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. 2013 Apr 16;110(16):E1490-9.
doi: 10.1073/pnas.1219992110. Epub 2013 Apr 1.

Genome-wide reprogramming of the chromatin landscape underlies endocrine therapy resistance in breast cancer

Luca Magnani  1 , Alexander Stoeck, Xiaoyang Zhang, András Lánczky, Anne C Mirabella, Tian-Li Wang, Balázs Gyorffy, Mathieu Lupien
Affiliations

Genome-wide reprogramming of the chromatin landscape underlies endocrine therapy resistance in breast cancer

Luca Magnani et al. Proc Natl Acad Sci U S A. .

Abstract

The estrogen receptor (ER)α drives growth in two-thirds of all breast cancers. Several targeted therapies, collectively termed endocrine therapy, impinge on estrogen-induced ERα activation to block tumor growth. However, half of ERα-positive breast cancers are tolerant or acquire resistance to endocrine therapy. We demonstrate that genome-wide reprogramming of the chromatin landscape, defined by epigenomic maps for regulatory elements or transcriptional activation and chromatin openness, underlies resistance to endocrine therapy. This annotation reveals endocrine therapy-response specific regulatory networks where NOTCH pathway is overactivated in resistant breast cancer cells, whereas classical ERα signaling is epigenetically disengaged. Blocking NOTCH signaling abrogates growth of resistant breast cancer cells. Its activation state in primary breast tumors is a prognostic factor of resistance in endocrine treated patients. Overall, our work demonstrates that chromatin landscape reprogramming underlies changes in regulatory networks driving endocrine therapy resistance in breast cancer.

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Conflict of interest statement

Conflict of interest statement: L.M. and M.L. hold a patent on the use of PBX1 and the NOTCH/PBX1-dependent gene signature presented in this paper for prognostic purposes to discriminate endocrine therapy-responsive from nonresponsive ERα-positive breast cancer patients.

Figures

Fig. 1.
Fig. 1.
Distinct transcriptional programs typify ET response. (A) Microarray-based expression profiling in ET-resistant LTED and -responsive MCF7 breast cancer cells reveals distinct transcriptional profiles. (B) MNase–ChIP-seq profiling of H3K36me3 in LTED (blue) and MCF7 (red) cells over a 4-kb window around called peaks (Left). The proportion (%) of H3K36me3 sites mapping to promoters (prom), intragenic (intra), or extragenic (extra) regions are presented for the unique or shared sites between MCF7 and LTED cells (Right). (C) ChIP-seq enrichment for H3K36me3 from either MCF7 (red line) or LTED (blue line) cells across genes specifically expressed in MCF7 (Upper) or LTED (Lower) cells based on the microarray expression profile. (D) Oncomine Concepts Map analysis comparing genes overexpressed in LTED (>twofold ratio vs. MCF7) or in MCF7 (>twofold ratio vs. LTED) cells and expression signatures from high-grade, low-grade, or poor-outcome breast tumors are presented.
Fig. 2.
Fig. 2.
ERα-dependent signaling is reduced in ET-resistant breast cancer cells. (A) MNase–ChIP-seq against H3K4me2 in MCF7 and LTED cells. Results are presented as in Fig. 1B. (B) Genome-wide analysis of open chromatin regions (FAIRE-seq) from MCF7 and LTED are presented as in Fig. 1B. (C) Enrichment of the ERE within epigenetically defined regions (H3K4me2, FAIRE, and H3K36me3) from LTED and MCF7 cells. (D) Expression level based on microarray analysis in LTED (blue) and MCF7 (red) cells of genes discriminating ET response based on ERα-binding profiles in good-outcome (responsive) and poor-outcome (resistant) primary breast tumors. (E) Transcriptional analysis of a selected list of genes discriminating good- and poor-outcome breast tumors (55) in response to ERα silencing in MCF7 or ET-resistant breast cancer cell line models. Expression is presented as mRNA fold change comparing siERα to control (siCTRL). The central circle indicates ERα-silencing efficiency. (F) Growth assays using two different siRNA targeting ERα are represented. Cell number is plotted as a ratio against day 0.
Fig. 3.
Fig. 3.
NOTCH pathway is critical for growth of resistant cells. (A) Enriched pathway analysis using GREAT reveals the significant enrichment of the NOTCH pathway in H3K4me2, FAIRE, or extragenic H3K36me3 regions specific to LTED compared with MCF7 cells. (B) Expression level based on microarray analysis in LTED and MCF7 cells of genes defining the NOTCH pathway [Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway]. (C) Kaplan–Meier analysis for the NOTCH family members against ERα-positive breast tumors. (D) Growth assays using two different siRNA targeting NOTCH3 are represented. Cell number is plotted as a ratio against day 0.
Fig. 4.
Fig. 4.
PBX1 contributes to ETR regulating a unique transcriptional program. (A) Growth assays using two different siRNA targeting PBX1 are represented. Cell number is plotted as a ratio against day 0. (B) Microarray analysis comparing PBX1-dependent expressed genes in MCF7 and LTED cells and the expression levels of the one shared between both cell lines. (C) ChIP-seq for PBX1 around the PBX1-dependent expressed genes shared between MCF7 and LTED cells (±20 kb from transcription start site). Motif search analysis was conducted on the unique and shared PBX1-binding sites. (D) Microarray analysis for the transcription factors recognizing the motifs identified in C. (E) qRT-PCR of PKNOX1 mRNA levels upon siRNA treatment. (F) Growth assays using two different siRNA targeting PKNOX1 are represented. Cell number is plotted as a ratio against day 0.
Fig. 5.
Fig. 5.
GSI MRK003 antagonizes ET-resistant breast cancer cells through down-regulation of PBX1. (A) Growth assays in GSI-treated (MRK003 for HA-LTED and MK0572 for all other cell lines) or control-treated (CTRL) ET-resistant cells. (B) Microarray-based expression-profile analysis in LTED cells treated with the MRK003 GSI (Right) or transfected with siPBX1 (Left) are presented compared with their respective controls. All three replicates are shown. Genes whose expression is affected by both the MRK003 GSI and siPBX1 are presented (Center). (C) Oncomine Concepts Map analysis comparing the list of genes whose expression is down-regulated by both the MRK003 GSI and siPBX1 to expression signatures associated with breast tumors with poor outcome.
Fig. 6.
Fig. 6.
NOTCH-PBX1–driven transcriptional program predicts patient outcomes. (A) Kaplan–Meier analysis for recurrent events using the NOTCH-PBX1 gene signature consisting of PBX1 and the 24 genes whose expression is affected by MRK003 and siPBX1 in LTED cells that are found in at least 10% of all breast cancer poor-outcome expression signatures. Both the 5 and +15 y analysis is presented. (B) Kaplan–Meier analysis for metastatic events for 5 or +15 y analysis is presented as in A. (C) Schematic representation of changes in pathway addiction based on epigenetic reprogramming between ET-responsive and -resistant breast cancer cells.
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