Integrating pharmacology and in vivo cancer models in preclinical and clinical drug development

Biochemical hallmarks-targeting antineoplastic nanotherapeutics

Tumor microenvironments (TMEs) have received increasing attention in recent years as they play pivotal roles in tumorigenesis, progression, metastases, and resistance to the traditional modalities of cancer therapy like chemotherapy. With the rapid development of nanotechnology, effective antineoplastic nanotherapeutics targeting the aberrant hallmarks of TMEs have been proposed. The appropriate design and fabrication endow nanomedicines with the abilities for active targeting, TMEs-responsiveness, and optimization of physicochemical properties of tumors, thereby overcoming transport barriers and significantly improving antineoplastic therapeutic benefits. This review begins with the origins and characteristics of TMEs and discusses the latest strategies for modulating the TMEs by focusing on the regulation of biochemical microenvironments, such as tumor acidosis, hypoxia, and dysregulated metabolism. Finally, this review summarizes the challenges in the development of smart anti-cancer nanotherapeutics for TME modulation and examines the promising strategies for combination therapies with traditional treatments for further clinical translation.

Synergistic Antitumor Activity of Talazoparib and Temozolomide in Malignant Rhabdoid Tumors

Malignant rhabdoid tumors (MRTs) are among the most aggressive and treatment-resistant malignancies affecting infants, originating in the kidney, brain, liver, and soft tissues. The 5-year event-free survival rate for these cancers is a mere 20%. In nearly all cases of MRT, the SMARCB1 gene (occasionally SMARCA4)-a pivotal component of the SWI/SNF chromatin remodeling complex-is homozygously deleted, although the precise etiology of these tumors remains unknown. While young patients with localized MRT generally show improved outcomes, especially those who are older and have early-stage disease, the overall prognosis remains poor despite optimal standard treatments. This highlights the urgent need for more effective treatment strategies. We investigated the antitumor activity of a PARP1 inhibitor (talazoparib, TLZ) combined with a DNA alkylating agent (temozolomide, TMZ) in MRT xenograft models. PARP1 is a widely targeted molecule in cancer treatment and, beyond its role in DNA repair, it participates in transcriptional regulation by recruiting chromatin remodeling complexes to modulate DNA accessibility for RNA polymerases. To widen the therapeutic window of the drug combination, we employed PEGylated TLZ (PEG~TLZ), which has been reported to reduce systemic toxicity through slow drug release. Remarkably, our findings indicate that five out of six MRT xenografts exhibited an objective response to PEG~TLZ+TMZ therapy. Significantly, the loss of SMARCB1 was found to confer a protective effect, correlating with higher expression levels of DNA damage and repair proteins in SMARCB1-deficient MRT cells. Additionally, we identified MGMT as a potential biomarker indicative of in vivo MRT response to PEG~TLZ+TMZ therapy. Moreover, our analysis revealed alterations in signaling pathways associated with the observed antitumor efficacy. This study presents a novel and efficacious therapeutic approach for MRT, along with a promising candidate biomarker for predicting tumor response.

A PKPD Case Study: Achieving Clinically Relevant Exposures of AZD5991 in Oncology Mouse Models

Capturing human equivalent drug exposures preclinically is a key challenge in the translational process. Motivated by the need to recapitulate the pharmacokinetic (PK) profile of the clinical stage Mcl-1 inhibitor AZD5991 in mice, we describe the methodology used to develop a refined mathematical model relating clinically relevant concentration profiles to efficacy. Administration routes were explored to achieve target exposures matching the clinical exposure of AZD5991. Intravenous infusion using vascular access button (VAB) technology was found to best reproduce clinical target exposures of AZD5991 in mice. Exposure-efficacy relationships were evaluated, demonstrating that dissimilar PK profiles result in differences in target engagement and efficacy outcomes. Thus, these data underscore the importance of accurately ascribing key PK metrics in the translational process to enable clinically meaningful predictions of efficacy.

Multi compartmental 3D breast cancer disease model–recapitulating tumor complexity in in-vitro

Breast cancer is the most common ailment among women. In 2020, it had the highest incidence of any type of cancer. Many Phase II and III anti-cancer drugs fail due to efficacy, durability, and side effects. Thus, accelerated drug screening models must be accurate. In-vivo models have been used for a long time, but delays, inconsistent results, and a greater sense of responsibility among scientists toward wildlife have led to the search for in-vitro alternatives. Stromal components support breast cancer growth and survival. Multi-compartment Transwell models may be handy instruments. Co-culturing breast cancer cells with endothelium and fibroblasts improves modelling. The extracellular matrix (ECM) supports native 3D hydrogels in natural and polymeric forms. 3D Transwell cultured tumor spheroids mimicked in-vivo pathological conditions. Tumor invasion, migration, Trans-endothelial migration, angiogenesis, and spread are studied using comprehensive models. Transwell models can create a cancer niche and conduct high-throughput drug screening, promising future applications. Our comprehensive shows how 3D in-vitro multi compartmental models may be useful in producing breast cancer stroma in Transwell culture.

The predictive capacity of in vitro preclinical models to evaluate drugs for the treatment of retinoblastoma

Retinoblastoma is a rare childhood cancer of the eye. Of the small number of drugs are used to treat retinoblastoma, all have been repurposed from drugs developed for other conditions. In order to find drugs or drug combinations better suited to the improved treatment of retinoblastoma, reliable predictive models are required, which facilitate the challenging transition from in vitro studies to clinical trials. In this review, the research performed to date on the development of 2D and 3D in vitro models for retinoblastoma is presented. Most of this research was undertaken with a view to better biological understanding of retinoblastoma, and we discuss the potential for these models to be applied to drug screening. Future research directions for streamlined drug discovery are considered and evaluated, and many promising avenues identified.

Application status and future prospects of the PDX model in lung cancer

Lung cancer is one of the most prevalent, fatal, and highly heterogeneous diseases that, seriously threaten human health. Lung cancer is primarily caused by the aberrant expression of multiple genes in the cells. Lung cancer treatment options include surgery, radiation, chemotherapy, targeted therapy, and immunotherapy. In recent decades, significant progress has been made in developing therapeutic agents for lung cancer as well as a biomarker for its early diagnosis. Nonetheless, the alternative applications of traditional pre-clinical models (cell line models) for diagnosis and prognosis prediction are constrained by several factors, including the lack of microenvironment components necessary to affect cancer biology and drug response, and the differences between laboratory and clinical results. The leading reason is that substantial shifts accrued to cell biological behaviors, such as cell proliferative, metastatic, invasive, and gene expression capabilities of different cancer cells after decades of growing indefinitely in vitro. Moreover, the introduction of individualized treatment has prompted the development of appropriate experimental models. In recent years, preclinical research on lung cancer has primarily relied on the patient-derived tumor xenograft (PDX) model. The PDX provides stable models with recapitulate characteristics of the parental tumor such as the histopathology and genetic blueprint. Additionally, PDXs offer valuable models for efficacy screening of new cancer drugs, thus, advancing the understanding of tumor biology. Concurrently, with the heightened interest in the PDX models, potential shortcomings have gradually emerged. This review summarizes the significant advantages of PDXs over the previous models, their benefits, potential future uses and interrogating open issues.

