Predicting response and resistance to endocrine therapy

Tamoxifen Response at Single-Cell Resolution in Estrogen Receptor-Positive Primary Human Breast Tumors

PURPOSE

In estrogen receptor-positive (ER+)/HER2- breast cancer, multiple measures of intratumor heterogeneity are associated with a worse response to endocrine therapy. We sought to develop a novel experimental model to measure heterogeneity in response to tamoxifen treatment in primary breast tumors.

EXPERIMENTAL DESIGN

To investigate heterogeneity in response to treatment, we developed an operating room-to-laboratory pipeline for the collection of live normal breast specimens and human tumors immediately after surgical resection for processing into single-cell workflows for experimentation and genomic analyses. Live primary cell suspensions were treated ex vivo with tamoxifen (10 μmol/L) or control media for 12 hours, and single-cell RNA libraries were generated using the 10X Genomics droplet-based kit.

RESULTS

In total, we obtained and processed normal breast tissue from two women undergoing reduction mammoplasty and tumor tissue from 10 women with ER+/HER2- invasive breast carcinoma. We demonstrate differences in tamoxifen response by cell type and identify distinctly responsive and resistant subpopulations within the malignant cell compartment of human tumors. Tamoxifen resistance signatures from resistant subpopulations predict poor outcomes in two large cohorts of ER+ breast cancer patients and are enriched in endocrine therapy-resistant tumors.

CONCLUSIONS

This novel ex vivo model system now provides the foundation to define responsive and resistant subpopulations within heterogeneous human tumors, which can be used to develop precise single cell-based predictors of response to therapy and to identify genes and pathways driving therapeutic resistance.

Tamoxifen Response at Single Cell Resolution in Estrogen Receptor-Positive Primary Human Breast Tumors

In ER+/HER2- breast cancer, multiple measures of intra-tumor heterogeneity are associated with worse response to endocrine therapy. To investigate heterogeneity in response to treatment, we developed an operating room-to-laboratory pipeline for the collection of live human tumors and normal breast specimens immediately after surgical resection for processing into single-cell workflows for experimentation and genomic analyses. We demonstrate differences in tamoxifen response by cell type and identify distinctly responsive and resistant subpopulations within the malignant cell compartment of human tumors. Tamoxifen resistance signatures from 3 distinct resistant subpopulations are prognostic in large cohorts of ER+ breast cancer patients and enriched in endocrine therapy resistant tumors. This novel ex vivo model system now provides a foundation to define responsive and resistant sub-populations within heterogeneous tumors, to develop precise single cell-based predictors of response to therapy, and to identify genes and pathways driving resistance to therapy.

Neoadjuvant endocrine therapy in locally advanced estrogen or progesterone receptor-positive breast cancer: determining the optimal endocrine agent and treatment duration in postmenopausal women-a literature review and proposed guidelines

Introduction

For patients with locally advanced estrogen receptor or progesterone receptor-positive breast cancer, neoadjuvant endocrine therapy (NET) facilitates down-staging of the tumor and increased rates of breast-conserving surgery. However, NET remains under-utilized, and there are very limited clinical guidelines governing which therapeutic agent to use, or the optimal duration of treatment in postmenopausal women. This literature review aims to discuss the evidence surrounding (1) biomarkers for patient selection for NET, (2) the optimal neoadjuvant endocrine agent for postmenopausal women with locally advanced breast cancer, and (3) the optimal duration of NET. In addition, we make initial recommendations towards developing a clinical guideline for the prescribing of NET.

Method

A wide-ranging search of online electronic databases was conducted using a truncated PIC search strategy to identify articles that were relevant to these aims and revealed a number of key findings.

Results

Randomized trials have consistently demonstrated that aromatase inhibitors are more effective than tamoxifen, in terms of objective response rate and rate of BCS, and should be used as first-line NET. The three available aromatase inhibitors have so far been demonstrated to be biologically equivalent, with the choice of aromatase inhibitor not having been shown to affect clinical outcomes. There is increasing evidence for extending the duration of NET beyond 3 to 4 months, to at least 6 months or until maximal clinical response is achieved. While on-treatment levels of the proliferation marker Ki67 are predictive of long-term outcome, the choice of adjuvant therapy in patients who have received NET and then surgery is best guided by the preoperative endocrine prognostic index, or PEPI, which incorporates Ki67 with other clinical parameters.

