Patient-derived xenograft models to improve targeted therapy in epithelial ovarian cancer treatment

Assessment of Fallopian Tube Epithelium Features Derived from Induced Pluripotent Stem Cells of Both Fallopian Tube and Skin Origins

Fallopian tube epithelial cells (FTECs) play a significant role in the development of high-grade serous ovarian cancer (HGSOC), but their utilization in in vitro experiments presents challenges. To address these limitations, induced pluripotent stem cells (iPSCs) have been employed as a potential solution, driven by the hypothesis that orthologous iPSCs may offer superior differentiation capabilities compared with their non-orthologous counterparts. Our objective was to generate iPSCs from FTECs, referred to as FTEC-iPSCs, and compare their differentiation potential with iPSCs derived from skin keratinocytes (NHEK). By introducing a four-factor Sendai virus transduction system, we successfully derived iPSCs from FTECs. To assess the differentiation capacity of iPSCs, we utilized embryoid body formation, revealing positive immunohistochemical staining for markers representing the three germ layers. In vivo tumorigenesis evaluation further validated the pluripotency of iPSCs, as evidenced by the formation of tumors in immunodeficient mice, with histological analysis confirming the presence of tissues from all three germ layers. Quantitative polymerase chain reaction (qPCR) analysis illuminated a sequential shift in gene expression, encompassing pluripotent, mesodermal, and intermediate mesoderm-related genes, during the iPSC differentiation process into FTECs. Notably, the introduction of WNT3A following intermediate mesoderm differentiation steered the cells toward a FTEC phenotype, supported by the expression of FTEC-related markers and the formation of tubule-like structures. In specific culture conditions, the expression of FTEC-related genes was comparable in FTECs derived from FTEC-iPSCs compared with those derived from NHEK-iPSCs. To conclude, our study successfully generated iPSCs from FTECs, demonstrating their capacity for FTEC differentiation. Furthermore, iPSCs originating from orthologous cell sources exhibited comparable differentiation capabilities. These findings hold promise for using iPSCs in modeling and investigating diseases associated with these specific cell types.

Polyglycerol-Based Biomedical Matrix for Immunomagnetic Circulating Tumor Cell Isolation and Their Expansion into Tumor Spheroids for Drug Screening

Circulating tumor cells (CTCs) are established as distinct cancer biomarkers for diagnosis, as preclinical models, and therapeutic targets. Their use as preclinical models is limited owing to low purity after isolation and the lack of effective techniques to create 3D cultures that accurately mimic in vivo conditions. Herein, a two-component system for detecting, isolating, and expanding CTCs to generate multicellular tumor spheroids that mimic the physiology and microenvironment of the diseased organ is proposed. First, an antifouling biointerface on magnetic beads is fabricated by adding a bioinert polymer layer and conjugation of biospecific ligands to isolate cancer cells, dramatically enhancing the selectivity and purity of the isolated cancer cells. Next, the isolated cells are encapsulated into self-degradable hydrogels synthesized using a thiol-click approach. The hydrogels are mechanochemically tuned to enable tumor spheroid growth to a size greater than 300 µm and to further release the grown spheroids while retaining their tumor-like characteristics. In addition, drug treatment highlights the need for 3D culture environments rather than conventional 2D culture. The designed biomedical matrix shows potential as a universal method to ensure mimicry of in vivo tumor characteristics in individual patients and to improve the predictability of preclinical screening of personalized therapeutics.

Clinicopathological characteristics associated with the engraftment of patient lymphoma cells in NOG mice

Patient-derived xenograft (PDX) mouse models are useful for deepening our understanding of the biology of malignant lymphoma; however, factors associated with the success of the PDX lymphoma model are largely unknown. We retrospectively analyzed the characteristics of 66 xenotransplantations from 65 patients. In all, 43 (65%) specimens were obtained from patients aged > 60 years, and 42 (64%) specimens were obtained at diagnosis. Specimens were obtained from patients with the following diseases: diffuse large B-cell lymphoma (n = 30), intravascular large B-cell lymphoma (n = 12), follicular lymphoma (n = 8), peripheral T-cell lymphoma (n = 7), mantle cell lymphoma (n = 2), and other (n = 7). The specimens were sourced mainly from bone marrow (n = 31, 47%) and extranodal tumors (n = 13, 20%). Engraftment was successful in 33/66 (50%) xenotransplantations. The median age of patients who provided successful specimens was significantly higher than that for unsuccessful specimens (p = 0.013). Specimens with a high proportion of tumor cells in the graft and those obtained from patients with relapsed/refractory disease showed higher tendencies toward successful engraftment. Taken together, these data suggest that tumor cells with a highly malignant potential might have a high likelihood of engraftment.

Humanized Patient-derived Xenograft Models of Disseminated Ovarian Cancer Recapitulate Key Aspects of the Tumor Immune Environment within the Peritoneal Cavity

The importance of the immune microenvironment in ovarian cancer progression, metastasis, and response to therapies has become increasingly clear, especially with the new emphasis on immunotherapies. To leverage the power of patient-derived xenograft (PDX) models within a humanized immune microenvironment, three ovarian cancer PDXs were grown in humanized NBSGW (huNBSGW) mice engrafted with human CD34+ cord blood-derived hematopoietic stem cells. Analysis of cytokine levels in the ascites fluid and identification of infiltrating immune cells in the tumors demonstrated that these humanized PDX (huPDX) established an immune tumor microenvironment similar to what has been reported for patients with ovarian cancer. The lack of human myeloid cell differentiation has been a major setback for humanized mouse models, but our analysis shows that PDX engraftment increases the human myeloid population in the peripheral blood. Analysis of cytokines within the ascites fluid of huPDX revealed high levels of human M-CSF, a key myeloid differentiation factor as well as other elevated cytokines that have previously been identified in ovarian cancer patient ascites fluid including those involved in immune cell differentiation and recruitment. Human tumor-associated macrophages and tumor-infiltrating lymphocytes were detected within the tumors of humanized mice, demonstrating immune cell recruitment to tumors. Comparison of the three huPDX revealed certain differences in cytokine signatures and in the extent of immune cell recruitment. Our studies show that huNBSGW PDX models reconstitute important aspects of the ovarian cancer immune tumor microenvironment, which may recommend these models for preclinical therapeutic trials.

Significance

huPDX models are ideal preclinical models for testing novel therapies. They reflect the genetic heterogeneity of the patient population, enhance human myeloid differentiation, and recruit immune cells to the tumor microenvironment.

Shikonin impedes type 2 ovarian cancer progression via FasL/caspase-8 and mir-874-3p/XIAP axis and prohibits the properties of stemness

Ovarian cancer is the most lethal gynecological cancer in women. Shikonin (SHK), derived from Lithospermum eryothrorhizon, can reduce cancer activity; however, its clinical effect on type 2 ovarian cancer cells remains undetermined. Here, we studied the effects of SHK on type 2 ovarian cancer using the KURAMOCHI, OVSAHO, CP70, and ascites E04 cell lines. The proliferation curve and half-maximal inhibitory concentration of SHK for the cell lines were evaluated using the second-generation tetrazolium dye assay and the cell viability were determined by the annexin V/PI as well as TUNEL assay. The caspase dependent pathway was performed by western blotting assay with pan-caspase inhibitor Z-VAD-FMK and SHK induced miR-874-3p expression thus suppressed anti-apoptosis markers XIAP and Bcl-xL. The effect of SHK on type 2 ovarian cancer cell migration and invasion was evaluated using the wound healing and transwell assays. Quantitative RT-PCR and western blot was used to evaluate cancer stem cell (CSC)-related gene/protein (OCT4, SOX2, NANOG, ALDH1, and C-MYC) expressions, sphere formation assay was executed and a xenograft animal model for in vivo antitumor effects of SHK. Taken together, Shikonin suppressed type 2 ovarian cancer cell viability, migration, and invasion abilities; decreased CSC-related markers expression as well as the sphere colony numbers. It also reduced the tumorigenicity of KURAMOCHI ALDH+ cells and induced anti-tumor effect in a xenograft model. Thus, SHK could contribute a potential therapeutic strategy on type 2 ovarian cancer cells via multiple functions.

