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

Developing transcriptomic biomarkers for TAVO412 utilizing next generation sequencing analyses of preclinical tumor models

Introduction

TAVO412, a multi-specific antibody targeting epidermal growth factor receptor (EGFR), mesenchymal epithelial transition factor (c-Met), and vascular endothelial growth factor A (VEGF-A), is undergoing clinical development for the treatment of solid tumors. TAVO412 has multiple mechanisms of action for tumor growth inhibition that include shutting down the EGFR, c-Met, and VEGF signaling pathways, having enhanced Fc effector functions, addressing drug resistance that can be mediated by the crosstalk amongst these three targets, as well as inhibiting angiogenesis. TAVO412 demonstrated strong in vivo tumor growth inhibition in 23 cell-line derived xenograft (CDX) models representing diverse cancer types, as well as in 9 patient-derived xenograft (PDX) lung tumor models.

Methods

Using preclinical CDX data, we established transcriptomic biomarkers based on gene expression profiles that were correlated with anti-tumor response or distinguished between responders and non-responders. Together with specific driver mutation that associated with efficacy and the targets of TAVO412, a set of 21-gene biomarker was identified to predict the efficacy. A biomarker predictor was formulated based on the Linear Prediction Score (LPS) to estimate the probability of patients or tumor model response to TAVO412 treatment.

Results

This efficacy predictor for TAVO412 demonstrated 78% accuracy in the CDX training models. The biomarker model was further validated in the PDX data set and resulted in comparable accuracy.

Conclusions

In implementing precision medicine by leveraging preclinical model data, a predictive transcriptomic biomarker empowered by next-generation sequencing was identified that could optimize the selection of patients that may benefit most from TAVO412 treatment.

Cell-Derived Allograft Models as a Solution to the Obstacles of Preclinical Studies under Limited Resources: A Systematic Review on Experimental Lung Cancer Animal Models

BACKGROUND

The use of appropriate animal models for cancer studies is a major challenge, particularly for investigators who lack the resources to maintain and use xenograft animals or genetically engineered mouse models (GEMM). In addition, several countries intending to incorporate these models must conduct importation procedures, posing an additional challenge.

OBJECTIVE

This review aimed to explore the use of cell-derived allograft or syngeneic models under limited resources. The results can be used by investigators, specifically from low-middle-income countries, to contribute to lung cancer eradication.

METHODS

A literature search was carried out on various databases, including PubMed, Web of Science, and Scopus. In addition, the publication year of the selected articles was set between 2013 and 2023 with different search components (SC), namely lung cancer (SC1), animal models (SC2), and preclinical studies (SC3).

RESULTS

This systematic review focused on selecting animals, cells, and methods that could be applied to generating allograft-type lung cancer animal models from 101 included articles.

CONCLUSION

Based on the results, the use of cell-derived allograft models in cancer studies is feasible and relevant, and it provides valuable insights regarding the conditions with limited resources.

Progression and perspectives in disease modeling for Juvenile myelomonocytic leukemia

Juvenile myelomonocytic leukemia (JMML) is a rare myeloproliferative neoplasm occurring in infants and young children. JMML has been shown to be resistant to all conventional cytotoxic chemotherapy drugs, and current curative therapies still rely on hematopoietic stem cell transplantation, which carries a high risk of relapse post-transplantation. This underscores the urgent need for novel treatment strategies. However, the rarity of JMML poses a major limitation for research, as it is difficult to collect substantial primary research material. To gain a deeper insight into the underlying biological mechanisms of JMML, researchers are continuously improving and developing preclinical research models to better emulate the disease. Therefore, this review aims to delineate the various experimental models currently employed in JMML, including patient-derived cell-based models, cell models, and animal models. We will discuss the characterization of these models in the context of JMML, hoping to provide a valuable reference for researchers in this field.

3D whole body preclinical micro-CT database of subcutaneous tumors in mice with annotations from 3 annotators

A pivotal animal model for development of anticancer molecules is mice with subcutaneous tumors, grown by injection of xenografted tumor cells, where micro-Computed Tomography (µCT) of the mice is used to analyze the efficacy of the anticancer molecule. Manual delineation of the tumor region is necessary for the analysis, which is time-consuming and inconsistent, highlighting the need for automatic segmentation (AS) tools. This study introduces a preclinical µCT database, comprising 452 whole-body scans from 223 individual mice with subcutaneous tumors, spanning ten diverse µCT datasets conducted between 2014 and 2020 on a preclinical PET/CT scanner, making it the hitherto largest dataset of its kind. Each tumor is annotated manually by three expert annotators, allowing for robust model development. Inter-annotator agreement was analyzed, and we report an overall annotation agreement of 0.903 ± 0.046 (mean ± std) Fleiss' Kappa and a mean deviation in volume estimation of 0.015 ± 0.010 cm3 (6.9% ± 4.7), which establishes a human baseline accuracy for delineation of subcutaneous tumors, while showing good inter-annotator agreement.

Patient-Derived-Xenografts in Mice: A Preclinical Platform for Cancer Research

The use of patient-derived xenografts (PDXs) has dramatically improved drug development programs. PDXs (1) reproduce the pathological features and the genomic profile of the parental tumors more precisely than other preclinical models, and (2) more faithfully predict therapy response. However, PDXs have limitations. These include the inability to completely capture tumor heterogeneity and the role of the immune system, the low engraftment efficiency of certain tumor types, and the consequences of the human-host interactions. Recently, the use of novel mouse strains and specialized engraftment techniques has enabled the generation of "humanized" PDXs, partially overcoming such limitations. Importantly, establishing, characterizing, and maintaining PDXs is costly and requires a significant regulatory, administrative, clinical, and laboratory infrastructure. In this review, we will retrace the historical milestones that led to the implementation of PDXs for cancer research, review the most recent innovations in the field, and discuss future avenues to tackle deficiencies that still exist.

