Establishing and characterizing patient-derived xenografts using pre-chemotherapy percutaneous biopsy and post-chemotherapy surgical samples from a prospective neoadjuvant breast cancer study

Patient Characteristics Associated with Growth of Patient-Derived Tumor Implants in Mice (Patient-Derived Xenografts)

Background: patient-derived xenografts (PDXs) have defined the field of translational cancer research in recent years, becoming one of the most-used tools in early drug development. The process of establishing cancer models in mice has turned out to be challenging, since little research focuses on evaluating which factors impact engraftment success. We sought to determine the clinical, pathological, or molecular factors which may predict better engraftment rates in PDXs. Methods: between March 2017 and January 2021, tumor samples obtained from patients with primary or metastatic cancer were implanted into athymic nude mice. A full comprehensive evaluation of baseline factors associated with the patients and patients' tumors was performed, with the goal of potentially identifying predictive markers of engraftment. We focused on clinical (patient factors) pathological (patients' tumor samples) and molecular (patients' tumor samples) characteristics, analyzed either by immunohistochemistry (IHC) or next-generation sequencing (NGS), which were associated with the likelihood of final engraftment, as well as with tumor growth rates in xenografts. Results: a total of 585 tumor samples were collected and implanted. Twenty-one failed to engraft, due to lack of malignant cells. Of 564 tumor-positive samples, 187 (33.2%) grew at time of analysis. The study was able to find correlation and predictive value for engraftment for the following: the use of systemic antibiotics by the patient within 2 weeks of sampling (38.1% (72/189) antibiotics- group vs. 30.7% (115/375) no-antibiotics) (p = 0.048), and the administration of systemic steroids to the patients within 2 weeks of sampling (41.5% (34/48) steroids vs. 31.7% (153/329), no-steroids) (p = 0.049). Regarding patient's baseline tests, we found certain markers could help predict final engraftment success: for lactate dehydrogenase (LDH) levels, 34.1% (140/411) of tumors derived from patients with baseline blood LDH levels above the upper limit of normality (ULN) achieved growth, against 30.7% (47/153) with normal LDH (p = 0.047). Histological tumor characteristics, such as grade of differentiation, were also correlated. Grade 1: 25.4% (47/187), grade 2: 34.8% (65/187) and grade 3: 40.1% (75/187) tumors achieved successful growth (p = 0.043), suggesting the higher the grade, the higher the likelihood of success. Similarly, higher ki67 levels were also correlated with better engraftment rates: low (Ki67 < 15%): 8.9% (9/45) achieved growth vs. high (Ki67 ≥ 15%): 31% (35/113) (p: 0.002). Other markers of aggressiveness such as the presence of lymphovascular invasion in tumor sample of origin was also predictive: 42.2% (97/230) with lymphovascular vs. 26.9% (90/334) of samples with no invasion (p = 0.0001). From the molecular standpoint, mismatch-repair-deficient (MMRd) tumors showed better engraftment rates: 62.1% (18/29) achieved growth vs. 40.8% (75/184) of proficient tumors (p = 0.026). A total of 84 PDX were breast models, among which 57.9% (11/19) ER-negative models grew, vs. 15.4% (10/65) of ER-positive models (p = 0.0001), also consonant with ER-negative tumors being more aggressive. BRAFmut cancers are more likely to achieve engraftment during the development of PDX models. Lastly, tumor growth rates during first passages can help establish a cutoff point for the decision-making process during PDX development, since the higher the tumor grades, the higher the likelihood of success. Conclusions: tumors with higher grade and Ki67 protein expression, lymphovascular and/or perineural invasion, with dMMR and are negative for ER expression have a higher probability of achieving growth in the process of PDX development. The use of steroids and/or antibiotics in the patient prior to sampling can also impact the likelihood of success in PDX development. Lastly, establishing a cutoff point for tumor growth rates could guide the decision-making process during PDX development.

Patient-derived organoid culture in epithelial ovarian cancers-Techniques, applications, and future perspectives

Epithelial ovarian cancer (EOC) is a heterogeneous disease composed of different cell types with different molecular aberrations. Traditional cell lines and mice models cannot recapitulate the human tumor biology and tumor microenvironment (TME). Patient-derived organoids (PDOs) are freshly derived from patients' tissues and are then cultured with extracellular matrix and conditioned medium. The high concordance of epigenetic, genomic, and proteomic landscapes between the parental tumors and PDOs suggests that PDOs can provide more reliable results in studying cancer biology, allowing high throughput drug screening, and identifying their associated signaling pathways and resistance mechanisms. However, despite having a heterogeneity of cells in PDOs, some cells in TME will be lost during the culture process. Next-generation organoids have been developed to circumvent some of the limitations. Genetically engineered organoids involving targeted gene editing can facilitate the understanding of tumorigenesis and drug response. Co-culture systems where PDOs are cultured with different cell components like immune cells can allow research using immunotherapy which is otherwise impossible in conventional cell lines. In this review, the limitations of the traditional in vitro and in vivo assays, the use of PDOs, the challenges including some tips and tricks of PDO generation in EOC, and the future perspectives, will be discussed.

Pan-Cancer Pharmacogenomic Analysis of Patient-Derived Tumor Cells Using Clinically Relevant Drug Exposures

As a result of tumor heterogeneity and solid cancers harboring multiple molecular defects, precision medicine platforms in oncology are most effective when both genetic and pharmacologic determinants of a tumor are evaluated. Expandable patient-derived xenograft (PDX) mouse tumor and corresponding PDX culture (PDXC) models recapitulate many of the biological and genetic characteristics of the original patient tumor, allowing for a comprehensive pharmacogenomic analysis. Here, the somatic mutations of 23 matched patient tumor and PDX samples encompassing four cancers were first evaluated using next-generation sequencing (NGS). 19 antitumor agents were evaluated across 78 patient-derived tumor cultures using clinically relevant drug exposures. A binarization threshold sensitivity classification determined in culture (PDXC) was used to identify tumors that best respond to drug in vivo (PDX). Using this sensitivity classification, logic models of DNA mutations were developed for 19 antitumor agents to predict drug response. We determined that the concordance of somatic mutations across patient and corresponding PDX samples increased as variant allele frequency increased. Notable individual PDXC responses to specific drugs, as well as lineage-specific drug responses were identified. Robust responses identified in PDXC were recapitulated in vivo in PDX-bearing mice and logic modeling determined somatic gene mutation(s) defining response to specific antitumor agents. In conclusion, combining NGS of primary patient tumors, high-throughput drug screen using clinically relevant doses, and logic modeling, can provide a platform for understanding response to therapeutic drugs targeting cancer.

