Raising the bar for cancer therapy models

Maternal 129S1/SvImJ background attenuates the placental phenotypes induced by chronic paternal alcohol exposure

Paternal alcohol use is emerging as a plausible driver of alcohol-related growth and patterning defects. Studies from our lab using an inbred C57Bl/6 J mouse model suggest that these paternally-inherited phenotypes result from paternally programmed deficits in the formation and function of the placenta. The 129S1/SvImJ genetic background is typically more susceptible to fetoplacental growth defects due to strain-specific differences in placental morphology. We hypothesized that these placental differences would sensitize 129S1/SvImJ-C57Bl/6 J hybrid offspring to paternally-inherited fetoplacental growth phenotypes induced by paternal alcohol exposure. Using a limited access model, we exposed C57Bl/6 J males to alcohol and bred them to naïve 129S1/SvImJ dams. We then assayed F1 hybrid offspring for alterations in fetoplacental growth and used micro-CT imaging to contrast placental histological patterning between the preconception treatments. F1 hybrid placentae exhibit larger placental weights than pure C57Bl/6 J offspring but display a proportionally smaller junctional zone with increased glycogen content. The male F1 hybrid offspring of alcohol-exposed sires exhibit modest placental hyperplasia but, unlike pure C57Bl/6 J offspring, do not display observable changes in placental histology, glycogen content, or measurable impacts on fetal growth. Although F1 hybrid female offspring do not exhibit any measurable alterations in fetoplacental growth, RT-qPCR analysis of placental gene expression reveals increased expression of genes participating in the antioxidant response. The reduced placental junctional zone but increased glycogen stores of 129S1/SvImJ-C57Bl/6 J F1 hybrid placentae ostensibly attenuate the previously observed placental patterning defects and fetal growth restriction induced by paternal alcohol use in the C57Bl/6 J strain.

Cancer models in preclinical research: A chronicle review of advancement in effective cancer research

Cancer is a major stress for public well-being and is the most dreadful disease. The models used in the discovery of cancer treatment are continuously changing and extending toward advanced preclinical studies. Cancer models are either naturally existing or artificially prepared experimental systems that show similar features with human tumors though the heterogeneous nature of the tumor is very familiar. The choice of the most fitting model to best reflect the given tumor system is one of the real difficulties for cancer examination. Therefore, vast studies have been conducted on the cancer models for developing a better understanding of cancer invasion, progression, and early detection. These models give an insight into cancer etiology, molecular basis, host tumor interaction, the role of microenvironment, and tumor heterogeneity in tumor metastasis. These models are also used to predict novel cancer markers, targeted therapies, and are extremely helpful in drug development. In this review, the potential of cancer models to be used as a platform for drug screening and therapeutic discoveries are highlighted. Although none of the cancer models is regarded as ideal because each is associated with essential caveats that restraint its application yet by bridging the gap between preliminary cancer research and translational medicine. However, they promise a brighter future for cancer treatment.

Preclinical Metrics Correlate With Drug Activity in Phase II Trials of Targeted Therapies for Non-Small Cell Lung Cancer

Novel oncology drugs often fail to progress from preclinical experiments to FDA approval. Therefore, determining which preclinical or clinical factors associate with drug activity could accelerate development of effective therapies. We investigated whether preclinical metrics and patient characteristics are associated with objective response rate (ORR) in phase II clinical trials of targeted therapies for non-small cell lung cancer (NSCLC). We developed a reproducible process to select a single phase II trial and supporting preclinical publication for a given drug-indication pair, which we defined as the pairing of a small molecule inhibitor (e.g., crizotinib) with the specific patient population for which it was designed to work (e.g., patients with an ALK aberration). We demonstrated that robust drug activity in mice, as measured by change in tumor size, is independently associated with improved ORR in phase II clinical trials. The number of mice utilized in experiments, the number of publications referencing the drug for NSCLC before the phase II clinical trial, and whether the drug was approved for a cancer other than NSCLC also significantly correlated with ORR. Among clinical characteristics, sex, race, histology, and smoking history were significantly associated with ORR. Further research into metrics that correlate with drug activity has the potential to optimize selection of novel therapies for clinical trials and enrich the drug development pipeline, particularly for patients with targetable genetic aberrations and rare cancers.