Glioblastoma research on zebrafish xenograft models: a systematic review

Glioblastoma (GBM) constitutes the most common primary brain tumor in adults. The challenges in GBM therapeutics have shed light on zebrafish used as a promising animal model for preclinical GBM xenograft studies without a standardized methodology. This systematic review aims to summarize the advances in zebrafish GBM xenografting, compare research protocols to pinpoint advantages and underlying limitations, and designate the predominant xenografting parameters. Based on the PRISMA checklist, we systematically searched PubMed, Scopus, and ZFIN using the keywords "glioblastoma," "xenotransplantation," and "zebrafish" for papers published from 2005 to 2022, available in English. 46 articles meeting the review criteria were examined for the zebrafish strain, cancer cell line, cell labeling technique, injected cell number, time and site of injection, and maintenance temperature. Our review designated that AB wild-type zebrafish, Casper transparent mutants, transgenic Tg(fli1:EGFP), or crossbreeding of these predominate among the zebrafish strains. Orthotopic transplantation is more commonly employed. A number of 50-100 cells injected at 48 h post-fertilization in high density and low infusion volume is considered as an effective xenografting approach. U87 cells are used for GBM angiogenesis studies, U251 for GBM proliferation studies, and patient-derived xenograft (PDX) to achieve clinical relevance. Gradual acclimatization to 32-33 °C can partly address the temperature differential between the zebrafish and the GBM cells. Zebrafish xenograft models constitute valuable tools for preclinical studies with clinical relevance regarding PDX. The GBM xenografting research requires modification based on the objective of each research team. Automation and further optimization of the protocol parameters could scale up the anticancer drug trials.

Patient-Derived Xenograft Models in Cancer Research: Methodology, Applications, and Future Prospects

Patient-derived xenografts (PDXs) have emerged as a pivotal tool in translational cancer research, addressing limitations of traditional methods and facilitating improved therapeutic interventions. These models involve engrafting human primary malignant cells or tissues into immunodeficient mice, allowing for the investigation of cancer mechanobiology, validation of therapeutic targets, and preclinical assessment of treatment strategies. This chapter provides an overview of PDXs methodology and their applications in both basic cancer research and preclinical studies. Despite current limitations, ongoing advancements in humanized xenochimeric models and autologous immune cell engraftment hold promise for enhancing PDX model accuracy and relevance. As PDX models continue to refine and extend their applications, they are poised to play a pivotal role in shaping the future of translational cancer research.

Cancer organoid-based diagnosis reactivity prediction (CODRP) index-based anticancer drug sensitivity test in ALK-rearrangement positive non-small cell lung cancer (NSCLC)

BACKGROUND

Recently, cancer organoid-based drug sensitivity tests have been studied to predict patient responses to anticancer drugs. The area under curve (AUC) or IC50 value of the dose-response curve (DRC) is used to differentiate between sensitive and resistant patient's groups. This study proposes a multi-parameter analysis method (cancer organoid-based diagnosis reactivity prediction, CODRP) that considers the cancer stage and cancer cell growth rate, which represent the severity of cancer patients, in the sensitivity test.

METHODS

On the CODRP platform, patient-derived organoids (PDOs) that recapitulate patients with lung cancer were implemented by applying a mechanical dissociation method capable of high yields and proliferation rates. A disposable nozzle-type cell spotter with efficient high-throughput screening (HTS) has also been developed to dispense a very small number of cells due to limited patient cells. A drug sensitivity test was performed using PDO from the patient tissue and the primary cancer characteristics of PDOs were confirmed by pathological comparision with tissue slides.

RESULTS

The conventional index of drug sensitivity is the AUC of the DRC. In this study, the CODRP index for drug sensitivity test was proposed through multi-parameter analyses considering cancer cell proliferation rate, the cancer diagnosis stage, and AUC values. We tested PDOs from eight patients with lung cancer to verify the CODRP index. According to the anaplastic lymphoma kinase (ALK) rearrangement status, the conventional AUC index for the three ALK-targeted drugs (crizotinib, alectinib, and brigatinib) did not classify into sensitive and resistant groups. The proposed CODRP index-based drug sensitivity test classified ALK-targeted drug responses according to ALK rearrangement status and was verified to be consistent with the clinical drug treatment response.

CONCLUSIONS

Therefore, the PDO-based HTS and CODRP index drug sensitivity tests described in this paper may be useful for predicting and analyzing promising anticancer drug efficacy for patients with lung cancer and can be applied to a precision medicine platform.

Generation, evolution, interfering factors, applications, and challenges of patient-derived xenograft models in immunodeficient mice

Establishing appropriate preclinical models is essential for cancer research. Evidence suggests that cancer is a highly heterogeneous disease. This follows the growing use of cancer models in cancer research to avoid these differences between xenograft tumor models and patient tumors. In recent years, a patient-derived xenograft (PDX) tumor model has been actively generated and applied, which preserves both cell-cell interactions and the microenvironment of tumors by directly transplanting cancer tissue from tumors into immunodeficient mice. In addition to this, the advent of alternative hosts, such as zebrafish hosts, or in vitro models (organoids and microfluidics), has also facilitated the advancement of cancer research. However, they still have a long way to go before they become reliable models. The development of immunodeficient mice has enabled PDX to become more mature and radiate new vitality. As one of the most reliable and standard preclinical models, the PDX model in immunodeficient mice (PDX-IM) exerts important effects in drug screening, biomarker development, personalized medicine, co-clinical trials, and immunotherapy. Here, we focus on the development procedures and application of PDX-IM in detail, summarize the implications that the evolution of immunodeficient mice has brought to PDX-IM, and cover the key issues in developing PDX-IM in preclinical studies.

Refined high-content imaging-based phenotypic drug screening in zebrafish xenografts

Zebrafish xenotransplantation models are increasingly applied for phenotypic drug screening to identify small compounds for precision oncology. Larval zebrafish xenografts offer the opportunity to perform drug screens at high-throughput in a complex in vivo environment. However, the full potential of the larval zebrafish xenograft model has not yet been realized and several steps of the drug screening workflow still await automation to increase throughput. Here, we present a robust workflow for drug screening in zebrafish xenografts using high-content imaging. We established embedding methods for high-content imaging of xenografts in 96-well format over consecutive days. In addition, we provide strategies for automated imaging and analysis of zebrafish xenografts including automated tumor cell detection and tumor size analysis over time. We also compared commonly used injection sites and cell labeling dyes and show specific site requirements for tumor cells from different entities. We demonstrate that our setup allows us to investigate proliferation and response to small compounds in several zebrafish xenografts ranging from pediatric sarcomas and neuroblastoma to glioblastoma and leukemia. This fast and cost-efficient assay enables the quantification of anti-tumor efficacy of small compounds in large cohorts of a vertebrate model system in vivo. Our assay may aid in prioritizing compounds or compound combinations for further preclinical and clinical investigations.

