Changes in expression of oestrogen regulated and proliferation genes with neoadjuvant treatment highlight heterogeneity of clinical resistance to the aromatase inhibitor, letrozole

Acetyl-CoA carboxylase 1 controls a lipid droplet-peroxisome axis and is a vulnerability of endocrine-resistant ER+ breast cancer

Targeting aromatase deprives ER+ breast cancers of estrogens and is an effective therapeutic approach for these tumors. However, drug resistance is an unmet clinical need. Lipidomic analysis of long-term estrogen-deprived (LTED) ER+ breast cancer cells, a model of aromatase inhibitor resistance, revealed enhanced intracellular lipid storage. Functional metabolic analysis showed that lipid droplets together with peroxisomes, which we showed to be enriched and active in the LTED cells, controlled redox homeostasis and conferred metabolic adaptability to the resistant tumors. This reprogramming was controlled by acetyl-CoA-carboxylase-1 (ACC1), whose targeting selectively impaired LTED survival. However, the addition of branched- and very long-chain fatty acids reverted ACC1 inhibition, a process that was mediated by peroxisome function and redox homeostasis. The therapeutic relevance of these findings was validated in aromatase inhibitor-treated patient-derived samples. Last, targeting ACC1 reduced tumor growth of resistant patient-derived xenografts, thus identifying a targetable hub to combat the acquisition of estrogen independence in ER+ breast cancers.

Multi-omics analyses unravel DNA damage repair-related clusters in breast cancer with experimental validation

Background

As one of the most common malignancies worldwide, breast cancer (BC) exhibits high heterogeneity of molecular phenotypes. The evolving view regarding DNA damage repair (DDR) is that it is context-specific and heterogeneous, but its role in BC remains unclear.

Methods

Multi-dimensional data of transcriptomics, genomics, and single-cell transcriptome profiling were obtained to characterize the DDR-related features of BC. We collected 276 DDR-related genes based on the Molecular Signature Database (MSigDB) database and previous studies. We acquired public datasets included the SCAN-B dataset (GEO: GSE96058), METABRIC database, and TCGA-BRCA database. Corresponding repositories such as transcriptomics, genomics, and clinical information were also downloaded. We selected scRNA-seq data from GEO: GSE176078, GSE114727, GSE161529, and GSE158724. Bulk RNA-seq data from GEO: GSE176078, GSE18728, GSE5462, GSE20181, and GSE130788 were extracted for independent analyses.

Results

The DDR classification was constructed in the SCAN-B dataset (GEO: GSE96058) and METABRIC database, Among BC patients, there were two clusters with distinct clinical and molecular characteristics: the DDR-suppressed cluster and the DDR-active cluster. A superior survival rate is found for tumors in the DDR-suppressed cluster, while those with the DDR-activated cluster tend to have inferior prognoses and clinically aggressive behavior. The DDR classification was validated in the TCGA-BRCA cohort and shown similar results. We also found that two clusters have different pathway activities at the genomic level. Based on the intersection of the different expressed genes among these cohorts, we found that PRAME might play a vital role in DDR. The DDR classification was then enabled by establishing a DDR score, which was verified through multilayer cohort analysis. Furthermore, our results revealed that malignant cells contributed more to the DDR score at the single-cell level than nonmalignant cells. Particularly, immune cells with immunosuppressive properties (such as FOXP3+ CD4+ T cells) displayed higher DDR scores among those with distinguishable characteristics.

Conclusion

Collectively, this study performs general analyses of DDR heterogeneity in BC and provides insight into the understanding of individualized molecular and clinicopathological mechanisms underlying unique DDR profiles.

Chromatin Organization and Transcriptional Programming of Breast Cancer Cell Identity

The advent of sequencing technologies for assessing chromosome conformations has provided a wealth of information on the organization of the 3-dimensional genome and its role in cancer progression. It is now known that changes in chromatin folding and accessibility can promote aberrant activation or repression of transcriptional programs that can drive tumorigenesis and progression in diverse cancers. This includes breast cancer, which comprises several distinct subtypes defined by their unique transcriptomes that dictate treatment response and patient outcomes. Of these, basal-like breast cancer is an aggressive subtype controlled by a pluripotency-enforcing transcriptome. Meanwhile, the more differentiated luminal subtype of breast cancer is driven by an estrogen receptor-dominated transcriptome that underlies its responsiveness to antihormone therapies and conveys improved patient outcomes. Despite the clear differences in molecular signatures, the genesis of each subtype from normal mammary epithelial cells remains unclear. Recent technical advances have revealed key distinctions in chromatin folding and organization between subtypes that could underlie their transcriptomic and, hence, phenotypic differences. These studies also suggest that proteins controlling particular chromatin states may be useful targets for treating aggressive disease. In this review, we explore the current state of understanding of chromatin architecture in breast cancer subtypes and its potential role in defining their phenotypic characteristics.

Proteomic time course of breast cancer cells highlights enhanced sensitivity to Stat3 and Src inhibitors prior to endocrine resistance development

To prevent the development of endocrine-resistant breast cancer, additional targeted therapies are increasingly being trialled in combination with endocrine therapy. The molecular mechanisms facilitating cancer cell survival during endocrine treatment remain unknown but could help direct selection of additional targeted therapies. We present a novel proteomic timecourse dataset, profiling potential drug targets in a population of MCF7 cells during 1 year of tamoxifen treatment. Reverse phase protein arrays profiled >70 proteins across 30 timepoints. A biphasic response to tamoxifen was evident, which coincided with changes in growth rate. Tamoxifen strongly impeded cell growth for the first 160 days, followed by gradual growth recovery and eventual resistance development. The growth-impeded phase was distinguished by the phosphorylation of Stat3 (y705) and Src (y527). Tumour tissue from patients treated with neo-adjuvant endocrine therapy (<4 months) also displayed increased Stat3 and Src signalling. Inhibitors of Stat3 (napabucasin) and Src (dasatinib), were effective at killing tamoxifen-treated MCF7 and T47D cells. Sensitivity to both drugs was significantly enhanced once tamoxifen had induced the growth-impeded phase. This novel proteomic resource identifies key mechanisms enabling cell survival during tamoxifen treatment. It provides valuable insight into potential drug combinations and timing that may prevent the development of endocrine resistance.

Discovering gene regulatory networks of multiple phenotypic groups using dynamic Bayesian networks

Dynamic Bayesian networks (DBNs) can be used for the discovery of gene regulatory networks (GRNs) from time series gene expression data. Here, we suggest a strategy for learning DBNs from gene expression data by employing a Bayesian approach that is scalable to large networks and is targeted at learning models with high predictive accuracy. Our framework can be used to learn DBNs for multiple groups of samples and highlight differences and similarities in their GRNs. We learn these DBN models based on different structural and parametric assumptions and select the optimal model based on the cross-validated predictive accuracy. We show in simulation studies that our approach is better equipped to prevent overfitting than techniques used in previous studies. We applied the proposed DBN-based approach to two time series transcriptomic datasets from the Gene Expression Omnibus database, each comprising data from distinct phenotypic groups of the same tissue type. In the first case, we used DBNs to characterize responders and non-responders to anti-cancer therapy. In the second case, we compared normal to tumor cells of colorectal tissue. The classification accuracy reached by the DBN-based classifier for both datasets was higher than reported previously. For the colorectal cancer dataset, our analysis suggested that GRNs for cancer and normal tissues have a lot of differences, which are most pronounced in the neighborhoods of oncogenes and known cancer tissue markers. The identified differences in gene networks of cancer and normal cells may be used for the discovery of targeted therapies.

Correlation between CA12 and TFF3 and their prediction value of neoadjuvant chemotherapy response in breast cancer

WHAT IS KNOWN AND OBJECTIVE

Compared with other molecular subtypes, hormone receptor-positive breast cancer often shows worse neoadjuvant chemotherapy efficacy. This study aims to explore the relationship between the oestrogen receptor (ER)-related genes carbonic anhydrase 12 (CA12) and trefoil factor 3 (TFF3) and their predictive value of neoadjuvant chemotherapy for breast cancer.

METHODS

We investigated the relationships between CA12, TFF3 and ER status and their predictive value of anthracycline-taxane neoadjuvant chemotherapy in 115 female breast cancer patients via real-time polymerase chain reaction (RT-PCR) and 4 GEO datasets: GSE41998, GSE25065, GSE20194 and GSE20271. Then, the effects of CA12 and TFF3 on the chemotherapy drugs doxorubicin and docetaxel were verified in vitro in the breast cancer cell lines MCF-7 and BT474.

