Patient-derived tumor xenografts: transforming clinical samples into mouse models

Genomic characterisation of small cell lung cancer patient-derived xenografts generated from endobronchial ultrasound-guided transbronchial needle aspiration specimens

Patient-derived xenograft (PDX) models generated from surgical specimens are gaining popularity as preclinical models of cancer. However, establishment of PDX lines from small cell lung cancer (SCLC) patients is difficult due to very limited amount of available biopsy material. We asked whether SCLC cells obtained from endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) could generate PDX lines that maintained the phenotypic and genetic characteristics of the primary tumor. Following successful EBUS-TBNA sampling for diagnostic purposes, we obtained an extra sample for cytologic analysis and implantation into the flanks of immunodeficient mice. Animals were monitored for engraftment for up to 6 months. Histopathologic and immunohistochemical analysis, and targeted next-generation re-sequencing, were then performed in both the primary sample and the derivative PDX line. A total of 12 patients were enrolled in the study. EBUS-TBNA aspirates yielded large numbers of viable tumor cells sufficient to inject between 18,750 and 1,487,000 cells per flank, and to yield microgram quantities of high-quality DNA. Of these, samples from 10 patients generated xenografts (engraftment rate 83%) with a mean latency of 104 days (range 63–188). All but one maintained a typical SCLC phenotype that closely matched the original sample. Identical mutations that are characteristic of SCLC were identified in both the primary sample and xenograft line. EBUS-TBNA has the potential to be a powerful tool in the development of new targeting strategies for SCLC patients by providing large numbers of viable tumor cells suitable for both xenografting and complex genomic analysis.

KRAS and PIK3CA Mutation Frequencies in Patient-derived Xenograft Models of Pancreatic and Colorectal Cancer Are Reflective of Patient Tumors and Stable Across Passages

One obstacle in the translation of advances in cancer research into the clinic is a deficiency of adequate preclinical models that recapitulate human disease. Patient-derived xenograft (PDX) models are established by engrafting patient tumor tissue into mice and are advantageous because they capture tumor heterogeneity. One concern with these models is that selective pressure could lead to mutational drift and thus be an inaccurate reflection of patient tumors. Therefore, we evaluated if mutational frequency in PDX models is reflective of patient populations and if crucial mutations are stable across passages. We examined KRAS and PIK3CA gene mutations from pancreatic ductal adenocarcinoma (PDAC) (n = 30) and colorectal cancer (CRC) (n = 37) PDXs for as many as eight passages. DNA was isolated from tumors and target sequences were amplified by polymerase chain reaction. KRAS codons 12/13 and PIK3CA codons 542/545/1047 were examined using pyrosequencing. Twenty-three of 30 (77%) PDAC PDXs had KRAS mutations and one of 30 (3%) had PIK3CA mutations. Fifteen of 37 (41%) CRC PDXs had KRAS mutations and three of 37 (8%) had PIK3CA mutations. Mutations were 100 per cent preserved across passages. We found that the frequency of KRAS (77%) and PIK3CA (3%) mutations in PDAC PDX was similar to frequencies in patient tumors (71 to 100% KRAS, 0 to 11% PIK3CA). Similarly, KRAS (41%) and PIK3CA (8%) mutations in CRC PDX closely paralleled patient tumors (35 to 51% KRAS, 12 to 21% PIK3CA). The accurate mirroring and stability of genetic changes in PDX models compared with patient tumors suggest that these models are good preclinical surrogates for patient tumors.

Patient-derived xenograft models: an emerging platform for translational cancer research

Recently, there has been an increasing interest in the development and characterization of patient-derived tumor xenograft (PDX) models for cancer research. PDX models mostly retain the principal histologic and genetic characteristics of their donor tumor and remain stable across passages. These models have been shown to be predictive of clinical outcomes and are being used for preclinical drug evaluation, biomarker identification, biologic studies, and personalized medicine strategies. This article summarizes the current state of the art in this field, including methodologic issues, available collections, practical applications, challenges and shortcomings, and future directions, and introduces a European consortium of PDX models.

SIGNIFICANCE

PDX models are increasingly used in translational cancer research. These models are useful for drug screening, biomarker development, and the preclinical evaluation of personalized medicine strategies. This review provides a timely overview of the key characteristics of PDX models and a detailed discussion of future directions in the field.

