One mouse, one patient paradigm: New avatars of personalized cancer therapy

Quantitation of Murine Stroma and Selective Purification of the Human Tumor Component of Patient-Derived Xenografts for Genomic Analysis

Patient-derived xenograft (PDX) mouse models are increasingly used for preclinical therapeutic testing of human cancer. A limitation in molecular and genetic characterization of PDX tumors is the presence of integral murine stroma. This is particularly problematic for genomic sequencing of PDX models. Rapid and dependable approaches for quantitating stromal content and purifying the malignant human component of these tumors are needed. We used a recently developed technique exploiting species-specific polymerase chain reaction (PCR) amplicon length (ssPAL) differences to define the fractional composition of murine and human DNA, which was proportional to the fractional composition of cells in a series of lung cancer PDX lines. We compared four methods of human cancer cell isolation: fluorescence-activated cell sorting (FACS), an immunomagnetic mouse cell depletion (MCD) approach, and two distinct EpCAM-based immunomagnetic positive selection methods. We further analyzed DNA extracted from the resulting enriched human cancer cells by targeted sequencing using a clinically validated multi-gene panel. Stromal content varied widely among tumors of similar histology, but appeared stable over multiple serial tumor passages of an individual model. FACS and MCD were superior to either positive selection approach, especially in cases of high stromal content, and consistently allowed high quality human-specific genomic profiling. ssPAL is a dependable approach to quantitation of murine stromal content, and MCD is a simple, efficient, and high yield approach to human cancer cell isolation for genomic analysis of PDX tumors.

Designing a broad-spectrum integrative approach for cancer prevention and treatment

Targeted therapies and the consequent adoption of "personalized" oncology have achieved notable successes in some cancers; however, significant problems remain with this approach. Many targeted therapies are highly toxic, costs are extremely high, and most patients experience relapse after a few disease-free months. Relapses arise from genetic heterogeneity in tumors, which harbor therapy-resistant immortalized cells that have adopted alternate and compensatory pathways (i.e., pathways that are not reliant upon the same mechanisms as those which have been targeted). To address these limitations, an international task force of 180 scientists was assembled to explore the concept of a low-toxicity "broad-spectrum" therapeutic approach that could simultaneously target many key pathways and mechanisms. Using cancer hallmark phenotypes and the tumor microenvironment to account for the various aspects of relevant cancer biology, interdisciplinary teams reviewed each hallmark area and nominated a wide range of high-priority targets (74 in total) that could be modified to improve patient outcomes. For these targets, corresponding low-toxicity therapeutic approaches were then suggested, many of which were phytochemicals. Proposed actions on each target and all of the approaches were further reviewed for known effects on other hallmark areas and the tumor microenvironment. Potential contrary or procarcinogenic effects were found for 3.9% of the relationships between targets and hallmarks, and mixed evidence of complementary and contrary relationships was found for 7.1%. Approximately 67% of the relationships revealed potentially complementary effects, and the remainder had no known relationship. Among the approaches, 1.1% had contrary, 2.8% had mixed and 62.1% had complementary relationships. These results suggest that a broad-spectrum approach should be feasible from a safety standpoint. This novel approach has potential to be relatively inexpensive, it should help us address stages and types of cancer that lack conventional treatment, and it may reduce relapse risks. A proposed agenda for future research is offered.

Heralding a new paradigm in 3D tumor modeling

Numerous studies to date have contributed to a paradigm shift in modeling cancer, moving from the traditional two-dimensional culture system to three-dimensional (3D) culture systems for cancer cell culture. This led to the inception of tumor engineering, which has undergone rapid advances over the years. In line with the recognition that tumors are not merely masses of proliferating cancer cells but rather, highly complex tissues consisting of a dynamic extracellular matrix together with stromal, immune and endothelial cells, significant efforts have been made to better recapitulate the tumor microenvironment in 3D. These approaches include the development of engineered matrices and co-cultures to replicate the complexity of tumor-stroma interactions in vitro. However, the tumor engineering and cancer biology fields have traditionally relied heavily on the use of cancer cell lines as a cell source in tumor modeling. While cancer cell lines have contributed to a wealth of knowledge in cancer biology, the use of this cell source is increasingly perceived as a major contributing factor to the dismal failure rate of oncology drugs in drug development. Backing this notion is the increasing evidence that tumors possess intrinsic heterogeneity, which predominantly homogeneous cancer cell lines poorly reflect. Tumor heterogeneity contributes to therapeutic resistance in patients. To overcome this limitation, cancer cell lines are beginning to be replaced by primary tumor cell sources, in the form of patient-derived xenografts and organoids cultures. Moving forward, we propose that further advances in tumor engineering would require that tumor heterogeneity (tumor variants) be taken into consideration together with tumor complexity (tumor-stroma interactions). In this review, we provide a comprehensive overview of what has been achieved in recapitulating tumor complexity, and discuss the importance of incorporating tumor heterogeneity into 3D in vitro tumor models. This work carves out the roadmap for 3D tumor engineering and highlights some of the challenges that need to be addressed as we move forward into the next chapter.

Differentiation of tumor vasculature heterogeneity levels in small animals based on total hemoglobin concentration using magnetic resonance-guided diffuse optical tomography in vivo

Insight into the vasculature of the tumor in small animals has the potential to impact many areas of cancer research. The heterogeneity of the vasculature of a tumor is directly related to tumor stage and disease progression. In this small scale animal study, we investigated the feasibility of differentiating tumors with different levels of vasculature heterogeneity in vivo using a previously developed hybrid magnetic resonance imaging (MRI) and diffuse optical tomography (DOT) system for small animal imaging. Cross-sectional total hemoglobin concentration maps of 10 Fisher rats bearing R3230 breast tumors are reconstructed using multi-wavelength DOT measurements both with and without magnetic resonance (MR) structural a priori information. Simultaneously acquired MR structural images are used to guide and constrain the DOT reconstruction, while dynamic contrast-enhanced MR functional images are used as the gold standard to classify the vasculature of the tumor into two types: high versus low heterogeneity. These preliminary results show that the stand-alone DOT is unable to differentiate tumors with low and high vascular heterogeneity without structural a priori information provided by a high resolution imaging modality. The mean total hemoglobin concentrations comparing the vasculature of the tumors with low and high heterogeneity are significant (p-value 0.02) only when MR structural a priori information is utilized.

