Genetically engineered mouse models in oncology research and cancer medicine

Multiple reaction monitoring assays for large-scale quantitation of proteins from 20 mouse organs and tissues

Mouse is the mammalian model of choice to study human health and disease due to its size, ease of breeding and the natural occurrence of conditions mimicking human pathology. Here we design and validate multiple reaction monitoring mass spectrometry (MRM-MS) assays for quantitation of 2118 unique proteins in 20 murine tissues and organs. We provide open access to technical aspects of these assays to enable their implementation in other laboratories, and demonstrate their suitability for proteomic profiling in mice by measuring normal protein abundances in tissues from three mouse strains: C57BL/6NCrl, NOD/SCID, and BALB/cAnNCrl. Sex- and strain-specific differences in protein abundances are identified and described, and the measured values are freely accessible via our MouseQuaPro database: http://mousequapro.proteincentre.com . Together, this large library of quantitative MRM-MS assays established in mice and the measured baseline protein abundances represent an important resource for research involving mouse models.

Exploring the Impact of the β-Catenin Mutations in Hepatocellular Carcinoma: An In-Depth Review

Liver cancer, primarily hepatocellular carcinoma, represents a major global health issue with significant clinical, economic, and psychological impacts. Its incidence continues to rise, driven by risk factors such as hepatitis B and C infections, nonalcoholic steatohepatitis, and various environmental influences. The Wnt/β-Catenin signaling pathway, frequently dysregulated in HCC, emerges as a promising therapeutic target. Critical genetic alterations, particularly in the CTNNB1 gene, involve mutations at key phosphorylation sites on β-catenin's N-terminal domain (S33, S37, T41, and S45) and in armadillo repeat domains (K335I and N387 K). These mutations impede β-catenin degradation, enhancing its oncogenic potential. In addition to genetic alterations, molecular and epigenetic mechanisms, including DNA methylation, histone modifications, and noncoding RNAs, further influence β-catenin signaling and tumor progression. However, β-catenin activation alone is insufficient for hepatocarcinogenesis; additional genetic "hits" are required for tumor initiation. Mutations or alterations in genes such as Ras, c-Met, NRF2, and LKB1, when combined with β-catenin activation, significantly contribute to HCC development and progression. Understanding these cooperative mutations provides crucial insights into the disease and reveals potential therapeutic strategies. The complex interplay between genetic variations and the tumor microenvironment, coupled with novel therapeutic approaches targeting the Wnt/β-Catenin pathway, offers promise for improved treatment of HCC. Despite advances, translating preclinical findings into clinical practice remains a challenge. Future research should focus on elucidating how specific β-catenin mutations and additional genetic alterations contribute to HCC pathogenesis, leveraging genetically clengineered mouse models to explore distinct signaling impacts, and identifying downstream targets. Relevant clinical trials will be essential for advancing personalized therapies and enhancing patient outcomes. This review provides a comprehensive analysis of β-Catenin signaling in HCC, highlighting its role in pathogenesis, diagnosis, and therapeutic targeting, and identifies key research directions to improve understanding and clinical outcomes.

Current Insights in Murine Models for Breast Cancer: Present, Past and Future

Breast cancer is an intricate disease that is increasing at a fast pace, and numerous heterogeneities within it further make it difficult to investigate. We have always used animal models to understand cancer pathology and create an in vivo microenvironment that closely resembles human cancer. They are considered an indispensable part of any clinical investigation regarding cancer. Animal models have a high potency in identifying the relevant biomarkers and genetic pathways involved in the course of disease prognosis. Researchers have previously explored a variety of organisms, including Drosophila melanogaster, zebrafish, and guinea pigs, to analyse breast cancer, but murine models have proven the most comprehensive due to their homologous nature with human chromosomes, easy availability, simple gene editing, and high adaptability. The available models have their pros and cons, and it depends on the researcher to select the one most relevant to their research question. Chemically induced models are cost-effective and simple to create. Transplantation models such as allografts and xenografts can mimic the human breast cancer environment reliably. Genetically engineered mouse models (GEMMs) help to underpin the genetic alterations involved and test novel immunotherapies. Virus-mediated models and gene knockout models have also provided new findings regarding breast cancer progression and metastasis. These mouse models have also enabled the visualization of breast cancer metastases. It is also imperative to consider the cost-effectiveness of these models. Despite loopholes, mouse models have evolved and are required for disease analysis.

Preclinical liver cancer models in the context of immunoprecision therapy: Application and perspectives

Hepatocellular carcinoma (HCC), ranking as the third leading cause of cancer-related mortality globally, continues to pose challenges in achieving optimal treatment outcomes. The complex nature of HCC, characterized by high spatiotemporal heterogeneity, invasive potential, and drug resistance, presents difficulties in its research. Consequently, an in-depth understanding and accurate simulation of the immune microenvironment of HCC are of paramount importance. This article comprehensively explores the application of preclinical models in HCC research, encompassing cell line models, patient-derived xenograft mouse models, genetically engineered mouse models, chemically induced models, humanized mouse models, organoid models, and microfluidic chip-based patient derived organotypic spheroids models. Each model possesses its distinct advantages and limitations in replicating the biological behavior and immune microenvironment of HCC. By scrutinizing the limitations of existing models, this paper aims to propel the development of next-generation cancer models, enabling more precise emulation of HCC characteristics. This will, in turn, facilitate the optimization of treatment strategies, drug efficacy prediction, and safety assessments, ultimately contributing to the realization of personalized and precision therapies. Additionally, this article also provides insights into future trends and challenges in the fields of tumor biology and preclinical research.

Applications and advancements of CRISPR-Cas in the treatment of lung cancer

Lung cancer is one of the most malignant diseases and a major contributor to cancer-related deaths worldwide due to the deficiency of early diagnosis and effective therapy that are of great importance for patient prognosis and quality of life. Over the past decade, the advent of clustered regularly interspaced short palindromic repeats/CRISPR associated protein (CRISPR/Cas) system has significantly propelled the progress of both fundamental research and clinical trials of lung cancer. In this review, we review the current applications of the CRISPR/Cas system in diagnosis, target identification, and treatment resistance of lung cancer. Furthermore, we summarize the development of lung cancer animal models and delivery methods based on CRISPR system, providing novel insights into clinical diagnosis and treatment strategies of lung cancer.

Biomarkers and experimental models for cancer immunology investigation

The rapid advancement of tumor immunotherapies poses challenges for the tools used in cancer immunology research, highlighting the need for highly effective biomarkers and reproducible experimental models. Current immunotherapy biomarkers encompass surface protein markers such as PD-L1, genetic features such as microsatellite instability, tumor-infiltrating lymphocytes, and biomarkers in liquid biopsy such as circulating tumor DNAs. Experimental models, ranging from 3D in vitro cultures (spheroids, submerged models, air-liquid interface models, organ-on-a-chips) to advanced 3D bioprinting techniques, have emerged as valuable platforms for cancer immunology investigations and immunotherapy biomarker research. By preserving native immune components or coculturing with exogenous immune cells, these models replicate the tumor microenvironment in vitro. Animal models like syngeneic models, genetically engineered models, and patient-derived xenografts provide opportunities to study in vivo tumor-immune interactions. Humanized animal models further enable the simulation of the human-specific tumor microenvironment. Here, we provide a comprehensive overview of the advantages, limitations, and prospects of different biomarkers and experimental models, specifically focusing on the role of biomarkers in predicting immunotherapy outcomes and the ability of experimental models to replicate the tumor microenvironment. By integrating cutting-edge biomarkers and experimental models, this review serves as a valuable resource for accessing the forefront of cancer immunology investigation.