A Novel 4-Gene Score to Predict Survival, Distant Metastasis and Response to Neoadjuvant Therapy in Breast Cancer

We generated a 4-gene score with genes upregulated in LM2-4, a metastatic variant of MDA-MB-231 (DOK 4, HCCS, PGF, and SHCBP1) that was strongly associated with disease-free survival (DFS) in TCGA cohort (hazard ratio [HR]>1.2, p < 0.02). The 4-gene score correlated with overall survival of TCGA (HR = 1.44, p < 0.001), which was validated with DFS and disease-specific survival of METABRIC cohort. The 4-gene score was able to predict worse survival or clinically aggressive tumors, such as high Nottingham pathological grade and advanced cancer staging. High score was associated with worse survival in the hormonal receptor (HR)-positive/Her2-negative subtype. High score enriched cell proliferation-related gene sets in GSEA. The score was high in primary tumors that originated, in and metastasized to, brain and lung, and it predicted worse progression-free survival for metastatic tumors. Good tumor response to neoadjuvant chemotherapy or hormonal therapy was accompanied by score reduction. High scores were also predictive of response to neoadjuvant chemotherapy for HR-positive/Her2-negative subtype. High score tumors had increased expression of T cell exhaustion marker genes, suggesting that the score may also be a biomarker for immunotherapy response. Our novel 4-gene score with both prognostic and predictive values may, therefore, be clinically useful particularly in HR-positive breast cancer.

An ovarian spheroid based tumor model that represents vascularized tumors and enables the investigation of nanomedicine therapeutics

The failure of cancer therapies in clinical settings is often attributed to the lack of a relevant tumor model and pathological heterogeneity across tumor types in the clinic. The objective of this study was to develop a robust in vivo tumor model that better represents clinical tumors for the evaluation of anti-cancer therapies. We successfully developed a simple mouse tumor model based on 3D cell culture by injecting a single spheroid and compared it to a tumor model routinely used by injecting cell suspension from 2D monolayer cell culture. We further characterized both tumors with cellular markers for the presence of myofibroblasts, pericytes, endothelial cells and extracellular matrix to understand the role of the tumor microenvironment. We further investigated the effect of chemotherapy (doxorubicin), nanomedicine (Doxil®), biological therapy (Avastin®) and their combination. Our results showed that the substantial blood vasculature in the 3D spheroid model enhances the delivery of Doxil® by 2.5-fold as compared to the 2D model. Taken together, our data suggest that the 3D tumors created by simple subcutaneous spheroid injection represents a robust and more vascular murine tumor model which is a clinically relevant platform to test anti-cancer therapy in solid tumors.

Application of Computational Biology and Artificial Intelligence Technologies in Cancer Precision Drug Discovery

Artificial intelligence (AI) proves to have enormous potential in many areas of healthcare including research and chemical discoveries. Using large amounts of aggregated data, the AI can discover and learn further transforming these data into "usable" knowledge. Being well aware of this, the world's leading pharmaceutical companies have already begun to use artificial intelligence to improve their research regarding new drugs. The goal is to exploit modern computational biology and machine learning systems to predict the molecular behaviour and the likelihood of getting a useful drug, thus saving time and money on unnecessary tests. Clinical studies, electronic medical records, high-resolution medical images, and genomic profiles can be used as resources to aid drug development. Pharmaceutical and medical researchers have extensive data sets that can be analyzed by strong AI systems. This review focused on how computational biology and artificial intelligence technologies can be implemented by integrating the knowledge of cancer drugs, drug resistance, next-generation sequencing, genetic variants, and structural biology in the cancer precision drug discovery.

11PS04 is a new chemical entity identified by microRNA-based biosensing with promising therapeutic potential against cancer stem cells

Phenotypic drug discovery must take advantage of the large amount of clinical data currently available. In this sense, the impact of microRNAs (miRs) on human disease and clinical therapeutic responses is becoming increasingly well documented. Accordingly, it might be possible to use miR-based signatures as phenotypic read-outs of pathological status, for example in cancer. Here, we propose to use the information accumulating regarding the biology of miRs from clinical research in the preclinical arena, adapting it to the use of miR biosensors in the earliest steps of drug screening. Thus, we have used an amperometric dual magnetosensor capable of monitoring a miR-21/miR-205 signature to screen for new drugs that restore these miRs to non-tumorigenic levels in cell models of breast cancer and glioblastoma. In this way we have been able to identify a new chemical entity, 11PS04 ((3aR,7aS)-2-(3-propoxyphenyl)-7,7a-dihydro-3aH-pyrano[3,4-d]oxazol-6(4H)-one), the therapeutic potential of which was suggested in mechanistic assays of disease models, including 3D cell culture (oncospheres) and xenografts. These assays highlighted the potential of this compound to attack cancer stem cells, reducing the growth of breast and glioblastoma tumors in vivo. These data demonstrate the enhanced chain of translatability of this strategy, opening up new perspectives for drug-discovery pipelines and highlighting the potential of miR-based electro-analytical sensors as efficient tools in modern drug discovery.

