ESR1 ligand-binding domain mutations in hormone-resistant breast cancer. Nat Genet. 2013;45:1439-1445. [PMID: 24185512 PMCID: PMC3903423 DOI: 10.1038/ng.2822]

Acquired resistance to selective estrogen receptor modulators (SERMs) in clinical practice (tamoxifen & raloxifene) by selection pressure in breast cancer cell populations

Tamoxifen, a pioneering selective estrogen receptor modulator (SERM), has long been a therapeutic choice for all stages of estrogen receptor (ER)-positive breast cancer. The clinical application of long-term adjuvant antihormone therapy for the breast cancer has significantly improved breast cancer survival. However, acquired resistance to SERM remains a significant challenge in breast cancer treatment. The evolution of acquired resistance to SERMs treatment was primarily discovered using MCF-7 tumors transplanted in athymic mice to mimic years of adjuvant treatment in patients. Acquired resistance to tamoxifen is unique because the growth of resistant tumors is dependent on SERMs. It appears that acquired resistance to SERM is initially able to utilize either E2 or a SERM as the growth stimulus in the SERM-resistant breast tumors. Mechanistic studies reveal that SERMs continuously suppress nuclear ER-target genes even during resistance, whereas they function as agonists to activate multiple membrane-associated molecules to promote cell growth. Laboratory observations in vivo further show that three phases of acquired SERM-resistance exists, depending on the length of SERMs exposure. Tumors with Phase I resistance are stimulated by both SERMs and estrogen. Tumors with Phase II resistance are stimulated by SERMs, but are inhibited by estrogen due to apoptosis. The laboratory models suggest a new treatment strategy, in which limited-duration, low-dose estrogen can be used to purge Phase II-resistant breast cancer cells. This discovery provides an invaluable insight into the evolution of drug resistance to SERMs, and this knowledge is now being used to justify clinical trials of estrogen therapy following long-term antihormone therapy. All of these results suggest that cell populations that have acquired resistance are in constant evolution depending upon selection pressure. The limited availability of growth stimuli in any new environment enhances population plasticity in the trial and error search for survival.

Molecular mechanisms regulating the hormone sensitivity of breast cancer

Breast cancer is a heterogeneous disease. Approximately 70% of breast cancers are estrogen receptor (ER) positive. Endocrine therapy has dramatically improved the prognosis of ER-positive breast cancer; however, many tumors exhibit de novo or acquired resistance to endocrine therapy. A thorough understanding of the molecular mechanisms regulating hormone sensitivity or resistance is important to improve the efficacy of and overcome the resistance to endocrine therapy. The growth factor receptor signaling pathways, particularly the phosphatidylinositol 3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) pathway can mediate resistance to all forms of endocrine therapy. In contrast, FOXA1 transcription factor is a key determinant of ER function and endocrine response. Intriguingly, a link between hormone resistance induced by the PI3K/Akt/mTOR pathway and the function of FOXA1 has been suggested. In this review, we focus on the PI3K/Akt/mTOR pathway and functions of FOXA1 in terms of the molecular mechanisms regulating the hormone sensitivity of breast cancer.

Pharmacogenetics of cancer drugs

The variability in treatment outcomes among patients receiving the same therapy for seemingly similar tumors can be attributed in part to genetics. The tumor's (somatic) genome largely dictates the effectiveness of the therapy, and the patient's (germline) genome influences drug exposure and the patient's sensitivity to toxicity. Many potentially clinically useful associations have been discovered between common germline genetic polymorphisms and outcomes of cancer treatment. This review highlights the germline pharmacogenetic associations that are currently being used to guide cancer treatment decisions, those that are most likely to someday be clinically useful, and associations that are well known but their roles in clinical management are not yet certain. In the future, germline genetic information will likely be available from tumor genetic analyses, creating an efficient opportunity to integrate the two genomes to optimize treatment outcomes for each individual cancer patient.

Benchmarking mutation effect prediction algorithms using functionally validated cancer-related missense mutations

BACKGROUND

Massively parallel sequencing studies have led to the identification of a large number of mutations present in a minority of cancers of a given site. Hence, methods to identify the likely pathogenic mutations that are worth exploring experimentally and clinically are required. We sought to compare the performance of 15 mutation effect prediction algorithms and their agreement. As a hypothesis-generating aim, we sought to define whether combinations of prediction algorithms would improve the functional effect predictions of specific mutations.

