In Vivo Mouse Models for Adult Brain Tumors: Exploring Tumorigenesis and Advancing Immunotherapy Development.

Brain tumors, particularly glioblastoma (GBM), are devastating and challenging to treat, with a low 5-year survival rate of only 6.6%. Mouse models are established to understand tumorigenesis and develop new therapeutic strategies. Large-scale genomic studies have facilitated the identification of genetic alterations driving human brain tumor development and progression. Genetically engineered mouse models (GEMMs) with clinically relevant genetic alterations are widely used to investigate tumor origin. Additionally, syngeneic implantation models, utilizing cell lines derived from GEMMs or other sources, are popular for their consistent and relatively short latency period, addressing various brain cancer research questions. In recent years, the success of immunotherapy in specific cancer types has led to a surge in cancer immunology-related research which specifically necessitates the utilization of immunocompetent mouse models. In this review, we provide a comprehensive summary of GEMMs and syngeneic mouse models for adult brain tumors, emphasizing key features such as model origin, genetic alteration background, oncogenic mechanisms, and immune-related characteristics. Our review serves as a valuable resource for the brain tumor research community, aiding in the selection of appropriate models to study cancer immunology.

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.

Unlocking the potential of flavonoids: Natural solutions in the fight against colon cancer.

Colorectal cancer (CRC) is a major cause of cancer-related deaths worldwide, underscoring the importance of understanding the diverse molecular and genetic underpinnings of CRC to improve its diagnosis, prognosis, and treatment. This review delves into the adenoma-carcinoma-metastasis model, emphasizing the "APC-KRAS-TP53" signature events in CRC development. CRC is categorized into four consensus molecular subtypes, each characterized by unique genetic alterations and responses to therapy, illustrating its complexity and heterogeneity. Furthermore, we explore the role of chronic inflammation and the gut microbiome in CRC progression, emphasizing the potential of targeting these factors for prevention and treatment. This review discusses the impact of dietary carcinogens and lifestyle factors and the critical role of early detection in improving outcomes, and also examines conventional chemotherapy options for CRC and associated challenges. There is significant focus on the therapeutic potential of flavonoids for CRC management, discussing various types of flavonoids, their sources, and mechanisms of action, including their antioxidant properties, modulation of cell signaling pathways, and effects on cell cycle and apoptosis. This article presents evidence of the synergistic effects of flavonoids with conventional cancer therapies and their role in modulating the gut microbiome and immune response, thereby offering new avenues for CRC treatment. We conclude by emphasizing the importance of a multidisciplinary approach to CRC research and treatment, incorporating insights from genetic, molecular, and lifestyle factors. Further research is needed on the preventive and therapeutic potential of natural compounds, such as flavonoids, in CRC, underscoring the need for personalized and targeted treatment strategies.

Targeting inflammatory factors for chemoprevention and cancer interception to tackle malignant mesothelioma.

Mesothelioma is an incurable cancer of the mesothelial lining often caused by exposure to asbestos. Asbestos-induced inflammation is a significant contributing factor in the development of mesothelioma, and genetic factors also play a role in the susceptibility to this rapidly progressive and treatment-resistant malignancy. Consequently, novel approaches are urgently needed to treat mesothelioma and prevent or reduce the overall incidence of this fatal disease. In this research perspective, we review the current state of chemoprevention and cancer interception progress in asbestos-induced mesothelioma. We discuss the different preclinical mouse models used for these investigations and the inflammatory factors that may be potential targets for mesothelioma prevention. Preliminary studies with naturally occurring phytochemicals and synthetic agents are reviewed. Results of previous clinical chemoprevention trials in populations exposed to asbestos and considerations regarding future trials are also presented.

Genetic Deletion of Galectin-3 Inhibits Pancreatic Cancer Progression and Enhances the Efficacy of Immunotherapy.

