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Background Oestrogen receptor-positive (ER+) breast cancer is commonly treated using endocrine therapies such as aromatase inhibitors which block synthesis of oestradiol, but the influence of this therapy on the immune composition of breast tumours has not been fully explored. Previous findings suggest that tumour infiltrating lymphocytes and immune-related gene expression may be altered by treatment with aromatase inhibitors. However, whether these changes are a direct result of impacts on the host immune system or mediated through tumour cells is not known. We aimed to investigate the effect of oestrogen deprivation on the expression of chemokines and immune infiltration in vitro and in an ER+ immunocompetent mouse model. Methods RT-qPCR and a bead-based Bioplex system were used to investigate the expression of chemokines in MCF-7 breast cancer cells deprived of oestrogen. A migration assay and flow cytometry were used to measure the migration of human peripheral blood mononuclear cells (PBMCs) to MCF-7 cells grown without the main biologically active oestrogen, oestradiol. Using flow cytometry and immunohistochemistry, we examined the immune cell infiltrate into tumours created by injecting SSM3 ER+ breast cancer cells into wild-type, immunocompetent 129/SvEv mice. Results This study demonstrates that oestrogen deprivation increases breast cancer secretion of TNF, CCL5, IL-6, IL-8, and CCL22 and alters total human peripheral blood mononuclear cell migration in an in vitro assay. Oestrogen deprivation of breast cancer cells increases migration of CD4+ T cells and decreases migration of CD11c+ and CD14+ PBMC towards cancer cells. PBMC migration towards breast cancer cells can be reduced by treatment with the non-steroidal anti-inflammatory drugs, aspirin and celecoxib. Treatment with endocrine therapy using the aromatase inhibitor letrozole increases CD4+ T cell infiltration into ER+ breast cancer tumours in immune competent mice. Conclusions These results suggest that anti-oestrogen treatment of ER+ breast cancer cells can alter cytokine production and immune cells in the area surrounding the cancer cells. These findings may have implications for the combination and timing of anti-oestrogen therapies with other therapies.

Background: Aromatase inhibitors (AIs) have an established role in the treatment of estrogen receptor alpha positive post-menopausal breast cancer. Recently we have developed and validated a microarray-derived 4-gene test (Edinburgh EndoResponse4) to predict response to AIs in the neoadjuvant setting. We have also demonstrated the translational potential of this test in predicting accurately clinical response when mRNA is measured for these genes by polymerase chain reaction (PCR) or the gene protein is measured by immunohistochemistry (IHC). There is a major clinical need for biomarkers to predict which patients are likely to recur on adjuvant endocrine therapy so alternative or additional treatments can be provided to reduce recurrence and improve outcome. The aim of this study was to determine if Endoresponse4 and IHC of these gene proteins could do this. Methods: The original microarray assay used pre- and on-treatment (14-days) biopsies from 73 post-menopausal women with ER-rich breast cancer receiving 3 months of neoadjuvant letrozole prior to surgery with 10 years follow-up after adjuvant letrozole. Matched formalin-fixed paraffin embedded (FFPE) tissue sections from 42 of these patients were used for IHC and antibodies were optimised against 3 of the 4 proteins (where validated antibodies were available) using Envision technology. The ability of our test to estimate recurrence-free (RFS) and breast cancer specific overall survival (OS) using both PCR and IHC was then tested in a unique validation cohort of 140 post-menopausal women with ER-rich breast cancer treated with 2 weeks of neoadjuvant letrozole or anastrozole prior to surgery followed by adjuvant endocrine therapy and 10 years of follow up.. Results: Within our training cohort (n=73) using Kaplan-Meier analysis our 4-gene test predicted neoadjuvant clinical response and demonstrated a significant association with both RFS (P=0.029) and OS (P=0.009). This approach predicts outcomes within 2-weeks rather than 4-months of treatment required in other studies such as P024. Using IHC in the training cohort (n=42), two gene markers in combination (IL6ST at diagnosis and MCM4 after 2-weeks treatment) predicted both RFS (P=0.017) and OS (P=0.009) with great accuracy. The 140 patient group is being analysed and the findings are so far are consistent with the initial training cohort and indicate a significant association with outcomes. Conclusion: • A 4 gene model with clinical potential has been developed and validated to predict response to neoadjuvant aromatase inhibitors. • This 4 gene model predicts for response and also predicts relapse free and overall survival. • Proteins encoded by 2 of these 4 genes measured by IHC in an initial test set of 42 patients predict accurately both EFS and OS • A validation cohort (n=140) with over 10-years of follow-up will be available at SABCS 2015 to determine if this 2 biomarker test can predict outcome on adjuvant endocrine therapy. Citation Format: Turnbull AK, Arthur LM, Webber V, Thomas J, Uddin S, Webb H, Dunbier A, Dowsett M, Renshaw L, Sims AH, Dixon JM. A validated test for neoadjuvant clinical response to endocrine therapy in breast cancer that estimates accurately recurrence-free and overall survival. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P3-07-20.