Conclusion

This study reveals that in appropriately selected patients, NET can provide equivalent clinical benefit to neoadjuvant chemotherapy in the same cohort, if suitable treatments and durations are chosen. Our findings highlight the need for better defined biomarkers both for guiding patient selection and for measuring outcomes. Development of standard guidelines for the prescribing of NET has the potential to improve both clinical outcomes and quality of life in this patient cohort.

BASP1 interacts with oestrogen receptor α and modifies the tamoxifen response

Tamoxifen binds to oestrogen receptor α (ERα) to elicit distinct responses that vary by cell/tissue type and status, but the factors that determine these differential effects are unknown. Here we report that the transcriptional corepressor BASP1 interacts with ERα and in breast cancer cells, this interaction is enhanced by tamoxifen. We find that BASP1 acts as a major selectivity factor in the transcriptional response of breast cancer cells to tamoxifen. In all, 40% of the genes that are regulated by tamoxifen in breast cancer cells are BASP1 dependent, including several genes that are associated with tamoxifen resistance. BASP1 elicits tumour-suppressor activity in breast cancer cells and enhances the antitumourigenic effects of tamoxifen treatment. Moreover, BASP1 is expressed in breast cancer tissue and is associated with increased patient survival. Our data have identified BASP1 as an ERα cofactor that has a central role in the transcriptional and antitumourigenic effects of tamoxifen.

Aromatase inhibition remodels the clonal architecture of estrogen-receptor-positive breast cancers

Resistance to oestrogen-deprivation therapy is common in oestrogen-receptor-positive (ER+) breast cancer. To better understand the contributions of tumour heterogeneity and evolution to resistance, here we perform comprehensive genomic characterization of 22 primary tumours sampled before and after 4 months of neoadjuvant aromatase inhibitor (NAI) treatment. Comparing whole-genome sequencing of tumour/normal pairs from the two time points, with coincident tumour RNA sequencing, reveals widespread spatial and temporal heterogeneity, with marked remodelling of the clonal landscape in response to NAI. Two cases have genomic evidence of two independent tumours, most obviously an ER− ‘collision tumour', which was only detected after NAI treatment of baseline ER+ disease. Many mutations are newly detected or enriched post treatment, including two ligand-binding domain mutations in ESR1. The observed clonal complexity of the ER+ breast cancer genome suggests that precision medicine approaches based on genomic analysis of a single specimen are likely insufficient to capture all clinically significant information.

Aromatase inhibitors are used to treat oestrogen-receptor-positive breast cancer. Here, the authors use genomic approaches to analyse tumours before and after neo-adjuvant treatment and find that treatment alters the clonal landscape of the tumours.

Molecular effects of oestrogen deprivation in breast cancer

This paper reviews the effects of oestrogen deprivation by third generation aromatase inhibitors on molecular profiles in breast cancers. It particularly focuses on results obtained as a result of pre-operative and neoadjuvant therapy in which primary breast cancers have been biopsied or excised before and during treatment with letrozole, anastrozole or exemestane. Studies may be subdivided into those evaluating early (10-14 days) or late (3-4 months) changes; a single investigation charted sequential changes. Early changes involved downregulation of genes classically induced by oestrogen or associated with cell cycle and proliferation. In contrast, expressions of genes associated with stromal signatures were upregulated. Considerably more genes were changed at later time-points; these probably represent not only primary effects on cellular expression but secondary consequences of cell death and clonal selection. Thus, after 3-4 months of treatment mitochondrial-related genes and those associated with cell cycle and cell division were downregulated whereas genes associated with extracellular matrix (ECM) remodelling, vascularization, inflammatory responses and cell adhesion were upregulated. Recently, observations have been reported from a study in which tumours were sequentially sampled to include pretreatment and both early and later time-points. This allowed direct monitoring of the dynamic changes in gene expression. Different patterns of changes in gene expression were identified which were also associated with general differences in sub-cellular distribution of corresponding proteins. The effect of treatment on expression of specific genes and processes such as aromatase, oestrogen receptor (ER), oestrogen-regulated genes, HER2, p53, ribosomal proteins, markers of proliferation, oxidative phosphorylation and stromal response are summarized.