Modeling Lung Carcinoids with Zebrafish Tumor Xenograft

Lung carcinoids are neuroendocrine tumors that comprise well-differentiated typical (TCs) and atypical carcinoids (ACs). Preclinical models are indispensable for cancer drug screening since current therapies for advanced carcinoids are not curative. We aimed to develop a novel in vivo model of lung carcinoids based on the xenograft of lung TC (NCI-H835, UMC-11, and NCI-H727) and AC (NCI-H720) cell lines and patient-derived cell cultures in Tg(fli1a:EGFP)y1 zebrafish embryos. We exploited this platform to test the anti-tumor activity of sulfatinib. The tumorigenic potential of TC and AC implanted cells was evaluated by the quantification of tumor-induced angiogenesis and tumor cell migration as early as 24 h post-injection (hpi). The characterization of tumor-induced angiogenesis was performed in vivo and in real time, coupling the tumor xenograft with selective plane illumination microscopy on implanted zebrafish embryos. TC-implanted cells displayed a higher pro-angiogenic potential compared to AC cells, which inversely showed a relevant migratory behavior within 48 hpi. Sulfatinib inhibited tumor-induced angiogenesis, without affecting tumor cell spread in both TC and AC implanted embryos. In conclusion, zebrafish embryos implanted with TC and AC cells faithfully recapitulate the tumor behavior of human lung carcinoids and appear to be a promising platform for drug screening.

Characterisation of 3D Bioprinted Human Breast Cancer Model for In Vitro Drug and Metabolic Targeting

Monolayer cultures, the less standard three-dimensional (3D) culturing systems, and xenografts are the main tools used in current basic and drug development studies of cancer research. The aim of biofabrication is to design and construct a more representative in vivo 3D environment, replacing two-dimensional (2D) cell cultures. Here, we aim to provide a complex comparative analysis of 2D and 3D spheroid culturing, and 3D bioprinted and xenografted breast cancer models. We established a protocol to produce alginate-based hydrogel bioink for 3D bioprinting and the long-term culturing of tumour cells in vitro. Cell proliferation and tumourigenicity were assessed with various tests. Additionally, the results of rapamycin, doxycycline and doxorubicin monotreatments and combinations were also compared. The sensitivity and protein expression profile of 3D bioprinted tissue-mimetic scaffolds showed the highest similarity to the less drug-sensitive xenograft models. Several metabolic protein expressions were examined, and the in situ tissue heterogeneity representing the characteristics of human breast cancers was also verified in 3D bioprinted and cultured tissue-mimetic structures. Our results provide additional steps in the direction of representing in vivo 3D situations in in vitro studies. Future use of these models could help to reduce the number of animal experiments and increase the success rate of clinical phase trials.

Identification of NVP-CLR457 as an Orally Bioavailable Non-CNS-Penetrant pan-Class IA Phosphoinositol-3-Kinase Inhibitor

Balanced pan-class I phosphoinositide 3-kinase inhibition as an approach to cancer treatment offers the prospect of treating a broad range of tumor types and/or a way to achieve greater efficacy with a single inhibitor. Taking buparlisib as the starting point, the balanced pan-class I PI3K inhibitor 40 (NVP-CLR457) was identified with what was considered to be a best-in-class profile. Key to the optimization to achieve this profile was eliminating a microtubule stabilizing off-target activity, balancing the pan-class I PI3K inhibition profile, minimizing CNS penetration, and developing an amorphous solid dispersion formulation. A rationale for the poor tolerability profile of 40 in a clinical study is discussed.

De novo individualized disease modules reveal the synthetic penetrance of genes and inform personalized treatment regimens

Current understandings of individual disease etiology and therapeutics are limited despite great need. To fill the gap, we propose a novel computational pipeline that collects potent disease gene cooperative pathways to envision individualized disease etiology and therapies. Our algorithm constructs individualized disease modules de novo, which enables us to elucidate the importance of mutated genes in specific patients and to understand the synthetic penetrance of these genes across patients. We reveal that importance of the notorious cancer drivers TP53 and PIK3CA fluctuate widely across breast cancers and peak in tumors with distinct numbers of mutations and that rarely mutated genes such as XPO1 and PLEKHA1 have high disease module importance in specific individuals. Furthermore, individualized module disruption enables us to devise customized singular and combinatorial target therapies that were highly varied across patients, showing the need for precision therapeutics pipelines. As the first analysis of de novo individualized disease modules, we illustrate the power of individualized disease modules for precision medicine by providing deep novel insights on the activity of diseased genes in individuals.

Preclinical Solid Tumor Models to Study Novel Therapeutics in Brain Metastases

Metastases are the most common malignancy of the adult central nervous system and are becoming an increasingly troubling problem in oncology largely due to the lack of successful therapeutic options. The limited selection of treatments is a result of the currently poor understanding of the biological mechanisms of metastatic development, which in turn is difficult to achieve because of limited preclinical models that can accurately represent the clinical progression of metastasis. Described in this article are in vitro and in vivo model systems that are used to enhance the understanding of metastasis and to identify new therapies for the treatment of brain metastasis. © 2021 Wiley Periodicals LLC.

Pre-clinical Models of Metastasis in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is a hostile solid malignancy coupled with an extremely high mortality rate. Metastatic disease is already found in most patients at the time of diagnosis, resulting in a 5-year survival rate below 5%. Improved comprehension of the mechanisms leading to metastasis is pivotal for the development of new targeted therapies. A key field to be improved are modeling strategies applied in assessing cancer progression, since traditional platforms fail in recapitulating the complexity of PDAC. Consequently, there is a compelling demand for new preclinical models that mirror tumor progression incorporating the pressure of the immune system, tumor microenvironment, as well as molecular aspects of PDAC. We suggest the incorporation of 3D organoids derived from genetically engineered mouse models or patients as promising new tools capable to transform PDAC pre-clinical modeling and access new frontiers in personalized medicine.