The Tribbles family of pseudokinases recruits substrates to the ubiquitin ligase COP1 to facilitate ubiquitylation. CCAAT/enhancer-binding protein (C/EBP) family transcription factors are crucial Tribbles substrates in adipocyte and myeloid cell development. We found that the TRIB1 pseudokinase was able to recruit various C/EBP family members and that the binding of C/EBPβ was attenuated by phosphorylation. To explain the mechanism of C/EBP recruitment, we solved the crystal structure of TRIB1 in complex with C/EBPα, which revealed that TRIB1 underwent a substantial conformational change relative to its substrate-free structure and bound C/EBPα in a pseudosubstrate-like manner. Crystallographic analysis and molecular dynamics and subsequent biochemical assays showed that C/EBP binding triggered allosteric changes that link substrate recruitment to COP1 binding. These findings offer a view of pseudokinase regulation with striking parallels to bona fide kinase regulation—by means of the activation loop and αC helix—and raise the possibility of small molecules targeting either the activation “loop-in” or “loop-out” conformations of Tribbles pseudokinases.

One Sentence SummarySubstrate binding to Tribbles-homolog 1 (TRIB1) pseudokinase induces allosteric changes that allow formation of a complex with the COP1 ubiquitin ligase.AbstractThe Tribbles family of pseudokinases recruit substrates to the COP1 ubiquitin ligase for ubiquitination. CCAAT-enhancer binding protein (C/EBP) family transcription factors are crucial Tribbles substrates in adipocyte and myeloid development. Here we show that the TRIB1 pseudokinase can recruit various C/EBP family members, with binding of C/EBPβ attenuated by phosphorylation. To explain the mechanism of substrate recruitment, we solved the crystal structure of TRIB1 in complex with C/EBPα. TRIB1 undergoes a significant conformational change relative to its substrate-free structure, to bind C/EBPα in a pseudo-substrate-like manner. Crucially, substrate binding triggers allosteric changes that link substrate recruitment to COP1 binding, which is consistent with molecular dynamics and biochemical studies. These findings offer a view of pseudokinase regulation with striking parallels to bona fide kinase regulation— via the activation loop and αC-helix—and raise the possibility of small molecules targeting either the activation loop-in, or loop-out, conformations of Tribbles pseudokinases.

Purpose Aromatase inhibitors (AIs) have an established role in the treatment of breast cancer. Response rates are only 50% to 70% in the neoadjuvant setting and lower in advanced disease. Accurate biomarkers are urgently needed to predict response in these settings and to determine which individuals will benefit from adjuvant AI therapy. Patients and Methods Pretreatment and on-treatment (after 2 weeks and 3 months) biopsies were obtained from 89 postmenopausal women who had estrogen receptor–alpha positive breast cancer and were receiving neoadjuvant letrozole for transcript profiling. Dynamic clinical response was assessed with use of three-dimensional ultrasound measurements. Results The molecular response to letrozole was characterized and a four-gene classifier of clinical response was established (accuracy of 96%) on the basis of the level of two genes before treatment (one gene [IL6ST] was associated with immune signaling, and the other [NGFRAP1] was associated with apoptosis) and the level of two proliferation genes (ASPM, MCM4) after 2 weeks of therapy. The four-gene signature was found to be 91% accurate in a blinded, completely independent validation data set of patients treated with anastrozole. Matched 2-week on-treatment biopsies were associated with improved predictive power as compared with pretreatment biopsies alone. This signature also significantly predicted recurrence-free survival (P = .029) and breast cancer –specific survival (P = .009). We demonstrate that the test can also be performed with use of quantitative polymerase chain reaction or immunohistochemistry. Conclusion A four-gene predictive model of clinical response to AIs by 2 weeks has been generated and validated. Deregulated immune and apoptotic responses before treatment and cell proliferation that is not reduced 2 weeks after initiation of treatment are functional characteristics of breast tumors that do not respond to AIs.

Purpose: To investigate potential associations between gene modules representing key biologic processes and response to aromatase inhibitors (AI) in estrogen receptor–positive (ER+) breast cancer. Patients and Methods: Paired gene expression and Ki67 protein expression were available from 69 postmenopausal women with ER+ early breast cancer, at baseline and 2 weeks post-anastrozole treatment, in the presurgical setting. Functional gene modules (n = 26) were retrieved from published studies and their module scores were computed before and after elimination of proliferation-associated genes (PAG). Ki67 and module scores were assessed at baseline and 2 weeks post-anastrozole. Unsupervised clustering was used to assess associations between modules and Ki67. Results: Proliferation-based modules were highly correlated with Ki67 expression both pretreatment and on-treatment. At baseline with and without PAGs, Ki67 expression was significantly inversely correlated with ERG, ESR1.2, SET, and PIK3CA modules. Modules measuring estrogen signaling strongly predicted antiproliferative response to therapy with and without PAGs. Baseline expression of insulin-like growth factor-1 (IGF-I) module predicted a poor change in Ki67-implicating genes within the module as involved in de novo resistance to AIs. High expression of Immune.2.STAT1 module pretreatment predicted poor antiproliferative response to therapy. A significant association between estrogen-regulated genes modules (ESR1, ESR1-2, SET, and ERG) was evident post AI. Conclusions: Multiple processes and pathways are affected by AI treatment in ER+ breast cancer. Modules closely associated with ESR1 expression were predictive of good antiproliferative response to AIs, but modules representing immune activity and IGF-I/MAPK were predictive of poor Ki67 response, supporting their therapeutic targeting in combination with AIs. Clin Cancer Res; 20(9); 2485–94. ©2014 AACR.