Uncovering the liver's role in immunity through RNA co-expression networks

Gene co-expression analysis has proven to be a powerful tool for ascertaining the organization of gene products into networks that are important for organ function. An organ, such as the liver, engages in a multitude of functions important for the survival of humans, rats, and other animals; these liver functions include energy metabolism, metabolism of xenobiotics, immune system function, and hormonal homeostasis. With the availability of organ-specific transcriptomes, we can now examine the role of RNA transcripts (both protein-coding and non-coding) in these functions. A systems genetic approach for identifying and characterizing liver gene networks within a recombinant inbred panel of rats was used to identify genetically regulated transcriptional networks (modules). For these modules, biological consensus was found between functional enrichment analysis and publicly available phenotypic quantitative trait loci (QTL). In particular, the biological function of two liver modules could be linked to immune response. The eigengene QTLs for these co-expression modules were located at genomic regions coincident with highly significant phenotypic QTLs; these phenotypes were related to rheumatoid arthritis, food preference, and basal corticosterone levels in rats. Our analysis illustrates that genetically and biologically driven RNA-based networks, such as the ones identified as part of this research, provide insight into the genetic influences on organ functions. These networks can pinpoint phenotypes that manifest through the interaction of many organs/tissues and can identify unannotated or under-annotated RNA transcripts that play a role in these phenotypes.

Failure of a patient-derived xenograft for brain tumor model prepared by implantation of tissue fragments

Background

With the continuing development of new anti-cancer drugs comes a need for preclinical experimental models capable of predicting the clinical activity of these novel agents in cancer patients. However existing models have a limited ability to recapitulate the clinical characteristics and associated drug sensitivity of tumors. Among the more promising approaches for improving preclinical models is direct implantation of patient-derived tumor tissue into immunocompromised mice, such as athymic nude or non-obese diabetic/severe combined immunodeficient (NOD/SCID) mice. In the current study, we attempted to develop patient-derived xenograft (PDX) models using tissue fragments from surgical samples of brain tumors.

Methods

In this approach, tiny tissue fragments of tumors were biopsied from eight brain tumor patients—seven glioblastoma patients and one primitive neuroectodermal tumor patient. Two administration methods—a cut-down syringe and a pipette—were used to implant tissue fragments from each patient into the brains of athymic nude mice.

Results

In contrast to previous reports, and contrary to our expectations, we found that none of these fragments from brain tumor biopsies resulted in the successful establishment of xenograft tumors.

Conclusions

These results suggest that fragments of surgical specimens from brain tumor patients are unsuitable for implementation of brain tumor PDX models, and instead recommend other in vivo testing platforms for brain tumors, such as cell-based brain tumor models.

Electronic supplementary material

The online version of this article (doi:10.1186/s12935-016-0319-0) contains supplementary material, which is available to authorized users.

Predictive In Vivo Models for Oncology

Experimental oncology research and preclinical drug development both substantially require specific, clinically relevant in vitro and in vivo tumor models. The increasing knowledge about the heterogeneity of cancer requested a substantial restructuring of the test systems for the different stages of development. To be able to cope with the complexity of the disease, larger panels of patient-derived tumor models have to be implemented and extensively characterized. Together with individual genetically engineered tumor models and supported by core functions for expression profiling and data analysis, an integrated discovery process has been generated for predictive and personalized drug development.Improved “humanized” mouse models should help to overcome current limitations given by xenogeneic barrier between humans and mice. Establishment of a functional human immune system and a corresponding human microenvironment in laboratory animals will strongly support further research.Drug discovery, systems biology, and translational research are moving closer together to address all the new hallmarks of cancer, increase the success rate of drug development, and increase the predictive value of preclinical models.

Drafting biological material transfer agreement: a ready-to-sign model for biobanks and biorepositories

PURPOSE

Due to the scarcity of publications, guidelines, and harmonization among national regulations, biobanks and institutions face practical and theoretical issues when drafting a material transfer agreement (MTA), the fundamental tool to regulate the successful exchange of biosamples and information. Frequently researchers do not execute MTAs because of a general lack of knowledge about this topic. It is thus critical to develop new models to prevent loss of traceability and opportunities both for researchers and biobanks, their exposure to various risks, and delays in transferring biomaterials.

METHODS

Through the involvement of institutional groups and professionals with multidisciplinary expertise, we have drawn up a ready-to-sign MTA for the CRO-Biobank (the biobank of the National Cancer Institute, CRO, Aviano), a standardized template that can be employed as a ready-to-use model agreement.

RESULTS

The team identified the essential components to be included in the MTA, which comprise i) permissions, liability and representations; ii) custodianship and distribution limitations; iii) appropriate use of materials, including biosafety concerns; iv) confidentiality, non-disclosure, and publications; v) intellectual property protection for both the provider and recipient.

CONCLUSIONS

This paper aims to be an unabridged report (among the few works in the existing literature) providing a description of the whole process related to the formation of an MTA. Biobanks and institutions may consider adopting our ready-to-sign form as a standard model. The article discusses the most important issues tackled during the drafting of the document, thus proposing an operative approach for other institutions that face the same problems.

Testing chemotherapy efficacy in HER2 negative breast cancer using patient-derived spheroids

BACKGROUND

Targeted anti-HER2 therapy has greatly improved the prognosis for many breast cancer patients. However, treatment for HER2 negative disease is currently still selected from a multitude of untargeted chemotherapeutic treatment options. A predictive test was developed using patient-derived spheroids to identify the most effective therapy for patients with HER2 negative breast cancer of all stages, for clinically relevant subgroups, as well as individual patients.

METHODS

Tumor samples from 120 HER2 negative patients obtained through biopsy or surgical excision were tested in the breast cancer spheroid model using scaffold-free cell culture. Similarly, spheroids were also generated from established HER2 negative breast cancer cell lines T-47D, MCF7, HCC1143, and HCC1937 to compare treatment efficacy of heterogeneous cell populations from patient tumor tissue with homogeneous cell lines. Spheroids were treated in vitro with guideline-recommended compounds. Treatment mediated impact on cell survival was subsequently quantified using an ATP assay.

RESULTS

Differences were observed in the metabolic activity of the untreated spheroids, whereby cell lines consistently achieved higher values compared to tissue spheroids (p < 0.001). A higher number of cells per spheroid correlated with a higher basal metabolic activity in tissue-derived spheroids (p < 0.01), while the opposite was observed for cell line spheroids (p < 0.01). Recurrent tumors showed a higher mean vitality (p < 0.01) compared to primary tumors. Except for taxanes, treatment efficacy for most tested compounds differed significantly between breast cancer tissue spheroids and breast cancer cell lines. Overall a high variability in treatment response in vitro was seen in the tissue spheroids regardless of the tested substances. A greater response to anthracycline/docetaxel was observed for hormone receptor negative samples (p < 0.01). A higher response to 5-FU (p < 0.01) and anthracycline (p < 0.05) was seen in high grade tumors. Smaller tumor size and negative lymph node status were both associated with a higher treatment efficacy to anthracycline treatment combined with 5-FU (cT1/2 vs cT3/4, p = 0.035, cN+ vs cN-, p < 0.05).