An optimized protocol for the generation and monitoring of conditional orthotopic lung cancer in the KP mouse model using an adeno-associated virus vector compatible with biosafety level 1

BACKGROUND

The inducible Kras/p53 lung adenocarcinoma mouse model, which faithfully recapitulates human disease, is routinely initiated by the intratracheal instillation of a virus-based Cre recombinase delivery system. Handling virus-based delivery systems requires elevated biosafety levels, e.g., biosafety level 2 (BSL-2). However, in experimental animal research facilities, following exposure to viral vectors in a BSL-2 environment, rodents may not be reclassified to BSL-1 according to standard practice, preventing access to small animal micro-computed tomography (micro-CT) scanners that are typically housed in general access areas such as BSL-1 rooms. Therefore, our goal was to adapt the protocol so that the Cre-induced KP mouse model could be handled under BSL-1 conditions during the entire procedure.

RESULTS

The Kras-Lox-STOP-Lox-G12D/p53 flox/flox (KP)-based lung adenocarcinoma mouse model was activated by intratracheal instillation of either an adenoviral-based or a gutless, adeno-associated viral-based Cre delivery system. Tumor growth was monitored over time by micro-CT. We have successfully substituted the virus-based Cre delivery system with a commercially available, gutless, adeno-associated, Cre-expressing vector that allows the KP mouse model to be handled and imaged in a BSL-1 facility. By optimizing the anesthesia protocol and switching to a microscope-guided vector instillation procedure, productivity was increased and procedure-related complications were significantly reduced. In addition, repeated micro-CT analysis of individual animals allowed us to monitor tumor growth longitudinally, dramatically reducing the number of animals required per experiment. Finally, we documented the evolution of tumor volume for different doses, which revealed that individual tumor nodules induced by low-titer AAV-Cre transductions can be monitored over time by micro-CT.

CONCLUSION

Modifications to the anesthesia and instillation protocols increased the productivity of the original KP protocol. In addition, the switch to a gutless, adeno-associated, Cre-expressing vector allowed longitudinal monitoring of tumor growth under BSL-1 conditions, significantly reducing the number of animals required for an experiment, in line with the 3R principles.

Bioconjugated liquid-like solid enhances characterization of solid tumor - chimeric antigen receptor T cell interactions

Chimeric antigen receptor (CAR) T cell therapy has demonstrated remarkable success as an immunotherapy for hematological malignancies, and its potential for treating solid tumors is an active area of research. However, limited trafficking and mobility of T cells within the tumor microenvironment (TME) present challenges for CAR T cell therapy in solid tumors. To gain a better understanding of CAR T cell function in solid tumors, we subjected CD70-specific CAR T cells to a challenge by evaluating their immune trafficking and infiltration through a confined 3D microchannel network in a bio-conjugated liquid-like solid (LLS) medium. Our results demonstrated successful CAR T cell migration and anti-tumor activity against CD70-expressing glioblastoma and osteosarcoma tumors. Through comprehensive analysis of cytokines and chemokines, combined with in situ imaging, we elucidated that immune recruitment occurred via chemotaxis, and the effector-to-target ratio plays an important role in overall antitumor function. Furthermore, through single-cell collection and transcriptomic profiling, we identified differential gene expression among the immune subpopulations. Our findings provide valuable insights into the complex dynamics of CAR T cell function in solid tumors, informing future research and development in this promising cancer treatment approach. STATEMENT OF SIGNIFICANCE: The use of specialized immune cells named CAR T cells to combat cancers has demonstrated remarkable success against blood cancers. However, this success is not replicated in solid tumors, such as brain or bone cancers, mainly due to the physical barriers of these solid tumors. Currently, preclinical technologies do not allow for reliable evaluation of tumor-immune cell interactions. To better study these specialized CAR T cells, we have developed an innovative in vitro three-dimensional model that promises to dissect the interactions between tumors and CAR T cells at the single-cell level. Our findings provide valuable insights into the complex dynamics of CAR T cell function in solid tumors, informing future research and development in this promising cancer treatment approach.

Preclinical Models and Technologies in Glioblastoma Research: Evolution, Current State, and Future Avenues

Glioblastoma is the most common malignant primary central nervous system tumor and one of the most debilitating cancers. The prognosis of patients with glioblastoma remains poor, and the management of this tumor, both in its primary and recurrent forms, remains suboptimal. Despite the tremendous efforts that are being put forward by the research community to discover novel efficacious therapeutic agents and modalities, no major paradigm shifts have been established in the field in the last decade. However, this does not mirror the abundance of relevant findings and discoveries made in preclinical glioblastoma research. Hence, developing and utilizing appropriate preclinical models that faithfully recapitulate the characteristics and behavior of human glioblastoma is of utmost importance. Herein, we offer a holistic picture of the evolution of preclinical models of glioblastoma. We further elaborate on the commonly used in vitro and vivo models, delving into their development, favorable characteristics, shortcomings, and areas of potential improvement, which aids researchers in designing future experiments and utilizing the most suitable models. Additionally, this review explores progress in the fields of humanized and immunotolerant mouse models, genetically engineered animal models, 3D in vitro models, and microfluidics and highlights promising avenues for the future of preclinical glioblastoma research.

Bridging live-cell imaging and next-generation cancer treatment

By providing spatial, molecular and morphological data over time, live-cell imaging can provide a deeper understanding of the cellular and signalling events that determine cancer response to treatment. Understanding this dynamic response has the potential to enhance clinical outcome by identifying biomarkers or actionable targets to improve therapeutic efficacy. Here, we review recent applications of live-cell imaging for uncovering both tumour heterogeneity in treatment response and the mode of action of cancer-targeting drugs. Given the increasing uses of T cell therapies, we discuss the unique opportunity of time-lapse imaging for capturing the interactivity and motility of immunotherapies. Although traditionally limited in the number of molecular features captured, novel developments in multidimensional imaging and multi-omics data integration offer strategies to connect single-cell dynamics to molecular phenotypes. We review the effect of these recent technological advances on our understanding of the cellular dynamics of tumour targeting and discuss their implication for next-generation precision medicine.

Glioblastoma Margin as a Diffusion Barrier Revealed by Photoactivation of Plasmonic Nanovesicles

Glioblastoma (GBM) is the most complex and lethal adult primary brain cancer. Adequate drug diffusion and penetration are essential for treating GBM, but how the spatial heterogeneity in GBM impacts drug diffusion and transport is poorly understood. Herein, we report a new method, photoactivation of plasmonic nanovesicles (PANO), to measure molecular diffusion in the extracellular space of GBM. By examining three genetically engineered GBM mouse models that recapitulate key clinical features including angiogenic core and diffuse infiltration, we found that the tumor margin has the lowest diffusion coefficient (highest tortuosity) compared with the tumor core and surrounding brain tissue. Analysis of the cellular composition shows that the tortuosity in the GBM is strongly correlated with neuronal loss and astrocyte activation. Our all-optical measurement reveals the heterogeneous GBM microenvironment and highlights the tumor margin as a diffusion barrier for drug transport in the brain, with implications for therapeutic delivery.

Colorectal cancer mouse metastasis model combining bioluminescent and micro-computed tomography imaging for monitoring the effects of 5-fluorouracil treatment

Background

Colorectal cancer (CRC) is the fifth most fatal cancer with a low probability of surgery and limited treatment options, especially in metastatic CRC. In this study, we investigated whether a mouse model of metastatic CRC mimicked tumor progression and evaluated the effect of 5-fluorouracil (5-FU) treatment.

Methods

The CT26 mouse derived CRC cancer cell line was inoculated into mice, and the tumor bearing mice were divided into two groups: the experimental group and the control group. Micro-computed tomography (CT) and in vivo fluorescence were used to monitor the progression of metastatic CRC. A lung metastasis mouse model was employed to determine the effects of 5-FU on metastasis.