An updated review on the efficacy of adjuvant endocrine therapies in hormone receptor-positive early breast cancer

The third-generation aromatase inhibitors (AIS) are largely replacing tamoxifen in the adjuvant treatment of early-stage breast cancer in postmenopausal women with hormone receptor–positive tumours. To date, multiple trials have been conducted comparing tamoxifen treatment with an AI, and all have demonstrated improved disease-free survival with AI treatment. Trials have included direct 5-year comparisons between tamoxifen and an AI, switching to an AI within 5 years after initial tamoxifen treatment, or extending treatment with an AI after 5 years of completed tamoxifen treatment. Some of these trials have been completed; others are ongoing; and head-to-head trial comparisons of individual AIS are also in progress. The present article summarizes the data obtained from various clinical trials of hormonal therapy for early breast cancer. It also reviews recent data so as to shed light on the current status of these therapies. The focus is on the efficacy of treatment with an AI. Toxicity is discussed in the second article in this supplement.

Markers of sensitivity, dependence and resistance to endocrine therapy for breast cancer

Owing to its efficacy and relative lack of toxicities, endocrine therapy is a major treatment modality for breast cancer. However, resistance and the inability to accurately predict response are obstacles to optimal management. There is a need to identify markers of clinical response and elucidate mechanisms of resistance. In this article, evidence will be presented demonstrating that: discovery of predictive markers is dependent upon the approach employed and the application required; and mechanisms of resistance are diverse and not simply mirror images of response. Different information may be obtained according to assessment read outs and type of analysis. Tumors respond to endocrine therapy in a variety of ways and a range of end points can be used to monitor hormone dependence, sensitivity and resistance to treatment. Different forms of endocrine therapies may have differing mechanisms of action - hence, markers of sensitivity/response can vary between treatments and there may be correspondingly differing mechanisms of resistance.

Aromatase inhibitors: prediction of response and nature of resistance

IMPORTANCE OF THE FIELD

Aromatase inhibitors (AIs) are recommended for and central to endocrine management of breast cancer patients. Response rates can be high, but resistance is a major obstacle. Optimal management therefore requires accurate prediction of response and an understanding of the nature by which resistance occurs. These are the subjects of this review.

AREAS COVERED IN THIS REVIEW

The complications of assessing response in different clinical settings and the types of response in terms of clinical, pathological, proliferative and molecular endpoints are reviewed. The current status of predictors of response such as estrogen receptors (ERs), progesterone receptors, other markers of estrogen action, ER phosphorylation, ER coregulators and multigene signatures are assessed. Different types of resistance to AIs, their heterogeneity, diversity in mechanisms of resistance and their identification are also considered.

WHAT THE READER WILL GAIN

The review provides fundamental information on response and predictors of response to AIs as well as an understanding of the diversity of resistance mechanisms to such endocrine agents.

TAKE HOME MESSAGES

ER status is the only factor used routinely for treatment selection, but additional markers are needed to predict response. Other markers have some predictive powers, but are of limited utility. The hope is, therefore, that discovery strategies based on genome-wide searches will identify new markers. Assessments may be required both before and after a short period of treatment so that early changes can be used to predict subsequent clinical response. Mechanisms of resistance to AIs are diverse. Knowledge of specific resistance mechanisms in individual cases will be necessary if strategies to circumvent resistance are to be developed rationally. A future can be envisaged in which molecular phenotyping of individual tumors is used to decide not only which patients should be treated with AIs but also whether AIs should be used alone or in combination/sequence with other drug regimes.