RESULTS AND DISCUSSION

The GEO datasets and RT-PCR results showed that the relative expression of both CA12 and TFF3 was higher in oestrogen receptor-positive samples compared with the other samples (p < 0.05). CA12 was significantly correlated with TFF3 (p < 0.05). In MCF-7 cells, inhibition of TFF3 induced downregulation of CA12 and ESR1 (p < 0.05) at both the mRNA and the protein levels, while inhibition of CA12 also downregulated TFF3 and ESR1 (p < 0.05). In BT474 cells, inhibition of TFF3 downregulated CA12 and ESR1 (p < 0.05) at both the mRNA and the protein levels, while inhibition of CA12 led to slight upregulation of TFF3 and ESR1 (p > 0.05). Moreover, GEO datasets and RT-PCR results showed that CA12 and TFF3 were more highly expressed in nonpathological complete response (non-pCR) samples than in pCR samples (p < 0.05). Cell viability assays of MCF-7 and BT474 cells showed that inhibiting CA12 and TFF3 could enhance sensitivity to doxorubicin and docetaxel (p < 0.05).

WHAT IS NEW AND CONCLUSION

CA12 and TFF3 were correlated with each other, and their high expression might explain the worse efficacy of neoadjuvant chemotherapy in oestrogen receptor-positive breast cancer patients.

Suppressed estrogen supply via extra-ovarian progesterone receptor membrane component 1 in menopause

In post-menopausal women, intra-mammary estrogen, which is converted from extra-ovarian estrone (E1), promotes the growth of breast cancer. Since the aromatase inhibitor letrozole does not suppress 17β-estradiol (E2) production from E1, high intra-mammary E1 concentrations impair letrozole's therapeutic efficacy. Progesterone receptor membrane component 1 (Pgrmc1) is a non-classical progesterone receptor associated with breast cancer progression. In the present study, we introduced a Pgrmc1 heterozygous knockout (hetero KO) murine model exhibiting low Pgrmc1 expression, and observed estrogen levels and steroidogenic gene expression. Naïve Pgrmc1 hetero KO mice exhibited low estrogen (E2 and E1) levels and low progesterone receptor (PR) expression, compared to wild-type mice. In contrast, Pgrmc1 hetero KO mice that have been ovariectomized (OVX), including letrozole-treated OVX mice (OVX-letrozole), exhibited high estrogen levels and PR expression. Increased extra-ovarian estrogen production in Pgrmc1 hetero KO mice was observed with the induction of steroid sulfatase (STS). In MCF-7 cell, letrozole suppressed PR expression, but PGRMC1 knockdown increased PR and STS expression. Our presented results highlight the important role of Pgrmc1 in modulating estrogen production when ovary-derived estrogen is limited, thereby suggesting a potential therapeutic approach for letrozole resistance.

Degree of Early Estrogen Response Predict Survival after Endocrine Therapy in Primary and Metastatic ER-Positive Breast Cancer

Simple Summary

Over 70% of breast cancer patients in the US have estrogen receptor (ER)-positive tumors. A better predictive biomarker of endocrine therapy would be useful to improve patient compliance. We found that estrogen response early score generated by a GSEA algorithm was significantly associated with immune cell infiltrations, patient survival, and endocrine therapy response in ER-positive breast cancer. Furthermore, the score may be a useful tool to predict response to endocrine therapy in both primary and metastatic breast cancer compared to ER gene expression. This study demonstrates that the estrogen response early score may be a useful prognostic and predicative biomarker in patients with either primary or metastatic breast cancer.

Abstract

Endocrine therapy is the gold-standard treatment for ER-positive/HER2-negative breast cancer. Although its clear benefit, patient compliance is poor (50–80%) due to its long administration period and adverse effects. Therefore, a predictive biomarker that can predict whether endocrine therapy is truly beneficial may improve patient compliance. In this study, we use estrogen response early gene sets of gene set enrichment assay algorithm as the score. We hypothesize that the score could predict the response to endocrine therapy and survival of breast cancer patients. A total of 6549 breast cancer from multiple patient cohorts were analyzed. The score was highest in ER-positive/HER2-negative compared to the other subtypes. Earlier AJCC stage, as well as lower Nottingham pathological grade, were associated with a high score. Low score tumors enriched only allograft rejection gene set, and was significantly infiltrated with immune cells, and high cytolytic activity score. A low score was significantly associated with a worse response to endocrine therapy and worse survival in both primary and metastatic breast cancer patients. The hazard ratio was double that of ESR1 expression. In conclusion, the estrogen response early score predicts response to endocrine therapy and is associated with survival in primary and metastatic breast cancer.

Cancer gene expression profiles associated with clinical outcomes to chemotherapy treatments

Background

Machine learning (ML) methods still have limited applicability in personalized oncology due to low numbers of available clinically annotated molecular profiles. This doesn’t allow sufficient training of ML classifiers that could be used for improving molecular diagnostics.

Methods

We reviewed published datasets of high throughput gene expression profiles corresponding to cancer patients with known responses on chemotherapy treatments. We browsed Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and Tumor Alterations Relevant for GEnomics-driven Therapy (TARGET) repositories.

Results

We identified data collections suitable to build ML models for predicting responses on certain chemotherapeutic schemes. We identified 26 datasets, ranging from 41 till 508 cases per dataset. All the datasets identified were checked for ML applicability and robustness with leave-one-out cross validation. Twenty-three datasets were found suitable for using ML that had balanced numbers of treatment responder and non-responder cases.

Conclusions

We collected a database of gene expression profiles associated with clinical responses on chemotherapy for 2786 individual cancer cases. Among them seven datasets included RNA sequencing data (for 645 cases) and the others – microarray expression profiles. The cases represented breast cancer, lung cancer, low-grade glioma, endothelial carcinoma, multiple myeloma, adult leukemia, pediatric leukemia and kidney tumors. Chemotherapeutics included taxanes, bortezomib, vincristine, trastuzumab, letrozole, tipifarnib, temozolomide, busulfan and cyclophosphamide.

Revisiting the Concept of Stress in the Prognosis of Solid Tumors: A Role for Stress Granules Proteins?

Simple Summary

Stress Granules (SGs) were discovered in 1999 and while the first decade of research has focused on some fundamental questions, the field is now investigating their role in human pathogenesis. Since then, evidences of a link between SGs and cancerology are accumulating in vitro and in vivo. In this work we summarized the role of SGs proteins in cancer development and their prognostic values. We find that level of expression of protein involved in SGs formation (and not mRNA level) could serve a prognostic marker in cancer. With this review we strongly suggest that SGs (proteins) could be targets of choice to block cancer development and counteract resistance to improve patients care.

Abstract

Cancer treatments are constantly evolving with new approaches to improve patient outcomes. Despite progresses, too many patients remain refractory to treatment due to either the development of resistance to therapeutic drugs and/or metastasis occurrence. Growing evidence suggests that these two barriers are due to transient survival mechanisms that are similar to those observed during stress response. We review the literature and current available open databases to study the potential role of stress response and, most particularly, the involvement of Stress Granules (proteins) in cancer. We propose that Stress Granule proteins may have prognostic value for patients.

Association of Sperm-Associated Antigen 5 and Treatment Response in Patients With Estrogen Receptor-Positive Breast Cancer

Importance

There is no proven test that can guide the optimal treatment, either endocrine therapy or chemotherapy, for estrogen receptor-positive breast cancer.

Objective

To investigate the associations of sperm-associated antigen 5 (SPAG5) transcript and SPAG5 protein expressions with treatment response in systemic therapy for estrogen receptor-positive breast cancer.

Design, Settings, and Participants

This retrospective cohort study included patients with estrogen receptor-positive breast cancer who received 5 years of adjuvant endocrine therapy with or without neoadjuvant anthracycline-based combination chemotherapy (NACT) derived from 11 cohorts from December 1, 1986, to November 28, 2019. The associations of SPAG5 transcript and SPAG5 protein expression with pathological complete response to NACT were evaluated, as was the association of SPAG5 mRNA expression with response to neoadjuvant endocrine therapy. The associations of distal relapse-free survival with SPAG5 transcript or SPAG5 protein expressions were analyzed. Data were analyzed from September 9, 2015, to November 28, 2019.

Main Outcomes and Measures

The primary outcomes were breast cancer-specific survival, distal relapse-free survival, pathological complete response, and clinical response. Outcomes were examined using Kaplan-Meier, multivariable logistic, and Cox regression models.