The Proteolytic Landscape of Ovarian Cancer: Applications in Nanomedicine

Ovarian cancer (OvCa) is one of the leading causes of mortality globally with an overall 5-year survival of 47%. The predominant subtype of OvCa is epithelial carcinoma, which can be highly aggressive. This review launches with a summary of the clinical features of OvCa, including staging and current techniques for diagnosis and therapy. Further, the important role of proteases in OvCa progression and dissemination is described. Proteases contribute to tumor angiogenesis, remodeling of extracellular matrix, migration and invasion, major processes in OvCa pathology. Multiple proteases, such as metalloproteinases, trypsin, cathepsin and others, are overexpressed in the tumor tissue. Presence of these catabolic enzymes in OvCa tissue can be exploited for improving early diagnosis and therapeutic options in advanced cases. Nanomedicine, being on the interface of molecular and cellular scales, can be designed to be activated by proteases in the OvCa microenvironment. Various types of protease-enabled nanomedicines are described and the studies that focus on their diagnostic, therapeutic and theranostic potential are reviewed.

Instructive Hydrogels for Primary Tumor Cell Culture: Current Status and Outlook

Primary tumor organoids (PTOs) growth in hydrogels have emerged as an important in vitro model that recapitulates many characteristics of the native tumor tissue, and have important applications in fundamental cancer research and for the development of useful therapeutic treatment. This paper begins with reviewing the methods of isolation of primary tumor cells. Then, recent advances on the instructive hydrogels as biomimetic extracellular matrix for primary tumor cell culture and construction of PTO models are summarized. Emerging microtechnology for growth of PTOs in microscale hydrogels and the applications of PTOs are highlighted. This paper concludes with an outlook on the future directions in the investigation of instructive hydrogels for PTO growth.

Three-Dimensional Modelling of Ovarian Cancer: From Cell Lines to Organoids for Discovery and Personalized Medicine

Ovarian cancer has the highest mortality of all of the gynecological malignancies. There are several distinct histotypes of this malignancy characterized by specific molecular events and clinical behavior. These histotypes have differing responses to platinum-based drugs that have been the mainstay of therapy for ovarian cancer for decades. For histotypes that initially respond to a chemotherapeutic regime of carboplatin and paclitaxel such as high-grade serous ovarian cancer, the development of chemoresistance is common and underpins incurable disease. Recent discoveries have led to the clinical use of PARP (poly ADP ribose polymerase) inhibitors for ovarian cancers defective in homologous recombination repair, as well as the anti-angiogenic bevacizumab. While predictive molecular testing involving identification of a genomic scar and/or the presence of germline or somatic BRCA1 or BRCA2 mutation are in clinical use to inform the likely success of a PARP inhibitor, no similar tests are available to identify women likely to respond to bevacizumab. Functional tests to predict patient response to any drug are, in fact, essentially absent from clinical care. New drugs are needed to treat ovarian cancer. In this review, we discuss applications to address the currently unmet need of developing physiologically relevant in vitro and ex vivo models of ovarian cancer for fundamental discovery science, and personalized medicine approaches. Traditional two-dimensional (2D) in vitro cell culture of ovarian cancer lacks critical cell-to-cell interactions afforded by culture in three-dimensions. Additionally, modelling interactions with the tumor microenvironment, including the surface of organs in the peritoneal cavity that support metastatic growth of ovarian cancer, will improve the power of these models. Being able to reliably grow primary tumoroid cultures of ovarian cancer will improve the ability to recapitulate tumor heterogeneity. Three-dimensional (3D) modelling systems, from cell lines to organoid or tumoroid cultures, represent enhanced starting points from which improved translational outcomes for women with ovarian cancer will emerge.

Xenograft Models of Ovarian Cancer for Therapy Evaluation

The evaluation of novel treatment regimes in ovarian cancer, ranging from cytotoxic agents and targeted therapy to surgery, demands clinically relevant mouse models to mimic human disease. These more advanced preclinical models provide a tool to obtain robust data on the mechanism of action, cytotoxicity and therapeutic efficacy of newly emerging antitumor therapies.In this chapter, we describe how to generate ovarian cancer xenograft models through injection of human tumor cell lines in immunocompromised mice. Detailed methodological descriptions are provided for both the commonly applied subcutaneous model and the more technically challenging orthotopic tumor model that involves inoculation of cancer cells in the ovarian bursa. We demonstrate how to monitor tumor growth and metastases in orthotopic ovarian models through noninvasive optical imaging and the procedures for treatment strategy, including administration of test compounds and debulking surgery. We comment on the strengths, limitations, and procedural challenges associated with each of the models.

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.

The role of the tumor primary chemosensitivity relative to the success of the medical-surgical management in patients with advanced ovarian carcinomas

In patients with advanced ovarian carcinomas, the first-line treatment has historically relied on debulking surgery and platinum-based chemotherapy. If the major therapeutic/prognostic role of the surgery part is well understood, and integrated in disease-management algorithms, the impact of chemotherapy efficacy has been insufficiently addressed. This review describes the main indicators of the chemosensitivity reported in the literature (pathological response score & biomarkers; genomic alterations; DNA scars; imaging; and circulating tumor markers), and investigates the respective roles of the debulking surgery and tumor primary chemosensitivity relative to the success of the comprehensive medical-surgical treatment. The tumor primary chemosensitivity exhibits a major independent prognostic impact on the feasibility of complete interval debulking surgery after neoadjuvant chemotherapy, risk of subsequent platinum-resistant relapse, efficacy of subsequent maintenance therapies with bevacizumab or PARP inhibitors, progression-free survival, overall and long-term survival. While both the completeness of the surgery and the tumor primary chemosensitivity are undoubtedly major prognostic factors, the impact of the surgery may differ according to the primary chemosensitivity. This assumption raises a potential new concept: in patients with advanced ovarian carcinomas, the maximum tumor debulking should ideally be both biological (induced by systemic treatments) and physical (induced by surgery) for maximizing patient survival. Besides BRCA and HRD biomarkers, future trials and algorithms may integrate indicator(s) of the tumor primary chemosensitivity for guiding more subtly the surgical and medical management in first-line setting. Moreover, such a parameter would help in the development of novel approaches meant to reverse the resistance to chemotherapy and PARP inhibitors.

Personalized models of heterogeneous 3D epithelial tumor microenvironments: Ovarian cancer as a model

Intractable human diseases such as cancers, are context dependent, unique to both the individual patient and to the specific tumor microenvironment. However, conventional cancer treatments are often nonspecific, targeting global similarities rather than unique drivers. This limits treatment efficacy across heterogeneous patient populations and even at different tumor locations within the same patient. Ultimately, this poor efficacy can lead to adverse clinical outcomes and the development of treatment-resistant relapse. To prevent this and improve outcomes, it is necessary to be selective when choosing a patient's optimal adjuvant treatment. In this review, we posit the use of personalized, tumor-specific models (TSM) as tools to achieve this remarkable feat. First, using ovarian cancer as a model disease, we outline the heterogeneity and complexity of both the cellular and extracellular components in the tumor microenvironment. Then we examine the advantages and disadvantages of contemporary cancer models and the rationale for personalized TSM. We discuss how to generate precision 3D models through careful and detailed analysis of patient biopsies. Finally, we provide clinically relevant applications of these versatile personalized cancer models to highlight their potential impact. These models are ideal for a myriad of fundamental cancer biology and translational studies. Importantly, these approaches can be extended to other carcinomas, facilitating the discovery of new therapeutics that more effectively target the unique aspects of each individual patient's TME. STATEMENT OF SIGNIFICANCE: In this article, we have presented the case for the application of biomaterials in developing personalized models of complex diseases such as cancers. TSM could bring about breakthroughs in the promise of precision medicine. The critical components of the diverse tumor microenvironments, that lead to treatment failures, include cellular- and extracellular matrix- heterogeneity, and biophysical signals to the cells. Therefore, we have described these dynamic components of the tumor microenvironments, and have highlighted how contemporary biomaterials can be utilized to create personalized in vitro models of cancers. We have also described the application of the TSM to predict the dynamic patterns of disease progression, and predict effective therapies that can produce durable responses, limit relapses, and treat any minimal residual disease.

