The Mouse Hospital and Its Integration in Ultra-Precision Approaches to Cancer Care

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

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

In Vivo Models for Prostate Cancer Research

In 2022, prostate cancer (PCa) is estimated to be the most commonly diagnosed cancer in men in the United States-almost 270,000 American men are estimated to be diagnosed with PCa in 2022. This review compares and contrasts in vivo models of PCa with regards to the altered genes, signaling pathways, and stages of tumor progression associated with each model. The main type of model included in this review are genetically engineered mouse models, which include conditional and constitutive knockout model. 2D cell lines, 3D organoids and spheroids, xenografts and allografts, and patient derived models are also included. The major applications, advantages and disadvantages, and ease of use and cost are unique to each type of model, but they all make it easier to translate the tumor progression that is seen in the mouse prostate to the human prostate. Although both human and mouse prostates are androgen-dependent, the fact that the native, genetically unaltered prostate in mice cannot give rise to carcinoma is an especially critical component of PCa models. Thanks to the similarities between the mouse and human genome, our knowledge of PCa has been expanded, and will continue to do so, through models of PCa.

Personalized Treatment of Advanced Gastric Cancer Guided by the MiniPDX Model

Background

The morbidity and mortality of gastric cancer are high in China. There are challenges to develop precise and individualized drug regimens for patients with gastric cancer after a standard treatment. Choosing the most appropriate anticancer drug after a patient developing drug resistance is very important to improve the patient's prognosis. MiniPDX has been widely used as a new and reliable preclinical research model to predict the sensitivity of anticancer drugs.

Methods

The OncoVee® MiniPDX system developed by Shanghai LIDE Biotech Co., Ltd. was used to establish the MiniPDX models using specimens of patients with gastric cancer. The cancer tissues were biopsied under endoscopy, and then, the tumor cell suspension was prepared for a drug sensitivity test by subcutaneously implanting into Balb/c-nude mice. The selected optimal regimen obtained from the MiniPDX assay was used to treat patients with drug-resistant gastric cancer.

Results

We successfully established an individualized and sensitive drug screening system for four patients from January 2021 to July 2021. MiniPDX models identified potentially effective drugs for these four patients, with partial remission in two of the patients after treatment and disease progression in the remaining of two patients. Severe side effects from chemotherapy or targeted therapy were not observed in all patients.

Conclusion

Establishing a personalized drug screening system for patients with drug-resistant gastric cancer can guide the selection of clinical drugs, improve the clinical benefit of patients, and avoid ineffective treatments. It can be an effective supplement for treatment options.

In vivo inducible reverse genetics in patients' tumors to identify individual therapeutic targets

High-throughput sequencing describes multiple alterations in individual tumors, but their functional relevance is often unclear. Clinic-close, individualized molecular model systems are required for functional validation and to identify therapeutic targets of high significance for each patient. Here, we establish a Cre-ER^T2-loxP (causes recombination, estrogen receptor mutant T2, locus of X-over P1) based inducible RNAi- (ribonucleic acid interference) mediated gene silencing system in patient-derived xenograft (PDX) models of acute leukemias in vivo. Mimicking anti-cancer therapy in patients, gene inhibition is initiated in mice harboring orthotopic tumors. In fluorochrome guided, competitive in vivo trials, silencing of the apoptosis regulator MCL1 (myeloid cell leukemia sequence 1) correlates to pharmacological MCL1 inhibition in patients´ tumors, demonstrating the ability of the method to detect therapeutic vulnerabilities. The technique identifies a major tumor-maintaining potency of the MLL-AF4 (mixed lineage leukemia, ALL1-fused gene from chromosome 4) fusion, restricted to samples carrying the translocation. DUX4 (double homeobox 4) plays an essential role in patients’ leukemias carrying the recently described DUX4-IGH (immunoglobulin heavy chain) translocation, while the downstream mediator DDIT4L (DNA-damage-inducible transcript 4 like) is identified as therapeutic vulnerability. By individualizing functional genomics in established tumors in vivo, our technique decisively complements the value chain of precision oncology. Being broadly applicable to tumors of all kinds, it will considerably reinforce personalizing anti-cancer treatment in the future.