Health benefits of resveratrol: Evidence from clinical studies

Resveratrol is a polyphenolic nutraceutical that exhibits pleiotropic activities in human subjects. The efficacy, safety, and pharmacokinetics of resveratrol have been documented in over 244 clinical trials, with an additional 27 clinical trials currently ongoing. Resveretrol is reported to potentially improve the therapeutic outcome in patients suffering from diabetes mellitus, obesity, colorectal cancer, breast cancer, multiple myeloma, metabolic syndrome, hypertension, Alzheimer's disease, stroke, cardiovascular diseases, kidney diseases, inflammatory diseases, and rhinopharyngitis. The polyphenol is reported to be safe at doses up to 5 g/d, when used either alone or as a combination therapy. The molecular basis for the pleiotropic activities of resveratrol are based on its ability to modulate multiple cell signaling molecules such as cytokines, caspases, matrix metalloproteinases, Wnt, nuclear factor-κB, Notch, 5'-AMP-activated protein kinase, intercellular adhesion molecule, vascular cell adhesion molecule, sirtuin type 1, peroxisome proliferator-activated receptor-γ coactivator 1α, insulin-like growth factor 1, insulin-like growth factor-binding protein 3, Ras association domain family 1α, pAkt, vascular endothelial growth factor, cyclooxygenase 2, nuclear factor erythroid 2 like 2, and Kelch-like ECH-associated protein 1. Although the clinical utility of resveratrol is well documented, the rapid metabolism and poor bioavailability have limited its therapeutic use. In this regard, the recently produced micronized resveratrol formulation called SRT501, shows promise. This review discusses the currently available clinical data on resveratrol in the prevention, management, and treatment of various diseases and disorders. Based on the current evidence, the potential utility of this molecule in the clinic is discussed.

Overlooked benefits of using polyclonal antibodies

The benefits of polyclonal antibodies as tools for assay-specific target discovery and detection are numerous. As the future of basic research, diagnostics and biomarker discovery is dependent on high-quality reproducible data, there is a need to understand the importance and benefits of these valuable tools. All antibody forms - polyclonal, hybridoma-based monoclonal and recombinant monoclonal - have pros and cons for development, validation and use. Yet, polyclonal antibodies are embroiled in a firestorm of controversy concerning data reproducibility. We address best practices for developing and using polyclonal antibodies, pitfalls to their use and how to avoid them, and benefits to the life science community. Eliminating their use risks overlooking the unique benefits of polyclonal antibodies as 'fit-for-purpose' life science tools.

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.

Modeling nasopharyngeal carcinoma in three dimensions

Nasopharyngeal carcinoma (NPC) is a type of cancer endemic in Asia, including Malaysia, Southern China, Hong Kong and Taiwan. Treatment resistance, particularly in recurring cases, remains a challenge. Thus, studies to develop novel therapeutic agents are important. Potential therapeutic compounds may be effectively examined using two-dimensional (2D) cell culture models, three-dimensional (3D) spheroid models or in vivo animal models. The majority of drug assessments for cancers, including for NPC, are currently performed with 2D cell culture models. This model offers economical and high-throughput screening advantages. However, 2D cell culture models cannot recapitulate the architecture and the microenvironment of a tumor. In vivo models may recapitulate certain architectural and microenvironmental conditions of a tumor, however, these are not feasible for the screening of large numbers of compounds. By contrast, 3D spheroid models may be able to recapitulate a physiological microenvironment not observed in 2D cell culture models, in addition to avoiding the impediments of in vivo animal models. Thus, the 3D spheroid model offers a more representative model for the study of NPC growth, invasion and drug response, which may be cost-effective without forgoing quality.

De-Risking Immunotherapy: Report of a Consensus Workshop of the Cancer Immunotherapy Consortium of the Cancer Research Institute

With the recent FDA approvals of pembrolizumab and nivolumab, and a host of additional immunomodulatory agents entering clinical development each year, the field of cancer immunotherapy is changing rapidly. Strategies that can assist researchers in choosing the most promising drugs and drug combinations to move forward through clinical development are badly needed in order to reduce the likelihood of late-stage clinical trial failures. On October 5, 2014, the Cancer Immunotherapy Consortium of the Cancer Research Institute, a collaborative think tank composed of stakeholders from academia, industry, regulatory agencies, and patient interest groups, met to discuss strategies for de-risking immunotherapy development, with a focus on integrating preclinical and clinical studies, and conducting smarter early-phase trials, particularly for combination therapies. Several recommendations were made, including making better use of clinical data to inform preclinical research, obtaining adequate tissues for biomarker studies, and choosing appropriate clinical trial endpoints to identify promising drug candidates and combinations in nonrandomized early-phase trials.

Critical evaluation of challenges and future use of animals in experimentation for biomedical research

Animal experiments that are conducted worldwide contribute to significant findings and breakthroughs in the understanding of the underlying mechanisms of various diseases, bringing up appropriate clinical interventions. However, their predictive value is often low, leading to translational failure. Problems like translational failure of animal studies and poorly designed animal experiments lead to loss of animal lives and less translatable data which affect research outcomes ethically and economically. Due to increasing complexities in animal usage with changes in public perception and stringent guidelines, it is becoming difficult to use animals for conducting studies. This review deals with challenges like poor experimental design and ethical concerns and discusses key concepts like sample size, statistics in experimental design, humane endpoints, economic assessment, species difference, housing conditions, and systematic reviews and meta-analyses that are often neglected. If practiced, these strategies can refine the procedures effectively and help translate the outcomes efficiently.