Comprehending the Proteomic Landscape of Ovarian Cancer: A Road to the Discovery of Disease Biomarkers

Despite recent technological advancements allowing the characterization of cancers at a molecular level along with biomarkers for cancer diagnosis, the management of ovarian cancers (OC) remains challenging. Proteins assume functions encoded by the genome and the complete set of proteins, termed the proteome, reflects the health state. Comprehending the circulatory proteomic profiles for OC subtypes, therefore, has the potential to reveal biomarkers with clinical utility concerning early diagnosis or to predict response to specific therapies. Furthermore, characterization of the proteomic landscape of tumor-derived tissue, cell lines, and PDX models has led to the molecular stratification of patient groups, with implications for personalized therapy and management of drug resistance. Here, we review single and multiple marker panels that have been identified through proteomic investigations of patient sera, effusions, and other biospecimens. We discuss their clinical utility and implementation into clinical practice.

Establishment and preclinical application of a patient-derived xenograft model for uterine cancer

BACKGROUND

The patient-derived xenograft (PDX) model is a promising translational platform for duplicating the characteristics of primary tumors. Here, we established and characterized PDX models of uterine cancer to demonstrate their utility for preclinical drug testing.

MATERIALS AND METHODS

We generated PDX tumors surgically derived from 58 cases of uterine cancer. Subrenal capsule xenografts and primary tumors were compared using microscopic examination, short tandem repeat analyses, and targeted sequencing analyses. A phosphatidylinositol 3-kinase (PI3K) inhibitor was administered to mice whose PDX tumors harbored a PTEN deletion or PIK3CA mutation. We also generated an orthotopic PDX model using uterine horn implantation.

RESULTS

Thirty-three (56.9%) PDXs were successfully generated and passaged to maintain tumors. The histological features of the PDX tumors were stable over subsequent passages. By contrast, the proportions of epithelial and mesenchymal components of carcinosarcoma PDX models varied by generation. Targeted sequencing analyses revealed that all mutated cancer-related genes were stable during establishment and subgrafting. Treatment with a PI3K inhibitor cased a significant decrease in tumor weight in the clear cell carcinoma PDX harboring a frameshift PTEN deletion (p = 0.049) and in the serous carcinoma PDX harboring a missense PI3KCA mutation (p = 0.003) compared with matched controls. We also successfully established orthotopic PDX models (3/3; 100.0%).

CONCLUSIONS

The histological and genetic features of PDXs were similar to those of primary tumors. This model is a promising translational platform for preclinical testing of new anticancer drugs and will enable the personalized development of therapeutic options for uterine cancer.

Assessing Preclinical Research Models for Immunotherapy for Gynecologic Malignancies

Gynecologic malignancies are increasing in incidence, with a plateau in clinical outcomes necessitating novel treatment options. Immunotherapy and modulation of the tumor microenvironment are rapidly developing fields of interest in gynecologic oncology translational research; examples include the PD-1 (programmed cell death 1) and CTLA-4 (cytotoxic T-lymphocyte-associated protein 4) axes and the Wnt pathway. However, clinical successes with these agents have been modest and lag behind immunotherapy successes in other malignancies. A thorough contextualization of preclinical models utilized in gynecologic oncology immunotherapy research is necessary in order to effectively and efficiently develop translational medicine. These include murine models, in vitro assays, and three-dimensional human-tissue-based systems. Here, we provide a comprehensive review of preclinical models for immunotherapy in gynecologic malignancies, including benefits and limitations of each, in order to inform study design and translational research models. Improved model design and implementation will optimize preclinical research efficiency and increase the translational value to positive findings, facilitating novel treatments that improve patient outcomes.

A Novel, Personalized Drug-Screening System for Platinum-Resistant Ovarian Cancer Patients: A Preliminary Clinical Report

PURPOSE

With this study, we intended to construct a personalized drug-screening system for platinum-resistant ovarian cancer patients by consulting a patient's medical history, data derived from gene mutation detection, and drug screening results derived from mini-PDX (patient-derived xenograft) models. We also aimed to evaluate the efficacy and safety of our system.

PATIENTS AND METHODS

We selected 12 patients with platinum-resistant ovarian cancer who were treated at our hospital from January 2018 to December 2019 to design a single-arm clinical trial. The subsequent chemotherapeutic plans were selected according to a personalized drug-screening system that circulating tumor DNA (ctDNA) testing and the establishment of mini-PDX models. We then analyzed the patients for clinical benefits side-effects in response to chemotherapy in order to evaluate the clinical effects and safety of our new personalized drug-selection system.

RESULTS

We successfully established an individualized and sensitive drug-screening system for the 12 patients. Mini-PDX models verified that potentially effective drugs were identified for 11 of the patients. Treatment resulted in complete remission (one patient), partial remission (five patients), and stable disease (three patients). The remaining three patients experienced disease progression. The overall clinical-benefit rate was 75.0%. Following treatment, the levels of CA125 levels decreased significantly in seven of the 12 patients. Severe side effects, arising from chemotherapy, were only observed in one case.

CONCLUSION

Constructing a personalized drug-screening system for platinum-resistant ovarian cancer patients can be used to guide clinical drug selection and improve the clinical-benefit rate for patients.

TRIAL REGISTRATION NUMBER

ChiCTR1800016766 (Chinese Clinical Trial Registry Center).

Patient-derived xenograft models for the study of benign human neoplasms

Preclinical models are a core feature of translational research, and patient-derived xenograft (PDX) models have increasingly been used with such purpose. PDX involves the transplantation of fresh human tumor samples into immunodeficient mice to overcome immunologic rejection. It is a valuable tool for basic as well as preclinical research, contributing to the establishment of models to characterize the neoplasms to drug screening and to allow the identification of therapeutic targets. The use of these models is justified because they retain the histological and genomic features of the primary tumor. PDX models are well described for malignant neoplasms, for which the advantages are clear and include the development of drug treatments. The establishment of malignant tumors PDX is undeniably important from a medical perspective. However, few studies have used such models for benign neoplasms. The use of PDX for benign neoplasm studies can help to clarify the pathobiology of these diseases, as well as invasion and malignant transformation mechanisms, which from a biological perspective is equally important to the study of malignant tumors. Therefore, the aim of this study is to review the current methodology for PDX model generation and to cover its main applications, focusing on benign neoplasms.