Challenges and Prospects of Patient-Derived Xenografts for Cancer Research

We discuss the importance of the in vivo models in elucidating cancer biology, focusing on the patient-derived xenograft (PDX) models, which are classic and standard functional in vivo platforms for preclinical evaluation. We provide an overview of the most representative models, including cell-derived xenografts (CDX), tumor and metastatic cell-derived xenografts, and PDX models utilizing humanized mice (HM). The orthotopic models, which could reproduce the cancer environment and its progression, similar to human tumors, are particularly common. The standard procedures and rationales of gastric adenocarcinoma (GAC) orthotopic models are addressed. Despite the significant advantages of the PDX models, such as recapitulating key features of human tumors and enabling drug testing in the in vivo context, some challenges must be acknowledged, including loss of heterogeneity, selection bias, clonal evolution, stroma replacement, tumor micro-environment (TME) changes, host cell carryover and contaminations, human-to-host cell oncogenic transformation, human and host viral infections, as well as limitations for immunologic research. To compensate for these limitations, other mouse models, such as syngeneic and humanized mouse models, are currently utilized. Overall, the PDX models represent a powerful tool in cancer research, providing critical insights into tumor biology and potential therapeutic targets, but their limitations and challenges must be carefully considered for their effective use. Lastly, we present an intronic quantitative PCR (qPCR) method to authenticate, detect, and quantify human/murine cells in cell lines and PDX samples.

Patient-derived xenograft models in cancer therapy: technologies and applications

Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.

The Role of ERα and ERβ in Castration-Resistant Prostate Cancer and Current Therapeutic Approaches

Castration-resistant prostate cancer, or CRPC, is an aggressive stage of prostate cancer (PCa) in which PCa cells invade nearby or other parts of the body. When a patient with PCa goes through androgen deprivation therapy (ADT) and the cancer comes back or worsens, this is called CRPC. Instead of androgen-dependent signalling, recent studies show the involvement of the estrogen pathway through the regulation of estrogen receptor alpha (ERα) and estrogen receptor beta (ERβ) in CRPC development. Reduced levels of testosterone due to ADT lead to low ERβ functionality in inhibiting the proliferation of PCa cells. Additionally, ERα, which possesses androgen independence, continues to promote the proliferation of PCa cells. The functions of ERα and ERβ in controlling PCa progression have been studied, but further research is needed to elucidate their roles in promoting CRPC. Finding new ways to treat the disease and stop it from becoming worse will require a clear understanding of the molecular processes that can lead to CRPC. The current review summarizes the underlying processes involving ERα and ERβ in developing CRPC, including castration-resistant mechanisms after ADT and available medication modification in mitigating CRPC progression, with the goal of directing future research and treatment.

Pharmacological Targeting of Androgen Receptor Elicits Context-Specific Effects in Estrogen Receptor-Positive Breast Cancer

Androgen receptor (AR) is expressed in 80% to 90% of estrogen receptor α-positive (ER+) breast cancers. Accumulated evidence has shown that AR is a tumor suppressor and that its expression is associated with improved prognosis in ER+ breast cancer. However, both a selective AR agonist (RAD140) and an AR inhibitor (enzalutamide, ENZ) have shown a therapeutic effect on ER+ breast cancer, so the potential for clinical application of AR-targeting therapy for ER+ breast cancer is still in dispute. In this study, we evaluated the efficacy of ENZ and RAD140 in vivo and in vitro in AR+/ER+ breast cancer models, characterizing the relationship of AR and ER levels to response to AR-targeting drugs and investigating the alterations of global gene expression and chromatin binding of AR and ERα after ENZ treatment. In the AR-low setting, ENZ directly functioned as an ERα antagonist. Cell growth inhibition by ENZ in breast cancer with low AR expression was independent of AR and instead dependent on ER. In AR-high breast cancer models, AR repressed ERα signaling and ENZ promoted ERα signaling by antagonizing AR. In contrast, RAD140 activated AR signaling and suppressed AR-high tumor growth by deregulating ERα expression and blocking ERα function. Overall, analysis of the dynamic efficacies and outcomes of AR agonist, and antagonist in the presence of different AR and ERα levels reveals regulators of response and supports the clinical investigation of ENZ in selected ER+ tumors with a low AR/ER ratio and AR agonists in tumors with a high AR/ER ratio.

SIGNIFICANCE

The ratio of androgen receptor to estrogen receptor in breast cancer dictates the response to AR-targeted therapies, providing guidelines for developing AR-directed treatment strategies for patients with breast cancer.

Identification of Src Family Kinases as Potential Therapeutic Targets for Chemotherapy-Resistant Triple Negative Breast Cancer

Neoadjuvant chemotherapy (NAC) remains the cornerstone of the treatment for triple negative breast cancer (TNBC), with the goal of complete eradication of disease. However, for patients with residual disease after NAC, recurrence and mortality rates are high and the identification of novel therapeutic targets is urgently needed. We quantified tyrosine phosphorylation (pTyr)-mediated signaling networks in chemotherapy sensitive (CS) and resistant (CR) TNBC patient-derived xenografts (PDX), to gain novel therapeutic insights. The antitumor activity of SFK inhibition was examined in vivo. Treated tumors were further subjected to phosphoproteomic and RNAseq analysis, to identify the mechanism of actions of the drug. We identified Src Family Kinases (SFKs) as potential therapeutic targets in CR TNBC PDXs. Treatment with dasatinib, an FDA approved SFK inhibitor, led to inhibition of tumor growth in vivo. Further analysis of post-treatment PDXs revealed multiple mechanisms of actions of the drug, confirming the multi-target inhibition of dasatinib. Analysis of pTyr in tumor specimens suggested a low prevalence of SFK-driven tumors, which may provide insight into prior clinical trial results demonstrating a lack of dasatinib antitumor activity in unselected breast cancer patients. Taken together, these results underscore the importance of pTyr characterization of tumors, in identifying new targets, as well as stratifying patients based on their activated signaling networks for therapeutic options. Our data provide a strong rationale for studying SFK inhibitors in biomarker-selected SFK-driven TNBC.

A Molecularly Characterized Preclinical Platform of Subcutaneous Renal Cell Carcinoma (RCC) Patient-Derived Xenograft Models to Evaluate Novel Treatment Strategies

Renal cell carcinoma (RCC) is a kidney cancer with an onset mainly during the sixth or seventh decade of the patient’s life. Patients with advanced, metastasized RCC have a poor prognosis. The majority of patients develop treatment resistance towards Standard of Care (SoC) drugs within months. Tyrosine kinase inhibitors (TKIs) are the backbone of first-line therapy and have been partnered with an immune checkpoint inhibitor (ICI) recently. Despite the most recent progress, the development of novel therapies targeting acquired TKI resistance mechanisms in advanced and metastatic RCC remains a high medical need. Preclinical models with high translational relevance can significantly support the development of novel personalized therapies. It has been demonstrated that patient-derived xenograft (PDX) models represent an essential tool for the preclinical evaluation of novel targeted therapies and their combinations. In the present project, we established and molecularly characterized a comprehensive panel of subcutaneous RCC PDX models with well-conserved molecular and pathological features over multiple passages. Drug screening towards four SoC drugs targeting the vascular endothelial growth factor (VEGF) and PI3K/mTOR pathway revealed individual and heterogeneous response profiles in those models, very similar to observations in patients. As unique features, our cohort includes PDX models from metastatic disease and multi-tumor regions from one patient, allowing extended studies on intra-tumor heterogeneity (ITH). The PDX models are further used as basis for developing corresponding in vitro cell culture models enabling advanced high-throughput drug screening in a personalized context. PDX models were subjected to next-generation sequencing (NGS). Characterization of cancer-relevant features including driver mutations or cellular processes was performed using mutational and gene expression data in order to identify potential biomarker or treatment targets in RCC. In summary, we report a newly established and molecularly characterized panel of RCC PDX models with high relevance for translational preclinical research.