The first Japanese biobank of patient-derived pediatric acute lymphoblastic leukemia xenograft models

A lack of practical resources in Japan has limited preclinical discovery and testing of therapies for pediatric relapsed and refractory acute lymphoblastic leukemia (ALL), which has poor outcomes. Here, we established 57 patient-derived xenografts (PDXs) in NOD.Cg-Prkdc^scid ll2rg^tm1Sug /ShiJic (NOG) mice and created a biobank by preserving PDX cells including 3 extramedullary relapsed ALL PDXs. We demonstrated that our PDX mice and PDX cells mimicked the biological features of relapsed ALL and that PDX models reproduced treatment-mediated clonal selection. Our PDX biobank is a useful scientific resource for capturing drug sensitivity features of pediatric patients with ALL, providing an essential tool for the development of targeted therapies.

Targeting pancreatic cancer with combinatorial treatment of CPI-613 and inhibitors of lactate metabolism

Pancreatic cancer is the fourth leading cause of cancer death, with a 5-year survival rate of 10%. A stagnant high mortality rate over the last decades highlights the need for innovative therapeutic approaches. Pancreatic tumors pursue an altered metabolism in order to maintain energy generation under low nutrient influx and hypoxic conditions. Targeting these metabolic strategies might therefore be a reasonable therapeutic approach for pancreatic cancer. One promising agent is CPI- 613, a potent inhibitor of two enzymes of the tricarboxylic acid cycle. The present study evaluated the anti-cancerous efficacy of CPI-613 in combination with galloflavin, a lactate dehydrogenase inhibitor or with alpha-cyano-4-hydroxycinnamic acid, an inhibitor of monocarboxylate transporters. The efficacy of both combination therapies was tested in vitro on one human and two murine pancreatic cancer cell lines and in vivo in an orthotopic pancreatic cancer model. Tumor progression was evaluated by MRI and 18F-FDG PET-CT. Both combinatorial treatments demonstrated in vitro a significant inhibition of pancreatic cancer cell proliferation and induction of cell death. In contrast to the in vitro results, both combination therapies did not significantly reduce tumor growth in vivo. The in vitro results suggest that a combined inhibition of different metabolic pathways might be a promising approach for cancer therapy. However, the in vivo experiments indicate that applying a higher dosage or using other drugs targeting these metabolic pathways might be more promising.

Nanocarriers Call the Last Shot in the Treatment of Brain Cancers

Our brain is protected by physio-biological barriers. The blood–brain barrier (BBB) main mechanism of protection relates to the abundance of tight junctions (TJs) and efflux pumps. Although BBB is crucial for healthy brain protection against toxins, it also leads to failure in a devastating disease like brain cancer. Recently, nanocarriers have been shown to pass through the BBB and improve patients’ survival rates, thus becoming promising treatment strategies. Among nanocarriers, inorganic nanocarriers, solid lipid nanoparticles, liposomes, polymers, micelles, and dendrimers have reached clinical trials after delivering promising results in preclinical investigations. The size of these nanocarriers is between 10 and 1000 nm and is modified by surface attachment of proteins, peptides, antibodies, or surfactants. Multiple research groups have reported transcellular entrance as the main mechanism allowing for these nanocarriers to cross BBB. Transport proteins and transcellular lipophilic pathways exist in BBB for small and lipophilic molecules. Nanocarriers cannot enter via the paracellular route, which is limited to water-soluble agents due to the TJs and their small pore size. There are currently several nanocarriers in clinical trials for the treatment of brain cancer. This article reviews challenges as well as fitting attributes of nanocarriers for brain tumor treatment in preclinical and clinical studies.

Restoring Tumour Selectivity of the Bioreductive Prodrug PR-104 by Developing an Analogue Resistant to Aerobic Metabolism by Human Aldo-Keto Reductase 1C3

PR-104 is a phosphate ester pre-prodrug that is converted in vivo to its cognate alcohol, PR-104A, a latent alkylator which forms potent cytotoxins upon bioreduction. Hypoxia selectivity results from one-electron nitro reduction of PR-104A, in which cytochrome P450 oxidoreductase (POR) plays an important role. However, PR-104A also undergoes ‘off-target’ two-electron reduction by human aldo-keto reductase 1C3 (AKR1C3), resulting in activation in oxygenated tissues. AKR1C3 expression in human myeloid progenitor cells probably accounts for the dose-limiting myelotoxicity of PR-104 documented in clinical trials, resulting in human PR-104A plasma exposure levels 3.4- to 9.6-fold lower than can be achieved in murine models. Structure-based design to eliminate AKR1C3 activation thus represents a strategy for restoring the therapeutic window of this class of agent in humans. Here, we identified SN29176, a PR-104A analogue resistant to human AKR1C3 activation. SN29176 retains hypoxia selectivity in vitro with aerobic/hypoxic IC50 ratios of 9 to 145, remains a substrate for POR and triggers γH2AX induction and cell cycle arrest in a comparable manner to PR-104A. SN35141, the soluble phosphate pre-prodrug of SN29176, exhibited superior hypoxic tumour log cell kill (>4.0) to PR-104 (2.5–3.7) in vivo at doses predicted to be achievable in humans. Orthologues of human AKR1C3 from mouse, rat and dog were incapable of reducing PR-104A, thus identifying an underlying cause for the discrepancy in PR-104 tolerance in pre-clinical models versus humans. In contrast, the macaque AKR1C3 gene orthologue was able to metabolise PR-104A, indicating that this species may be suitable for evaluating the toxicokinetics of PR-104 analogues for clinical development. We confirmed that SN29176 was not a substrate for AKR1C3 orthologues across all four pre-clinical species, demonstrating that this prodrug analogue class is suitable for further development. Based on these findings, a prodrug candidate was subsequently identified for clinical trials.

Nanotechnology Addressing Cutaneous Melanoma: The Italian Landscape

Cutaneous melanoma is one of the most aggressive solid tumors, with a low survival for the metastatic stage. Currently, clinical melanoma treatments include surgery, chemotherapy, targeted therapy, immunotherapy and radiotherapy. Of note, innovative therapeutic regimens concern the administration of multitarget drugs in tandem, in order to improve therapeutic efficacy. However, also, if this drug combination is clinically relevant, the patient's response is not yet optimal. In this scenario, nanotechnology-based delivery systems can play a crucial role in the clinical treatment of advanced melanoma. In fact, their nano-features enable targeted drug delivery at a cellular level by overcoming biological barriers. Various nanomedicines have been proposed for the treatment of cutaneous melanoma, and a relevant number of them are undergoing clinical trials. In Italy, researchers are focusing on the pharmaceutical development of nanoformulations for malignant melanoma therapy. The present review reports an overview of the main melanoma-addressed nanomedicines currently under study in Italy, alongside the state of the art of melanoma therapy. Moreover, the latest Italian advances concerning the pre-clinical evaluation of nanomedicines for melanoma are described.

Translating complexity and heterogeneity of pancreatic tumor: 3D in vitro to in vivo models

Pancreatic ductal adenocarcinoma (PDAC) is an extremely aggressive type of cancer with an overall survival rate of less than 7-8%, emphasizing the need for novel effective therapeutics against PDAC. However only a fraction of therapeutics which seemed promising in the laboratory environment will eventually reach the clinic. One of the main reasons behind this low success rate is the complex tumor microenvironment (TME) of PDAC, a highly fibrotic and dense stroma surrounding tumor cells, which supports tumor progression as well as increases the resistance against the treatment. In particular, the growing understanding of the PDAC TME points out a different challenge in the development of efficient therapeutics - a lack of biologically relevant in vitro and in vivo models that resemble the complexity and heterogeneity of PDAC observed in patients. The purpose and scope of this review is to provide an overview of the recent developments in different in vitro and in vivo models, which aim to recapitulate the complexity of PDAC in a laboratory environment, as well to describe how 3D in vitro models can be integrated into drug development pipelines that are already including sophisticated in vivo models. Hereby a special focus will be given on the complexity of in vivo models and the challenges in vitro models face to reach the same levels of complexity in a controllable manner. First, a brief introduction of novel developments in two dimensional (2D) models and ex vivo models is provided. Next, recent developments in three dimensional (3D) in vitro models are described ranging from spheroids, organoids, scaffold models, bioprinted models to organ-on-chip models including a discussion on advantages and limitations for each model. Furthermore, we will provide a detailed overview on the current PDAC in vivo models including chemically-induced models, syngeneic and xenogeneic models, highlighting hetero- and orthotopic, patient-derived tissues (PDX) models, and genetically engineered mouse models. Finally, we will provide a discussion on overall limitations of both, in vitro and in vivo models, and discuss necessary steps to overcome these limitations to reach an efficient drug development pipeline, as well as discuss possibilities to include novel in silico models in the process.