Patient-derived ovarian cancer explants: preserved viability and histopathological features in long-term agitation-based cultures

Ovarian carcinoma (OvC) remains a major therapeutic challenge due to its propensity to develop resistance after an initial response to chemotherapy. Interactions of tumour cells with the surrounding microenvironment play a role in tumour survival, invasion capacity and drug resistance. Cancer models that retain tissue architecture and tumour microenvironment components are therefore essential to understand drug response and resistance mechanisms. Herein, our goal was to develop a long-term OvC patient-derived explant (OvC-PDE) culture strategy in which architecture and cell type heterogeneity of the original tumour would be retained. Samples from 25 patients with distinct OvC types and one with a benign tumour, were cultured for 30 days in agitation-based culture systems with 100% success rate. OvC-PDE cultures retained the original tumour architecture and main cellular components: epithelial cells, fibroblasts and immune cells. Epithelial cells kept their original levels of proliferation and apoptosis. Moreover, the major extracellular components, such as collagen-I and -IV, were retained in explants. OvC-PDE cultures were exposed to standard-of-care chemotherapeutics agents for 2 weeks, attesting the ability of the platform for drug assays employing cyclic drug exposure regimens. We established an OvC-PDE dynamic culture in which tumour architecture and cell type heterogeneity were preserved for the different OvC types, replicating features of the original tumour and compatible with long-term drug exposure for drug efficacy and resistance studies.

Epithelial/mesenchymal heterogeneity of high-grade serous ovarian carcinoma samples correlates with miRNA let-7 levels and predicts tumor growth and metastasis

Patient‐derived samples present an advantage over current cell line models of high‐grade serous ovarian cancer (HGSOC) that are not always reliable and phenotypically faithful models of in vivo HGSOC. To improve upon cell line models of HGSOC, we set out to characterize a panel of patient‐derived cells and determine their epithelial and mesenchymal characteristics. We analyzed RNA and protein expression levels in patient‐derived xenograft (PDX) models of HGSOC, and functionally characterized these models using flow cytometry, wound healing assays, invasion assays, and spheroid cultures. Besides in vitro work, we also evaluated the growth characteristics of PDX in vivo (orthotopic PDX). We found that all samples had hybrid characteristics, covering a spectrum from an epithelial‐to‐mesenchymal state. Samples with a stronger epithelial phenotype were more active in self‐renewal assays and more tumorigenic in orthotopic xenograft models as compared to samples with a stronger mesenchymal phenotype, which were more migratory and invasive. Additionally, we observed an inverse association between microRNA let‐7 (lethal‐7) expression and stemness, consistent with the loss of let‐7 being an important component of the cancer stem cell phenotype. We observed that lower let‐7 levels were associated with the epithelial state and a lower epithelial mesenchymal transition (EMT) score, more efficient spheroid and tumor formation, and increased sensitivity to platinum‐based chemotherapy. Surprisingly, in these HGSOC cells, stemness could be dissociated from invasiveness: Cells with lower let‐7 levels were more tumorigenic, but less migratory, and with a lower EMT score, than those with higher let‐7 levels. We conclude that let‐7 expression and epithelial/mesenchymal state are valuable predictors of HGSOC proliferation, in vitro self‐renewal, and tumor burden in vivo.

CD24-targeted fluorescence imaging in patient-derived xenograft models of high-grade serous ovarian carcinoma

BACKGROUND

The survival rate of patients with advanced high-grade serous ovarian carcinoma (HGSOC) remains disappointing. Clinically translatable orthotopic cell line xenograft models and patient-derived xenografts (PDXs) may aid the implementation of more personalised treatment approaches. Although orthotopic PDX reflecting heterogeneous molecular subtypes are considered the most relevant preclinical models, their use in therapeutic development is limited by lack of appropriate imaging modalities.

METHODS

We developed novel orthotopic xenograft and PDX models for HGSOC, and applied a near-infrared fluorescently labelled monoclonal antibody targeting the cell surface antigen CD24 for non-invasive molecular imaging of epithelial ovarian cancer. CD24-Alexa Fluor 680 fluorescence imaging was compared to bioluminescence imaging in three orthotopic cell line xenograft models of ovarian cancer (OV-90^luc+, Skov-3^luc+ and Caov-3^luc+, n = 3 per model). The application of fluorescence imaging to assess treatment efficacy was performed in carboplatin-paclitaxel treated orthotopic OV-90 xenografts (n = 10), before the probe was evaluated to detect disease progression in heterogenous PDX models (n = 7).

FINDINGS

Application of the near-infrared probe, CD24-AF680, enabled both spatio-temporal visualisation of tumour development, and longitudinal therapy monitoring of orthotopic xenografts. Notably, CD24-AF680 facilitated imaging of multiple PDX models representing different histological subtypes of the disease.

INTERPRETATION

The combined implementation of CD24-AF680 and orthotopic PDX models creates a state-of-the-art preclinical platform which will impact the identification and validation of new targeted therapies, fluorescence image-guided surgery, and ultimately the outcome for HGSOC patients.

FUNDING

This study was supported by the H2020 program MSCA-ITN [675743], Helse Vest RHF, and Helse Bergen HF [911809, 911852, 912171, 240222, HV1269], as well as by The Norwegian Cancer Society [182735], and The Research Council of Norway through its Centers of excellence funding scheme [223250, 262652].

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.

In vitro three-dimensional culture systems of salivary glands

Dry mouth can be caused by salivary gland hypofunction due to Sjögren's syndrome (SS) or radiation therapy for head and neck cancer, and it can also be a side effect of medications. The use of sialagogues effectively increases saliva secretion in patients with dry mouth. However, the application of sialagogues is not always satisfactory because of their side effects, such as sweating, nausea, runny nose and diarrhea. Two-dimensional (2D) cell cultures have been used not only for drug screening and discovery but also to clarify disease mechanisms. However, three-dimensional (3D) cell cultures are expected to be even more advantageous than 2D cell cultures. Therefore, we have tried to develop an in vitro cell culture system that can reconstitute 3D salivary glands. Sox9 and Foxc1 were identified as important genes that differentiate mouse embryonic stem cell-derived oral ectoderm into salivary gland placode. Using these genes and organoid culture systems, we succeeded in generating salivary gland organoids that exhibited a morphology and gene expression profile that were similar to those of the embryonic rudiment from which salivary glands arise in normal mice. These organoids are expected to be a promising tool for disease modeling, drug discovery and regenerative medicine in salivary glands.

A Preliminary Study on the Establishment of the PDTX Model

Objective

The current study aims to explore the establishment of the patient-derived tumor xenograft (PDTX) model.

Materials and Methods

Twenty patients with gastric cancer, 10 males and 10 females, were enrolled in the current study. Firstly, the volume, invasion and metastasis of the xenografts were observed. Subsequently, the correlation between tumor tissues of the PDTX mouse model and the patients' primary tumor tissues was evaluated by pathological H&E staining and immunohistochemistry.

Results

The results showed that the PDTX models corresponding to 15 of the 20 patients were successfully established, and the success rate of PDTX model establishment was 75%. Furthermore, the PDTX models maintained the differentiation degree, morphological characteristics and structural characteristics of tumor cells.

Conclusion

A PDTX model can be used as a substitute for cancer patients in clinical practice and may be suitable for clinical pharmacodynamic screening and new drug development.

A living biobank of ovarian cancer ex vivo models reveals profound mitotic heterogeneity

High-grade serous ovarian carcinoma is characterised by TP53 mutation and extensive chromosome instability (CIN). Because our understanding of CIN mechanisms is based largely on analysing established cell lines, we developed a workflow for generating ex vivo cultures from patient biopsies to provide models that support interrogation of CIN mechanisms in cells not extensively cultured in vitro. Here, we describe a "living biobank" of ovarian cancer models with extensive replicative capacity, derived from both ascites and solid biopsies. Fifteen models are characterised by p53 profiling, exome sequencing and transcriptomics, and karyotyped using single-cell whole-genome sequencing. Time-lapse microscopy reveals catastrophic and highly heterogeneous mitoses, suggesting that analysis of established cell lines probably underestimates mitotic dysfunction in advanced human cancers. Drug profiling reveals cisplatin sensitivities consistent with patient responses, demonstrating that this workflow has potential to generate personalized avatars with advantages over current pre-clinical models and the potential to guide clinical decision making.