In Vivo Modeling of Human Breast Cancer Using Cell Line and Patient-Derived Xenografts

Historically, human breast cancer has been modeled largely in vitro using long-established cell lines primarily in two-dimensional culture, but also in three-dimensional cultures of varying cellular and molecular complexities. A subset of cell line models has also been used in vivo as cell line-derived xenografts (CDX). While outstanding for conducting detailed molecular analysis of regulatory mechanisms that may function in vivo, results of drug response studies using long-established cell lines have largely failed to translate clinically. In an attempt to address this shortcoming, many laboratories have succeeded in developing clinically annotated patient-derived xenograft (PDX) models of human cancers, including breast, in a variety of host systems. While immunocompromised mice are the predominant host, the immunocompromised rat and pig, zebrafish, as well as the chicken egg chorioallantoic membrane (CAM) have also emerged as potential host platforms to help address perceived shortcomings of immunocompromised mice. With any modeling platform, the two main issues to be resolved are criteria for "credentialing" the models as valid models to represent human cancer, and utility with respect to the ability to generate clinically relevant translational research data. Such data are beginning to emerge, particularly with the activities of PDX consortia such as the NCI PDXNet Program, EuroPDX, and the International Breast Cancer Consortium, as well as a host of pharmaceutical companies and contract research organizations (CRO). This review focuses primarily on these important aspects of PDX-related research, with a focus on breast cancer.

Patient-Derived Xenografts of High-Grade Serous Ovarian Cancer Subtype as a Powerful Tool in Pre-Clinical Research

(1) Background. PDX models have become the preferred tool in research laboratories seeking to improve development and pre-clinical testing of new drugs. PDXs have been shown to capture the cellular and molecular characteristics of human tumors better than simpler cell line-based models. More recently, however, hints that PDXs may change their characteristics over time have begun to emerge, emphasizing the need for comprehensive analysis of PDX evolution. (2) Methods. We established a panel of high-grade serous ovarian carcinoma (HGSOC) PDXs and developed and validated a 300-SNP signature that can be successfully utilized to assess genetic drift across PDX passages and detect PDX contamination with lymphoproliferative tissues. In addition, we performed a detailed histological characterization and functional assessment of multiple PDX passages. (3) Results. Our data show that the PDXs remain largely stable throughout propagation, with marginal genetic drift at the time of PDX initiation and adaptation to mouse host. Importantly, our PDX lines retained the major histological characteristics of the original patients' tumors even after multiple passages in mice, demonstrating a strong concordance with the clinical responses of their corresponding patients. (4) Conclusions. Our data underline the value of defined HGSOC PDXs as a pre-clinical tumor model.

Establishment and characterization of immortalized human breast cancer cell lines from breast cancer patient-derived xenografts (PDX)

The application of patient-derived xenografts (PDX) in drug screening and testing is a costly and time-consuming endeavor. While cell lines permit extensive mechanistic studies, many human breast cancer cell lines lack patient characteristics and clinical treatment information. Establishing cell lines that retain patient's genetic and drug response information would enable greater drug screening and mechanistic studies. Therefore, we utilized breast cancer PDX from the Mayo Breast Cancer Genome Guided Therapy Study (BEAUTY) to establish two immortalized, genomically unique breast cancer cell lines. Through extensive genetic and therapeutic testing, the cell lines were found to retain the same clinical subtype, major somatic alterations, and drug response phenotypes as their corresponding PDX and patient tumor. Our findings demonstrate PDX can be utilized to develop immortalized breast cancer cell lines and provide a valuable tool for understanding the molecular mechanism of drug resistance and exploring novel treatment strategies.

Inhibition of ATM Induces Hypersensitivity to Proton Irradiation by Upregulating Toxic End Joining

Proton Bragg peak irradiation has a higher ionizing density than conventional photon irradiation or the entrance of the proton beam profile. Whether targeting the DNA damage response (DDR) could enhance vulnerability to the distinct pattern of damage induced by proton Bragg peak irradiation is currently unknown. Here, we performed genetic or pharmacologic manipulation of key DDR elements and evaluated DNA damage signaling, DNA repair, and tumor control in cell lines and xenografts treated with the same physical dose across a radiotherapy linear energy transfer spectrum. Radiotherapy consisted of 6 MV photons and the entrance beam or Bragg peak of a 76.8 MeV spot scanning proton beam. More complex DNA double-strand breaks (DSB) induced by Bragg peak proton irradiation preferentially underwent resection and engaged homologous recombination (HR) machinery. Unexpectedly, the ataxia-telangiectasia mutated (ATM) inhibitor, AZD0156, but not an inhibitor of ATM and Rad3-related, rendered cells hypersensitive to more densely ionizing proton Bragg peak irradiation. ATM inhibition blocked resection and shunted more DSBs to processing by toxic ligation through nonhomologous end-joining, whereas loss of DNA ligation via XRCC4 or Lig4 knockdown rescued resection and abolished the enhanced Bragg peak cell killing. Proton Bragg peak monotherapy selectively sensitized cell lines and tumor xenografts with inherent HR defects, and the repair defect induced by ATM inhibitor coadministration showed enhanced efficacy in HR-proficient models. In summary, inherent defects in HR or administration of an ATM inhibitor in HR-proficient tumors selectively enhances the relative biological effectiveness of proton Bragg peak irradiation. SIGNIFICANCE: Coadministration of an ATM inhibitor rewires DNA repair machinery to render cancer cells uniquely hypersensitive to DNA damage induced by the proton Bragg peak, which is characterized by higher density ionization.See related commentary by Nickoloff, p. 3156.

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.

Xenografts derived from patients with head and neck cancer recapitulate patient tumour properties

Rodent models mimic the heterogeneity of head and neck cancer (HNC) malignancies and are used to investigate HNC-associated biomarkers and evaluate drug responses. To assess the utility of patient-derived xenografts (PDXs) as an HNC model, 18 tumour samples were obtained from surgical specimens of patients with HNC and implanted into non-obese diabetic severe combined immunodeficient mice. The histological features of PDXs and corresponding patient samples were compared. Furthermore, the present study investigated how PDX responses to anticancer drugs mimic patient clinical responses, as well as the expression of adenosine triphosphate-binding cassette transporters through chemotherapy in an HNC-PDX model. A total of five PDXs from patients with HNC exhibiting high correspondence with histopathological features of the original patient samples were established (establishment rate, 28%). The responses of three PDXs to cisplatin were associated with clinical responses of the patients. ABC transporter expression was augmented in one PDX model after anticancer drug treatment, but not in PBS-treated passaged PDXs. PDX models exhibited similar biological and chemosensitive characteristics to those of the primary tumours. PDXs could be a useful preclinical tool to test novel therapeutic agents and identify novel targets and biomarkers in HNC.

Genomic profile of metastatic breast cancer patient-derived xenografts established using percutaneous biopsy

Background

Metastatic breast cancer (mBC) is a complex and life-threatening disease and although it is difficult to cure, patients can benefit from sequential anticancer treatment, including endocrine therapy, targeted therapy and cytotoxic chemotherapy. The patient-derived xenograft (PDX) model is suggested as a practical tool to predict the clinical outcome of this disease as well as to screen novel drugs. This study aimed to establish PDX models in Korean patients and analyze their genomic profiles and utility for translational research.