Background: Aromatase inhibitors (AIs) have an established role in the treatment of estrogen receptor alpha positive post-menopausal breast cancer. Response rates are only 50-70% even in patients with ER-rich cancers in the neoadjuvant setting and are lower in advanced disease. Recently we developed and validated a microarray-derived 4-gene test to predict response to AIs in the neoadjuvant setting. Whole-genome expression analysis is impractical for clinical utility. There is a need to translate and validate any test utilising clinically accessible and reproducible material and technologies such as polymerase chain reaction (PCR) and immunohistochemistry (IHC). Methods: The original microarray experiment used pre- and on-treatment (at 14 days and 3-months) biopsies from 89 post-menopausal women with ER-rich breast cancer receiving 3 months of neoadjuvant letrozole. Dynamic response was based on periodic 3D ultrasound measurements performed during treatment. The derived 4-gene model was independently validated in a cohort of 44 post-menopausal women with ER-rich breast cancer treated with neoadjuvant anastrozole [table 1]. RNA was extracted from the original biopsies for RT-qPCR analysis using validated primers for the 4 genes with SYBR-green technology normalised to the geometric mean of 3 housekeeping genes. Matched formalin-fixed paraffin embedded (FFPE) tissue sections were used for IHC with optimised antibodies against 3 of the 4 proteins (where validated antibodies were available) using Envision technology. Results: PCR: Microarray and PCR expression levels for each of the four genes were well correlated (Pearson r=0.87-0.65, p Conclusion: Table 1NAccuracySensitivitySpecificityPPVNPVMicroarray (Training)890.960.890.980.980.96Microarray (Validation)440.910.800.970.920.90PCR260.960.951.001.000.86IHC280.890.861.001.000.89Sensitivity and specificity of model in training (microarray, PCR, IHC) and validation datasets (microarray). PPV/NPV = postivie/negative predictive value. •A 4 gene model has been developed and validated to predict response to neoadjuvant aromatase inhibitors. •This model has been shown to work with a high degree of accuracy using both PCR and IHC technologies. Further independent validation is currently underway. •This new test has the potential to predict accurately the benefit of endocrine therapy and has huge potential clinical value. Citation Format: Arran K Turnbull, Laura Arthur, Victoria Webber, Jeremy Thomas, Charlotte Heerlyn, Phoebe Thornton, Anita Dunbier, Mitch Dowsett, Lorna Renshaw, Andrew H Sims, J Michael Dixon. Development for clinical utility of a validated predictive test of clinical response to aromatase inhibitors [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-05-01.

Purpose: Estrogen withdrawal by treatment with aromatase inhibitors is the most effective form of endocrine therapy for postmenopausal estrogen receptor–positive (ER+) breast cancer. However, response to therapy varies markedly and understanding of the precise molecular effects of aromatase inhibitors and causes of resistance is limited. We aimed to identify in clinical breast cancer those genes and pathways most associated with resistance to aromatase inhibitors by examining the global transcriptional effects of AI treatment. Experimental Design: Baseline and 2-week posttreatment biopsies were obtained from 112 postmenopausal women with ER+ breast cancer receiving neoadjuvant anastrozole. Gene expression data were obtained from 81 baseline and 2-week paired samples. Pathway analysis identified (i) the most prevalent changes in expression and (ii) the pretreatment genes/pathways most related to poor antiproliferative response. Results: A total of 1,327 genes were differentially expressed after 2-week treatment (false discovery rate < 0.01). Proliferation-associated genes and classical estrogen-dependent genes were strongly downregulated whereas collagens and chemokines were upregulated. Pretreatment expression of an inflammatory signature correlated with antiproliferative response to anastrozole and this observation was validated in an independent study. Higher expression of immune-related genes such as SLAMF8 and TNF as well as lymphocytic infiltration were associated with poorer response (P < 0.001) and validated in an independent cohort. Conclusions: The molecular response to aromatase inhibitor treatment varies greatly between patients consistent with the variable clinical benefit from aromatase inhibitor treatment. Higher baseline expression of an inflammatory signature is associated with poor antiproliferative response and should be assessed further as a novel biomarker and potential target for aromatase inhibitor-treated patients. Clin Cancer Res; 19(10); 2775–86. ©2013 AACR.

Most estrogen receptor α (ER)-positive breast cancers initially respond to antiestrogens, but many eventually become estrogen-independent and recur. We identified an estrogen-independent role for ER and the CDK4/Rb/E2F transcriptional axis in the hormone-independent growth of breast cancer cells. ER downregulation with fulvestrant or small interfering RNA (siRNA) inhibited estrogen-independent growth. Chromatin immunoprecipitation identified ER genomic binding activity in estrogen-deprived cells and primary breast tumors treated with aromatase inhibitors. Gene expression profiling revealed an estrogen-independent, ER/E2F-directed transcriptional program. An E2F activation gene signature correlated with a lesser response to aromatase inhibitors in patients' tumors. siRNA screening showed that CDK4, an activator of E2F, is required for estrogen-independent cell growth. Long-term estrogen-deprived cells hyperactivate phosphatidylinositol 3-kinase (PI3K) independently of ER/E2F. Fulvestrant combined with the pan-PI3K inhibitor BKM120 induced regression of ER+ xenografts. These data support further development of ER downregulators and CDK4 inhibitors, and their combination with PI3K inhibitors for treatment of antiestrogen-resistant breast cancers. Significance: ERα retains genomic activity and drives a CDK4/E2F-dependent transcriptional program despite estrogen deprivation therapy. Combined inhibition of ER and PI3K induced regression of ER+ xenografts, supporting further development of strong ER downregulators and CDK4 inhibitors, and their combination with PI3K inhibitors for the treatment of antiestrogen-resistant breast cancers. Cancer Discovery; 1(4); 338–51. ©2011 AACR. Read the Commentary on this article by Van Tine et al., p. 287 This article is highlighted in the In This Issue feature, p. 275