Strategies for Delivery of siRNAs to Ovarian Cancer Cells

The unmet need for novel therapeutic options for ovarian cancer (OC) deserves further investigation. Among the different novel drugs, small interfering RNAs (siRNAs) are particularly attractive because of their specificity of action and efficacy, as documented in many experimental setups. However, the fragility of these molecules in the biological environment necessitates the use of delivery materials able to protect them and possibly target them to the cancer cells. Among the different delivery materials, those based on polymers and lipids are considered very interesting because of their biocompatibility and ability to carry/deliver siRNAs. Despite these features, polymers and lipids need to be engineered to optimize their delivery properties for OC. In this review, we concentrated on the description of the therapeutic potential of siRNAs and polymer-/lipid-based delivery systems for OC. After a brief description of OC and siRNA features, we summarized the strategies employed to minimize siRNA delivery problems, the targeting strategies to OC, and the preclinical models available. Finally, we discussed the most interesting works published in the last three years about polymer-/lipid-based materials for siRNA delivery.

Current strategies for different paclitaxel-loaded Nano-delivery Systems towards therapeutic applications for ovarian carcinoma: A review article

Ovarian carcinoma (OC) is one of the leading causes of death among gynecologic malignancies all over the world. It is characterized by high mortality rate because of the lack of early diagnosis. The first-line chemotherapeutic regimen for late stage epithelial ovarian cancer is paclitaxel in combination to carboplatin. However, in most of cases, relapse occurs within six months despite the initial success of this chemotherapeutic combination. A lot of challenges have been encountered with the conventional delivery of paclitaxel in addition to the occurrence of severe off-target toxicity. One major problem is poor paclitaxel solubility which was improved by addition of Cremophor EL that unfortunately resulted in hypersensitivity side effects. Another obstacle is the multi drug resistance which is the main cause of OC recurrence. Accordingly, incorporation of paclitaxel, solely or in combination to other drugs, in nanocarrier systems has grabbed attention of many researchers to circumvent all these hurdles. The current review is the first article that provides a comprehensive overview on multi-faceted implementations of paclitaxel loaded nanoplatforms to solve delivery obstacles of paclitaxel in management of ovarian carcinoma. Moreover, challenges in physicochemical properties, biological activity and targeted delivery of PTX were depicted with corresponding solutions using nanotechnology. Different categories of nanocarriers employed were collected included lipid, protein, polymeric, solid nanoemulsion and hybrid systems. Future perspectives including imperative research considerations in ovarian cancer therapy were proposed as well.

Establishment of patient-derived xenograft model in ovarian cancer and its influence factors analysis

AIM

Patient-derived xenograft (PDX) model has been applied to the study of breast cancer, lung cancer, colon cancer and other cancers. However, its feasibility in ovarian cancer has not been understood. This study aimed to establish ovarian cancer PDX model and reveal its influence factors.

METHODS

In this study, 27 patients in Obstetrics and Gynecology Hospital affiliated to Fudan University from May 2015 to May 2016 were employed to explore the method of PDX model in ovarian cancer and verify its feasibility.

RESULTS

Finally, five cases of PDX models were successfully established, and the tumor formation rate (TFR) was 18.52%. In addition, immunohistochemistry and transcriptome sequencing analysis showed that tumor of PDX model have similar gene expression, gene splicing, gene fusion and single nucleotide polymorphisms with primary tumor (R² = 0.741). Furthermore, it was revealed that compared to epithelial ovarian cancer, the TFR of PDX models with nonepithelial ovarian cancer was higher, while other factors such as the initiation site of tumor, the degree of tumor malignancy, the stage of tumor, the type of tumor and the species of experimental animals were not associated with the TFR.

CONCLUSION

Ovarian cancer PDX model, as a new scientific research model, can better keep the biological characteristics of primary tumor, which has great research value in ovarian cancer.

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.

Establishment of the PDTX model of gynecological tumors

OBJECTIVE

Fresh tumor tissues from patients with gynecological tumors were obtained by surgery or biopsy, and transplanted into NOD-Prkdcem26ll2rgem26Nju (NCG) mice to establish a patient-derived tumor xenograft (PDTX).

MATERIALS AND METHODS

A total of 15 patients with gynecologic tumors were enrolled into the present study. Among these patients, 12 patients had epithelial fallopian tube/ovarian/peritoneal cancer, one patient had metastatic ovarian cancer, and two patients had cervical cancer. Furthermore, among these patients, three patients were treated with puncture or microscopy biopsy, six patients underwent laparoscopic surgery, and six patients underwent robotic surgery. The tumor formation latency, tumor formation rate, tumor volume, tumor invasion and metastasis of the transplanted tumor were observed, the consistency of the PDTX model tumor tissue and patient's primary tumor tissue was compared by pathological H&E staining, and pharmacodynamics testing was performed.

RESULTS

Seven of 15 PDTX models were successfully established, with a success rate of 46.7%. The tumor formation time ranged within 21-130 days, with a median tumor formation time of 73 days. The PDTX model maintained the differentiation, morphological and structural characteristics of tumor cells, and the pharmacodynamic test was completed in five patients.

CONCLUSION

The PDTX model is highly consistent with the pathology of the patient's tumor, and can be used as a substitute for clinical patients to guide the accurate treatment and scientific research of gynecological tumors.

Current Status of Patient-Derived Ovarian Cancer Models

Ovarian cancer (OC) is one of the leading causes of female cancer death. Recent studies have documented its extensive variations as a disease entity, in terms of cell or tissue of origin, pre-cancerous lesions, common mutations, and therapeutic responses, leading to the notion that OC is a generic term referring to a whole range of different cancer subtypes. Despite such heterogeneity, OC treatment is stereotypic; aggressive surgery followed by conventional chemotherapy could result in chemo-resistant diseases. Whereas molecular-targeted therapies will become shortly available for a subset of OC, there still remain many patients without effective drugs, requiring development of groundbreaking therapeutic agents. In preclinical studies for drug discovery, cancer cell lines used to be the gold standard, but now this has declined due to frequent failure in predicting therapeutic responses in patients. In this regard, patient-derived cells and tumors are gaining more attention in precise and physiological modeling of in situ tumors, which could also pave the way to implementation of precision medicine. In this article, we comprehensively overviewed the current status of various platforms for patient-derived OC models. We highly appreciate the potentials of organoid culture in achieving high success rate and retaining tumor heterogeneity.

Gene expression differences between matched pairs of ovarian cancer patient tumors and patient-derived xenografts

As patient derived xenograft (PDX) models are increasingly used for preclinical drug development, strategies to account for the nonhuman component of PDX RNA expression data are critical to its interpretation. A bioinformatics pipeline to separate donor tumor and mouse stroma transcriptome profiles was devised and tested. To examine the molecular fidelity of PDX versus donor tumors, we compared mRNA differences between paired PDX-donor tumors from nine ovarian cancer patients. 1,935 differentially expressed genes were identified between PDX and donor tumors. Over 90% (n = 1767) of these genes were down-regulated in PDX models and enriched in stroma-specific functions. Several protein kinases were also differentially expressed in PDX tumors, e.g. PDGFRA, PDGFRB and CSF1R. Upon in silico removal of these PDX-donor tumor differentially expressed genes, a stronger transcriptional resemblance between PDX-donor tumor pairs was seen (average correlation coefficient increases from 0.91 to 0.95). We devised and validated an effective bioinformatics strategy to separate mouse stroma expression from human tumor expression for PDX RNAseq. In addition, we showed most of the PDX-donor differentially expressed genes were implicated in stromal components. The molecular similarities and differences between PDX and donor tumors have implications in future therapeutic trial designs and treatment response evaluations using PDX models.