Preclinical molecular models are useful that mimic a patient´s response to targeted therapy. Here, the authors establish an in vivo inducible RNAi-mediated gene silencing system in patient-derived xenograft models of acute leukemia to identify individual vulnerabilities and therapeutic targets.

Preclinical evaluation of eltrombopag in a PDX model of myelodysplastic syndromes

Preclinical research of myelodysplastic syndromes (MDSs) is hampered by a lack of feasible disease models. Previously, we have established a robust patient-derived xenograft (PDX) model for MDS. Here we demonstrate for the first time that this model is applicable as a preclinical platform to address pending clinical questions by interrogating the efficacy and safety of the thrombopoietin receptor agonist eltrombopag. Our preclinical study included n = 49 xenografts generated from n = 9 MDS patient samples. Substance efficacy was evidenced by FACS-based human platelet quantification and clonal bone marrow evolution was reconstructed by serial whole-exome sequencing of the PDX samples. In contrast to clinical trials in humans, this experimental setup allowed vehicle- and replicate-controlled analyses on a patient–individual level deciphering substance-specific effects from natural disease progression. We found that eltrombopag effectively stimulated thrombopoiesis in MDS PDX without adversely affecting the patients’ clonal composition. In conclusion, our MDS PDX model is a useful tool for testing new therapeutic concepts in MDS preceding clinical trials.

Current methods in translational cancer research

Recent developments in pre-clinical screening tools, that more reliably predict the clinical effects and adverse events of candidate therapeutic agents, has ushered in a new era of drug development and screening. However, given the rapid pace with which these models have emerged, the individual merits of these translational research tools warrant careful evaluation in order to furnish clinical researchers with appropriate information to conduct pre-clinical screening in an accelerated and rational manner. This review assesses the predictive utility of both well-established and emerging pre-clinical methods in terms of their suitability as a screening platform for treatment response, ability to represent pharmacodynamic and pharmacokinetic drug properties, and lastly debates the translational limitations and benefits of these models. To this end, we will describe the current literature on cell culture, organoids, in vivo mouse models, and in silico computational approaches. Particular focus will be devoted to discussing gaps and unmet needs in the literature as well as current advancements and innovations achieved in the field, such as co-clinical trials and future avenues for refinement.

Mouse avatars of human cancers: the temporality of translation in precision oncology

Patient-derived xenografts (PDXs) are currently promoted as new translational models in precision oncology. PDXs are immunodeficient mice with human tumors that are used as surrogate models to represent specific types of cancer. By accounting for the genetic heterogeneity of cancer tumors, PDXs are hoped to provide more clinically relevant results in preclinical research. Further, in the function of so-called "mouse avatars", PDXs are hoped to allow for patient-specific drug testing in real-time (in parallel to treatment of the corresponding cancer patient). This paper examines the circulation of knowledge and bodily material across the species boundary of human and personalized mouse model, historically as well as in contemporary practices. PDXs raise interesting questions about the relation between animal model and human patient, and about the capacity of hybrid or interspecies models to close existing translational gaps. We highlight that the translational potential of PDXs not only depends on representational matching of model and target, but also on temporal alignment between model development and practical uses. Aside from the importance of ensuring temporal stability of human tumors in a murine body, the mouse avatar concept rests on the possibility of aligning the temporal horizons of the clinic and the lab. We examine strategies to address temporal challenges, including cryopreservation and biobanking, as well as attempts to speed up translation through modification and use of faster developing organisms. We discuss how featured model virtues change with precision oncology, and contend that temporality is a model feature that deserves more philosophical attention.