Results

This study included 12 720 women aged 24 to 78 years (mean [SD] age, 58.46 [12.45] years) with estrogen receptor-positive breast cancer, including 1073 women with SPAG5 transcript expression and 361 women with SPAG5 protein expression of locally advanced disease stage IIA through IIIC. Women with SPAG5 transcript and SPAG5 protein expressions achieved higher pathological complete response compared with those without SPAG5 transcript or SPAG5 protein expressions (transcript: odds ratio, 2.45 [95% CI, 1.71-3.51]; P < .001; protein: odds ratio, 7.32 [95% CI, 3.33-16.22]; P < .001). Adding adjuvant anthracycline chemotherapy to adjuvant endocrine therapy for SPAG5 mRNA expression in estrogen receptor-positive breast cancer was associated with prolonged 5-year distal relapse-free survival in patients without lymph node involvement (hazard ratio, 0.34 [95% CI, 0.14-0.87]; P = .03) and patients with lymph node involvement (hazard ratio, 0.35 [95% CI, 0.18-0.68]; P = .002) compared with receiving 5-year endocrine therapy alone. Mean (SD) SPAG5 transcript was found to be downregulated after 2 weeks of neoadjuvant endocrine therapy compared with pretreatment levels in 68 of 92 patients (74%) (0.23 [0.18] vs 0.34 [0.24]; P < .001).

Conclusions and Relevance

These findings suggest that SPAG5 transcript and SPAG5 protein expressions could be used to guide the optimal therapies for estrogen receptor-positive breast cancer. Retrospective and prospective clinical trials are warranted.

The therapeutic response of ER+/HER2- breast cancers differs according to the molecular Basal or Luminal subtype

The genomics-based molecular classifications aim at identifying more homogeneous classes than immunohistochemistry, associated with a more uniform clinical outcome. We conducted an in silico analysis on a meta-dataset including gene expression data from 5342 clinically defined ER+/HER2- breast cancers (BC) and DNA copy number/mutational and proteomic data. We show that the Basal (16%) versus Luminal (74%) subtypes as defined using the 80-gene signature differ in terms of response/vulnerability to systemic therapies of BC. The Basal subtype is associated with better chemosensitivity, lesser benefit from adjuvant hormone therapy, and likely better sensitivity to PARP inhibitors, platinum salts and immune therapy, and other targeted therapies under development such as FGFR inhibitors. The Luminal subtype displays potential better sensitivity to CDK4/6 inhibitors and vulnerability to targeted therapies such as PIK3CA, AR and Bcl-2 inhibitors. Expression profiles are very different, showing an intermediate position of the ER+/HER2- Basal subtype between the ER+/HER2- Luminal and ER- Basal subtypes, and let suggest a different cell-of-origin. Our data suggest that the ER+/HER2- Basal and Luminal subtypes should not be assimilated and treated as a homogeneous group.

Flexible Data Trimming Improves Performance of Global Machine Learning Methods in Omics-Based Personalized Oncology

(1) Background: Machine learning (ML) methods are rarely used for an omics-based prescription of cancer drugs, due to shortage of case histories with clinical outcome supplemented by high-throughput molecular data. This causes overtraining and high vulnerability of most ML methods. Recently, we proposed a hybrid global-local approach to ML termed floating window projective separator (FloWPS) that avoids extrapolation in the feature space. Its core property is data trimming, i.e., sample-specific removal of irrelevant features. (2) Methods: Here, we applied FloWPS to seven popular ML methods, including linear SVM, k nearest neighbors (kNN), random forest (RF), Tikhonov (ridge) regression (RR), binomial naïve Bayes (BNB), adaptive boosting (ADA) and multi-layer perceptron (MLP). (3) Results: We performed computational experiments for 21 high throughput gene expression datasets (41–235 samples per dataset) totally representing 1778 cancer patients with known responses on chemotherapy treatments. FloWPS essentially improved the classifier quality for all global ML methods (SVM, RF, BNB, ADA, MLP), where the area under the receiver-operator curve (ROC AUC) for the treatment response classifiers increased from 0.61–0.88 range to 0.70–0.94. We tested FloWPS-empowered methods for overtraining by interrogating the importance of different features for different ML methods in the same model datasets. (4) Conclusions: We showed that FloWPS increases the correlation of feature importance between the different ML methods, which indicates its robustness to overtraining. For all the datasets tested, the best performance of FloWPS data trimming was observed for the BNB method, which can be valuable for further building of ML classifiers in personalized oncology.

Molecular changes during extended neoadjuvant letrozole treatment of breast cancer: distinguishing acquired resistance from dormant tumours

BACKGROUND

The risk of recurrence for endocrine-treated breast cancer patients persists for many years or even decades following surgery and apparently successful adjuvant therapy. This period of dormancy and acquired resistance is inherently difficult to investigate; previous efforts have been limited to in-vitro or in-vivo approaches. In this study, sequential tumour samples from patients receiving extended neoadjuvant aromatase inhibitor therapy were characterised as a novel clinical model.

METHODS

Consecutive tumour samples from 62 patients undergoing extended (4-45 months) neoadjuvant aromatase inhibitor therapy with letrozole were subjected to transcriptomic and proteomic analysis, representing before (≤ 0), early (13-120 days), and long-term (> 120 days) neoadjuvant aromatase inhibitor therapy with letrozole. Patients with at least a 40% initial reduction in tumour size by 4 months of treatment were included. Of these, 42 patients with no subsequent progression were classified as "dormant", and the remaining 20 patients as "acquired resistant".

RESULTS

Changes in gene expression in dormant tumours begin early and become more pronounced at later time points. Therapy-induced changes in resistant tumours were common features of treatment, rather than being specific to the resistant phenotype. Comparative analysis of long-term treated dormant and resistant tumours highlighted changes in epigenetics pathways including DNA methylation and histone acetylation. The DNA methylation marks 5-methylcytosine and 5-hydroxymethylcytosine were significantly reduced in resistant tumours compared with dormant tissues after extended letrozole treatment.

CONCLUSIONS

This is the first patient-matched gene expression study investigating long-term aromatase inhibitor-induced dormancy and acquired resistance in breast cancer. Dormant tumours continue to change during treatment whereas acquired resistant tumours more closely resemble their diagnostic samples. Global loss of DNA methylation was observed in resistant tumours under extended treatment. Epigenetic alterations may lead to escape from dormancy and drive acquired resistance in a subset of patients, supporting a potential role for therapy targeted at these epigenetic alterations in the management of resistance to oestrogen deprivation therapy.

Key regulators of lipid metabolism drive endocrine resistance in invasive lobular breast cancer

Background

Invasive lobular breast carcinoma (ILC) is a histological subtype of breast cancer that is characterized by loss of E-cadherin and high expression of estrogen receptor alpha (ERα). In many cases, ILC is effectively treated with adjuvant aromatase inhibitors (AIs); however, acquired AI resistance remains a significant problem.

Methods

To identify underlying mechanisms of acquired anti-estrogen resistance in ILC, we recently developed six long-term estrogen-deprived (LTED) variant cell lines from the human ILC cell lines SUM44PE (SUM44; two lines) and MDA-MB-134VI (MM134; four lines). To better understand mechanisms of AI resistance in these models, we performed transcriptional profiling analysis by RNA-sequencing followed by candidate gene expression and functional studies.

Results

MM134 LTED cells expressed ER at a decreased level and lost growth response to estradiol, while SUM44 LTED cells retained partial ER activity. Our transcriptional profiling analysis identified shared activation of lipid metabolism across all six independent models. However, the underlying basis of this signature was distinct between models. Oxysterols were able to promote the proliferation of SUM44 LTED cells but not MM134 LTED cells. In contrast, MM134 LTED cells displayed a high expression of the sterol regulatory element-binding protein 1 (SREBP1), a regulator of fatty acid and cholesterol synthesis, and were hypersensitive to genetic or pharmacological inhibition of SREBPs. Several SREBP1 downstream targets involved in fatty acid synthesis, including FASN, were induced, and MM134 LTED cells were more sensitive to etomoxir, an inhibitor of the rate-limiting enzyme in beta-oxidation, than their respective parental control cells. Finally, in silico expression analysis in clinical specimens from a neo-adjuvant endocrine trial showed a significant association between the increase of SREBP1 expression and lack of clinical response, providing further support for a role of SREBP1 in the acquisition of endocrine resistance in breast cancer.

Conclusions

Our characterization of a unique series of AI-resistant ILC models identifies the activation of key regulators of fatty acid and cholesterol metabolism, implicating lipid-metabolic processes driving estrogen-independent growth of ILC cells. Targeting these changes may prove a strategy for prevention and treatment of endocrine resistance for patients with ILC.