Results

Bioluminescence imaging (BLI) and computed tomography (CT), as non-invasive methods, can continuously monitor the growth of tumors in vivo. Thus, imaging techniques can be used to qualitatively and quantitatively evaluate tumor growth indicators. 5-FU injected intravenously reduced the viability of metastatic CRC cells and resulted in prolonged survival compared to the control group. Moreover, the 5-FU-treated group had significantly reduced fluorescence of the CT26 cells in the lung. The results observed by BLI and CT are consistent with the tissue morphology and structure presented in pathological examination.

Conclusions

In summary, a successful mouse model of CRC metastasis for clinical application has been established.

Meningioma animal models: a systematic review and meta-analysis

BACKGROUND

Animal models are widely used to study pathological processes and drug (side) effects in a controlled environment. There is a wide variety of methods available for establishing animal models depending on the research question. Commonly used methods in tumor research include xenografting cells (established/commercially available or primary patient-derived) or whole tumor pieces either orthotopically or heterotopically and the more recent genetically engineered models-each type with their own advantages and disadvantages. The current systematic review aimed to investigate the meningioma model types used, perform a meta-analysis on tumor take rate (TTR), and perform critical appraisal of the included studies. The study also aimed to assess reproducibility, reliability, means of validation and verification of models, alongside pros and cons and uses of the model types.

METHODS

We searched Medline, Embase, and Web of Science for all in vivo meningioma models. The primary outcome was tumor take rate. Meta-analysis was performed on tumor take rate followed by subgroup analyses on the number of cells and duration of incubation. The validity of the tumor models was assessed qualitatively. We performed critical appraisal of the methodological quality and quality of reporting for all included studies.

RESULTS

We included 114 unique records (78 using established cell line models (ECLM), 21 using primary patient-derived tumor models (PTM), 10 using genetically engineered models (GEM), and 11 using uncategorized models). TTRs for ECLM were 94% (95% CI 92-96) for orthotopic and 95% (93-96) for heterotopic. PTM showed lower TTRs [orthotopic 53% (33-72) and heterotopic 82% (73-89)] and finally GEM revealed a TTR of 34% (26-43).

CONCLUSION

This systematic review shows high consistent TTRs in established cell line models and varying TTRs in primary patient-derived models and genetically engineered models. However, we identified several issues regarding the quality of reporting and the methodological approach that reduce the validity, transparency, and reproducibility of studies and suggest a high risk of publication bias. Finally, each tumor model type has specific roles in research based on their advantages (and disadvantages).

SYSTEMATIC REVIEW REGISTRATION

PROSPERO-ID CRD42022308833.

Of mice and lymphoid aggregates: modeling tertiary lymphoid structures in cancer

Tertiary lymphoid structures (TLS) are lymph node-like aggregates that can form in association with chronic inflammation or cancer. Mature TLS are organized into B and T cell zones, and are not encapsulated but include all cell types necessary for eliciting an adaptive immune response. TLS have been observed in various cancer types and are generally associated with a positive prognosis as well as increased sensitivity to cancer immunotherapy. However, a comprehensive understanding of the roles of TLS in eliciting anti-tumor immunity as well as the mechanisms involved in their formation and function is still lacking. Further studies in orthotopic, immunocompetent cancer models are necessary to evaluate the influence of TLS on cancer therapies, and to develop new treatments that promote their formation in cancer. Here, we review key insights obtained from functional murine studies, discuss appropriate models that can be used to study cancer-associated TLS, and suggest guidelines on how to identify TLS and distinguish them from other antigen-presenting niches.

Oncogenic context shapes the fitness landscape of tumor suppression

Tumors acquire alterations in oncogenes and tumor suppressor genes in an adaptive walk through the fitness landscape of tumorigenesis. However, the interactions between oncogenes and tumor suppressor genes that shape this landscape remain poorly resolved and cannot be revealed by human cancer genomics alone. Here, we use a multiplexed, autochthonous mouse platform to model and quantify the initiation and growth of more than one hundred genotypes of lung tumors across four oncogenic contexts: KRAS G12D, KRAS G12C, BRAF V600E, and EGFR L858R. We show that the fitness landscape is rugged-the effect of tumor suppressor inactivation often switches between beneficial and deleterious depending on the oncogenic context-and shows no evidence of diminishing-returns epistasis within variants of the same oncogene. These findings argue against a simple linear signaling relationship amongst these three oncogenes and imply a critical role for off-axis signaling in determining the fitness effects of inactivating tumor suppressors.

MYC Deregulation and PTEN Loss Model Tumor and Stromal Heterogeneity of Aggressive Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) patients have a poor prognosis and few treatment options. Mouse models of TNBC are important for development of new therapies, however, few mouse models represent the complexity of TNBC. Here, we develop a female TNBC murine model by mimicking two common TNBC mutations with high co-occurrence: amplification of the oncogene MYC and deletion of the tumor suppressor PTEN. This Myc;Ptenfl model develops heterogeneous triple-negative mammary tumors that display histological and molecular features commonly found in human TNBC. Our research involves deep molecular and spatial analyses on Myc;Ptenfl tumors including bulk and single-cell RNA-sequencing, and multiplex tissue-imaging. Through comparison with human TNBC, we demonstrate that this genetic mouse model develops mammary tumors with differential survival and therapeutic responses that closely resemble the inter- and intra-tumoral and microenvironmental heterogeneity of human TNBC, providing a pre-clinical tool for assessing the spectrum of patient TNBC biology and drug response.

Preclinical Imaging Studies: Protocols, Preparation, Anesthesia, and Animal Care

Today preclinical PET imaging connects laboratory research with clinical applications. Here PET clearly bridges the gap, as nearly identical imaging protocols can be applied to both animal and humans. However, some hurdles exist and researchers must be careful, partly because the animals are usually anesthetized during the scans, while human volunteers are awake. This review is based on our own experiences of some of the most important pitfalls and how to overcome them. This includes how studies should be designed, how to select the right anesthesia and monitoring. The choice of anesthesia is quite crucial, as it may have a greater influence on the results than the effect of the tested procedures. Monitoring is necessary, as the animals cannot fully maintain homeostasis during anesthesia, and reliable results are dependent on a stable physiology. Additionally, it is important to note that rodents, in particular, are prone to rapidly becoming hypothermic. Thus, the selection of an appropriate anesthetic and monitoring protocol is crucial for both obtaining accurate results and ensuring animal welfare. Prior to imaging, catheters for tracer administration and, if necessary, blood sampling should be implanted. The administration of tracers should be done in a manner that minimizes interference with the scans, and the same applies to any serial blood sampling. The limited blood volume and organ size of rodents should also be taken into consideration when planning experiments. Finally, if the animal needs to be awakened after the scan, proper care must be taken to ensure their welfare.

Advances in glioma models using in vivo electroporation to highjack neurodevelopmental processes

Glioma is the most prevalent type of neurological malignancies. Despite decades of efforts in neurosurgery, chemotherapy and radiation therapy, glioma remains one of the most treatment-resistant brain tumors with unfavorable outcomes. Recent progresses in genomic and epigenetic profiling have revealed new concepts of genetic events involved in the etiology of gliomas in humans, meanwhile, revolutionary technologies in gene editing and delivery allows to code these genetic "events" in animals to genetically engineer glioma models. This approach models the initiation and progression of gliomas in a natural microenvironment with an intact immune system and facilitates probing therapeutic strategies. In this review, we focus on recent advances in in vivo electroporation-based glioma modeling and outline the established genetically engineered glioma models (GEGMs).