Aromatase inhibitors (AI) have improved the treatment of oestrogen receptor positive (ER+) breast cancer. Despite the efficacy of these agents over 40% of patients relapse with endocrine resistant disease. Here we describe an in vitro model of acquired resistance to long-term oestrogen deprivation (LTED). The LTED cells retain expression of the ER and appear hypersensitive to oestrogen as a result of altered kinase activity. Furthermore analysis of temporal changes in gene expression during the acquisition of resistance highlight growth factor receptor pathways as key mediators of this adaptive process.

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. Activation of the MYC pathway was associated with this resistance. Clin Cancer Res; 17(7); 2024–34. ©2011 AACR.

Purpose: The majority of breast cancer patients who have estrogen receptor positive (ER+) tumors whose proliferation is reduced after estrogen deprivation by aromatase inhibitors (AI). This study investigates any link between proliferation and hypoxia, a major determinant of tumor biology, and defines the effect of estrogen deprivation on hypoxia-associated genes. Methods: Genome-wide expression profiles were obtained from tumor biopsies from 81 ER+ postmenopausal patients, before and after 2 weeks' anastrozole treatment. A hypoxia metagene was developed by identifying genes clustered with classical hypoxia-regulated genes, excluding those associated with proliferation. Proliferation was measured by Ki67 and a proliferation metagene derived from two published breast cancer data sets. Results: Hypoxia and proliferation metagenes were associated at baseline (Pearson correlation coefficient, r = 0.67, P < 10−4) and after 2 weeks (r = 0.71, P < 10−4). Hypoxia metagene at baseline was associated with 2-week Ki67 (r = 0.43, P = 0.0002) and more weakly with poor 2-week Ki67 change consistent with a weak association with AI resistance. Hypoxia metagene was significantly downregulated with AI. This downregulation was significantly associated with change in the proliferation metagene and with Ki67 but, importantly, not with the substantial change in expression of classical estrogen-dependent genes. Conclusions: Hypoxia metagene is closely associated with proliferation before and after AI treatment. The downregulation of hypoxia metagene after AI therapy is most likely the result of changes in proliferation. There may be a weak effect of hypoxia metagene on de novo resistance to AIs. These findings are important to consider in coapplication of antiproliferative agents with antiangiogenic or antihypoxia agents. Clin Cancer Res; 17(9); 3005–12. ©2011 AACR.

Aim: To identify molecular mechanisms and predictors of response to aromatase inhibitors (AIs) in primary ER+ breast cancer. Background: Although AIs are highly effective suppressants of estrogen synthesis in postmenopausal women, up to 50% of patients derive little or no clinical benefit from AI treatment. The proliferation marker Ki67 provides a valuable pharmacodynamic marker for response in the presurgical setting and 2 week measurements of this marker have been shown to predict recurrence-free survival1. However, understanding of the precise molecular effects of AIs and causes of resistance is limited. We present, to our knowledge, the largest study of the transcriptional effects of AI treatment in the neoadjuvant setting. Methods: Baseline and 2wk post-treatment core-cut tumor biopsies were obtained from 112 postmenopausal women with stage I to IIIB ER+ early breast cancer who received single agent neoadjuvant anastrozole2. RNA extracted from biopsies was analysed on Illumina 48K microarrays. Genes which changed expression upon anastrozole treatment were identified using paired class comparison of the 81 matched baseline and 2wk pairs from which gene expression data was available. Correlates of response were determined using multiple testing corrected Spearman correlation analysis. Pathway analysis was performed on the ranked list of correlated genes. IHC for Ki67, ER and PgR was performed centrally on FFPE sections from duplicate core biopsies. Results: At a false discovery rate (FDR) of 0.01, 1154 genes were differentially expressed (792 down-regulated and 362 up-regulated). Proliferation-associated genes and classical estrogen-dependent genes such as TOP2A, CCNB2, TFF1, and PDZK1 were strongly downregulated (FDR 1. Dowsett et al., JNCI, 2007, 99, 167-70. 2. Smith et al., JCO, 2007, 3816-22. Supported by the Mary-Jean Mitchell Green Foundation and Breakthrough Breast Cancer. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr S2-5.

The IX International Aromatase Conference focused upon key developments in research related to the aromatase enzyme that had occurred since the last meeting. A session took place at the conclusion of conference discussing key areas for future research and issues currently facing researchers in the field. While significant progress on understanding structural elements of the enzyme and regulatory mechanisms of both the gene and protein provides an excellent basis for development of improved aromatase inhibitors and exploration of the important problem of aromatase inhibitor resistance, significant challenges remain. Increasing the speed with which findings are translated into clinical practice and finding an appropriate balance between basic and translational research were identified as areas which require further attention before the next meeting in 2010.