Combined MEK and BCL-2/XL Inhibition Is Effective in High-Grade Serous Ovarian Cancer Patient-Derived Xenograft Models and BIM Levels Are Predictive of Responsiveness

Most patients with late-stage high-grade serous ovarian cancer (HGSOC) initially respond to chemotherapy but inevitably relapse and develop resistance, highlighting the need for novel therapies to improve patient outcomes. The MEK/ERK pathway is activated in a large subset of HGSOC, making it an attractive therapeutic target. Here, we systematically evaluated the extent of MEK/ERK pathway activation and efficacy of pathway inhibition in a large panel of well-annotated HGSOC patient-derived xenograft models. The vast majority of models were nonresponsive to the MEK inhibitor cobimetinib (GDC-0973) despite effective pathway inhibition. Proteomic analyses of adaptive responses to GDC-0973 revealed that GDC-0973 upregulated the proapoptotic protein BIM, thus priming the cells for apoptosis regulated by BCL2-family proteins. Indeed, combination of both MEK inhibitor and dual BCL-2/XL inhibitor (ABT-263) significantly reduced cell number, increased cell death, and displayed synergy in vitro in most models. In vivo, GDC-0973 and ABT-263 combination was well tolerated and resulted in greater tumor growth inhibition than single agents. Detailed proteomic and correlation analyses identified two subsets of responsive models-those with high BIM at baseline that was increased with MEK inhibition and those with low basal BIM and high pERK levels. Models with low BIM and low pERK were nonresponsive. Our findings demonstrate that combined MEK and BCL-2/XL inhibition has therapeutic activity in HGSOC models and provide a mechanistic rationale for the clinical evaluation of this drug combination as well as the assessment of the extent to which BIM and/or pERK levels predict drug combination effectiveness in chemoresistant HGSOC.

Predictive approaches for drug combination discovery in cancer

Drug combinations have been proposed as a promising therapeutic strategy to overcome drug resistance and improve efficacy of monotherapy regimens in cancer. This strategy aims at targeting multiple components of this complex disease. Despite the increasing number of drug combinations in use, many of them were empirically found in the clinic, and the molecular mechanisms underlying these drug combinations are often unclear. These challenges call for rational, systematic approaches for drug combination discovery. Although high-throughput screening of single-agent therapeutics has been successfully implemented, it is not feasible to test all possible drug combinations, even for a reduced subset of anticancer drugs. Hence, in vitro and in vivo screening of a large number of drug combinations are not practical. Therefore, devising computational methods to efficiently explore the space of drug combinations and to discover efficacious combinations has attracted a lot of attention from the scientific community in the past few years. Nevertheless, in the absence of consensus regarding the computational approaches used to predict efficacious drug combinations, a plethora of methods, techniques and hypotheses have been developed to date, while the research field lacks an elaborate categorization of the existing computational methods and the available data sources. In this manuscript, we review and categorize the state-of-the-art computational approaches for drug combination prediction, and elaborate on the limitations of these methods and the existing challenges. We also discuss about the recent pan-cancer drug combination data sets and their importance in revising the available methods or developing more performant approaches.

Hydrogel microenvironments for cancer spheroid growth and drug screening

Multicellular cancer spheroids (MCSs) have emerged as a promising in vitro model that replicates many features of solid tumors in vivo. Biomimetic hydrogel scaffolds for MCS growth offer a broad spectrum of biophysical and biochemical cues that help to recapitulate the behavior of natural extracellular matrix, essential for regulating cancer cell behavior. This perspective highlights recent advances in the development of hydrogel environments for MCS growth, release, and drug screening. We review the use of different types of hydrogels for MCS growth, the effect of biophysical and biochemical cues on MCS fate, the isolation of MCSs from hydrogel scaffolds, the utilization of microtechnologies, and the applications of MCSs grown in hydrogels. We conclude with the discussion of new research directions in the development of hydrogels for MCS growth.

Novel ex vivo ovarian cancer tissue explant assay for prediction of chemosensitivity and response to novel therapeutics

The majority of ovarian cancer patients present with advanced disease and despite aggressive treatment, prognosis remains poor. Response to first-line carboplatin-containing chemotherapy is usually good, however, recurrence rates and subsequent chemoresistance are very high and ultimately responsible for the fatal outcome of the disease. To improve treatment outcomes pre-clinical models that can predict individual patient response to 1st line chemotherapy and novel therapeutics are urgently required. In this study, we employed an ex vivo ovarian cancer tissue explant assay to assess response to carboplatin and an inhibitor of the extracellular matrix molecule, hyaluronan (4-methylubelliferone, 4-MU), shown to inhibit cancer metastasis. Cryopreserved ovarian cancer tissues were cultured on gelatine sponges for 48-120 h with increasing concentrations of carboplatin (0-400 μM) or 4-MU (1 mM) alone or the combination of both drugs. Effects on apoptosis and proliferation were assessed by immunohistochemistry using antibodies to cleaved caspase 3 or Ki67, respectively. The ex vivo tissue explant assay maintained viable tumor cells in an intact tumor microenvironment similar to the in vivo situation over the 120 h culture period. Carboplatin treatment promoted apoptosis in chemosensitive (P = 0.0047) but not chemoresistant cancer tissues. The combination of 4-MU (1 mM) and carboplatin (100 μM) significantly increased apoptosis (P = 0.0111) and reduced proliferation (P = 0.0064) in chemoresistant tissues. Overall, our results show that the ex vivo explant assay is a robust and cost effective model to assess chemosensitivity and the effect of novel therapeutics in ovarian cancer.

Aptamers as potential therapeutic agents for ovarian cancer

Current therapy for ovarian cancer typically involves indiscriminate chemotherapies that can have severe off target effects on healthy tissue and are still plagued by aggressive recurrence. Recent shifts towards targeted therapies offer the possibility of circumventing the obstacles experienced by these traditional treatments. While antibodies are the pioneering agents in targeted therapies, clinical experience has demonstrated that their antitumor efficacy is limited due to their high immunogenicity, large molecular size, and costly and laborious production. In contrast, nucleic acid based chemical antibodies, also known as aptamers, are ideal for this application given their small size, lack of immunogenicity and in vitro production. As aptamers have begun to demonstrate their promise through targeting Epithelial Cell Adhesion Molecule (EpCAM), as well as a number of ovarian cancer biomarkers, in in vivo and in vitro models, their clinical applicability is slowly being realised. This review explores some of the current progress of aptamers targeting cancer biomarkers and their potential role as ovarian cancer therapeutics.

Directed Differentiation of Human Induced Pluripotent Stem Cells into Fallopian Tube Epithelium

The fallopian tube epithelium (FTE) has been recognized as a site of origin of high-grade serous ovarian cancer (HGSC). However, the absence of relevant in vitro human models that can recapitulate tissue-specific architecture has hindered our understanding of FTE transformation and initiation of HGSC. Here, induced pluripotent stem cells (iPSCs) were used to establish a novel 3-dimensional (3D) human FTE organoid in vitro model containing the relevant cell types of the human fallopian tube as well as a luminal architecture that closely reflects the organization of fallopian tissues in vivo. Modulation of Wnt and BMP signaling directed iPSC differentiation into Müllerian cells and subsequent use of pro-Müllerian growth factors promoted FTE precursors. The expression and localization of Müllerian markers verified correct cellular differentiation. An innovative 3D growth platform, which enabled the FTE organoid to self-organize into a convoluted luminal structure, permitted matured differentiation to a FTE lineage. This powerful human-derived FTE organoid model can be used to study the earliest stages of HGSC development and to identify novel and specific biomarkers of early fallopian tube epithelial cell transformation.