Preclinical tumor mouse models for studying esophageal cancer

Preclinical models are extensively employed in cancer research because they can be manipulated in terms of their environment, genome, molecular biology, organ systems, and physical activity to mimic human behavior and conditions. The progress made in in vivo cancer research has resulted in significant advancements, enabling the creation of spontaneous, metastatic, and humanized mouse models. Most recently, the remarkable and extensive developments in genetic engineering, particularly the utilization of CRISPR/Cas9, transposable elements, epigenome modifications, and liquid biopsies, have further facilitated the design and development of numerous mouse models for studying cancer. In this review, we have elucidated the production and usage of current mouse models, such as xenografts, chemical-induced models, and genetically engineered mouse models (GEMMs), for studying esophageal cancer. Additionally, we have briefly discussed various gene-editing tools that could potentially be employed in the future to create mouse models specifically for esophageal cancer research.

A Primer for Research Scientists on Assessing Mouse Gross and Histopathology Images in the Biomedical Literature

Advances in genomic technologies have enabled the development of abundant mouse models of human disease, requiring accurate phenotyping to elucidate the consequences of genetic manipulation. Anatomic pathology, an important component of the mouse phenotyping pipeline, is ideally performed by human or veterinary pathologists; however, due to insufficient numbers of pathologists qualified to assess these mouse models morphologically, research scientists may perform "do-it-yourself" pathology, resulting in diagnostic error. In the biomedical literature, pathology data is commonly presented as images of tissue sections, stained with either hematoxylin and eosin or antibodies via immunohistochemistry, accompanied by a figure legend. Data presented in such images and figure legends may contain inaccuracies. Furthermore, there is limited guidance for non-pathologist research scientists concerning the elements required in an ideal pathology image and figure legend in a research publication. In this overview, the components of an ideal pathology image and figure legend are outlined and comprise image quality, image composition, and image interpretation. Background knowledge is important for producing accurate pathology images and critically assessing these images in the literature. This foundational knowledge includes understanding relevant human and mouse anatomy and histology and, for cancer researchers, an understanding of human and mouse tumor classification and morphology, mouse stain background lesions, and tissue processing artifacts. Accurate interpretation of immunohistochemistry is also vitally important and is detailed with emphasis on the requirement for tissue controls and the distribution, intensity, and intracellular location of staining. Common pitfalls in immunohistochemistry interpretation are outlined, and a checklist of questions is provided by which any pathology image may be critically examined. Collaboration with pathologist colleagues is encouraged. This overview aims to equip researchers to critically assess the quality and accuracy of pathology images in the literature to improve the reliability and reproducibility of published pathology data. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC.

Effectively utilizing publicly available databases for cancer target evaluation

The majority of compounds designed against cancer drug targets do not progress to become approved drugs, mainly due to lack of efficacy and/or unmanageable toxicity. Robust target evaluation is therefore required before progressing through the drug discovery process to reduce the high attrition rate. There are a wealth of publicly available databases that can be mined to generate data as part of a target evaluation. It can, however, be challenging to learn what databases are available, how and when they should be used, and to understand the associated limitations. Here, we have compiled and present key, freely accessible and easy-to-use databases that house informative datasets from in vitro, in vivo and clinical studies. We also highlight comprehensive target review databases that aim to bring together information from multiple sources into one-stop portals. In the post-genomics era, a key objective is to exploit the extensive cell, animal and patient characterization datasets in order to deliver precision medicine on a patient-specific basis. Effective utilization of the highlighted databases will go some way towards supporting the cancer research community achieve these aims.

Socs1-knockout in skin-resident CD4+ T cells in a protracted contact-allergic reaction results in an autonomous skin inflammation with features of early-stage mycosis fungoides

Recent detailed genomic analysis of mycosis fungoides (MF) identified suppressor of cytokine signaling 1 (SOCS1), an inhibitor of JAK/STAT signaling, as one of the frequently deleted tumor suppressors in MF, and one-copy deletion of SOCS1 was confirmed in early-stage MF lesions. To better understand the functional role of SOCS1 in the genesis of MF, we used a genetically engineered mouse model emulating heterozygous SOCS1 loss in skin resident CD4+ T cells. In these mice an experimentally induced contact-allergic reaction was maintained for 20 weeks. Ten weeks after discontinuing contact-allergic challenges, only the skin with locally one-copy deletion of Socs1 in CD4+ T cells still showed high numbers of CD3+/CD4+ Socs1 k.o. cells in the dermis (p ＜ 0.0001) with prevalent Stat3 activation (p ＜0.001). And in one out of 9 mice, this had progressed to far more dramatic increases, including the thickened epidermis, and with an explosive growth of Socs1 k.o. T cells in circulation; indicative of cutaneous lymphoma. Hence, we show that Socs1 mono-allelic loss in CD4+ T cells locally in protractedly inflamed skin results in autonomous skin inflammation with features of early-stage MF.

Sensitive, non-immunogenic in vivo imaging of cancer metastases and immunotherapy response

Non-invasive imaging of tumors expressing reporter transgenes is a popular preclinical method for studying tumor development and response to therapy in vivo due to its ability to distinguish signal from tumors over background noise. However, the utilized transgenes, such as firefly luciferase, are immunogenic and, therefore, impact results when expressed in immune-competent hosts. This represents an important limitation, given that cancer immunology and immunotherapy are currently among the most impactful areas of research and therapeutic development. Here we present a non-immunogenic preclinical tumor imaging approach. Based on the expression of murine sodium iodide symporter (mNIS), it facilitates sensitive, non-invasive detection of syngeneic tumor cells in immune-competent tumor models without additional immunogenicity arising from exogenous transgenic protein or selection marker expression. NIS-expressing tumor cells internalize the gamma-emitting [99mTc]pertechnetate ion and so can be detected by SPECT (single photon emission computed tomography). Using a mouse model of pancreatic ductal adenocarcinoma hepatic metastases in immune-competent C57BL/6 mice, we demonstrate that the technique enables the detection of very early metastatic lesions and longitudinal assessment of immunotherapy responses using precise and quantifiable whole-body SPECT/CT imaging.

Ablative radiotherapy improves survival but does not cure autochthonous mouse models of prostate and colorectal cancer

BACKGROUND

Genetically engineered mouse models (GEMMs) of cancer are powerful tools to study mechanisms of disease progression and therapy response, yet little is known about how these models respond to multimodality therapy used in patients. Radiation therapy (RT) is frequently used to treat localized cancers with curative intent, delay progression of oligometastases, and palliate symptoms of metastatic disease.

METHODS

Here we report the development, testing, and validation of a platform to immobilize and target tumors in mice with stereotactic ablative RT (SART). Xenograft and autochthonous tumor models were treated with hypofractionated ablative doses of radiotherapy.

RESULTS

We demonstrate that hypofractionated regimens used in clinical practice can be effectively delivered in mouse models. SART alters tumor stroma and the immune environment, improves survival in GEMMs of primary prostate and colorectal cancer, and synergizes with androgen deprivation in prostate cancer. Complete pathologic responses were achieved in xenograft models, but not in GEMMs.

CONCLUSIONS

While SART is capable of fully ablating xenografts, it is unable to completely eradicate disease in GEMMs, arguing that resistance to potentially curative therapy can be modeled in GEMMs.