Methods

Percutaneous core needle biopsy or punch biopsy samples were used for xenotransplantation. Whole exome sequencing and transcriptome analysis were performed to assess the genomic and RNA expression profiles, respectively. Copy number variation and mutational burden were analyzed and compared with other metastatic breast cancer genomic results. Mutational signatures were also analyzed. The antitumor effect of an ATR inhibitor was tested in the relevant PDX model.

Results

Of the 151 cases studied, 40 (26%) PDX models were established. Notably, the take rate of all subtypes, including the hormone receptor-positive (HR +) subtype, exceeded 20%. The PDX model had genomic fidelity and copy number variation that represented the pattern of its donor sample. TP53, PIK3CA, ESR1, and GATA3 mutations were frequently found in our samples, with TP53 being the most frequently mutated, and the somatic mutations in these genes strengthened their frequency in the PDX model. The ESR1 mutation, CCND1 amplification, and the APOBEC signature were significant features in our HR + HER2- PDX model. Fulvestrant in combination with palbociclib showed a partial response to the relevant patient’s tumor harboring the ESR1 mutation, and CCND1 amplification was found in the PDX model. AZD6738, an ATR inhibitor, delayed tumor growth in a relevant PDX model.

Conclusions

Our PDX model was established using core needle biopsy samples from primary and metastatic tissues. Genomic profiles of the samples reflected their original tissue characteristics and could be used for the interpretation of clinical outcomes.

The Essential Factors of Establishing Patient-derived Tumor Model

Establishing an applicable preclinical model is vital for translational cancer research. Patient-derived xenograft has been important preclinical model systems and widely used for cancer research. Patient-derived xenograft models that represent the tumors of the patients are necessary to better translate research discoveries and to test potential therapeutic approaches. However, research in this field is hampered by the limited engraftment rate. In this review, we go over a large number of researches on patient-derived xenograft transplantation and firstly systematically summarize the main factors in methodology to successfully establish models. These results will be applied to the development of patient-derived xenograft leading to better preclinical research.

Metabolic Imaging Detects Resistance to PI3Kα Inhibition Mediated by Persistent FOXM1 Expression in ER+ Breast Cancer

PIK3CA, encoding the PI3Kα isoform, is the most frequently mutated oncogene in estrogen receptor (ER)-positive breast cancer. Isoform-selective PI3K inhibitors are used clinically but intrinsic and acquired resistance limits their utility. Improved selection of patients that will benefit from these drugs requires predictive biomarkers. We show here that persistent FOXM1 expression following drug treatment is a biomarker of resistance to PI3Kα inhibition in ER+ breast cancer. FOXM1 drives expression of lactate dehydrogenase (LDH) but not hexokinase 2 (HK-II). The downstream metabolic changes can therefore be detected using MRI of LDH-catalyzed hyperpolarized 13C label exchange between pyruvate and lactate but not by positron emission tomography measurements of HK-II-mediated trapping of the glucose analog 2-deoxy-2-[18F]fluorodeoxyglucose. Rapid assessment of treatment response in breast cancer using this imaging method could help identify patients that benefit from PI3Kα inhibition and design drug combinations to counteract the emergence of resistance.

XENOBREAST Trial: A prospective study of xenografts establishment from surgical specimens of patients with triple negative or luminal b breast cancer

Introduction: Patient-derived xenografts (PDX) can be used to explore tumour pathophysiology and could be useful to better understand therapeutic response in breast cancer. PDX from mammary tumours are usually made from metastatic tumours. Thus, PDX from primary mammary tumours or after neoadjuvant treatment are still rare. This study aims to assess the feasibility to establish xenografts from tumour samples of patients with triple negative or luminal B breast cancer in neoadjuvant, adjuvant or metastatic setting.

Methods: XENOBREAST is a single-centre and prospective study. This feasibility pilot trial aims to produce xenografts from tumour samples of patients with triple negative or luminal B breast cancer. Patient enrolment is expected to take 3 years: 85 patients will be enrolled and followed for 28 months. Additional blood samples will be taken as part of the study. Surgical specimens from post-NAC surgery, primary surgery or surgical excision of the metastases will be collected to establish PDX. Histomolecular characteristics of the established PDX will be investigated and compared with the initial histomolecular profile of the collected tumours to ensure that they are well-established.

Ethics and dissemination: XENOBREAST belongs to category 2 interventional research on the human person. This study has been approved by the Sud Méditerranée IV – Montpellier ethics committee. It is conducted notably in accordance with the Declaration of Helsinki and General Data Protection Regulation (GDPR). Study data and findings will be published in peer-reviewed medical journals. We also plan to present the study and all data at national congresses and conferences.

Registration: ClinicalTrials.gov ID NCT04133077; registered on October 21, 2019.

A Biobank of Colorectal Cancer Patient-Derived Xenografts

Colorectal cancer (CRC) is a challenging disease, with a high mortality rate and limited effective treatment options, particularly for late-stage disease. Patient-derived xenografts (PDXs) have emerged as an informative, renewable experimental resource to model CRC architecture and biology. Here, we describe the generation of a biobank of CRC PDXs from stage I to stage IV patients. We demonstrate that PDXs within our biobank recapitulate the histopathological and mutation features of the original patient tumor. In addition, we demonstrate the utility of this resource in pre-clinical chemotherapy and targeted treatment studies, highlighting the translational potential of PDX models in the identification of new therapies that will improve the overall survival of CRC patients.

Comparing the fate of brain metastatic breast cancer cells in different immune compromised mice with cellular magnetic resonance imaging

Metastasis is the leading cause of mortality in breast cancer patients, with brain metastases becoming increasingly prevalent. Studying this disease is challenging due to the limited experimental models and methods available. Here, we used iron-based cellular MRI to track the fate of a mammary carcinoma cell line (MDA-MB-231-BR) in vivo to characterize the growth of brain metastases in the nude and severely immune-compromised NOD/SCID/ILIIrg-/- (NSG) mouse. Nude and NSG mice received injections of iron-labeled MDA-MB-231-BR cells. Images were acquired with a 3T MR system and assessed for signal voids and metastases. The percentage of signal voids and the number and volume of metastases were quantified. Ex vivo imaging of the liver, histology, and immunofluorescence labeling was performed. Brain metastases grew more rapidly in NSG mice. At day 21 post cell injection, the average number of brain tumors in NSG mice was approximately four times greater than in nude mice. The persistence of iron-labeled cells, visualized as signal voids by MRI, was also examined. The percentage of voids decreased significantly over time for both nude and NSG mice. Body images revealed that the NSG mice also had metastases in the liver, lungs, and lymph nodes while tumors were only detected in the brains of nude mice. This work demonstrates the advantages of using the highly immune-compromised NSG mouse to study breast cancer metastasis, treatments aimed at inhibiting metastasis and outgrowth of breast cancer metastases in multiple organs, and the role that imaging can play toward credentialing these models that cannot be done with other in vitro or histopathologic methods alone.

