory loop between PPARGC1B and ESR1 further augments their protein interaction, which provides a plausible mechanistic explanation for the synergistic genetic interaction between PPARGC1B and ESR1 in ER-positive breast cancer. Our study also highlights that biochemically and genomically informed candidate gene studies can enhance the discovery of interactive disease susceptibility genes.

Country
United States
Keywords

570, Genotype, Transcription, Genetic, 610, Breast Neoplasms, Polymorphism, Single Nucleotide, Risk Assessment, Medicine and Health Sciences, Humans, Genetic Predisposition to Disease, Finland, Aged, Medicine(all), Sweden, Estrogen Receptor alpha, Life Sciences, RNA-Binding Proteins, Epistasis, Genetic, Middle Aged, Case-Control Studies, Female, Carrier Proteins, Research Article

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    18
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
18
Top 10%
Top 10%
Top 10%
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gold