RESULTS

Literature and database mining of single nucleotide variants (SNVs) affecting 15 cancer genes was performed to identify mutations supported by functional evidence or hereditary disease association to be classified either as non-neutral (n = 849) or neutral (n = 140) with respect to their impact on protein function. These SNVs were employed to test the performance of 15 mutation effect prediction algorithms. The accuracy of the prediction algorithms varies considerably. Although all algorithms perform consistently well in terms of positive predictive value, their negative predictive value varies substantially. Cancer-specific mutation effect predictors display no-to-almost perfect agreement in their predictions of these SNVs, whereas the non-cancer-specific predictors showed no-to-moderate agreement. Combinations of predictors modestly improve accuracy and significantly improve negative predictive values.

CONCLUSIONS

The information provided by mutation effect predictors is not equivalent. No algorithm is able to predict sufficiently accurately SNVs that should be taken forward for experimental or clinical testing. Combining algorithms aggregates orthogonal information and may result in improvements in the negative predictive value of mutation effect predictions.

Circulating tumor cells and circulating tumor DNA for precision medicine: dream or reality?

Next-generation sequencing studies have provided further evidence to support the notion that cancer is a disease characterized by Darwinian evolution. Today, we often fail to capture this evolution and treatment decisions, even in the metastatic setting, are often based on analysis of primary tumor diagnosed years ago. Currently, this is considered a major reason for treatment failures in cancer care. Recent technological advances in the detection and characterization of circulating tumor cells and circulating tumor DNA might address this and allow for treatment tailoring based on real-time monitoring of tumor evolution. In this review, we summarize the most important recent findings in the field, focusing on challenges and opportunities in moving these tools forward in clinical practice.

Gene therapy for cancer: present status and future perspective

Advancements in human genomics over the last two decades have shown that cancer is mediated by somatic aberration in the host genome. This discovery has incited enthusiasm among cancer researchers; many now use therapeutic approaches in genetic manipulation to improve cancer regression and find a potential cure for the disease. Such gene therapy includes transferring genetic material into a host cell through viral (or bacterial) and non-viral vectors, immunomodulation of tumor cells or the host immune system, and manipulation of the tumor microenvironment, to reduce tumor vasculature or to increase tumor antigenicity for better recognition by the host immune system. Overall, modest success has been achieved with relatively minimal side effects. Previous approaches to cancer treatment, such as retrovirus integration into the host genome with the risk of mutagenesis and second malignancies, immunogenicity against the virus and/or tumor, and resistance to treatment with disease relapse, have markedly decreased with the new generation of viral and non-viral vectors. Several tumor-specific antibodies and genetically modified immune cells and vaccines have been developed, yet few are presently commercially available, while many others are still ongoing in clinical trials. It is anticipated that gene therapy will play an important role in future cancer therapy as part of a multimodality treatment, in combination with, or following other forms of cancer therapy, such as surgery, radiation and chemotherapy. The type and mode of gene therapy will be determined based on an individual's genomic constituents, as well as his or her tumor specifics, genetics, and host immune status, to design a multimodality treatment that is unique to each individual's specific needs.

Gene therapy for cancer: present status and future perspective

Advancements in human genomics over the last two decades have shown that cancer is mediated by somatic aberration in the host genome. This discovery has incited enthusiasm among cancer researchers; many now use therapeutic approaches in genetic manipulation to improve cancer regression and find a potential cure for the disease. Such gene therapy includes transferring genetic material into a host cell through viral (or bacterial) and non-viral vectors, immunomodulation of tumor cells or the host immune system, and manipulation of the tumor microenvironment, to reduce tumor vasculature or to increase tumor antigenicity for better recognition by the host immune system. Overall, modest success has been achieved with relatively minimal side effects. Previous approaches to cancer treatment, such as retrovirus integration into the host genome with the risk of mutagenesis and second malignancies, immunogenicity against the virus and/or tumor, and resistance to treatment with disease relapse, have markedly decreased with the new generation of viral and non-viral vectors. Several tumor-specific antibodies and genetically modified immune cells and vaccines have been developed, yet few are presently commercially available, while many others are still ongoing in clinical trials. It is anticipated that gene therapy will play an important role in future cancer therapy as part of a multimodality treatment, in combination with, or following other forms of cancer therapy, such as surgery, radiation and chemotherapy. The type and mode of gene therapy will be determined based on an individual's genomic constituents, as well as his or her tumor specifics, genetics, and host immune status, to design a multimodality treatment that is unique to each individual's specific needs.