A Decade of Experience in Developing Preclinical Models of Advanced- or Early-Stage Spontaneous Metastasis to Study Antiangiogenic Drugs, Metronomic Chemotherapy, and the Tumor Microenvironment

The clinical circumstance of treating spontaneous metastatic disease, after resection of primary tumors, whether advanced/overt or microscopic in nature, is seldom modeled in mice and may be a major factor in explaining the frequent discordance between preclinical and clinical therapeutic outcomes where the trend is "overprediction" of positive results in preclinical mouse model studies. To evaluate this hypothesis, a research program was initiated a decade ago to develop multiple models of metastasis in mice, using variants of human tumor cell lines selected in vivo for enhanced spontaneous metastatic aggressiveness after surgical resection of established orthotopic primary tumors. These models have included breast, renal, and colorectal carcinomas; ovarian cancer (but without prior surgery); and malignant melanoma. They have been used primarily for experimental therapeutic investigations involving various antiangiogenic drugs alone or with chemotherapy, especially "metronomic" low-dose chemotherapy. The various translational studies undertaken have revealed a number of clinically relevant findings. These include the following: (i) the potential of metronomic chemotherapy, especially when combined with a vascular endothelial growth factor pathway targeting drug to successfully treat advanced metastatic disease; (ii) the development of relapsed spontaneous brain metastases in mice with melanoma or breast cancer whose systemic metastatic disease is successfully controlled for a period with a given therapy; (iii) foreshadowing the failure of adjuvant antiangiogenic drug-based phase III trials; (iv) recapitulating the failure of oral antiangiogenic tyrosine kinase inhibitors plus standard chemotherapy in contrast to the modest successes of antiangiogenic antibodies plus chemotherapy in metastatic breast cancer; and (v) revealing "vessel co-option" and absence of angiogenesis as a determinant of intrinsic resistance or minimal responsiveness to antiangiogenic therapy in lung metastases. Developing similar models of metastatic disease but involving mouse tumors grown in syngeneic immunocompetent mice may also prove useful for future translational studies of immune therapy-based treatments.

Serendipity in Cancer Drug Discovery: Rational or Coincidence?

Novel drug development leading to final approval by the US FDA can cost as much as two billion dollars. Why the cost of novel drug discovery is so expensive is unclear, but high failure rates at the preclinical and clinical stages are major reasons. Although therapies targeting a given cell signaling pathway or a protein have become prominent in drug discovery, such treatments have done little in preventing or treating any disease alone because most chronic diseases have been found to be multigenic. A review of the discovery of numerous drugs currently being used for various diseases including cancer, diabetes, cardiovascular, pulmonary, and autoimmune diseases indicates that serendipity has played a major role in the discovery. In this review we provide evidence that rational drug discovery and targeted therapies have minimal roles in drug discovery, and that serendipity and coincidence have played and continue to play major roles. The primary focus in this review is on cancer-related drug discovery.

Engineered Polymeric Hydrogels for 3D Tissue Models

Polymeric biomaterials are widely used in a wide range of biomedical applications due to their unique properties, such as biocompatibility, multi-tunability and easy fabrication. Specifically, polymeric hydrogel materials are extensively utilized as therapeutic implants and therapeutic vehicles for tissue regeneration and drug delivery systems. Recently, hydrogels have been developed as artificial cellular microenvironments because of the structural and physiological similarity to native extracellular matrices. With recent advances in hydrogel materials, many researchers are creating three-dimensional tissue models using engineered hydrogels and various cell sources, which is a promising platform for tissue regeneration, drug discovery, alternatives to animal models and the study of basic cell biology. In this review, we discuss how polymeric hydrogels are used to create engineered tissue constructs. Specifically, we focus on emerging technologies to generate advanced tissue models that precisely recapitulate complex native tissues in vivo.

An unappreciated challenge to oncology drug discovery: pitfalls in preclinical research

Unfortunately, preclinical research studies frequently suffer from a lack of rigor and robustness that precludes their use as a foundation for a drug-development program. Too often they lack the characteristics that typically are expected in high-quality clinical studies, yet despite that, they are published in top-tier scientific journals. The key attributes that are missing include lack of blinding of investigators, failure to repeat experiments, lack of positive and negative controls, use of nonvalidated reagents, inappropriate use of statistical tests, and data selection (ignoring results that do not fit the hypothesis). Physicians and scientists should view preclinical findings that lack these characteristics with skepticism and should proceed very cautiously in applying such findings to the clinic.