Using a rhabdomyosarcoma patient-derived xenograft to examine precision medicine approaches and model acquired resistance

BACKGROUND

Precision (Personalized) medicine has the potential to revolutionize patient health care especially for many cancers where the fundamental disease etiology remains either elusive or has no available therapy. Here we outline a study in alveolar rhabdomyosarcoma, in which we use gene expression profiling and a series of drug prediction algorithms combined with a matched patient-derived xenograft (PDX) model to test bioinformatically predicted therapies.

PROCEDURE

A PDX model was developed from a patient biopsy and a number of drugs identified using gene expression analysis in combination with drug prediction algorithms. Drugs chosen from each of the predictive methodologies, along with the patient's standard-of-care therapy (ICE-T), were tested in vivo in the PDX tumor. A second study was initiated using the tumors that re-grew following the ICE-T treatment. Further expression analysis identified additional therapies with potential anti-tumor efficacy.

RESULTS

A number of the predicted therapies were found to be active against the tumors in particular BGJ398 (FGFR2) and ICE-T. Re-transplanted ICE-T treated tumorgrafts demonstrated a decreased response to ICE-T recapitulating the patient's refractory disease. Gene expression profiling of the ICE-T treated tumorgrafts identified cytarabine (SLC29A1) as a potential therapy, which was shown, along with BGJ398, to be highly active in vivo.

CONCLUSIONS

This study illustrates that PDX models are suitable surrogates for testing potential therapeutic strategies based on gene expression analysis, modeling clinical drug resistance and hold the potential to assist in guiding prospective patient care.

KRAS and PIK3CA mutation frequencies in patient-derived xenograft models of pancreatic and colorectal cancer are reflective of patient tumors and stable across passages

One obstacle in the translation of advances in cancer research into the clinic is a deficiency of adequate preclinical models that recapitulate human disease. Patient-derived xenograft (PDX) models are established by engrafting patient tumor tissue into mice and are advantageous because they capture tumor heterogeneity. One concern with these models is that selective pressure could lead to mutational drift and thus be an inaccurate reflection of patient tumors. Therefore, we evaluated if mutational frequency in PDX models is reflective of patient populations and if crucial mutations are stable across passages. We examined KRAS and PIK3CA gene mutations from pancreatic ductal adenocarcinoma (PDAC) (n = 30) and colorectal cancer (CRC) (n = 37) PDXs for as many as eight passages. DNA was isolated from tumors and target sequences were amplified by polymerase chain reaction. KRAS codons 12/13 and PIK3CA codons 542/545/1047 were examined using pyrosequencing. Twenty-three of 30 (77%) PDAC PDXs had KRAS mutations and one of 30 (3%) had PIK3CA mutations. Fifteen of 37 (41%) CRC PDXs had KRAS mutations and three of 37 (8%) had PIK3CA mutations. Mutations were 100 per cent preserved across passages. We found that the frequency of KRAS (77%) and PIK3CA (3%) mutations in PDAC PDX was similar to frequencies in patient tumors (71 to 100% KRAS, 0 to 11% PIK3CA). Similarly, KRAS (41%) and PIK3CA (8%) mutations in CRC PDX closely paralleled patient tumors (35 to 51% KRAS, 12 to 21% PIK3CA). The accurate mirroring and stability of genetic changes in PDX models compared with patient tumors suggest that these models are good preclinical surrogates for patient tumors.