Organoids: approaches and utility in cancer research

ABSTRACT

Organoids are three-dimensional cellular structures with self-organizing and self-differentiation capacities. They faithfully recapitulate structures and functions of in vivo organs as represented by functionality and microstructural definitions. Heterogeneity in in vitro disease modeling is one of the main reasons for anti-cancer therapy failures. Establishing a powerful model to represent tumor heterogeneity is crucial for elucidating tumor biology and developing effective therapeutic strategies. Tumor organoids can retain the original tumor heterogeneity and are commonly used to mimic the cancer microenvironment when co-cultured with fibroblasts and immune cells; therefore, considerable effort has been made recently to promote the use of this new technology from basic research to clinical studies in tumors. In combination with gene editing technology and microfluidic chip systems, engineered tumor organoids show promising abilities to recapitulate tumorigenesis and metastasis. In many studies, the responses of tumor organoids to various drugs have shown a positive correlation with patient responses. Owing to these consistent responses and personalized characteristics with patient data, tumor organoids show excellent potential for preclinical research. Here, we summarize the properties of different tumor models and review their current state and progress in tumor organoids. We further discuss the substantial challenges and prospects in the rapidly developing tumor organoid field.

Genetically engineered mouse models of head and neck cancers

The head and neck region is one of the anatomic sites commonly afflicted by cancer, with ~1.5 million new diagnoses reported worldwide in 2020 alone. Remarkable progress has been made in understanding the underlying disease mechanisms, personalizing care based on each tumor's individual molecular characteristics, and even therapeutically exploiting the inherent vulnerabilities of these neoplasms. In this regard, genetically engineered mouse models (GEMMs) have played an instrumental role. While progress in the development of GEMMs has been slower than in other major cancer types, several GEMMs are now available that recapitulate most of the heterogeneous characteristics of head and neck cancers such as the tumor microenvironment. Different approaches have been employed in GEMM development and implementation, though each can generally recapitulate only certain disease aspects. As a result, appropriate model selection is essential for addressing specific research questions. In this review, we present an overview of all currently available head and neck cancer GEMMs, encompassing models for head and neck squamous cell carcinoma, nasopharyngeal carcinoma, and salivary and thyroid gland carcinomas.

Rethinking our approach to cancer metabolism to deliver patient benefit

Altered cellular metabolism is a major mechanism by which tumours support nutrient consumption associated with increased cellular proliferation. Selective dependency on specific metabolic pathways provides a therapeutic vulnerability that can be targeted in cancer therapy. Anti-metabolites have been used clinically since the 1940s and several agents targeting nucleotide metabolism are now well established as standard of care treatment in a range of indications. However, despite great progress in our understanding of the metabolic requirements of cancer and non-cancer cells within the tumour microenvironment, there has been limited clinical success for novel agents targeting pathways outside of nucleotide metabolism. We believe that there is significant therapeutic potential in targeting metabolic processes within cancer that is yet to be fully realised. However, current approaches to identify novel targets, test novel therapies and select patient populations most likely to benefit are sub-optimal. We highlight recent advances in technologies and understanding that will support the identification and validation of novel targets, re-evaluation of existing targets and design of optimal clinical positioning strategies to deliver patient benefit.

Models in Pancreatic Neuroendocrine Neoplasms: Current Perspectives and Future Directions

Pancreatic neuroendocrine neoplasms (pNENs) are a heterogeneous group of tumors derived from multiple neuroendocrine origin cell subtypes. Incidence rates for pNENs have steadily risen over the last decade, and outcomes continue to vary widely due to inability to properly screen. These tumors encompass a wide range of functional and non-functional subtypes, with their rarity and slow growth making therapeutic development difficult as most clinically used therapeutics are derived from retrospective analyses. Improved molecular understanding of these cancers has increased our knowledge of the tumor biology for pNENs. Despite these advances in our understanding of pNENs, there remains a dearth of models for further investigation. In this review, we will cover the current field of pNEN models, which include established cell lines, animal models such as mice and zebrafish, and three-dimensional (3D) cell models, and compare their uses in modeling various disease aspects. While no study model is a complete representation of pNEN biology, each has advantages which allow for new scientific understanding of these rare tumors. Future efforts and advancements in technology will continue to create new options in modeling these cancers.

Dual Recombinase-Based Mouse Models Help Decipher Cancer Biology and Targets for Therapy

The advent of next-generation sequencing (NGS) and single-cell profiling technologies has revealed the complex and heterogenous ecosystem of human tumors under steady-state and therapeutic perturbation. Breakthroughs in the development of genetically engineered mouse models (GEMM) of human cancers that are based on the combination of two site-specific recombinase systems [dual-recombinase system (DRS)] offer fundamental new possibilities to elucidate and understand critical drivers of the diverse tumor phenotypes and validate potential targets for therapy. Here, we discuss opportunities DRS-based cancer GEMMs offer to model, trace, manipulate, and functionally investigate established cancers, their interactions with the host, and their response to therapy.

High-Throughput Identification, Modeling, and Analysis of Cancer Driver Genes In Vivo

The vast number of genomic and molecular alterations in cancer pose a substantial challenge to uncovering the mechanisms of tumorigenesis and identifying therapeutic targets. High-throughput functional genomic methods in genetically engineered mouse models allow for rapid and systematic investigation of cancer driver genes. In this review, we discuss the basic concepts and tools for multiplexed investigation of functionally important cancer genes in vivo using autochthonous cancer models. Furthermore, we highlight emerging technical advances in the field, potential opportunities for future investigation, and outline a vision for integrating multiplexed genetic perturbations with detailed molecular analyses to advance our understanding of the genetic and molecular basis of cancer.

A C57BL/6J Fancg-KO Mouse Model Generated by CRISPR/Cas9 Partially Captures the Human Phenotype

Fanconi anemia (FA) develops due to a mutation in one of the FANC genes that are involved in the repair of interstrand crosslinks (ICLs). FANCG, a member of the FA core complex, is essential for ICL repair. Previous FANCG-deficient mouse models were generated with drug-based selection cassettes in mixed mice backgrounds, leading to a disparity in the interpretation of genotype-related phenotype. We created a Fancg-KO (KO) mouse model using CRISPR/Cas9 to exclude these confounders. The entire Fancg locus was targeted and maintained on the immunological well-characterized C57BL/6J background. The intercrossing of heterozygous mice resulted in sub-Mendelian numbers of homozygous mice, suggesting the loss of FANCG can be embryonically lethal. KO mice displayed infertility and hypogonadism, but no other developmental problems. Bone marrow analysis revealed a defect in various hematopoietic stem and progenitor subsets with a bias towards myelopoiesis. Cell lines derived from Fancg-KO mice were hypersensitive to the crosslinking agents cisplatin and Mitomycin C, and Fancg-KO mouse embryonic fibroblasts (MEFs) displayed increased γ-H2AX upon cisplatin treatment. The reconstitution of these MEFs with Fancg cDNA corrected for the ICL hypersensitivity. This project provides a new, genetically, and immunologically well-defined Fancg-KO mouse model for further in vivo and in vitro studies on FANCG and ICL repair.

Advances in experimental animal models of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a common malignant tumor with insidious early symptoms, easy metastasis, postoperative recurrence, poor drug efficacy, and a high drug resistance rate when surgery is missed, leading to a low 5-year survival rate. Research on the pathogenesis and drugs is particularly important for clinical treatment. Animal models are crucial for basic research, which is conducive to studying pathogenesis and drug screening more conveniently and effectively. An appropriate animal model can better reflect disease occurrence and development, and the process of anti-tumor immune response in the human body. This review summarizes the classification, characteristics, and advances in experimental animal models of HCC to provide a reference for researchers on model selection.

New hormone receptor-positive breast cancer mouse cell line mimicking the immune microenvironment of anti-PD-1 resistant mammary carcinoma

BACKGROUND

Progress in breast cancer (BC) research relies on the availability of suitable cell lines that can be implanted in immunocompetent laboratory mice. The best studied mouse strain, C57BL/6, is also the only one for which multiple genetic variants are available to facilitate the exploration of the cancer-immunity dialog. Driven by the fact that no hormone receptor-positive (HR+) C57BL/6-derived mammary carcinoma cell lines are available, we decided to establish such cell lines.