Establishment and characterization of an ovarian yolk sac tumor patient-derived xenograft model

OBJECTIVE

The lack of appropriate preclinical models of ovarian yolk sac tumor (OYST) is currently hindering the pursuit of new methods of treatment and investigation of the pathogenesis of the disease. We developed and characterized an OYST patient-derived xenograft (PDX) model in this study.

METHODS

Tumor fragments from a patient with an OYST were implanted subcutaneously into BALB/c Nude mice. Engrafted xenografts were compared with the original tumor according to histology, immunohistochemistry, humanized identified, and drug efficacy testing with in vivo treatment programs.

RESULTS

There was a high degree of histologic and immunohistochemical (IHC) resemblance between the established PDX model and its corresponding human tumors. Bleomycin, etoposide, and cisplatin (JEB) chemotherapy regimens were effective in clinical patients and were effective in the OYST PDX model; therefore, the effect of PDX intervention was consistent with clinical outcomes of OYSTs.

CONCLUSION

We have successfully established an OYST PDX model. This OYST model preserves the basic molecular features of the primary human tumor, thereby providing a valuable method to preclinically evaluate new treatments and explore disease pathogenesis.

Targeted Liposomal Chemotherapies to Treat Triple-Negative Breast Cancer

Simple Summary

Triple-negative breast cancers (TNBCs) are mainly treated with standard chemotherapies. Combined therapies have been demonstrated as a promising treatment strategy in clinics. The aim of this study was to develop a new formulation of combined chemotherapies facilitated with a targeted delivery vehicle. We found that the mertansine and gemcitabine with different anti-cancer mechanisms resulted in high cytotoxicity in TNBC cells. The in vivo evaluations using two TNBC xenograft models confirmed the anti-tumor efficacy, i.e., significantly reduced tumor growth rate. Furthermore, the antibody-tagged liposomes effectively delivered the therapeutic drugs to TNBC tumor, which could reduce the side effects. This study is highly translational and the targeted liposomal drug formulation can be further investigated in future clinical trials for TNBC treatment.

Abstract

Triple-negative breast cancers (TNBCs) are highly aggressive and recurrent. Standard cytotoxic chemotherapies are currently the main treatment options, but their clinical efficacies are limited and patients usually suffer from severe side effects. The goal of this study was to develop and evaluate targeted liposomes-delivered combined chemotherapies to treat TNBCs. Specifically, the IC₅₀ values of the microtubule polymerization inhibitor mertansine (DM1), mitotic spindle assembly defecting taxane (paclitaxel, PTX), DNA synthesis inhibitor gemcitabine (GC), and DNA damage inducer doxorubicin (AC) were tested in both TNBC MDA-MB-231 and MDA-MB-468 cells. Then we constructed the anti-epidermal growth factor receptor (EGFR) monoclonal antibody (mAb) tagged liposomes and confirmed its TNBC cell surface binding using flow cytometry, internalization with confocal laser scanning microscopy, and TNBC xenograft targeting in NSG female mice using In Vivo Imaging System. The safe dosage of anti-EGFR liposomal chemotherapies, i.e., <20% body weight change, was identified. Finally, the in vivo anti-tumor efficacy studies in TNBC cell line-derived xenograft and patient-derived xenograft models revealed that the targeted delivery of chemotherapies (mertansine and gemcitabine) can effectively inhibit tumor growth. This study demonstrated that the targeted liposomes enable the new formulations of combined therapies that improve anti-TNBC efficacy.

3D Tumor Models for Breast Cancer: Whither We Are and What We Need

Three-dimensional (3D) models have led to a paradigm shift in disease modeling in vitro, particularly for cancer. The past decade has seen a phenomenal increase in the development of 3D models for various types of cancers with a focus on studying stemness, invasive behavior, angiogenesis, and chemoresistance of cancer cells, as well as contributions of its stroma, which has expanded our understanding of these processes. Cancer biology is moving into exploring the emerging hallmarks of cancer, such as inflammation, immune evasion, and reprogramming of energy metabolism. Studies into these emerging concepts have provided novel targets and treatment options such as antitumor immunotherapy. However, 3D models that can investigate the emerging hallmarks are few and underexplored. As commonly used immunocompromised mice and syngenic mice cannot accurately mimic human immunology, stromal interactions, and metabolism and require the use of prohibitively expensive humanized mice, there is tremendous scope to develop authentic 3D tumor models in these areas. Taking the specific case of breast cancer, we discuss the currently available 3D models, their applications to mimic signaling in cancer, tumor-stroma interactions, drug responses, and assessment of drug delivery systems and therapies. We discuss the lacunae in the development of 3D tumor models for the emerging hallmarks of cancer, for lesser-explored forms of breast cancer, and provide insights to develop such models. We discuss how the next generation of 3D models can provide a better mimic of human cancer modeling compared to xenograft models and the scope toward preclinical models and precision medicine.

Diversity of Epithelial-Mesenchymal Phenotypes in Circulating Tumour Cells from Prostate Cancer Patient-Derived Xenograft Models

Simple Summary

Spread of prostate cancer to other parts of the body is responsible for the majority of deaths. Tumour cell epithelial mesenchymal plasticity (EMP) increases their metastatic potential and facilitates their survival in the blood as circulating tumour cells (CTCs). The aim of this study was to molecularly characterise CTCs in a panel of prostate cancer patient-derived xenografts using genes associated with epithelial and mesenchymal phenotypes, and to compare the EMP status of CTCs with their matched primary tumours. The study highlights high heterogeneity in CTC enumeration and EMP gene expression between tumour-bearing mice and within individual blood samples, and therefore caution should be taken when interpreting pooled CTC analyses. Critically, tumour cells were present in the epithelial-mesenchymal hybrid state in the circulation. The study also demonstrates that there is high variation in CTC size, which would introduce sample bias to size-based CTC isolation techniques.