AXL mediates resistance to cetuximab therapy

The EGFR antibody cetuximab is used to treat numerous cancers, but intrinsic and acquired resistance to this agent is a common clinical outcome. In this study, we show that overexpression of the oncogenic receptor tyrosine kinase AXL is sufficient to mediate acquired resistance to cetuximab in models of non-small cell lung cancer (NSCLC) and head and neck squamous cell carcinoma (HNSCC), where AXL was overexpressed, activated, and tightly associated with EGFR expression in cells resistant to cetuximab (Ctx(R) cells). Using RNAi methods and novel AXL-targeting agents, we found that AXL activation stimulated cell proliferation, EGFR activation, and MAPK signaling in Ctx(R) cells. Notably, EGFR directly regulated the expression of AXL mRNA through MAPK signaling and the transcription factor c-Jun in Ctx(R) cells, creating a positive feedback loop that maintained EGFR activation by AXL. Cetuximab-sensitive parental cells were rendered resistant to cetuximab by stable overexpression of AXL or stimulation with EGFR ligands, the latter of which increased AXL activity and association with the EGFR. In tumor xenograft models, the development of resistance following prolonged treatment with cetuximab was associated with AXL hyperactivation and EGFR association. Furthermore, in an examination of patient-derived xenografts established from surgically resected HNSCCs, AXL was overexpressed and activated in tumors that displayed intrinsic resistance to cetuximab. Collectively, our results identify AXL as a key mediator of cetuximab resistance, providing a rationale for clinical evaluation of AXL-targeting drugs to treat cetuximab-resistant cancers. Cancer Res; 74(18); 5152-64. ©2014 AACR.

Modeling astrocytoma pathogenesis in vitro and in vivo using cortical astrocytes or neural stem cells from conditional, genetically engineered mice

Current astrocytoma models are limited in their ability to define the roles of oncogenic mutations in specific brain cell types during disease pathogenesis and their utility for preclinical drug development. In order to design a better model system for these applications, phenotypically wild-type cortical astrocytes and neural stem cells (NSC) from conditional, genetically engineered mice (GEM) that harbor various combinations of floxed oncogenic alleles were harvested and grown in culture. Genetic recombination was induced in vitro using adenoviral Cre-mediated recombination, resulting in expression of mutated oncogenes and deletion of tumor suppressor genes. The phenotypic consequences of these mutations were defined by measuring proliferation, transformation, and drug response in vitro. Orthotopic allograft models, whereby transformed cells are stereotactically injected into the brains of immune-competent, syngeneic littermates, were developed to define the role of oncogenic mutations and cell type on tumorigenesis in vivo. Unlike most established human glioblastoma cell line xenografts, injection of transformed GEM-derived cortical astrocytes into the brains of immune-competent littermates produced astrocytomas, including the most aggressive subtype, glioblastoma, that recapitulated the histopathological hallmarks of human astrocytomas, including diffuse invasion of normal brain parenchyma. Bioluminescence imaging of orthotopic allografts from transformed astrocytes engineered to express luciferase was utilized to monitor in vivo tumor growth over time. Thus, astrocytoma models using astrocytes and NSC harvested from GEM with conditional oncogenic alleles provide an integrated system to study the genetics and cell biology of astrocytoma pathogenesis in vitro and in vivo and may be useful in preclinical drug development for these devastating diseases.

Animal models of gastrointestinal and liver diseases. New mouse models for studying dietary prevention of colorectal cancer

Colorectal cancer is a heterogeneous disease that is one of the major causes of cancer death in the U.S. There is evidence that lifestyle factors like diet can modulate the course of this disease. Demonstrating the benefit and mechanism of action of dietary interventions against colon cancer will require studies in preclinical models. Many mouse models have been developed to study colon cancer but no single model can reflect all types of colon cancer in terms of molecular etiology. In addition, many models develop only low-grade cancers and are confounded by development of the disease outside of the colon. This review will discuss how mice can be used to model human colon cancer and it will describe a variety of new mouse models that develop colon-restricted cancer as well as more advanced phenotypes for studies of late-state disease.

Maturation stage of T-cell acute lymphoblastic leukemia determines BCL-2 versus BCL-XL dependence and sensitivity to ABT-199

Acute lymphoblastic leukemia (ALL) is a hematopoietic malignancy derived from immature B-lymphoid and T-lymphoid cells (T-ALL). In T-ALL, there is an early T-cell progenitor (ETP) subgroup that has a very high risk for relapse. In this study, we used mitochondrial BH3 profiling to determine antiapoptotic protein dependencies in T-ALL. We found that T-ALL cell lines and primary patient samples are dependent upon BCL-XL, except when the cancer bears an ETP phenotype, in which case it is BCL-2 dependent. These distinctions directly relate to differential sensitivity to the BH3 mimetics ABT-263 and ABT-199, both in vitro and in vivo. We thus describe for the first time a change of antiapoptotic protein dependence that is related to the differentiation stage of the leukemic clone. Our findings demonstrate that BCL-2 is a clinically relevant target for therapeutic intervention with ABT-199 in ETP-ALL.