Chemical biology approaches to target validation in cancer

Target validation is a crucial element of drug discovery. Especially given the wealth of potential targets emerging from cancer genome sequencing and functional genetic screens, and also considering the time and cost of downstream drug discovery efforts, it is essential to build confidence in a proposed target, ideally using different technical approaches. We argue that complementary biological and chemical biology strategies are essential for robust target validation. We discuss recent progress in the discovery and application of high quality chemical tools and other chemical biology approaches to target validation in cancer. Among other topical examples, we highlight the emergence of designed irreversible chemical tools to study potential target proteins and oncogenic pathways that were hitherto regarded as poorly druggable.

High expression of LMTK3 is an independent factor indicating a poor prognosis in estrogen receptor α-positive breast cancer patients

OBJECTIVE

Over 70% of breast cancers are estrogen receptor alpha-positive, and endocrine therapy targeting estrogen action decreases mortality from breast cancer. Recently, a novel protein kinase that regulates estrogen receptor alpha activity, lemur tyrosine kinase-3, has been identified. In this study, we investigated whether messenger RNA expression and polymorphisms of the gene encoding the kinase, LMTK3, are associated with prognosis in breast cancer patients during long-term follow-up.

METHODS

First, we investigated the relationship between messenger RNA expression of LMTK3 and patient outcome in 219 breast cancers. The effects of several variables on survival were tested by Cox proportional hazards regression analysis. Next, we performed LMTK3 genotyping in 471 breast cancers to clarify the prognostic role of these polymorphisms.

RESULTS

Our data showed that LMTK3 expression level was not associated with prognosis in all patients. We then analyzed the impact of LMTK3 mRNA expression on the prognosis of breast cancer according to estrogen receptor alpha status. Both disease-free survival and overall survival were significantly shorter in estrogen receptor alpha-positive patients with high LMTK3 expression receiving adjuvant endocrine therapy than in those patients with low LMTK3 expression. Multivariate Cox regression analysis revealed that high LMTK3 expression was an independent poor prognostic factor in estrogen receptor alpha-positive breast cancer patients. We did not find any correlation between LMTK3 genotypes and prognosis of breast cancer patients in our series.

CONCLUSIONS

Our results show that high expression of LMTK3 is an independent prognostic factor in estrogen receptor alpha-positive breast cancer patients receiving adjuvant endocrine therapy.

Aromatase inhibitors for metastatic male breast cancer: molecular, endocrine, and clinical considerations

Male breast cancer is a rare condition. Aromatase inhibitors are widely used for treating metastatic male breast cancer patients. In this setting, their use is not substantiated by prospective clinical trials, but is rather driven by similarities supposedly existing with breast cancer in postmenopausal women. This oversimplified approach was questioned by studies addressing the molecular and endocrine roots of the disease. In this manuscript, we discuss relevant aspects of the current use of aromatase inhibitors in metastatic male breast cancer in light of the most updated evidence on the molecular landscape of the disease and the specific changes in the hormonal background occurring with aging. We further point to strategies for blocking multiple hormonal pathway nodes with the goal of improving their therapeutic potential. We searched PubMed from its inception until March 2014 for relevant literature on the use of aromatase inhibitors in metastatic male breast cancer. Selected terms were combined and used both as medical headings and text words. The reference list of the suitable manuscripts was inspected for further publications. Aromatase inhibitors represent the mainstay of treatment in the metastatic setting. Yet, efforts aimed at sharpening the therapeutic potential of aromatase inhibitors still pose a challenge due to the paucity of data. The choice of dual hormonal (or sequential) therapy combining aromatase inhibitors with a GnRH analogue may represent a valid alterative, particularly if informed by cancer- and patient-related features including molecular, endocrine, and clinic characteristics.

Advancing clinical oncology through genome biology and technology

The use of genomic technologies for the molecular characterization of tumors has propelled our understanding of cancer biology and is transforming the way patients with cancer are diagnosed and treated.