Housing Temperature-Induced Stress Is Suppressing Murine Graft-versus-Host Disease through β2-Adrenergic Receptor Signaling

Graft-versus-host disease (GVHD) is the major complication of allogeneic hematopoietic cell transplantation, a potentially curative therapy for hematologic diseases. It has long been thought that murine bone marrow-derived T cells do not mediate severe GVHD because of their quantity and/or phenotype. During the course of experiments testing the impact of housing temperatures on GVHD, we discovered that this apparent resistance is a function of the relatively cool ambient housing temperature. Murine bone marrow-derived T cells have the ability to mediate severe GVHD in mice housed at a thermoneutral temperature. Specifically, mice housed at Institutional Animal Care and Use Committee-mandated, cool standard temperatures (∼ 22°C) are more resistant to developing GVHD than are mice housed at thermoneutral temperatures (∼ 30°C). We learned that the mechanism underlying this housing-dependent immunosuppression is associated with increased norepinephrine production and excessive signaling through β-adrenergic receptor signaling, which is increased when mice are cold stressed. Treatment of mice housed at 22°C with a β2-adrenergic antagonist reverses the norepinephrine-driven suppression of GVHD and yields similar disease to mice housed at 30°C. Conversely, administering a β2-adrenergic agonist decreases GVHD in mice housed at 30°C. In further mechanistic studies using β2-adrenergic receptor-deficient (β2-AR(-/-)) mice, we found that it is host cell β2-AR signaling that is essential for decreasing GVHD. These data reveal how baseline levels of β-adrenergic receptor signaling can influence murine GVHD and point to the feasibility of manipulation of β2-AR signaling to ameliorate GVHD in the clinical setting.

Preclinical imaging and translational animal models of cancer for accelerated clinical implementation of nanotechnologies and macromolecular agents

The majority of animal models of cancer have performed poorly in terms of predicting clinical performance of new therapeutics, which are most often first evaluated in patients with advanced, metastatic disease. The development and use of metastatic models of cancer may enhance clinical translatability of preclinical studies focused on the development of nanotechnology-based drug delivery systems and macromolecular therapeutics, potentially accelerating their clinical implementation. It is recognized that the development and use of such models are not without challenge. Preclinical imaging tools offer a solution by allowing temporal and spatial characterization of metastatic lesions. This paper provides a review of imaging methods applicable for evaluation of novel therapeutics in clinically relevant models of advanced cancer. An overview of currently utilized models of oncology in small animals is followed by image-based development and characterization of visceral metastatic cancer models. Examples of imaging tools employed for metastatic lesion detection, evaluation of anti-tumor and anti-metastatic potential and biodistribution of novel therapies, as well as the co-development and/or use of imageable surrogates of response, are also discussed. While the focus is on development of macromolecular and nanotechnology-based therapeutics, examples with small molecules are included in some cases to illustrate concepts and approaches that can be applied in the assessment of nanotechnologies or macromolecules.

Biomimetic nanoparticles for siRNA delivery in the treatment of leukaemia

Leukaemia is a bone marrow cancer occurring in acute and chronic subtypes. Acute leukaemia is a rapidly fatal cancer potentially causing death within a few weeks, if untreated. Leukaemia arises as a result of disruption to haematopoietic precursors, caused either by acquired gene fusions, gene mutations or inappropriate expression of the relevant oncogenes. Current treatment options have made significant progress, but the 5 year survival for acute leukaemia remains under 10% in elderly patients, and less than 50% for some types of acute leukaemia in younger adults. For chronic leukaemias longer survival is generally expected and for chronic myeloid leukaemia patients on tyrosine kinase inhibitors the median survival is not yet reached and is expected to exceed 10 years. Chemotherapy and haematopoietic stem cell transplantation (HSCT) for acute leukaemia provide the mainstay of therapy for patients under 65 and both carry significant morbidity and mortality. Alternative and superior therapeutic strategies for acute leukaemias are urgently required. Recent molecular-based knowledge of recurring chromosome rearrangements, in particular translocations and inversions, has resulted in significant advances in understanding the molecular pathogenesis of leukaemia. Identification of a number of unique fusion genes has facilitated the development of highly specific small interfering RNAs (siRNA). Although delivery of siRNA using multifunctional nanoparticles has been investigated to treat solid cancers, the application of this approach to blood cancers is at an early stage. This review describes current treatments for leukaemia and highlights the potential of leukaemic fusion genes as therapeutic targets for RNA interference (RNAi). In addition, the design of biomimetic nanoparticles which are capable of responding to the physiological environment of leukaemia and their potential to advance RNAi therapeutics to the clinic will be critically evaluated.

Poor antibody validation is a challenge in biomedical research: a case study for detection of c-FLIP

Successful translation of findings derived from preclinical studies into effective therapies is critical in biomedical research. Lack of robustness and reproducibility of the preclinical data, due to insufficient number of repeats, inadequate cell-based and mouse models contribute to the poor success rate. Antibodies are widely used in preclinical research, notably to determine the expression of potential therapeutic targets in tissues of interest, including tumors, but also to identify disease and/or treatment response biomarkers. We sought to determine whether the current antibody characterization standards in preclinical research are sufficient to ensure reliability of the data found in peer-reviewed publications. To address this issue, we used detection of the protein c-FLIP, a major factor of resistance to apoptosis, as a proof of concept. Accurate detection of endogenous c-FLIP levels in the preclinical settings is imperative since it is considered as a potential theranostic biomarker. Several sources of c-FLIP antibodies validated by their manufacturer and recommended for western blotting were therefore rigorously tested. We found a wide divergence in immune recognition properties. While these antibodies have been used in many publications, our results show that several of them failed to detect endogenous c-FLIP protein by Western blotting. Our results suggest that antibody validation standards are inadequate, and that systematic use of genetic knockdowns and/or knockouts to establish proof of specificity is critical, even for antibodies previously used in the scientific literature. Because antibodies are fundamental tools in both preclinical and clinical research, ensuring their specificity is crucial.