Regulation of sister chromatid cohesion by nuclear PD-L1

Programmed death ligand-1 (PD-L1 or B7-H1) is well known for its role in immune checkpoint regulation, but its function inside the tumor cells has rarely been explored. Here we report that nuclear PD-L1 is important for cancer cell sister chromatid cohesion. We found that depletion of PD-L1 suppresses cancer cell proliferation, colony formation in vitro, and tumor growth in vivo in immune-deficient NSG mice independent of its role in immune checkpoint. Specifically, PD-L1 functions as a subunit of the cohesin complex, and its deficiency leads to formation of multinucleated cells and causes a defect in sister chromatid cohesion. Mechanistically, PD-L1 compensates for the loss of Sororin, whose expression is suppressed in cancer cells overexpressing PD-L1. PD-L1 competes with Wing Apart-Like (WAPL) for binding to PDS5B, and secures proper sister chromatid cohesion and segregation. Our findings suggest an important role for nuclear PD-L1 in cancer cells independent of its function in immune checkpoint.

Development of gemcitabine-resistant patient-derived xenograft models of pancreatic ductal adenocarcinoma

AIM

Gemcitabine is a frontline agent for locally-advanced and metastatic pancreatic ductal adenocarcinoma (PDAC), but neither gemcitabine alone nor in combination produces durable remissions of this tumor type. We developed three PDAC patient-derived xenograft (PDX) models with gemcitabine resistance (gemR) acquired in vivo, with which to identify mechanisms of resistance relevant to drug exposure in vivo and to evaluate novel therapies.

METHODS

Mice bearing independently-derived PDXs received 100 mg/kg gemcitabine once or twice weekly. Tumors initially responded, but regrew on treatment and were designated gemR. We used immunohistochemistry to compare expression of proteins previously associated with gemcitabine resistance [ribonucleotide reductase subunit M1 (RRM1), RRM2, human concentrative nucleoside transporter 1 (hCNT1), human equilibrative nucleoside transporter 1 (hENT1), cytidine deaminase (CDA), and deoxycytidine kinase (dCK)] in gemR and respective gemcitabine-naive parental tumors.

RESULTS

Parental and gemR tumors did not differ in tumor cell morphology, amount of tumor-associated stroma, or expression of stem cell markers. No consistent pattern of expression of the six gemR marker proteins was observed among the models. Increases in RRM1 and CDA were consistent with in vitro-derived gemR models. However, rather than the expected decreases of hCNT1, hENT1, and dCK, gemR tumors expressed no change in or higher levels of these gemR marker proteins than parental tumors.

CONCLUSION

These models are the first PDAC PDX models with gemcitabine resistance acquired in vivo. The data indicate that mechanisms identified in models with resistance acquired in vitro are unlikely to be the predominant mechanisms when resistance is acquired in vivo. Ongoing work focuses on characterizing unidentified mechanisms of gemR and on identifying agents with anti-tumor efficacy in these gemR models.

Drug responses are conserved across patient-derived xenograft models of melanoma leading to identification of novel drug combination therapies

BACKGROUND

Patient-derived xenograft (PDX) mouse tumour models can predict response to therapy in patients. Predictions made from PDX cultures (PDXC) would allow for more rapid and comprehensive evaluation of potential treatment options for patients, including drug combinations.

METHODS

We developed a PDX library of BRAF-mutant metastatic melanoma, and a high-throughput drug-screening (HTDS) platform utilising clinically relevant drug exposures. We then evaluated 34 antitumor agents across eight melanoma PDXCs, compared drug response to BRAF and MEK inhibitors alone or in combination with PDXC and the corresponding PDX, and investigated novel drug combinations targeting BRAF inhibitor-resistant melanoma.

RESULTS

The concordance of cancer-driving mutations across patient, matched PDX and subsequent PDX generations increases as variant allele frequency (VAF) increases. There was a high correlation in the magnitude of response to BRAF and MEK inhibitors between PDXCs and corresponding PDXs. PDXCs and corresponding PDXs from metastatic melanoma patients that progressed on standard-of-care therapy demonstrated similar resistance patterns to BRAF and MEK inhibitor therapy. Importantly, HTDS identified novel drug combinations to target BRAF-resistant melanoma.

CONCLUSIONS

The biological consistency observed between PDXCs and PDXs suggests that PDXCs may allow for a rapid and comprehensive identification of treatments for aggressive cancers, including combination therapies.

Dual mTORC1/2 Inhibition Sensitizes Testicular Cancer Models to Cisplatin Treatment

Testicular cancer is the most common cancer type among young men. Despite highly effective cisplatin-based chemotherapy, around 20% of patients with metastatic disease will still die from the disease. The aim of this study was to explore the use of kinase inhibitors to sensitize testicular cancer cells to cisplatin treatment. Activation of kinases, including receptor tyrosine kinases and downstream substrates, was studied in five cisplatin-sensitive or -resistant testicular cancer cell lines using phospho-kinase arrays and Western blotting. The phospho-kinase array showed AKT and S6 to be among the top phosphorylated proteins in testicular cancer cells, which are part of the PI3K/AKT/mTORC pathway. Inhibitors of most active kinases in the PI3K/AKT/mTORC pathway were tested using apoptosis assays and survival assays. Two mTORC1/2 inhibitors, AZD8055 and MLN0128, strongly enhanced cisplatin-induced apoptosis in all tested testicular cancer cell lines. Inhibition of mTORC1/2 blocked phosphorylation of the mTORC downstream proteins S6 and 4E-BP1. Combined treatment with AZD8055 and cisplatin led to reduced clonogenic survival of testicular cancer cells. Two testicular cancer patient-derived xenografts (PDX), either from a chemosensitive or -resistant patient, were treated with cisplatin in the absence or presence of kinase inhibitor. Combined AZD8055 and cisplatin treatment resulted in effective mTORC1/2 inhibition, increased caspase-3 activity, and enhanced tumor growth inhibition. In conclusion, we identified mTORC1/2 inhibition as an effective strategy to sensitize testicular cancer cell lines and PDX models to cisplatin treatment. Our results warrant further investigation of this combination therapy in the treatment of patients with testicular cancer with high-risk relapsed or refractory disease.

Precision medicine, agriculture, and genome editing: science and ethics

The era of precision medicine has generated advances in various fields of science and medicine with the potential for a paradigm shift in healthcare delivery that will ultimately lead to an individualized approach to medicine. Such timely topics were explored in 2018 at a workshop held at the Third International Conference on One Medicine One Science (iCOMOS), in Minneapolis, Minnesota. A broad range of scientists and regulatory experts provided detailed insights into the challenges and opportunities associated with precision medicine and gene editing. There was a general consensus that advances in studying the genomic traits driving differential pharmacogenomics will undoubtedly enhance individualized treatments for a wide variety of diseases. Ethical considerations, societal implications, approaches for prioritizing safe and secure use of treatment modalities, and the advent of high-throughput computing and analysis of large, complex datasets were discussed. Large biobanks, such as the All of Us Research Program and the Veterans Affairs Million Veterans Program, can aid studies of various conditions in massive cohorts of patients. As the applications of precision medicine continue to mature, the full potential and promise of these individualized approaches will continue to yield important advances in transplant medicine, oncology, public health, agriculture, pharmacology, and bioinformatics.

Targeting DNA methylation for treating triple-negative breast cancer

Triple-negative breast cancer (TNBC) accounts for 15-20% of all invasive breast cancers and tends to have aggressive histological features and poor clinical outcomes. Unlike, estrogen receptor- or HER2-positive diseases, TNBC patients currently lack the US FDA-approved targeted therapies. DNA methylation is a critical mechanism of epigenetic modification. It is well known that aberrant DNA methylation contributes to the malignant transformation of cells by silencing critical tumor suppressor genes. DNA methyltransferase inhibitors reactivate silenced tumor suppressor genes and result in tumor growth arrest, with therapeutic effects observed in patients with hematologic malignancies. The antitumor effect of these DNA methyltransferase inhibitors has also been explored in solid tumors, especially in TNBC that currently lacks targeted therapies.

