Oestrogen deprivation induces chemokine production and immune cell recruitment in in vitro and in vivo models of oestrogen receptor-positive breast cancer.

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.

Fatty acid oxidation is associated with proliferation and prognosis in breast and other cancers.

BACKGROUND: Altered cellular metabolism is a hallmark of cancer but the association between utilisation of particular metabolic pathways in tumours and patient outcome is poorly understood. We sought to investigate the association between fatty acid metabolism and outcome in breast and other cancers. METHODS: Cox regression analysis and Gene Set Enrichment Analysis (GSEA) of a gene expression dataset from primary breast tumours with well annotated clinical and survival information was used to identify genesets associated with outcome. A geneset representing fatty acid oxidation (FAO) was then examined in other datasets. A doxycycline-inducible breast cancer cell line model overexpressing the rate-limiting enzyme in FAO, carnitine palmitoyl transferase 1A (CPT1A) was generated and analysed to confirm the association between FAO and cancer-associated characteristics in vitro. RESULTS: We identified a gene expression signature composed of 19 genes associated with fatty acid oxidation (FAO) that was significantly associated with patient outcome. We validated this observation in eight independent breast cancer datasets, and also observed the FAO signature to be prognostic in other cancer types. Furthermore, the FAO signature expression was significantly downregulated in tumours, compared to normal tissues from a variety of anatomic origins. In breast cancer, the expression of CPT1A was higher in oestrogen receptor (ER)-positive, compared to ER-negative tumours and cell lines. Importantly, overexpression of CPT1A significantly decreased the proliferation and wound healing migration rates of MDA-MB231 breast cancer cells, compared to basal expression control. CONCLUSIONS: Our findings suggest that FAO is downregulated in multiple tumour types, and activation of this pathway may lower cancer cell proliferation, and is associated with improved outcomes in some cancers.

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.

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.

Restriction site associated DNA sequencing for tumour mutation burden estimation and mutation signature analysis.

BACKGROUND: Genome-wide measures of genetic disruption such as tumour mutation burden (TMB) and mutation signatures are emerging as useful biomarkers to stratify patients for treatment. Clinicians commonly use cancer gene panels for tumour mutation burden estimation, and whole genome sequencing is the gold standard for mutation signature analysis. However, the accuracy and cost associated with these assays limits their utility at scale. METHODS: WGS data from 560 breast cancer patients was used for in silico library simulations to evaluate the accuracy of an FDA approved cancer gene panel as well as restriction enzyme associated DNA sequencing (RADseq) libraries for TMB estimation and mutation signature analysis. We also transfected a mouse mammary cell line with APOBEC enzymes and sequenced resulting clones to evaluate the efficacy of RADseq in an experimental setting. RESULTS: RADseq had improved accuracy of TMB estimation and derivation of mutation profiles when compared to the FDA approved cancer panel. Using simulated immune checkpoint blockade (ICB) trials, we show that inaccurate TMB estimation leads to a reduction in power for deriving an optimal TMB cutoff to stratify patients for immune checkpoint blockade treatment. Additionally, prioritisation of APOBEC hypermutated tumours in these trials optimises TMB cutoff determination for breast cancer. The utility of RADseq in an experimental setting was also demonstrated, based on characterisation of an APOBEC mutation signature in an APOBEC3A transfected mouse cell line. CONCLUSION: In conclusion, our work demonstrates that RADseq has the potential to be used as a cost-effective, accurate solution for TMB estimation and mutation signature analysis by both clinicians and basic researchers.

Structure vs. Function of TRIB1-Myeloid Neoplasms and Beyond.

The Tribbles family of proteins-comprising TRIB1, TRIB2, TRIB3 and more distantly related STK40-play important, but distinct, roles in differentiation, development and oncogenesis. Of the four Tribbles proteins, TRIB1 has been most well characterised structurally and plays roles in diverse cancer types. The most well-understood role of TRIB1 is in acute myeloid leukaemia, where it can regulate C/EBP transcription factors and kinase pathways. Structure-function studies have uncovered conformational switching of TRIB1 from an inactive to an active state when it binds to C/EBPα. This conformational switching is centred on the active site of TRIB1, which appears to be accessible to small-molecule inhibitors in spite of its inability to bind ATP. Beyond myeloid neoplasms, TRIB1 plays diverse roles in signalling pathways with well-established roles in tumour progression. Thus, TRIB1 can affect both development and chemoresistance in leukaemia; glioma; and breast, lung and prostate cancers. The pervasive roles of TRIB1 and other Tribbles proteins across breast, prostate, lung and other cancer types, combined with small-molecule susceptibility shown by mechanistic studies, suggests an exciting potential for Tribbles as direct targets of small molecules or biomarkers to predict treatment response.