Electronic supplementary material

The online version of this article (10.1186/s13058-018-1041-8) contains supplementary material, which is available to authorized users.

Predictive markers of endocrine response in breast cancer

Ongoing clinical and research efforts seek to optimise the use of endocrine therapy in the treatment of breast cancer. Accurate biomarkers are needed that predict response for individual patients. The presence of the estrogen receptor (ER) as the direct (for tamoxifen and fulvestrant) or indirect (for aromatase inhibitors) target molecule for endocrine therapy remains the foremost biomarker and determinant of response. However, ER expression only poorly predicts outcome and further indicators of response or resistance are required. The development and application of molecular signature assays such as Oncotype Dx, Prosigna, Mammaprint and Endopredict have provided valuable information on prognosis and these are being used to support clinical decision making on whether endocrine therapy alone alongside surgery is sufficient for ER-positive early stage breast cancers or whether combination of endocrine with chemotherapy are also warranted. Ki67, the proliferation marker, has been widely used in the neo-adjuvant (pre-operative) setting to help predict response and long term outcome. Gene expression studies within the same setting have allowed monitoring of changes of potential predictive markers. These have identified frequent changes in estrogen-regulated and proliferation genes. Specific molecules such as mutant ER may also prove helpful biomarkers in predicting outcome and monitoring response to treatment.

Therapeutic predictors of neoadjuvant endocrine therapy response in estrogen receptor-positive breast cancer with reference to optimal gene expression profiling

PURPOSE

Neoadjuvant endocrine therapy (NAET) for estrogen receptor-positive primary breast cancer causes adequate tumor shrinkage, and is expected to be helpful for breast-conserving surgery, but the adaptation criteria, especially in regard to treatment duration, have never been elucidated. Re-visiting past gene expression profiles, we explored the data for specialized pre-therapeutic predictors and validated the results using our in-house clinical cohorts.

METHODS

We sorted the genes related to a > 30% tumor volume reduction through NAET from a cDNA microarray data-set of GSE20181, then selected the top 40 genes. We validated these gene expression levels using pre-therapeutic biopsy samples obtained from patients treated with long-term NAET (over 4 months; N = 40). A short-term (2-8 weeks; N = 37) NAET cohort was also validated to clarify whether expression of these genes is also related to a rapid response of Ki67 and PEPI score.

RESULTS

In the long-term group, higher expression of KRAS, CUL2, FAM13A, ADCK2, and LILRA2 was significantly associated with tumor shrinkage, and KRAS, MMS19, and IVD were related to lower PEPI score (≤ 3). Meanwhile in the short-term group, none of these genes except CUL2 showed a direct correlation with Ki67 reduction or PEPI score. This suggested that tumor shrinkage by NAET might be induced by response to the hypoxic environment (CUL2, FAM13A, KRAS) and activation of tumor immune system (LILRA2), without involving inhibition of proliferation.

CONCLUSION

Expression of specific genes may allow selection of the most responsive patients for maximum tumor shrinkage with NAET.

BCMA (TNFRSF17) Induces APRIL and BAFF Mediated Breast Cancer Cell Stemness

Recent advances in cancer immunology revealed immune-related properties of cancer cells as novel promising therapeutic targets. The two TNF superfamily members, APRIL (TNFSF13), and BAFF (TNFSF13B), which are type II membrane proteins, released in active forms by proteolytic cleavage and are primarily involved in B-lymphocyte maturation, have also been associated with tumor growth and aggressiveness in several solid tumors, including breast cancer. In the present work we studied the effect of APRIL and BAFF on epithelial to mesenchymal transition, migration, and stemness of breast cancer cells. Our findings show that both molecules increase epithelial to mesenchymal transition and migratory capacity of breast cancer cells, as well as cancer stem cell numbers, by increasing the expression of pluripotency genes such as ALDH1A1, KLF4, and NANOG. These effects are mediated by their common receptor BCMA (TNFRSF17) and the JNK signaling pathway. Interestingly, transcriptional data analysis from breast cancer cells and patients revealed that androgens can increase APRIL transcription and subsequently, in an autocrine/paracrine manner, enhance its pluripotency effect. In conclusion, our data suggest a possible role of APRIL and BAFF in breast cancer disease progression and provide evidence for a new possible mechanism of therapy resistance, that could be particularly relevant in aromatase inhibitors-treated patients, were local androgen is increased.

FGFR1 underlies obesity-associated progression of estrogen receptor-positive breast cancer after estrogen deprivation

Obesity increases breast cancer mortality by promoting resistance to therapy. Here, we identified regulatory pathways in estrogen receptor-positive (ER-positive) tumors that were shared between patients with obesity and those with resistance to neoadjuvant aromatase inhibition. Among these was fibroblast growth factor receptor 1 (FGFR1), a known mediator of endocrine therapy resistance. In a preclinical model with patient-derived ER-positive tumors, diet-induced obesity promoted a similar gene expression signature and sustained the growth of FGFR1-overexpressing tumors after estrogen deprivation. Tumor FGFR1 phosphorylation was elevated with obesity and predicted a shorter disease-free and disease-specific survival for patients treated with tamoxifen. In both human and mouse mammary adipose tissue, FGF1 ligand expression was associated with metabolic dysfunction, weight gain, and adipocyte hypertrophy, implicating the impaired response to a positive energy balance in growth factor production within the tumor niche. In conjunction with these studies, we describe a potentially novel graft-competent model that can be used with patient-derived tissue to elucidate factors specific to extrinsic (host) and intrinsic (tumor) tissue that are critical for obesity-associated tumor promotion. Taken together, we demonstrate that obesity and excess energy establish a tumor environment with features of endocrine therapy resistance and identify a role for ligand-dependent FGFR1 signaling in obesity-associated breast cancer progression.

Neoadjuvant Therapy for Breast Cancer: Established Concepts and Emerging Strategies

In the last decade, the systemic treatment approach for patients with early breast cancer has partly shifted from adjuvant treatment to neoadjuvant treatment. Systemic treatment administration started as a 'one size fits all' approach but is currently customized according to each breast cancer subtype. Systemic treatment in a neoadjuvant setting is at least as effective as in an adjuvant setting and has several additional advantages. First, it enables response monitoring and provides prognostic information; second, it downstages the tumor, allowing for less extensive surgery, improved cosmetic outcomes, and reduced postoperative complications such as lymphedema; and third, it enables early development of new treatment strategies by using pathological complete remission as a surrogate outcome of event-free and overall survival. In this review we give an overview of the current standard of neoadjuvant systemic treatment strategies for the three main subtypes of breast cancer: hormone receptor-positive, triple-negative, and human epidermal growth factor receptor 2-positive. Additionally, we summarize drugs that are under investigation for use in the neoadjuvant setting.

Curated compendium of human transcriptional biomarker data

One important use of genome-wide transcriptional profiles is to identify relationships between transcription levels and patient outcomes. These translational insights can guide the development of biomarkers for clinical application. Data from thousands of translational-biomarker studies have been deposited in public repositories, enabling reuse. However, data-reuse efforts require considerable time and expertise because transcriptional data are generated using heterogeneous profiling technologies, preprocessed using diverse normalization procedures, and annotated in non-standard ways. To address this problem, we curated 45 publicly available, translational-biomarker datasets from a variety of human diseases. To increase the data's utility, we reprocessed the raw expression data using a uniform computational pipeline, addressed quality-control problems, mapped the clinical annotations to a controlled vocabulary, and prepared consistently structured, analysis-ready data files. These data, along with scripts we used to prepare the data, are available in a public repository. We believe these data will be particularly useful to researchers seeking to perform benchmarking studies—for example, to compare and optimize machine-learning algorithms' ability to predict biomedical outcomes.

Immunohistochemical Ki67 after short-term hormone therapy identifies low-risk breast cancers as reliably as genomic markers

Background

The purpose of this study was to test whether immunohistochemical (IHC) Ki67 levels after short-term preoperative hormone therapy (post-Ki67) predict similar numbers of patients with favorable prognoses as genomic markers.

Results

Thirty paired cases (60 samples) were enrolled in this study. Post-Ki67 levels were significantly lower than pre-treatment Ki67 levels (P < 0.001). Post-Ki67 predicted more low-risk cases (83.3%, 25/30) than pre-genomic surrogate signature(GSS) (66.7%: 20/30), but the difference in predictive power was not significant (P = 0.233). Proliferation (MKI67, STK15, Survivin, CCNB1, and MYBL2) and estrogen (ER, PGR, BCL2, and SCUBE2) related signatures were significantly downregulated after therapy (P < 0.001 and 0.041, respectively).