Bringing androgens up a NOTCH in breast cancer

While it has been known for decades that androgen hormones influence normal breast development and breast carcinogenesis, the underlying mechanisms have only been recently elucidated. To date, most studies have focused on androgen action in breast cancer cell lines, yet these studies represent artificial systems that often do not faithfully replicate/recapitulate the cellular, molecular and hormonal environments of breast tumours in vivo. It is critical to have a better understanding of how androgens act in the normal mammary gland as well as in in vivo systems that maintain a relevant tumour microenvironment to gain insights into the role of androgens in the modulation of breast cancer development. This in turn will facilitate application of androgen-modulation therapy in breast cancer. This is particularly relevant as current clinical trials focus on inhibiting androgen action as breast cancer therapy but, depending on the steroid receptor profile of the tumour, certain individuals may be better served by selectively stimulating androgen action. Androgen receptor (AR) protein is primarily expressed by the hormone-sensing compartment of normal breast epithelium, commonly referred to as oestrogen receptor alpha (ERa (ESR1))-positive breast epithelial cells, which also express progesterone receptors (PRs) and prolactin receptors and exert powerful developmental influences on adjacent breast epithelial cells. Recent lineage-tracing studies, particularly those focussed on NOTCH signalling, and genetic analysis of cancer risk in the normal breast highlight how signalling via the hormone-sensing compartment can influence normal breast development and breast cancer susceptibility. This provides an impetus to focus on the relationship between androgens, AR and NOTCH signalling and the crosstalk between ERa and PR signalling in the hormone-sensing component of breast epithelium in order to unravel the mechanisms behind the ability of androgens to modulate breast cancer initiation and growth.

Cancer therapy. Ex vivo culture of circulating breast tumor cells for individualized testing of drug susceptibility

Circulating tumor cells (CTCs) are present at low concentrations in the peripheral blood of patients with solid tumors. It has been proposed that the isolation, ex vivo culture, and characterization of CTCs may provide an opportunity to noninvasively monitor the changing patterns of drug susceptibility in individual patients as their tumors acquire new mutations. In a proof-of-concept study, we established CTC cultures from six patients with estrogen receptor-positive breast cancer. Three of five CTC lines tested were tumorigenic in mice. Genome sequencing of the CTC lines revealed preexisting mutations in the PIK3CA gene and newly acquired mutations in the estrogen receptor gene (ESR1), PIK3CA gene, and fibroblast growth factor receptor gene (FGFR2), among others. Drug sensitivity testing of CTC lines with multiple mutations revealed potential new therapeutic targets. With optimization of CTC culture conditions, this strategy may help identify the best therapies for individual cancer patients over the course of their disease.

Investigation of estrogen receptor (ESR1) for breast cancer from traditional Chinese medicine

Recently, an important topic of breast cancer had been published in 2013. In this report, estrogen receptor (ESR1) had defined the relation of hormone-cause breast cancer. The screening of traditional Chinese medicine (TCM) database has found the molecular compounds by simulating molecular docking and molecular dynamics to regulate ESR1. S-Allylmercaptocysteine and 5-hydroxy-L-tryptophan are selected according to the highest docking score than that of other TCM compounds and Raloxifene (control). The simulation from molecular dynamics is helpful in analyzing and detecting the protein-ligand interactions. After a comparing the control and the Apo form, then based on the docking poses, hydrophobic interactions, hydrogen bond and structure variations, this research postulates that S-allylmercaptocysteine may be more appropriate than other compounds for protein-ligand interaction.

VAV3 mediates resistance to breast cancer endocrine therapy

Introduction

Endocrine therapies targeting cell proliferation and survival mediated by estrogen receptor α (ERα) are among the most effective systemic treatments for ERα-positive breast cancer. However, most tumors initially responsive to these therapies acquire resistance through mechanisms that involve ERα transcriptional regulatory plasticity. Herein we identify VAV3 as a critical component in this process.