PANOPLY: Omics-Guided Drug Prioritization Method Tailored to an Individual Patient

PURPOSE

The majority of patients with cancer receive treatments that are minimally informed by omics data. We propose a precision medicine computational framework, PANOPLY (Precision Cancer Genomic Report: Single Sample Inventory), to identify and prioritize drug targets and cancer therapy regimens.

MATERIALS AND METHODS

The PANOPLY approach integrates clinical data with germline and somatic features obtained from multiomics platforms and applies machine learning and network analysis approaches in the context of the individual patient and matched controls. The PANOPLY workflow uses the following four steps: selection of matched controls to the patient of interest; identification of patient-specific genomic events; identification of suitable drugs using the driver-gene network and random forest analyses; and provision of an integrated multiomics case report of the patient with prioritization of anticancer drugs.

RESULTS

The PANOPLY workflow can be executed on a stand-alone virtual machine and is also available for download as an R package. We applied the method to an institutional breast cancer neoadjuvant chemotherapy study that collected clinical and genomic data as well as patient-derived xenografts to investigate the prioritization offered by PANOPLY. In a chemotherapy-resistant patient-derived xenograft model, we found that that the prioritized drug, olaparib, was more effective than placebo in treating the tumor ( P < .05). We also applied PANOPLY to in-house and publicly accessible multiomics tumor data sets with therapeutic response or survival data available.

CONCLUSION

PANOPLY shows promise as a means to prioritize drugs on the basis of clinical and multiomics data for an individual patient with cancer. Additional studies are needed to confirm this approach.

Bone sarcoma patient-derived xenografts are faithful and stable preclinical models for molecular and therapeutic investigations

Standard therapy of osteosarcoma (OS) and Ewing sarcoma (EW) rests on cytotoxic regimes, which are largely unsuccessful in advanced patients. Preclinical models are needed to break this impasse. A panel of patient-derived xenografts (PDX) was established by implantation of fresh, surgically resected osteosarcoma (OS) and Ewing sarcoma (EW) in NSG mice. Engraftment was obtained in 22 of 61 OS (36%) and 7 of 29 EW (24%). The success rate in establishing primary cell cultures from OS was lower than the percentage of PDX engraftment in mice, whereas the reverse was observed for EW; the implementation of both in vivo and in vitro seeding increased the proportion of patients yielding at least one workable model. The establishment of in vitro cultures from PDX was highly efficient in both tumor types, reaching 100% for EW. Morphological and immunohistochemical (SATB2, P-glycoprotein 1, CD99, caveolin 1) studies and gene expression profiling showed a remarkable similarity between patient’s tumor and PDX, which was maintained over several passages in mice, whereas cell cultures displayed a lower correlation with human samples. Genes differentially expressed between OS original tumor and PDX mostly belonged to leuykocyte-specific pathways, as human infiltrate is gradually replaced by murine leukocytes during growth in mice. In EW, which contained scant infiltrates, no gene was differentially expressed between the original tumor and the PDX. A novel therapeutic combination of anti-CD99 diabody C7 and irinotecan was tested against two EW PDX; both drugs inhibited PDX growth, the addition of anti-CD99 was beneficial when chemotherapy alone was less effective. The panel of OS and EW PDX faithfully mirrored morphologic and genetic features of bone sarcomas, representing reliable models to test therapeutic approaches.

Patient-Derived Xenograft Models of Breast Cancer and Their Application

Recently, patient-derived xenograft (PDX) models of many types of tumors including breast cancer have emerged as a powerful tool for predicting drug efficacy and for understanding tumor characteristics. PDXs are established by the direct transfer of human tumors into highly immunodeficient mice and then maintained by passaging from mouse to mouse. The ability of PDX models to maintain the original features of patient tumors and to reflect drug sensitivity has greatly improved both basic and clinical study outcomes. However, current PDX models cannot completely predict drug efficacy because they do not recapitulate the tumor microenvironment of origin, a failure which puts emphasis on the necessity for the development of the next generation PDX models. In this article, we summarize the advantages and limitations of current PDX models and discuss the future directions of this field.

Spontaneous murine tumors in the development of patient-derived xenografts: a potential pitfall

Patient-derived xenografts (PDX) are generated in immune deficient mice and demonstrate histologic and molecular features similar to their corresponding human tumors. However, murine tumors (non-human) spontaneously occur in these models. 120 consecutive patients with high-risk primary breast cancer enrolled in the prospective neoadjuvant BEAUTY study had tumor tissue obtained at the time of diagnosis. These tumor cells, including initial tissue and subsequent generations, were injected into either NSG (n = 365) or NOD-SCID (n = 396) female mice. Mice with initial tumor growth sufficient for transfer to the 2nd generation underwent histologic review by pathologists, including Ki67 staining. After passaging the tumors for up to 4 generations, at least one primary mouse tumor was detected from 24 of the 54 PDX-lines, for a frequency of 3.2% (24 mice out of 761 mice), including murine lymphomas (n = 13), mammary tumors (n = 7), osteosarcomas (n = 2), and hemangiosarcomas (n = 2). While true PDX showed scattered strong staining with Ki67, murine tumors were Ki67 negative. No significant differences (p = 0.062) were observed comparing development of murine tumors in NOD-SCID (n = 8) vs NSG mice (n = 16). While PDX are a useful tool in cancer research, there is a potential for spontaneous murine tumors to arise, which could alter results of studies utilizing PDX. Morphologic review by a pathologist, potentially along with Ki67 staining, is necessary to ensure that tumor growth represents the desired PDX prior to use in downstream studies. This study is the first prospective study evaluating the frequency, type, and time frame for development of non-human tumors.

Systematic Review of Patient-Derived Xenograft Models for Preclinical Studies of Anti-Cancer Drugs in Solid Tumors

Patient-derived xenograft (PDX) models are used as powerful tools for understanding cancer biology in PDX clinical trials and co-clinical trials. In this systematic review, we focus on PDX clinical trials or co-clinical trials for drug development in solid tumors and summarize the utility of PDX models in the development of anti-cancer drugs, as well as the challenges involved in this approach, following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Recently, the assessment of drug efficacy by PDX clinical and co-clinical trials has become an important method. PDX clinical trials can be used for the development of anti-cancer drugs before clinical trials, with their efficacy assessed by the modified response evaluation criteria in solid tumors (mRECIST). A few dozen cases of PDX models have completed enrollment, and the efficacy of the drugs is assessed by 1 × 1 × 1 or 3 × 1 × 1 approaches in the PDX clinical trials. Furthermore, co-clinical trials can be used for personalized care or precision medicine with the evaluation of a new drug or a novel combination. Several PDX models from patients in clinical trials have been used to assess the efficacy of individual drugs or drug combinations in co-clinical trials.