METHODS

BC was induced in female C57BL/6 mice using a synthetic progesterone analog (medroxyprogesterone acetate, MPA) combined with a DNA damaging agent (7,12-dimethylbenz[a]anthracene, DMBA). Cell lines were established from these tumors and selected for dual (estrogen+progesterone) receptor positivity, as well as transplantability into C57BL/6 immunocompetent females.

RESULTS

One cell line, which we called B6BC, fulfilled these criteria and allowed for the establishment of invasive estrogen receptor-positive (ER+) tumors with features of epithelial to mesenchymal transition that were abundantly infiltrated by myeloid immune populations but scarcely by T lymphocytes, as determined by single-nucleus RNA sequencing and high-dimensional leukocyte profiling. Such tumors failed to respond to programmed cell death-1 (PD-1) blockade, but reduced their growth on treatment with ER antagonists, as well as with anthracycline-based chemotherapy, which was not influenced by T-cell depletion. Moreover, B6BC-derived tumors reduced their growth on CD11b blockade, indicating tumor sustainment by myeloid cells. The immune environment and treatment responses recapitulated by B6BC-derived tumors diverged from those of ER+ TS/A cell-derived tumors in BALB/C mice, and of ER- E0771 cell-derived and MPA/DMBA-induced tumors in C57BL/6 mice.

CONCLUSIONS

B6BC is the first transplantable HR+ BC cell line derived from C57BL/6 mice and B6BC-derived tumors recapitulate the complex tumor microenvironment of locally advanced HR+ BC naturally resistant to PD-1 immunotherapy.

Emerging Preclinical Applications of Humanized Mouse Models in the Discovery and Validation of Novel Immunotherapeutics and Their Mechanisms of Action for Improved Cancer Treatment

Cancer therapeutics have undergone immense research over the past decade. While chemotherapies remain the mainstay treatments for many cancers, the advent of new molecular techniques has opened doors for more targeted modalities towards cancer cells. Although immune checkpoint inhibitors (ICIs) have demonstrated therapeutic efficacy in treating cancer, adverse side effects related to excessive inflammation are often reported. There is a lack of clinically relevant animal models to probe the human immune response towards ICI-based interventions. Humanized mouse models have emerged as valuable tools for pre-clinical research to evaluate the efficacy and safety of immunotherapy. This review focuses on the establishment of humanized mouse models, highlighting the challenges and recent advances in these models for targeted drug discovery and the validation of therapeutic strategies in cancer treatment. Furthermore, the potential of these models in the process of uncovering novel disease mechanisms is discussed.

Dissecting metastasis using preclinical models and methods

Metastasis has long been understood to lead to the overwhelming majority of cancer-related deaths. However, our understanding of the metastatic process, and thus our ability to prevent or eliminate metastases, remains frustratingly limited. This is largely due to the complexity of metastasis, which is a multistep process that likely differs across cancer types and is greatly influenced by many aspects of the in vivo microenvironment. In this Review, we discuss the key variables to consider when designing assays to study metastasis: which source of metastatic cancer cells to use and where to introduce them into mice to address different questions of metastasis biology. We also examine methods that are being used to interrogate specific steps of the metastatic cascade in mouse models, as well as emerging techniques that may shed new light on previously inscrutable aspects of metastasis. Finally, we explore approaches for developing and using anti-metastatic therapies, and how mouse models can be used to test them.

A targeted genetic modifier screen in Drosophila uncovers vulnerabilities in a genetically complex model of colon cancer

Received on 16 January 2023; accepted on 21 February 2023Kinases are key regulators of cellular signal transduction pathways. Many diseases, including cancer, are associated with global alterations in protein phosphorylation networks. As a result, kinases are frequent targets of drug discovery efforts. However, target identification and assessment, a critical step in targeted drug discovery that involves identifying essential genetic mediators of disease phenotypes, can be challenging in complex, heterogeneous diseases like cancer, where multiple concurrent genomic alterations are common. Drosophila is a particularly useful genetic model system to identify novel regulators of biological processes through unbiased genetic screens. Here, we report 2 classic genetic modifier screens focusing on the Drosophila kinome to identify kinase regulators in 2 different backgrounds: KRAS TP53 PTEN APC, a multigenic cancer model that targets 4 genes recurrently mutated in human colon tumors and KRAS alone, a simpler model that targets one of the most frequently altered pathways in cancer. These screens identified hits unique to each model and one shared by both, emphasizing the importance of capturing the genetic complexity of human tumor genome landscapes in experimental models. Our follow-up analysis of 2 hits from the KRAS-only screen suggests that classical genetic modifier screens in heterozygous mutant backgrounds that result in a modest, nonlethal reduction in candidate gene activity in the context of a whole animal-a key goal of systemic drug treatment-may be a particularly useful approach to identify the most rate-limiting genetic vulnerabilities in disease models as ideal candidate drug targets.

Experimental Murine Models for Colorectal Cancer Research

Colorectal cancer (CRC) is the third most prevalent malignancy worldwide and in both sexes. Numerous animal models for CRC have been established to study its biology, namely carcinogen-induced models (CIMs) and genetically engineered mouse models (GEMMs). CIMs are valuable for assessing colitis-related carcinogenesis and studying chemoprevention. On the other hand, CRC GEMMs have proven to be useful for evaluating the tumor microenvironment and systemic immune responses, which have contributed to the discovery of novel therapeutic approaches. Although metastatic disease can be induced by orthotopic injection of CRC cell lines, the resulting models are not representative of the full genetic diversity of the disease due to the limited number of cell lines suitable for this purpose. On the other hand, patient-derived xenografts (PDX) are the most reliable for preclinical drug development due to their ability to retain pathological and molecular characteristics. In this review, the authors discuss the various murine CRC models with a focus on their clinical relevance, benefits, and drawbacks. From all models discussed, murine CRC models will continue to be an important tool in advancing our understanding and treatment of this disease, but additional research is required to find a model that can correctly reflect the pathophysiology of CRC.

Tumor heterogeneity: preclinical models, emerging technologies, and future applications

Heterogeneity describes the differences among cancer cells within and between tumors. It refers to cancer cells describing variations in morphology, transcriptional profiles, metabolism, and metastatic potential. More recently, the field has included the characterization of the tumor immune microenvironment and the depiction of the dynamics underlying the cellular interactions promoting the tumor ecosystem evolution. Heterogeneity has been found in most tumors representing one of the most challenging behaviors in cancer ecosystems. As one of the critical factors impairing the long-term efficacy of solid tumor therapy, heterogeneity leads to tumor resistance, more aggressive metastasizing, and recurrence. We review the role of the main models and the emerging single-cell and spatial genomic technologies in our understanding of tumor heterogeneity, its contribution to lethal cancer outcomes, and the physiological challenges to consider in designing cancer therapies. We highlight how tumor cells dynamically evolve because of the interactions within the tumor immune microenvironment and how to leverage this to unleash immune recognition through immunotherapy. A multidisciplinary approach grounded in novel bioinformatic and computational tools will allow reaching the integrated, multilayered knowledge of tumor heterogeneity required to implement personalized, more efficient therapies urgently required for cancer patients.