BACKGROUND & AIMS: Pancreatic ductal adenocarcinoma (PDAC) has a desmoplastic tumor stroma and immunosuppressive microenvironment. Galectin-3 (GAL3) is enriched in PDAC, highly expressed by cancer cells and myeloid cells. However, the functional roles of GAL3 in the PDAC microenvironment remain elusive. METHODS: We generated a novel transgenic mouse model (LSL-KrasG12D/+;Trp53loxP/loxP;Pdx1-Cre;Lgals3-/- [KPPC;Lgals3-/-]) that allows the genetic depletion of GAL3 from both cancer cells and myeloid cells in spontaneous PDAC formation. Single-cell RNA-sequencing analysis was used to identify the alterations in the tumor microenvironment upon GAL3 depletion. We investigated both the cancer cell-intrinsic function and immunosuppressive function of GAL3. We also evaluated the therapeutic efficacy of GAL3 inhibition in combination with immunotherapy. RESULTS: Genetic deletion of GAL3 significantly inhibited the spontaneous pancreatic tumor progression and prolonged the survival of KPPC;Lgals3-/- mice. Single-cell analysis revealed that genetic deletion of GAL3 altered the phenotypes of immune cells, cancer cells, and other cell populations. GAL3 deletion significantly enriched the antitumor myeloid cell subpopulation with high major histocompatibility complex class II expression. We also identified that GAL3 depletion resulted in CXCL12 upregulation, which could act as a potential compensating mechanism on GAL3 deficiency. Combined inhibition of the CXCL12-CXCR4 axis and GAL3 enhanced the efficacy of anti-PD-1 immunotherapy, leading to significantly inhibited PDAC progression. In addition, deletion of GAL3 also inhibited the basal/mesenchymal-like phenotype of pancreatic cancer cells. CONCLUSIONS: GAL3 promotes PDAC progression and immunosuppression via both cancer cell-intrinsic and immune-related mechanisms. Combined treatment targeting GAL3, CXCL12-CXCR4 axis, and PD-1 represents a novel therapeutic strategy for PDAC.

Colorectal cancer murine models: Initiation to metastasis.

Despite significant advancements in prevention and treatment, colorectal cancer (CRC) remains the third leading cause of cancer-related deaths. Animal models, including xenografts, syngeneic, and genetically engineered, have emerged as indispensable tools in cancer research. These models offer a valuable platform to address critical questions regarding molecular pathogenesis and test therapeutic interventions before moving on to clinical trials. Advancements in CRC animal models have also facilitated the advent of personalized and precision medicine. Patient-derived xenografts and genetically engineered mice that mirror features of human tumors allow for tailoring treatments to specific CRC subtypes, improving treatment outcomes and quality of life. To overcome the limitations of individual model systems, recent studies have employed a multi-modal approach, combining different animal models, 3D organoids, and in vitro studies. This integrative approach provides a comprehensive understanding of CRC biology, including the tumor microenvironment and therapeutic responses, driving the development of more effective and personalized therapeutic interventions. This review discusses the animal models used for CRC research, including recent advancements and limitations of these animal models.

Applying deep learning to segmentation of murine lung tumors in pre-clinical micro-computed tomography.

Lung cancer remains a leading cause of cancer-related death, but scientists have made great strides in developing new treatments recently, partly owing to the use of genetically engineered mouse models (GEMMs). GEMM tumors represent a translational model that recapitulates human disease better than implanted models because tumors develop spontaneously in the lungs. However, detection of these tumors relies on in vivo imaging tools, specifically micro-Computed Tomography (micro-CT or µCT), and image analysis can be laborious with high inter-user variability. Here we present a deep learning model trained to perform fully automated segmentation of lung tumors without the interference of other soft tissues. Trained and tested on 100 3D µCT images (18,662 slices) that were manually segmented, the model demonstrated a high correlation to manual segmentations on the testing data (r2=0.99, DSC=0.78) and on an independent dataset (n = 12 3D scans or 2328 2D slices, r2=0.97, DSC=0.73). In a comparison against manual segmentation performed by multiple analysts, the model (r2=0.98, DSC=0.78) performed within inter-reader variability (r2=0.79, DSC=0.69) and close to intra-reader variability (r2=0.99, DSC=0.82), all while completing 5+ hours of manual segmentations in 1 minute. Finally, when applied to a real-world longitudinal study (n = 55 mice), the model successfully detected tumor progression over time and the differences in tumor burden between groups induced with different virus titers, aligning well with more traditional analysis methods. In conclusion, we have developed a deep learning model which can perform fast, accurate, and fully automated segmentation of µCT scans of murine lung tumors.