SIGNIFICANCE

ETP T-ALL is a treatment-resistant subtype of T-ALL for which novel targeted therapies are urgently needed. We have discovered, through BH3 profiling, that ETP-ALL is BCL-2 dependent and is very sensitive to in vitro and in vivo treatment with ABT-199, a drug well tolerated in clinical trials.

Obesity and resistance to cancer chemotherapy: interacting roles of inflammation and metabolic dysregulation

The prevalence of obesity, an established risk factor for many chronic diseases, including several types of cancer, has risen steadily over the past four decades in the United States and worldwide. To date, research in this area has focused on the epidemiologic associations between obesity and cancer risk, as well as on the mechanisms underlying those associations. However, an emerging but understudied issue of clinical importance is the diminution of chemotherapeutic efficacy in obese cancer patients. The mechanisms underlying the negative impact of obesity on therapeutic responses are likely multifactorial. The effects of obesity on chemotherapy drug pharmacokinetics and dosage have been extensively reviewed elsewhere, so this review will focus on the interplay among obesity, increased inflammation, metabolic perturbations, and chemoresistance. The ultimate goal of this review is to delineate areas for future research that could lead to the identification of new targets and strategies for improved cancer outcomes in obese patients.

Advances in patient-derived tumor xenografts: from target identification to predicting clinical response rates in oncology

Most oncology compounds entering clinical development have passed stringent preclinical pharmacology evaluation criteria. However, only a small fraction of experimental agents induce meaningful antitumor activities in the clinic. Low predictability of conventional preclinical pharmacology models is frequently cited as a main reason for the unusually high clinical attrition rates of therapeutic compounds in oncology. Therefore, improvement in the predictive values of preclinical efficacy models for clinical outcome holds great promise to reduce the clinical attrition rates of experimental compounds. Recent reports suggest that pharmacology studies conducted with patient derived xenograft (PDX) tumors are more predictive for clinical outcome compared to conventional, cell line derived xenograft (CDX) models, in particular when therapeutic compounds were tested at clinically relevant doses (CRDs). Moreover, the study of the most malignant cell types within tumors, the tumor initiating cells (TICs), relies on the availability of preclinical models that mimic the lineage hierarchy of cells within tumors. PDX models were shown to more closely recapitulate the heterogeneity of patient tumors and maintain the molecular, genetic, and histological complexity of human tumors during early stages of sequential passaging in mice, rendering them ideal tools to study the responses of TICs, tumor- and stromal cells to therapeutic intervention. In this commentary, we review the progress made in the development of PDX models in key areas of oncology research, including target identification and validation, tumor indication search and the development of a biomarker hypothesis that can be tested in the clinic to identify patients that will benefit most from therapeutic intervention.

Chemogenetic evaluation of the mitotic kinesin CENP-E reveals a critical role in triple-negative breast cancer

Breast cancer patients with tumors lacking the three diagnostic markers (ER, PR, and HER2) are classified as triple-negative (primarily basal-like) and have poor prognosis because there is no disease-specific therapy available. To address this unmet medical need, gene expression analyses using more than a thousand breast cancer samples were conducted, which identified elevated centromere protein E (CENP-E) expression in the basal-a molecular subtype relative to other subtypes. CENP-E, a mitotic kinesin component of the spindle assembly checkpoint, is shown to be induced in basal-a tumor cell lines by the mitotic spindle inhibitor drug docetaxel. CENP-E knockdown by inducible shRNA reduces basal-a breast cancer cell viability. A potent, selective CENP-E inhibitor (PF-2771) was used to define the contribution of CENP-E motor function to basal-like breast cancer. Mechanistic evaluation of PF-2771 in basal-a tumor cells links CENP-E-dependent molecular events (e.g., phosphorylation of histone H3 Ser-10; phospho-HH3-Ser10) to functional outcomes (e.g., chromosomal congression defects). Across a diverse panel of breast cell lines, CENP-E inhibition by PF-2771 selectively inhibits proliferation of basal breast cancer cell lines relative to premalignant ones and its response correlates with the degree of chromosomal instability. Pharmacokinetic-pharmacodynamic efficacy analysis in a basal-a xenograft tumor model shows that PF-2771 exposure is well correlated with increased phospho-HH3-Ser10 levels and tumor growth regression. Complete tumor regression is observed in a patient-derived, basal-a breast cancer xenograft tumor model treated with PF-2771. Tumor regression is also observed with PF-2771 in a taxane-resistant basal-a model. Taken together, CENP-E may be an effective therapeutic target for patients with triple-negative/basal-a breast cancer.