Aromatase inhibitors play a key role in the clinical management of hormone receptor–positive breast cancer and have potential utility as chemopreventive agents. Further understanding of the molecular effects of estrogen and its deprivation in normal breast tissue may allow the development of biomarkers of risk of breast cancer and help to predict the value of chemoprevention with aromatase inhibitors. Core biopsies of normal breast tissue were taken before and after letrozole treatment from postmenopausal women in the LITMaS pilot prevention study. RNA was extracted from these samples and used for cDNA microarray analysis. Gene expression changes induced by letrozole treatment were much less extensive than observed in estrogen receptor–positive malignant tissue; however, overall, they correlated to a highly significant degree (ρ = 0.511; P < 10−20). As well as some classically estrogen-associated genes, many genes associated with extracellular matrix remodeling were affected by estrogen deprivation in the normal breast in vivo. These data indicate for the first time that gene expression of normal breast tissue remains dependent on endogenous estrogens after the menopause. The modest degree of gene change suggests that intermediate markers of chemoprevention may be difficult to identify. (Cancer Epidemiol Biomarkers Prev 2008;17(4):855–63)

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. Electronic supplementary material The online version of this article (doi:10.1186/s13058-015-0532-0) contains supplementary material, which is available to authorized users.

Mechanisms of resistance to aromatase inhibitor treatment have been examined in vitro, in mouse models and in tumours in human patients. These varying approaches have yielded a range of potential routes through which breast cancer cells may survive and continue to proliferate during treatment with aromatase inhibitors. Many of these mechanisms are not directly linked to endocrine signalling pathways, and include alterations in other growth factor pathways and the tumour microenvironment. In general, approaches focussing on long-term oestrogen deprivation of cultured cells have identified cell-intrinsic mechanisms of resistance while utilising whole tumour specimens has detected the contribution of stromal elements. Many mechanisms have been validated in more than one setting. In this chapter, we discuss the role of key growth factor pathways such as PI3K/mTOR, IGF, GDNF and Myc as well as the contribution of inflammatory immune cells and adipocytes. Advances in genomic analysis and greater understanding of the role of tumour heterogeneity look likely to provide further insight into the mechanisms through which cells withstand treatment with aromatase inhibitors and help improve therapy in the future.

Purpose: Endocrine therapies include aromatase inhibitors and the selective estrogen receptor (ER) downregulator fulvestrant. This study aimed to determine whether the reported efficacy of fulvestrant over anastrozole, and high- over low-dose fulvestrant, reflect distinct transcriptional responses. Experimental Design: Global gene expression profiles from ERα-positive breast carcinomas before and during presurgical treatment with fulvestrant (n = 22) or anastrozole (n = 81), and corresponding in vitro models, were compared. Transcripts responding differently to fulvestrant and estrogen deprivation were identified and integrated using Gene Ontology, pathway and network analyses to evaluate their potential significance. Results: The overall transcriptional response to fulvestrant and estrogen deprivation was correlated (r = 0.61 in presurgical studies, r = 0.87 in vitro), involving downregulation of estrogen-regulated and proliferation-associated genes. The transcriptional response to fulvestrant was of greater magnitude than estrogen deprivation (slope = 0.62 in presurgical studies, slope = 0.63 in vitro). Comparative analyses identified 28 genes and 40 Gene Ontology categories affected differentially by fulvestrant. Seventeen fulvestrant-specific genes, including CAV1/2, SNAI2, and NRP1, associated with ERα, androgen receptor (AR), and TP53, in a network regulating cell cycle, death, survival, and tumor morphology. Eighteen genes responding differently to fulvestrant specifically predicted antiproliferative response to fulvestrant, but not anastrozole. Transcriptional effects of low-dose fulvestrant correlated with high-dose treatment, but were of lower magnitude (ratio = 0.29). Conclusions: The transcriptional response to fulvestrant has much in common with estrogen deprivation, but is stronger with distinctions potentially attributable to arrest of estrogen-independent ERα activity and involvement of AR signaling. Genes responding differently to fulvestrant may have predictive utility. These data are consistent with the clinical efficacy of fulvestrant versus anastrozole and higher dosing regimens. Clin Cancer Res; 20(15); 3962–73. ©2014 AACR.

Breast cancer is the most common malignancy and is the second leading cause of cancer-related death in American women. Approximately 75% of breast tumors express the oestrogen receptor, which can be targeted for with selective oestrogen receptor modulator such as tamoxifen, or by blocking oestrogen synthesis using aromatase inhibitors. However, approximately a quarter of patients treated for at least five years relapse with the disease within a decade. Many transcriptome studies have been conducted on breast tumor samples with clinical data to generate gene signatures predictive of treatment outcome. While several signatures have been reported, these features tend to be correlated with proliferation and give little information about the underlying tumor biology. An emerging hallmark of cancer is the reprogramming of metabolic networks to meet the demand required for rapid growth of a tumor. Tumors are generally highly glycolytic to meet their energetic requirements, as well as to provide substrates for anabolic reactions necessary for cell growth. However, perturbations in other metabolic pathways that are essential for tumor development and growth remain poorly understood. In this study, we sought to identify and characterise molecular features associated with metabolism that are significantly correlated with breast cancer patient outcome. To achieve this, we performed Cox regression analysis on a training set of microarray gene expression data of 973 oestrogen-receptor positive breast tumors. To identify functional enrichment for the molecular features associated with disease-free survival, gene set enrichment analysis was performed. This analysis revealed a 19-gene signature involved in fatty acid metabolism that showed higher expression to be correlated with good prognosis in the training data (multivariate hazard ratio = 0.51, log-rank p = 2.23e-10). The prognostic performance of this signature was validated on an independent dataset (n=654, multivariate hazard ratio = 0.66, log-rank p = 6.51e-5). Using the online KMplotter software, the fatty acid metabolism signature was found to also be prognostic in both lung cancer (n=1926, univariate hazard ratio = 0.58, log-rank p = 1.1e-16) and gastric cancer (n=593, univariate hazard ratio = 0.73, log-rank p = 0.0012). Based on our bioinformatic findings, we hypothesise that tumors with lowered fatty acid metabolism are more likely to exhibit invasive properties. Current work is focused on understanding how modulating fatty acid metabolism affects tumor biology, and may present a therapeutically tractable process that can be targeted with existing drugs. Citation Format: Abdul Aziz Bin Aiderus, Michael A. Black, Anita K. Dunbier. Expression of metabolic genes is associated with prognosis in breast cancer. [abstract]. In: Proceedings of the AACR Special Conference: Metabolism and Cancer; Jun 7-10, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(1_Suppl):Abstract nr A44.