CONCLUSIONS

The tissue spheroid model reflects current guideline treatment recommendations for HER2 negative breast cancer, whereas tested cell lines did not. This model represents a unique diagnostic method to select the most effective therapy out of several equivalent treatment options.

Establishment and characterization of a canine soft tissue sarcoma patient-derived xenograft model

Spontaneously occurring soft tissue sarcoma (STS) is relatively common in canine cancer patients. Because of the similarities to human disease, canine STSs are a valuable and readily available resource for the study of new therapeutics. In this study, a canine patient-derived xenograft (PDX) model, CDX-STS2, was established. The CDX-STS2 model was engrafted and expanded for systemic administration studies with chemotherapeutic agents commonly used to treat STS, including doxorubicin, docetaxel and gemcitabine. Immunohistochemistry for drug-specific biomarkers and tumour growth measurement revealed tumour sensitivity to doxorubicin and docetaxel, whereas gemcitabine had no effect on tumour growth. Although many human PDX tumour models have been established, relatively few canine PDX models have been reported to date. CDX-STS2 represents a new STS PDX research model of canine origin that will be useful in bridging preclinical research with clinical studies of STS in pet dogs.

Patient-derived xenograft platform of OSCC: a renewable human bio-bank for preclinical cancer research and a new co-clinical model for treatment optimization

Advances in next-generation sequencing and bioinformatics have begun to reveal the complex genetic landscape in human cancer genomes, including oral squamous cell carcinoma (OSCC). Sophisticated preclinical models that fully represent intra- and inter-tumoral heterogeneity are required to understand the molecular diversity of cancer and achieve the goal of personalized therapies. Over the last decade, patient-derived xenograft (PDX) models generated from human tumor samples that can retain the histological and genetic features of their donor tumors have been shown to be the preferred preclinical tool in translational cancer research compared with other conventional preclinical models. Specifically, genetically well-defined PDX models can be applied to accelerate targeted antitumor drug development and biomarker discovery. Recently, we have successfully established and characterized an OSCC PDX panel as part of our tumor bio-bank for translational cancer research. In this paper, we discuss the establishment, characterization, and preclinical applications of the PDX models. In particular, we focus on the classification and applications of the PDX models based on validated annotations, including clinicopathological features, genomic profiles, and pharmacological testing information. We also explore the translational value of this well-annotated PDX panel in the development of co-clinical trials for patient stratification and treatment optimization in the near future. Although various limitations still exist, this preclinical approach should be further tested and improved.

The Development of a Recombinant scFv Monoclonal Antibody Targeting Canine CD20 for Use in Comparative Medicine

Monoclonal antibodies are leading agents for therapeutic treatment of human diseases, but are limited in use by the paucity of clinically relevant models for validation. Sporadic canine tumours mimic the features of some human equivalents. Developing canine immunotherapeutics can be an approach for modeling human disease responses. Rituximab is a pioneering agent used to treat human hematological malignancies. Biologic mimics that target canine CD20 are just being developed by the biotechnology industry. Towards a comparative canine-human model system, we have developed a novel anti-CD20 monoclonal antibody (NCD1.2) that binds both human and canine CD20. NCD1.2 has a sub-nanomolar K_d as defined by an octet red binding assay. Using FACS, NCD1.2 binds to clinically derived canine cells including B-cells in peripheral blood and in different histotypes of B-cell lymphoma. Immunohistochemical staining of canine tissues indicates that the NCD1.2 binds to membrane localized cells in Diffuse Large B-cell lymphoma, Marginal Zone Lymphoma, and other canine B-cell lymphomas. We cloned the heavy and light chains of NCD1.2 from hybridomas to determine whether active scaffolds can be acquired as future biologics tools. The V_H and V_L genes from the hybridomas were cloned using degenerate primers and packaged as single chains (scFv) into a phage-display library. Surprisingly, we identified two scFv (scFv-3 and scFv-7) isolated from the hybridoma with bioactivity towards CD20. The two scFv had identical V_H genes but different V_L genes and identical CDR3s, indicating that at least two light chain mRNAs are encoded by NCD1.2 hybridoma cells. Both scFv-3 and scFv-7 were cloned into mammalian vectors for secretion in CHO cells and the antibodies were bioactive towards recombinant CD20 protein or peptide. The scFv-3 and scFv-7 were cloned into an ADEPT-CPG2 bioconjugate vector where bioactivity was retained when expressed in bacterial systems. These data identify a recombinant anti-CD20 scFv that might form a useful tool for evaluation in bioconjugate-directed anti-CD20 immunotherapies in comparative medicine.

Xenograft models for adrenocortical carcinoma

Adrenocortical carcinomas (ACCs) are rare, heterogeneous and very malignant endocrine tumors with a poor prognosis. An important prerequisite to optimize existing therapeutic regimens and to develop novel therapeutic strategies are preclinical disease models. In recent years molecular and genetic profiling of surgical tumor specimen led to the identification of novel interesting markers. However, precise involvement of these markers in tumorigenesis and their functional relevance in therapeutic outcome is still under investigation. Xenograft models are important tools for such functional studies as they bear the potential to mimic the complexity of solid tumors including tumor cells, stroma and blood vessels. Thus, for the successful and safe development of novel therapeutic strategies xenograft models remain to be indispensable experimental tools. Here we provide an overview on currently existing xenograft models for ACC, their tissue origins, establishment, implications as well as limitations.

An Integrated Analysis of Heterogeneous Drug Responses in Acute Myeloid Leukemia That Enables the Discovery of Predictive Biomarkers

Many promising new cancer drugs proceed through preclinical testing and early-phase trials only to fail in late-stage clinical testing. Thus, improved models that better predict survival outcomes and enable the development of biomarkers are needed to identify patients most likely to respond to and benefit from therapy. Here, we describe a comprehensive approach in which we incorporated biobanking, xenografting, and multiplexed phospho-flow (PF) cytometric profiling to study drug response and identify predictive biomarkers in acute myeloid leukemia (AML) patients. To test the efficacy of our approach, we evaluated the investigational JAK2 inhibitor fedratinib (FED) in 64 patient samples. FED robustly reduced leukemia in mouse xenograft models in 59% of cases and was also effective in limiting the protumorigenic activity of leukemia stem cells as shown by serial transplantation assays. In parallel, PF profiling identified FED-mediated reduction in phospho-STAT5 (pSTAT5) levels as a predictive biomarker of in vivo drug response with high specificity (92%) and strong positive predictive value (93%). Unexpectedly, another JAK inhibitor, ruxolitinib (RUX), was ineffective in 8 of 10 FED-responsive samples. Notably, this outcome could be predicted by the status of pSTAT5 signaling, which was unaffected by RUX treatment. Consistent with this observed discrepancy, PF analysis revealed that FED exerted its effects through multiple JAK2-independent mechanisms. Collectively, this work establishes an integrated approach for testing novel anticancer agents that captures the inherent variability of response caused by disease heterogeneity and in parallel, facilitates the identification of predictive biomarkers that can help stratify patients into appropriate clinical trials.