Three-dimensional cancer models mimic cell-matrix interactions in the tumour microenvironment

Basic in vitro systems can be used to model and assess complex diseases, such as cancer. Recent advances in this field include the incorporation of multiple cell types and extracellular matrix proteins into three-dimensional (3D) models to recapitulate the structure, organization and functionality of live tissue in situ. Cells within such a 3D environment behave very differently from cells on two-dimensional (2D) substrates, as cell-matrix interactions trigger signalling pathways and cellular responses in 3D, which may not be observed in 2D. Thus, the use of 3D systems can be advantageous for the assessment of disease progression over 2D set-ups alone. Here, we highlight the current advantages and challenges of employing 3D systems in the study of cancer and provide an overview to guide the appropriate use of distinct models in cancer research.

A microphysiological system model of therapy for liver micrometastases

Metastasis accounts for almost 90% of cancer-associated mortality. The effectiveness of cancer therapeutics is limited by the protective microenvironment of the metastatic niche and consequently these disseminated tumors remain incurable. Metastatic disease progression continues to be poorly understood due to the lack of appropriate model systems. To address this gap in understanding, we propose an all-human microphysiological system that facilitates the investigation of cancer behavior in the liver metastatic niche. This existing LiverChip is a 3D-system modeling the hepatic niche; it incorporates a full complement of human parenchymal and non-parenchymal cells and effectively recapitulates micrometastases. Moreover, this system allows real-time monitoring of micrometastasis and assessment of human-specific signaling. It is being utilized to further our understanding of the efficacy of chemotherapeutics by examining the activity of established and novel agents on micrometastases under conditions replicating diurnal variations in hormones, nutrients and mild inflammatory states using programmable microdispensers. These inputs affect the cues that govern tumor cell responses. Three critical signaling groups are targeted: the glucose/insulin responses, the stress hormone cortisol and the gut microbiome in relation to inflammatory cues. Currently, the system sustains functioning hepatocytes for a minimum of 15 days; confirmed by monitoring hepatic function (urea, α-1-antitrypsin, fibrinogen, and cytochrome P450) and injury (AST and ALT). Breast cancer cell lines effectively integrate into the hepatic niche without detectable disruption to tissue, and preliminary evidence suggests growth attenuation amongst a subpopulation of breast cancer cells. xMAP technology combined with systems biology modeling are also employed to evaluate cellular crosstalk and illustrate communication networks in the early microenvironment of micrometastases. This model is anticipated to identify new therapeutic strategies for metastasis by elucidating the paracrine effects between the hepatic and metastatic cells, while concurrently evaluating agent efficacy for metastasis, metabolism and tolerability.

Hydrogel-based 3D model of patient-derived prostate xenograft tumors suitable for drug screening

The lack of effective therapies for bone metastatic prostate cancer (PCa) underscores the need for accurate models of the disease to enable the discovery of new therapeutic targets and to test drug sensitivities of individual tumors. To this end, the patient-derived xenograft (PDX) PCa model using immunocompromised mice was established to model the disease with greater fidelity than is possible with currently employed cell lines grown on tissue culture plastic. However, poorly adherent PDX tumor cells exhibit low viability in standard culture, making it difficult to manipulate these cells for subsequent controlled mechanistic studies. To overcome this challenge, we encapsulated PDX tumor cells within a three-dimensional hyaluronan-based hydrogel and demonstrated that the hydrogel maintains PDX cell viability with continued native androgen receptor expression. Furthermore, a differential sensitivity to docetaxel, a chemotherapeutic drug, was observed as compared to a traditional PCa cell line. These findings underscore the potential impact of this novel 3D PDX PCa model as a diagnostic platform for rapid drug evaluation and ultimately push personalized medicine toward clinical reality.