Inter-Metastatic Heterogeneity of Tumor Marker Expression and Microenvironment Architecture in a Preclinical Cancer Model

BACKGROUND

Preclinical drug development studies rarely consider the impact of a candidate drug on established metastatic disease. This may explain why agents that are successful in subcutaneous and even orthotopic preclinical models often fail to demonstrate efficacy in clinical trials. It is reasonable to anticipate that sites of metastasis will be phenotypically unique, as each tumor will have evolved heterogeneously with respect to gene expression as well as the associated phenotypic outcome of that expression. The objective for the studies described here was to gain an understanding of the tumor heterogeneity that exists in established metastatic disease and use this information to define a preclinical model that is more predictive of treatment outcome when testing novel drug candidates clinically.

METHODS

Female NCr nude mice were inoculated with fluorescent (mKate), Her2/neu-positive human breast cancer cells (JIMT-mKate), either in the mammary fat pad (orthotopic; OT) to replicate a primary tumor, or directly into the left ventricle (intracardiac; IC), where cells eventually localize in multiple sites to create a model of established metastasis. Tumor development was monitored by in vivo fluorescence imaging (IVFI). Subsequently, animals were sacrificed, and tumor tissues were isolated and imaged ex vivo. Tumors within organ tissues were further analyzed via multiplex immunohistochemistry (mIHC) for Her2/neu expression, blood vessels (CD31), as well as a nuclear marker (Hoechst) and fluorescence (mKate) expressed by the tumor cells.

RESULTS

Following IC injection, JIMT-1mKate cells consistently formed tumors in the lung, liver, brain, kidney, ovaries, and adrenal glands. Disseminated tumors were highly variable when assessing vessel density (CD31) and tumor marker expression (mkate, Her2/neu). Interestingly, tumors which developed within an organ did not adopt a vessel microarchitecture that mimicked the organ where growth occurred, nor did the vessel microarchitecture appear comparable to the primary tumor. Rather, metastatic lesions showed considerable variability, suggesting that each secondary tumor is a distinct disease entity from a microenvironmental perspective.

CONCLUSIONS

The data indicate that more phenotypic heterogeneity in the tumor microenvironment exists in models of metastatic disease than has been previously appreciated, and this heterogeneity may better reflect the metastatic cancer in patients typically enrolled in early-stage Phase I/II clinical trials. Similar to the suggestion of others in the past, the use of models of established metastasis preclinically should be required as part of the anticancer drug candidate development process, and this may be particularly important for targeted therapeutics and/or nanotherapeutics.

Poor outcome with anti-programmed death-ligand 1 (PD-L1) antibody due to poor pharmacokinetic properties in PD-1/PD-L1 blockade-sensitive mouse models

Background

Recently, antiprogrammed cell death protein 1 (aPD-1) and antiprogrammed death-ligand 1 (aPD-L1) monoclonal antibodies (mAbs) have been approved. Even though aPD-1 and aPD-L1 mAbs target the same PD-1/PD-L1 axis, it is still unclear whether both mAbs exert equivalent pharmacological activity in patients who are sensitive to PD-1/PD-L1 blockade therapy, as there is no direct comparison of their pharmacokinetics (PK) and antitumor effects. Therefore, we evaluated the differences between both mAbs in PK and therapeutic effects in PD-1/PD-L1 blockade-sensitive mouse models.

Methods

Herein, murine breast MM48 and colon MC38 xenografts were used to analyze the pharmacological activity of aPD-1 and aPD-L1 mAbs. The PK of the mAbs in the tumor-bearing mice was investigated at low and high doses using two radioisotopes (Indium-111 and Iodine-125) to evaluate the accumulation and degradation of the mAbs.

Results

aPD-1 mAb showed antitumor effect in a dose-dependent manner, indicating that the tumor model was sensitive to PD-1/PD-L1 blockade therapy, whereas aPD-L1 mAb failed to suppress tumor growth. The PK study showed that aPD-L1 mAb was accumulated largely in normal organs such as the spleen, liver, and kidney, resulting in low blood concentration and low distributions to tumors at a low dose, even though the tumors expressed PD-L1. Sufficient accumulation of aPD-L1 mAb in tumors was achieved by administration at a high dose owing to the saturation of target-mediated binding in healthy organs. However, degradation of aPD-L1 mAb in tumors was greater than that of aPD-1 mAb, which resulted in poor outcome presumably due to less inhibition of PD-L1 by aPD-L1 mAb than that of PD-1 by aPD-1 mAb.

Conclusion

According to the PK studies, aPD-1 mAb showed linear PK, whereas aPD-L1 mAb showed non-linear PK between low and high doses. Collectively, the poor PK characteristics of aPD-L1 mAb caused lower antitumor activity than of aPD-1 mAb. These results clearly indicated that aPD-L1 mAb required higher doses than aPD-1 mAb in clinical setting. Thus, targeting of PD-1 would be more advantageous than PD-L1 in terms of PK.

Patient-Derived Cancer Organoids for Precision Oncology Treatment

The emergence of three-dimensional human organoids has opened the door for the development of patient-derived cancer organoid (PDO) models, which closely recapitulate parental tumor tissue. The mainstays of preclinical cancer modeling include in vitro cell lines and patient-derived xenografts, but these models lack the cellular heterogeneity seen in human tumors. Moreover, xenograft establishment is resource and time intensive, rendering these models difficult to use to inform clinical trials and decisions. PDOs, however, can be created efficiently and retain tumor-specific properties such as cellular heterogeneity, cell-cell and cell-stroma interactions, the tumor microenvironment, and therapeutic responsiveness. PDO models and drug-screening protocols have been described for several solid tumors and, more recently, for gliomas. Since PDOs can be developed in clinically relevant time frames and share many characteristics of parent tumors, they may enhance the ability to provide precision oncologic care for patients. This review explores the current literature on cancer organoids, highlighting the history of PDO development, organoid models of glioma, and potential clinical applications of PDOs.

Developing New Agents for Treatment of Childhood Cancer: Challenges and Opportunities for Preclinical Testing

Developing new therapeutics for the treatment of childhood cancer has challenges not usually associated with adult malignancies. Firstly, childhood cancer is rare, with approximately 12,500 new diagnoses annually in the U.S. in children 18 years or younger. With current multimodality treatments, the 5-year event-free survival exceeds 80%, and 70% of patients achieve long-term “cure”, hence the overall number of patients eligible for experimental drugs is small. Childhood cancer comprises many disease entities, the most frequent being acute lymphoblastic leukemias (25% of cancers) and brain tumors (21%), and each of these comprises multiple molecular subtypes. Hence, the numbers of diagnoses even for the more frequently occurring cancers of childhood are small, and undertaking clinical trials remains a significant challenge. Consequently, development of preclinical models that accurately represent each molecular entity can be valuable in identifying those agents or combinations that warrant clinical evaluation. Further, new regulations under the Research to Accelerate Cures and Equity for Children Act (RACE For Children Act) will change the way in which drugs are developed. Here, we will consider some of the limitations of preclinical models and consider approaches that may improve their ability to translate therapy to clinical trial more accurately.