3D cancer models: One step closer to in vitro human studies

Cancer immunotherapy is the great breakthrough in cancer treatment as it displayed prolonged progression-free survival over conventional therapies, yet, to date, in only a minority of patients. In order to broad cancer immunotherapy clinical applicability some roadblocks need to be overcome, first among all the lack of preclinical models that faithfully depict the local tumor microenvironment (TME), which is known to dramatically affect disease onset, progression and response to therapy. In this review, we provide the reader with a detailed overview of current 3D models developed to mimick the complexity and the dynamics of the TME, with a focus on understanding why the TME is a major target in anticancer therapy. We highlight the advantages and translational potentials of tumor spheroids, organoids and immune Tumor-on-a-Chip models in disease modeling and therapeutic response, while outlining pending challenges and limitations. Thinking forward, we focus on the possibility to integrate the know-hows of micro-engineers, cancer immunologists, pharmaceutical researchers and bioinformaticians to meet the needs of cancer researchers and clinicians interested in using these platforms with high fidelity for patient-tailored disease modeling and drug discovery.

Patient-derived models: Promising tools for accelerating the clinical translation of breast cancer research findings

Breast cancer has become the highest incidence of cancer in women. It was extensively and deeply studied by biologists and medical workers worldwide. However, the meaningful results in lab researches cannot be realized in clinical, and a part of new drugs in clinical experiments do not obtain as good results as the preclinical researches. It is urgently that promote a kind of breast cancer research models that can get study results closer to the physiological condition of the human body. Patient-derived models (PDMs) originating from clinical tumor, contain primary elements of tumor and maintain key clinical features of tumor. So they are promising research models to facilitate laboratory researches translate to clinical application, and predict the treatment outcome of patients. In this review, we summarize the establishment of PDMs of breast cancer, reviewed the application of PDMs in clinical translational researches and personalized precision medicine with breast cancer as an example, to improve the understanding of PDMs among researchers and clinician, facilitate them to use PDMs on a large scale of breast cancer researches and promote the clinical translation of laboratory research and new drug development.

The Blood-Brain Barrier: Implications for Experimental Cancer Therapeutics

The blood-brain barrier is critically important for the treatment of both primary and metastatic cancers of the central nervous system (CNS). Clinical outcomes for patients with primary CNS tumors are poor and have not significantly improved in decades. As treatments for patients with extracranial solid tumors improve, the incidence of CNS metastases is on the rise due to suboptimal CNS exposure of otherwise systemically active agents. Despite state-of-the art surgical care and increasingly precise radiation therapy, clinical progress is limited by the ability to deliver an effective dose of a therapeutic agent to all cancerous cells. Given the tremendous heterogeneity of CNS cancers, both across cancer subtypes and within a single tumor, and the range of diverse therapies under investigation, a nuanced examination of CNS drug exposure is needed. With a shared goal, common vocabulary, and interdisciplinary collaboration, the field is poised for renewed progress in the treatment of CNS cancers.

Preclinical efficacy of oncolytic VSV-IFNβ in treating cancer: A systematic review

Background

Cancer incidence and mortality are increasing rapidly worldwide, necessitating further investigation into developing and optimizing emergent cancer therapies. Oncolytic viruses such as vesicular stomatitis virus encoding interferon β (VSV-IFNβ) have attracted considerable attention, as they offer great efficacy and safety profiles. This systematic review aimed to determine and compare the efficacy profile between VSV-IFNβ and non-treatment controls in preclinical cancer models.

Methodology

The Embase and Medline databases were systematically searched for relevant studies using related key terms and Medical Subject Headings (MeSH). Titles, abstracts, and full texts were screened, and data from eligible articles were extracted by two groups independently and in duplicate (two reviewers per group). Disagreements were resolved by a fifth independent reviewer. The included articles were all preclinical (translational) in vivo English studies that investigated and compared the efficacy profile between VSV-IFNβ and non-treatment controls in animal models. The risk of bias among the studies was assessed by two reviewers independently and in duplicate using SYRCLE’s risk-of-bias tool for animal studies; disparities were addressed by a third independent reviewer.

Results

After employing relevant MeSH and key terms, we identified 1598 articles. A total of 87 articles were either duplicates or conference proceedings and were thus excluded. Following title and abstract screening, 37 articles were included in the full-text assessment. Finally, 14 studies met the eligibility criteria. Forty-two experiments from the included studies examined the potential efficacy of VSV-IFNβ through different routes of administration, including intratumoral, intraperitoneal, and intravenous routes. Thirty-seven experiments reported positive outcomes. Meanwhile, five experiments reported negative outcomes, three and two of which examined intratumoral and intravenous VSV-IFNβ administration, respectively.

Conclusion

Although the majority of the included studies support the promising potential of VSV-IFNβ as an oncolytic virus, further research is necessary to ensure a safe and efficacious profile to translate its application into clinical trials.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022335418.

Improving the predictive power of xenograft and syngeneic anti-tumour studies using mice humanised for pathways of drug metabolism

Drug development is an expensive and time-consuming process, with only a small fraction of drugs gaining regulatory approval from the often many thousands of candidates identified during target validation. Once a lead compound has been identified and optimised, they are subject to intensive pre-clinical research to determine their pharmacodynamic, pharmacokinetic and toxicological properties, procedures which inevitably involve significant numbers of animals - mainly mice and rats, but also dogs and monkeys in much smaller numbers and for specific types of drug candidates. Many compounds that emerge from this process, having been shown to be safe and efficacious in pre-clinical studies, subsequently fail to replicate this outcome in clinical trials, therefore wasting time, money and, most importantly, animals. Due to high rates of metabolism and a differing spectrum of metabolites (some pharmacologically active) in rodents, species differences in drug metabolism can be a major impediment to drug discovery programmes and confound the extrapolation of animal data to humans. To circumvent this, we have developed a complex transgenic mouse model – 8HUM - which faithfully replicates human Phase I drug metabolism (and its regulation), and which will generate more human-relevant data from fewer animals in a pre-clinical setting and reduce attrition in the clinic. One key area for the pre-clinical application of animals in an oncology setting – almost exclusively mice - is their use in anti-tumour studies. We now further demonstrate the utility of the 8HUM mouse using a murine melanoma cell line as a syngeneic tumour and also present an immunodeficient version 8HUM_Rag2 -/- - for use in xenograft studies. These models will be of significant benefit not only to Pharma for pre-clinical drug development work, but also throughout the drug efficacy, toxicology, pharmacology, and drug metabolism communities, where fewer animals will be needed to generate more human-relevant data.

A survey of open questions in adaptive therapy: Bridging mathematics and clinical translation

Adaptive therapy is a dynamic cancer treatment protocol that updates (or 'adapts') treatment decisions in anticipation of evolving tumor dynamics. This broad term encompasses many possible dynamic treatment protocols of patient-specific dose modulation or dose timing. Adaptive therapy maintains high levels of tumor burden to benefit from the competitive suppression of treatment-sensitive subpopulations on treatment-resistant subpopulations. This evolution-based approach to cancer treatment has been integrated into several ongoing or planned clinical trials, including treatment of metastatic castrate resistant prostate cancer, ovarian cancer, and BRAF-mutant melanoma. In the previous few decades, experimental and clinical investigation of adaptive therapy has progressed synergistically with mathematical and computational modeling. In this work, we discuss 11 open questions in cancer adaptive therapy mathematical modeling. The questions are split into three sections: (1) integrating the appropriate components into mathematical models (2) design and validation of dosing protocols, and (3) challenges and opportunities in clinical translation.