Cancer cell lines for drug discovery and development

Despite the millions of dollars spent on target validation and drug optimization in preclinical models, most therapies still fail in phase III clinical trials. Our current model systems, or the way we interpret data from them, clearly do not have sufficient clinical predictive power. Current opinion suggests that this is because the cell lines and xenografts that are commonly used are inadequate models that do not effectively mimic and predict human responses. This has become such a widespread belief that it approaches dogma in the field of drug discovery and optimization and has spurred a surge in studies devoted to the development of more sophisticated animal models such as orthotopic patient-derived xenografts in an attempt to obtain more accurate estimates of whether particular cancers will respond to given treatments. Here, we explore the evidence that has led to the move away from the use of in vitro cell lines and toward various forms of xenograft models for drug screening and development. We review some of the pros and cons of each model and give an overview of ways in which the use of cell lines could be modified to improve the predictive capacity of this well-defined model.

Cancer mouse models: past, present and future

The development and advances in gene targeting technology over the past three decades has facilitated the generation of cancer mouse models that recapitulate features of human malignancies. These models have been and still remain instrumental in revealing the complexities of human cancer biology. However, they will need to evolve in the post-genomic era of cancer research. In this review we will highlight some of the key developments over the past decades and will discuss the new possibilities of cancer mouse models in the light of emerging powerful gene manipulating tools.

Mouse tumour models to guide drug development and identify resistance mechanisms

We need improved, translatable and predictive tumour models for the evaluation of response and the evolution of resistance to targeted therapeutics. We provide a review of the use of different types of preclinical tumour models to evaluate novel anticancer agents, and model the rapidly evolving landscape of resistance to targeted therapy. We focus on describing the various preclinical models available for candidate drug development and design considerations for preclinical experiments, depending on the aspect of drug action being interrogated. We discuss selected examples of how experimental findings have translated into clinical outcomes for targeted agents, predicted mechanisms that drive resistance and strategies to overcome the evolution thereof. We discuss challenges in preclinical experimental design and interpretation and possible improvements in animal models of therapeutic response and resistance, with an emphasis on improved translation of experimental research into clinical practice.

Establishment and characterization of 7 novel hepatocellular carcinoma cell lines from patient-derived tumor xenografts

Hepatocellular carcinoma (HCC) is a common cancer with poor prognosis worldwide and the molecular mechanism is not well understood. This study aimed to establish a collection of human HCC cell lines from patient-derived xenograft (PDX) models. From the 20 surgical HCC sample collections, 7 tumors were successfully developed in immunodeficient mice and further established 7 novel HCC cell lines (LIXC002, LIXC003, LIXC004, LIXC006, LIXC011, LIXC012 and CPL0903) by primary culture. The characterization of cell lines was defined by morphology, growth kinetics, cell cycle, chromosome analysis, short tandem repeat (STR) analysis, molecular profile, and tumorigenicity. Additionally, response to clinical chemotherapeutics was validated both in vitro and in vivo. STR analysis indicated that all cell lines were unique cells different from known cell lines and free of contamination by bacteria or mycoplasma. The other findings were quite heterogeneous between individual lines. Chromosome aberration could be found in all cell lines. Alpha-fetoprotein was overexpressed only in 3 out of 7 cell lines. 4 cell lines expressed high level of vimentin. Ki67 was strongly stained in all cell lines. mRNA level of retinoic acid induced protein 3 (RAI3) was decreased in all cell lines. The 7 novel cell lines showed variable sensitivity to 8 tested compounds. LIXC011 and CPL0903 possessed multiple drug resistance property. Sorafenib inhibited xenograft tumor growth of LIXC006, but not of LIXC012. Our results indicated that the 7 novel cell lines with low passage maintaining their clinical and pathological characters could be good tools for further exploring the molecular mechanism of HCC and anti-cancer drug screening.