Materials and Methods

Core needle biopsy specimens of primary breast cancer were collected at Okayama University Hospital from hormone receptor-positive and human epidermal growth factor 2-negative patients that subsequently received two weeks of neoadjuvant hormone therapy. Paired post-treatment specimens from surgical samples were also collected. IHC Ki67 levels and GSS were compared between pre- and post-hormone treatment samples. Changes of gene expression pattern in short-term hormone therapy were also assessed.

Conclusions

IHC based post-Ki67 levels may have distinct predictive power compared with the naïve IHC Ki67. Future studies with larger cohorts and longer follow-up periods may be needed to validate our results.

Molecular changes in premenopausal oestrogen receptor-positive primary breast cancer in Vietnamese women after oophorectomy

For premenopausal women with primary ER + breast cancer, oophorectomy (OvX) is an evidence-based cost-effective option and is standard treatment in many countries. However, there is virtually no data describing the effects of OvX on breast tumour biology. We therefore, characterised the endocrine and genome-wide transcriptional impact of OvX in 56 premenopausal women with ER + breast cancer for 2 weeks prior to mastectomy. Plasma estradiol concentrations decreased from 406 ± 41 to 20.7 ± 2.6 pmol/l (mean ± sem) 24 h after OvX, and to 8.1 ± 0.8 pmol/l 2 weeks later at mastectomy. Ki67 decreased in 33/36 (91.7%) tumours. The expression of 655 genes changed significantly (FDR < 1%) with an absolute mean fold-change (FC) ≥ 1.25 (257 up, 398 down). Archetypal oestrogen-regulated genes (TFF1, GREB1, PGR and PDZK1) showed large decreases in expression (FC = 0.20–0.69; p < 1e-6-1e-7). Proliferation-associated genes (e.g. TOP2A, AURKA and UBE2C) were also strongly downregulated (FC = 0.38–0.56; p < 1e-7) along with putative progesterone-regulated genes (e.g. FKBP4, MYB; FC = 0.64–0.68; p < 1e-4-1e-7). The gene expression changes did not differ according to HER2 status and correlated strongly with the changes reported previously after aromatase inhibitor (AI) treatment in postmenopausal women (rho = 0.55, p < 1e-04). However, after OvX the mean FC was significantly higher compared to AI (p < 1e-04). In conclusion, changes in tumoural gene expression after OvX were largely similar, but of a greater magnitude to those observed after AI in postmenopausal patients; however, OvX appeared to have a greater effect on progesterone-regulated genes than AI.

Surgical removal of the ovaries alters the expression of hundreds of genes in the tumour cells of premenopausal women with breast cancer. Ben Haynes from Royal Marsden Hospital in London, UK and colleagues characterised molecular changes in 56 premenopausal women from Vietnam with oestrogen receptor-positive breast cancer who underwent oophorectomies, a standard treatment for this patient population. They showed that blood levels of the hormone estradiol dropped precipitously following ovary-removal surgery. Levels of a protein that was indicative of tumour growth also went down, as did genes involved in regulating hormone signalling and cell proliferation. The results are consistent with those seen in postmenopausal women following treatment with an oestrogen-blocking drug, but oophorectomy had a more dramatic effect. The data could aid the search for predictive biomarkers of who stands to benefit most from ovary removal.

Neoadjuvant endocrine therapy in breast cancer patients

Highlights

The overall response rate to neoadjuvant endocrine therapy (NET) was 54.55%.The eight patients proposed to tumour's downstage, after 9.71 months of NET, preserved their breast.In the group which achieved response, 10.28 months was the mean time to accomplish it.Even patients who had the worst outcome only began to suffer latter in the course of therapy.NET can be done beyond the conventional 3-4 months to allow additional downstage of the tumour.

Background

The aim of this study is to evaluate if the extension of neoadjuvant endocrine therapy (NET), beyond the conventional time, allows additional downstage of the tumour, in order to perform a breast conservative surgery (BCS), and to analyze if it is a good option for long-term control in patients who refuse or are unfit for surgery.

Patients and methods

We retrospectively reviewed a database containing all patients treated in our institution with NET. All included patients were post-menopausal with primary local disease. The type of response obtained was assessed using modified RECIST criteria.

Results

Thirty-three patients were included. Two patients had tumours with 90% expression of oestrogen receptors and all the others had 100%. The tumour size in the largest diameter was 6.51 cm before treatment and 5.18 cm after. Eighteen patients achieved a partial response after 10.28 months of therapy. Patients that were proposed to downstage the tumour performed 9.71 months of therapy until surgery and all were submitted to BCS. Progression occurred after 27.5 months.

Conclusion

Endocrine therapy is a feasible option for a longer time to allow additional downstage of the tumour and is a good solution in patients who refuse or are unfit for surgery.

A preliminary study of 18F-FES PET/CT in predicting metastatic breast cancer in patients receiving docetaxel or fulvestrant with docetaxel

The present explorative study was initiated to evaluate the clinical value of ¹⁸F-FES PET/CT in monitoring the change of estrogen receptor (ER) expression and potential predictive value in metastatic breast cancer patients. Twenty-two pathology-confirmed breast cancer patients were prospectively enrolled and randomly divided into two groups (T: docetaxel, n = 14 and TF: docetaxel + fulvestrant, n = 8). The percentage of patients without disease progression after 12 months (PFS > 12 months) was 62.5% in group TF compared with 21.4% in group T (P = 0.08). According to ¹⁸F-FES PET/CT scans, the SUVmax (maximum standard uptake value) of all the metastatic lesions decreased in group TF after 2 cycles of treatment (6 weeks ± 3 days). However, 6 of 9 patients in group T had at least one lesion with higher post-treatment SUVmax. There was a significant difference in the reduction of ER expression between these two groups (P = 0.028). In group TF, the patients with PFS > 12 months had significantly greater SUVmax changes of ¹⁸F-FES than those with PFS < 12 months (PFS > 12 months: 91.0 ± 12.0% versus PFS < 12 months: 20.7 ± 16.2%; t = −4.64, P = 0.01). Our preliminary study showed that ¹⁸F-FES PET/CT, as a noninvasive method to monitor ER expression, could be utilized to predict prognosis based on changes in SUVmax.

Serum TFF1 and TFF3 but not TFF2 are higher in women with breast cancer than in women without breast cancer

Breast cancer remains a common malignancy in women, but the take-up for breast cancer screening programs in Japan is still low, possibly due to its perceived inconvenience. TFF1 and TFF3 are expressed in both breast cancer tissue and normal breast. Serum trefoil proteins were reported as cancer screening markers for gastric, prostate, lung, pancreatic cancer and cholangio carcinoma. The purpose of this study was to examine whether serum trefoil proteins could be screening biomarkers for breast cancer. Serum trefoil proteins in 94 breast cancer patients and 84 health check females were measured by ELISA. Serum TFF1 and TFF3 were significantly higher and serum TFF2 was significantly lower in breast cancer patients. Area under the curve of receiver operating characteristic of TFF1, TFF2, and TFF3 was 0.69, 0.83, and. 0.72, respectively. AUC of the combination of TFF1, TFF2, and TFF3 was 0.96. Immunohistochemically, TFF1 expression was positive in 56.5% and TFF3 was positive in 73.9% of breast cancers, while TFF2 was negative in all tumors. Serum TFF1 had positive correlation with expression of TFF1 in breast cancer tissue. Serum concentrations of TFF1 and TFF3 but not TFF2 are higher in women with breast cancer than in women without breast cancer.

EGR1 regulates cellular metabolism and survival in endocrine resistant breast cancer

About 70% of all breast cancers are estrogen receptor alpha positive (ER+; ESR1). Many are treated with antiestrogens. Unfortunately, de novo and acquired resistance to antiestrogens is common but the underlying mechanisms remain unclear. Since growth of cancer cells is dependent on adequate energy and metabolites, the metabolomic profile of endocrine resistant breast cancers likely contains features that are deterministic of cell fate. Thus, we integrated data from metabolomic and transcriptomic analyses of ER+ MCF7-derived breast cancer cells that are antiestrogen sensitive (LCC1) or resistant (LCC9) that resulted in a gene-metabolite network associated with EGR1 (early growth response 1). In human ER+ breast tumors treated with endocrine therapy, higher EGR1 expression was associated with a more favorable prognosis. Mechanistic studies showed that knockdown of EGR1 inhibited cell growth in both cells and EGR1 overexpression did not affect antiestrogen sensitivity. Comparing metabolite profiles in LCC9 cells following perturbation of EGR1 showed interruption of lipid metabolism. Tolfenamic acid, an anti-inflammatory drug, decreased EGR1 protein levels and synergized with antiestrogens in inhibiting cell proliferation in LCC9 cells. Collectively, these findings indicate that EGR1 is an important regulator of breast cancer cell metabolism and is a promising target to prevent or reverse endocrine resistance.