PD-L1 (B7-H1) Competes with the RNA Exosome to Regulate the DNA Damage Response and Can Be Targeted to Sensitize to Radiation or Chemotherapy

Programmed death ligand 1 (PD-L1, also called B7-H1) is an immune checkpoint protein that inhibits immune function through its binding of the programmed cell death protein 1 (PD-1) receptor. Clinically approved antibodies block extracellular PD-1 and PD-L1 binding, yet the role of intracellular PD-L1 in cancer remains poorly understood. Here, we discovered that intracellular PD-L1 acts as an RNA binding protein that regulates the mRNA stability of NBS1, BRCA1, and other DNA damage-related genes. Through competition with the RNA exosome, intracellular PD-L1 protects targeted RNAs from degradation, thereby increasing cellular resistance to DNA damage. RNA immunoprecipitation and RNA-seq experiments demonstrated that PD-L1 regulates RNA stability genome-wide. Furthermore, we developed a PD-L1 antibody, H1A, which abrogates the interaction of PD-L1 with CMTM6, thereby promoting PD-L1 degradation. Intracellular PD-L1 may be a potential therapeutic target to enhance the efficacy of radiotherapy and chemotherapy in cancer through the inhibition of DNA damage response and repair.

Integrative In Vivo Drug Testing Using Gene Expression Signature and Patient-Derived Xenografts from Treatment-Refractory HER2 Positive and Triple-Negative Subtypes of Breast Cancer

Patient-derived xenografts (PDXs) are powerful tools for translational cancer research. Here, we established PDX models from different molecular subtypes of breast cancer for in vivo drug tests and compared the histopathologic features of PDX model tumors with those of patient tumors. Predictive biomarkers were identified by gene expression analysis of PDX samples using Nanostring nCount cancer panels. Validation of predictive biomarkers for treatment response was conducted in established PDX models by in vivo drug testing. Twenty breast cancer PDX models were generated from different molecular subtypes (overall success rate, 17.5%; 3.6% for HR⁺/HER2^-, 21.4% for HR⁺/HER2⁺, 21.9% for HR^-/HER2⁺ and 22.5% for triple-negative breast cancer (TNBC)). The histopathologic features of original tumors were retained in the PDX models. We detected upregulated HIF1A, RAF1, AKT2 and VEGFA in TNBC cases and demonstrated the efficacy of combined treatment with sorafenib and everolimus or docetaxel and bevacizumab in each TNBC model. Additionally, we identified upregulated HIF1A in two cases of trastuzumab-exposed HR^-/HER2⁺ PDX models and validated the efficacy of the HIF1A inhibitor, PX-478, alone or in combination with neratinib. Our results demonstrate that PDX models can be used as effective tools for predicting therapeutic markers and evaluating personalized treatment strategies in breast cancer patients with resistance to standard chemotherapy regimens.

Patient-Derived Xenografts Can Be Reliably Generated from Patient Clinical Biopsy Specimens

BACKGROUND

Patient-derived xenografts (PDX) are clinically relevant human cancer models that can be used to guide individualized medicine. We aimed to generate PDX models from clinically obtained biopsy specimens (surgical or image-guided) hypothesizing that low volume biopsy specimens could provide sufficient viable tissue to successfully engraft PDX models from patients with unresectable or metastatic disease.

MATERIALS AND METHODS

We maintain a prospective high volume gastrointestinal malignancy PDX program. With informed consent and institutional approval, biopsy specimens (surgical or image-guided) were obtained from patients with unresectable or metastatic tumors: pancreatic adenocarcinoma (PDAC), cholangiocarcinoma, gastric and gallbladder carcinoma. Biopsies were implanted into immunodeficient mice. Tumor growth was monitored, viable tumor was passed into subsequent generations, and histopathology was confirmed.

RESULTS

In this study, biopsy specimens from 29 patients were used for PDX engraftment. Successful PDX engraftment was variable with highest engraftment rates in gastric and gallbladder carcinoma specimens (100%) compared to engraftment rates of 33% and 29% in PDAC and cholangiocarcinoma respectively. PDX models created from metastasis biopsies compared to unresectable primary tumor tissue demonstrated higher engraftment rates (69% versus 15.4%, p = 0.001). PDX models demonstrated higher engraftment rates when biopsies were obtained during surgical operations (n = 15) compared to image-guided (n = 14) (73% versus 14%, p = 0.003). Patient age, pretreatment status, or ischemic time was not different between biopsy methods.

CONCLUSIONS

PDX models can be successfully created from clinical biopsy specimens in patients with metastatic or unresectable GI cancers. The use of clinical biopsy specimens for PDX engraftment can expand the repertoire of stage-specific PDX models for downstream basic/translational research.

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.

Post-neoadjuvant treatment and the management of residual disease in breast cancer: state of the art and perspectives

Achieving a pathologic complete response after neoadjuvant treatment is associated with improved prognosis in breast cancer. The CREATE-X trial demonstrated a significant survival improvement with capecitabine in patients with residual invasive disease after neoadjuvant chemotherapy, and the KATHERINE trial showed a significant benefit of trastuzumab-emtansine (TDM1) in human epidermal growth factor receptor 2 (HER2)-positive patients who did not achieve a pathologic complete response after neoadjuvant treatment, creating interesting alternatives of post-neoadjuvant treatments for high-risk patients. New agents are arising as therapeutic options for metastatic breast cancer such as the cyclin-dependent kinase inhibitors and the immune-checkpoint inhibitors, but none has been incorporated into the post-neoadjuvant setting so far. Evolving techniques such as next-generation sequencing and gene expression profiles have improved our knowledge regarding the biology of residual disease, and also on the mechanisms involved in treatment resistance. The present manuscript reviews the current available strategies, the ongoing trials, the potential biomarker-guided approaches and the perspectives for the post-neoadjuvant treatment and the management of residual disease after neoadjuvant treatment in breast cancer.

The novel function of tumor protein D54 in regulating pyruvate dehydrogenase and metformin cytotoxicity in breast cancer

Background

The role of tumor protein D54 in breast cancer has not been studied and its function in breast cancer remains unclear. In our previous pharmacogenomic studies using lymphoblastoid cell line (LCL), this protein has been identified to affect metformin response. Although metformin has been widely studied as a prophylactic and chemotherapeutic drug, there is still a lack of biomarkers predicting the response to metformin in breast cancer. In this study, we revealed the novel function of TPD54 in breast cancer through understanding how TPD54 altered the cancer cell sensitivity to metformin.

Methods

The role of TPD54 in altering cellular sensitivity to metformin treatment was carried out by either knockdown or overexpression of TPD54, followed by measuring cell viability and reactive oxygen species (ROS) production in MCF7 breast cancer cell line and breast cancer patient-derived xenografts. Functional analysis of TPD54 in breast cancer cells was demonstrated by studying TPD54 protein localization and identification of potential binding partners of TPD54 through immunoprecipitation followed by mass spectrometry. The effect of TPD54 on pyruvate dehydrogenase (PDH) protein regulation was demonstrated by western blot, immunoprecipitation, and site-directed mutagenesis.

Results

TPD54 inhibited colony formation and enhanced cellular sensitivity to metformin treatment in MCF7 cells and breast cancer patient-derived xenografts. Mechanistic study indicated that TPD54 had mitochondrial localization, bound to and stabilized pyruvate dehydrogenase E1α by blocking pyruvate dehydrogenase kinase 1 (PDK1)-mediated serine 232 phosphorylation. TPD54 knockdown increased PDH E1α protein degradation and led to decreased PDH enzyme activity, which reduced mitochondrial oxygen consumption and reactive oxygen species (ROS) production, thus contributing to the resistance of breast cancer cells to metformin treatment.