PCAT: an integrated portal for genomic and preclinical testing data of pediatric cancer patient-derived xenograft models

Although cancer is the leading cause of disease-related mortality in children, the relative rarity of pediatric cancers poses a significant challenge for developing novel therapeutics to further improve prognosis. Patient-derived xenograft (PDX) models, which are usually developed from high-risk tumors, are a useful platform to study molecular driver events, identify biomarkers and prioritize therapeutic agents. Here, we develop PDX for Childhood Cancer Therapeutics (PCAT), a new integrated portal for pediatric cancer PDX models. Distinct from previously reported PDX portals, PCAT is focused on pediatric cancer models and provides intuitive interfaces for querying and data mining. The current release comprises 324 models and their associated clinical and genomic data, including gene expression, mutation and copy number alteration. Importantly, PCAT curates preclinical testing results for 68 models and 79 therapeutic agents manually collected from individual agent testing studies published since 2008. To facilitate comparisons of patterns between patient tumors and PDX models, PCAT curates clinical and molecular data of patient tumors from the TARGET project. In addition, PCAT provides access to gene fusions identified in nearly 1000 TARGET samples. PCAT was built using R-shiny and MySQL. The portal can be accessed at http://pcat.zhenglab.info or http://www.pedtranscriptome.org.

Modeling human pancreatic ductal adenocarcinoma for translational research: current options, challenges, and prospective directions

Pancreatic ductal adenocarcinoma (PDAC) is a devastating malignancy with one of the lowest survival rates. Early detection, an improved understanding of tumor biology, and novel therapeutic discoveries are needed in order to improve overall patient survival. Scientific progress towards meeting these goals relies upon accurate modeling of the human disease. From two-dimensional (2D) cell lines to the advanced modeling available today, we aim to characterize the critical tools in efforts to further understand PDAC biology. The National Center for Biotechnology Information's PubMed and the Elsevier's SCOPUS were used to perform a comprehensive literature review evaluating preclinical human-derived PDAC models. Keywords included pancreatic cancer, PDAC, preclinical models, KRAS mutations, xenograft, co-culturing fibroblasts, co-culturing lymphocytes and PDAC immunotherapy Initial search was limited to articles about PDAC and was then expanded to include other gastrointestinal malignancies where information may complement our effort. A supervised review of the key literature's references was utilized to augment the capture of relevant data. The discovery and refinement of techniques enabling immortalized 2D cell culture provided the cornerstone for modern cancer biology research. Cell lines have been widely used to represent PDAC in vitro but are limited in capacity to model three-dimensional (3D) tumor attributes and interactions within the tumor microenvironment. Xenografts are an alternative method to model PDAC with improved capacity to understand certain aspects of 3D tumor biology in vivo while limited by the use of immunodeficient mice. Advances of in vitro modeling techniques have led to 3D organoid models for PDAC biology. Co-culturing models in the 3D environment have been proposed as an efficient modeling system for improving upon the limitations encountered in the standard 2D and xenograft tumor models. The integrated network of cells and stroma that comprise PDAC in vivo need to be accurately depicted ex vivo to continue to make progress in this disease. Recapitulating the complex tumor microenvironment in a preclinical model of human disease is an outstanding and urgent need in PDAC. Definitive characterization of available human models for PDAC serves to further the core mission of pancreatic cancer translational research.

A novel semi-mechanistic tumor growth fraction model for translation of preclinical efficacy of anti-glypican 3 antibody drug conjugate to human

The growing fraction (GF) of tumor has been reported as one of the predictive markers of the efficacy of chemotherapeutics. Therefore, a semi-mechanistic model has been developed that describes tumor growth on the basis of cell cycle, allowing the incorporation of the GF of a tumor in pharmacokinetic/pharmacodynamic (PK/PD) modeling. Efficacy data of anti-glypican 3 (GPC3) antibody drug conjugate (ADC) in a hepatocellular carcinoma (HCC) patient derived xenograft (PDX) model was used for evaluation of this proposed model. Our model was able to describe the kinetics of growth inhibition of HCC PDX models following treatment with anti-GPC3 ADC remarkably well. The estimated tumurostatic concentrations were used in tandem with human PKs translated from cynomolgus monkey for prediction of the efficacious dose. The projected efficacious human dose of anti-GPC3 ADC was in the range 0.20-0.63 mg/kg for the Q3W dosing regimen, with a median dose of 0.50 mg/kg. This publication is the first step in evaluating the applicability of GF in PK/PD modeling of ADCs. The authors are hopeful that incorporation of GF will result in an improved translation of the preclinical efficacy of ADCs to clinical settings and thereby better prediction of the efficacious human dose.

Intrapulmonary inoculation of multicellular spheroids to construct an orthotopic lung cancer xenograft model that mimics four clinical stages of non-small cell lung cancer

INTRODUCTION

Lung cancer leads in mortality among all types of cancer in US and Non-small cell lung cancer (NSCLC) is the major type of lung cancer. Mice models of lung cancer based on subcutaneous or orthotopic inoculation of cancer cell suspension do not adequately mimic the progression of lung cancer in clinic.

METHODS

A549-iRFP cells (human NSCLC adenocarcinoma) were cultured to form multicellular spheroids (MCS), which were then inoculated intrapulmonarily into male athymic nude mice. The xenograft cancer development was monitored by in vivo fluorescent imaging and validated by open-chest anatomy, ex vivo fluorescent imaging, and histological studies.

RESULTS

The newly developed orthotopic xenograft model of lung cancer simulated all four clinical stages of NSCLC progression over one month: Stage 1) localized tumor at the inoculation site, Stage 2) multiple tumor nodules or larger tumor nodule on the same side of the lung, Stage 3) cancer growth on heart surface, and Stage 4) metastatic cancer on both sides of the lung. The model yielded high rates of postoperative survival (100%) and parenchymal tumor establishment (88.9%). The roughness of the inoculated MCS associated negatively with the time needed to develop metastatic cancer (p = .0299).

DISCUSSION

This new orthotopic xenograft model of NSCLC would facilitate the development of medications to treat lung cancer.

Polymer nanoparticle-assisted chemotherapy of pancreatic cancer

Pancreatic cancer is a lethal disease characterized by highly dense stroma fibrosis. Only 15-20% of patients with pancreatic cancer have resectable tumors, and only around 20% of them survive to 5 years. Traditional cancer treatments have little effect on their prognosis, and successful surgical resection combined with effective perioperative therapy is the main method for maximizing long-term survival. For this reason, chemotherapy is an adjunct treatment for resectable cancer and is the main therapy for incurable pancreatic cancer, including metastatic pancreatic adenocarcinoma. However, there are various side effects of chemotherapeutic medicine and low drug penetration because the complex tumor microenvironment limits the application of chemotherapy. As a novel strategy, polymer nanoparticles make it possible to target the tumor microenvironment, release cytotoxic agents through various responsive reactions, and thus overcome the treatment barrier. As drug carriers, polymer nanoparticles show marked advantages, such as increased drug delivery and efficiency, controlled drug release, decreased side effects, prolonged half-life, and evasion of immunogenic blockade. In this review, we discuss the factors that cause chemotherapy obstacles in pancreatic cancer, and introduce the application of polymer nanoparticles to treat pancreatic cancer.