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.

International audience; Over the last 20 years, aromatase inhibitors have been developed to become a highly effective treatment strategy for treatment of hormone receptor positive breast cancer. Despite their success, poor response and resistance limit the effectiveness of these agents in up to 50% of patients. In recent years, studies using highly sensitive hormone assays have provided insight into the source of oestrogen production for the stimulation of oestrogen receptor positive breast cancer growth, suggesting that uptake from the circulation is likely to make a significant contribution to intratumoural oestradiol. To obtain insight into how tumours become resistant to oestrogen after aromatase inhibition, long term oestrogen deprivation of cultured cells has been used to mimic acquired resistance to aromatase inhibitors. This work has aided the selection of agents to rationally combine with aromatase inhibitors to combat resistance. Molecular profiling using genome-wide approaches has shed new light on the heterogeneity of responses to oestrogen deprivation and predictors of resistance . Testing new agents and combinations in short-term pre-surgical studies using biomarkers such as Ki67 is critical for increasing the rate at which new rational combinations can be assessed for efficacy.

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, Author Summary Recent genome-wide analysis has revealed that the way in which genes are arranged on chromosomes and the conformation of these chromosomes are crucial for the regulation of gene expression. Reflecting this arrangement, clusters of genes which are regulated together have been discovered. We have identified a previously unreported transcriptional activity hub spanning ESR1, the gene encoding the important breast cancer biomarker oestrogen receptor. Genetic variants immediately upstream of ESR1 have recently been linked to breast cancer risk. We found that three open reading frames within this region are tightly co-expressed with ESR1. We investigated the function of these genes and discovered that one of these co-expressed genes, C6ORF211, affects proliferation in cultured cells and is correlated with proliferation in breast tumours. Another of the genes, C6ORF97, is negatively correlated with proliferation in breast tumours and predicts for outcome on the anti-oestrogen drug tamoxifen. These findings suggest that the genes could contribute to the phenotype associated with oestrogen-receptor positivity. In addition, they may be involved in the mechanism by which genetic variation in this region of the genome contributes to breast cancer susceptibility.

The contribution of local synthesis versus circulatory delivery of normal breast as well as breast cancer tissue estrogens has remained a controversial area for decades. Novel data on tissue estrogen levels confirm a positive normal breast tissue to plasma concentration gradient for estrone, and to a smaller extent estradiol. Remarkably, this gradient is similar for pre- and post-menopausal women. Together with pharmacokinetic data on estrogen disposition, these findings suggest plasma and breast tissue estrogens to rapidly equilibrate, with circulating estrogens being a major contributor to breast tissue estrone levels. A likely explanation to the concentration gradient could be the fact that non-polar estrogens easily dissolve into tissue fat compartments as compared to plasma. While intratumor estrone levels are low as compared to benign tissue concentrations, intratumor estradiol is elevated in ER+ tumors. The correlation between intratumor estradiol levels and expression levels of dehydrogenases reducing estrone into estradiol but also intratumor ER concentrations are consistent with intratumor estrogen activation but also a scavenger effect of the ER.

Background Inherited genetic factors such as E-cadherin (CDH1) promoter variants are believed to influence the risk towards sporadic diffuse gastric cancer (DGC). Recently, a new regulatory region essential for CDH1 transcription has been identified in CDH1 intron 2. Methods We genotyped all known polymorphisms located within conserved sequences of CDH1 intron 2 (rs10673765, rs9932686, rs1125557, rs9282650, rs9931853) in an Italian population consisting of 134 DGC cases and 100 healthy controls (55 patient relatives and 45 unrelated, matched individuals). The influence of individual variants on DGC risk was assessed using χ2-tests and logistic regression. The relative contribution of alleles was estimated by haplotype analysis. Results We observed a significant (p < 0.0004) association of the CDH1 163+37235G>A variant (rs1125557) with DGC risk. Odds ratios were 4.55 (95%CI = 2.09–9.93) and 1.38 (95%CI = 0.75–2.55) for AA and GA carriers, respectively. When adjusted for age, sex, smoking status, alcohol intake and H. pylori infection, the risk estimates remained largely significant for AA carriers. Haplotype analysis suggested the 163+37235A-allele contributes to disease risk independently of the other variants studied. Conclusion The CDH1 163+37235G>A polymorphism may represent a novel susceptibility variant for sporadic DGC if confirmed in other populations. Considering the broad expression of E-cadherin in epithelia, this exploratory study encourages further evaluation of the 163+37235A-allele as a susceptibility variant in other carcinomas.