Influence of the implantation site on the sensitivity of patient pancreatic tumor xenografts to Apo2L/TRAIL therapy

OBJECTIVES

We have previously demonstrated activity of Apo2L/TRAIL against patient pancreatic tumor xenografts. Here, we have examined the influence of the tumor implantation site on therapeutic response of orthotopic tumors and their metastases to Apo2L/TRAIL.

METHODS

Sensitivity of 6 patient pancreatic tumor xenografts to Apo2L/TRAIL was determined in a subcutaneous model. To compare the response of orthotopic tumors, cells from subcutaneous xenografts were injected into the pancreas. Tumor growth was confirmed by histological examination of selected mice, and then treatment was started. When all control mice developed externally palpable tumors, the experiment was terminated, and pancreatic weights compared between control and treated groups. Magnetic resonance imaging was used to quantitate the response of orthotopic and metastatic tumors.

RESULTS

The sensitivity to Apo2L/TRAIL observed in subcutaneous tumors was maintained in orthotopic tumors. Metastatic spread was observed with orthotopic tumor implantation. In an orthotopic model of a sensitive tumor, primary and metastatic tumor burden was significantly reduced, and median survival significantly extended by Apo2L/TRAIL therapy.

CONCLUSIONS

Our data provide evidence that the site of tumor engraftment does not alter the inherent sensitivity of patient xenografts to Apo2L/TRAIL, and these results highlight the potential of Apo2L/TRAIL therapy against primary and metastatic pancreatic cancer.

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.

Drugs for solid cancer: the productivity crisis prompts a rethink

Despite remarkable progress in cancer-drug discovery, the delivery of novel, safe, and sustainably effective products to the clinic has stalled. Using Src as a model, we examine key steps in drug development. The preclinical evidence on the relationship between Src and solid cancer is in sharp contrast with the modest anticancer effect noted in conventional clinical trials. Here, we consider Src inhibitors as an example of a promising drug class directed to invasion and metastasis and identify roadblocks in translation. We question the assumption that a drug-induced tumor shrinkage in preclinical and clinical studies predicts a successful outcome. Our analysis indicates that the key areas requiring attention are related, and include preclinical models (in vitro and mouse models), meaningful clinical trial end points, and an appreciation of the role of metastasis in morbidity and mortality. Current regulations do not reflect the natural history of the disease, and may be unrelated to the key complications: local invasion, metastasis, and the development of resistance. Alignment of preclinical and clinical studies and regulations based on mechanistic trial end points and platforms may help in overcoming these roadblocks. Viewed kaleidoscopically, most elements necessary and sufficient for a novel translational paradigm are in place.

Mouse models for studying angiogenesis and lymphangiogenesis in cancer

The formation of new blood vessels (angiogenesis) is required for the growth of most tumors. The tumor microenvironment also induces lymphangiogenic factors that promote metastatic spread. Anti-angiogenic therapy targets the mechanisms behind the growth of the tumor vasculature. During the past two decades, several strategies targeting blood and lymphatic vessels in tumors have been developed. The blocking of vascular endothelial growth factor (VEGF)/VEGF receptor-2 (VEGFR-2) signaling has proven effective for inhibition of tumor angiogenesis and growth, and inhibitors of VEGF-C/VEGFR-3 involved in lymphangiogenesis have recently entered clinical trials. However, thus far anti-angiogenic treatments have been less effective in humans than predicted on the basis of pre-clinical tests in mice. Intrinsic and induced resistance against anti-angiogenesis occurs in patients, and thus far the clinical benefit of the treatments has been limited to modest improvements in overall survival in selected tumor types. Our current knowledge of tumor angiogenesis is based mainly on experiments performed in tumor-transplanted mice, and it has become evident that these models are not representative of human cancer. For an improved understanding, angiogenesis research needs models that better recapitulate the multistep tumorigenesis of human cancers, from the initial genetic insults in single cells to malignant progression in a proper tissue environment. To improve anti-angiogenic therapies in cancer patients, it is necessary to identify additional molecular targets important for tumor angiogenesis, and to get mechanistic insight into their interactions for eventual combinatorial targeting. The recent development of techniques for manipulating the mammalian genome in a precise and predictable manner has opened up new possibilities for the generation of more reliable models of human cancer that are essential for the testing of new therapeutic strategies. In addition, new imaging modalities that permit visualization of the entire mouse tumor vasculature down to the resolution of single capillaries have been developed in pre-clinical models and will likely benefit clinical imaging.