Conclusion

We have discovered a novel mechanism by which TPD54 regulates pyruvate dehydrogenase and affects the sensitivity of breast cancer to metformin treatment. Our findings highlight the important post-translational regulation of PDK1 on PDH E1α and the potential application of TPD54 as a biomarker for selecting tumors that may be sensitive to metformin therapy. These provide new insights into understanding the regulation of PDH complexes and the resistance mechanisms of cancer cells to metformin treatment.

Electronic supplementary material

The online version of this article (10.1186/s40170-018-0193-4) contains supplementary material, which is available to authorized users.

Tyrosine Phosphorylation of Mitochondrial Creatine Kinase 1 Enhances a Druggable Tumor Energy Shuttle Pathway

How mitochondrial metabolism is altered by oncogenic tyrosine kinases to promote tumor growth is incompletely understood. Here, we show that oncogenic HER2 tyrosine kinase signaling induces phosphorylation of mitochondrial creatine kinase 1 (MtCK1) on tyrosine 153 (Y153) in an ABL-dependent manner in breast cancer cells. Y153 phosphorylation, which is commonly upregulated in HER2+ breast cancers, stabilizes MtCK1 to increase the phosphocreatine energy shuttle and promote proliferation. Inhibition of the phosphocreatine energy shuttle by MtCK1 knockdown or with the creatine analog cyclocreatine decreases proliferation of trastuzumab-sensitive and -resistant HER2+ cell lines in culture and in xenografts. Finally, we show that cyclocreatine in combination with the HER2 kinase inhibitor lapatinib reduces the growth of a trastuzumab-resistant HER2+ patient-derived xenograft. These findings suggest that activation of the phosphocreatine energy shuttle by MtCK1 Y153 phosphorylation creates a druggable metabolic vulnerability in cancer.

ATR Inhibition Is a Promising Radiosensitizing Strategy for Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is characterized by elevated locoregional recurrence risk despite aggressive local therapies. New tumor-specific radiosensitizers are needed. We hypothesized that the ATR inhibitor, VX-970 (now known as M6620), would preferentially radiosensitize TNBC. Noncancerous breast epithelial and TNBC cell lines were investigated in clonogenic survival, cell cycle, and DNA damage signaling and repair assays. In addition, patient-derived xenograft (PDX) models generated prospectively as part of a neoadjuvant chemotherapy study from either baseline tumor biopsies or surgical specimens with chemoresistant residual disease were assessed for sensitivity to fractionated radiotherapy, VX-970, or the combination. To explore potential response biomarkers, exome sequencing was assessed for germline and/or somatic alterations in homologous recombination (HR) genes and other alterations associated with ATR inhibitor sensitivity. VX-970 preferentially inhibited ATR-Chk1-CDC25a signaling, abrogated the radiotherapy-induced G₂-M checkpoint, delayed resolution of DNA double-strand breaks, and reduced colony formation after radiotherapy in TNBC cells relative to normal-like breast epithelial cells. In vivo, VX-970 did not exhibit significant single-agent activity at the dose administered even in the context of genomic alterations predictive of ATR inhibitor responsiveness, but significantly sensitized TNBC PDXs to radiotherapy. Exome sequencing and functional testing demonstrated that combination therapy was effective in both HR-proficient and -deficient models. PDXs established from patients with chemoresistant TNBC were also highly radiosensitized. In conclusion, VX-970 is a tumor-specific radiosensitizer for TNBC. Patients with residual TNBC after neoadjuvant chemotherapy, a subset at particularly high risk of relapse, may be ideally suited for this treatment intensification strategy. Mol Cancer Ther; 17(11); 2462-72. ©2018 AACR.

DNA methyltransferase expression in triple-negative breast cancer predicts sensitivity to decitabine

Triple-negative breast cancer (TNBC) is a heterogeneous disease with poor prognosis that lacks targeted therapies, especially in patients with chemotherapy-resistant disease. Since DNA methylation-induced silencing of tumor suppressors is common in cancer, reversal of promoter DNA hypermethylation by 5-aza-2'-deoxycytidine (decitabine), an FDA-approved DNA methyltransferase (DNMT) inhibitor, has proven effective in treating hematological neoplasms. However, its antitumor effect varies in solid tumors, stressing the importance of identifying biomarkers predictive of therapeutic response. Here, we focused on the identification of biomarkers to select decitabine-sensitive TNBC through increasing our understanding of the mechanism of decitabine action. We showed that protein levels of DNMTs correlated with response to decitabine in patient-derived xenograft (PDX) organoids originating from chemotherapy-sensitive and -resistant TNBCs, suggesting DNMT levels as potential biomarkers of response. Furthermore, all 3 methytransferases, DNMT1, DNMT3A, and DNMT3B, were degraded following low-concentration, long-term decitabine treatment both in vitro and in vivo. The DNMT proteins could be ubiquitinated by the E3 ligase, TNF receptor-associated factor 6 (TRAF6), leading to lysosome-dependent protein degradation. Depletion of TRAF6 blocked decitabine-induced DNMT degradation, conferring resistance to decitabine. Our study suggests a potential mechanism of regulating DNMT protein degradation and DNMT levels as response biomarkers for DNMT inhibitors in TNBCs.

Discovery of a Glucocorticoid Receptor (GR) Activity Signature Using Selective GR Antagonism in ER-Negative Breast Cancer

Purpose: Although high glucocorticoid receptor (GR) expression in early-stage estrogen receptor (ER)-negative breast cancer is associated with shortened relapse-free survival (RFS), how associated GR transcriptional activity contributes to aggressive breast cancer behavior is not well understood. Using potent GR antagonists and primary tumor gene expression data, we sought to identify a tumor-relevant gene signature based on GR activity that would be more predictive than GR expression alone.Experimental Design: Global gene expression and GR ChIP-sequencing were performed to identify GR-regulated genes inhibited by two chemically distinct GR antagonists, mifepristone and CORT108297. Differentially expressed genes from MDA-MB-231 cells were cross-evaluated with significantly expressed genes in GR-high versus GR-low ER-negative primary breast cancers. The resulting subset of GR-targeted genes was analyzed in two independent ER-negative breast cancer cohorts to derive and then validate the GR activity signature (GRsig).Results: Gene expression pathway analysis of glucocorticoid-regulated genes (inhibited by GR antagonism) revealed cell survival and invasion functions. GR ChIP-seq analysis demonstrated that GR antagonists decreased GR chromatin association for a subset of genes. A GRsig that comprised n = 74 GR activation-associated genes (also reversed by GR antagonists) was derived from an adjuvant chemotherapy-treated Discovery cohort and found to predict probability of relapse in a separate Validation cohort (HR = 1.9; P = 0.012).Conclusions: The GRsig discovered herein identifies high-risk ER-negative/GR-positive breast cancers most likely to relapse despite administration of adjuvant chemotherapy. Because GR antagonism can reverse expression of these genes, we propose that addition of a GR antagonist to chemotherapy may improve outcome for these high-risk patients. Clin Cancer Res; 24(14); 3433-46. ©2018 AACR.