Challenges and Opportunities for Childhood Cancer Drug Development

Cancer in children is rare with approximately 15,700 new cases diagnosed in the United States annually. Through use of multimodality therapy (surgery, radiation therapy, and aggressive chemotherapy), 70% of patients will be "cured" of their disease, and 5-year event-free survival exceeds 80%. However, for patients surviving their malignancy, therapy-related long-term adverse effects are severe, with an estimated 50% having chronic life-threatening toxicities related to therapy in their fourth or fifth decade of life. While overall intensive therapy with cytotoxic agents continues to reduce cancer-related mortality, new understanding of the molecular etiology of many childhood cancers offers an opportunity to redirect efforts to develop effective, less genotoxic therapeutic options, including agents that target oncogenic drivers directly, and the potential for use of agents that target the tumor microenvironment and immune-directed therapies. However, for many high-risk cancers, significant challenges remain.

Electrospun Polylactic Acid (PLLA) Microtube Array Membrane (MTAM)-An Advanced Substrate for Anticancer Drug Screening

The advent of personalized cancer treatment resulted in the shift from the administration of cytotoxic drugs with broad activity spectrum to a targeted tumor-specific therapy. Aligned to this development, the focus of this study revolved around the application of our novel and patented microtube array membrane (MTAM) in the US National Cancer Institute (NCI) developed an HFA (hollow fiber assay) assay; hereinafter known as MTAM/HFA. Electrospun poly-L-lactic acid (PLLA) MTAM was sterilized and loaded with cell lines/patient derived tumor cells (PDTC) and subcutaneously implanted into the backs of BALB/C mice. Anticancer drugs were administered at the respective time points and the respective MTAMs were retrieved and the viability tumor cells within were quantified with the MTT assay. Results revealed that the MTAMs were excellent culture substrate for various cancer cell lines and PDTCs (patient derived tumor cells). Compared to traditional HFA systems that utilize traditional hollow fibers, MTAM/HFA revealed superior drug sensitivity for a wide range of anticancer drug classes. Additionally, the duration for each test was <14 days; all this while capable of producing similar trend outcome to the current gold-standard xenograft models. These benefits were observed in both the in vitro and in vivo stages, making it a highly practical phenotypic-based solution that could potentially be applied in personalized medicine.

Hypoxia-activated prodrugs and (lack of) clinical progress: The need for hypoxia-based biomarker patient selection in phase III clinical trials

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Hypoxia-activated prodrugs have yielded promising results up to phase II trials.

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Implementation of hypoxia-activated prodrugs in the clinic has not been successful.

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Phase III clinical trials lack patient stratification based on tumor hypoxia status.

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Stratification will decrease the number of patients needed and increase success.

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Improvements in hypoxia-activated prodrug design can also increase success rates.

Hypoxia-activated prodrugs (HAPs) are designed to specifically target the hypoxic cells of tumors, which are an important cause of treatment resistance to conventional therapies. Despite promising preclinical and clinical phase I and II results, the most important of which are described in this review, the implementation of hypoxia-activated prodrugs in the clinic has, so far, not been successful. The lack of stratification of patients based on tumor hypoxia status, which can vary widely, is sufficient to account for the failure of phase III trials. To fully exploit the potential of hypoxia-activated prodrugs, hypoxia stratification of patients is needed. Here, we propose a biomarker-stratified enriched Phase III study design in which only biomarker-positive (i.e. hypoxia-positive) patients are randomized between standard treatment and the combination of standard treatment with a hypoxia-activated prodrug. This implies the necessity of a Phase II study in which the biomarker or a combination of biomarkers will be evaluated. The total number of patients needed for both clinical studies will be far lower than in currently used randomize-all designs. In addition, we elaborate on the improvements in HAP design that are feasible to increase the treatment success rates.

Humanized Mouse Models for the Preclinical Assessment of Cancer Immunotherapy

Immunotherapy is one of the most exciting recent breakthroughs in the field of cancer treatment. Many different approaches are being developed and a number have already gained regulatory approval or are under investigation in clinical trials. However, learning from the past, preclinical animal models often insufficiently reflect the physiological situation in humans, which subsequently causes treatment failures in clinical trials. Due to species-specific differences in most parts of the immune system, the transfer of knowledge from preclinical studies to clinical trials is eminently challenging. Human tumor cell line-based or patient-derived xenografts in immunocompromised mice have been successfully applied in the preclinical testing of cytotoxic or molecularly targeted agents, but naturally these systems lack the human immune system counterpart. The co-transplantation of human peripheral blood mononuclear cells or hematopoietic stem cells is employed to overcome this limitation. This review summarizes some important aspects of the different available tumor xenograft mouse models, their history, and their implementation in drug development and personalized therapy. Moreover, recent progress, opportunities and limitations of different humanized mouse models will be discussed.

The Evaluation of Animal Models in the Development of Anticancer Agents: From Preclinical to Clinical Tests

BACKGROUND

One of the main reasons for most of the anticancer drugs to fail in the late preclinical testing and early clinical trials is the differences in drug effects observed from animals and patients, and the challenge has been to find a balance to reduce the inherent differences from species.

OBJECTIVE

Predicting safe starting doses and dosing schedules for human clinical trials is the main purpose of toxicological studies of anticancer drugs.

METHODS

Relevant information and data were assimilated from manuscripts, congress publications, and online sources.

RESULTS

We systematically overview the cons and pros of animal models and briefed the ways to determine human clinical starting doses derived from animal toxicological studies for anticancer drugs.

CONCLUSION

This information helps smart select the suitable predictive model for anti-cancer drugs with the different mechanisms and emphasized the pharmaceutical challenges behind and ahead.

Patient-derived xenografts effectively capture responses to oncology therapy in a heterogeneous cohort of patients with solid tumors

Background

While patient-derived xenografts (PDXs) offer a powerful modality for translational cancer research, a precise evaluation of how accurately patient responses correlate with matching PDXs in a large, heterogeneous population is needed for assessing the utility of this platform for preclinical drug-testing and personalized patient cancer treatment.

Patients and methods

Tumors obtained from surgical or biopsy procedures from 237 cancer patients with a variety of solid tumors were implanted into immunodeficient mice and whole-exome sequencing was carried out. For 92 patients, responses to anticancer therapies were compared with that of their corresponding PDX models.

Results

We compared whole-exome sequencing of 237 PDX models with equivalent information in The Cancer Genome Atlas database, demonstrating that tumorgrafts faithfully conserve genetic patterns of the primary tumors. We next screened PDXs established for 92 patients with various solid cancers against the same 129 treatments that were administered clinically and correlated patient outcomes with the responses in corresponding models. Our analysis demonstrates that PDXs accurately replicate patients' clinical outcomes, even as patients undergo several additional cycles of therapy over time, indicating the capacity of these models to correctly guide an oncologist to treatments that are most likely to be of clinical benefit.

Conclusions

Integration of PDX models as a preclinical platform for assessment of drug efficacy may allow a higher success-rate in critical end points of clinical benefit.