From Mice to Men and Back: An Assessment of Preclinical Model Systems for the Study of Lung Cancers

INTRODUCTION

Studies of preclinical models are essential for determining the biology of lung cancers and testing new and novel therapeutic approaches. We review the commonly used preclinical models for lung cancers and evaluate their strengths and weaknesses.

METHODS

We searched the MEDLINE database via PubMed using combinations of the following medical subject headings: lung cancer; animal models, mice; cell line, tumor; cell culture, mice; transgenic, mice; SCID, transplantation; heterologous; and genetic engineering. We reviewed the relevant published articles.

RESULTS

Multiple examples of the three major preclinical models-tumor cell lines, patient-derived xenografts, and genetically engineered mouse models-exist and have been used by investigators worldwide, with more than 15,000 relevant publications. Each model has its strengths and actual or potential weaknesses. In addition, newer forms of these models have been proposed or are in use as potential improvements over the conventional models.

CONCLUSIONS

A large number and variety of models have been developed and extensively used for the study of all major types of lung cancer. While they remain the cornerstone of preclinical studies, each model has its individual strengths and weaknesses. These must be carefully evaluated and applied to the proposed studies to obtain the maximum usefulness from the models.

Preclinical mouse cancer models: a maze of opportunities and challenges

Significant advances have been made in developing novel therapeutics for cancer treatment, and targeted therapies have revolutionized the treatment of some cancers. Despite the promise, only about five percent of new cancer drugs are approved, and most fail due to lack of efficacy. The indication is that current preclinical methods are limited in predicting successful outcomes. Such failure exacts enormous cost, both financial and in the quality of human life. This Primer explores the current status, promise, and challenges of preclinical evaluation in advanced mouse cancer models and briefly addresses emerging models for early-stage preclinical development.

Proteomic Characterization of Head and Neck Cancer Patient-Derived Xenografts

Despite advances in treatment approaches for head and neck squamous cell carcinoma (HNSCC), survival rates have remained stagnant due to the paucity of preclinical models that accurately reflect the human tumor. Patient-derived xenografts (PDX) are an emerging model system where patient tumors are implanted directly into mice. Increased understanding of the application and limitations of PDXs will facilitate their rational use. Studies to date have not reported protein profiles of PDXs. Therefore, we developed a large cohort of HNSCC PDXs and found that tumor take rate was not influenced by the clinical, pathologic, or processing features. Protein expression profiles, from a subset of the PDXs, were characterized by reverse-phase protein array and the data was compared with The Cancer Genome Atlas HNSCC data. Cluster analysis revealed that HNSCC PDXs were more similar to primary HNSCC than to any other tumor type. Interestingly, while a significant fraction of proteins were expressed similarly in both primary HNSCC and PDXs, a subset of proteins/phosphoproteins were expressed at higher (or lower) levels in PDXs compared with primary HNSCC. These findings indicate that the proteome is generally conserved in PDXs, but mechanisms for both positive and negative model selection and/or differences in the stromal components exist.

IMPLICATIONS

Proteomic characterization of HNSCC PDXs demonstrates potential drivers for model selection and provides a framework for improved utilization of this expanding model system.

Targeted Hsp70 expression combined with CIK-activated immune reconstruction synergistically exerts antitumor efficacy in patient-derived hepatocellular carcinoma xenograft mouse models

The patient-derived tumor xenograft (PDTX) models can reproduce a similar natural genetic background and similar biological behaviors to tumor cells in patients, which is conducive to the assessment of personalized cancer treatment. In this study, to verify the targeting and effectiveness of the therapeutic strategy using a Survivin promoter-regulated oncolytic adenovirus expressing Hsp70, the PDTX models of hepatocellular carcinoma (HCC) were established in nude mice and the cytokine-induced killer (CIK) cells were intravenously infused into mice to partially reconstruct the mouse immune function. The results demonstrated that, either the immune anti-tumor effect caused by CIK cell infusion or the oncolytic effect generated by oncolytic adenovirus replication was very limited. However, the synergistic tumor inhibitory effect was significantly enhanced after treatments with oncolytic adenovirus expressing Hsp70 combined with CIK cells. Oncolytic adenovirus mediated the specific expression of Hsp70 in cancer tissues allowed the CIK chemotaxis, and induce the infiltration of CD3+ T cells in tumor stroma, thereby exhibiting anti-tumor activity. The anti-tumor effect was more effective for the highly malignant tumor xenografts with highly Survivin expression. This strategy can synergistically activate multiple anti-tumor mechanisms and exert effective anti-tumor activities that have a significant inhibitory effect against the growth of HCC xenografts.

Patient-derived xenograft models in gynecologic malignancies

In the era of targeted therapies, patients with gynecologic malignancies have not yet been major beneficiaries of this new class of agents. This may reflect the fact that the main tumor types-ovarian, uterine, and cervical--are a highly heterogeneous group of cancers with variable response to standard chemotherapies and the lack of models in which to study the diversity of these cancers. Cancer-derived cell lines fail to adequately recapitulate molecular hallmarks of specific cancer subsets and complex microenvironments, which may be critical for sensitivity to targeted therapies. Patient-derived xenografts (PDX) generated from fresh human tumor without prior in vitro culture, combined with whole genome expression, gene copy number, and sequencing analyses, could dramatically aid the development of novel therapies for gynecologic malignancies. Gynecologic tumors can be engrafted in immunodeficient mice with a high rate of success and within a reasonable time frame. The resulting PDX accurately recapitulates the patient's tumor with respect to histologic, molecular, and in vivo treatment response characteristics. Orthotopic PDX develop complications relevant to the clinic, such as ascites and bowel obstruction, providing opportunities to understand the biology of these clinical problems. Thus, PDX have great promise for improved understanding of gynecologic malignancies, serve as better models for designing novel therapies and clinical trials, and could underpin individualized, directed therapy for patients from whom such models have been established.

Rethinking ovarian cancer II: reducing mortality from high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSOC) accounts for 70-80% of ovarian cancer deaths, and overall survival has not changed significantly for several decades. In this Opinion article, we outline a set of research priorities that we believe will reduce incidence and improve outcomes for women with this disease. This 'roadmap' for HGSOC was determined after extensive discussions at an Ovarian Cancer Action meeting in January 2015.