The prognostic significance of Cdc6 and Cdt1 in breast cancer

DNA replication is a critical step in cell proliferation. Overexpression of MCM2-7 genes correlated with poor prognosis in breast cancer patients. However, the roles of Cdc6 and Cdt1, which work with MCMs to regulate DNA replication, in breast cancers are largely unknown. In the present study, we have shown that the expression levels of Cdc6 and Cdt1 were both significantly correlated with an increasing number of MCM2-7 genes overexpression. Both Cdc6 and Cdt1, when expressed in a high level, alone or in combination, were significantly associated with poorer survival in the breast cancer patient cohort (n = 1441). In line with this finding, the expression of Cdc6 and Cdt1 was upregulated in breast cancer cells compared to normal breast epithelial cells. Expression of Cdc6 and Cdt1 was significantly higher in ER negative breast cancer, and was suppressed when ER signalling was inhibited either by tamoxifen in vitro or letrozole in human subjects. Importantly, breast cancer patients who responded to letrozole expressed significantly lower Cdc6 than those patients who did not respond. Our results suggest that Cdc6 is a potential prognostic marker and therapeutic target in breast cancer patients.

Effects of In Utero Exposure to Ethinyl Estradiol on Tamoxifen Resistance and Breast Cancer Recurrence in a Preclinical Model

Background

Responses to endocrine therapies vary among patients with estrogen receptor (ER+) breast cancer. We studied whether in utero exposure to endocrine-disrupting compounds might explain these variations.

Methods

We describe a novel ER+ breast cancer model to study de novo and acquired tamoxifen (TAM) resistance. Pregnant Sprague Dawley rats were exposed to 0 or 0.1 ppm ethinyl estradiol (EE2), and the response of 9,12-dimethylbenz[a]anthracene (DMBA)-induced mammary tumors to 15 mg/kg TAM, with (n = 17 tumors in the controls and n = 20 tumors in EE2 offspring) or without 1.2 g/kg valproic acid and 5 mg/kg hydralazine (n = 24 tumors in the controls and n = 32 tumors in EE2 offspring) in the female offspring, was assessed. One-sided Chi2 tests were used to calculate P values. Comparisons of differentially expressed genes between mammary tumors in in utero EE2-exposed and control rats, and between anti-estrogen-resistant LCC9 and -sensitive LCC1 human breast cancer cells, were also performed.

Results

In our preclinical model, 54.2% of mammary tumors in the control rats exhibited a complete response to TAM, of which 23.1% acquired resistance with continued anti-estrogen treatment and recurred. Mammary tumors in the EE2 offspring were statistically significantly less likely to respond to TAM (P = .047) and recur (P = .007). In the EE2 offspring, but not in controls, adding valproic acid and hydralazine to TAM prevented recurrence (P < .001). Three downregulated and hypermethylated genes (KLF4, LGALS3, MICB) and one upregulated gene (ETV4) were identified in EE2 tumors and LCC9 breast cancer cells, and valproic acid and hydralazine normalized the altered expression of all four genes.

Conclusions

Resistance to TAM may be preprogrammed by in utero exposure to high estrogen levels and mediated through reversible epigenetic alterations in genes associated with epithelial-mesenchymal transition and tumor immune responses.

LRG1 mRNA expression in breast cancer associates with PIK3CA genotype and with aromatase inhibitor therapy outcome

BACKGROUND

PIK3CA is the most frequent somatic mutated oncogene in estrogen receptor (ER) positive breast cancer. We previously observed an association between PIK3CA genotype and aromatase inhibitors (AI) treatment outcome. This study now evaluates whether expression of mRNAs and miRs are linked to PIK3CA genotype and are independently related to AI therapy response in order to define potential expressed biomarkers for treatment outcome.

MATERIALS AND METHODS

The miR and mRNA expression levels were evaluated for their relationship with the PIK3CA genotype in two breast tumor datasets, i.e. 286 luminal cancers from the TCGA consortium and our set of 84 ER positive primary tumors of metastatic breast cancer patients who received first line AI. BRB Array tools class comparison was performed to define miRs and mRNAs whose expression associate with PIK3CA exon 9 and 20 status. Spearman correlations established miR-mRNA pairs and mRNAs with related expression. Next, a third dataset of 25 breast cancer patients receiving neo-adjuvant letrozole was evaluated, to compare expression levels of identified miRs and mRNAs in biopsies before and after treatment. Finally, to identify potential biomarkers miR and mRNA levels were related with overall survival (OS) and progression free survival (PFS) after first-line AI therapy.

RESULTS

Expression of 3 miRs (miR-449a, miR-205-5p, miR-301a-3p) and 9 mRNAs (CCNO, FAM81B, LRG1, NEK10, PLCL1, PGR, SERPINA3, SORBS2, VTCN1) was related to the PIK3CA status in both datasets. All except miR-301a-3p had an increased expression in tumors with PIK3CA mutations. Validation in a publicly available dataset showed that LRG1, PGR, and SERPINA3 levels were decreased after neo-adjuvant AI-treatment. Six miR-mRNA pairs correlated significantly and stepdown analysis of all 12 factors revealed 3 mRNAs (PLCL1, LRG1, FAM81B) related to PFS. Further analyses showed LRG1 and PLCL1 expression to be unrelated with luminal subtype and to associate with OS and with PFS, the latter independent from traditional predictive factors.

CONCLUSION

We showed in two datasets of ER positive and luminal breast tumors that the expression of 3 miRs and 9 mRNAs associate with the PIK3CA status. Expression of LRG1 is independent of luminal (A or B) subtype, decreased after neo-adjuvant AI-treatment, and is proposed as potential biomarker for AI therapy outcome.

Interleukin-6 is a potential therapeutic target in interleukin-6 dependent, estrogen receptor-α-positive breast cancer

Introduction

Interleukin-6 (IL-6) is an important growth factor for estrogen receptor-α (ERα)-positive breast cancer, and elevated serum IL-6 is associated with poor prognosis.

Methods

The role of the phosphorylated signal transducer and activator of transcription 3 pathway was investigated in ERα-positive breast cancer. A panel of cell lines was treated with exogenous IL-6. An IL-6 specific gene signature was generated by profiling ten ERα-positive breast cancer cell lines alone or following treatment with 10 ng/mL recombinant IL-6 or human marrow stromal cell-conditioned media, with or without siltuximab (a neutralizing anti-IL-6 antibody) and grown in three-dimensional tumor microenvironment-aligned cultures for 4 days, 5 days, or 6 days. The established IL-6 signature was validated against 36 human ERα-positive breast tumor samples with matched serum. A comparative MCF-7 xenograft murine model was utilized to determine the role of IL-6 in estrogen-supplemented ERα-positive breast cancer to assess the efficacy of anti-IL-6 therapy in vivo.

Results

In eight of nine ERα-positive breast cancer cell lines, recombinant IL-6 increased phosphorylation of tyrosine 705 of STAT3. Differential gene expression analysis identified 17 genes that could be used to determine IL-6 pathway activation by combining their expression intensity into a pathway activation score. The gene signature included a variety of genes involved in immune cell function and migration, cell growth and apoptosis, and the tumor microenvironment. Validation of the IL-6 gene signature in 36 matched human serum and ERα-positive breast tumor samples showed that patients with a high IL-6 pathway activation score were also enriched for elevated serum IL-6 (≥10 pg/mL). When human IL-6 was provided in vivo, MCF-7 cells engrafted without the need for estrogen supplementation, and addition of estrogen to IL-6 did not further enhance engraftment. Subsequently, we prophylactically treated mice at MCF-7 engraftment with siltuximab, fulvestrant, or combination therapy. Siltuximab alone was able to blunt MCF-7 engraftment. Similarly, siltuximab alone induced regressions in 90% (9/10) of tumors, which were established in the presence which were established in the presence of hMSC expressing human IL-6 and estrogen.

Conclusion

Given the established role for IL-6 in ERα-positive breast cancer, these data demonstrate the potential for anti-IL-6 therapeutics in breast cancer.