Methods

A cell-based chemical compound screen was carried out to identify therapeutic strategies against resistance to endocrine therapy. Binding to ERα was evaluated by molecular docking analyses, an agonist fluoligand assay and short hairpin (sh)RNA–mediated protein depletion. Microarray analyses were performed to identify altered gene expression. Western blot analysis of signaling and proliferation markers, and shRNA-mediated protein depletion in viability and clonogenic assays, were performed to delineate the role of VAV3. Genetic variation in VAV3 was assessed for association with the response to tamoxifen. Immunohistochemical analyses of VAV3 were carried out to determine its association with therapeutic response and different tumor markers. An analysis of gene expression association with drug sensitivity was carried out to identify a potential therapeutic approach based on differential VAV3 expression.

Results

The compound YC-1 was found to comparatively reduce the viability of cell models of acquired resistance. This effect was probably not due to activation of its canonical target (soluble guanylyl cyclase), but instead was likely a result of binding to ERα. VAV3 was selectively reduced upon exposure to YC-1 or ERα depletion, and, accordingly, VAV3 depletion comparatively reduced the viability of cell models of acquired resistance. In the clinical scenario, germline variation in VAV3 was associated with the response to tamoxifen in Japanese breast cancer patients (rs10494071 combined P value = 8.4 × 10⁻⁴). The allele association combined with gene expression analyses indicated that low VAV3 expression predicts better clinical outcome. Conversely, high nuclear VAV3 expression in tumor cells was associated with poorer endocrine therapy response. Based on VAV3 expression levels and the response to erlotinib in cancer cell lines, targeting EGFR signaling may be a promising therapeutic strategy.

Conclusions

This study proposes VAV3 as a biomarker and a rationale for its use as a signaling target to prevent and/or overcome resistance to endocrine therapy in breast cancer.

Drug resistance to targeted therapies: déjà vu all over again

A major limitation of targeted anticancer therapies is intrinsic or acquired resistance. This review emphasizes similarities in the mechanisms of resistance to endocrine therapies in breast cancer and those seen with the new generation of targeted cancer therapeutics. Resistance to single-agent cancer therapeutics is frequently the result of reactivation of the signaling pathway, indicating that a major limitation of targeted agents lies in their inability to fully block the cancer-relevant signaling pathway. The development of mechanism-based combinations of targeted therapies together with non-invasive molecular disease monitoring is a logical way forward to delay and ultimately overcome drug resistance development.

Mathematical models of the transitions between endocrine therapy responsive and resistant states in breast cancer

Endocrine therapy, targeting the oestrogen receptor pathway, is the most common treatment for oestrogen receptor-positive breast cancers. Unfortunately, these tumours frequently develop resistance to endocrine therapies. Among the strategies to treat resistant tumours are sequential treatment (in which second-line drugs are used to gain additional responses) and intermittent treatment (in which a 'drug holiday' is imposed between treatments). To gain a more rigorous understanding of the mechanisms underlying these strategies, we present a mathematical model that captures the transitions among three different, experimentally observed, oestrogen-sensitivity phenotypes in breast cancer (sensitive, hypersensitive and independent). To provide a global view of the transitions between these phenotypes, we compute the potential landscape associated with the model. We show how this oestrogen response landscape can be reshaped by population selection, which is a crucial force in promoting acquired resistance. Techniques from statistical physics are used to create a population-level state-transition model from the cellular-level model. We then illustrate how this population-level model can be used to analyse and optimize sequential and intermittent oestrogen-deprivation protocols for breast cancer. The approach used in this study is general and can also be applied to investigate treatment strategies for other types of cancer.

Defining the conformation of the estrogen receptor complex that controls estrogen-induced apoptosis in breast cancer

Development of acquired antihormone resistance exposes a vulnerability in breast cancer: estrogen-induced apoptosis. Triphenylethylenes (TPEs), which are structurally similar to 4-hydroxytamoxifen (4OHT), were used for mechanistic studies of estrogen-induced apoptosis. These TPEs all stimulate growth in MCF-7 cells, but unlike the planar estrogens they block estrogen-induced apoptosis in the long-term estrogen-deprived MCF7:5C cells. To define the conformation of the TPE:estrogen receptor (ER) complex, we employed a previously validated assay using the induction of transforming growth factor α (TGFα) mRNA in situ in MDA-MB 231 cells stably transfected with wild-type ER (MC2) or D351G ER mutant (JM6). The assays discriminate ligand fit in the ER based on the extremes of published crystallography of planar estrogens or TPE antiestrogens. We classified the conformation of planar estrogens or angular TPE complexes as "estrogen-like" or "antiestrogen-like" complexes, respectively. The TPE:ER complexes did not readily recruit the coactivator steroid receptor coactivator-3 (SRC3) or ER to the PS2 promoter in MCF-7 and MCF7:5C cells, and molecular modeling showed that they prefer to bind to the ER in an antagonistic fashion, i.e., helix 12 not sealing the ligand binding domain (LBD) effectively, and therefore reduce critical SRC3 binding. The fully activated ER complex with helix 12 sealing the LBD is suggested to be the appropriate trigger to initiate rapid estrogen-induced apoptosis.

