Preclinical and clinical studies of estrogen deprivation support the PDGF/Abl pathway as a novel therapeutic target for overcoming endocrine resistance in breast cancer

INTRODUCTION: The majority of breast tumors at primary diagnosis are estrogen receptor positive (ER+). Estrogen (E) mediates its effects by binding to the ER. Therapies targeting the estrogenic stimulation of tumor growth reduce mortality from ER+ breast cancer. However, resistance remains a major clinical problem. METHODS: To identify molecular mechanisms associated with resistance to E-deprivation, we assessed the temporal changes in global gene expression during adaptation to long-term culture of MCF7 human breast cancer cells in the absence of estradiol (E2), long term estrogen deprived (LTED), that leads to recovery of proliferative status and models resistance to an aromatase inhibitor (AI). The expression levels of proteins were determined by western blotting. Proliferation assays were carried out using the dual platelet derived growth factor receptor (PDGFR)/Abelson tyrosine kinase (Abl) inhibitor nilotinib. Luciferase reporter assays were used to determine effects on ER-mediated transactivation. Changes in recruitment of cofactors to the gene regulated by estrogen in breast cancer 1 (GREB1) promoter were determined by chromatin immunoprecipitation (ChIP). Gene expression data were derived from 81 postmenopausal women with ER+ BC pre-treatment and at two-weeks post-treatment with single agent anastrozole in a neoadjuvant trial. RESULTS: The PDGF/Abl canonical pathway was significantly elevated as early as one week post E-deprivation (P = 1.94 E-04) and this became the top adaptive pathway at the point of proliferative recovery (P = 1.15 E-07). Both PDGFRβ and Abl protein levels were elevated in the LTED cells compared to wild type (wt)-MCF7 cells. The PDGF/Abl tyrosine kinase inhibitor nilotinib, suppressed proliferation in LTED cells in the presence or absence of E. Nilotinib also suppressed ER-mediated transcription by destabilizing the ER and reducing recruitment of amplified in breast cancer-1 (AIB1) and the CREB binding protein (CBP) to the promoter of the E-responsive gene GREB1. High PDGFRβ in primary ER+ breast cancer of 81 patients prior to neoadjuvant treatment with an AI was associated with poorer antiproliferative response. Additionally PDGFRβ expression increased after two weeks of AI therapy (1.25 fold, P = 0.003). CONCLUSIONS: These preclinical and clinical data indicate that the PDGF/Abl signaling pathway merits clinical evaluation as a therapeutic target with endocrine therapy in ER+ breast cancer

Integrative analyses identify modulators of response to neoadjuvant aromatase inhibitors in patients with early breast cancer

Introduction Aromatase inhibitors (AIs) are a vital component of estrogen receptor positive (ER+) breast cancer treatment. De novo and acquired resistance, however, is common. The aims of this study were to relate patterns of copy number aberrations to molecular and proliferative response to AIs, to study differences in the patterns of copy number aberrations between breast cancer samples pre- and post-AI neoadjuvant therapy, and to identify putative biomarkers for resistance to neoadjuvant AI therapy using an integrative analysis approach. Methods Samples from 84 patients derived from two neoadjuvant AI therapy trials were subjected to copy number profiling by microarray-based comparative genomic hybridisation (aCGH, n = 84), gene expression profiling (n = 47), matched pre- and post-AI aCGH (n = 19 pairs) and Ki67-based AI-response analysis (n = 39). Results Integrative analysis of these datasets identified a set of nine genes that, when amplified, were associated with a poor response to AIs, and were significantly overexpressed when amplified, including CHKA, LRP5 and SAPS3. Functional validation in vitro, using cell lines with and without amplification of these genes (SUM44, MDA-MB134-VI, T47D and MCF7) and a model of acquired AI-resistance (MCF7-LTED) identified CHKA as a gene that when amplified modulates estrogen receptor (ER)-driven proliferation, ER/estrogen response element (ERE) transactivation, expression of ER-regulated genes and phosphorylation of V-AKT murine thymoma viral oncogene homolog 1 (AKT1). Conclusions These data provide a rationale for investigation of the role of CHKA in further models of de novo and acquired resistance to AIs, and provide proof of concept that integrative genomic analyses can identify biologically relevant modulators of AI response

Identification of chemokine receptors as potential modulators of endocrine resistance in oestrogen receptor–positive breast cancers