Patient Derived Xenografts for Genome-Driven Therapy of Osteosarcoma

Osteosarcoma (OS) is a rare malignant primary tumor of mesenchymal origin affecting bone. It is characterized by a complex genotype, mainly due to the high frequency of chromothripsis, which leads to multiple somatic copy number alterations and structural rearrangements. Any effort to design genome-driven therapies must therefore consider such high inter- and intra-tumor heterogeneity. Therefore, many laboratories and international networks are developing and sharing OS patient-derived xenografts (OS PDX) to broaden the availability of models that reproduce OS complex clinical heterogeneity. OS PDXs, and new cell lines derived from PDXs, faithfully preserve tumor heterogeneity, genetic, and epigenetic features and are thus valuable tools for predicting drug responses. Here, we review recent achievements concerning OS PDXs, summarizing the methods used to obtain ectopic and orthotopic xenografts and to fully characterize these models. The availability of OS PDXs across the many international PDX platforms and their possible use in PDX clinical trials are also described. We recommend the coupling of next-generation sequencing (NGS) data analysis with functional studies in OS PDXs, as well as the setup of OS PDX clinical trials and co-clinical trials, to enhance the predictive power of experimental evidence and to accelerate the clinical translation of effective genome-guided therapies for this aggressive disease.

Toward improved models of human cancer

Human cancer is a complex and heterogeneous collection of diseases that kills more than 18 million people every year worldwide. Despite advances in detection, diagnosis, and treatments for cancers, new strategies are needed to combat deadly cancers. Models of human cancer continue to evolve for preclinical research and have culminated in patient-derived systems that better represent the diversity and complexity of cancer. Still, no model is perfect. This Perspective attempts to address ways that we can improve the clinical translatability of models used for cancer research, from the point of view of researchers who mainly conduct cancer studies in vivo.

In Vitro and In Vivo Tumor Models for the Evaluation of Anticancer Nanoparticles

Multiple studies about tumor biology have revealed the determinant role of the tumor microenvironment in cancer progression, resulting from the dynamic interactions between tumor cells and surrounding stromal cells within the extracellular matrix. This malignant microenvironment highly impacts the efficacy of anticancer nanoparticles by displaying drug resistance mechanisms, as well as intrinsic physical and biochemical barriers, which hamper their intratumoral accumulation and biological activity.Currently, two-dimensional cell cultures are used as the initial screening method in vitro for testing cytotoxic nanocarriers. However, this fails to mimic the tumor heterogeneity, as well as the three-dimensional tumor architecture and pathophysiological barriers, leading to an inaccurate pharmacological evaluation.Biomimetic 3D in vitro tumor models, on the other hand, are emerging as promising tools for more accurately assessing nanoparticle activity, owing to their ability to recapitulate certain features of the tumor microenvironment and thus provide mechanistic insights into nanocarrier intratumoral penetration and diffusion rates.Notwithstanding, in vivo validation of nanomedicines remains irreplaceable at the preclinical stage, and a vast variety of more advanced in vivo tumor models is currently available. Such complex animal models (e.g., genetically engineered mice and patient-derived xenografts) are capable of better predicting nanocarrier clinical efficiency, as they closely resemble the heterogeneity of the human tumor microenvironment.Herein, the development of physiologically more relevant in vitro and in vivo tumor models for the preclinical evaluation of anticancer nanoparticles will be discussed, as well as the current limitations and future challenges in clinical translation.

Future Perspective of Diabetic Animal Models

Objective

The need of today’s research is to develop successful and reliable diabetic animal models for understanding the disease susceptibility and pathogenesis. Enormous success of animal models had already been acclaimed for identifying key genetic and environmental factors like Idd loci and effects of microorganisms including the gut microbiota. Furthermore, animal models had also helped in identifying many therapeutic targets and strategies for immune-intervention. In spite of a quite success, we have acknowledged that many of the discovered immunotherapies are working on animals and did not have a significant impact on human. Number of animal models were developed in the past to accelerate drug discovery pipeline. However, due to poor initial screening and assessment on inequivalent animal models, the percentage of drug candidates who succeeded during clinical trials was very low. Therefore, it is essential to bridge this gap between pre-clinical research and clinical trial by validating the existing animal models for consistency.

