Endocrine-therapy-resistant ESR1 variants revealed by genomic characterization of breast-cancer-derived xenografts

Subclonal heterogeneity and evolution in breast cancer

Subclonal heterogeneity and evolution are characteristics of breast cancer that play a fundamental role in tumour development, progression and resistance to current therapies. In this review, we focus on the recent advances in understanding the epigenetic and transcriptomic changes that occur within breast cancer and their importance in terms of cancer development, progression and therapy resistance with a particular focus on alterations at the single-cell level. Furthermore, we highlight the utility of using single-cell tracing and molecular barcoding methodologies in preclinical models to assess disease evolution and response to therapy. We discuss how the integration of single-cell profiling from patient samples can be used in conjunction with results from preclinical models to untangle the complexities of this disease and identify biomarkers of disease progression, including measures of intra-tumour heterogeneity themselves, and how enhancing this understanding has the potential to uncover new targetable vulnerabilities in breast cancer.

Influence of Estrogen Treatment on ESR1+ and ESR1- Cells in ER+ Breast Cancer: Insights from Single-Cell Analysis of Patient-Derived Xenograft Models

Simple Summary

The benefit of endocrine therapy is normally observed for cancers with 10% or more of cells positive for ER expression. We compared the gene expression profiles in both ESR1⁺ and ESR1^– cells in ER⁺ tumors following estrogen treatment. Our single-cell RNA sequencing analysis of estrogen-stimulated (SC31) and estrogen-suppressed (GS3) patient-derived xenograft models offered an unprecedented opportunity to address the molecular and functional differences between ESR1⁺ and ESR1^– cells. While estrogen should activate ERα and stimulate ESR1⁺ cells, our findings regarding ESR1^– cells were important, indicating that the proliferation of ESR1^– cells in ER⁺ cancer is also influenced by estrogen. Another valuable finding from our studies was that estrogen also upregulated a tumor-suppressor gene, IL-24, only in GS3. Estrogen increased the percentage of cells expressing IL-24, associated with the estrogen-dependent inhibition of GS3 tumor growth.

Abstract

A 100% ER positivity is not required for an endocrine therapy response. Furthermore, while estrogen typically promotes the progression of hormone-dependent breast cancer via the activation of estrogen receptor (ER)-α, estrogen-induced tumor suppression in ER⁺ breast cancer has been clinically observed. With the success in establishing estrogen-stimulated (SC31) and estrogen-suppressed (GS3) patient-derived xenograft (PDX) models, single-cell RNA sequencing analysis was performed to determine the impact of estrogen on ESR1⁺ and ESR1^– tumor cells. We found that 17β-estradiol (E2)-induced suppression of GS3 transpired through wild-type and unamplified ERα. E2 upregulated the expression of estrogen-dependent genes in both SC31 and GS3; however, E2 induced cell cycle advance in SC31, while it resulted in cell cycle arrest in GS3. Importantly, these gene expression changes occurred in both ESR1⁺ and ESR1^– cells within the same breast tumors, demonstrating for the first time a differential effect of estrogen on ESR1^– cells. E2 also upregulated a tumor-suppressor gene, IL-24, in GS3. The apoptosis gene set was upregulated and the G2M checkpoint gene set was downregulated in most IL-24⁺ cells after E2 treatment. In summary, estrogen affected pathologically defined ER⁺ tumors differently, influencing both ESR1⁺ and ESR1^– cells. Our results also suggest IL-24 to be a potential marker of estrogen-suppressed tumors.

Transcriptional reprogramming differentiates active from inactive ESR1 fusions in endocrine therapy-refractory metastatic breast cancer

Genomic analysis has recently identified multiple ESR1 gene translocations in estrogen receptor-alpha positive (ERα+) metastatic breast cancer (MBC) that encode chimeric proteins whereby the ESR1 ligand binding domain (LBD) is replaced by C-terminal sequences from many different gene partners. Here we functionally screened 15 ESR1 fusions and identified 10 that promoted estradiol-independent cell growth, motility, invasion, EMT and resistance to fulvestrant. RNA sequencing identified a gene expression pattern specific to functionally active ESR1 gene fusions that was subsequently reduced to a diagnostic 24-gene signature. This signature was further examined in 20 ERα+ patient-derived xenografts (PDXs) and in 55 ERα+ MBC samples. The 24-gene signature successfully identified cases harboring ESR1 gene fusions and also accurately diagnosed the presence of activating ESR1 LBD point mutations. Therefore, the 24-gene signature represents an efficient approach to screening samples for the presence of diverse somatic ESR1 mutations and translocations that drive endocrine treatment failure in MBC.

Atlas of Lobular Breast Cancer Models: Challenges and Strategic Directions

Invasive lobular carcinoma (ILC) accounts for up to 15% of all breast cancer (BC) cases and responds well to endocrine treatment when estrogen receptor α-positive (ER+) yet differs in many biological aspects from other ER+ BC subtypes. Up to 30% of patients with ILC will develop late-onset metastatic disease up to ten years after initial tumor diagnosis and may experience failure of systemic therapy. Unfortunately, preclinical models to study ILC progression and predict the efficacy of novel therapeutics are scarce. Here, we review the current advances in ILC modeling, including cell lines and organotypic models, genetically engineered mouse models, and patient-derived xenografts. We also underscore four critical challenges that can be addressed using ILC models: drug resistance, lobular tumor microenvironment, tumor dormancy, and metastasis. Finally, we highlight the advantages of shared experimental ILC resources and provide essential considerations from the perspective of the European Lobular Breast Cancer Consortium (ELBCC), which is devoted to better understanding and translating the molecular cues that underpin ILC to clinical diagnosis and intervention. This review will guide investigators who are considering the implementation of ILC models in their research programs.

Lnc-DC promotes estrogen independent growth and tamoxifen resistance in breast cancer

Selective estrogen receptor modulators (SERMs) such as tamoxifen have proven to be effective in the treatment of estrogen receptor (ER) positive breast cancer. However, a major obstacle for such endocrine therapy is estrogen independent growth, leading to resistance, and the underlying mechanism is not fully understood. The purpose of this study was to determine whether long non-coding RNAs (lncRNAs) are involved in regulation of estrogen independent growth and tamoxifen resistance in ER positive breast cancer. Using a CRISPR/Cas9-based SAM (synergistic activation mediator) library against a focus group of lncRNAs, we identify Lnc-DC as a candidate lncRNA. Further analysis suggests that Lnc-DC is able to reduce tamoxifen-induced apoptosis by upregulation of anti-apoptotic genes such as Bcl2 and Bcl-xL. Furthermore, Lnc-DC activates STAT3 by phosphorylation (pSTAT3Y705), and the activated STAT3 subsequently induces expression of cytokines which in turn activate STAT3, forming an autocrine loop. Clinically, upregulation of Lnc-DC is associated with poor prognosis. In particular, analysis of a tamoxifen-treated patient cohort indicates that Lnc-DC expression can predict the response to tamoxifen. Together, this study demonstrates a previously uncharacterized function of Lnc-DC/STAT3/cytokine axis in estrogen independent growth and tamoxifen resistance, and Lnc-DC may serve as a potential predictor for tamoxifen response.

Identification of nuclear export inhibitor-based combination therapies in preclinical models of triple-negative breast cancer

•

High-throughput drug screening reveals promising therapeutic candidates for TNBC.

•

KPT-330, an XPO1 inhibitor, and GSK2126458 exhibit synergism in preclinical models of TNBC.

•

XPO1 is overexpressed in basal-like breast tumors.

•

XPO1 expression is associated with PIK3CA, MTOR, and MKI67 expression at the single-cell level.

•

XPO1 overexpression in basal-like patients is associated with greater rates of metastases.

An estimated 284,000 Americans will be diagnosed with breast cancer in 2021. Of these individuals, 15–20% have basal-like triple-negative breast cancer (TNBC), which is known to be highly metastatic. Chemotherapy is standard of care for TNBC patients, but chemoresistance is a common clinical problem. There is currently a lack of alternative, targeted treatment strategies for TNBC; this study sought to identify novel therapeutic combinations to treat basal-like TNBCs. For these studies, four human basal-like TNBC cell lines were utilized to determine the cytotoxicity profile of 1363 clinically-used drugs. Ten promising therapeutic candidates were identified, and synergism studies were performed in vitro. Two drug combinations that included KPT-330, an XPO1 inhibitor, were synergistic in all four cell lines. In vivo testing of four basal-like patient-derived xenografts (PDX) identified one combination, KPT-330 and GSK2126458 (a PI3K/mTOR inhibitor), that decreased tumor burden in mice significantly more than monotherapy with either single agent. Bulk and single-cell RNA-sequencing, immunohistochemistry, and analysis of published genomic datasets found that XPO1 was abundantly expressed in human basal-like TNBC cell lines, PDXs, and patient tumor samples. Within basal-like PDXs, XPO1 overexpression was associated with increased proliferation at the cellular level. Within patient datasets, XPO1 overexpression was correlated with greater rates of metastasis in patients with basal-like tumors. These studies identify a promising potential new combination therapy for patients with basal-like breast cancer.