Naturally occurring canine sarcomas: Bridging the gap from mouse models to human patients through cross-disciplinary research partnerships

Fueled by support from the National Cancer Institute's "Cancer Moonshot" program, the past few years have witnessed a renewed interest in the canine spontaneous cancer model as an invaluable resource in translational oncology research. Increasingly, there is awareness that pet dogs with cancer provide an accessible bridge to improving the efficiency of cancer drug discovery and clinical therapeutic development. Canine tumors share many biological, genetic, and histologic features with their human tumor counterparts, and most importantly, retain the complexities of naturally occurring drug resistance, metastasis, and tumor-host immune interactions, all of which are difficult to recapitulate in induced or genetically engineered murine tumor models. The utility of canine models has been particularly apparent in sarcoma research, where the increased incidence of sarcomas in dogs as compared to people has facilitated comparative research resulting in treatment advances benefitting both species. Although there is an increasing awareness of the advantages in using spontaneous canine sarcoma models for research, these models remain underutilized, in part due to a lack of more permanent institutional and cross-institutional infrastructure to support partnerships between veterinary and human clinician-scientists. In this review, we provide an updated overview of historical and current applications of spontaneously occurring canine tumor models in sarcoma research, with particular attention to knowledge gaps, limitations, and growth opportunities within these applications. Furthermore, we propose considerations for working within existing veterinary translational and comparative oncology research infrastructures to maximize the benefit of partnerships between veterinary and human biomedical researchers within and across institutions to improve the utility and application of spontaneous canine sarcomas in translational oncology research.

Circadian disruption: from mouse models to molecular mechanisms and cancer therapeutic targets

The circadian clock is a timekeeping system for numerous biological rhythms that contribute to the regulation of numerous homeostatic processes in humans. Disruption of circadian rhythms influences physiology and behavior and is associated with adverse health outcomes, especially cancer. However, the underlying molecular mechanisms of circadian disruption-associated cancer initiation and development remain unclear. It is essential to construct good circadian disruption models to uncover and validate the detailed molecular clock framework of circadian disruption in cancer development and progression. Mouse models are the most widely used in circadian studies due to their relatively small size, fast reproduction cycle, easy genome manipulation, and economic practicality. Here, we reviewed the current mouse models of circadian disruption, including suprachiasmatic nuclei destruction, genetic engineering, light disruption, sleep deprivation, and other lifestyle factors in our understanding of the crosstalk between circadian rhythms and oncogenic signaling, as well as the molecular mechanisms of circadian disruption that promotes cancer growth. We focused on the discoveries made with the nocturnal mouse, diurnal human being, and cell culture and provided several circadian rhythm-based cancer therapeutic strategies.

Rational combinations of targeted cancer therapies: background, advances and challenges

Over the past two decades, elucidation of the genetic defects that underlie cancer has resulted in a plethora of novel targeted cancer drugs. Although these agents can initially be highly effective, resistance to single-agent therapies remains a major challenge. Combining drugs can help avoid resistance, but the number of possible drug combinations vastly exceeds what can be tested clinically, both financially and in terms of patient availability. Rational drug combinations based on a deep understanding of the underlying molecular mechanisms associated with therapy resistance are potentially powerful in the treatment of cancer. Here, we discuss the mechanisms of resistance to targeted therapies and how effective drug combinations can be identified to combat resistance. The challenges in clinically developing these combinations and future perspectives are considered.

Senescent cancer cell-derived nanovesicle as a personalized therapeutic cancer vaccine

The development of therapeutic cancer vaccines (TCVs) that provide clinical benefits is challenging mainly due to difficulties in identifying immunogenic tumor antigens and effectively inducing antitumor immunity. Furthermore, there is an urgent need for personalized TCVs because only a limited number of tumor antigens are shared among cancer patients. Several autologous nanovaccines that do not require the identification of immunogenic tumor antigens have been proposed as personalized TCVs. However, these nanovaccines generally require exogenous adjuvants (e.g., Toll-like receptor agonists) to improve vaccine immunogenicity, which raises safety concerns. Here, we present senescent cancer cell-derived nanovesicle (SCCNV) as a personalized TCV that provides patient-specific tumor antigens and improved vaccine immunogenicity without the use of exogenous adjuvants. SCCNVs are prepared by inducing senescence in cancer cells ex vivo and subsequently extruding the senescent cancer cells through nanoporous membranes. In the clinical setting, SCCNVs can be prepared from autologous cancer cells from the blood of liquid tumor patients or from tumors surgically removed from solid cancer patients. SCCNVs also contain interferon-γ and tumor necrosis factor-α, which are expressed during senescence. These endogenous cytokines act as adjuvants and enhance vaccine immunogenicity, avoiding the need for exogenous adjuvants. Intradermally injected SCCNVs effectively activate dendritic cells and tumor-specific T cells and inhibit primary and metastatic tumor growth and tumor recurrence. SCCNV therapy showed an efficacy similar to that of immune checkpoint blockade (ICB) therapy and synergized with ICB. SCCNVs, which can be prepared using a simple and facile procedure, show potential as personalized TCVs.

Three-Dimensional Bioconjugated Liquid-Like Solid (LLS) Enhance Characterization of Solid Tumor - Chimeric Antigen Receptor T cell interactions

Cancer immunotherapy offers lifesaving treatments for cancers, but the lack of reliable preclinical models that could enable the mechanistic studies of tumor-immune interactions hampers the identification of new therapeutic strategies. We hypothesized 3D confined microchannels, formed by interstitial space between bio-conjugated liquid-like solids (LLS), enable CAR T dynamic locomotion within an immunosuppressive TME to carry out anti-tumor function. Murine CD70-specific CAR T cells cocultured with the CD70-expressing glioblastoma and osteosarcoma demonstrated efficient trafficking, infiltration, and killing of cancer cells. The anti-tumor activity was clearly captured via longterm in situ imaging and supported by upregulation of cytokines and chemokines including IFNg, CXCL9, CXCL10, CCL2, CCL3, and CCL4. Interestingly, target cancer cells, upon an immune attack, initiated an "immune escape" response by frantically invading the surrounding microenvironment. This phenomenon however was not observed for the wild-type tumor samples which remained intact and produced no relevant cytokine response. Single cells collection and transcriptomic profiling of CAR T cells at regions of interest revealed feasibility of identifying differential gene expression amongst the immune subpopulations. Complimentary 3D in vitro platforms are necessary to uncover cancer immune biology mechanisms, as emphasized by the significant roles of the TME and its heterogeneity.

OncoLoop: A Network-Based Precision Cancer Medicine Framework

Prioritizing treatments for individual patients with cancer remains challenging, and performing coclinical studies using patient-derived models in real time is often unfeasible. To circumvent these challenges, we introduce OncoLoop, a precision medicine framework that predicts drug sensitivity in human tumors and their preexisting high-fidelity (cognate) model(s) by leveraging drug perturbation profiles. As a proof of concept, we applied OncoLoop to prostate cancer using genetically engineered mouse models (GEMM) that recapitulate a broad spectrum of disease states, including castration-resistant, metastatic, and neuroendocrine prostate cancer. Interrogation of human prostate cancer cohorts by Master Regulator (MR) conservation analysis revealed that most patients with advanced prostate cancer were represented by at least one cognate GEMM-derived tumor (GEMM-DT). Drugs predicted to invert MR activity in patients and their cognate GEMM-DTs were successfully validated in allograft, syngeneic, and patient-derived xenograft (PDX) models of tumors and metastasis. Furthermore, OncoLoop-predicted drugs enhanced the efficacy of clinically relevant drugs, namely, the PD-1 inhibitor nivolumab and the AR inhibitor enzalutamide.

SIGNIFICANCE

OncoLoop is a transcriptomic-based experimental and computational framework that can support rapid-turnaround coclinical studies to identify and validate drugs for individual patients, which can then be readily adapted to clinical practice. This framework should be applicable in many cancer contexts for which appropriate models and drug perturbation data are available. This article is highlighted in the In This Issue feature, p. 247.