Rethinking ovarian cancer II: reducing mortality from high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSOC) accounts for 70-80% of ovarian cancer deaths, and overall survival has not changed significantly for several decades. In this Opinion article, we outline a set of research priorities that we believe will reduce incidence and improve outcomes for women with this disease. This 'roadmap' for HGSOC was determined after extensive discussions at an Ovarian Cancer Action meeting in January 2015.

Rethinking ovarian cancer II: reducing mortality from high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSOC) accounts for 70-80% of ovarian cancer deaths, and overall survival has not changed significantly for several decades. In this Opinion article, we outline a set of research priorities that we believe will reduce incidence and improve outcomes for women with this disease. This 'roadmap' for HGSOC was determined after extensive discussions at an Ovarian Cancer Action meeting in January 2015.

c-Myc alterations confer therapeutic response and acquired resistance to c-Met inhibitors in MET-addicted cancers

Use of kinase inhibitors in cancer therapy leads invariably to acquired resistance stemming from kinase reprogramming. To overcome the dynamic nature of kinase adaptation, we asked whether a signal-integrating downstream effector might exist that provides a more applicable therapeutic target. In this study, we reported that the transcriptional factor c-Myc functions as a downstream effector to dictate the therapeutic response to c-Met inhibitors in c-Met-addicted cancer and derived resistance. Dissociation of c-Myc from c-Met control, likely overtaken by a variety of reprogrammed kinases, led to acquisition of drug resistance. Notably, c-Myc blockade by RNA interference or pharmacologic inhibition circumvented the acquired resistance to c-Met inhibition. Combining c-Myc blockade and c-Met inhibition in MET-amplified patient-derived xenograft mouse models heightened therapeutic activity. Our findings offer a preclinical proof of concept for the application of c-Myc-blocking agents as a tactic to thwart resistance to kinase inhibitors.

Lung cancer nanomedicine: potentials and pitfalls

Lung cancer is by far the most common cause of cancer-related deaths in the world. Nanoparticle-based therapies enable targeted drug delivery for lung cancer treatment with increased therapeutic efficiency and reduced systemic toxicity. At the same time, nanomedicine has the potential for multimodal treatment of lung cancer that may involve 'all-in-one' targeting of several tumor-associated cell types in a timely and spatially controlled manner. Therapeutic approaches, however, are hampered by a translational gap between basic scientists, clinicians and pharma industry due to suboptimal animal models and difficulties in scale-up production of nanoagents. This calls for a disease-centered approach with interdisciplinary basic and clinical research teams with the support of pharma industries.

Current State of Animal (Mouse) Modeling in Melanoma Research

Despite the considerable progress in understanding the biology of human cancer and technological advancement in drug discovery, treatment failure remains an inevitable outcome for most cancer patients with advanced diseases, including melanoma. Despite FDA-approved BRAF-targeted therapies for advanced stage melanoma showed a great deal of promise, development of rapid resistance limits the success. Hence, the overall success rate of melanoma therapy still remains to be one of the worst compared to other malignancies. Advancement of next-generation sequencing technology allowed better identification of alterations that trigger melanoma development. As development of successful therapies strongly depends on clinically relevant preclinical models, together with the new findings, more advanced melanoma models have been generated. In this article, besides traditional mouse models of melanoma, we will discuss recent ones, such as patient-derived tumor xenografts, topically inducible BRAF mouse model and RCAS/TVA-based model, and their advantages as well as limitations. Although mouse models of melanoma are often criticized as poor predictors of whether an experimental drug would be an effective treatment, development of new and more relevant models could circumvent this problem in the near future.

The future of patient-derived tumor xenografts in cancer treatment

Over the last decades, major technological advancements have led to a better understanding of the molecular drivers of human malignancies. Nonetheless, this progress only marginally impacted the cancer therapeutic approach, probably due to the limited ability of experimental models to predict efficacy in clinical trials. In an effort to offset this limitation, there has been an increasing interest in the development of patient-derived xenograft (PDX) models where human tumors are xenotransplanted into immunocompromised mice. Considering their high resemblance to human tumors and their stability, PDX models are becoming the preferred translational tools in preclinical studies. Nonetheless, several limitations hamper a wider use of PDX models and tarnish the concept that they might represent the missing piece in the personalized medicine puzzle.

The combinational therapy of trastuzumab and cetuximab inhibits tumor growth in a patient-derived tumor xenograft model of gastric cancer

PURPOSE

Gastric cancer (GC) is one of the leading causes of cancer mortality worldwide. Although therapeutic strategies for GC have improved, the prognosis for advanced GC remains poor. Herein, the present study sought to design a personalized cancer therapy specific to a stage III GC patient.

METHODS

The tumor was surgically removed and was used to establish a patient-derived tumor xenograft (PDTX) model utilizing nude mice. Various molecular-targeted anticancer treatments were tested in the study, including control (no treatment), bevacizumab, cetuximab, bevacizumab + cetuximab, trastuzumab, and trastuzumab + cetuximab.

RESULTS

Trastuzumab + cetuximab treatment exhibited the best antitumor growth effect, followed by trastuzumab, bevacizumab + cetuximab, cetuximab, and bevacizumab. Similarly, trastuzumab + cetuximab was also the most effective treatment at inducing apoptosis and cell cycle arrest in primary cultures of the patient's gastric cancer cells. Among all treatments tested in the study, trastuzumab + cetuximab showed the most profound effect in reducing the protein expression of proliferation and metastatic markers (VEGF, MMP-7, EGFT, Ki-67 and, PCNA) in tumors obtained from PDTX models, which may be the mechanism underlying the profound antitumor growth effect exerted by trastuzumab + cetuximab.

CONCLUSIONS

The data indicate that trastuzumab + cetuximab combinational therapy should be the most effective antitumor growth therapy for the GC patient whom we took the cancer cells from.

Pathomimetic cancer avatars for live-cell imaging of protease activity

Proteases are essential for normal physiology as well as multiple diseases, e.g., playing a causative role in cancer progression, including in tumor angiogenesis, invasion, and metastasis. Identification of dynamic alterations in protease activity may allow us to detect early stage cancers and to assess the efficacy of anti-cancer therapies. Despite the clinical importance of proteases in cancer progression, their functional roles individually and within the context of complex protease networks have not yet been well defined. These gaps in our understanding might be addressed with: 1) accurate and sensitive tools and methods to directly identify changes in protease activities in live cells, and 2) pathomimetic avatars for cancer that recapitulate in vitro the tumor in the context of its cellular and non-cellular microenvironment. Such avatars should be designed to facilitate mechanistic studies that can be translated to animal models and ultimately the clinic. Here, we will describe basic principles and recent applications of live-cell imaging for identification of active proteases. The avatars optimized by our laboratory are three-dimensional (3D) human breast cancer models in a matrix of reconstituted basement membrane (rBM). They are designated mammary architecture and microenvironment engineering (MAME) models as they have been designed to mimic the structural and functional interactions among cell types in the normal and cancerous human breast. We have demonstrated the usefulness of these pathomimetic avatars for following dynamic and temporal changes in cell:cell interactions and quantifying changes in protease activity associated with these interactions in real-time (4D). We also briefly describe adaptation of the avatars to custom-designed and fabricated tissue architecture and microenvironment engineering (TAME) chambers that enhance our ability to analyze concomitant changes in the malignant phenotype and the associated tumor microenvironment.