The initial development of diffuse gastric cancer (DGC) is poorly understood. The study of E-cadherin (CDH1) germ line mutation carriers predisposed to DGC provides a rare opportunity to elucidate the genetic and biological events surrounding disease initiation. Samples from various stages of hereditary and sporadic DGC were investigated to determine general mechanisms underlying early DGC development. Paraffin-embedded tissues from 13 CDH1 mutation carriers and from 10 sporadic early DGC cases were analyzed. Immunofluorescence and immunohistochemistry using differentiation, proliferation, and adhesion markers showed that DGC initiation seems to occur at the proliferative zone (the upper neck) of the gastric epithelium and correlates with absent or reduced expression of junctional proteins (β-actin, p120, Lin-7). Slow proliferation of neoplastic cells at the upper gastric neck leads to the formation of intramucosal signet-ring cell carcinoma (SRCC) displaying differentiated features. As shown by immunolabeling, invasion from SRCC lesions beyond the gastric mucosa is associated with poor differentiation, increased proliferation, activation of the c-Src system, and an epithelial-mesenchymal transition. Our results provide a molecular description of the early development of DGC and explain the relationship between the two main DGC types, poorly differentiated carcinoma and SRCC: both share their origin, but SRCC develops following cancer cell differentiation and seems relatively indolent in its intramucosal stage. [Cancer Res 2007;67(6):2480–9]

Background: Aromatase inhibitors (AIs) have an established role in the treatment of estrogen receptor alpha positive (ER+) post-menopausal breast cancer. Response rates are 50-70% in the neoadjuvant setting and lower in advanced disease. There is a need to identify biomarkers to predict response that outperform those currently available, to be able to offer more stratified treatments and improved patient care. Methods: Pre- and on-treatment (at 14 days and 3-months) biopsies were obtained from 89 post-menopausal women with ER+ breast cancer receiving 3 months of neoadjuvant Letrozole. Illumina Beadarray gene expression data (n = 34) were combined with Affymetrix GeneChip data (n = 55) and cross-platform integration approaches developed as part of this study were implemented to combine data. Dynamic clinical response was assessed for each patient using periodic 3D ultrasound measurements performed during treatment. A gene classifier was developed from pre and 14 day gene array expression data to predict response. An independent series from the Royal Marsden was used to validate the classifier. Results: Response to endocrine therapy in the neoadjuvant setting based on the expression of 4 genes has been developed. The classifier comprises baseline expression of an immune signalling gene and an apoptosis related gene, together with 14 day expression of two proliferation genes. Early on-treatment gene changes in combination with pre-treatment gene expression significantly improve predictive power compared to pre-treatment gene expression alone. The classifier had a 96% accuracy in a training dataset (n = 73) and 91% accuracy in an independent validation dataset (n = 44) dataset. Table 1 AccuracySensitivitySpecificityPPVNPVAUC (ROC)Training0.960.890.980.890.960.96Validation0.910.80.970.920.9NASensitivity and specificity of model in training and validation datasets Expression of the pre-treatment immune signalling gene alone predicted for response with 85% and 82% accuracy in training and validation datasets respectively. Higher pre-treatment levels of this gene were associated with a significantly better 1 year progression free survival (PFS) (P = 0.0001). In a larger series of patients treated with neoadjuvant Letrozole (n = 129) higher expression of this gene alone was associated with a significantly improved 10 year RFS (p = 0.0359). In a separate tamoxifen treated cohort (n = 212) higher expression of this gene at diagnosis was associated with a significantly improved 5 year (p = 0.0015) and 10 year (p = 0.04) recurrence free survival (RFS). Conclusion: • A 4 gene classifier has been developed and validated to predict response to neoadjuvant Letrozole. • One of the genes identified is a significant predictor in independent data sets of long term RFS in endocrine treated patients. • This new classifier has the potential to predict accurately the benefit of endocrine therapy and has huge potential clinical value. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr PD3-2.

Aim: To determine the relevance of PDGF/Abl signaling pathway as a therapeutic target in endocrine resistance in vitro and in vivo. Rationale: Targeting estrogenic stimulation reduces mortality from ER-positive (ER+) breast cancer (BC) but resistance remains a major clinical problem. To identify the molecular mechanisms associated with resistance to estrogen-deprivation, we previously assessed the temporal changes in gene expression during adaptation to long-term culture of MCF7 human breast cancer cells in the absence of estradiol (E2) (LTED), modeling resistance to an aromatase inhibitor (AI). Platelet-derived growth factor (PDGF)/Abl signaling was the top adaptive pathway at the point of resistance (p=1.15 E-07), but there is limited evidence for it playing a role clinically. Methods: Gene expression data from postmenopausal women with ER+ BC at pre-treatment and at 2-week on-treatment with neoadjuvant anastrozole were interrogated. Immunohistochemical staining using antibodies against PDGFRα, β and Abl was assessed in paired clinical specimen of 45 patients who had received an AI and presented progressive disease. Proliferation assays, immunoblots and ChIP assays were carried out using either the PDGFR/Abl inhibitor nilotinib or siRNA knockdowns in LTED and wild-type MCF7 cells. Results: In vitro: PDGFRβ and Abl expression and phosphorylation were elevated in LTED cells. Cell proliferation was decreased in LTED cells by siRNA knock-down of either PDGFRβ (50% p High post-treatment tumor and stromal PDGFRβ levels were associated with a short time to treatment failure (TTF) (T: Rs −0.284, p=0.066; S: Rs −0.307, p=0.046). Expression of PDGFRα in relapsing tumor specimens was correlated with Abl expression (Rs 0.342, p=0.027) and Ki67 levels (Rs 0.39, p=0.01). Furthermore, changes in Abl correlated significantly with changes in ER expression (Rs 0.307, p=0.048). Discussion: These in vitro and clinical data support a biological interaction between PDGF/Abl and ER-signaling and suggest that the PDGF signaling pathway warrants clinical evaluation as a therapeutic target in endocrine resistant breast cancer. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P4-01-01.