Estrogen receptor mutations in breast cancer--new focus on an old target

Recent studies have provided strong evidence for the emergence of substantial numbers of constitutively active ESR1 mutations in estrogen receptor-positive metastatic breast cancer that are undetected in primary disease. Some of these mutants remain partially sensitive to current anti-estrogen therapies but effective therapeutics targeted at them may require new approaches.

The emergence of targeted drugs in breast cancer to prevent resistance to endocrine treatment and chemotherapy

INTRODUCTION

Deregulated signaling pathways are associated with resistance to chemotherapy and endocrine treatment, providing a rationale for the implementation of novel targeted therapies in breast cancer therapy. Key molecules targeted therapeutically in ongoing clinical breast cancer trials are phosphoinositide 3-kinase-Akt-mammalian target of rapamycin (mTOR), Src, insulin-like growth factor 1 receptor, heat shock protein-90, histone deacetylases, cyclin-dependent kinases (CDKs), Notch and human epidermal growth factor receptors (HERs).

AREAS COVERED

This review provides an overview of novel targeted agents currently explored in clinical breast cancer trials and registered in ClinicalTrials.gov. The main focus will be on their ability to prevent or reverse endocrine resistance and chemoresistance in breast cancer.

EXPERT OPINION

HER2 targeted agents have extended survival substantially, both in the adjuvant and metastatic setting, pointing to a crucial dependency on this pathway in HER2-amplified breast cancer, including drug resistance reversal. While data on mTOR inhibitors are encouraging and preliminary results on CDK4/6 and Src inhibitors exciting, so far other targeted agents have been of limited benefit when added in concert with conventional therapies. Future clinical trials should systematically explore biomarkers and defects in functional gene cascades to identify relevant biological mechanisms to be targeted therapeutically in breast cancer.

The search for ESR1 mutations in breast cancer

Two new studies report the identification of activating ESR1 gene mutations in aromatase inhibitor-resistant metastatic breast cancers. This insight into therapeutic resistance suggests new approaches that may be useful in the management of endocrine-resistant breast cancer.

Development and validation of a gene expression score that predicts response to fulvestrant in breast cancer patients

Fulvestrant is a selective estrogen receptor antagonist. Based on the measured growth inhibition of 60 human cancer cell lines (NCI60) in the presence of fulvestrant, as well as the baseline gene expression of the 60 cell lines, a gene expression score that predicts response to fulvestrant was developed. The score is based on 414 genes, 103 of which show increased expression in sensitive cell lines, while 311 show increased expression in the non-responding cell lines. The sensitivity genes primarily sense signaling through estrogen receptor alpha, whereas the resistance genes modulate the PI3K signaling pathway. The latter genes suggest that resistance to fulvestrant can be overcome by drugs targeting the PI3K pathway. The level of this gene expression score and its correlation with fulvestrant response was measured in a panel of 20 breast cancer cell lines. The predicted sensitivity matched the measured sensitivity well (CC = -0.63, P = 0.003). The predictor was applied to tumor biopsies obtained from a Phase II clinical trial. The sensitivity of each patient to treatment with fulvestrant was predicted based on the RNA profile of the biopsy taken before neoadjuvant treatment and without knowledge of the subsequent response. The prediction was then compared to clinical response to show that the responders had a significantly higher sensitivity prediction than the non-responders (P = 0.01). When clinical covariates, tumor grade and estrogen receptor H-score, were included in the prediction, the difference in predicted senstivity between responders and non-responders improved (P = 0.003). Using a pre-defined cutoff to separate patients into predicted sensitive and predicted resistant yielded a positive predictive value of 88% and a negative predictive value of 100% when compared to clinical data. We conclude that pre-screening patients with the new gene expression predictor has the potential to identify those postmenopausal women with locally advanced, estrogen-receptor-positive breast cancer most likely to respond to fulvestrant.