Strategies for improving the clinical benefit of antiangiogenic drug based therapies for breast cancer

Viewed as a whole, the aggregate outcomes of a number of positive randomized phase III clinical trial results evaluating the VEGF-pathway targeting antiangiogenic drug bevacizumab, with or without concurrent chemotherapy, in metastatic breast cancer patients have been disappointingly modest. In the case of antiangiogenic tyrosine kinase inhibitors (TKIs) the results have been negative. Nevertheless, several findings indicate antiangiogenic drugs, especially bevacizumab, are active and can lead to demonstrable clinical benefit in some patients, thus stimulating research into developing strategies to significantly improve their efficacy and reduce toxicity. Some of these initiatives include: 1) discovery and validation of predictive markers that can prospectively identify patients more likely to benefit from antiangiogenic therapy; 2) recognition that the nature of the chemotherapy partner or backbone can strongly impact outcomes when combined with antiangiogenic drugs such as bevacizumab, and thus developing what may be improved combination chemotherapy partner regimens, e.g. metronomic chemotherapy; 3) evaluating prospectively in more depth whether subtypes of the disease-especially triple negative or inflammatory breast cancer-are more responsive to antiangiogenic therapy than other subtypes; 4) evaluating new agents that inhibit angiogenesis in a VEGF-independent manner and other types of drug that can be effectively combined with antiangiogenics, e.g. c-met inhibitors; 5) uncovering the basis of resistance or relapse/progression on the therapy with antiangiogenic drugs; 6) development of improved predictive preclinical breast cancer models for therapy testing, e.g. treatment of mice with established multi-organ breast cancer metastatic disease or genetically engineered mouse models of breast cancer, or mice bearing patient derived breast cancer tissue xenografts.

Integrating constitutive gene expression and chemoactivity: mining the NCI60 anticancer screen

Studies into the genetic origins of tumor cell chemoactivity pose significant challenges to bioinformatic mining efforts. Connections between measures of gene expression and chemoactivity have the potential to identify clinical biomarkers of compound response, cellular pathways important to efficacy and potential toxicities; all vital to anticancer drug development. An investigation has been conducted that jointly explores tumor-cell constitutive NCI60 gene expression profiles and small-molecule NCI60 growth inhibition chemoactivity profiles, viewed from novel applications of self-organizing maps (SOMs) and pathway-centric analyses of gene expressions, to identify subsets of over- and under-expressed pathway genes that discriminate chemo-sensitive and chemo-insensitive tumor cell types. Linear Discriminant Analysis (LDA) is used to quantify the accuracy of discriminating genes to predict tumor cell chemoactivity. LDA results find 15% higher prediction accuracies, using ∼30% fewer genes, for pathway-derived discriminating genes when compared to genes derived using conventional gene expression-chemoactivity correlations. The proposed pathway-centric data mining procedure was used to derive discriminating genes for ten well-known compounds. Discriminating genes were further evaluated using gene set enrichment analysis (GSEA) to reveal a cellular genetic landscape, comprised of small numbers of key over and under expressed on- and off-target pathway genes, as important for a compound’s tumor cell chemoactivity. Literature-based validations are provided as support for chemo-important pathways derived from this procedure. Qualitatively similar results are found when using gene expression measurements derived from different microarray platforms. The data used in this analysis is available at http://pubchem.ncbi.nlm.nih.gov/andhttp://www.ncbi.nlm.nih.gov/projects/geo (GPL96, GSE32474).

Animal models and conserved processes

BACKGROUND

The concept of conserved processes presents unique opportunities for using nonhuman animal models in biomedical research. However, the concept must be examined in the context that humans and nonhuman animals are evolved, complex, adaptive systems. Given that nonhuman animals are examples of living systems that are differently complex from humans, what does the existence of a conserved gene or process imply for inter-species extrapolation?

METHODS

We surveyed the literature including philosophy of science, biological complexity, conserved processes, evolutionary biology, comparative medicine, anti-neoplastic agents, inhalational anesthetics, and drug development journals in order to determine the value of nonhuman animal models when studying conserved processes.

RESULTS

Evolution through natural selection has employed components and processes both to produce the same outcomes among species but also to generate different functions and traits. Many genes and processes are conserved, but new combinations of these processes or different regulation of the genes involved in these processes have resulted in unique organisms. Further, there is a hierarchy of organization in complex living systems. At some levels, the components are simple systems that can be analyzed by mathematics or the physical sciences, while at other levels the system cannot be fully analyzed by reducing it to a physical system. The study of complex living systems must alternate between focusing on the parts and examining the intact whole organism while taking into account the connections between the two. Systems biology aims for this holism. We examined the actions of inhalational anesthetic agents and anti-neoplastic agents in order to address what the characteristics of complex living systems imply for inter-species extrapolation of traits and responses related to conserved processes.