Abstract

Metastasis is the leading cause of cancer-related deaths worldwide. The epithelial-mesenchymal plasticity (EMP) status of primary tumours has relevance to metastatic potential and therapy resistance. Circulating tumour cells (CTCs) provide a window into the metastatic process, and molecular characterisation of CTCs in comparison to their primary tumours could lead to a better understanding of the mechanisms involved in the metastatic cascade. In this study, paired blood and tumour samples were collected from four prostate cancer patient-derived xenograft (PDX) models (BM18, LuCaP70, LuCaP96, LuCaP105) and assessed using an EMP-focused, 42 gene human-specific, nested quantitative RT-PCR assay. CTC burden varied amongst the various xenograft models with LuCaP96 having the highest number of CTCs per mouse (mean: 704; median: 31) followed by BM18 (mean: 101; median: 21), LuCaP70 (mean: 73; median: 16) and LuCaP105 (mean: 57; median: 6). A significant relationship was observed between tumour size and CTC number (p = 0.0058). Decreased levels of kallikrein-related peptidase 3 (KLK3) mRNA (which encodes prostate-specific antigen; PSA) were observed in CTC samples from all four models compared to their primary tumours. Both epithelial- and mesenchymal-associated genes were commonly expressed at higher levels in CTCs compared to the bulk primary tumour, although some common EMT-associated genes (CDH1, VIM, EGFR, EPCAM) remained unchanged. Immunofluorescence co-staining for pan-cytokeratin (KRT) and vimentin (VIM) indicated variable proportions of CTCs across the full EMP axis, even in the same model. EMP hybrids predominated in the BM18 and LuCaP96 models, but were not detected in the LuCaP105 model, and variable numbers of KRT⁺ and human VIM⁺ cells were observed in each model. SERPINE1, which encodes plasminogen activator inhibitor-1 (PAI-1), was enriched at the RNA level in CTCs compared to primary tumours and was the most commonly expressed mesenchymal gene in the CTCs. Co-staining for SERPINE1 and KRT revealed SERPINE1⁺ cells in 7/11 samples, six of which had SERPINE⁺KRT⁺ CTCs. Cell size variation was observed in CTCs. The majority of samples (8/11) contained larger CTCs ranging from 15.3 to 37.8 µm, whilst smaller cells (10.7 ± 4.1 µm, similar in size to peripheral blood mononuclear cells (PBMCs)) were identified in 6 of 11 samples. CTC clusters were also identified in 9/11 samples, containing 2–100 CTCs per cluster. Where CTC heterogeneity was observed in the clusters, epithelial-like cells (KRT⁺VIM⁻) were located on the periphery of the cluster, forming a layer around hybrid (KRT⁺VIM⁺) or mesenchymal-like (KRT⁻VIM⁺) cells. The CTC heterogeneity observed in these models emphasises the complexity in CTC isolation and classification and supports the increasingly recognised importance of the epithelial-mesenchymal hybrid state in cancer progression and metastasis.

Does the Microenvironment Hold the Hidden Key for Functional Precision Medicine in Pancreatic Cancer?

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers and no significant improvement in patient survival has been seen in the past three decades. Treatment options are limited and selection of chemotherapy in the clinic is usually based on the performance status of a patient rather than the biology of their disease. In recent years, research has attempted to unlock a personalised treatment strategy by identifying actionable molecular targets in tumour cells or using preclinical models to predict the effectiveness of chemotherapy. However, these approaches rely on the biology of PDAC tumour cells only and ignore the importance of the microenvironment and fibrotic stroma. In this review, we highlight the importance of the microenvironment in driving the chemoresistant nature of PDAC and the need for preclinical models to mimic the complex multi-cellular microenvironment of PDAC in the precision medicine pipeline. We discuss the potential for ex vivo whole-tissue culture models to inform precision medicine and their role in developing novel therapeutic strategies that hit both tumour and stromal compartments in PDAC. Thus, we highlight the critical role of the tumour microenvironment that needs to be addressed before a precision medicine program for PDAC can be implemented.

Mouse Models of Peritoneal Carcinomatosis to Develop Clinical Applications

Simple Summary

Peritoneal carcinomatosis mouse models as a platform to test, improve and/or predict the appropriate therapeutic interventions in patients are crucial to providing medical advances. Here, we overview reported mouse models to explore peritoneal carcinomatosis in translational biomedical research.

Abstract

Peritoneal carcinomatosis of primary tumors originating in gastrointestinal (e.g., colorectal cancer, gastric cancer) or gynecologic (e.g., ovarian cancer) malignancies is a widespread type of tumor dissemination in the peritoneal cavity for which few therapeutic options are available. Therefore, reliable preclinical models are crucial for research and development of efficacious treatments for this condition. To date, a number of animal models have attempted to reproduce as accurately as possible the complexity of the tumor microenvironment of human peritoneal carcinomatosis. These include: Syngeneic tumor cell lines, human xenografts, patient-derived xenografts, genetically induced tumors, and 3D scaffold biomimetics. Each experimental model has its own strengths and limitations, all of which can influence the subsequent translational results concerning anticancer and immunomodulatory drugs under exploration. This review highlights the current status of peritoneal carcinomatosis mouse models for preclinical development of anticancer drugs or immunotherapeutic agents.

Ex vivo culture of intact human patient derived pancreatic tumour tissue

The poor prognosis of pancreatic ductal adenocarcinoma (PDAC) is attributed to the highly fibrotic stroma and complex multi-cellular microenvironment that is difficult to fully recapitulate in pre-clinical models. To fast-track translation of therapies and to inform personalised medicine, we aimed to develop a whole-tissue ex vivo explant model that maintains viability, 3D multicellular architecture, and microenvironmental cues of human pancreatic tumours. Patient-derived surgically-resected PDAC tissue was cut into 1-2 mm explants and cultured on gelatin sponges for 12 days. Immunohistochemistry revealed that human PDAC explants were viable for 12 days and maintained their original tumour, stromal and extracellular matrix architecture. As proof-of-principle, human PDAC explants were treated with Abraxane and we observed different levels of response between patients. PDAC explants were also transfected with polymeric nanoparticles + Cy5-siRNA and we observed abundant cytoplasmic distribution of Cy5-siRNA throughout the PDAC explants. Overall, our novel model retains the 3D architecture of human PDAC and has advantages over standard organoids: presence of functional multi-cellular stroma and fibrosis, and no tissue manipulation, digestion, or artificial propagation of organoids. This provides unprecedented opportunity to study PDAC biology including tumour-stromal interactions and rapidly assess therapeutic response to drive personalised treatment.