HER2 Activation and Endocrine Treatment Resistance in HER2-negative Breast Cancer

The lethality of estrogen receptor alpha positive (ER+) breast cancer, which is often considered to have better prognosis than other subtypes, is defined by resistance to the standard of care endocrine treatment. Relapse and metastasis are inevitable in almost every patient whose cancer is resistant to endocrine treatment. Therefore, understanding the underlying causes of treatment resistance remains an important biological and clinical focus of research in this area. Growth factor receptor pathway activation, specifically HER2 activation, has been identified as 1 mechanism of endocrine treatment resistance across a range of experimental model systems. However, clinical trials conducted to test whether targeting HER2 benefits patients with endocrine treatment-resistant ER+ breast cancer have consistently and disappointingly shown mixed results. One reason for the failure of these clinical trials could be the complexity of crosstalk between ER, HER2, and other growth factor receptors and the fluidity of HER2 activation in these cells, which makes it challenging to identify stratifiers for this targeted intervention. In the absence of stratifiers that can be assayed at diagnosis to allow prospective tailoring of HER2 inhibition to the right patients, clinical trials will continue to disappoint. To understand stratifiers, it is important that the field invests in key understudied areas of research including characterization of the tumor secretome and receptor activation in response to endocrine treatment, and mapping the ER-HER2 growth factor network in the normal and developing mammary gland. Understanding these mechanisms further is critical to improving outcomes for the hard-to-treat endocrine treatment-resistant ER+ breast cancer cohort.

Microenvironmental modulation of the developing tumour: an immune-stromal dialogue

Successful establishment of a tumour relies on a cascade of interactions between cancer cells and stromal cells within an evolving microenvironment. Both immune and nonimmune cellular components are key factors in this process, and the individual players may change their role from tumour elimination to tumour promotion as the microenvironment develops. While the tumour-stroma crosstalk present in an established tumour is well-studied, aspects in the early tumour or premalignant microenvironment have received less attention. This is in part due to the challenges in studying this process in the clinic or in mouse models. Here, we review the key anti- and pro-tumour factors in the early microenvironment and discuss how understanding this process may be exploited in the clinic.

Automating UbiFast for High-throughput and Multiplexed Ubiquitin Enrichment

Robust methods for deep-scale enrichment and site-specific identification of ubiquitylation sites are necessary for characterizing the myriad roles of protein ubiquitylation. To this end we previously developed UbiFast, a sensitive method for highly multiplexed ubiquitylation profiling where K-ϵ-GG peptides are enriched with anti-K-ε-GG antibody and labeled on-antibody with isobaric labeling reagents for sample multiplexing. Here, we present robotic automation of the UbiFast method using a magnetic bead-conjugated K-ε-GG antibody (mK-ε-GG) and a magnetic particle processor. We report the identification of ∼20,000 ubiquitylation sites from a TMT10-plex with 500 μg input per sample processed in ∼2 h. Automation of the UbiFast method greatly increased the number of identified and quantified ubiquitylation sites, improved reproducibility, and significantly reduced processing time. The automated method also significantly reduced variability across process replicates compared with the manual method. The workflow enables processing of up to 96 samples in a single day making it suitable to study ubiquitylation in large sample sets. Here we demonstrate the applicability of the method to profile small amounts of tissue using breast cancer patient–derived xenograft (PDX) tissue samples.

•

HS mag anti-K-ε-GG antibody increases sensitivity of ubiquitylation site detection.

•

Automated UbiFast increases reproducibility and sample processing throughput.

•

The automated UbiFast workflow enables processing of up to 96 samples in one day.

•

UbiFast can be employed to profile ubiquitylomes from small amounts of tumor tissue.

NSG-Pro mouse model for uncovering resistance mechanisms and unique vulnerabilities in human luminal breast cancers

Most breast cancer deaths are caused by estrogen receptor-α–positive (ER+) disease. Preclinical progress is hampered by a shortage of therapy-naïve ER+ tumor models that recapitulate metastatic progression and clinically relevant therapy resistance. Human prolactin (hPRL) is a risk factor for primary and metastatic ER+ breast cancer. Because mouse prolactin fails to activate hPRL receptors, we developed a prolactin-humanized Nod-SCID-IL2Rγ (NSG) mouse (NSG-Pro) with physiological hPRL levels. Here, we show that NSG-Pro mice facilitate establishment of therapy-naïve, estrogen-dependent PDX tumors that progress to lethal metastatic disease. Preclinical trials provide first-in-mouse efficacy of pharmacological hPRL suppression on residual ER+ human breast cancer metastases and document divergent biology and drug responsiveness of tumors grown in NSG-Pro versus NSG mice. Oncogenomic analyses of PDX lines in NSG-Pro mice revealed clinically relevant therapy-resistance mechanisms and unexpected, potently actionable vulnerabilities such as DNA-repair aberrations. The NSG-Pro mouse unlocks previously inaccessible precision medicine approaches for ER+ breast cancers.

A highly multiplexed quantitative phosphosite assay for biology and preclinical studies

Reliable methods to quantify dynamic signaling changes across diverse pathways are needed to better understand the effects of disease and drug treatment in cells and tissues but are presently lacking. Here, we present SigPath, a targeted mass spectrometry (MS) assay that measures 284 phosphosites in 200 phosphoproteins of biological interest. SigPath probes a broad swath of signaling biology with high throughput and quantitative precision. We applied the assay to investigate changes in phospho-signaling in drug-treated cancer cell lines, breast cancer preclinical models, and human medulloblastoma tumors. In addition to validating previous findings, SigPath detected and quantified a large number of differentially regulated phosphosites newly associated with disease models and human tumors at baseline or with drug perturbation. Our results highlight the potential of SigPath to monitor phosphoproteomic signaling events and to nominate mechanistic hypotheses regarding oncogenesis, response, and resistance to therapy.

Zebrafish Patient-Derived Xenografts Identify Chemo-Response in Pancreatic Ductal Adenocarcinoma Patients

It is increasingly evident the necessity of new predictive tools for the treatment of pancreatic ductal adenocarcinoma in a personalized manner. We present a co-clinical trial testing the predictiveness of zPDX (zebrafish patient-derived xenograft) for assessing if patients could benefit from a therapeutic strategy (ClinicalTrials.gov: XenoZ, NCT03668418). zPDX are generated xenografting tumor tissues in zebrafish embryos. zPDX were exposed to chemotherapy regimens commonly used. We considered a zPDX a responder (R) when a decrease ≥50% in the relative tumor area was reported; otherwise, we considered them a non-responder (NR). Patients were classified as Responder if their own zPDX was classified as an R for the chemotherapy scheme she/he received an adjuvant treatment; otherwise, we considered them a Non-Responder. We compared the cancer recurrence rate at 1 year after surgery and the disease-free survival (DFS) of patients of both groups. We reported a statistically significant higher recurrence rate in the Non-Responder group: 66.7% vs. 14.3% (p = 0.036), anticipating relapse/no relapse within 1 year after surgery in 12/16 patients. The mean DFS was longer in the R-group than the NR-group, even if not statistically significant: 19.2 months vs. 12.7 months, (p = 0.123). The proposed strategy could potentially improve preclinical evaluation of treatment modalities and may enable prospective therapeutic selection in everyday clinical practice.

ESR1 mutation as an emerging clinical biomarker in metastatic hormone receptor-positive breast cancer

In metastatic hormone receptor-positive breast cancer, ESR1 mutations are a common cause of acquired resistance to the backbone of therapy, estrogen deprivation by aromatase inhibition. How these mutations affect tumor sensitivity to established and novel therapies are active areas of research. These therapies include estrogen receptor-targeting agents, such as selective estrogen receptor modulators, covalent antagonists, and degraders (including tamoxifen, fulvestrant, and novel agents), and combination therapies, such as endocrine therapy plus CDK4/6, PI3K, or mTORC1 inhibition. In this review, we summarize existing knowledge surrounding the mechanisms of action of ESR1 mutations and roles in resistance to aromatase inhibition. We then analyze the recent literature on how ESR1 mutations affect outcomes in estrogen receptor-targeting and combination therapies. For estrogen receptor-targeting therapies such as tamoxifen and fulvestrant, ESR1 mutations cause relative resistance in vitro but do not clearly lead to resistance in patients, making novel agents in this category promising. Regarding combination therapies, ESR1 mutations nullify any aromatase inhibitor component of the combination. Thus, combinations using endocrine alternatives to aromatase inhibition, or combinations where the non-endocrine component is efficacious as monotherapy, are still effective against ESR1 mutations. These results emphasize the importance of investigating combinatorial resistance, challenging as these efforts are. We also discuss future directions and open questions, such as studying the differences among distinct ESR1 mutations, asking how to adjust clinical decisions based on molecular surveillance testing, and developing novel therapies that are effective against ESR1 mutations.

Liquid Biopsy in Breast Cancer: A Focused Review

CONTEXT.—

The role of liquid biopsy in cancer management has been gaining increased prominence in the past decade, with well-defined clinical applications now being established in lung cancer. Recently, the US Food and Drug Administration also approved the Therascreen PIK3CA RGQ polymerase chain reaction assay as a companion diagnostic assay to detect PIK3CA mutations in breast cancer for both tissue and liquid biopsies, bringing the role of liquid biopsy in breast cancer management to the fore. Its utility in other aspects of breast cancer, however, is yet to be clearly defined.

OBJECTIVE.—

To review the studies that looked at liquid biopsies in breast cancer and examine their potential for clinical application in the areas of early diagnosis, prognostication, monitoring disease response, detecting minimal residual disease, and predicting risk of progression or relapse. We focus mainly on circulating tumor cells and circulating tumor DNA.

DATA SOURCES.—

Peer-reviewed articles in PubMed.

CONCLUSIONS.—

Liquid biopsies in breast cancers have yielded promising results, especially in the areas of monitoring treatment response and predicting disease progression or relapse. With further study, and hopefully coupled with continued improvements in technologies that isolate tumor-derived materials, liquid biopsies may go on to play a greater role in the breast cancer clinic.

Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine

The National Institutes of Health’s (National Cancer Institute) precision medicine initiative emphasizes the biological and molecular bases for cancer prevention and treatment. Importantly, it addresses the need for consistency in preclinical and clinical research. To overcome the translational gap in cancer treatment and prevention, the cancer research community has been transitioning toward using animal models that more fatefully recapitulate human tumor biology. There is a growing need to develop best practices in translational research, including imaging research, to better inform therapeutic choices and decision-making. Therefore, the National Cancer Institute has recently launched the Co-Clinical Imaging Research Resource Program (CIRP). Its overarching mission is to advance the practice of precision medicine by establishing consensus-based best practices for co-clinical imaging research by developing optimized state-of-the-art translational quantitative imaging methodologies to enable disease detection, risk stratification, and assessment/prediction of response to therapy. In this communication, we discuss our involvement in the CIRP, detailing key considerations including animal model selection, co-clinical study design, need for standardization of co-clinical instruments, and harmonization of preclinical and clinical quantitative imaging pipelines. An underlying emphasis in the program is to develop best practices toward reproducible, repeatable, and precise quantitative imaging biomarkers for use in translational cancer imaging and therapy. We will conclude with our thoughts on informatics needs to enable collaborative and open science research to advance precision medicine.

Co-clinical FDG-PET radiomic signature in predicting response to neoadjuvant chemotherapy in triple-negative breast cancer

Purpose

We sought to exploit the heterogeneity afforded by patient-derived tumor xenografts (PDX) to first, optimize and identify robust radiomic features to predict response to therapy in subtype-matched triple negative breast cancer (TNBC) PDX, and second, to implement PDX-optimized image features in a TNBC co-clinical study to predict response to therapy using machine learning (ML) algorithms.

Methods

TNBC patients and subtype-matched PDX were recruited into a co-clinical FDG-PET imaging trial to predict response to therapy. One hundred thirty-one imaging features were extracted from PDX and human-segmented tumors. Robust image features were identified based on reproducibility, cross-correlation, and volume independence. A rank importance of predictors using ReliefF was used to identify predictive radiomic features in the preclinical PDX trial in conjunction with ML algorithms: classification and regression tree (CART), Naïve Bayes (NB), and support vector machines (SVM). The top four PDX-optimized image features, defined as radiomic signatures (RadSig), from each task were then used to predict or assess response to therapy. Performance of RadSig in predicting/assessing response was compared to SUV_mean, SUV_max, and lean body mass-normalized SUL_peak measures.

Results

Sixty-four out of 131 preclinical imaging features were identified as robust. NB-RadSig performed highest in predicting and assessing response to therapy in the preclinical PDX trial. In the clinical study, the performance of SVM-RadSig and NB-RadSig to predict and assess response was practically identical and superior to SUV_mean, SUV_max, and SUL_peak measures.

Conclusions

We optimized robust FDG-PET radiomic signatures (RadSig) to predict and assess response to therapy in the context of a co-clinical imaging trial.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05489-8.

Deep Learning Segmentation of Triple-Negative Breast Cancer (TNBC) Patient Derived Tumor Xenograft (PDX) and Sensitivity of Radiomic Pipeline to Tumor Probability Boundary

Preclinical magnetic resonance imaging (MRI) is a critical component in a co-clinical research pipeline. Importantly, segmentation of tumors in MRI is a necessary step in tumor phenotyping and assessment of response to therapy. However, manual segmentation is time-intensive and suffers from inter- and intra- observer variability and lack of reproducibility. This study aimed to develop an automated pipeline for accurate localization and delineation of TNBC PDX tumors from preclinical T1w and T2w MR images using a deep learning (DL) algorithm and to assess the sensitivity of radiomic features to tumor boundaries. We tested five network architectures including U-Net, dense U-Net, Res-Net, recurrent residual UNet (R2UNet), and dense R2U-Net (D-R2UNet), which were compared against manual delineation by experts. To mitigate bias among multiple experts, the simultaneous truth and performance level estimation (STAPLE) algorithm was applied to create consensus maps. Performance metrics (F1-Score, recall, precision, and AUC) were used to assess the performance of the networks. Multi-contrast D-R2UNet performed best with F1-score = 0.948; however, all networks scored within 1-3% of each other. Radiomic features extracted from D-R2UNet were highly corelated to STAPLE-derived features with 67.13% of T1w and 53.15% of T2w exhibiting correlation ρ ≥ 0.9 (p ≤ 0.05). D-R2UNet-extracted features exhibited better reproducibility relative to STAPLE with 86.71% of T1w and 69.93% of T2w features found to be highly reproducible (CCC ≥ 0.9, p ≤ 0.05). Finally, 39.16% T1w and 13.9% T2w features were identified as insensitive to tumor boundary perturbations (Spearman correlation (-0.4 ≤ ρ ≤ 0.4). We developed a highly reproducible DL algorithm to circumvent manual segmentation of T1w and T2w MR images and identified sensitivity of radiomic features to tumor boundaries.

Evaluation of endocrine resistance using ESR1 genotyping of circulating tumor cells and plasma DNA

PURPOSE

Therapeutic efficacy of hormonal therapies to target estrogen receptor (ER)-positive breast cancer is limited by the acquisition of ligand-independent ESR1 mutations, which confer treatment resistance to aromatase inhibitors (AIs). Monitoring for the emergence of such mutations may enable individualized therapy. We thus assessed CTC- and ctDNA-based detection of ESR1 mutations with the aim of evaluating non-invasive approaches for the determination of endocrine resistance.

PATIENTS AND METHODS

In a prospective cohort of 55 women with hormone receptor-positive metastatic breast cancer, we isolated circulating tumor cells (CTCs) and developed a high-sensitivity method for the detection of ESR1 mutations in these CTCs. In patients with sufficient plasma for the simultaneous extraction of circulating tumor DNA (ctDNA), we performed a parallel analysis of ESR1 mutations using multiplex droplet digital PCR (ddPCR) and examined the agreement between these two platforms. Finally, we isolated single CTCs from a subset of these patients and reviewed RNA expression to explore alternate methods of evaluating endocrine responsiveness.

RESULTS

High-sensitivity ESR1 sequencing from CTCs revealed mono- and oligoclonal mutations in 22% of patients. These were concordant with plasma DNA sequencing in 95% of cases. Emergence of ESR1 mutations was correlated both with time to metastatic relapse and duration of AI therapy following such recurrence. The Presence of an ESR1 mutation, compared to ESR1 wild type, was associated with markedly shorter Progression-Free Survival on AI-based therapies (p = 0.0006), but unaltered to other non-AI-based therapies (p = 0.73). Compared with ESR1 mutant cases, AI-resistant CTCs with wild-type ESR1 showed an elevated ER-coactivator RNA signature, consistent with their predicted response to second-line hormonal therapies.

CONCLUSION

Blood-based serial monitoring may guide the selection of precision therapeutics for women with AI-resistant ER-positive breast cancer.

CBP/p300: Critical Co-Activators for Nuclear Steroid Hormone Receptors and Emerging Therapeutic Targets in Prostate and Breast Cancers

The CREB-binding protein (CBP) and p300 are two paralogous lysine acetyltransferases (KATs) that were discovered in the 1980s-1990s. Since their discovery, CBP/p300 have emerged as important regulatory proteins due to their ability to acetylate histone and non-histone proteins to modulate transcription. Work in the last 20 years has firmly established CBP/p300 as critical regulators for nuclear hormone signaling pathways, which drive tumor growth in several cancer types. Indeed, CBP/p300 are critical co-activators for the androgen receptor (AR) and estrogen receptor (ER) signaling in prostate and breast cancer, respectively. The AR and ER are stimulated by sex hormones and function as transcription factors to regulate genes involved in cell cycle progression, metabolism, and other cellular functions that contribute to oncogenesis. Recent structural studies of the AR/p300 and ER/p300 complexes have provided critical insights into the mechanism by which p300 interacts with and activates AR- and ER-mediated transcription. Breast and prostate cancer rank the first and forth respectively in cancer diagnoses worldwide and effective treatments are urgently needed. Recent efforts have identified specific and potent CBP/p300 inhibitors that target the acetyltransferase activity and the acetytllysine-binding bromodomain (BD) of CBP/p300. These compounds inhibit AR signaling and tumor growth in prostate cancer. CBP/p300 inhibitors may also be applicable for treating breast and other hormone-dependent cancers. Here we provide an in-depth account of the critical roles of CBP/p300 in regulating the AR and ER signaling pathways and discuss the potential of CBP/p300 inhibitors for treating prostate and breast cancer.

Patient-Derived Xenograft Engraftment and Breast Cancer Outcomes in a Prospective Neoadjuvant Study (BEAUTY)

PURPOSE

Patient-derived xenografts (PDX) are a research tool for studying cancer biology and drug response phenotypes. While engraftment rates are higher for tumors with more aggressive characteristics, it is uncertain whether engraftment is prognostic for cancer recurrence.

PATIENTS AND METHODS

In a prospective study of patients with breast cancer treated with neoadjuvant chemotherapy (NAC) with taxane ± trastuzumab followed by anthracycline-based chemotherapy, we report the association between breast cancer events and PDX engraftment using tumors derived from treatment naïve (pre-NAC biopsies from 113 patients) and treatment resistant (post-NAC at surgery from 34 patients). Gray test was used to assess whether the cumulative incidence of a breast cancer event differs with respect to either pre-NAC PDX engraftment or post-NAC PDX engraftment.

RESULTS

With a median follow-up of 5.7 years, the cumulative incidence of breast cancer relapse did not differ significantly according to pre-NAC PDX engraftment (5-year rate: 13.6% vs. 13.4%; P = 0.89). However, the incidence of a breast event was greater for patients with post-NAC PDX engraftment (5-year rate: 50.0% vs. 19.6%), but this did not achieve significance (P = 0.11).

CONCLUSIONS

In treatment-naïve breast cancer receiving standard NAC, PDX engraftment was not prognostic for breast cancer recurrence. Further study is needed to establish whether PDX engraftment in the treatment-resistant setting is prognostic for cancer recurrence.

Optimally designed theranostic system based folic acids and chitosan as a promising mucoadhesive delivery system for encapsulating curcumin LbL nano-template against invasiveness of breast cancer

Curcumin is a potential candidate in cancer therapy due to its ability to inhibit many signalling pathways at the same time of exposure because of its unique content of aromatic ring, B diketone, olefinic linker, and O methoxy phenolic groups. Its applications in biomedical therapy is limited because of its sensitivity, and its rapid degradation. In the current study, curcumin inserted into polyelectrolyte pairs (protamine and dextran) and then was functionalized by folic acid conjugated chitosan used for the first time, as theranostic system. Such this strategy allows to improve its mucoadhesion and penetration that increases their accumulation inside cancer cells. CUR-LbL NPs were then used to investigate drug release inside Human Mammary Carcinoma (MCF-7 cell lines) after their incubations for 3 h, 6 h and 24 h. Flow cytometry indicated that the percentages of apoptosis, necrosis and cell cycle arrest were increased significantly in MCF-7 cell lines treated by CUR-LbL NPs. Furthermore, SEM image showed many debris in the section of MCF-7 treated by CUR-LbL NPs. Here, it can be summarized that curcumin functionalized by multi-layered polyelectrolyte capsules can be used as a model to study the fate of the adsorbed nanocarriers and to investigate the drug release inside cells.

Patient-Derived Xenograft Models in Breast Cancer Research

Patient-derived xenograft (PDX) model can be used as a platform to study the individual patient's sensitivity to targeted agents as well as its ability to guide our understanding in various aspects of tumor biology including the tumor's clonal evolution and interaction with microenvironment. In this chapter, we review the history of PDX models in various tumor types. Additionally, we highlight the key studies that suggested potential value of PDX models in cancer treatment. Specifically, we will briefly introduce several studies on the issue of PDX models for precision medicine. In latter part of this chapter, we focus on the studies that used PDX models to investigate the molecular biology of breast cancer that underlies the process of drug resistance and tumor metastasis. Also, we will address our own experience in developing PDX models using breast cancer tissues from Korean breast cancer patients.

Design and synthesis of novel benzothiophene analogs as selective estrogen receptor covalent antagonists against breast cancer

Endocrine therapy (ET) has benefited patients with estrogen receptor alpha (ERα) positive breast cancer for decades. Selective estrogen receptor modulator (SERM) such as Tamoxifen represents the clinical standard of care (SoC). Despite the therapeutic importance of current SoC agents, 30-50% of prolonged treatment patients inevitably generated resistant tumor cells, usually eventually suffered tumor relapse and developed into metastatic breast cancer (MBC), which was the leading cause of female cancer-related mortality. Among these, most resistant tumors remained dependent on ERα signaling, which reignited the need for the next generation of ERα related agents. We hypothesized that selective estrogen receptor covalent antagonists targeting ERα would provide a therapeutic alternative. In the current work, series of novel benzothiophene hybrids bearing electrophile moieties were synthesized and biologically evaluated. The representative analogue 15c exhibited potent anti-proliferative effect in MCF-7 cell lines in vitro, and further mechanism studies confirmed the necessity of covalent bonding. More importantly, 15c could attenuate the expression of TFF-1, GREB-1 and downregulate the levels of cellular ERα protein.

High estrogen receptor alpha activation confers resistance to estrogen deprivation and is required for therapeutic response to estrogen in breast cancer

Estrogen receptor alpha (ER)-positive breast cancer is commonly treated with endocrine therapies, including antiestrogens that bind and inhibit ER activity, and aromatase inhibitors that suppress estrogen biosynthesis to inhibit estrogen-dependent ER activity. Paradoxically, treatment with estrogens such as 17b-estradiol can also be effective against ER+ breast cancer. Despite the known efficacy of estrogen therapy, the lack of a predictive biomarker of response and understanding of the mechanism of action have contributed to its limited clinical use. Herein, we demonstrate that ER overexpression confers resistance to estrogen deprivation through ER activation in human ER+ breast cancer cells and xenografts grown in mice. However, ER overexpression and the associated high levels of ER transcriptional activation converted 17b-estradiol from a growth-promoter to a growth-suppressor, offering a targetable therapeutic vulnerability and a potential means of identifying patients likely to benefit from estrogen therapy. Since ER+ breast cancer cells and tumors ultimately developed resistance to continuous estrogen deprivation or continuous 17b-estradiol treatment, we tested schedules of alternating treatments. Oscillation of ER activity through cycling of 17b-estradiol and estrogen deprivation provided long-term control of patient-derived xenografts, offering a novel endocrine-only strategy to manage ER+ breast cancer.

Preexisting Somatic Mutations of Estrogen Receptor Alpha (ESR1) in Early-Stage Primary Breast Cancer

Background

More than three-quarters of primary breast cancers are positive for estrogen receptor alpha (ER; encoded by the gene ESR1), the most important factor for directing anti-estrogenic endocrine therapy (ET). Recently, mutations in ESR1 were identified as acquired mechanisms of resistance to ET, found in 12% to 55% of metastatic breast cancers treated previously with ET.

Methods

We analyzed 3217 population-based invasive primary (nonmetastatic) breast cancers (within the SCAN-B study, ClinicalTrials.gov NCT02306096), sampled from initial diagnosis prior to any treatment, for the presence of ESR1 mutations using RNA sequencing. Mutations were verified by droplet digital polymerase chain reaction on tumor and normal DNA. Patient outcomes were analyzed using Kaplan-Meier estimation and a series of 2-factor Cox regression multivariable analyses.

Results

We identified ESR1 resistance mutations in 30 tumors (0.9%), of which 29 were ER positive (1.1%). In ET-treated disease, presence of ESR1 mutation was associated with poor relapse-free survival and overall survival (2-sided log-rank test P < .001 and P = .008, respectively), with hazard ratios of 3.00 (95% confidence interval = 1.56 to 5.88) and 2.51 (95% confidence interval = 1.24 to 5.07), respectively, which remained statistically significant when adjusted for other prognostic factors.

Conclusions

These population-based results indicate that ESR1 mutations at diagnosis of primary breast cancer occur in about 1% of women and identify for the first time in the adjuvant setting that such preexisting mutations are associated to eventual resistance to standard hormone therapy. If replicated, tumor ESR1 screening should be considered in ER-positive primary breast cancer, and for patients with mutated disease, ER degraders such as fulvestrant or other therapeutic options may be considered as more appropriate.

Chromatin conformation capture (Hi-C) sequencing of patient-derived xenografts: analysis guidelines

BACKGROUND

Sequencing of patient-derived xenograft (PDX) mouse models allows investigation of the molecular mechanisms of human tumor samples engrafted in a mouse host. Thus, both human and mouse genetic material is sequenced. Several methods have been developed to remove mouse sequencing reads from RNA-seq or exome sequencing PDX data and improve the downstream signal. However, for more recent chromatin conformation capture technologies (Hi-C), the effect of mouse reads remains undefined.

RESULTS

We evaluated the effect of mouse read removal on the quality of Hi-C data using in silico created PDX Hi-C data with 10% and 30% mouse reads. Additionally, we generated 2 experimental PDX Hi-C datasets using different library preparation strategies. We evaluated 3 alignment strategies (Direct, Xenome, Combined) and 3 pipelines (Juicer, HiC-Pro, HiCExplorer) on Hi-C data quality.

CONCLUSIONS

Removal of mouse reads had little-to-no effect on data quality as compared with the results obtained with the Direct alignment strategy. Juicer extracted more valid chromatin interactions for Hi-C matrices, regardless of the mouse read removal strategy. However, the pipeline effect was minimal, while the library preparation strategy had the largest effect on all quality metrics. Together, our study presents comprehensive guidelines on PDX Hi-C data processing.

The bone microenvironment increases phenotypic plasticity of ER+ breast cancer cells

Estrogen receptor-positive (ER+) breast cancer exhibits a strong bone tropism in metastasis. How the bone microenvironment (BME) impacts ER signaling and endocrine therapy remains poorly understood. Here, we discover that the osteogenic niche transiently and reversibly reduces ER expression and activities specifically in bone micrometastases (BMMs), leading to endocrine resistance. As BMMs progress, the ER reduction and endocrine resistance may partially recover in cancer cells away from the osteogenic niche, creating phenotypic heterogeneity in macrometastases. Using multiple approaches, including an evolving barcoding strategy, we demonstrated that this process is independent of clonal selection, and represents an EZH2-mediated epigenomic reprogramming. EZH2 drives ER+ BMMs toward a basal and stem-like state. EZH2 inhibition reverses endocrine resistance. These data exemplify how epigenomic adaptation to BME promotes phenotypic plasticity of metastatic seeds, fosters intra-metastatic heterogeneity, and alters therapeutic responses. Our study provides insights into the clinical enigma of ER+ metastatic recurrences despite endocrine therapies.

Proteogenomic and metabolomic characterization of human glioblastoma

Glioblastoma (GBM) is the most aggressive nervous system cancer. Understanding its molecular pathogenesis is crucial to improving diagnosis and treatment. Integrated analysis of genomic, proteomic, post-translational modification and metabolomic data on 99 treatment-naive GBMs provides insights to GBM biology. We identify key phosphorylation events (e.g., phosphorylated PTPN11 and PLCG1) as potential switches mediating oncogenic pathway activation, as well as potential targets for EGFR-, TP53-, and RB1-altered tumors. Immune subtypes with distinct immune cell types are discovered using bulk omics methodologies, validated by snRNA-seq, and correlated with specific expression and histone acetylation patterns. Histone H2B acetylation in classical-like and immune-low GBM is driven largely by BRDs, CREBBP, and EP300. Integrated metabolomic and proteomic data identify specific lipid distributions across subtypes and distinct global metabolic changes in IDH-mutated tumors. This work highlights biological relationships that could contribute to stratification of GBM patients for more effective treatment.

Functional Characterization of Circulating Tumor Cells (CTCs) from Metastatic ER+/HER2- Breast Cancer Reveals Dependence on HER2 and FOXM1 for Endocrine Therapy Resistance and Tumor Cell Survival: Implications for Treatment of ER+/HER2- Breast Cancer

Simple Summary

Acquired endocrine resistance and late recurrence in patients with ER+/HER2− breast cancer are complex and not fully understood. Here, we evaluated mechanisms of acquired resistance in circulating tumor cells (CTCs) from an ER+/HER2− breast cancer patient who initially responded but later progressed under endocrine treatment. We found a switch from ERα-dependent to HER2-dependent and ERα-independent expression of FOXM1, which may enable disseminated ER+/HER2− cells to re-initiate tumor cell growth and metastasis formation in the presence of endocrine treatment. We found that NFkB signaling sustains HER2 and FOXM1 expression in CTCs in the presence of ERα inhibitors suggesting that NFkB and FOXM1 might be an efficient therapeutic approach to prevent late recurrence and to treat endocrine resistance. Collectively our data show that CTCs from patients with endocrine resistance allow mechanisms of acquired endocrine resistance to be delineated, and can be used to test potential drug regimens for combatting resistance.

Abstract

Mechanisms of acquired endocrine resistance and late recurrence in patients with ER+/HER2− breast cancer are complex and not fully understood. Here, we evaluated mechanisms of acquired resistance in circulating tumor cells (CTCs) from an ER+/HER2− breast cancer patient who initially responded but later progressed under endocrine treatment. We found a switch from ERα-dependent to HER2-dependent and ERα-independent expression of FOXM1, which may enable disseminated ER+/HER2− cells to re-initiate tumor cell growth and metastasis formation in the presence of endocrine treatment. Our results also suggest a role for HER2 in resistance, even in ER+ breast cancer cells that have neither HER2 amplification nor activating HER2 mutations. We found that NFkB signaling sustains HER2 and FOXM1 expression in CTCs in the presence of ERα inhibitors. Inhibition of NFkB signaling blocked expression of HER2 and FOXM1 in the CTCs, and induced apoptosis. Thus, targeting of NFkB and FOXM1 might be an efficient therapeutic approach to prevent late recurrence and to treat endocrine resistance. Collectively our data show that CTCs from patients with endocrine resistance allow mechanisms of acquired endocrine resistance to be delineated, and can be used to test potential drug regimens for combatting resistance.

Advances in Rodent Models for Breast Cancer Formation, Progression, and Therapeutic Testing

Breast cancer is a highly complicated disease. Advancement in the treatment and prevention of breast cancer lies in elucidation of the mechanism of carcinogenesis and progression. Rodent models of breast cancer have developed into premier tools for investigating the mechanisms and genetic pathways in breast cancer progression and metastasis and for developing and evaluating clinical therapeutics. Every rodent model has advantages and disadvantages, and the selection of appropriate rodent models with which to investigate breast cancer is a key decision in research. Design of a suitable rodent model for a specific research purpose is based on the integration of the advantages and disadvantages of different models. Our purpose in writing this review is to elaborate on various rodent models for breast cancer formation, progression, and therapeutic testing.

Significant impact of circulating tumour DNA mutations on survival in metastatic breast cancer patients

Mutational analysis of circulating tumour (ct) DNA holds promise as an effective tool to predict the course of metastatic breast cancer (MBC). In the present study we used targeted next generation sequencing of ctDNA to evaluate the impact of cancer driven mutations on the prognosis of MBC. The study included 59 oestrogen receptor-positive (ER+), HER2-negative MBC patients. Sequencing analysis was performed in ESR1, PIK3CA, ERBB2, PTEN, TP53, KRAS, HRAS, NRAS, and AR. At baseline, patients started receiving either chemotherapy (34%; n = 20) or cyclin-dependent kinase 4/6 inhibitor therapy in combination with endocrine therapy (CDK4/6i+ET; 66%; n = 39). Overall, 64.4% (n = 38) of the patients carried at least one pathogenic or likely-pathogenic mutation. Number of ctDNA mutations was significantly linked with worse progression free survival (PFS; p = 0.003) and overall survival (OS; p = 0.007). Furthermore, ctDNA load, defined by the number of mutant ctDNA molecules per mL plasma, significantly correlated with PFS (p < 0.001) and OS (p = 0.001). Furthermore, mutational status of ESR1 and TP53 significantly predicted PFS (p = 0.024 and p = 0.035, respectively) and OS (p < 0.001 and p = 0.035, respectively). These results emphasizes the clinical value of ctDNA mutational analysis in the management of advanced breast cancer.

Laboratory Models for Investigating Breast Cancer Therapy Resistance and Metastasis

While numerous therapies are highly efficacious in early-stage breast cancers and in particular subsets of breast cancers, therapeutic resistance and metastasis unfortunately arise in many patients. In many cases, tumors that are resistant to standard of care therapies, as well as tumors that have metastasized, are treatable but incurable with existing clinical strategies. Both therapy resistance and metastasis are multi-step processes during which tumor cells must overcome diverse environmental and selective hurdles. Mechanisms by which tumor cells achieve this are numerous and include acquisition of invasive and migratory capabilities, cell-intrinsic genetic and/or epigenetic adaptations, clonal selection, immune evasion, interactions with stromal cells, entering a state of dormancy or senescence, and maintaining self-renewal capacity. To overcome therapy resistance and metastasis in breast cancer, the ability to effectively model each of these mechanisms in the laboratory is essential. Herein we review historic and the current state-of-the-art laboratory model systems and experimental approaches used to investigate breast cancer metastasis and resistance to standard of care therapeutics. While each model system has inherent limitations, they have provided invaluable insights, many of which have translated into regimens undergoing clinical evaluation. We will discuss the limitations and advantages of a variety of model systems that have been used to investigate breast cancer metastasis and therapy resistance and outline potential strategies to improve experimental modeling to further our knowledge of these processes, which will be crucial for the continued development of effective breast cancer treatments.

Targeting ACSS2 with a Transition-State Mimetic Inhibits Triple-Negative Breast Cancer Growth

Acetyl-CoA is a vitally important and versatile metabolite used for many cellular processes including fatty acid synthesis, ATP production, and protein acetylation. Recent studies have shown that cancer cells upregulate acetyl-CoA synthetase 2 (ACSS2), an enzyme that converts acetate to acetyl-CoA, in response to stresses such as low nutrient availability and hypoxia. Stressed cancer cells use ACSS2 as a means to exploit acetate as an alternative nutrient source. Genetic depletion of ACSS2 in tumors inhibits the growth of a wide variety of cancers. However, there are no studies on the use of an ACSS2 inhibitor to block tumor growth. In this study, we synthesized a small-molecule inhibitor that acts as a transition-state mimetic to block ACSS2 activity in vitro and in vivo. Pharmacologic inhibition of ACSS2 as a single agent impaired breast tumor growth. Collectively, our findings suggest that targeting ACSS2 may be an effective therapeutic approach for the treatment of patients with breast cancer. SIGNIFICANCE: These findings suggest that targeting acetate metabolism through ACSS2 inhibitors has the potential to safely and effectively treat a wide range of patients with cancer.

SPA: A Quantitation Strategy for MS Data in Patient-derived Xenograft Models

With the development of mass spectrometry (MS)-based proteomics technologies, patient-derived xenograft (PDX), which is generated from the primary tumor of a patient, is widely used for the proteome-wide analysis of cancer mechanism and biomarker identification of a drug. However, the proteomics data interpretation is still challenging due to complex data deconvolution from the PDX sample that is a cross-species mixture of human cancerous tissues and immunodeficient mouse tissues. In this study, by using the lab-assembled mixture of human and mouse cells with different mixing ratios as a benchmark, we developed and evaluated a new method, SPA (shared peptide allocation), for protein quantitation by considering the unique and shared peptides of both species. The results showed that SPA could provide more convenient and accurate protein quantitation in human–mouse mixed samples. Further validation on a pair of gastric PDX samples (one bearing FGFR2 amplification while the other one not) showed that our new method not only significantly improved the overall protein identification, but also detected the differential phosphorylation of FGFR2 and its downstream mediators (such as RAS and ERK) exclusively. The tool pdxSPA is freely available at https://github.com/Li-Lab-Proteomics/pdxSPA.

Molecular Biomarkers for Contemporary Therapies in Hormone Receptor-Positive Breast Cancer

Systemic treatment of hormone receptor-positive (HR+) breast cancer is undergoing a renaissance, with a number of targeted therapies including CDK4/6, mTOR, and PI3K inhibitors now approved for use in combination with endocrine therapies. The increased use of targeted therapies has changed the natural history of HR+ breast cancers, with the emergence of new escape mechanisms leading to the inevitable progression of disease in patients with advanced cancers. The identification of new predictive and pharmacodynamic biomarkers to current standard-of-care therapies and discovery of new therapies is an evolving and urgent clinical challenge in this setting. While traditional, routinely measured biomarkers such as estrogen receptors (ERs), progesterone receptors (PRs), and human epidermal growth factor receptor 2 (HER2) still represent the best prognostic and predictive biomarkers for HR+ breast cancer, a significant proportion of patients either do not respond to endocrine therapy or develop endocrine resistant disease. Genomic tests have emerged as a useful adjunct prognostication tool and guide the addition of chemotherapy to endocrine therapy. In the treatment-resistant setting, mutational profiling has been used to identify ESR1, PIK3CA, and AKT mutations as predictive molecular biomarkers to newer therapies. Additionally, pharmacodynamic biomarkers are being increasingly used and considered in the metastatic setting. In this review, we summarise the current state-of-the-art therapies; prognostic, predictive, and pharmacodynamic molecular biomarkers; and how these are impacted by emerging therapies for HR+ breast cancer.

Modulating HSF1 levels impacts expression of the estrogen receptor α and antiestrogen response

This work shows that activation of the main cellular stress response pathway is responsible for antiestrogen resistance in breast cancer, a process that is reversible.

Master transcription factors control the transcriptional program and are essential to maintain cellular functions. Among them, steroid nuclear receptors, such as the estrogen receptor α (ERα), are central to the etiology of hormone-dependent cancers which are accordingly treated with corresponding endocrine therapies. However, resistance invariably arises. Here, we show that high levels of the stress response master regulator, the heat shock factor 1 (HSF1), are associated with antiestrogen resistance in breast cancer cells. Indeed, overexpression of HSF1 leads to ERα degradation, decreased expression of ERα-activated genes, and antiestrogen resistance. Furthermore, we demonstrate that reducing HSF1 levels reinstates expression of the ERα and restores response to antiestrogens. Last, our results establish a proof of concept that inhibition of HSF1, in combination with antiestrogens, is a valid strategy to tackle resistant breast cancers. Taken together, we are proposing a mechanism where high HSF1 levels interfere with the ERα-dependent transcriptional program leading to endocrine resistance in breast cancer.

3D Functional Genomics Screens Identify CREBBP as a Targetable Driver in Aggressive Triple-Negative Breast Cancer

Triple-negative breast cancers (TNBC) are resistant to standard-of-care chemotherapy and lack known targetable driver gene alterations. Identification of novel drivers could aid the discovery of new treatment strategies for this hard-to-treat patient population, yet studies using high-throughput and accurate models to define the functions of driver genes in TNBC to date have been limited. Here, we employed unbiased functional genomics screening of the 200 most frequently mutated genes in breast cancer, using spheroid cultures to model in vivo-like conditions, and identified the histone acetyltransferase CREBBP as a novel tumor suppressor in TNBC. CREBBP protein expression in patient tumor samples was absent in 8% of TNBCs and at a high frequency in other tumors, including squamous lung cancer, where CREBBP-inactivating mutations are common. In TNBC, CREBBP alterations were associated with higher genomic heterogeneity and poorer patient survival and resulted in upregulation and dependency on a FOXM1 proliferative program. Targeting FOXM1-driven proliferation indirectly with clinical CDK4/6 inhibitors (CDK4/6i) selectively impaired growth in spheroids, cell line xenografts, and patient-derived models from multiple tumor types with CREBBP mutations or loss of protein expression. In conclusion, we have identified CREBBP as a novel driver in aggressive TNBC and identified an associated genetic vulnerability in tumor cells with alterations in CREBBP and provide a preclinical rationale for assessing CREBBP alterations as a biomarker of CDK4/6i response in a new patient population. SIGNIFICANCE: This study demonstrates that CREBBP genomic alterations drive aggressive TNBC, lung cancer, and lymphomas and may be selectively treated with clinical CDK4/6 inhibitors.

Targeting transcription of MCL-1 sensitizes HER2-amplified breast cancers to HER2 inhibitors

Human epidermal growth factor receptor 2 gene (HER2) is focally amplified in approximately 20% of breast cancers. HER2 inhibitors alone are not effective, and sensitizing agents will be necessary to move away from a reliance on heavily toxic chemotherapeutics. We recently demonstrated that the efficacy of HER2 inhibitors is mitigated by uniformly low levels of the myeloid cell leukemia 1 (MCL-1) endogenous inhibitor, NOXA. Emerging clinical data have demonstrated that clinically advanced cyclin-dependent kinase (CDK) inhibitors are effective MCL-1 inhibitors in patients, and, importantly, well tolerated. We, therefore, tested whether the CDK inhibitor, dinaciclib, could block MCL-1 in preclinical HER2-amplified breast cancer models and therefore sensitize these cancers to dual HER2/EGFR inhibitors neratinib and lapatinib, as well as to the novel selective HER2 inhibitor tucatinib. Indeed, we found dinaciclib suppresses MCL-1 RNA and is highly effective at sensitizing HER2 inhibitors both in vitro and in vivo. This combination was tolerable in vivo. Mechanistically, liberating the effector BCL-2 protein, BAK, from MCL-1 results in robust apoptosis. Thus, clinically advanced CDK inhibitors may effectively combine with HER2 inhibitors and present a chemotherapy-free therapeutic strategy in HER2-amplified breast cancer, which can be tested immediately in the clinic.

FGFR4 regulates tumor subtype differentiation in luminal breast cancer and metastatic disease

Mechanisms driving tumor progression from less aggressive subtypes to more aggressive states represent key targets for therapy. We identified a subset of luminal A primary breast tumors that give rise to HER2-enriched (HER2E) subtype metastases, but remain clinically HER2 negative (cHER2-). By testing the unique genetic and transcriptomic features of these cases, we developed the hypothesis that FGFR4 likely participates in this subtype switching. To evaluate this, we developed 2 FGFR4 genomic signatures using a patient-derived xenograft (PDX) model treated with an FGFR4 inhibitor, which inhibited PDX growth in vivo. Bulk tumor gene expression analysis and single-cell RNA sequencing demonstrated that the inhibition of FGFR4 signaling caused molecular switching. In the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) breast cancer cohort, FGFR4-induced and FGFR4-repressed signatures each predicted overall survival. Additionally, the FGFR4-induced signature was an independent prognostic factor beyond subtype and stage. Supervised analysis of 77 primary tumors with paired metastases revealed that the FGFR4-induced signature was significantly higher in luminal/ER+ tumor metastases compared with their primaries. Finally, multivariate analysis demonstrated that the FGFR4-induced signature also predicted site-specific metastasis for lung, liver, and brain, but not for bone or lymph nodes. These data identify a link between FGFR4-regulated genes and metastasis, suggesting treatment options for FGFR4-positive patients, whose high expression is not caused by mutation or amplification.

Therapeutic Targeting of Nemo-like Kinase in Primary and Acquired Endocrine-resistant Breast Cancer

PURPOSE

Endocrine resistance remains a major clinical challenge in estrogen receptor (ER)-positive breast cancer. Despite the encouraging results from clinical trials for the drugs targeting known survival signaling, relapse is still inevitable. There is an unmet need to discover new drug targets in the unknown escape pathways. Here, we report Nemo-like kinase (NLK) as a new actionable kinase target that endows previously uncharacterized survival signaling in endocrine-resistant breast cancer.

EXPERIMENTAL DESIGN

The effects of NLK inhibition on the viability of endocrine-resistant breast cancer cell lines were examined by MTS assay. The effect of VX-702 on NLK activity was verified by kinase assay. The modulation of ER and its coactivator, SRC-3, by NLK was examined by immunoprecipitation, kinase assay, luciferase assay, and RNA sequencing. The therapeutic effects of VX-702 and everolimus were tested on cell line- and patient-derived xenograft (PDX) tumor models.

RESULTS

NLK overexpression endows reduced endocrine responsiveness and is associated with worse outcome of patients treated with tamoxifen. Mechanistically, NLK may function, at least in part, via enhancing the phosphorylation of ERα and its key coactivator, SRC-3, to modulate ERα transcriptional activity. Through interrogation of a kinase profiling database, we uncovered and verified a highly selective dual p38/NLK inhibitor, VX-702. Coadministration of VX-702 with the mTOR inhibitor, everolimus, demonstrated a significant therapeutic effect in cell line-derived xenograft and PDX tumor models of acquired or de novo endocrine resistance.

CONCLUSIONS

Together, this study reveals the potential of therapeutic modulation of NLK for the management of the endocrine-resistant breast cancers with active NLK signaling.

Hormonal modulation of ESR1 mutant metastasis

Estrogen receptor alpha gene (ESR1) mutations occur frequently in ER-positive metastatic breast cancer, and confer clinical resistance to aromatase inhibitors. Expression of the ESR1 Y537S mutation induced an epithelial-mesenchymal transition (EMT) with cells exhibiting enhanced migration and invasion potential in vitro. When small subpopulations of Y537S ESR1 mutant cells were injected along with WT parental cells, tumor growth was enhanced with mutant cells becoming the predominant population in distant metastases. Y537S mutant primary xenograft tumors were resistant to the antiestrogen tamoxifen (Tam) as well as to estradiol (E2) withdrawal. Y537S ESR1 mutant primary tumors metastasized efficiently in the absence of E2; however, Tam treatment significantly inhibited metastasis to distant sites. We identified a nine-gene expression signature, which predicted clinical outcomes of ER-positive breast cancer patients, as well as breast cancer metastasis to the lung. Androgen receptor (AR) protein levels were increased in mutant models, and the AR agonist dihydrotestosterone significantly inhibited estrogen-regulated gene expression, EMT, and distant metastasis in vivo, suggesting that AR may play a role in distant metastatic progression of ESR1 mutant tumors.

Overcoming oncogene addiction in breast and prostate cancers: a comparative mechanistic overview

Prostate cancer (PCa) and breast cancer (BCa) are both hormone-dependent cancers that require the androgen receptor (AR) and estrogen receptor (ER, ESR1) for growth and proliferation, respectively. Endocrine therapies that target these nuclear receptors (NRs) provide significant clinical benefit for metastatic patients. However, these therapeutic strategies are seldom curative and therapy resistance is prevalent. Because the vast majority of therapy-resistant PCa and BCa remain dependent on the augmented activity of their primary NR driver, common mechanisms of resistance involve enhanced NR signaling through overexpression, mutation, or alternative splicing of the receptor, coregulator alterations, and increased intracrine hormonal synthesis. In addition, a significant subset of endocrine therapy-resistant tumors become independent of their primary NR and switch to alternative NR or transcriptional drivers. While these hormone-dependent cancers generally employ similar mechanisms of endocrine therapy resistance, distinct differences between the two tumor types have been observed. In this review, we compare and contrast the most frequent mechanisms of antiandrogen and antiestrogen resistance, and provide potential therapeutic strategies for targeting both advanced PCa and BCa.

Hyaluronan-Conjugated Carbon Quantum Dots for Bioimaging Use

This work demonstrates the application of hyaluronan-conjugated nitrogen-doped carbon quantum dots (HA-nCQDs) for bioimaging of tumor cells and illustrates their potential use as carriers in targeted drug delivery. Quantum dots are challenging to deliver with specificity, which hinders their application. To facilitate targeted internalization by cancer cells, hyaluronic acid, a natural ligand of CD44 receptors, was covalently grafted on nCQDs. The HA-nCQD conjugate was synthesized by carbodiimide coupling of the amine moieties on nCQDs and the carboxylic acids on HA chains. Conjugated HA-nCQD retained sufficient fluorescence, although with 30% lower quantum efficiency than the original nCQDs. Confocal microscopy showed enhanced internalization of HA-nCQDs, facilitated by CD44 receptors. To demonstrate the specificity of HA-nCQDs toward human tumor cells, patient-derived breast cancer tissue with high-CD44 expression was implanted in adult mice. The tumors were allowed to grow up to 200-250 mm³ prior to the injection of HA-nCQDs. With either local or systemic injection, we achieved a high level of tumor specificity judged by a strong signal-to-noise ratio between the tumor and the surrounding tissue in vivo. Overall, the results show that HA-nCQDs can be used for imaging of CD44-specific tumors in preclinical models of human cancer and potentially used as carriers for targeted drug delivery into CD44-rich cells.

A Closer Look at Estrogen Receptor Mutations in Breast Cancer and Their Implications for Estrogen and Antiestrogen Responses

Breast cancer (BC) is the most common cancer among women worldwide. More than 70% of BC cases express estrogen receptor alpha (ERα), a central transcription factor that stimulates the proliferation of breast cancer cells, usually in the presence of estrogen. While most cases of ER-positive BC initially respond to antiestrogen therapies, a high percentage of cases develop resistance to treatment over time. The recent discovery of mutated forms of ERα that result in constitutively active forms of the receptor in the metastatic-resistance stage of BC has provided a strong rationale for the development of new antiestrogens. These molecules targeting clinically relevant ERα mutants and a combination with other pharmacological inhibitors of specific pathways may constitute alternative treatments to improve clinical practice in the fight against metastatic-resistant ER-positive BC. In this review, we summarize the latest advances regarding the particular involvement of point mutations of ERα in endocrine resistance. We also discuss the involvement of synonymous ERα mutations with respect to co-translational folding of the receptor and ribosome biogenesis in breast carcinogenesis.

Bea A.58de JongSteven58KralovaPetra59SedlacekRadislav59ClaeysElisa60LeucciEleonora60BorsaniMassimiliano61LanfranconeLuisa61PelicciPier Giuseppe61MælandsmoGunhild Mari62NorumJens Henrik62VinoloEmilie63. Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts

Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment and propagation, affecting the accuracy of PDX modeling of human cancer. Here, we exhaustively analyze copy number alterations (CNAs) in 1,451 PDX and matched patient tumor (PT) samples from 509 PDX models. CNA inferences based on DNA sequencing and microarray data displayed substantially higher resolution and dynamic range than gene expression-based inferences, and they also showed strong CNA conservation from PTs through late-passage PDXs. CNA recurrence analysis of 130 colorectal and breast PT/PDX-early/PDX-late trios confirmed high-resolution CNA retention. We observed no significant enrichment of cancer-related genes in PDX-specific CNAs across models. Moreover, CNA differences between patient and PDX tumors were comparable to variations in multiregion samples within patients. Our study demonstrates the lack of systematic copy number evolution driven by the PDX mouse host.

Practical consensus recommendations regarding the use of hormonal therapy in metastatic breast cancer

Metastatic breast cancer (MBC) is cancer that has spread from the breast to another part of the body or has come back in another distant location. Treatment options for MBC depend on several factors. One of these factors is the levels of hormone receptors (HRs) in the tumor. Cancers with high levels of HRs, called HR-positive, use the hormones estrogen and progesterone to grow and spread. Hormonal therapy is a type of treatment specifically for HR-positive breast cancer. This expert group used data from published literature, practical experience and opinion of a large group of academic oncologists to arrive at these practical consensus recommendations in regards with the use of hormonal therapy and the management of HR-positive MBC for the benefit of community oncologists.

Proteomic Resistance Biomarkers for PI3K Inhibitor in Triple Negative Breast Cancer Patient-Derived Xenograft Models

Simple Summary

The objective of this study is to identify potential proteomic biomarkers in triple negative breast cancer (TNBC) that associate with response to PI3K inhibitors which are in clinical trials. We tested a panel of TNBC patient-derived xenograft (PDX) models for their tumor growth response to a pan-PI3K inhibitor, BKM120. Proteomic analyses by reverse phase protein array (RPPA) of 182 markers were performed on baseline and post short-term treatment PDX samples, to correlate with tumor growth response. We identified several baseline and treatment induced proteomic biomarkers in association with resistance. These results provide important insights for the development of PI3K inhibitors in TNBC.

Abstract

PI3K pathway activation is frequently observed in triple negative breast cancer (TNBC). However, single agent PI3K inhibitors have shown limited anti-tumor activity. To investigate biomarkers of response and resistance mechanisms, we tested 17 TNBC patient-derived xenograft (PDX) models representing diverse genomic backgrounds and varying degrees of PI3K pathway signaling activities for their tumor growth response to the pan-PI3K inhibitor, BKM120. Baseline and post-treatment PDX tumors were subjected to reverse phase protein array (RPPA) to identify protein markers associated with tumor growth response. While BKM120 consistently reduced PI3K pathway activity, as demonstrated by reduced levels of phosphorylated AKT, percentage tumor growth inhibition (%TGI) ranged from 35% in the least sensitive to 84% in the most sensitive model. Several biomarkers showed significant association with resistance, including elevated baseline levels of growth factor receptors (EGFR, pHER3 Y1197), PI3Kp85 regulatory subunit, anti-apoptotic protein BclXL, EMT (Vimentin, MMP9, IntegrinaV), NFKB pathway (IkappaB, RANKL), and intracellular signaling molecules including Caveolin, CBP, and KLF4, as well as treatment-induced increases in the levels of phosphorylated forms of Aurora kinases. Interestingly, increased AKT phosphorylation or PTEN loss at baseline were not significantly correlated to %TGI. These results provide important insights into biomarker development for PI3K inhibitors in TNBC.

Targeting transcription factors in cancer drug discovery

Cancer drug discovery is currently dominated by clinical trials or clinical research. Several potential drug candidates have been brought into the pipeline of drug discovery after showing very promising results at the pre-clinical level and are waiting to be tested in human clinical trials. Interestingly, among the potential drug candidates, a few of them have targeted transcription factors highlighting the fundamental undruggable nature of these molecules. However, using advanced technologies, researchers were recently successful in partly unlocking this undruggable nature, which was considered as a ‘grey area’ in the early days of drug discovery, and as a result, several potential candidates have emerged recently. The purpose of the review is to highlight some of the recently reported studies of targeting transcription factors in cancer and their promising outcomes.

Methodological Advancements for Investigating Intra-tumoral Heterogeneity in Breast Cancer at the Bench and Bedside

There is a major need to overcome therapeutic resistance and metastasis that eventually arises in many breast cancer patients. Therapy resistant and metastatic tumors are increasingly recognized to possess intra-tumoral heterogeneity (ITH), a diversity of cells within an individual tumor. First hypothesized in the 1970s, the possibility that this complex ITH may endow tumors with adaptability and evolvability to metastasize and evade therapies is now supported by multiple lines of evidence. Our understanding of ITH has been driven by recent methodological advances including next-generation sequencing, computational modeling, lineage tracing, single-cell technologies, and multiplexed in situ approaches. These have been applied across a range of specimens, including patient tumor biopsies, liquid biopsies, cultured cell lines, and mouse models. In this review, we discuss these approaches and how they have deepened our understanding of the mechanistic origins of ITH amongst tumor cells, including stem cell-like differentiation hierarchies and Darwinian evolution, and the functional role for ITH in breast cancer progression. While ITH presents a challenge for combating tumor evolution, in-depth analyses of ITH in clinical biopsies and laboratory models hold promise to elucidate therapeutic strategies that should ultimately improve outcomes for breast cancer patients.