Gene expression profiling of response to mTOR inhibitor everolimus in pre-operatively treated post-menopausal women with oestrogen receptor-positive breast cancer

There is growing evidence that uncontrolled activation of the PI3K/Akt/mTOR pathway contributes to the development and progression of breast cancer. Inhibition of this pathway has antitumour effects in preclinical studies and efficacy in combination with other agents in breast cancer patients. The aim of this study is to characterise the effects of pre-operative everolimus treatment in primary breast cancer patients and to identify potential molecular predictors of response. Twenty-seven patients with oestrogen receptor (ER)-positive breast cancer completed 11-14 days of neoadjuvant treatment with 5-mg everolimus. Core biopsies were taken before and after treatment and analysed using Illumina HumanRef-8 v2 Expression BeadChips. Changes in proliferation (Ki67) and phospho-AKT were measured on diagnostic core biopsies/resection samples embedded in paraffin by immunohistochemistry to determine response to treatment. Patients that responded to everolimus treatment with significant reductions in proliferation (fall in % Ki67 positive cells) also had significant decreases in the expression of genes involved in cell cycle (P = 8.70E-09) and p53 signalling (P = 0.01) pathways. Highly proliferating tumours that have a poor prognosis exhibited dramatic reductions in the expression of cell cycle genes following everolimus treatment. The genes that most clearly separated responding from non-responding pre-treatment tumours were those involved with protein modification and dephosphorylation, including DYNLRB2, ERBB4, PTPN13, ULK2 and DUSP16. The majority of ER-positive breast tumours treated with everolimus showed a significant reduction in genes involved with proliferation, these may serve as markers of response and predict which patients will derive most benefit from mTOR inhibition.

Clinical, pathological, proliferative and molecular responses associated with neoadjuvant aromatase inhibitor treatment in breast cancer

Neoadjuvant treatment provides an exceptional setting in which to monitor clinical, pathological, proliferative and molecular responses to aromatase inhibitors. Sequential measurements of the primary tumour provide an accurate assessment of clinical changes and the relatively easy access to the tumour within the breast means that biopsies are available for histological and molecular measurements before and during treatment. Large randomised trials (P024 and IMPACT) together with informative non-randomised studies have demonstrated clinical responses to third generation aromatase inhibitors in 40-70% of ER-positive tumours, rates generally significantly higher than observed with tamoxifen. Pathological responses in terms of reduced cellularity/increased fibrosis are also seen in 65-75% of cases. Whilst these are more often seen in clinically responding tumours, the correlation between clinical and pathological response is not absolute. A marked feature of treatment with third generation inhibitors is a reduction in cellular proliferation. Using Ki67 as a marker, this may be observed as early as 10-14 days into treatment. Reduction in proliferation with treatment may be seen in both clinically responding and non-responding tumours, although incidence and degree of effect are higher in responding cases. Aromatase inhibitor treatment frequently fails to reduce proliferation in tumours over-expressing HER-2. In terms of molecular events, aromatase inhibitor treatment is associated with changes in expression of genes classically associated with oestrogen regulation (KIAA0101, ZWINT, IRS1 and TFF1) and cell cycle progression, most notably mitotic phase proteins (CDC2, CCNB1 and CKS2). Changes occur both in clinically responding and non-responding tumours. Although expression of no individual gene correlates absolutely with response status, expression signatures can be produced which distinguish between responding and non-responding tumours. In terms of gene ontology, terms relating to macro-molecular biosynthesis, translation and structural components of ribosomes are significantly enriched. Finally, molecular signatures can be used to illustrate the relative homogeneity of responding tumours and the disparate nature of non-responding tumours suggesting multiple and diverse pathways associated with resistance.

Challenges in defining predictive markers for response to endocrine therapy in breast cancer

Endocrine therapy is a major treatment modality for hormone-dependent breast cancer. It has a relatively low morbidity, and there is evidence that antihormonal treatments have had a significant effect in reducing mortality for breast cancer. Despite this, resistance to endocrine therapy, either primary or acquired during treatment, occurs in the majority of patients, and is a major obstacle to optimal clinical management. There is therefore an urgent need to identify, on an individual basis, those tumors that are most likely to respond to endocrine therapy (so sparing patients with resistant tumors the needless side effects of ineffective therapy), and the mechanisms of resistance in tumors that are nonresponsive to treatment (so these can be bypassed). These needs are the focus of this review, which discusses the particular issues encountered when investigating the potential of multigene expression signatures as predictive factors for response to aromatase inhibitors, which have recently become front-line endocrine therapies for postmenopausal patients with breast cancer.