Co-Clinical Trials: An Innovative Drug Development Platform for Cholangiocarcinoma

Cholangiocarcinoma (CCA), a group of malignancies that originate from the biliary tract, is associated with a high mortality rate and a concerning increase in worldwide incidence. In Thailand, where the incidence of CCA is the highest, the socioeconomic burden is severe. Yet, treatment options are limited, with surgical resection being the only form of treatment with curative intent. The current standard-of-care remains adjuvant and palliative chemotherapy which is ineffective in most patients. The overall survival rate is dismal, even after surgical resection and the tumor heterogeneity further complicates treatment. Together, this makes CCA a significant burden in Southeast Asia. For effective management of CCA, treatment must be tailored to each patient, individually, for which an assortment of targeted therapies must be available. Despite the increasing numbers of clinical studies in CCA, targeted therapy drugs rarely get approved for clinical use. In this review, we discuss the shortcomings of the conventional clinical trial process and propose the implementation of a novel concept, co-clinical trials to expedite drug development for CCA patients. In co-clinical trials, the preclinical studies and clinical trials are conducted simultaneously, thus enabling real-time data integration to accurately stratify and customize treatment for patients, individually. Hence, co-clinical trials are expected to improve the outcomes of clinical trials and consequently, encourage the approval of targeted therapy drugs. The increased availability of targeted therapy drugs for treatment is expected to facilitate the application of precision medicine in CCA.

Microengineered 3D Tumor Models for Anti-Cancer Drug Discovery in Female-Related Cancers

The burden of cancer continues to increase in society and negatively impacts the lives of numerous patients. Due to the high cost of current treatment strategies, there is a crucial unmet need to develop inexpensive preclinical platforms to accelerate the process of anti-cancer drug discovery to improve outcomes in cancer patients, most especially in female patients. Many current methods employ expensive animal models which not only present ethical concerns but also do not often accurately predict human physiology and the outcomes of anti-cancer drug responsiveness. Conventional treatment approaches for cancer generally include systemic therapy after a surgical procedure. Although this treatment technique is effective, the outcome is not always positive due to various complex factors such as intratumor heterogeneity and confounding factors within the tumor microenvironment (TME). Patients who develop metastatic disease still have poor prognosis. To that end, recent efforts have attempted to use 3D microengineered platforms to enhance the predictive power and efficacy of anti-cancer drug screening, ultimately to develop personalized therapies. Fascinating features of microengineered assays, such as microfluidics, have led to the advancement in the development of the tumor-on-chip technology platforms, which have shown tremendous potential for meaningful and physiologically relevant anti-cancer drug discovery and screening. Three dimensional microscale models provide unprecedented ability to unveil the biological complexities of cancer and shed light into the mechanism of anti-cancer drug resistance in a timely and resource efficient manner. In this review, we discuss recent advances in the development of microengineered tumor models for anti-cancer drug discovery and screening in female-related cancers. We specifically focus on female-related cancers to draw attention to the various approaches being taken to improve the survival rate of women diagnosed with cancers caused by sex disparities. We also briefly discuss other cancer types like colon adenocarcinomas and glioblastoma due to their high rate of occurrence in females, as well as the high likelihood of sex-biased mutations which complicate current treatment strategies for women. We highlight recent advances in the development of 3D microscale platforms including 3D tumor spheroids, microfluidic platforms as well as bioprinted models, and discuss how they have been utilized to address major challenges in the process of drug discovery, such as chemoresistance, intratumor heterogeneity, drug toxicity, etc. We also present the potential of these platform technologies for use in high-throughput drug screening approaches as a replacements of conventional assays. Within each section, we will provide our perspectives on advantages of the discussed platform technologies.

Rodent Models to Analyze the Glioma Microenvironment

Animal models are still indispensable for understanding the basic principles of glioma development and invasion. Preclinical approaches aim to analyze the treatment efficacy of new drugs before translation into clinical trials is possible. Various animal disease models are available, but not every approach is useful for addressing specific questions. In recent years, it has become increasingly evident that the tumor microenvironment plays a key role in the nature of glioma. In addition to providing an overview, this review evaluates available rodent models in terms of usability for research on the glioma microenvironment.

Patient-Derived Tumor Xenograft Models: Toward the Establishment of Precision Cancer Medicine

Patient-derived xenografts (PDXs) describe models involving the implantation of patient-derived tumor tissue into immunodeficient mice. Compared with conventional preclinical models involving the implantation of cancer cell lines into mice, PDXs can be characterized by the preservation of tumor heterogeneity, and the tumor microenvironment (including stroma/vasculature) more closely resembles that in patients. Consequently, the use of PDX models has improved the predictability of clinical therapeutic responses to 80% or greater, compared with approximately 5% for existing models. In the future, molecular biological analyses, omics analyses, and other experiments will be conducted using recently prepared PDX models under the strong expectation that the analysis of cancer pathophysiology, stem cells, and novel treatment targets and biomarkers will be improved, thereby promoting drug development. This review outlines the methods for preparing PDX models, advances in cancer research using PDX mice, and perspectives for the establishment of precision cancer medicine within the framework of personalized cancer medicine.

Update on in-vivo preclinical research models in adrenocortical carcinoma

PURPOSE OF REVIEW

The aim of this review is to summarize recent advances on development of in vivo preclinical models of adrenocortical carcinoma (ACC).

RECENT FINDINGS

Significant progress has been achieved in the underlying molecular mechanisms of adrenocortical tumorigenesis over the last decade, and recent comprehensive profiling analysis of ACC tumors identified several genetic and molecular drivers of this disease. Therapeutic breakthroughs, however, have been limited because of the lack of preclinical models recapitulating the molecular features and heterogeneity of the tumors. Recent publications on genetically engineered mouse models and development of patient-derived ACC xenografts in both nude mice and humanized mice now provide researchers with novel tools to explore therapeutic targets in the context of heterogeneity and tumor microenvironment in human ACC.