Results and Conclusion

In this review, we have discussed and evaluated the significance of animal models on behalf of published data on PUBMED. Amongst the most popular diabetic animal models, we have selected six animal models (e.g. BioBreeding rat, “LEW IDDM rat”, “Nonobese Diabetic (NOD) mouse”, “STZ RAT”, “LEPR Mouse” and “Zucker Diabetic Fatty (ZDF) rat” and ranked them as per their published literature on PUBMED. Moreover, the vision and brief imagination for developing an advanced and robust diabetic model of 21^st century was discussed with the theme of one mice-one human concept including organs-on-chips.

Patient-derived tumour models for personalized therapeutics in urological cancers

Preclinical knowledge of dysregulated pathways and potential biomarkers for urological cancers has undergone limited translation into the clinic. Moreover, the low approval rate of new anticancer drugs and the heterogeneous drug responses in patients indicate that current preclinical models do not always reflect the complexity of malignant disease. Patient-derived tumour models used in preclinical uro-oncology research include 3D culture systems, organotypic tissue slices and patient-derived xenograft models. Technological innovations have enabled major improvements in the capacity of these tumour models to reproduce the clinical complexity of urological cancers. Each type of patient-derived model has inherent advantages and limitations that can be exploited, either alone or in combination, to gather specific knowledge on clinical challenges and address unmet clinical needs. Nevertheless, few opportunities exist for patients with urological cancers to benefit from personalized therapeutic approaches. Clinical validation of experimental data is needed to facilitate the translation and implementation of preclinical knowledge into treatment decision making.

The role of mouse tumour models in the discovery and development of anticancer drugs

Our understanding of cancer biology has increased substantially over the past 30 years. Despite this, and an increasing pharmaceutical company expenditure on research and development, the approval of novel oncology drugs during the past decade continues to be modest. In addition, the attrition of agents during clinical development remains high. This attrition can be attributed, at least in part, to the clinical development being underpinned by the demonstration of predictable efficacy in experimental models of human tumours. This review will focus on the range of models available for the discovery and development of anticancer drugs, from traditional subcutaneous injection of tumour cell lines to mice genetically engineered to spontaneously give rise to tumours. It will consider the best time to use the models, along with practical applications and shortcomings. Finally, and most importantly, it will describe how these models reflect the underlying cancer biology and how well they predict efficacy in the clinic. Developing a line of sight to the clinic early in a drug discovery project provides clear benefit, as it helps to guide the selection of appropriate preclinical models and facilitates the investigation of relevant biomarkers.

Systematic Review of Patient-Derived Xenograft Models for Preclinical Studies of Anti-Cancer Drugs in Solid Tumors

Patient-derived xenograft (PDX) models are used as powerful tools for understanding cancer biology in PDX clinical trials and co-clinical trials. In this systematic review, we focus on PDX clinical trials or co-clinical trials for drug development in solid tumors and summarize the utility of PDX models in the development of anti-cancer drugs, as well as the challenges involved in this approach, following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Recently, the assessment of drug efficacy by PDX clinical and co-clinical trials has become an important method. PDX clinical trials can be used for the development of anti-cancer drugs before clinical trials, with their efficacy assessed by the modified response evaluation criteria in solid tumors (mRECIST). A few dozen cases of PDX models have completed enrollment, and the efficacy of the drugs is assessed by 1 × 1 × 1 or 3 × 1 × 1 approaches in the PDX clinical trials. Furthermore, co-clinical trials can be used for personalized care or precision medicine with the evaluation of a new drug or a novel combination. Several PDX models from patients in clinical trials have been used to assess the efficacy of individual drugs or drug combinations in co-clinical trials.