Molecular tests as prognostic factors in breast cancer

In early breast cancer, prognostic tests are used to guide decisions on adjuvant systemic hormonal therapy, chemotherapy and targeted therapy treatment. This has led to large research efforts to identify novel prognostic markers in breast cancer. At present, the tissue factors used to guide treatment of breast cancer patients are tumor size, lymph node status, histologic grade, ER status, PR status, and HER2 status; in addition, multigene-expression-based prognostic tests are rapidly emerging. While identification of prognostic gene expression profiles has been successful, it has not been possible yet to identify robust clinically useful predictors of response to systemic treatment. As a result of rapid advances in technology and bioinformatics, it has become possible to analyze large series of breast carcinomas using high-throughput genetic techniques, including whole genome sequence analysis and gene expression profiling. These genomic studies will lead to the development of additional prognostic and predictive tissue-based tests. The most important aspects of the currently used tissue-based prognostic and predictive tests and the research in this area are reviewed.

Estrogen receptor (ER) α mutations in breast cancer: hidden in plain sight

The idea that somatic ERα mutations could play an important role in the evolution of hormone-dependent breast cancers was proposed some years ago (Fuqua J Mammary Gland Biol Neoplasia 6(4):407-417, 2001; Dasgupta et al. Annu Rev Med 65:279-292, 2013), but has remained controversial until recently. A significant amount of new data has confirmed these initial observations and shown their significance, along with much additional work relevant to the treatment of breast cancer. Thus, it is the purpose of this review to summarize the research to date on the existence and clinical consequences of ERα mutations in primary and metastatic breast cancer.

Emergence of constitutively active estrogen receptor-α mutations in pretreated advanced estrogen receptor-positive breast cancer

PURPOSE

We undertook this study to determine the prevalence of estrogen receptor (ER) α (ESR1) mutations throughout the natural history of hormone-dependent breast cancer and to delineate the functional roles of the most commonly detected alterations.

EXPERIMENTAL DESIGN

We studied a total of 249 tumor specimens from 208 patients. The specimens include 134 ER-positive (ER(+)/HER2(-)) and, as controls, 115 ER-negative (ER(-)) tumors. The ER(+) samples consist of 58 primary breast cancers and 76 metastatic samples. All tumors were sequenced to high unique coverage using next-generation sequencing targeting the coding sequence of the estrogen receptor and an additional 182 cancer-related genes.

RESULTS

Recurring somatic mutations in codons 537 and 538 within the ligand-binding domain of ER were detected in ER(+) metastatic disease. Overall, the frequency of these mutations was 12% [9/76; 95% confidence interval (CI), 6%-21%] in metastatic tumors and in a subgroup of patients who received an average of 7 lines of treatment the frequency was 20% (5/25; 95% CI, 7%-41%). These mutations were not detected in primary or treatment-naïve ER(+) cancer or in any stage of ER(-) disease. Functional studies in cell line models demonstrate that these mutations render estrogen receptor constitutive activity and confer partial resistance to currently available endocrine treatments.

CONCLUSIONS

In this study, we show evidence for the temporal selection of functional ESR1 mutations as potential drivers of endocrine resistance during the progression of ER(+) breast cancer.

The horizon of precision medicine in breast cancer: fragmentation, alliance, or reunification?

Genomic studies have shown that breast cancer includes a large number of targetable genomic alterations. Most of these genomic alterations are rare and can evolve during the natural history of the disease. Three paths are being followed to develop precision medicine in metastatic breast cancer. First, the conventional path will consist of fragmenting the disease and developing drugs in each rare genomic segment. This will require screening large numbers of patients for genomic alterations to run the therapeutic trials, especially the registration trials. The second path will consist in clustering rare genomic alterations in more frequent segments defined by an altered pathway. Finally, one possible path for precision medicine will be to test genomic algorithms for the whole patient population with metastatic breast cancer. This latter scenario would reunify breast cancer into a single entity and test whether the use of genomics would improve outcomes in this population of patients. Challenges and perspective in the field of precision medicine will include the prediction of resistance, the integration of immunology, and DNA repair in the genomic algorithms and the transfer of concepts to early-stage breast cancers.