Introduction Endocrine therapies target oestrogenic stimulation of breast cancer (BC) growth, but resistance remains problematic. Our aims in this study were (1) to identify genes most strongly associated with resistance to endocrine therapy by intersecting global gene transcription data from patients treated presurgically with the aromatase inhibitor anastrazole with those from MCF7 cells adapted to long-term oestrogen deprivation (LTED) (2) to assess the clinical value of selected genes in public clinical data sets and (3) to determine the impact of targeting these genes with novel agents. Methods Gene expression and Ki67 data were available from 69 postmenopausal women with oestrogen receptor–positive (ER+) early BC, at baseline and 2 weeks after anastrazole treatment, and from cell lines adapted to LTED. The functional consequences of target genes on proliferation, ER-mediated transcription and downstream cell signalling were assessed. Results By intersecting genes predictive of a poor change in Ki67 with those upregulated in LTED cells, we identified 32 genes strongly correlated with poor antiproliferative response that were associated with inflammation and/or immunity. In a panel of LTED cell lines, C-X-C chemokine receptor type 7 (CXCR7) and CXCR4 were upregulated compared to their wild types (wt), and CXCR7, but not CXCR4, was associated with reduced relapse-free survival in patients with ER+ BC. The CXCR4 small interfering RNA variant (siCXCR4) had no specific effect on the proliferation of wt-SUM44, wt-MCF7 and their LTED derivatives. In contrast, siCXCR7, as well as CCX733, a CXCR7 antagonist, specifically suppressed the proliferation of MCF7-LTED cells. siCXCR7 suppressed proteins associated with G1/S transition and inhibited ER transactivation in MCF7-LTED, but not wt-MCF7, by impeding association between ER and proline-, glutamic acid– and leucine-rich protein 1, an ER coactivator. Conclusions These data highlight CXCR7 as a potential therapeutic target warranting clinical investigation in endocrine-resistant BC

Relationship Between Plasma Estradiol Levels and Estrogen-Responsive Gene Expression in Estrogen Receptor–Positive Breast Cancer in Postmenopausal Women

To determine whether plasma estradiol (E2) levels are related to gene expression in estrogen receptor (ER)–positive breast cancers in postmenopausal women

A Gene Expression Signature from Human Breast Cancer Cells with Acquired Hormone Independence Identifies MYC as a Mediator of Antiestrogen Resistance

PURPOSE: Although most patients with estrogen receptor α (ER)-positive breast cancer initially respond to endocrine therapy, many ultimately develop resistance to antiestrogens. However, mechanisms of antiestrogen resistance and biomarkers predictive of such resistance are underdeveloped. EXPERIMENTAL DESIGN: We adapted four ER+ human breast cancer cell lines to grow in an estrogen-depleted medium. A gene signature of estrogen independence was developed by comparing expression profiles of long-term estrogen-deprived (LTED) cells to their parental counterparts. We evaluated the ability of the LTED signature to predict tumor response to neoadjuvant therapy with an aromatase inhibitor, and disease outcome following adjuvant tamoxifen. We utilized Gene Set Analysis (GSA) of LTED cell gene expression profiles and a loss-of-function approach to identify pathways causally associated with resistance to endocrine therapy. RESULTS: The LTED gene expression signature was predictive of high tumor cell proliferation following neoadjuvant therapy with anastrozole and letrozole, each in different patient cohorts. This signature was also predictive of poor recurrence-free survival in two studies of patients treated with adjuvant tamoxifen. Bioinformatic interrogation of expression profiles in LTED cells revealed a signature of MYC activation. The MYC activation signature and high MYC protein levels were both predictive of poor outcome following tamoxifen therapy. Finally, knockdown of MYC inhibited LTED cell growth. CONCLUSIONS: A gene expression signature derived from ER+ breast cancer cells with acquired hormone independence predicted tumor response to aromatase inhibitors and associated with clinical markers of resistance to tamoxifen. In some cases, activation of the MYC pathway was associated with this resistance

ESR1 Is Co-Expressed with Closely Adjacent Uncharacterised Genes Spanning a Breast Cancer Susceptibility Locus at 6q25.1

Approximately 80% of human breast carcinomas present as oestrogen receptor α-positive (ER+ve) disease, and ER status is a critical factor in treatment decision-making. Recently, single nucleotide polymorphisms (SNPs) in the region immediately upstream of the ER gene (ESR1) on 6q25.1 have been associated with breast cancer risk. Our investigation of factors associated with the level of expression of ESR1 in ER+ve tumours has revealed unexpected associations between genes in this region and ESR1 expression that are important to consider in studies of the genetic causes of breast cancer risk. RNA from tumour biopsies taken from 104 postmenopausal women before and after 2 weeks treatment with an aromatase (oestrogen synthase) inhibitor was analyzed on Illumina 48K microarrays. Multiple-testing corrected Spearman correlation revealed that three previously uncharacterized open reading frames (ORFs) located immediately upstream of ESR1, C6ORF96, C6ORF97, and C6ORF211 were highly correlated with ESR1 (Rs = 0.67, 0.64, and 0.55 respectively, FDR<1×10−7). Publicly available datasets confirmed this relationship in other groups of ER+ve tumours. DNA copy number changes did not account for the correlations. The correlations were maintained in cultured cells. An ERα antagonist did not affect the ORFs' expression or their correlation with ESR1, suggesting their transcriptional co-activation is not directly mediated by ERα. siRNA inhibition of C6ORF211 suppressed proliferation in MCF7 cells, and C6ORF211 positively correlated with a proliferation metagene in tumours. In contrast, C6ORF97 expression correlated negatively with the metagene and predicted for improved disease-free survival in a tamoxifen-treated published dataset, independently of ESR1. Our observations suggest that some of the biological effects previously attributed to ER could be mediated and/or modified by these co-expressed genes. The co-expression and function of these genes may be important influences on the recently identified relationship between SNPs in this region and breast cancer risk

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca's large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells

Evolution of composite genomes in bacteria

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