Differential epigenetic reprogramming in response to specific endocrine therapies promotes cholesterol biosynthesis and cellular invasion

Endocrine therapies target the activation of the oestrogen receptor alpha (ERα) via distinct mechanisms, but it is not clear whether breast cancer cells can adapt to treatment using drug-specific mechanisms. Here we demonstrate that resistance emerges via drug-specific epigenetic reprogramming. Resistant cells display a spectrum of phenotypical changes with invasive phenotypes evolving in lines resistant to the aromatase inhibitor (AI). Orthogonal genomics analysis of reprogrammed regulatory regions identifies individual drug-induced epigenetic states involving large topologically associating domains (TADs) and the activation of super-enhancers. AI-resistant cells activate endogenous cholesterol biosynthesis (CB) through stable epigenetic activation in vitro and in vivo. Mechanistically, CB sparks the constitutive activation of oestrogen receptors alpha (ERα) in AI-resistant cells, partly via the biosynthesis of 27-hydroxycholesterol. By targeting CB using statins, ERα binding is reduced and cell invasion is prevented. Epigenomic-led stratification can predict resistance to AI in a subset of ERα-positive patients.

Gene expression alterations associated with outcome in aromatase inhibitor-treated ER+ early-stage breast cancer patients

Aromatase inhibitors (AI), either alone or together with chemotherapy, have become the standard adjuvant treatment for postmenopausal, estrogen receptor-positive (ER+) breast cancer. Although AIs improve overall survival, resistance is still a major clinical problem, thus additional biomarkers predictive of outcome of ER+ breast cancer patients treated with AIs are needed. Global gene expression analysis was performed on ER+ primary breast cancers from patients treated with adjuvant AI monotherapy; half experienced recurrence (median follow-up 6.7 years). Gene expression alterations were validated by qRT-PCR, and functional studies evaluating the effect of siRNA-mediated gene knockdown on cell growth were performed. Twenty-six genes, including TFF3, DACH1, RGS5, and GHR, were shown to exhibit altered expression in tumors from patients with recurrence versus non-recurrent (fold change ≥1.5, p < 0.05), and the gene expression alterations were confirmed using qRT-PCR. Ten of these 26 genes could be linked in a network associated with cellular proliferation, growth, and development. TFF3, which encodes for trefoil factor 3 and is an estrogen-responsive oncogene shown to play a functional role in tamoxifen resistance and metastasis of ER+ breast cancer, was also shown to be upregulated in an AI-resistant cell line model, and reduction of TFF3 levels using TFF3-specific siRNAs decreased the growth of both the AI-resistant and -sensitive parental cell lines. Moreover, overexpression of TFF3 in parental AI-sensitive MCF-7/S0.5 cells resulted in reduced sensitivity to the AI exemestane, whereas TFF3 overexpression had no effect on growth in the absence of exemestane, indicating that TFF3 mediates growth and survival signals that abrogate the growth inhibitory effect of exemestane. We identified a panel of 26 genes exhibiting altered expression associated with disease recurrence in patients treated with adjuvant AI monotherapy, including TFF3, which was shown to exhibit a growth- and survival-promoting effect in the context of AI treatment.

Amphiregulin Is a Critical Downstream Effector of Estrogen Signaling in ERα-Positive Breast Cancer

Estrogen stimulation promotes epithelial cell proliferation in estrogen receptor (ERα)-positive breast cancer. Many ERα target genes have been enumerated, but the identities of the key effectors mediating the estrogen signal remain obscure. During mouse mammary gland development, the estrogen growth factor receptor (EGFR) ligand amphiregulin acts as an important stage-specific effector of estrogen signaling. In this study, we investigated the role of amphiregulin in breast cancer cell proliferation using human tissue samples and tumor xenografts in mice. Amphiregulin was enriched in ERα-positive human breast tumor cells and required for estrogen-dependent growth of MCF7 tumor xenografts. Furthermore, amphiregulin levels were suppressed in patients treated with endocrine therapy. Suppression of EGF receptor signaling appeared necessary for the therapeutic response in this setting. Our findings implicate amphiregulin as a critical mediator of the estrogen response in ERα-positive breast cancer, emphasizing the importance of EGF receptor signaling in breast tumor pathogenesis and therapeutic response.

Neoadjuvant endocrine therapy: Patient selection, treatment duration and surrogate endpoints

Neoadjuvant endocrine treatment has become of increasing interest for downstaging primary ER+ breast cancers as it has become clear that the pathologic complete response rate of luminal tumours to chemotherapy is much lower than that of non-luminal and differs little from that to endocrine therapy. There is much more experience in postmenopausal than premenopausal women. Aromatase inhibitors are generally the agent of choice. Responses are lower in those with the low levels of ER. While duration of endocrine treatment in clinical trials has usually been standardized at around three to four months it is clear that volume reductions continue to occur beyond that time in a large proportion of cases and routine clinical practice is often to treat to maximum response. This relatively slow emergence of downstaging relates to the absence of any increase in apoptosis with endocrine therapy and dependence of responses on the antiproliferative effects of oestrogen withdrawal: apoptosis occurs but at a slightly lower rate such that cell loss is attritional. The dependence of responses on the reduced proliferation underpins the value of Ki67 as an intermediate end-point for treatment benefit with multiple studies having found that relative effects on proliferation by different drugs in neoadjuvant trials match their relative impact on recurrence. While change in Ki67 is now accepted as a validated endpoint for comparing endocrine agents in the neoadjuvant scenario, on-treatment levels of Ki67 are related to long-term prognosis more closely than pretreatment Ki67. The Preoperative Endocrine Prognostic Index (PEPI) that combines residual Ki67 score with measures of on-treatment ER and other clinicopathologic factors has also found application in clinical trials. The potential to make longitudinal assessments of both clinical and biomarker responses has encouraged the development of novel clinical trial designs for assessing the impact of agents that aim to enhance response beyond that of endocrine agents alone. Such strategies include the early measurement of residual Ki67 levels after challenge with an endocrine agent alone and evaluation of the impact of the added agent on Ki67 or other agent-specific end-points.

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.

The Discovery of Novel Biomarkers Improves Breast Cancer Intrinsic Subtype Prediction and Reconciles the Labels in the METABRIC Data Set

BACKGROUND

The prediction of breast cancer intrinsic subtypes has been introduced as a valuable strategy to determine patient diagnosis and prognosis, and therapy response. The PAM50 method, based on the expression levels of 50 genes, uses a single sample predictor model to assign subtype labels to samples. Intrinsic errors reported within this assay demonstrate the challenge of identifying and understanding the breast cancer groups. In this study, we aim to: a) identify novel biomarkers for subtype individuation by exploring the competence of a newly proposed method named CM1 score, and b) apply an ensemble learning, as opposed to the use of a single classifier, for sample subtype assignment. The overarching objective is to improve class prediction.

METHODS AND FINDINGS

The microarray transcriptome data sets used in this study are: the METABRIC breast cancer data recorded for over 2000 patients, and the public integrated source from ROCK database with 1570 samples. We first computed the CM1 score to identify the probes with highly discriminative patterns of expression across samples of each intrinsic subtype. We further assessed the ability of 42 selected probes on assigning correct subtype labels using 24 different classifiers from the Weka software suite. For comparison, the same method was applied on the list of 50 genes from the PAM50 method.

CONCLUSIONS

The CM1 score portrayed 30 novel biomarkers for predicting breast cancer subtypes, with the confirmation of the role of 12 well-established genes. Intrinsic subtypes assigned using the CM1 list and the ensemble of classifiers are more consistent and homogeneous than the original PAM50 labels. The new subtypes show accurate distributions of current clinical markers ER, PR and HER2, and survival curves in the METABRIC and ROCK data sets. Remarkably, the paradoxical attribution of the original labels reinforces the limitations of employing a single sample classifiers to predict breast cancer intrinsic subtypes.