SUMMARY

We review current in-vivo models of ACC and discuss potential therapeutic opportunities that have emerged from these studies.

Modeling the Tumor Microenvironment and Pathogenic Signaling in Bone Sarcoma

Investigations of cancer biology and screening of potential therapeutics for efficacy and safety begin in the preclinical laboratory setting. A staple of most basic research in cancer involves the use of tissue culture plates, on which immortalized cell lines are grown in monolayers. However, this practice has been in use for over six decades and does not account for vital elements of the tumor microenvironment that are thought to aid in initiation, propagation, and ultimately, metastasis of cancer. Furthermore, information gleaned from these techniques does not always translate to animal models or, more crucially, clinical trials in cancer patients. Osteosarcoma (OS) and Ewing sarcoma (ES) are the most common primary tumors of bone, but outcomes for patients with metastatic or recurrent disease have stagnated in recent decades. The unique elements of the bone tumor microenvironment have been shown to play critical roles in the pathogenesis of these tumors and thus should be incorporated in the preclinical models of these diseases. In recent years, the field of tissue engineering has leveraged techniques used in designing scaffolds for regenerative medicine to engineer preclinical tumor models that incorporate spatiotemporal control of physical and biological elements. We herein review the clinical aspects of OS and ES, critical elements present in the sarcoma microenvironment, and engineering approaches to model the bone tumor microenvironment. Impact statement The current paradigm of cancer biology investigation and therapeutic testing relies heavily on monolayer, monoculture methods developed over half a century ago. However, these methods often lack essential hallmarks of the cancer microenvironment that contribute to tumor pathogenesis. Tissue engineers incorporate scaffolds, mechanical forces, cells, and bioactive signals into biological environments to drive cell phenotype. Investigators of bone sarcomas, aggressive tumors that often rob patients of decades of life, have begun to use tissue engineering techniques to devise in vitro models for these diseases. Their efforts highlight how critical elements of the cancer microenvironment directly affect tumor signaling and pathogenesis.

Ruthenium(II) Complex Containing a Redox-Active Semiquinonate Ligand as a Potential Chemotherapeutic Agent: From Synthesis to In Vivo Studies

Chemotherapy remains one of the dominant treatments to cure cancer. However, due to the many inherent drawbacks, there is a search for new chemotherapeutic drugs. Many classes of compounds have been investigated over the years to discover new targets and synergistic mechanisms of action including multicellular targets. In this work, we designed a new chemotherapeutic drug candidate against cancer, namely, [Ru(DIP)₂(sq)](PF₆) (Ru-sq) (DIP = 4,7-diphenyl-1,10-phenanthroline; sq = semiquinonate ligand). The aim was to combine the great potential expressed by Ru(II) polypyridyl complexes and the singular redox and biological properties associated with the catecholate moiety. Experimental evidence (e.g., X-ray crystallography, electron paramagnetic resonance, electrochemistry) demonstrates that the semiquinonate is the preferred oxidation state of the dioxo ligand in this complex. The biological activity of Ru-sq was then scrutinized in vitro and in vivo, and the results highlight the promising potential of this complex as a chemotherapeutic agent against cancer.

Breast cancer organoids from a patient with giant papillary carcinoma as a high-fidelity model

BACKGROUND

Papillary carcinoma is an uncommon type of breast cancer. Additionally, patients with huge breast papillary carcinoma are extremely rare in clinical practice. To improve therapeutic effect on such patients, it is urgent to explore biologically and clinically relevant models of the disease to discover effective drugs.

METHODS

We collected surgical tumor specimens from a 63-year-old Chinese woman who has been diagnosed breast papillary carcinoma. The tumor was more than 15 cm in diameter, and applied to establish patient-derived papillary carcinoma organoids that could continuously propagate for more than 6 months.

RESULTS

The papillary carcinoma organoids matched the histological characteristics of orginal tumor by H&E staining identification, and maintained the expression of the breast cancer biomarkers by IHC, including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor (HER2) and antigen Ki-67 (Ki67). In addition, we performed a 3-D drug screening to examine the effects of endocrine drugs (Fulvestrant, Tamoxifen) and targeted therapy drugs (Palbociclib, Everolimus, BKM120) on breast papillary carcinoma in the mimic in vivo environment. The drug sensitivities of our breast papillary carcinoma organoids were investigated as follows, Fulvestrant (IC50 0.275 μmol), Palbociclib (IC50 2.21 μmol), BKM120 (IC50 3.81 μmol), Everolimus (IC50 4.45 μmol), Tamoxifen (IC50 19.13 μmol).

CONCLUSIONS

These results showed that an effective organoid platform for 3-D in vitro culture of breast cancer organoids from patients with breast papillary carcinoma could be used to identify possible treatments, and might be commonly applied to explore clinicopathological characteristics of breast papillary carcinoma.

Genetically Engineered Pigs to Study Cancer

Recent decades have seen groundbreaking advances in cancer research. Genetically engineered animal models, mainly in mice, have contributed to a better understanding of the underlying mechanisms involved in cancer. However, mice are not ideal for translating basic research into studies closer to the clinic. There is a need for complementary information provided by non-rodent species. Pigs are well suited for translational biomedical research as they share many similarities with humans such as body and organ size, aspects of anatomy, physiology and pathophysiology and can provide valuable means of developing and testing novel diagnostic and therapeutic procedures. Porcine oncology is a new field, but it is clear that replication of key oncogenic mutation in pigs can usefully mimic several human cancers. This review briefly outlines the technology used to generate genetically modified pigs, provides an overview of existing cancer models, their applications and how the field may develop in the near future.