Emerging biomarkers and new understanding of traditional markers in personalized therapy for breast cancer.

The era of personalized medicine is likely to see an escalation in the use of biomarkers to ensure breast cancer patients receive optimal treatment. A combination of prognostic and predictive biomarkers should enable better quantification of the residual risk faced by patients and indicate the potential value of additional treatment. Established biomarkers such as estrogen receptor and progesterone receptor already play a significant role in the selection of patients for endocrine therapy. Human epidermal growth factor receptor 2 (HER2) is recognized as a strong predictor of response to trastuzumab whereas, more recently, the role of estrogen receptor and HER2 as negative and positive indicators for chemotherapy has also been explored. Ki67 has traditionally been recognized as a modest prognostic factor, but recent neoadjuvant studies suggest that on-treatment measurement may be a more effective predictor of treatment efficacy for both endocrine treatment and chemotherapy. The last decade has seen the emergence of numerous multigene expression profiles that aim to outdo traditional predictive and prognostic factors. The Oncotype DX assay and the MammaPrint profile are currently undergoing prospective clinical trials to clearly define their role. Other gene expression-based assays also show potential but are yet to be tested clinically. Rigorous comparison of these emerging markers with current treatment selection criteria will be required to determine whether they offer significant benefit to justify their use.

Impact of estrogen deprivation on gene expression profiles of normal postmenopausal breast tissue in vivo.

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 (rho = 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.

Substrate binding allosterically relieves autoinhibition of the pseudokinase TRIB1.

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/EBPß 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.

A PAM50-Based Chemoendocrine Score for Hormone Receptor-Positive Breast Cancer with an Intermediate Risk of Relapse.

Purpose: Hormone receptor-positive (HR+) breast cancer is clinically and biologically heterogeneous, and subgroups with different prognostic and treatment sensitivities need to be identified.Experimental Design: Research-based PAM50 subtyping and expression of additional genes was performed on 63 patients with HR+/HER2- disease randomly assigned to neoadjuvant multiagent chemotherapy versus endocrine therapy in a phase II trial. The biology associated with treatment response was used to derive a PAM50-based chemoendocrine score (CES). CES's predictive ability was evaluated in 4 independent neoadjuvant data sets (n = 675) and 4 adjuvant data sets (n = 1,505). The association of CES, intrinsic biology, and PAM50 risk of relapse (ROR) was explored across 6,007 tumors.Results: Most genes associated with endocrine sensitivity were also found associated with chemotherapy resistance. In the chemotherapy test/validation data sets, CES was independently associated with pathologic complete response (pCR), even after adjusting for intrinsic subtype. pCR rates of the CES endocrine-sensitive (CES-E), uncertain (CES-U), and chemotherapy-sensitive (CES-C) groups in both data sets combined were 25%, 11%, and 2%, respectively. In the endocrine test/validation data sets, CES was independently associated with response. Compared with ROR, >90% of ROR-low and ROR-high tumors were identified as CES-E and CES-C, respectively; however, each CES group represented >25% of ROR-intermediate disease. In terms of survival outcome, CES-C was associated with poor relapse-free survival in patients with ROR-intermediate disease treated with either adjuvant endocrine therapy only or no adjuvant systemic therapy, but not in patients treated with (neo)adjuvant chemotherapy.Conclusions: CES is a genomic signature capable of estimating chemoendocrine sensitivity in HR+ breast cancer beyond intrinsic subtype and risk of relapse. Clin Cancer Res; 23(12); 3035-44. ©2016 AACR.

Accurate Prediction and Validation of Response to Endocrine Therapy in Breast Cancer.

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.

Effect of aromatase inhibition on functional gene modules in estrogen receptor-positive breast cancer and their relationship with antiproliferative response.

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.

Differences in the transcriptional response to fulvestrant and estrogen deprivation in ER-positive breast cancer.

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.

Comparison of PAM50 risk of recurrence score with oncotype DX and IHC4 for predicting risk of distant recurrence after endocrine therapy.