Revisiting colorectal cancer animal model - An improved metastatic model for distal rectosigmoid colon carcinoma

Colorectal cancer (CRC) is the second most frequent and fatal cancer in Western countries. Understanding its biology with different incidence along the colon and rectum, genetic profile and how these factors contribute to local/distant progression, has been hampered by the lack of a suitable CRC model. We report a reproducible model, using human CRC cell lines (CL) (WiDr, LS1034, C2BBe1) injected (1 × 10⁷ cells/animal) in RNU rats (n = 55) which underwent cecostomy and descending colostomy with mucosal-cutaneous fistula of the sigmoid colon. CL were characterized by immunohistochemistry: CK20, CDX2, P53, vimentin, Ki67, CD44, CD133, E-cadherin, β-catenin and CEA; cancer stem cells-immune system interaction was studied and tumor progression was assessed with nuclear medicine imaging (^99mTc-MIBI). Animals developed locally invasive tumors and with WiDr neural invasion was registered. Cancer stem cells were detected in WiDr (CD44 positive). All the cell lines stimulated the immune system, being WiDr the most aggressive. Imaging studies demonstrated tumor uptake. With this CRC model we can study the microenvironment role and tumor-stroma interactions. All CL developed primary disease, but only the WiDR established neural invasion which may represent a metastatic pathway. This model can help unveiling the underlying metastatic mechanisms, and ultimately test better therapeutic approaches for CRC.

Targeting autophagic cancer stem-cells to reverse chemoresistance in human triple negative breast cancer

There is growing evidence for the role of cancer stem-cells in drug resistance, but with few in situ studies on human tumor samples to decipher the mechanisms by which they resist anticancer agents.Triple negative breast cancer (TNBC) is the most severe sub-type of breast cancer, occurring in younger women and associated with poor prognosis even when treated at a localized stage.We investigated here the relationship between complete pathological response after chemotherapy and breast cancer stem-cell characteristics in pre-treatment biopsies of 78 women with triple negative breast carcinoma (TNBC).We found that chemoresistance was associated with large numbers of breast cancer stem-cells, and that these cancer stem-cells were neither proliferative nor apoptotic, but in an autophagic state related to hypoxia. Using relevant pharmacological models of patient-derived TNBC xenografts, we further investigated the role of autophagy in chemoresistance of breast cancer stem-cells. We demonstrated that hypoxia increased drug resistance of autophagic TNBC stem-cells, and showed that molecular or chemical inhibition of autophagic pathway was able to reverse chemoresistance.Our results support breast cancer stem-cell evaluation in pre-treatment biopsies of TNBC patients, and the need for further research on autophagy inhibition to reverse resistance to chemotherapy.

Patient-derived xenografts: A platform for accelerating translational research in prostate cancer

Recently, there has been renewed interest in the development and characterization of patient-derived tumour xenograft (PDX) models. Numerous PDX models have been established for prostate cancer and, importantly, retain the principal molecular, genetic, and histological characteristics of the donor tumour. As such, these models provide significant improvements over standard cell line xenograft models for biological studies, preclinical drug development, and personalized medicine strategies. This review summarizes the current state of the art in this field, illustrating the opportunities and limitations of PDX models in translational prostate cancer research.

Pancreas 3D Organoids: Current and Future Aspects as a Research Platform for Personalized Medicine in Pancreatic Cancer

Pancreatic ductal adenocarcinoma is one of the most aggressive forms of cancer, and the third leading cause of cancer-related mortality in the United States. Although important advances have been made in the last decade, the mortality rate of pancreatic ductal adenocarcinoma has not changed appreciably. This review summarizes a rapidly emerging model of pancreatic cancer research, focusing on 3-dimensional organoids as a powerful tool for several applications, but above all, representing a step toward personalized medicine.

Nanoparticle design strategies for enhanced anticancer therapy by exploiting the tumour microenvironment

Nanovehicles can efficiently carry and deliver anticancer agents to tumour sites. Compared with normal tissue, the tumour microenvironment has some unique properties, such as vascular abnormalities, hypoxia and acidic pH. There are many types of cells, including tumour cells, macrophages, immune and fibroblast cells, fed by defective blood vessels in the solid tumour. Exploiting the tumour microenvironment can benefit the design of nanoparticles for enhanced therapeutic effectiveness. In this review article, we summarized the recent progress in various nanoformulations for cancer therapy, with a special emphasis on tumour microenvironment stimuli-responsive ones. Numerous tumour microenvironment modulation strategies with promising cancer therapeutic efficacy have also been highlighted. Future challenges and opportunities of design consideration are also discussed in detail. We believe that these tumour microenvironment modulation strategies offer a good chance for the practical translation of nanoparticle formulas into clinic.

Application of a PK-PD Modeling and Simulation-Based Strategy for Clinical Translation of Antibody-Drug Conjugates: a Case Study with Trastuzumab Emtansine (T-DM1)

Successful clinical translation of antibody-drug conjugates (ADCs) can be challenging due to complex pharmacokinetics and differences between preclinical and clinical tumors. To facilitate this translation, we have developed a general pharmacokinetic-pharmacodynamic (PK-PD) modeling and simulation (M&S)-based strategy for ADCs. Here we present the validation of this strategy using T-DM1 as a case study. A previously developed preclinical tumor disposition model for T-DM1 (Singh and Shah, AAPSJ. 2015; 18(4):861-875) was used to develop a PK-PD model that can characterize in vivo efficacy of T-DM1 in preclinical tumor models. The preclinical data was used to estimate the efficacy parameters for T-DM1. Human PK of T-DM1 was a priori predicted using allometric scaling of monkey PK parameters. The predicted human PK, preclinically estimated efficacy parameters, and clinically observed volume and growth parameters for breast cancer were combined to develop a translated clinical PK-PD model for T-DM1. Clinical trial simulations were performed using the translated PK-PD model to predict progression-free survival (PFS) and objective response rates (ORRs) for T-DM1. The model simulated PFS rates for HER2 1+ and 3+ populations were comparable to the rates observed in three different clinical trials. The model predicted only a modest improvement in ORR with an increase in clinically approved dose of T-DM1. However, the model suggested that a fractionated dosing regimen (e.g., front loading) may provide an improvement in the efficacy. In general, the PK-PD M&S-based strategy presented here is capable of a priori predicting the clinical efficacy of ADCs, and this strategy has been now retrospectively validated for all clinically approved ADCs.

Clinically Relevant Concentrations of Anticancer Drugs: A Guide for Nonclinical Studies

Approved and marketed drugs are frequently studied in nonclinical models to evaluate the potential application to additional disease indications or to gain insight about molecular mechanisms of action. A survey of the literature reveals that nonclinical experimental designs (in vitro or in vivo) often include evaluation of drug concentrations or doses that are much higher than what can be achieved in patients (i.e., above the maximally tolerated dose or much higher than the clinically relevant exposures). The results obtained with these high concentrations may be particularly helpful in elucidating off-target effects and toxicities, but it is critical to have a dose-response curve that includes the minimally effective or clinically effective concentration for comparison. We have reviewed the clinical literature and drug product labels for all small molecules and biological agents approved by the FDA for use in oncology to identify and compile the available pharmacokinetic parameters. The data summarized here can serve as a guide for selection of in vitro concentrations and in vivo plasma exposures for evaluation of drug effects in nonclinical studies. Inclusion of drug concentrations or exposures that are relevant to those observed in clinical practice can improve translation of nonclinical mechanism of action findings into potentially relevant clinical effects. Clin Cancer Res; 23(14); 3489-98. ©2017 AACR.