The challenges facing block copolymer micelles for cancer therapy: In vivo barriers and clinical translation

The application of block copolymer micelles (BCMs) in oncology has benefitted from advances in polymer chemistry, drug formulation and delivery as well as in vitro and in vivo biological models. While great strides have been made in each of these individual areas, there remains some disappointment overall, citing, in particular, the absence of more BCM formulations in clinical evaluation and practice. In this review, we aim to provide an overview of the challenges presented by in vivo systems to the effective design and development of BCMs. In particular, the barriers posed by systemic administration and tumor properties are examined. The impact of critical features, such as the size, stability and functionalization of BCMs is discussed, while key pre-clinical endpoints and models are critiqued. Given clinical considerations, we present this work as a means to stimulate a renewed focus on the unique chemical versatility bestowed by BCMs and a measured grasp of representative in vitro and in vivo models.

Dose-Independent ADME Properties and Tentative Identification of Metabolites of α-Mangostin from Garcinia mangostana in Mice by Automated Microsampling and UPLC-MS/MS Methods

The information about a marker compound's pharmacokinetics in herbal products including the characteristics of absorption, distribution, metabolism, excretion (ADME) is closely related to the efficacy/toxicity. Also dose range and administration route are critical factors to determine the ADME profiles. Since the supply of a sufficient amount of a marker compound in in vivo study is still difficult, pharmacokinetic investigations which overcome the limit of blood collection in mice are desirable. Thus, we have attempted to investigate concurrently the ADME and proposed metabolite identification of α-mangostin, a major constituent of mangosteen, Garcinia mangostana L, in mice with a wide dose range using an in vitro as well as in vivo automated micro-sampling system together. α-mangostin showed dose-proportional pharmacokinetics at intravenous doses of 5–20 mg/kg and oral doses of 10–100 mg/kg. The gastrointestinal absorption of α-mangostin was poor and the distribution of α-mangostin was relatively high in the liver, intestine, kidney, fat, and lung. α-mangostin was extensively metabolized in the liver and intestine. With regards to the formation of metabolites, the glucuronidated, bis-glucuronidated, dehydrogenated, hydrogenated, oxidized, and methylated α-mangostins were tentatively identified. We suggest that these dose-independent pharmacokinetic characteristics of α-mangostin in mice provide an important basis for preclinical applications of α-mangostin as well as mangosteen. In addition, these experimental methods can be applied to evaluate the pharmacokinetics of natural products in mice.

Patient-derived tumour xenografts as models for breast cancer drug development

PURPOSE OF REVIEW

Patient-derived xenografts (PDXs) are becoming increasing popular as a preclinical tool for evaluating novel therapeutic strategies in cancer. These models maintain the biological characteristics of the donor tumours and have a predictive power in the translation of cancer therapeutics into clinical settings. This review focuses on the rapidly growing body of literature on PDX models of breast cancer and their applications and challenges in cancer drug development.

RECENT FINDINGS

Several articles in the last 2 years have reported that breast cancer PDXs can reproduce the phenotype and diversity of patients' tumours. This preservation of breast cancer biology involves a number of different aspects, including gene expression patterns, mutational status, drug response and tumour architecture. These models have been shown to be a valuable tool for the identification of new treatment targets, rational drug combinations, biomarkers and mechanisms of drug resistance.

SUMMARY

The development of relevant, predictive models is key to increase the success rate for new drugs. PDX models of breast cancer hold the promise for the development of new and more efficient therapeutic strategies.

Melanoma patient-derived xenografts accurately model the disease and develop fast enough to guide treatment decisions

The development of novel therapies against melanoma would benefit from individualized tumor models to ensure the rapid and accurate identification of biomarkers of therapy response. Previous studies have suggested that patient-derived xenografts (PDXes) could be useful. However, the utility of PDXes in guiding real-time treatment decisions has only been reported in anecdotal forms. Here tumor biopsies from patients with stage III and IV metastatic malignant melanoma were transplanted into immunocompromised mice to generate PDXes. 23/26 melanoma biopsies generated serially transplantable PDX models, and their histology, mutation status and expression profile resembled their corresponding patient biopsy. The potential treatment for one patient was revealed by an in vitro drug screen and treating PDXes with the MEK inhibitor trametinib. In another patient, the BRAF mutation predicted the response of both the patient and its corresponding PDXes to MAPK-targeted therapy. Importantly, in this unselected group of patients, the time from biopsy for generation of PDXes until death was significantly longer than the time required to reach the treatment phase of the PDXes. Thus, it could be clinically meaningful to use this type of platform for melanoma patients as a pre-selection tool in clinical trials.

Clinical management of breast cancer heterogeneity

Traditionally, intertumour heterogeneity in breast cancer has been documented in terms of different histological subtypes, treatment sensitivity profiles, and clinical outcomes among different patients. Results of high-throughput molecular profiling studies have subsequently revealed the true extent of this heterogeneity. Further complicating this scenario, the heterogeneous expression of the oestrogen receptor (ER), progesterone receptor (PR), and HER2 has been reported in different areas of the same tumour. Furthermore, discordance, in terms of ER, PR and HER2 expression, has also been reported between primary tumours and their matched metastatic lesions. High-throughput molecular profiling studies have confirmed that spatial and temporal intratumour heterogeneity of breast cancers exist at a level beyond common expectations. We describe the different levels of tumour heterogeneity, and discuss the strategies that can be adopted by clinicians to tackle treatment response and resistance issues associated with such heterogeneity, including a rationally selected combination of agents that target driver mutations, the targeting of deleterious passenger mutations, identifying and eradicating the 'lethal' clone, targeting the tumour microenvironment, or using adaptive treatments and immunotherapy. The identification of the most-appropriate strategies and their implementation in the clinic will prove highly challenging and necessitate the adoption of radically new practices for the optimal clinical management of breast malignancies.