Investigation of factors affecting the efficacy of 3C23K, a human monoclonal antibody targeting MISIIR

MISIIR is a potential target for ovarian cancer (OC) therapy due to its tissue-specific pattern of expression. 3C23K is a novel therapeutic monoclonal anti-MISIIR antibody designed to recruit effector cells and promote cell death through ADCC (antibody dependent cell-mediated cytotoxicity). Our objective was to determine the tolerability and efficacy of 3C23K in OC patient-derived xenografts (PDX) and to identify factors affecting efficacy. Quantitative RT-PCR, immunohistochemistry (IHC), and flow cytometry were used to categorize MISIIR expression in established PDX models derived from primary OC patients. We selected two high expressing models and two low expressing models for in vivo testing. One xenograft model using an MISIIR over-expressing SKOV3ip cell line (Z3) was a positive control. The primary endpoint was change in tumor size. The secondary endpoint was final tumor mass. We observed no statistically significant differences between control and treated animals. The lack of response could be secondary to a number of variables including the lack of known biomarkers of response, the low membrane expression of MISIIR, and a limited ability of 3C23K to induce ADCC in PDX models. Further study is needed to determine the magnitude of ovarian cancer response to 3C23K and also if there is a threshold surface expression to predict response.

Prevention of Human Lymphoproliferative Tumor Formation in Ovarian Cancer Patient-Derived Xenografts

Interest in preclinical drug development for ovarian cancer has stimulated development of patient-derived xenograft (PDX) or tumorgraft models. However, the unintended formation of human lymphoma in severe combined immunodeficiency (SCID) mice from Epstein-Barr virus (EBV)–infected human lymphocytes can be problematic. In this study, we have characterized ovarian cancer PDXs which developed human lymphomas and explore methods to suppress lymphoproliferative growth. Fresh human ovarian tumors from 568 patients were transplanted intraperitoneally in SCID mice. A subset of PDX models demonstrated atypical patterns of dissemination with mediastinal masses, hepatosplenomegaly, and CD45-positive lymphoblastic atypia without ovarian tumor engraftment. Expression of human CD20 but not CD3 supported a B-cell lineage, and EBV genomes were detected in all lymphoproliferative tumors. Immunophenotyping confirmed monoclonal gene rearrangements consistent with B-cell lymphoma, and global gene expression patterns correlated well with other human lymphomas. The ability of rituximab, an anti-CD20 antibody, to suppress human lymphoproliferation from a patient's ovarian tumor in SCID mice and prevent growth of an established lymphoma led to a practice change with a goal to reduce the incidence of lymphomas. A single dose of rituximab during the primary tumor heterotransplantation process reduced the incidence of CD45-positive cells in subsequent PDX lines from 86.3% (n = 117 without rituximab) to 5.6% (n = 160 with rituximab), and the lymphoma rate declined from 11.1% to 1.88%. Taken together, investigators utilizing PDX models for research should routinely monitor for lymphoproliferative tumors and consider implementing methods to suppress their growth.

Patient-Derived Xenograft Models of Epithelial Ovarian Cancer for Preclinical Studies

Purpose

Patient-derived tumor xenografts (PDXs) can provide more reliable information about tumor biology than cell line models. We developed PDXs for epithelial ovarian cancer (EOC) that have histopathologic and genetic similarities to the primary patient tissues and evaluated their potential for use as a platform for translational EOC research.

Materials and Methods

We successfully established PDXs by subrenal capsule implantation of primary EOC tissues into female BALB/C-nude mice. The rate of successful PDX engraftment was 48.8% (22/45 cases). Hematoxylin and eosin staining and short tandem repeat analysis showed histopathological and genetic similarity between the PDX and primary patient tissues.

Results

Patients whose tumors were successfully engrafted in mice had significantly inferior overall survival when compared with those whose tumors failed to engraft (p=0.040). In preclinical tests of this model, we found that paclitaxel-carboplatin combination chemotherapy significantly deceased tumor weight in PDXs compared with the control treatment (p=0.013). Moreover, erlotinib treatment significantly decreased tumor weight in epidermal growth factor receptor–overexpressing PDX with clear cell histology (p=0.023).

Conclusion

PDXs for EOC with histopathological and genetic stability can be efficiently developed by subrenal capsule implantation and have the potential to provide a promising platform for future translational research and precision medicine for EOC.

Biological basis of cancer health disparities: resources and challenges for research

Last few decades have witnessed remarkable progress in our understanding of cancer initiation and progression leading to refinement of prevention and treatment approaches. Although these advances have improved the survival of cancer patients in general, certain racial/ethnic groups have benefited only partially. Footprints of cancer-associated racial disparities are very much evident in cancers of the prostate, breast, cervical, colorectal, endometrium, liver and lung. These health inequalities are mostly attributed to socioeconomic differences among races, but there is a growing realization that these may actually be due to inherent biological differences as well. Indeed, significant data now exist to support the biological basis of racial disparities in cancer, warranting basic research investigations, using appropriate tools and model systems. In this article, we have aimed to succinctly review the literature supporting the biological bases of racial disparities in cancer, along with available resources, databases and model systems that will be of interest to researchers. Moreover, we have highlighted the specific areas that need attention in terms of development of resources and/or tools, and discuss the opportunities and challenges in basic biological research in cancer health disparities.

Genome-wide methylation profiling of ovarian cancer patient-derived xenografts treated with the demethylating agent decitabine identifies novel epigenetically regulated genes and pathways

Background

In high-grade serous ovarian cancer (HGSOC), intrinsic and/or acquired resistance against platinum-containing chemotherapy is a major obstacle for successful treatment. A low frequency of somatic mutations but frequent epigenetic alterations, including DNA methylation in HGSOC tumors, presents the cancer epigenome as a relevant target for innovative therapy. Patient-derived xenografts (PDXs) supposedly are good preclinical models for identifying novel drug targets. However, the representativeness of global methylation status of HGSOC PDXs compared to their original tumors has not been evaluated so far. Aims of this study were to explore how representative HGSOC PDXs are of their corresponding patient tumor methylome and to evaluate the effect of epigenetic therapy and cisplatin on putative epigenetically regulated genes and their related pathways in PDXs.

Methods

Genome-wide analysis of the DNA methylome of HGSOC patients with their corresponding PDXs, from different generations, was performed using Infinium 450 K methylation arrays. Furthermore, we analyzed global methylome changes after treatment of HGSOC PDXs with the FDA approved demethylating agent decitabine and cisplatin. Findings were validated by bisulfite pyrosequencing with subsequent pathway analysis. Publicly available datasets comprising HGSOC patients were used to analyze the prognostic value of the identified genes.

Results

Only 0.6–1.0 % of all analyzed CpGs (388,696 CpGs) changed significantly (p < 0.01) during propagation, showing that HGSOC PDXs were epigenetically stable. Treatment of F3 PDXs with decitabine caused a significant reduction in methylation in 10.6 % of CpG sites in comparison to untreated PDXs (p < 0.01, false discovery rate <10 %). Cisplatin treatment had a marginal effect on the PDX methylome. Pathway analysis of decitabine-treated PDX tumors revealed several putative epigenetically regulated pathways (e.g., the Src family kinase pathway). In particular, the C-terminal Src kinase (CSK) gene was successfully validated for epigenetic regulation in different PDX models and ovarian cancer cell lines. Low CSK methylation and high CSK expression were both significantly associated (p < 0.05) with improved progression-free survival and overall survival in HGSOC patients.

Conclusions

HGSOC PDXs resemble the global epigenome of patients over many generations and can be modulated by epigenetic drugs. Novel epigenetically regulated genes such as CSK and related pathways were identified in HGSOC. Our observations encourage future application of PDXs for cancer epigenome studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-016-0361-5) contains supplementary material, which is available to authorized users.