Effect of cryopreservation on delineation of immune cell subpopulations in tumor specimens as determinated by multiparametric single cell mass cytometry analysis

Background

Comprehensive understanding of cellular immune subsets involved in regulation of tumor progression is central to the development of cancer immunotherapies. Single cell immunophenotyping has historically been accomplished by flow cytometry (FC) analysis, enabling the analysis of up to 18 markers. Recent advancements in mass cytometry (MC) have facilitated detection of over 50 markers, utilizing high resolving power of mass spectrometry (MS). This study examined an analytical and operational feasibility of MC for an in-depth immunophenotyping analysis of the tumor microenvironment, using the commercial CyTOF™ instrument, and further interrogated challenges in managing the integrity of tumor specimens.

Results

Initial longitudinal studies with frozen peripheral blood mononuclear cells (PBMCs) showed minimal MC inter-assay variability over nine independent runs. In addition, detection of common leukocyte lineage markers using MC and FC detection confirmed that these methodologies are comparable in cell subset identification. An advanced multiparametric MC analysis of 39 total markers enabled a comprehensive evaluation of cell surface marker expression in fresh and cryopreserved tumor samples. This comparative analysis revealed significant reduction of expression levels of multiple markers upon cryopreservation. Most notably myeloid derived suppressor cells (MDSC), defined by co-expression of CD66b⁺ and CD15⁺, HLA-DR^dim and CD14⁻ phenotype, were undetectable in frozen samples.

Conclusion

These results suggest that optimization and evaluation of cryopreservation protocols is necessary for accurate biomarker discovery in frozen tumor specimens.

Electronic supplementary material

The online version of this article (doi:10.1186/s12865-017-0192-1) contains supplementary material, which is available to authorized users.

Patient-Derived Xenograft Models of Non-Small Cell Lung Cancer and Their Potential Utility in Personalized Medicine

Traditional preclinical studies of cancer therapeutics have relied on the use of established human cell lines that have been adapted to grow in the laboratory and, therefore, may deviate from the cancer they were meant to represent. With the emphasis of cancer drug development shifting from non-specific cytotoxic agents to rationally designed molecularly targeted therapies or immunotherapy comes the need for better models with predictive value regarding therapeutic activity and response in clinical trials. Recently, the diversity and accessibility of immunodeficient mouse strains has greatly enhanced the production and utility of patient-derived xenograft (PDX) models for many tumor types, including non-small cell lung cancer (NSCLC). Combined with next-generation sequencing, NSCLC PDX mouse models offer an exciting tool for drug development and for studying targeted therapies while utilizing patient samples with the hope of eventually aiding in clinical decision-making. Here, we describe NSCLC PDX mouse models generated by us and others, their ability to reflect the parental tumors’ histomorphological characteristics, as well as the effect of clonal selection and evolution on maintaining genomic integrity in low-passage PDXs compared to the donor tissue. We also raise vital questions regarding the practical utility of PDX and humanized PDX models in predicting patient response to therapy and make recommendations for addressing those questions. Once collaborations and standardized xenotransplantation and data management methods are established, NSCLC PDX mouse models have the potential to be universal and invaluable as a preclinical tool that guides clinical trials and standard therapeutic decisions.

Radiolabeled bombesin derivatives for preclinical oncological imaging

Despite efforts, cancer is still one of the leading causes of morbidity and mortality worldwide, with approximately 14 million new cases and 8.2 million cancer-related deaths each year, according to the World Health Organization. Among the strategies to reduce cancer progression and improving its management, implementing early detection technologies is crucial. Based on the fact that several types of cancer cells overexpress surface receptors, small molecule ligands, such as peptides, have been developed to allow tumor identification at earlier stages. Allied with imaging techniques such as PET and SPECT, radiolabeled peptides play a pivotal role in nuclear medicine. Bombesin, a peptide of 14 amino acids, is an amphibian homolog to the mammalian gastrin-releasing peptide (GRP), that has been extensively studied as a targeting ligand for diagnosis and therapy of GRP positive tumors, such as breast, pancreas, lungs and prostate cancers. In this context, herein we provide a review of reported bombesin derivatives radiolabeled with a multitude of radioactive isotopes for diagnostic purposes in the preclinical setting. Moreover, since animal models are highly relevant for assessing the potential of clinical translation of this radiopeptides, a brief report of the currently used GRP-positive tumor-bearing animal models is described.

Preclinical and Clinical Assessment of Cannabinoids as Anti-Cancer Agents

Cancer is the second leading cause of death in the United States with 1.7 million new cases estimated to be diagnosed in 2016. This disease remains a formidable clinical challenge and represents a substantial financial burden to the US health care system. Therefore, research and development of novel therapeutics for the treatment of cancer is of high priority. Cannabinoids and their derivatives have been utilized for their medicinal and therapeutic properties throughout history. Cannabinoid activity is regulated by the endocannabinoid system (ECS), which is comprised of cannabinoid receptors, transporters, and enzymes involved in cannabinoid synthesis and breakdown. More recently, cannabinoids have gained special attention for their role in cancer cell proliferation and death. However, many studies investigated these effects using in vitro models which may not adequately mimic tumor growth and metastasis. As such, this article aims to review study results which evaluated effects of cannabinoids from plant, synthetic and endogenous origins on cancer development in preclinical animal models and to examine the current standing of cannabinoids that are being tested in human cancer patients.

Evaluation of Alternative In Vivo Drug Screening Methodology: A Single Mouse Analysis

Traditional approaches to evaluating antitumor agents using human tumor xenograft models have generally used cohorts of 8 to 10 mice against a limited panel of tumor models. An alternative approach is to use fewer animals per tumor line, allowing a greater number of models that capture greater molecular/genetic heterogeneity of the cancer type. We retrospectively analyzed 67 agents evaluated by the Pediatric Preclinical Testing Program to determine whether a single mouse, chosen randomly from each group of a study, predicted the median response for groups of mice using 83 xenograft models. The individual tumor response from a randomly chosen mouse was compared with the group median response using established response criteria. A total of 2,134 comparisons were made. The single tumor response accurately predicted the group median response in 1,604 comparisons (75.16%). The mean tumor response correct prediction rate for 1,000 single mouse random samples was 78.09%. Models had a range for correct prediction (60%-87.5%). Allowing for misprediction of ± one response category, the overall mean correct single mouse prediction rate was 95.28%, and predicted overall objective response rates for group data in 66 of 67 drug studies. For molecularly targeted agents, occasional exceptional responder models were identified and the activity of that agent confirmed in additional models with the same genotype. Assuming that large treatment effects are targeted, this alternate experimental design has similar predictive value as traditional approaches, allowing for far greater numbers of models to be used that more fully encompass the heterogeneity of disease types. Cancer Res; 76(19); 5798-809. ©2016 AACR.

Physiologically-based pharmacokinetic models: approaches for enabling personalized medicine

Personalized medicine strives to deliver the 'right drug at the right dose' by considering inter-person variability, one of the causes for therapeutic failure in specialized populations of patients. Physiologically-based pharmacokinetic (PBPK) modeling is a key tool in the advancement of personalized medicine to evaluate complex clinical scenarios, making use of physiological information as well as physicochemical data to simulate various physiological states to predict the distribution of pharmacokinetic responses. The increased dependency on PBPK models to address regulatory questions is aligned with the ability of PBPK models to minimize ethical and technical difficulties associated with pharmacokinetic and toxicology experiments for special patient populations. Subpopulation modeling can be achieved through an iterative and integrative approach using an adopt, adapt, develop, assess, amend, and deliver methodology. PBPK modeling has two valuable applications in personalized medicine: (1) determining the importance of certain subpopulations within a distribution of pharmacokinetic responses for a given drug formulation and (2) establishing the formulation design space needed to attain a targeted drug plasma concentration profile. This review article focuses on model development for physiological differences associated with sex (male vs. female), age (pediatric vs. young adults vs. elderly), disease state (healthy vs. unhealthy), and temporal variation (influence of biological rhythms), connecting them to drug product formulation development within the quality by design framework. Although PBPK modeling has come a long way, there is still a lengthy road before it can be fully accepted by pharmacologists, clinicians, and the broader industry.