Fit-for purpose use of mouse models to improve predictivity of cancer therapeutics evaluation

Preclinical animal models are useful tools to better understand tumor initiation and progression and to predict the activity of an anticancer agent in the clinic. Ideally, these models should recapitulate the biological characteristics of the tumor and of the related tumor microenvironment (e.g. vasculature, immune cells) in patients. Even if several examples of translational success have been reported it is a matter of fact that clinical trials in oncology often fail to meet their primary endpoints despite encouraging preclinical data. For this reason, there is an increasing need of improved and more predictive models. This review aims to give an overview on existing mouse models for preclinical evaluation of cancer therapeutics and their applicability. Different types of mouse models commonly used for the evaluation of cancer therapeutics are described and considerations for a "fit-for purpose" application of these models for the evaluation of different cancer therapeutics dependent on their mode of action are outlined. Furthermore, considerations for study design and data interpretation to translatability of findings into the clinics are given.

CONCLUSION

Detailed knowledge of the molecular/biological properties of the respective model, diligent experimental setup, and awareness of its limitations are indispensable prerequisites for the successful translational use of animal models.

Masked selection: a straightforward and flexible approach for the selection of binders against specific epitopes and differentially expressed proteins by phage display

Phage display is a well-established procedure to isolate binders against a wide variety of antigens that can be performed on purified antigens, but also on intact cells. As selection steps are performed in vitro, it is possible to focus the outcome of the selection on relevant epitopes by performing some additional steps, such as depletion or competitive elutions. However in practice, the efficiency of these steps is often limited and can lead to inconsistent results. We have designed a new selection method named masked selection, based on the blockade of unwanted epitopes to favor the targeting of relevant ones. We demonstrate the efficiency and flexibility of this method by selecting single-domain antibodies against a specific portion of a fusion protein, by selecting binders against several members of the seven transmembrane receptor family using transfected HEK cells, or by selecting binders against unknown breast cancer markers not expressed on normal samples. The relevance of this approach for antibody-based therapies was further validated by the identification of four of these markers, Epithelial cell adhesion molecule, Transferrin receptor 1, Metastasis cell adhesion molecule, and Sushi containing domain 2, using immunoprecipitation and mass spectrometry. This new phage display strategy can be applied to any type of antibody fragments or alternative scaffolds, and is especially suited for the rapid discovery and identification of cell surface markers.

Development and characterization of a colon PDX model that reproduces drug responsiveness and the mutation profiles of its original tumor

Cultures of primary tumors are very useful as a personalized screening system for effective therapeutic options. We here describe an effective method of reproducing human primary colon tumors through primary culture and a mouse xenograft model. A total of 199 primary colon tumor cultures were successfully established under optimized conditions to enrich for tumor cells and to expand it for long-term storage in liquid nitrogen. To examine whether these stored cultures retained original tumor properties, fifty primary cultures were xenografted into NOD-SCID mouse. Histological and tumor marker analysis of four representative tumor xenografts revealed that all of the xenograft retained its primary tumor characteristics. Oncomap analysis further showed no change in the major mutations in the xenografts, confirming that our method faithfully reproduced human colon tumors. A drug sensitivity assay revealed that two of the primary cultures were hypersensitive to oxaliplatin rather than 5-FU, which was used in the patients, suggesting it as an effective therapeutic option. We thus present an effective, reproducible preclinical model for testing various personalized therapeutic options in colon cancer patients.

ALDH1-positive cancer stem cells predict engraftment of primary breast tumors and are governed by a common stem cell program

Cancer stem-like cells (CSC) have been widely studied, but their clinical relevance has yet to be established in breast cancer. Here, we report the establishment of primary breast tumor-derived xenografts (PDX) that encompass the main diversity of human breast cancer and retain the major clinicopathologic features of primary tumors. Successful engraftment was correlated with the presence of ALDH1-positive CSCs, which predicted prognosis in patients. The xenografts we developed showed a hierarchical cell organization of breast cancer with the ALDH1-positive CSCs constituting the tumorigenic cell population. Analysis of gene expression from functionally validated CSCs yielded a breast CSC signature and identified a core transcriptional program of 19 genes shared with murine embryonic, hematopoietic, and neural stem cells. This generalized stem cell program allowed the identification of potential CSC regulators, which were related mainly to metabolic processes. Using an siRNA genetic screen designed to target the 19 genes, we validated the functional role of this stem cell program in the regulation of breast CSC biology. Our work offers a proof of the functional importance of CSCs in breast cancer, and it establishes the reliability of PDXs for use in developing personalized CSC therapies for patients with breast cancer.