CONCLUSION

We conclude that even the presence of conserved processes is insufficient for inter-species extrapolation when the trait or response being studied is located at higher levels of organization, is in a different module, or is influenced by other modules. However, when the examination of the conserved process occurs at the same level of organization or in the same module, and hence is subject to study solely by reductionism, then extrapolation is possible.

Drug response in a genetically engineered mouse model of multiple myeloma is predictive of clinical efficacy

The attrition rate for anticancer drugs entering clinical trials is unacceptably high. For multiple myeloma (MM), we postulate that this is because of preclinical models that overemphasize the antiproliferative activity of drugs, and clinical trials performed in refractory end-stage patients. We validate the Vk*MYC transgenic mouse as a faithful model to predict single-agent drug activity in MM with a positive predictive value of 67% (4 of 6) for clinical activity, and a negative predictive value of 86% (6 of 7) for clinical inactivity. We identify 4 novel agents that should be prioritized for evaluation in clinical trials. Transplantation of Vk*MYC tumor cells into congenic mice selected for a more aggressive disease that models end-stage drug-resistant MM and responds only to combinations of drugs with single-agent activity in untreated Vk*MYC MM. We predict that combinations of standard agents, histone deacetylase inhibitors, bromodomain inhibitors, and hypoxia-activated prodrugs will demonstrate efficacy in the treatment of relapsed MM.

Antiangiogenic therapy: impact on invasion, disease progression, and metastasis

Antiangiogenic drugs targeting the VEGF pathway have slowed metastatic disease progression in some patients, leading to progression-free survival (PFS) and overall survival benefits compared with controls. However, the results are more modest than predicted by most preclinical testing and benefits in PFS are frequently not accompanied by overall survival improvements. Questions have emerged about the basis of drug resistance and the limitations of predictive preclinical models, and also about whether the nature of disease progression following antiangiogenic therapy is different to classic cytotoxic therapies-in particular whether therapy may lead to more invasive or metastatic behavior. In addition, because of recent clinical trial failures of antiangiogenic therapy in patients with early-stage disease, and the fact that there are hundreds of trials underway in perioperative neoadjuvant and adjuvant settings, there is now greater awareness about the lack of appropriate preclinical testing that preceded these studies. Improved preclinical assessment of all stages of metastatic disease should be a priority for future antiangiogenic drug discovery and development.

Mouse models of advanced spontaneous metastasis for experimental therapeutics

An enduring problem in cancer research is the failure to reproduce highly encouraging preclinical therapeutic findings using transplanted or spontaneous primary tumours in mice in clinical trials of patients with advanced metastatic disease. There are several reasons for this, including the failure to model established, visceral metastatic disease. We therefore developed various models of aggressive multi-organ spontaneous metastasis after surgical resection of orthotopically transplanted human tumour xenografts. In this Opinion article we provide a personal perspective summarizing the prospect of their increased clinical relevance. This includes the reduced efficacy of certain targeted anticancer drugs, the late emergence of spontaneous brain metastases and the clinical trial results evaluating a highly effective therapeutic strategy previously tested using such models.

Intratumoral mediated immunosuppression is prognostic in genetically engineered murine models of glioma and correlates to immunotherapeutic responses

PURPOSE

Preclinical murine model systems used for the assessment of therapeutics have not been predictive of human clinical responses, primarily because their clonotypic nature does not recapitulate the heterogeneous biology and immunosuppressive mechanisms of humans. Relevant model systems with mice that are immunologically competent are needed to evaluate the efficacy of therapeutic agents, especially immunotherapeutics.

EXPERIMENTAL DESIGN

Using the RCAS/Ntv-a system, mice were engineered to coexpress platelet-derived growth factor B (PDGF-B) receptor + B-cell lymphoma 2 (Bcl-2) under the control of the glioneuronal specific Nestin promoter. The degree and type of tumor-mediated immunosuppression were determined in these endogenously arising gliomas on the basis of the presence of macrophages and regulatory T cells. The immunotherapeutic agent WP1066 was tested in vivo to assess therapeutic efficacy and immunomodulation.

RESULTS

Ntv-a mice were injected with RCAS vectors to express PDGF-B + Bcl-2, resulting in both low- and high-grade gliomas. Consistent with observations in human high-grade gliomas, mice with high-grade gliomas also developed a marked intratumoral influx of macrophages that was influenced by tumor signal transducer and activator of transduction 3 (STAT3) expression. The presence of intratumoral F4/80 macrophages was a negative prognosticator for long-term survival. In mice coexpressing PDGF-B + Bcl-2that were treated with WP1066, there was 55.5% increase in median survival time (P < 0.01), with an associated inhibition of intratumoral STAT3 and macrophages.

CONCLUSIONS

Although randomization is necessary for including mice in a therapeutic trial, these murine model systems are more suitable for testing therapeutics, especially immunotherapeutics, in the context of translational studies.