Translational pharmacokinetic/pharmacodynamic analysis in cancer pharmacology: a tool to maximize the value of antitumor efficacy from tumor bearing mice

Translational pharmacokinetic/pharmacodynamic (PK/PD) analysis is becoming an increasingly important tool for the identification and selection of new anticancer agents. There are two important elements of effectively using PK/PD analysis to translate preclinical antitumor efficacy from tumor bearing mice (xenografts and allografts) to cancer patients. These two sometimes overlapping elements are termed translation 'WITHIN' and 'ACROSS' species. Translating 'WITHIN' species refers to the quantitative characterization of drug action and disease behavior within tumor bearing mice using PK/PD modeling in order to use this information to make predictions of drug response in humans. Translating 'ACROSS' species refers to use of PK/PD modeling to quantify species similarities and differences in drug response in order to understand the clinical relevance of preclinical efficacy data.

Identification of Mithramycin Analogues with Improved Targeting of the EWS-FLI1 Transcription Factor

PURPOSE

The goal of this study was to identify second-generation mithramycin analogues that better target the EWS-FLI1 transcription factor for Ewing sarcoma. We previously established mithramycin as an EWS-FLI1 inhibitor, but the compound's toxicity prevented its use at effective concentrations in patients.

EXPERIMENTAL DESIGN

We screened a panel of mithralogs to establish their ability to inhibit EWS-FLI1 in Ewing sarcoma. We compared the IC50 with the MTD established in mice to determine the relationship between efficacy and toxicity. We confirmed the suppression of EWS-FLI1 at the promoter, mRNA, gene signature, and protein levels. We established an improved therapeutic window by using time-lapse microscopy to model the effects on cellular proliferation in Ewing sarcoma cells relative to HepG2 control cells. Finally, we established an improved therapeutic window using a xenograft model of Ewing sarcoma.

RESULTS

EC-8105 was found to be the most potent analogue and was able to suppress EWS-FLI1 activity at concentrations nontoxic to other cell types. EC-8042 was substantially less toxic than mithramycin in multiple species but maintained suppression of EWS-FLI1 at similar concentrations. Both compounds markedly suppressed Ewing sarcoma xenograft growth and inhibited EWS-FLI1 in vivo

CONCLUSIONS

These results provide a basis for the continued development of EC-8042 and EC-8105 as EWS-FLI1 inhibitors for the clinic. Clin Cancer Res; 22(16); 4105-18. ©2016 AACR.

Rational design of an AKR1C3-resistant analog of PR-104 for enzyme-prodrug therapy

The clinical stage anti-cancer agent PR-104 has potential utility as a cytotoxic prodrug for exogenous bacterial nitroreductases expressed from replicating vector platforms. However substrate selectivity is compromised due to metabolism by the human one- and two-electron oxidoreductases cytochrome P450 oxidoreductase (POR) and aldo-keto reductase 1C3 (AKR1C3). Using rational drug design we developed a novel mono-nitro analog of PR-104A that is essentially free of this off-target activity in vitro and in vivo. Unlike PR-104A, there was no biologically relevant cytotoxicity in cells engineered to express AKR1C3 or POR, under aerobic or anoxic conditions, respectively. We screened this inert prodrug analog, SN34507, against a type I bacterial nitroreductase library and identified E. coli NfsA as an efficient bioactivator using a DNA damage response assay and recombinant enzyme kinetics. Expression of E. coli NfsA in human colorectal cancer cells led to selective cytotoxicity to SN34507 that was associated with cell cycle arrest and generated a robust 'bystander effect' at tissue-like cell densities when only 3% of cells were NfsA positive. Anti-tumor activity of SN35539, the phosphate pre-prodrug of SN34507, was established in 'mixed' tumors harboring a minority of NfsA-positive cells and demonstrated marked tumor control following heterogeneous suicide gene expression. These experiments demonstrate that off-target metabolism of PR-104 can be avoided and identify the suicide gene/prodrug partnership of E. coli NfsA/SN35539 as a promising combination for development in armed vectors.

A review of new agents evaluated against pediatric acute lymphoblastic leukemia by the Pediatric Preclinical Testing Program

Acute lymphoblastic leukemia (ALL) in children exemplifies how multi-agent chemotherapy has improved the outcome for patients. Refinements in treatment protocols and improvements in supportive care for this most common pediatric malignancy have led to a cure rate that now approaches 90%. However, certain pediatric ALL subgroups remain relatively intractable to treatment and many patients who relapse face a similarly dismal outcome. Moreover, survivors of pediatric ALL suffer the long-term sequelae of their intensive treatment throughout their lives. Therefore, the development of drugs to treat relapsed/refractory pediatric ALL, as well as those that more specifically target leukemia cells, remains a high priority. As pediatric malignancies represent a minority of the overall cancer burden, it is not surprising that they are generally underrepresented in drug development efforts. The identification of novel therapies relies largely on the reappropriation of drugs developed for adult malignancies. However, despite the large number of experimental agents available, clinical evaluation of novel drugs for pediatric ALL is hindered by limited patient numbers and the availability of effective established drugs. The Pediatric Preclinical Testing Program (PPTP) was established in 2005 to provide a mechanism by which novel therapeutics could be evaluated against xenograft and cell line models of the most common childhood malignancies, including ALL, to prioritize those with the greatest activity for clinical evaluation. In this article, we review the results of >50 novel agents and combinations tested against the PPTP ALL xenografts, highlighting comparisons between PPTP results and clinical data where possible.

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.

Preclinical to Clinical Translation of Antibody-Drug Conjugates Using PK/PD Modeling: a Retrospective Analysis of Inotuzumab Ozogamicin

A mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) model was used for preclinical to clinical translation of inotuzumab ozogamicin, a CD22-targeting antibody-drug conjugate (ADC) for B cell malignancies including non-Hodgkin's lymphoma (NHL) and acute lymphocytic leukemia (ALL). Preclinical data was integrated in a PK/PD model which included (1) a plasma PK model characterizing disposition and clearance of inotuzumab ozogamicin and its released payload N-Ac-γ-calicheamicin DMH, (2) a tumor disposition model describing ADC diffusion into the tumor extracellular environment, (3) a cellular model describing inotuzumab ozogamicin binding to CD22, internalization, intracellular N-Ac-γ-calicheamicin DMH release, binding to DNA, or efflux from the tumor cell, and (4) tumor growth and inhibition in mouse xenograft models. The preclinical model was translated to the clinic by incorporating human PK for inotuzumab ozogamicin and clinically relevant tumor volumes, tumor growth rates, and values for CD22 expression in the relevant patient populations. The resulting stochastic models predicted progression-free survival (PFS) rates for inotuzumab ozogamicin in patients comparable to the observed clinical results. The model suggested that a fractionated dosing regimen is superior to a conventional dosing regimen for ALL but not for NHL. Simulations indicated that tumor growth is a highly sensitive parameter and predictive of successful outcome. Inotuzumab ozogamicin PK and N-Ac-γ-calicheamicin DMH efflux are also sensitive parameters and would be considered more useful predictors of outcome than CD22 receptor expression. In summary, a multiscale, mechanism-based model has been developed for inotuzumab ozogamicin, which can integrate preclinical biomeasures and PK/PD data to predict clinical response.