The majority of breast tumours at primary diagnosis are estrogen receptor positive (ER). Estrogen (E) mediates its effects by binding to the ER. E-bound ER associates classically with estrogen response elements (EREs) on target genes controlling proliferation and cell survival. ER's ability to regulate gene transcription is also influenced by the activity of co-regulatory proteins such as AIB1. Therapies targeting the estrogenic stimulation of tumour growth have been a major success in reducing mortality from ER-positive breast cancer. However, resistance remains a major clinical problem. To identify the molecular mechanisms associated with resistance to E-deprivation, we assessed the temporal changes in gene expression during adaptation to long-term culture of MCF7 human breast cancer cells in the absence of E2 (LTED), modelling resistance to an aromatase inhibitor (AI). Analyses of canonical signalling pathways showed that platelet-derived growth factor (PDGF)/Abl was significantly elevated as early as one-week post E-deprivation (p=1.94 E-04). Of note this became the top adaptive pathway at the point of resistance (p=1.15 E-07). Clinical data from 88 patients treated with an AI in the neoadjuvant setting, showed increases in PDGFRβ and PDGF expression after two weeks (1.25 fold, p=0.003 and 1.43 fold, p=4.4E-06). Low PDGFRβ at pre-treatment was associated with a better response. Assessment of the level of protein expression and activation status in a panel of cell lines modelling both endocrine sensitive and resistant breast cancer showed PDGFRβ was elevated in both LTED and tamoxifen resistant MCF7 cells (TAMR) compared to wt-MCF7. Moreover, the level of receptor phosphorylation was increased in the resistant cell lines. PDGFRβ expression was also evident in SKBR3 (ER-/ERBB2+) but not in BT474 (ER+/ERBB2+) cells. Of note both LTED and TAMR cells were sensitive to the inhibitory effect of the PDGFR/Abl tyrosine kinase inhibitor nilotinib, in the presence or absence of E. In contrast wt-MCF7 cells showed limited sensitivity in the presence of E. Both SKBR3 and BT474 cells were insensitive. These data suggested that PDGFRβ was associated with the endocrine resistant phenotype. Assessment using ER/ERE linked reporter assays showed nilotinib suppressed ER-mediated transcription and inhibited expression of two endogenous E-regulated genes TFF1 and PGR. Chromatin immunoprecipitation indicated that nilotinib reduced the recruitment of AIB1 and CBP to the TFF1 promoter. Furthermore we were able to demonstrate that nilotinib in combination with tamoxifen resensitised TAMR cells to the inhibitory effect of tamoxifen. These data for the first time reveal cross talk between ER and PDGF/Abl, strongly suggesting that the PDGF signalling pathway merits clinical evaluation as a therapeutic target in endocrine resistant breast cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2920.

Aromatase inhibitors (AI) have improved the treatment of estrogen receptor positive (ER+) early and advanced breast cancer (BC). However, the efficacy of AIs is limited by disease progression or relapse. No data is available assessing the temporal changes in gene expression during the development of acquired resistance to long-term estrogen deprivation (LTED). To model the adaptive changes associated with resistance to AI therapy, ER+ human BC cells MCF7 were cultured in the absence of estrogen (E). Genome-wide expression analysis using Illumina 48K arrays was performed to assess changes in gene expression during adaptation at 10 time-points up to 40 weeks (wks). Strikingly, the expression of a proliferation metagene showed resistance to E-deprivation occurred as early as 9 wks. Validation by global assessment of gene expression, revealed a stabilisation of the gene signatures after this time-point. Further analyses were restricted to a triangular pairwise comparison: wt MCF7 cells (modelling pre-treatment), 1 wk post E-deprivation (on AI treatment) and at 9 wks (clinical relapse). Comparison of wt MCF7 versus 1 wk showed 2158 genes were down-regulated and 1724 genes were up-regulated (p Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4598.

Aberrant promoter methylation and the associated loss of gene expression is a common accompaniment of human cancers. Nonetheless, it has been challenging to demonstrate in any given tumour that methylation of a specific gene was causal and not consequent to malignant transformation. In this regard, our attention was drawn to the genesis of gastric cancers in individuals with hereditary diffuse gastric cancer (HDGC). These individuals harbour germline mutations in the gene encoding E-cadherin, CDH1, but their cancers have consistently demonstrated absence of loss of heterozygosity at the CDH1 locus. These findings suggested the hypothesis that CDH1 promoter methylation might function as the 'second genetic hit' in the genesis of these cancers.