Antihormone induced compensatory signalling in breast cancer: an adverse event in the development of endocrine resistance

Using MCF7 breast cancer cells, it has been shown that antihormones promote expression/activity of oestrogen-repressed tyrosine kinases, notably EGFR, HER2 and Src. These inductive events confer responsiveness to targeted inhibitors (e.g., gefitinib, trastuzumab, saracatinib). We observed that these antihormone-induced phenomena are common to ER+HER2- and ER+HER2+ breast cancer models in vitro, where targeting of EGFR, HER2 or Src alongside antihormone improves antitumour response and delays/prevents endocrine resistance. Such targeted inhibitors also subvert acquired endocrine resistant cells which retain increased EGFR, HER2 and Src (e.g., TAMR and FASR models derived after 6-12 months of tamoxifen or Faslodex treatment). Thus, antihormone-induced tyrosine kinases comprise "compensatory signalling" crucial in limiting maximal initial antihormone response and subsequently driving acquired resistance in vitro. However, despite such convincing preclinical findings from our group and others, clinical trials examining equivalent antigrowth factor strategies have proved relatively disappointing. Our new studies deciphering underlying causes reveal that further antihormone-promoted events could be pivotal in vivo. Firstly, Faslodex induces HER3 and HER4 which sensitise ER+ cells to heregulin, a paracrine growth factor that overcomes endocrine response and diminishes antitumour effect of agents targeting EGFR, HER2 or Src alongside antihormone. Secondly, extended antihormone exposure (experienced by ER+ cells prior to adjuvant clinical relapse) can "reprogramme" the compensatory kinase profile in vitro, hindering candidate antigrowth factor targeting of endocrine resistance. Faslodex resistant cells maintained with this antihormone for 3 years in vitro lose EGFR/HER2 dependency, gaining alternative mitogenic/invasion kinases. Deciphering these previously unrecognised antihormone-induced events could provide superior treatments to control endocrine relapse in the clinic.

Prognostic significance of minichromosome maintenance proteins in breast cancer

A role for the minichromosome maintenance (MCM) proteins in cancer initiation and progression is slowly emerging. Functioning as a complex to ensure a single chromosomal replication per cell cycle, the six family members have been implicated in several neoplastic disease states, including breast cancer. Our study aim to investigate the prognostic significance of these proteins in breast cancer. We studied the expression of MCMs in various datasets and the associations of the expression with clinicopathological parameters. When considered alone, high level MCM4 overexpression was only weakly associated with shorter survival in the combined breast cancer patient cohort (n = 1441, Hazard Ratio = 1.31; 95% Confidence Interval = 1.11-1.55; p = 0.001). On the other hand, when we studied all six components of the MCM complex, we found that overexpression of all MCMs was strongly associated with shorter survival in the same cohort (n = 1441, Hazard Ratio = 1.75; 95% Confidence Interval = 1.31-2.34; p < 0.001), suggesting these MCM proteins may cooperate to promote breast cancer progression. Indeed, their expressions were significantly correlated with each other in these cohorts. In addition, we found that increasing number of overexpressed MCMs was associated with negative ER status as well as treatment response. Together, our findings are reproducible in seven independent breast cancer cohorts, with 1441 patients, and suggest that MCM profiling could potentially be used to predict response to treatment and prognosis in breast cancer patients.

Endocrine Resistance in Breast Cancer

Around 70% of all breast cancers are estrogen receptor alpha positive and hence their development is highly dependent on estradiol. While the invention of endocrine therapies has revolusioned the treatment of the disease, resistance to therapy eventually occurs in a large number of patients. This paper seeks to illustrate and discuss the complexity and heterogeneity of the mechanisms which underlie resistance and the approaches proposed to combat them. It will also focus on the use and development of methods for predicting which patients are likely to develop resistance.

Acquired resistance to endocrine treatments is associated with tumor-specific molecular changes in patient-derived luminal breast cancer xenografts

PURPOSE

Patients with luminal breast cancer (LBC) often become endocrine resistant over time. We investigated the molecular changes associated with acquired hormonoresistances in patient-derived xenografts of LBC.

EXPERIMENTAL DESIGN

Two LBC xenografts (HBCx22 and HBCx34) were treated with different endocrine treatments (ET) to obtain xenografts with acquired resistances to tamoxifen (TamR) and ovariectomy (OvaR). PI3K pathway activation was analyzed by Western blot analysis and IHC and responses to ET combined to everolimus were investigated in vivo. Gene expression analyses were performed by RT-PCR and Affymetrix arrays.

RESULTS

HBCx22 TamR xenograft was cross-resistant to several hormonotherapies, whereas HBCx22 OvaR and HBCx34 TamR exhibited a treatment-specific resistance profile. PI3K pathway was similarly activated in parental and resistant xenografts but the addition of everolimus did not restore the response to tamoxifen in TamR xenografts. In contrast, the combination of fulvestrant and everolimus induced tumor regression in vivo in HBCx34 TamR, where we found a cross-talk between the estrogen receptor (ER) and PI3K pathways. Expression of several ER-controlled genes and ER coregulators was significantly changed in both TamR and OvaR tumors, indicating impaired ER transcriptional activity. Expression changes associated with hormonoresistance were both tumor and treatment specific and were enriched for genes involved in cell growth, cell death, and cell survival.

CONCLUSIONS

PDX models of LBC with acquired resistance to endocrine therapies show a great diversity of resistance phenotype, associated with specific deregulations of ER-mediated gene transcription. These models offer a tool for developing anticancer therapies and to investigate the dynamics of resistance emerging during pharmacologic interventions. Clin Cancer Res; 20(16); 4314-25. ©2014 AACR.

Hallmarks of aromatase inhibitor drug resistance revealed by epigenetic profiling in breast cancer

Aromatase inhibitors are the major first-line treatment of estrogen receptor-positive breast cancer, but resistance to treatment is common. To date, no biomarkers have been validated clinically to guide subsequent therapy in these patients. In this study, we mapped the genome-wide chromatin-binding profiles of estrogen receptor α (ERα), along with the epigenetic modifications H3K4me3 and H3K27me3, that are responsible for determining gene transcription (n = 12). Differential binding patterns of ERα, H3K4me3, and H3K27me3 were enriched between patients with good or poor outcomes after aromatase inhibition. ERα and H3K27me3 patterns were validated in an additional independent set of breast cancer cases (n = 10). We coupled these patterns to array-based proximal gene expression and progression-free survival data derived from a further independent cohort of 72 aromatase inhibitor-treated patients. Through this approach, we determined that the ERα and H3K27me3 profiles predicted the treatment outcomes for first-line aromatase inhibitors. In contrast, the H3K4me3 pattern identified was not similarly informative. The classification potential of these genes was only partially preserved in a cohort of 101 patients who received first-line tamoxifen treatment, suggesting some treatment selectivity in patient classification.

Genome-wide reprogramming of the chromatin landscape underlies endocrine therapy resistance in breast cancer

The estrogen receptor (ER)α drives growth in two-thirds of all breast cancers. Several targeted therapies, collectively termed endocrine therapy, impinge on estrogen-induced ERα activation to block tumor growth. However, half of ERα-positive breast cancers are tolerant or acquire resistance to endocrine therapy. We demonstrate that genome-wide reprogramming of the chromatin landscape, defined by epigenomic maps for regulatory elements or transcriptional activation and chromatin openness, underlies resistance to endocrine therapy. This annotation reveals endocrine therapy-response specific regulatory networks where NOTCH pathway is overactivated in resistant breast cancer cells, whereas classical ERα signaling is epigenetically disengaged. Blocking NOTCH signaling abrogates growth of resistant breast cancer cells. Its activation state in primary breast tumors is a prognostic factor of resistance in endocrine treated patients. Overall, our work demonstrates that chromatin landscape reprogramming underlies changes in regulatory networks driving endocrine therapy resistance in breast cancer.

The development, application and limitations of breast cancer cell lines to study tamoxifen and aromatase inhibitor resistance

Estrogen plays important roles in hormone receptor-positive breast cancer. Endocrine therapies, such as the antiestrogen tamoxifen, antagonize the binding of estrogen to estrogen receptor (ER), whereas aromatase inhibitors (AIs) directly inhibit the production of estrogen. Understanding the mechanisms of endocrine resistance and the ways in which we may better treat these types of resistance has been aided by the development of cellular models for resistant breast cancers. In this review, we will discuss what is known thus far regarding both de novo and acquired resistance to tamoxifen or AIs. Our laboratory has generated a collection of AI- and tamoxifen-resistant cell lines in order to comprehensively study the individual types of resistance mechanisms. Through the use of microarray analysis, we have determined that our cell lines resistant to a particular AI (anastrozole, letrozole, or exemestane) or tamoxifen are distinct from each other, indicating that these mechanisms can be quite complex. Furthermore, we will describe two novel de novo AI-resistant cell lines that were generated from our laboratory. Initial characterization of these cells reveals that they are distinct from our acquired AI-resistant cell models. In addition, we will review potential therapies which may be useful for overcoming resistant breast cancers through studies using endocrine resistant cell lines. Finally, we will discuss the benefits and shortcomings of cell models. Together, the information presented in this review will provide us a better understanding of acquired and de novo resistance to tamoxifen and AI therapies, the use of appropriate cell models to better study these types of breast cancer, which are valuable for identifying novel treatments and strategies for overcoming both tamoxifen and AI-resistant breast cancers.