PURPOSE: Risk of distant recurrence (DR) among women with estrogen receptor (ER) -positive early breast cancer is the major determinant of recommendations for or against chemotherapy. It is frequently estimated using the Oncotype DX recurrence score (RS). The PAM50 risk of recurrence (ROR) score provides an alternative approach, which also identifies intrinsic subtypes. PATIENTS AND METHODS: mRNA from 1,017 patients with ER-positive primary breast cancer treated with anastrozole or tamoxifen in the ATAC trial was assessed for ROR using the NanoString nCounter. Likelihood ratio (LR) tests and concordance indices (c indices) were used to assess the prognostic information provided beyond that of a clinical treatment score (CTS) by RS, ROR, or IHC4, an index of DR risk derived from immunohistochemical assessment of ER, progesterone receptor, human epidermal growth factor receptor 2 (HER2), and Ki67. RESULTS: ROR added significant prognostic information beyond CTS in all patients (Δ LR-χ(2) = 33.9; P < .001) and in all four subgroups: node negative, node positive, HER2 negative, and HER2 negative/node negative; more information was added by ROR than by RS. C indices in the HER2-negative/node-negative subgroup were 0.73, 0.76, and 0.78 for CTS, CTS plus RS, and CTS plus ROR, respectively. More patients were scored as high risk and fewer as intermediate risk by ROR than by RS. Relatively similar prognostic information was added by ROR and IHC4 in all patients but more by ROR in the HER2-negative/node-negative group. CONCLUSION: ROR provides more prognostic information in endocrine-treated patients with ER-positive, node-negative disease than RS, with better differentiation of intermediate- and higher-risk groups.

Molecular profiling of aromatase inhibitor-treated postmenopausal breast tumors identifies immune-related correlates of resistance.

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.

New and translational perspectives of oestrogen deprivation in breast cancer.

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 in vivo. 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.

Association between breast cancer subtypes and response to neoadjuvant anastrozole.

Considerable heterogeneity exists amongst oestrogen receptor positive (ER+ve) breast cancer in both its molecular profile and response to therapy. Attempts to better define variation amongst breast tumours have led to the definition of four main "intrinsic" subtypes of breast cancer with two of these classes, Luminal A and B, composed almost entirely of ER+ve cancers. In this study we set out to investigate the significance of intrinsic subtypes within a group of ER+ve breast cancers treated with neoadjuvant anastrozole. RNA from tumour biopsies taken from 104 postmenopausal women before and after 2 weeks treatment with anastrozole was analyzed on Illumina 48K microarrays. Gene-expression based subtypes and risk of relapse (ROR) scores for tumours pre- and post-treatment were determined using the PAM50 method. Amongst pre-treatment samples, all intrinsic subtypes were found to be present, although luminal groups were represented most highly. Luminal A and B tumours obtained similar benefit from treatment, as measured by the proportional fall in the proliferation marker Ki67 upon treatment (mean suppression=75.5% vs 75.7%). Tumours classified as basal and Her2-like showed poor reductions in Ki67 upon treatment. Residual Ki67 staining after two weeks remained higher in the Luminal B group. ROR score was significantly associated with anti-proliferative response to AI and with clinical response. These results suggest that in the short-term, Luminal A and B tumours may gain similar benefit from an AI but that the higher residual Ki67 level seen in Luminal B is indicative of poorer long term outcome.

Close and stable relationship between proliferation and a hypoxia metagene in aromatase inhibitor-treated ER-positive breast cancer.

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.

Progress in aromatase research and identification of key future directions.

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.

Relationship between plasma estradiol levels and estrogen-responsive gene expression in estrogen receptor-positive breast cancer in postmenopausal women.

PURPOSE To determine whether plasma estradiol (E2) levels are related to gene expression in estrogen receptor (ER)-positive breast cancers in postmenopausal women. Materials and METHODS Genome-wide RNA profiles were obtained from pretreatment core-cut tumor biopsies from 104 postmenopausal patients with primary ER-positive breast cancer treated with neoadjuvant anastrozole. Pretreatment plasma E2 levels were determined by highly sensitive radioimmunoassay. Genes were identified for which expression was correlated with pretreatment plasma E2 levels. Validation was performed in an independent set of 73 ER-positive breast cancers. Results The expression of many known estrogen-responsive genes and gene sets was highly significantly associated with plasma E2 levels (eg, TFF1/pS2, GREB1, PDZK1 and PGR; P < .005). Plasma E2 explained 27% of the average expression of these four average estrogen-responsive genes (ie, AvERG; r = 0.51; P < .0001), and a standardized mean of plasma E2 levels and ER transcript levels explained 37% (r, 0.61). These observations were validated in an independent set of 73 ER-positive tumors. Exploratory analysis suggested that addition of the nuclear coregulators in a multivariable analysis with ER and E2 levels might additionally improve the relationship with the AvERG. Plasma E2 and the standardized mean of E2 and ER were both significantly correlated with 2-week Ki67, a surrogate marker of clinical outcome (r = -0.179; P = .05; and r = -0.389; P = .0005, respectively). CONCLUSION Plasma E2 levels are significantly associated with gene expression of ER-positive breast cancers and should be considered in future genomic studies of ER-positive breast cancer. The AvERG is a new experimental tool for the study of putative estrogenic stimuli of breast cancer.