Plasma Hsp90 Level as a Marker of Early Acute Lymphoblastic Leukemia Engraftment and Progression in Mice

Current monitoring of acute lymphoblastic leukemia (ALL) in living mice is based on FACS analysis of blood hCD45+ cells. In this work, we evaluated the use of human IGFBP2, B2M or Hsp90 as soluble markers of leukemia. ELISA for B2M and IGFBP2 resulted in high background levels in healthy animals, precluding its use. Conversely, plasma levels of Hsp90 showed low background and linear correlation to FACS results. In another experiment, we compared Hsp90 levels with percentage of hCD45+ cells in blood, bone marrow, liver and spleen of animals weekly sacrificed. Hsp90 levels proved to be a superior method for the earlier detection of ALL engraftment and correlated linearly to ALL burden and progression in all compartments, even at minimal residual disease levels. Importantly, the Hsp90/hCD45+ ratio was not altered when animals were treated with dexamethasone or a PI3K inhibitor, indicating that chemotherapy does not directly interfere with leukemia production of Hsp90. In conclusion, plasma Hsp90 was validated as a soluble biomarker of ALL, useful for earlier detection of leukemia engraftment, monitoring leukemia kinetics at residual disease levels, and pre-clinical or mouse avatar evaluations of anti-leukemic drugs.

Phenotypic diversity of patient-derived melanoma populations in stem cell medium

Melanomas are highly heterogeneous tumors and there is no treatment effective at achieving long-term remission for metastatic melanoma patients. Thus, an appropriate model system for studying melanoma biology and response to drugs is necessary. It has been shown that composition of the medium is a critical factor in preserving the complexity of the tumor in in vitro settings, and melanospheres maintained in stem cell medium are a good model in this respect. In the present study, we observed that not all nodular melanoma patient-derived cell populations grown in stem cell medium were capable of forming melanospheres, and cell aggregates and anchorage-independent single-cell cultures emerged instead. Self-renewing capacity and unlimited growth potential indicated the presence of cells with stem-like properties in all patient-derived populations but immunophenotype and MITF expression exhibited variability. Enhanced MITF expression and activity was observed in melanospheres in comparison with cell aggregates and single-cell culture, and hypoxic-like conditions that increased the ability of single-cell population to form melanospheres enhanced MITF expression and cell pigmentation as well. Thus, MITF seems to be a critical transcription factor for formation of both patient-derived and hypoxia-induced melanospheres. After 2 years of continuous culturing, melanospheres progressively underwent transition into cell aggregates that was accompanied by changes in expression of several MITF-dependent genes associated with melanogenesis and survival and alterations in the composition of subpopulations but not in the frequency of ABCB5-positive cells. Several biological properties of parent tumor are well preserved in patient-derived melanospheres, but during prolonged culturing the heterogeneity is substantially lost when the melanospheres are substituted by cell aggregates. This should be considered when cell aggregates instead of melanospheres are used in the study of melanoma biology and cell response to drugs.

Spontaneous Post-Transplant Disorders in NOD.Cg- Prkdcscid Il2rgtm1Sug/JicTac (NOG) Mice Engrafted with Patient-Derived Metastatic Melanomas

Patient-derived tumor xenograft (PDTX) approach is nowadays considered a reliable preclinical model to study in vivo cancer biology and therapeutic response. NOD scid and Il2rg-deficient mice represent the "gold standard" host for the generation of PDTXs. Compared to other immunocompromised murine lines, these mice offers several advantages including higher engraftment rate, longer lifespan and improved morphological and molecular preservation of patient-derived neoplasms. Here we describe a spectrum of previously uncharacterized post-transplant disorders affecting 14/116 (12%) NOD.Cg- Prkdcscid Il2rgtm1Sug/JicTac (NOG) mice subcutaneously engrafted with patient-derived metastatic melanomas. Affected mice exhibited extensive scaling/crusting dermatitis (13/14) associated with emaciation (13/14) and poor/unsuccessful tumor engraftment (14/14). In this context, the following pathological conditions have been recognized and characterized in details: (i) immunoinflammatory disorders with features of graft versus host disease (14/14); (ii) reactive lymphoid infiltrates effacing xenografted tumors (8/14); (iii) post-transplant B cell lymphomas associated with Epstein-Barr virus reactivation (2/14). We demonstrate that all these entities are driven by co-transplanted human immune cells populating patient-derived tumor samples. Since the exploding interest in the utilization of NOD scid and Il2rg-deficient mice for the establishment of PDTX platforms, it is of uppermost importance to raise the awareness of the limitations associated with this model. The disorders here described adversely impact tumor engraftment rate and animal lifespan, potentially representing a major confounding factor in the context of efficacy and personalized therapy studies. The occurrence of these conditions in the NOG model reflects the ability of this mouse line to promote efficient engraftment of human immune cells. Co-transplanted human lymphoid cells have indeed the potential to colonize the recipient mouse initiating the post-transplant conditions here reported. On the other hand, the evidence of an immune response of human origin against the xenotransplanted melanoma opens intriguing perspectives for the establishment of suitable preclinical models of anti-melanoma immunotherapy.

Patient-Derived Xenografts as a Model System for Radiation Research

The cancer literature is filled with promising preclinical studies demonstrating impressive efficacy for new therapeutics, yet translation of these approaches into clinical successes has been rare, indicating that current methods used to predict efficacy are suboptimal. The most likely reason for the limitation of these studies is the disconnect between preclinical models and cancers treated in the clinic. Specifically, most preclinical models are poor representations of human disease. Immortalized cancer cell lines that dominate the cancer literature may be, in a sense, "paper tigers" that have been selected by decades of culture to be artificially driven by highly targetable proteins. Thus, although effective in treating these cell lines either in vitro or as artificial tumors transplanted from culture into experimental animals as xenografts, the identified therapies would likely underperform in a clinical setting. This inherent limitation applies not only to drug testing but also to experiments with radiation therapy. Indeed, traditional radiobiology methods rely on monolayer culture systems, with emphasis on colony formation and DNA damage assessment that may have limited clinical translation. As such, there has been keen interest in developing tumor explant systems in which patient tumors are directly transplanted into and solely maintained in vivo, using immunocompromised mice. These so-called patient-derived xenografts (PDXs) represent a robust model system that has been garnering support in academia and industry as a superior preclinical approach to drug testing. Likewise, PDX models have the potential to improve radiation research. In this review, we describe how PDX models are currently being used for both drug and radiation testing and how they can be incorporated into a translational research program.

Translating genomics for precision cancer medicine

The Human Genome Project not only provided the essential reference map for the human genome but also stimulated the development of technology and analytic tools to process massive quantities of genomic data. As a result of this project, new technologies for DNA sequencing have improved in efficiency and cost by more than a millionfold over the past decade, and these technologies can now be routinely applied at a cost of less than $5,000 per genome. Although the application of these technologies in cancer genomics research has continued to contribute to basic discoveries, opportunities for translating them for individual patients have also emerged. This is especially important in clinical cancer research, where genetic alterations in a patient's tumor may be matched to molecularly targeted therapies. In this review, we discuss the integration of cancer genomics and clinical oncology and the opportunity to deliver precision cancer medicine.