Histologic and molecular analysis of patient derived xenografts of high-grade serous ovarian carcinoma

BACKGROUND

Patient derived xenografts (PDX) are generated by transplanting the original patient's tumor tissue into immune-deficient mice. Unlike xenograft models derived from cell lines, PDX models can better preserve the histopathology from the original patient and molecular pathways. High-grade serous carcinoma (HGSC) is a deadly form of ovarian/fallopian tube cancer whose response to current chemotherapies varies widely due to patient variability. Therefore, a PDX model can provide a valuable tool to study and test treatment options for each individual patient.

METHODS

In this study, over 200 PDX tumors from nine HGSC were analyzed to investigate the nature and behavior of PDX tumors originating from HGSC. PDX tumors were serially passaged (from P0 to P4) and tumors were grafted orthotopically under the ovarian bursa or subcutaneously.

RESULTS

Comparative analysis of the histology and molecular markers of tumors from over 200 PDX tumor-bearing mice, revealed that the tumors maintained similar histologies, stem cell populations, and expression for the majority of the tested oncogenic markers, compared to the primary tumors. However, a significant loss of steroid hormone receptors and altered expression of immunoresponsive genes in PDX tumors were also noted.

CONCLUSION

Our findings provide substantial new information about PDX tumor characteristics from HGSC which will be valuable towards the development of personalized therapy and new drug development for HGSC.

Successful Xenograft of Endoscopic Ultrasound-Guided Fine-Needle Aspiration Specimen from Human Extrahepatic Cholangiocarcinoma into an Immunodeficient Mouse

Patient-derived tumor xenograft is the transfer of primary human tumors directly into an immunodeficient mouse. Patient-derived tumor xenograft plays an important role in the development and evaluation of new chemotherapeutic agents. We succeeded in generating a patient-derived tumor xenograft of a biliary tumor obtained by endoscopic ultrasound-guided fine-needle aspiration from a patient who had an inoperable extrahepatic cholangiocarcinoma. This patient-derived tumor xenograft will be a promising tool for individualized cancer therapy and can be used in developing new chemotherapeutic agents for the treatment of biliary cancer in the future.

Patient-Derived Tumor Xenografts Are Susceptible to Formation of Human Lymphocytic Tumors

Patient-derived xenograft (PDX) tumor models have emerged as a new approach to evaluate the effects of cancer drugs on patients’ personalized tumor grafts enabling to select the best treatment for the cancer patient and providing a new tool for oncology drug developers. Here, we report that human tumors engrafted in immunodeficient mice are susceptible to formation of B-and T-cell PDX tumors. We xenografted human primary and metastatic tumor samples into immunodeficient mice and found that a fraction of PDX tumors generated from patients’ samples of breast, colon, pancreatic, bladder and renal cancer were histologically similar to lymphocytic neoplasms. Moreover, we found that the first passage of breast and pancreatic cancer PDX tumors after initial transplantation of the tumor pieces from the same human tumor graft could grow as a lymphocytic tumor in one mouse and as an adenocarcinoma in another mouse. Whereas subcutaneous PDX tumors resembling human adenocarcinoma histology were slow growing and non-metastatic, we found that subcutaneous PDX lymphocytic tumors were fast growing and formed large metastatic lesions in mouse lymph nodes, liver, lungs, and spleen. PDX lymphocytic tumors were comprised of B-cells which were Epstein-Barr virus positive and expressed CD45 and CD20. Because B-cells are typically present in malignant solid tumors, formation of B-cell tumor may evolve in a wide range of PDX tumor models. Although PDX tumor models show great promise in the development of personalized therapy for cancer patients, our results suggest that confidence in any given PDX tumor model requires careful screening of lymphocytic markers.

Precision or Personalized Medicine for Cancer Chemotherapy: Is there a Role for Herbal Medicine

Although over 100 chemotherapeutic agents are currently available for the treatment of cancer patients, the overall long term clinical benefit is disappointing due to the lack of effectiveness or severe side effects from these agents. In order to improve the therapeutic outcome, a new approach called precision medicine or personalized medicine has been proposed and initiated by the U.S. National Institutes of Health. However, the limited availability of effective medications and the high cost are still the major barriers for many cancer patients. Thus alternative approaches such as herbal medicines could be a feasible and less costly option. Unfortunately, scientific evidence for the efficacy of a majority of herbal medicines is still lacking and their development to meet FDA approval or other regulatory agencies is a big challenge. However, herbal medicines may be able to play an important role in precision medicine or personalized medicine. This review will focus on the existing and future technologies that could speed the development of herbal products for treatment of resistant cancer in individual patients. Specifically, it will concentrate on reviewing the phenotypic (activity based) rather than genotypic (mechanism based) approach to develop herbal medicine useful for personalized cancer chemotherapy.

Preclinical models for interrogating drug action in human cancers using Stable Isotope Resolved Metabolomics (SIRM)

AIMS

In this review we compare the advantages and disadvantages of different model biological systems for determining the metabolic functions of cells in complex environments, how they may change in different disease states, and respond to therapeutic interventions.

BACKGROUND

All preclinical drug-testing models have advantages and drawbacks. We compare and contrast established cell, organoid and animal models with ex vivo organ or tissue culture and in vivo human experiments in the context of metabolic readout of drug efficacy. As metabolism reports directly on the biochemical state of cells and tissues, it can be very sensitive to drugs and/or other environmental changes. This is especially so when metabolic activities are probed by stable isotope tracing methods, which can also provide detailed mechanistic information on drug action. We have developed and been applying Stable Isotope-Resolved Metabolomics (SIRM) to examine metabolic reprogramming of human lung cancer cells in monoculture, in mouse xenograft/explant models, and in lung cancer patients in situ (Lane et al. 2011; T. W. Fan et al. 2011; T. W-M. Fan et al. 2012; T. W. Fan et al. 2012; Xie et al. 2014b; Ren et al. 2014a; Sellers et al. 2015b). We are able to determine the influence of the tumor microenvironment using these models. We have now extended the range of models to fresh human tissue slices, similar to those originally described by O. Warburg (Warburg 1923), which retain the native tissue architecture and heterogeneity with a paired benign versus cancer design under defined cell culture conditions. This platform offers an unprecedented human tissue model for preclinical studies on metabolic reprogramming of human cancer cells in their tissue context, and response to drug treatment (Xie et al. 2014a). As the microenvironment of the target human tissue is retained and individual patient's response to drugs is obtained, this platform promises to transcend current limitations of drug selection for clinical trials or treatments.

CONCLUSIONS AND FUTURE WORK

Development of ex vivo human tissue and animal models with humanized organs including bone marrow and liver show considerable promise for analyzing drug responses that are more relevant to humans. Similarly using stable isotope tracer methods with these improved models in advanced stages of the drug development pipeline, in conjunction with tissue biopsy is expected significantly to reduce the high failure rate of experimental drugs in Phase II and III clinical trials.

Network Modeling Identifies Patient-specific Pathways in Glioblastoma

Glioblastoma is the most aggressive type of malignant human brain tumor. Molecular profiling experiments have revealed that these tumors are extremely heterogeneous. This heterogeneity is one of the principal challenges for developing targeted therapies. We hypothesize that despite the diverse molecular profiles, it might still be possible to identify common signaling changes that could be targeted in some or all tumors. Using a network modeling approach, we reconstruct the altered signaling pathways from tumor-specific phosphoproteomic data and known protein-protein interactions. We then develop a network-based strategy for identifying tumor specific proteins and pathways that were predicted by the models but not directly observed in the experiments. Among these hidden targets, we show that the ERK activator kinase1 (MEK1) displays increased phosphorylation in all tumors. By contrast, protein numb homolog (NUMB) is present only in the subset of the tumors that are the most invasive. Additionally, increased S100A4 is associated with only one of the tumors. Overall, our results demonstrate that despite the heterogeneity of the proteomic data, network models can identify common or tumor specific pathway-level changes. These results represent an important proof of principle that can improve the target selection process for tumor specific treatments.