NSG mice as hosts for oncological precision medicine

Patient-derived xenograft (PDX) models have been rediscovered as meaningful research tool. By using severely immunodeficient mice, high-engraftment rates can be theoretically achieved, permitting clinical stratification strategies. Apart from engraftment efficacy, tolerability towards certain cytostatic drugs varies among individual mouse strains thus impeding large-scale screenings. Here, we aimed at optimizing an in vivo treatment schedule using the widely applied cytostatic drug 5-fluoruracil (5-FU) for exemplary response prediction in colorectal cancer (CRC) PDX models. Four different individual CRC PDX models were engrafted into NOD.Cg-PrkdcscidIl2rgtm1Wjl (NSG) mice. Mice with established PDX were allocated to different treatment groups, receiving 5-FU, the oral prodrug Capecitabine, or 5-FU/leucovorin (LV) at different doses. Body weight, tumor size, and general behavior were assessed during therapy. Ex vivo analyses were done from blood samples, liver, as well as tumor resection specimen. Engraftment efficacy was high as expected in NSG mice, yielding stable PDX growth for therapy stratification. However, overall tolerability towards 5-FU was unexpectedly low, whereas the prodrug Capecitabine as well as the combination of 5-FU/LV at low doses were well tolerated. Accompanying plasma level determination of DYPD, the rate-limiting enzyme for 5-FU-mediated toxicity, revealed reduced activity in NSG mice compared with other common laboratory mouse strains, offering a likely explanation for the drug incompatibility. Also, the De Ritis quotient was highly elevated in treated mice, reflecting overall organ injury even at low doses. Summarizing these findings, NSG mice are ideal hosts for in vivo engraftment studies. However, the complex immunodeficiency reduces tolerance to certain drugs, thus making those mice especially sensitive. Consequently, such dose finding and tolerance tests constitute a necessity for similar cancer precision medicine approaches.

Application of Highly Immunocompromised Mice for the Establishment of Patient-Derived Xenograft (PDX) Models

Patient-derived xenograft (PDX) models are created by engraftment of patient tumor tissues into immunocompetent mice. Since a PDX model retains the characteristics of the primary patient tumor including gene expression profiles and drug responses, it has become the most reliable in vivo human cancer model. The engraftment rate increases with the introduction of Non-obese diabetic Severe combined immunodeficiency (NOD/SCID)-based immunocompromised mice, especially the NK-deficient NOD strains NOD/SCID/interleukin-2 receptor gamma chain(IL2Rγ)null (NOG/NSG) and NOD/SCID/Jak3(Janus kinase 3)null (NOJ). Success rates differ with tumor origin: gastrointestinal tumors acquire a higher engraftment rate, while the rate is lower for breast cancers. Subcutaneous transplantation is the most popular method to establish PDX, but some tumors require specific environments, e.g., orthotropic or renal capsule transplantation. Human hormone treatment is necessary to establish hormone-dependent cancers such as prostate and breast cancers. PDX mice with human hematopoietic and immune systems (humanized PDX) are powerful tools for the analysis of tumor-immune system interaction and evaluation of immunotherapy response. A PDX biobank equipped with patients' clinical data, gene-expression patterns, mutational statuses, tumor tissue architects, and drug responsiveness will be an authoritative resource for developing specific tumor biomarkers for chemotherapeutic predictions, creating individualized therapy, and establishing precise cancer medicine.

Development of Personalized Therapeutic Strategies by Targeting Actionable Vulnerabilities in Metastatic and Chemotherapy-Resistant Breast Cancer PDXs

Human breast cancer is characterized by a high degree of inter-patients heterogeneity in terms of histology, genomic alterations, gene expression patterns, and metastatic behavior, which deeply influences individual prognosis and treatment response. The main cause of mortality in breast cancer is the therapy-resistant metastatic disease, which sets the priority for novel treatment strategies for these patients. In the present study, we demonstrate that Patient Derived Xenografts (PDXs) that were obtained from metastatic and therapy-resistant breast cancer samples recapitulate the wide spectrum of the disease in terms of histologic subtypes and mutational profiles, as evaluated by whole exome sequencing. We have integrated genomic and transcriptomic data to identify oncogenic and actionable pathways in each PDX. By taking advantage of primary short-term in vitro cultures from PDX tumors, we showed their resistance to standard chemotherapy (Paclitaxel), as seen in the patients. Moreover, we selected targeting drugs and analyzed PDX sensitivity to single agents or to combination of targeted and standard therapy on the basis of PDX-specific genomic or transcriptomic alterations. Our data demonstrate that PDXs represent a suitable model to test new targeting drugs or drug combinations and to prioritize personalized therapeutic regimens for pre-clinal and clinical tests.

Establishment of Novel Gastric Cancer Patient-Derived Xenografts and Cell Lines: Pathological Comparison between Primary Tumor, Patient-Derived, and Cell-Line Derived Xenografts

Patient-derived xenograft (PDX) models have been recognized as being more suitable for predicting therapeutic efficacy than cell-culture models. However, there are several limitations in applying PDX models in preclinical studies, including their availability—especially for cancers such as gastric cancer—that are not frequently encountered in Western countries. In addition, the differences in morphology between primary, PDX, and tumor cell line-derived xenograft (CDX) models have not been well established. In this study, we aimed to establish a series of gastric cancer PDXs and cell-lines from a relatively large number of gastric cancer patients. We also investigated the clinicopathological factors associated with the establishment of PDX and CDX models, and compared the histology between the primary tumor, PDX, and CDX that originated from the same patient. We engrafted 232 gastric cancer tissues into immune-deficient mice subcutaneously and successfully established 35 gastric cancer PDX models (15.1% success rate). Differentiated type adenocarcinomas (DAs, 19.4%) were more effectively established than poorly differentiated type adenocarcinomas (PDAs, 10.8%). For establishing CDXs, the success rate was less influenced by histological differentiation grade (DA vs. PDA, 12.1% vs. 9.8%). In addition, concordance of histological differentiation grade between primary tumors and PDXs was significant (p < 0.01), while concordance between primary tumors and CDXs was not. Among clinicopathological factors investigated, pathological nodal metastasis status (pN) was significantly associated with the success rate of PDX establishment. Although establishing cell lines from ascites fluid was more efficient (41.2%, 7/17) than resected tissues, it should be noted that all CDXs from ascites fluid had the PDA phenotype. In conclusion, we established 35 PDX and 32 CDX models from 249 gastric cancer patients; among them, 21 PDX/CDX models were established from the same patients. Our findings may provide helpful insights for establishing PDX and CDX models not only from gastric but from other cancer types, as well as select preclinical models for developing new therapeutics.

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.