Deciphering the cellular source of tumor relapse identifies CD44 as a major therapeutic target in pancreatic adenocarcinoma

It has been commonly found that in patients presenting Pancreatic Ductal Adenocarcinoma (PDAC), after a period of satisfactory response to standard treatments, the tumor becomes non-responsive and patient death quickly follows. This phenomenon is mainly due to the rapid and uncontrolled development of the residual tumor. The origin and biological characteristics of residual tumor cells in PDAC still remain unclear. In this work, using PDACs from patients, preserved as xenografts in nude mice, we demonstrated that a residual PDAC tumor originated from a small number of CD44+ cells present in the tumor. During PDAC relapse, proliferating CD44+ cells decrease expression of ZEB1, while overexpressing the MUC1 protein, and gain morphological and biological characteristics of differentiation. Also, we report that CD44+ cells, in primary and residual PDAC tumors, are part of a heterogeneous population, which includes variable numbers of CD133+ and EpCAM+ cells. We confirmed the propagation of CD44+ cells in samples from cases of human relapse, following standard PDAC treatment. Finally, using systemic administration of anti-CD44 antibodies in vivo, we demonstrated that CD44 is an efficient therapeutic target for treating tumor relapse, but not primary PDAC tumors. We conclude that CD44+ cells generate the relapsing tumor and, as such, are themselves promising therapeutic targets for treating patients with recurrent PDAC.

Prioritizing therapeutic targets using patient-derived xenograft models

Effective systemic treatment of cancer relies on the delivery of agents with optimal therapeutic potential. The molecular age of medicine has provided genomic tools that can identify a large number of potential therapeutic targets in individual patients, heralding the promise of personalized treatment. However, determining which potential targets actually drive tumor growth and should be prioritized for therapy is challenging. Indeed, reliable molecular matches of target and therapeutic agent have been stringently validated in the clinic for only a small number of targets. Patient-derived xenografts (PDXs) are tumor models developed in immunocompromised mice using tumor procured directly from the patient. As patient surrogates, PDX models represent a powerful tool for addressing individualized therapy. Challenges include humanizing the immune system of PDX models and ensuring high quality molecular annotation, in order to maximize insights for the clinic. Importantly, PDX can be sampled repeatedly and in parallel, to reveal clonal evolution, which may predict mechanisms of drug resistance and inform therapeutic strategy design.

A new mouse avatar model of non-small cell lung cancer

Introduction: Lung cancer remains the leading cause of tumor-related deaths, despite advances in the understanding of the disease pathogenesis and in its clinical treatment. It is crucial to develop novel technologies to discover disease biomarkers and predict individual therapy response.

Materials and methods: We established 48 patients-derived tumor xenografts (PDTXs) implanted in the subrenal capsule of immunodeficient mice using thin, precision-cut tumor tissue slices, derived from five patients affected by non-small cell lung cancer. Twenty-six tissue slices were immediately processed and implanted at sample recovery [patients-derived tumor xenografts derived from fresh tissue (dPDTX)], whereas the remaining sections were cultured on specific organotypic supports at 37°C and 5% CO₂ for 24 h before grafting [patients-derived tumor xenografts derived from cultured tissue (cPDTX)]. At sacrifice, xenografts tissue morphology, proliferation (Ki67), and histotype markers were analyzed. Oncogenic miRNAs profiles were assessed in PDTXs, human tumors, and serum from one patient.

Results: Xenografts retained the original cancer features and there were no differences between dPDTXs and cPDTXs. Squamous cell carcinoma (SCC) xenografts showed a higher engraftment rate than adenocarcinoma (AC)-derived tumors. At basal time, Ki67 levels were higher in SCCs than in ACs, and the expression levels of genes associated to a stem cell-like phenotype were also more expressed in SCC samples. The analysis of oncogenic miRNAs showed that circulating miR-19b, -21, and -210 levels were correlated with higher Ki67 expression in xenografts.

Conclusion: Our study implemented the PDTX model with thin, precision-cut tumor slices from small tumors, which could be useful for clinical applications and predictive purposes. The different engraftment success is likely determined by tumor histotype, high proliferation index, and the expression of genes essential for cancer stem cells maintenance. Our PDTXs model could be a valid tool to expand primary tumors for the discovery of new biomarkers and explore therapeutic options.

Impact of the spheroid model complexity on drug response

Pharmaceutical investigators are searching for preclinical models closely resembling the original cancer and predicting clinical outcome. This study compares drug response of three in vitro 3D-drug screening models with different complexity. Tumor cell line spheroids were generated from the cell lines Caco-2, DLD-1, COLO 205, HT-29 and HCT-116, and treated with clinically relevant combination therapies, namely 5-FU/oxaliplatin (FO), 5-FU/irinotecan (FI) and the molecular drugs Cetuximab, Trastuzumab, Vorinostat and Everolimus. Treatment results were compared with spheroids originated from tumor cell lines (Caco-2, DLD-1) co-cultured with stromal cells (PBMCs, cancer-associated fibroblasts of colorectal origin) and spheroids directly prepared from colon cancer tissues. Different microenvironment compositions altered the tumor cell line spheroid response patterns. Adding PBMCs increased resistance to FO treatment by 10-15% in Caco-2 and DLD-1 spheroids but decreased resistance to FI by 16% in DLD-1 spheroids. Fibroblast co-cultures decreased resistance to FI in Caco-2 spheroids by 38% but had no impact on FO. Treatment of colon cancer tissue spheroids revealed three distinct response pattern subgroups not detectable in 3D cell lines models. The cancer tissue spheroid model mimics both tumor characteristics and the stromal microenvironment and therefore is an invaluable screening model for pharmaceutical drug development.

Probing Human NK Cell Biology Using Human Immune System (HIS) Mice

Our incomplete understanding of the mechanisms that orchestrate human lymphocyte differentiation and condition human immune responses is in part due to the limited access to normal human tissue samples that can inform on these complex processes. In addition, in vitro culture conditions fail to recapitulate the three-dimensional microenvironments that influence cell-cell interactions and impact on immune outcomes. Small animals provide a preclinical model to dissect and probe immunity and over the past decades, development of immunodeficient hosts that can be engrafted with human hematopoietic precursors and mature cells have led to the development of new in vivo models to study human lymphocyte development and function. Natural killer (NK) cells are implicated in the recognition and elimination of pathogen-infected and transformed cells and belong to a family of diverse innate lymphoid cells (ILCs) that provide early immune defense against disease. Here, we summarize the use of humanized mouse models for the study of NK cell and group 1 ILCs and their respective roles in immunity and tissue homeostasis.