In situ aromatase expression in primary tumor is associated with estrogen receptor expression but is not predictive of response to endocrine therapy in advanced breast cancer

Background

New, third-generation aromatase inhibitors (AIs) have proven comparable or superior to the anti-estrogen tamoxifen for treatment of estrogen receptor (ER) and/or progesterone receptor (PR) positive breast cancer. AIs suppress total body and intratumoral estrogen levels. It is unclear whether in situ carcinoma cell aromatization is the primary source of estrogen production for tumor growth and whether the aromatase expression is predictive of response to endocrine therapy. Due to methodological difficulties in the determination of the aromatase protein, COX-2, an enzyme involved in the synthesis of aromatase, has been suggested as a surrogate marker for aromatase expression.

Methods

Primary tumor material was retrospectively collected from 88 patients who participated in a randomized clinical trial comparing the AI letrozole to the anti-estrogen tamoxifen for first-line treatment of advanced breast cancer. Semi-quantitative immunohistochemical (IHC) analysis was performed for ER, PR, COX-2 and aromatase using Tissue Microarrays (TMAs). Aromatase was also analyzed using whole sections (WS). Kappa analysis was applied to compare association of protein expression levels. Univariate Wilcoxon analysis and the Cox-analysis were performed to evaluate time to progression (TTP) in relation to marker expression.

Results

Aromatase expression was associated with ER, but not with PR or COX-2 expression in carcinoma cells. Measurements of aromatase in WS were not comparable to results from TMAs. Expression of COX-2 and aromatase did not predict response to endocrine therapy. Aromatase in combination with high PR expression may select letrozole treated patients with a longer TTP.

Conclusion

TMAs are not suitable for IHC analysis of in situ aromatase expression and we did not find COX-2 expression in carcinoma cells to be a surrogate marker for aromatase. In situ aromatase expression in tumor cells is associated with ER expression and may thus point towards good prognosis. Aromatase expression in cancer cells is not predictive of response to endocrine therapy, indicating that in situ estrogen synthesis may not be the major source of intratumoral estrogen. However, aromatase expression in combination with high PR expression may select letrozole treated patients with longer TTP.

Trial registration

Sub-study of trial P025 for advanced breast cancer.

Bioinformatics and breast cancer: what can high-throughput genomic approaches actually tell us?

High-throughput genomic technology has rapidly become a major tool for the study of breast cancer. Gene expression profiling has been applied to many areas of research from basic science to translational studies, with the potential to identify new targets for treatment, mechanisms of resistance and to improve on current tools for the analysis of prognosis. However, the sheer scale of the data generated along with the number of different protocols, platforms and analysis methods can make these studies difficult for clinicians to comprehend. Similarly, computational scientists and statisticians that may be called upon to analyse the data generated are often unaware of the processes involved in sample collection or the relevance and impact of genetics and pathological characteristics. There is a pressing need for better understanding of the challenges and limitations of microarray approaches, both in experimental design and data analysis. Holistic, whole-genome approaches are still relatively new and critics have been quick to highlight non-overlapping results from groups testing similar hypotheses. However, it is often subtle differences in the experimental design and technology that underpin the variation between these studies. Rather than indicating that the data are meaningless, this suggests that many findings are real, but highly context dependent. This review explores both the current state and potential of bioinformatics to bring meaning to high-throughput genomic approaches in the understanding of breast cancer.

Approaches towards expression profiling the response to treatment

Over the past 8 years there has been a wealth of breast cancer gene expression studies. The majority of these studies have focused upon characterising a tumour at presentation, before treatment, rather than looking at the effects of treatment on the tumour. More recently, a number of groups have moved from predicting prognosis based upon long-term follow-up to alternative approaches of using expression profiling to measure the effect of treatment on breast tumours and potentially predict response to therapy using either post-treatment samples or both pre-treatment and post-treatment samples. Whilst this provides great potential to further our understanding of the mode of action of treatments and to more accurately select which patients will benefit from a particular treatment, serious issues of experimental design must be considered.