Dataset Information

Modeling the ESR1 tyrosine 537 mutation with CRISPR-Cas9 for mechanistic studies and evaluation of therapeutic approaches for metastatic breast cancer [ChIP-Seq]

ABSTRACT: Estrogen receptor-α (ERα) is an important driver of breast cancer and is the target for hormonal therapies, anti-estrogens and drugs that limit estrogen biosynthesis (aromatase inhibitors). Mutations in the ESR1 gene identified in metastatic breast cancer provide a potential mechanism for acquired resistance to hormone therapies. We have used CRISPR-Cas9 mediated genome editing in the MCF-7 breast cancer cell line, generating MCF-7-Y537S. MCF-7-Y537S cells encode a wild-type (tyrosine 537) and a mutant (serine 537) allele. Growth of the line is estrogen-independent and expression of ERα target genes is elevated in the absence of estrogen. ER ChIP-seq was carried out to map global ERα binding sites in the presence and absence of estrogen. RNA-seq following estrogen treatment was used for gene expression analysis. We show that expression of ER target genes and ER recruitment to ER binding regions is similar in MCF-7 and MCF-7-Y537S cells, except that ER recruitment to DNA and expression of ER target genes is frequently elevated in the absence of estrogen

ORGANISM(S): Homo sapiens

PROVIDER: GSE78284 | GEO | 2016/10/25

SECONDARY ACCESSION(S): PRJNA313092

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Abstract Several endocrine therapy (ET) resistance mechanisms for ER-positive (ER+) breast cancer (BC) have been proposed, including acquired ESR1 (ERα gene) mutations. The two most common ESR1 mutations are Y537S and D538G, which give rise to a constitutively active receptor with reduced affinity for agonists and antagonists. The discovery of new effective therapies remains a significant challenge in treating mutated ER+ BC. In this context, Poly (ADP-ribose) polymerase-1 (PARP-1) has captured considerable interest as a target for therapeutic inhibitors in specific types of cancers. Here, we report that crosstalk between PARP-1 and ERα may represent a novel therapeutic approach for ER+ BC. We have demonstrated that the up-regulation of PARP-1 expression, stimulated by 17-β estradiol (E2), was blocked by treatment with fulvestrant (Ful), a potent ERα antagonist, or ESR1 siRNA in ER+ MCF7 and T47D BC cell models that express both wild type ERα and the Y537S mutation, indicating that ERα regulates the expression of PARP-1. In addition, ERα-mediated transcriptional activity depended on PARP-1 activity in these models, as confirmed by ERα target gene expression and ERE reporter gene analyses +/- niraparib (Nira). Notably, PARP-1 modulates the estrogen-dependent genomic binding of ERα and FoxA1, which play a crucial role in the proliferation of ER+ BC. We also showed that PARP-1 inhibition prevented proliferation and cell cycle activities of ERα WT and ERα Y537S cells upon ERα activation. In vivo, Nira and lasofoxifene (Laso), an ERα antagonist, significantly reduced primary tumor growth versus vehicle, both as single agents and in combination. Moreover, RNA-seq analyses demonstrated the downregulation of ERα signaling in the mammary glands of mice treated with Nira versus Vehicle. Our results provide novel insights into the molecular events through which PARP-1 may serve as a more comprehensive therapeutic approach to target ET BC resistance in women with advanced ER+ BC.

Project description:Background: The constitutively active ESR1 Y537S mutation is associated with endocrine therapy resistance and progression of metastatic breast cancer through its effects on estrogen receptor (ERα) gene regulatory functions. However, the complex relationship between ERα and the progesterone receptor (PR), known as ERα/PR crosstalk, has yet to be characterized in the context of the ERα Y537S mutation. This study aimed to elucidate the effects of the ERα Y537S mutation on ERα/PR crosstalk and resultant transcriptional activity and to identify potential therapeutic sensitivities that may offer novel treatment options to patients with endocrine therapy-resistant breast cancer. Methods: Proximity-based interactions of ERα and PR were assessed via proximity ligation assay (PLA). Gene expression in MCF7 and T47D cells was assessed by RNA-seq analysis with comparison to publicly available patient tumor transcriptome data. Chromatin immunoprecipitation (ChIP)-qPCR and immunoblotting were used to assess ERα/PR-associated gene expression and protein expression, respectively. Data were analyzed by ordinary two-way ANOVA (α = 0.05) with Tukey’s multiple comparisons tests. Results: Physical interaction of ERα and PR was increased in the context of the ERα Y537S mutation, including in the nucleus where this interaction may translate to altered gene expression. As such, more than 30 genes were differentially expressed in both patient tumor and cell line data (MCF7 and/or T47D cells) in the context of the ERα Y537S mutation compared to ERα WT. Of these, IRS1 stood out as a gene of interest, and ERα and PR occupancy at chromatin binding sites along IRS1 were uniquely altered in the context of ERα Y537S. Furthermore, siRNA knockdown of IRS1 or treatment with the IRS1 inhibitor NT-157 indicated a significant anti-proliferative effect of IRS1 depletion or inhibition in ERα Y537S cell lines. Conclusions: Previous research has characterized gene regulatory changes associated with the ERα Y537S mutation from the viewpoint of ERα. Here, we identify consequential changes to both ERα and PR transcription factor activity, including at chromatin binding sites for the signaling adaptor protein IRS1. We identified a significant dependence of ERα Y537S-expressing cells on IRS1 for proliferation, implicating IRS1 as a potential therapeutic target for restoring treatment sensitivity to patients with breast cancers harboring ERα Y537S mutations.

Dataset Information

Modeling the ESR1 tyrosine 537 mutation with CRISPR-Cas9 for mechanistic studies and evaluation of therapeutic approaches for metastatic breast cancer [ChIP-Seq]

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets