Establishment of Patient-Derived Xenograft (PDX) Models of Human Breast Cancer

The progressive trend of modeling and drug screening systems of breast cancer bone metastasis

Bone metastasis is considered as a considerable challenge for breast cancer patients. Various in vitro and in vivo models have been developed to examine this occurrence. In vitro models are employed to simulate the intricate tumor microenvironment, investigate the interplay between cells and their adjacent microenvironment, and evaluate the effectiveness of therapeutic interventions for tumors. The endeavor to replicate the latency period of bone metastasis in animal models has presented a challenge, primarily due to the necessity of primary tumor removal and the presence of multiple potential metastatic sites.The utilization of novel bone metastasis models, including three-dimensional (3D) models, has been proposed as a promising approach to overcome the constraints associated with conventional 2D and animal models. However, existing 3D models are limited by various factors, such as irregular cellular proliferation, autofluorescence, and changes in genetic and epigenetic expression. The imperative for the advancement of future applications of 3D models lies in their standardization and automation. The utilization of artificial intelligence exhibits the capability to predict cellular behavior through the examination of substrate materials' chemical composition, geometry, and mechanical performance. The implementation of these algorithms possesses the capability to predict the progression and proliferation of cancer. This paper reviewed the mechanisms of bone metastasis following primary breast cancer. Current models of breast cancer bone metastasis, along with their challenges, as well as the future perspectives of using these models for translational drug development, were discussed.

RANK is a poor prognosis marker and a therapeutic target in ER-negative postmenopausal breast cancer

Despite strong preclinical data, the therapeutic benefit of the RANKL inhibitor, denosumab, in breast cancer patients, beyond the bone, is unclear. Aiming to select patients who may benefit from denosumab, we hereby analyzed RANK and RANKL protein expression in more than 2,000 breast tumors (777 estrogen receptor-negative, ER- ) from four independent cohorts. RANK protein expression was more frequent in ER- tumors, where it associated with poor outcome and poor response to chemotherapy. In ER- breast cancer patient-derived orthoxenografts (PDXs), RANKL inhibition reduced tumor cell proliferation and stemness, regulated tumor immunity and metabolism, and improved response to chemotherapy. Intriguingly, tumor RANK protein expression associated with poor prognosis in postmenopausal breast cancer patients, activation of NFKB signaling, and modulation of immune and metabolic pathways, suggesting that RANK signaling increases after menopause. Our results demonstrate that RANK protein expression is an independent biomarker of poor prognosis in postmenopausal and ER- breast cancer patients and support the therapeutic benefit of RANK pathway inhibitors, such as denosumab, in breast cancer patients with RANK+ ER- tumors after menopause.

NAD+ supplementation limits triple-negative breast cancer metastasis via SIRT1-P66Shc signaling

NAD⁺ levels decline with age and in certain disease conditions. NAD⁺ precursors have been shown to stimulate NAD⁺ biosynthesis and ameliorate various age-associated diseases in mouse models. However, NAD⁺ metabolism is complicated in cancer and its role in triple-negative breast cancer (TNBC) remains elusive. Here, we show that NAD⁺ supplement suppresses tumor metastasis in a TNBC orthotopic patient-derived xenograft (PDX) model. Sirtuin1 lysine deacetylase (SIRT1) is required for the effects since SIRT1 knockdown blocks NAD⁺-suppressed tumor metastasis. Overexpression of SIRT1 effectively impairs the metastatic potential of TNBC. Importantly, the interaction between SIRT1 and p66Shc causes the deacetylation and functional inactivation of p66Shc, which inhibits epithelial-mesenchymal transition (EMT). Overall, we demonstrate that NAD⁺ supplementation executes its anti-tumor function via activating the SIRT1-p66Shc axis, which highlights the preventive and therapeutic potential of SIRT1 activators as effective interventions for TNBC.

ncRNAs-mediated high expression of TIMM8A correlates with poor prognosis and act as an oncogene in breast cancer

Background

Breast cancer is notorious for its increasing incidence for decades. Ascending evidence has demonstrated that translocase of inner mitochondrial membrane (TIMM) proteins play vital roles in progression of several types of human cancer. However, the biological behaviors and molecular mechanisms of TIMM8A in breast cancer remain not fully illustrated.

Methods

Pan-cancer analysis was firstly performed for TIMM8A’s expression and prognosis by Oncomine database. Subsequently, TIMM8A-related noncoding RNAs (ncRNAs) were identified by a series of bioinformatics analyses and dual-luciferase reporter assay, including expression analysis, correlation analysis, and survival analysis. Moreover, the effect of TIMM8A on breast cancer proliferation and apoptosis was evaluated in vitro by CCK-8 assays, EdU cell proliferation assays, JC-1 mitochondrial membrane potential detection assays and Western blot assays and the in vivo effect was revealed through a patient-derived xenograft mouse model.

Results

We found that TIMM8A showed higher expression level in breast cancer and the higher TIMM8A mRNA expression group had a poorer prognosis than the lower TIMM8A group. hsa-circ-0107314/hsa-circ-0021867/hsa-circ-0122013 might be the three most potential upstream circRNAs of hsa-miR-34c-5p/hsa-miR-449a-TIMM8A axis in breast cancer. TIMM8A promotes proliferation of breast cancer cells in vitro and tumor growth in vivo.

Conclusion

Our results confirmed that ncRNAs-mediated upregulation of TIMM8A correlated with poor prognosis and act as an oncogene in breast cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02595-x.

Engineering complexity in human tissue models of cancer

Major progress in the understanding and treatment of cancer have tremendously improved our knowledge of this complex disease and improved the length and quality of patients' lives. Still, major challenges remain, in particular with respect to cancer metastasis which still escapes effective treatment and remains responsible for 90% of cancer related deaths. In recent years, the advances in cancer cell biology, oncology and tissue engineering converged into the engineered human tissue models of cancer that are increasingly recapitulating many aspects of cancer progression and response to drugs, in a patient-specific context. The complexity and biological fidelity of these models, as well as the specific questions they aim to investigate, vary in a very broad range. When selecting and designing these experimental models, the fundamental question is "how simple is complex enough" to accomplish a specific goal of cancer research. Here we review the state of the art in developing and using the human tissue models in cancer research and developmental drug screening. We describe the main classes of models providing different levels of biological fidelity and complexity, discuss their advantages and limitations, and propose a framework for designing an appropriate model for a given study. We close by outlining some of the current needs, opportunities and challenges in this rapidly evolving field.

HER2-specific chimeric antigen receptor-T cells for targeted therapy of metastatic colorectal cancer

Chimeric antigen receptor (CAR) - T cell therapy is a new class of cellular immunotherapies, which has made great achievements in the treatment of malignant tumors. Despite improvements in colorectal cancer (CRC) therapy, treatment of many patients fails because of metastasis and recurrence. The human epidermal growth factor receptor 2 (HER2) is a substantiated target for CAR-T therapy, and has been reported recently to be over-expressed in CRC, which may provide a potential therapeutic target for CRC treatment. Herein, HER2 was a promising target of metastatic colorectal cancer (mCRC) in CAR-T therapy as assessed by flow cytometry and tissue microarray (TMA) with 9-year survival follow-up data. Furthermore, HER2-specific CAR-T cells exhibited strong cytotoxicity and cytokine-secreting ability against CRC cells in vitro. Moreover, through the tumor-bearing model of the NOD-Prkdc^em26cd52Il2rg^em26Cd22/Nju (NCG) mice, HER2 CAR-T cells showed signs of effectively preventing CRC progression in three different xenograft models. Notably, HER2 CAR-T cells displayed greater aggressiveness in HER2⁺ CRC in the patient-derived tumor xenograft (PDX) models and had potent immunotherapeutic capacity for mCRC in the metastatic xenograft mouse models. In conclusion, our studies provide scientific evidence that HER2 CAR-T cells represent an emerging immunotherapy for the treatment of mCRC.

Exploitation of sulfated glycosaminoglycan status for precision medicine of Triplatin in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a subtype of breast cancer lacking targetable biomarkers. TNBC is known to be most aggressive, and when metastatic is often drug resistant and uncurable. Biomarkers predicting response to therapy improve treatment decisions and allow personalized approaches for TNBC patients. This study explores sulfated glycosaminoglycan (sGAG) levels as a predictor of TNBC response to platinum therapy. sGAG levels were quantified in three distinct TNBC tumor models including cell line-derived, patient-derived xenograft (PDX) tumors, and isogenic models deficient in sGAG biosynthesis. The in vivo antitumor efficacy of Triplatin, a sGAG-directed platinum agent, was compared in these models to the clinical platinum agent, carboplatin. We determined that >40% of TNBC PDX tissue microarray samples have high levels of sGAGs. The in vivo accumulation of Triplatin in tumors as well as antitumor efficacy of Triplatin positively correlated with sGAG levels on tumor cells, whereas carboplatin followed the opposite trend. In carboplatin-resistant tumor models expressing high levels of sGAGs, Triplatin decreased primary tumor growth, reduced lung metastases, and inhibited metastatic growth in lungs, liver, and ovaries. sGAG levels served as a predictor of Triplatin sensitivity in TNBC. Triplatin may be particularly beneficial in treating patients with chemotherapy-resistant tumors who have evidence of residual disease after standard neoadjuvant chemotherapy. More effective neoadjuvant and adjuvant treatment will likely improve clinical outcome of TNBC.

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.

A genome-scale CRISPR Cas9 dropout screen identifies synthetically lethal targets in SRC-3 inhibited cancer cells

Steroid receptor coactivator 3 (SRC-3/NCoA3/AIB1), is a key regulator of gene transcription and it plays a central role in breast cancer (BC) tumorigenesis, making it a potential therapeutic target. Beyond its function as an important regulator of estrogen receptor transcriptional activity, SRC-3 also functions as a coactivator for a wide range of other transcription factors, suggesting SRC-3 inhibition can be beneficial in hormone-independent cancers as well. The recent discovery of a potent SRC-3 small molecule inhibitor, SI-2, enabled the further development of additional related compounds. SI-12 is an improved version of SI-2 that like SI-2 has anti-proliferative activity in various cancer types, including BC. Here, we sought to identify gene targets, that when inhibited in the presence of SI-12, would lead to enhanced BC cell cytotoxicity. We performed a genome-scale CRISPR-Cas9 screen in MCF-7 BC cells under conditions of pharmacological pressure with SI-12. A parallel screen was performed with an ER inhibitor, fulvestrant, to shed light on both common and distinct activities between SRC-3 and ERα inhibition. Bearing in mind the key role of SRC-3 in tumorigenesis of other types of cancer, we extended our study by validating potential hits identified from the MCF-7 screen in other cancer cell lines.

DAXX-inducing phytoestrogens inhibit ER+ tumor initiating cells and delay tumor development

Recurrence of estrogen receptor (ER)-positive breast tumors despite curative-intent adjuvant therapy is thought to be due to enrichment of tumor initiating cells (TIC) during endocrine therapy (ET). Recently, it was identified that by antagonizing the ER, ET promotes rapid degradation of the death-associated factor 6 (DAXX) protein, which is necessary and sufficient to potently inhibit TICs. Thus, the goal of the current study was to identify a DAXX-inducing agent to inhibit TICs and prevent proliferation of the tumor. Phytoestrogens (naringenin, resveratrol, genistein, apigenin, and quercetin) were screened for DAXX protein expression, anti-TIC and anti-proliferative efficacy in vitro and in vivo. Specific DAXX-inducing phytoestrogens were tested to assess selectivity towards ERα and/or ERβ. Results showed that phytoestrogens tested induced DAXX protein expression and inhibited survival of TICs from ER+ MCF-7 and T47D cells. Only naringenin, resveratrol, and quercetin did not stimulate total cell proliferation. Naringenin, resveratrol, but not quercetin inhibited survival of TICs in vitro and in vivo in a DAXX-dependent manner. Naringenin-induced DAXX protein expression and inhibition of TICs seemed to be more selective towards ERβ while resveratrol was more selective through ERα. Naringenin or resveratrol inhibited the rate of tumor initiation and rate of tumor growth in a DAXX-dependent manner. These results suggest that a therapeutic approach using a phytoestrogen to induce DAXX protein expression could potently inhibit TICs within a tumor to delay or prevent tumor initiation. Therefore, a DAXX-promoting phytoestrogen should be explored for prevention of tumor progression in advanced disease and relapse in the adjuvant setting.

Patient-derived xenografts as compatible models for precision oncology

Cancer is a very heterogeneous disease, displaying heterogeneity between patients (inter-tumoral heterogeneity) and heterogeneity within a patient (intra-tumoral heterogeneity). Precision oncology is a diagnostic and therapeutic approach for cancers based on the stratification of patients using genomic and molecular profiling of tumors. To develop diagnostic and therapeutic tools for the application of precision oncology, appropriate preclinical mouse models that reflect tumor heterogeneity are required. Patient-derived xenograft (PDX) models are generated by the engraftment of patient tumors into immunodeficient mice that retain several aspects of the patient’s tumor characteristics, including inter-tumoral heterogeneity and intra-tumoral heterogeneity. Therefore, PDX models can be applied in various developmental steps of cancer diagnostics and therapeutics, such as biomarker development, companion diagnostics, drug efficacy testing, overcoming drug resistance, and co-clinical trials. This review summarizes the diverse aspects of PDX models, addressing the factors considered for PDX generation, application of PDX models for cancer research, and future directions of PDX models.

Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer

Preclinical models that faithfully recapitulate tumor heterogeneity and therapeutic response are critical for translational breast cancer research. Immortalized cell lines are easy to grow and genetically modify to study molecular mechanisms, yet the selective pressure from cell culture often leads to genetic and epigenetic alterations over time. Patient-derived xenograft (PDX) models faithfully recapitulate the heterogeneity and drug response of human breast tumors. PDX models exhibit a relatively short latency after orthotopic transplantation that facilitates the investigation of breast tumor biology and drug response. The transplantable genetically engineered mouse models allow the study of breast tumor immunity. The current protocol describes the method to orthotopically transplant breast tumor fragments into the mammary fat pad followed by drug treatments. These preclinical models provide valuable approaches to investigate breast tumor biology, drug response, biomarker discovery and mechanisms of drug resistance.

Regulation of hypoxia-inducible factor functions in the nucleus by sphingosine-1-phosphate

Sphingosine kinase 2 (SphK2) is known to phosphorylate the nuclear sphingolipid metabolite to generate sphingosine-1-phosphate (S1P). Nuclear S1P is involved in epigenetic regulation of gene expression; however, the underlying mechanisms are not well understood. In this work, we have identified the role of nuclear S1P and SphK2 in regulating hypoxia-responsive master transcription factors hypoxia-inducible factor (HIF)-1α/2α, and their functions in breast cancer, with a focus on triple-negative breast cancer (TNBC). We have shown SphK2 is associated with HIF-1α in protein complexes, and is enriched at the promoters of HIF target genes, including vascular endothelial growth factor (VEGF), where it enhances local histone H3 acetylation and transcription. S1P specifically binds to the PAS domains of HIF-1α. SphK2, and HIF-1α expression levels are elevated in metastatic estrogen receptor-positive (ER+) and TNBC clinical tissue specimens compared to healthy breast tissue samples. To determine if S1P formation in the nucleus by SphK2 is a key regulator of HIF functions, we found using a preclinical TNBC xenograft mouse model, and an existing selective SphK2 inhibitor K-145, that nuclear S1P, histone acetylation, HIF-1α expression, and TNBC tumor growth were all reduced in vivo. Our results suggest that S1P and SphK2 in the nucleus are linked to the regulation of HIF-1α/2α functions associated with breast cancer progression, and may provide potential therapeutic targets.

Magnetic Resonance Imaging for Translational Research in Oncology

The translation of results from the preclinical to the clinical setting is often anything other than straightforward. Indeed, ideas and even very intriguing results obtained at all levels of preclinical research, i.e., in vitro, on animal models, or even in clinical trials, often require much effort to validate, and sometimes, even useful data are lost or are demonstrated to be inapplicable in the clinic. In vivo, small-animal, preclinical imaging uses almost the same technologies in terms of hardware and software settings as for human patients, and hence, might result in a more rapid translation. In this perspective, magnetic resonance imaging might be the most translatable technique, since only in rare cases does it require the use of contrast agents, and when not, sequences developed in the lab can be readily applied to patients, thanks to their non-invasiveness. The wide range of sequences can give much useful information on the anatomy and pathophysiology of oncologic lesions in different body districts. This review aims to underline the versatility of this imaging technique and its various approaches, reporting the latest preclinical studies on thyroid, breast, and prostate cancers, both on small laboratory animals and on human patients, according to our previous and ongoing research lines.

How to Choose a Mouse Model of Breast Cancer, a Genomic Perspective

Human breast cancer is a heterogeneous disease with numerous subtypes that have been defined through immunohistological, histological, and gene expression patterns. The diversity of breast cancer has made the study of its various underlying causes complex. To facilitate the examination of particular facets of breast cancer, mouse models have been generated, ranging from carcinogen induced models to genetically engineered mice. While mouse models have been generated to mimic the initiating event, including p53 loss, BRCA loss, or overexpression of HER2 / Neu / erbB2, other genomic events are often not well characterized. However, these secondary genetic events are often critical to the mouse tumor evolution, subtype, and outcome, just as they are in human breast cancer. As such, these other genomic events are a critical component of what models are chosen to study specific subtypes of human breast cancer. Here we review the genomic analyses that have been completed for various genetically engineered mouse models, how they compare to human breast cancer, and detail how this information can be used in choosing a mouse model for analysis.

DAXX Suppresses Tumor-Initiating Cells in Estrogen Receptor-Positive Breast Cancer Following Endocrine Therapy

Estrogen receptor (ER)-positive breast cancer recurrence is thought to be driven by tumor-initiating cells (TIC). TICs are enriched by endocrine therapy through NOTCH signaling. Side effects have limited clinical trial testing of NOTCH-targeted therapies. Death-associated factor 6 (DAXX) is a newly identified marker whose RNA expression inversely correlates with NOTCH in human ER⁺ breast tumor samples. In this study, knockdown and overexpression approaches were used to investigate the role of DAXX on stem/pluripotent gene expression, TIC survival in vitro, and TIC frequency in vivo, and the mechanism by which DAXX suppresses TICs in ER⁺ breast cancer. 17β-Estradiol (E₂)-mediated ER activation stabilized the DAXX protein, which was required for repressing stem/pluripotent genes (NOTCH4, SOX2, OCT4, NANOG, and ALDH1A1), and TICs in vitro and in vivo. Conversely, endocrine therapy promoted rapid protein depletion due to increased proteasome activity. DAXX was enriched at promoters of stem/pluripotent genes, which was lost with endocrine therapy. Ectopic expression of DAXX decreased stem/pluripotent gene transcripts to levels similar to E₂ treatment. DAXX-mediated repression of stem/pluripotent genes and suppression of TICs was dependent on DNMT1. DAXX or DNMT1 was necessary to inhibit methylation of CpGs within the SOX2 promoter and moderately within the gene body of NOTCH4, NOTCH activation, and TIC survival. E₂-mediated stabilization of DAXX was necessary and sufficient to repress stem/pluripotent genes by recruiting DNMT1 to methylate some promoters and suppress TICs. These findings suggest that a combination of endocrine therapy and DAXX-stabilizing agents may inhibit ER⁺ tumor recurrence. SIGNIFICANCE: Estradiol-mediated stabilization of DAXX is necessary and sufficient to repress genes associated with stemness, suggesting that the combination of endocrine therapy and DAXX-stabilizing agents may inhibit tumor recurrence in ER⁺ breast cancer.

Factors that influence response classifications in chemotherapy treated patient-derived xenografts (PDX)

In this study, we investigated the impact of initial tumor volume, rate of tumor growth, cohort size, study duration, and data analysis method on chemotherapy treatment response classifications in patient-derived xenografts (PDXs). The analyses were conducted on cisplatin treatment response data for 70 PDX models representing ten cancer types with up to 28-day study duration and cohort sizes of 3-10 tumor-bearing mice. The results demonstrated that a 21-day dosing study using a cohort size of eight was necessary to reliably detect responsive models (i.e., tumor volume ratio of treated animals to control between 0.1 and 0.42)-independent of analysis method. A cohort of three tumor-bearing animals led to a reliable classification of models that were both highly responsive and highly nonresponsive to cisplatin (i.e., tumor volume ratio of treated animals to control animals less than 0.10). In our set of PDXs, we found that tumor growth rate in the control group impacted treatment response classification more than initial tumor volume. We repeated the study design factors using docetaxel treated PDXs with consistent results. Our results highlight the importance of defining endpoints for PDX dosing studies when deciding the size of cohorts to use in dosing studies and illustrate that response classifications for a study do not differ significantly across the commonly used analysis methods that are based on tumor volume changes in treatment versus control groups.

Patient-derived xenograft mouse models: A high fidelity tool for individualized medicine

Patient-derived xenograft (PDX) mouse models involve the direct transfer of fresh human tumor samples into immunodeficient mice following surgical resection or other medical operations. Gene expression in tumors may be maintained by serial passages of tumors from mouse to mouse. These models aid research into tumor biology and pharmacology without manual manipulation of cell cultures in vitro. and are widely used in individualized cancer therapy/translational medicine, drug development and coclinical trials. PDX models exhibit higher predictive values for clinical outcomes than cell line-derived xenograft models and genetically engineered mouse models. However, PDX models are associated with certain challenges in clinical application. The present study reviewed current collections of PDX models and assessed the challenges and future directions of this field.

TEM8/ANTXR1-Specific CAR T Cells as a Targeted Therapy for Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is an aggressive disease lacking targeted therapy. In this study, we developed a CAR T cell-based immunotherapeutic strategy to target TEM8, a marker initially defined on endothelial cells in colon tumors that was discovered recently to be upregulated in TNBC. CAR T cells were developed that upon specific recognition of TEM8 secreted immunostimulatory cytokines and killed tumor endothelial cells as well as TEM8-positive TNBC cells. Notably, the TEM8 CAR T cells targeted breast cancer stem-like cells, offsetting the formation of mammospheres relative to nontransduced T cells. Adoptive transfer of TEM8 CAR T cells induced regression of established, localized patient-derived xenograft tumors, as well as lung metastatic TNBC cell line-derived xenograft tumors, by both killing TEM8+ TNBC tumor cells and targeting the tumor endothelium to block tumor neovascularization. Our findings offer a preclinical proof of concept for immunotherapeutic targeting of TEM8 as a strategy to treat TNBC.Significance: These findings offer a preclinical proof of concept for immunotherapeutic targeting of an endothelial antigen that is overexpressed in triple-negative breast cancer and the associated tumor vasculature. Cancer Res; 78(2); 489-500. ©2017 AACR.

EMT cells increase breast cancer metastasis via paracrine GLI activation in neighbouring tumour cells

Recent fate-mapping studies concluded that EMT is not required for metastasis of carcinomas. Here we challenge this conclusion by showing that these studies failed to account for possible crosstalk between EMT and non-EMT cells that promotes dissemination of non-EMT cells. In breast cancer models, EMT cells induce increased metastasis of weakly metastatic, non-EMT tumour cells in a paracrine manner, in part by non-cell autonomous activation of the GLI transcription factor. Treatment with GANT61, a GLI1/2 inhibitor, but not with IPI 926, a Smoothened inhibitor, blocks this effect and inhibits growth in PDX models. In human breast tumours, the EMT-transcription factors strongly correlate with activated Hedgehog/GLI signalling but not with the Hh ligands. Our findings indicate that EMT contributes to metastasis via non-cell autonomous effects that activate the Hh pathway. Although all Hh inhibitors may act against tumours with canonical Hh/GLI signalling, only GLI inhibitors would act against non-canonical EMT-induced GLI activation.

In vivo models in breast cancer research: progress, challenges and future directions

Research using animal model systems has been instrumental in delivering improved therapies for breast cancer, as well as in generating new insights into the mechanisms that underpin development of the disease. A large number of different models are now available, reflecting different types and stages of the disease; choosing which one to use depends on the specific research question(s) to be investigated. Based on presentations and discussions from leading experts who attended a recent workshop focused on in vivo models of breast cancer, this article provides a perspective on the many varied uses of these models in breast cancer research, their strengths, associated challenges and future directions. Among the questions discussed were: how well do models represent the different stages of human disease; how can we model the involvement of the human immune system and microenvironment in breast cancer; what are the appropriate models of metastatic disease; can we use models to carry out preclinical drug trials and identify pathways responsible for drug resistance; and what are the limitations of patient-derived xenograft models? We briefly outline the areas where the existing breast cancer models require improvement in light of the increased understanding of the disease process, reflecting the drive towards more personalised therapies and identification of mechanisms of drug resistance.

Patient-derived xenograft (PDX) models in basic and translational breast cancer research

Patient-derived xenograft (PDX) models of a growing spectrum of cancers are rapidly supplanting long-established traditional cell lines as preferred models for conducting basic and translational preclinical research. In breast cancer, to complement the now curated collection of approximately 45 long-established human breast cancer cell lines, a newly formed consortium of academic laboratories, currently from Europe, Australia, and North America, herein summarizes data on over 500 stably transplantable PDX models representing all three clinical subtypes of breast cancer (ER+, HER2+, and "Triple-negative" (TNBC)). Many of these models are well-characterized with respect to genomic, transcriptomic, and proteomic features, metastatic behavior, and treatment response to a variety of standard-of-care and experimental therapeutics. These stably transplantable PDX lines are generally available for dissemination to laboratories conducting translational research, and contact information for each collection is provided. This review summarizes current experiences related to PDX generation across participating groups, efforts to develop data standards for annotation and dissemination of patient clinical information that does not compromise patient privacy, efforts to develop complementary data standards for annotation of PDX characteristics and biology, and progress toward "credentialing" of PDX models as surrogates to represent individual patients for use in preclinical and co-clinical translational research. In addition, this review highlights important unresolved questions, as well as current limitations, that have hampered more efficient generation of PDX lines and more rapid adoption of PDX use in translational breast cancer research.

NSG Mice Provide a Better Spontaneous Model of Breast Cancer Metastasis than Athymic (Nude) Mice

Metastasis is the most common cause of mortality in breast cancer patients worldwide. To identify improved mouse models for breast cancer growth and spontaneous metastasis, we examined growth and metastasis of both estrogen receptor positive (T47D) and negative (MDA-MB-231, SUM1315, and CN34BrM) human breast cancer cells in nude and NSG mice. Both primary tumor growth and spontaneous metastases were increased in NSG mice compared to nude mice. In addition, a pattern of metastasis similar to that observed in human breast cancer patients (metastases to the lungs, liver, bones, brain, and lymph nodes) was found in NSG mice. Furthermore, there was an increase in the metastatic burden in NSG compared to nude mice that were injected with MDA-MB-231 breast cancer cells in an intracardiac experimental metastasis model. This data demonstrates that NSG mice provide a better model for studying human breast cancer metastasis compared to the current nude mouse model.

mTOR Inhibitors Suppress Homologous Recombination Repair and Synergize with PARP Inhibitors via Regulating SUV39H1 in BRCA-Proficient Triple-Negative Breast Cancer

PURPOSE

Triple-negative breast cancer (TNBC) is a highly heterogeneous disease and has the worst outcome among all subtypes of breast cancers. Although PARP inhibitors represent a promising treatment in TNBC with BRCA1/BRCA2 mutations, there is great interest in identifying drug combinations that can extend the use of PARP inhibitors to a majority of TNBC patients with wild-type BRCA1/BRCA2 Here we explored whether mTOR inhibitors, through modulating homologous recombination (HR) repair, would provide therapeutic benefit in combination with PARP inhibitors in preclinical models of BRCA-proficient TNBC.

EXPERIMENTAL DESIGN

We have studied the effects of mTOR inhibitors on HR repair following DNA double-strand breaks (DSB). We further demonstrated the in vitro and in vivo activities of combined treatment of mTOR inhibitors with PARP inhibitors in BRCA-proficient TNBC. Moreover, microarray analysis and rescue experiments were used to investigate the molecular mechanisms of action.

RESULTS

We found that mTOR inhibitors significantly suppressed HR repair in two BRCA-proficient TNBC cell lines. mTOR inhibitors and PARP inhibitors in combination exhibited strong synergism against these TNBC cell lines. In TNBC xenografts, we observed enhanced efficacy of everolimus in combination with talazoparib (BMN673) compared with either drug alone. We further identified through microarray analysis and by rescue assays that mTOR inhibitors suppressed HR repair and synergized with PARP inhibitors through regulating the expression of SUV39H1 in BRCA-proficient TNBCs.

CONCLUSIONS

Collectively, these findings strongly suggest that combining mTOR inhibitors and PARP inhibitors would be an effective therapeutic approach to treat BRCA-proficient TNBC patients.

Patient-derived xenograft models of breast cancer and their predictive power

Despite advances in the treatment of patients with early and metastatic breast cancer, mortality remains high due to intrinsic or acquired resistance to therapy. Increased understanding of the genomic landscape through massively parallel sequencing has revealed somatic mutations common to specific subtypes of breast cancer, provided new prognostic and predictive markers, and highlighted potential therapeutic targets. Evaluating new targets using established cell lines is limited by the inexact correlation between responsiveness observed in cell lines versus that elicited in the patient. Patient-derived xenografts (PDXs) generated from fresh tumor specimens recapitulate the diversity of breast cancer and reflect histopathology, tumor behavior, and the metastatic properties of the original tumor. The high degree of genomic preservation evident across primary tumors and their matching PDXs over serial passaging validate them as important preclinical tools. Indeed, there is accumulating evidence that PDXs can recapitulate treatment responses of the parental tumor. The finding that tumor engraftment is an independent and poor prognostic indicator of patient outcome represents the first step towards personalized medicine. Here we review the utility of breast cancer PDX models to study the clonal evolution of tumors and to evaluate novel therapies and drug resistance.

Identification and Characterization of Separase Inhibitors (Sepins) for Cancer Therapy

Separase is an endopeptidase that cleaves cohesin subunit Rad21, facilitating the repair of DNA damage during interphase and the resolution of sister chromatid cohesion at anaphase. Separase activity is negatively regulated by securin and Cdk1-cyclin B in vivo. Separase overexpression is reported in a broad range of human tumors, and its overexpression in mouse models results in tumorigenesis. To elucidate further the mechanism of separase function and to test if inhibition of overexpressed separase can be used as a strategy to inhibit tumor-cell proliferation, small-molecule inhibitors of separase enzyme are essential. Here, we report a high-throughput screening for separase inhibitors (Sepins). We developed a fluorogenic separase assay using rhodamine 110-conjugated Rad21 peptide as substrate and screened a small-molecule compound library. We identified a noncompetitive inhibitor of separase called Sepin-1 that inhibits separase enzymatic activity with a half maximal inhibitory concentration (IC50) of 14.8 µM. Sepin-1 can inhibit the growth of human cancer cell lines and breast cancer xenograft tumors in mice by inhibiting cell proliferation and inducing apoptosis. The sensitivity to Sepin-1 in most cases is positively correlated to the level of separase in both cancer cell lines and tumors.

A renewable tissue resource of phenotypically stable, biologically and ethnically diverse, patient-derived human breast cancer xenograft models

Breast cancer research is hampered by difficulties in obtaining and studying primary human breast tissue, and by the lack of in vivo preclinical models that reflect patient tumor biology accurately. To overcome these limitations, we propagated a cohort of human breast tumors grown in the epithelium-free mammary fat pad of severe combined immunodeficient (SCID)/Beige and nonobese diabetic (NOD)/SCID/IL-2γ-receptor null (NSG) mice under a series of transplant conditions. Both models yielded stably transplantable xenografts at comparably high rates (∼21% and ∼19%, respectively). Of the conditions tested, xenograft take rate was highest in the presence of a low-dose estradiol pellet. Overall, 32 stably transplantable xenograft lines were established, representing 25 unique patients. Most tumors yielding xenografts were "triple-negative" [estrogen receptor (ER)-progesterone receptor (PR)-HER2+; n = 19]. However, we established lines from 3 ER-PR-HER2+ tumors, one ER+PR-HER2-, one ER+PR+HER2-, and one "triple-positive" (ER+PR+HER2+) tumor. Serially passaged xenografts show biologic consistency with the tumor of origin, are phenotypically stable across multiple transplant generations at the histologic, transcriptomic, proteomic, and genomic levels, and show comparable treatment responses as those observed clinically. Xenografts representing 12 patients, including 2 ER+ lines, showed metastasis to the mouse lung. These models thus serve as a renewable, quality-controlled tissue resource for preclinical studies investigating treatment response and metastasis.