Modeling the crosstalk between malignant B cells and their microenvironment in B-cell lymphomas: challenges and opportunities.

B-cell lymphomas are a group of heterogeneous neoplasms resulting from the clonal expansion of mature B cells arrested at various stages of differentiation. Specifically, two lymphoma subtypes arise from germinal centers (GCs), namely follicular lymphoma (FL) and GC B-cell diffuse large B-cell lymphoma (GCB-DLBCL). In addition to recent advances in describing the genetic landscape of FL and GCB-DLBCL, tumor microenvironment (TME) has progressively emerged as a central determinant of early lymphomagenesis, subclonal evolution, and late progression/transformation. The lymphoma-supportive niche integrates a dynamic and coordinated network of immune and stromal cells defining microarchitecture and mechanical constraints and regulating tumor cell migration, survival, proliferation, and immune escape. Several questions are still unsolved regarding the interplay between lymphoma B cells and their TME, including the mechanisms supporting these bidirectional interactions, the impact of the kinetic and spatial heterogeneity of the tumor niche on B-cell heterogeneity, and how individual genetic alterations can trigger both B-cell intrinsic and B-cell extrinsic signals driving the reprogramming of non-malignant cells. Finally, it is not clear whether these interactions might promote resistance to treatment or, conversely, offer valuable therapeutic opportunities. A major challenge in addressing these questions is the lack of relevant models integrating tumor cells with specific genetic hits, non-malignant cells with adequate functional properties and organization, extracellular matrix, and biomechanical forces. We propose here an overview of the 3D in vitro models, xenograft approaches, and genetically-engineered mouse models recently developed to study GC B-cell lymphomas with a specific focus on the pros and cons of each strategy in understanding B-cell lymphomagenesis and evaluating new therapeutic strategies.

Neurofibromatosis Type 1-Associated Optic Pathway Gliomas: Current Challenges and Future Prospects.

Optic pathway glioma (OPG) occurs in as many as one-fifth of individuals with the neurofibromatosis type 1 (NF1) cancer predisposition syndrome. Generally considered low-grade and slow growing, many children with NF1-OPGs remain asymptomatic. However, due to their location within the optic pathway, ~20-30% of those harboring NF1-OPGs will experience symptoms, including progressive vision loss, proptosis, diplopia, and precocious puberty. While treatment with conventional chemotherapy is largely effective at attenuating tumor growth, it is not clear whether there is much long-term recovery of visual function. Additionally, because these tumors predominantly affect young children, there are unique challenges to NF1-OPG diagnosis, monitoring, and longitudinal management. Over the past two decades, the employment of authenticated genetically engineered Nf1-OPG mouse models have provided key insights into the function of the NF1 protein, neurofibromin, as well as the molecular and cellular pathways that contribute to optic gliomagenesis. Findings from these studies have resulted in the identification of new molecular targets whose inhibition blocks murine Nf1-OPG growth in preclinical studies. Some of these promising compounds have now entered into early clinical trials. Future research focused on defining the determinants that underlie optic glioma initiation, expansion, and tumor-induced optic nerve injury will pave the way to personalized risk assessment strategies, improved tumor monitoring, and optimized treatment plans for children with NF1-OPG.

Translational Models in Glioma Immunotherapy Research.

Immunotherapy is a promising therapeutic domain for the treatment of gliomas. However, clinical trials of various immunotherapeutic modalities have not yielded significant improvements in patient survival. Preclinical models for glioma research should faithfully represent clinically observed features regarding glioma behavior, mutational load, tumor interactions with stromal cells, and immunosuppressive mechanisms. In this review, we dive into the common preclinical models used in glioma immunology, discuss their advantages and disadvantages, and highlight examples of their utilization in translational research.

In vivo models of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with high mortality rate. Within the next decade, PDAC is projected to become the second leading cause of cancer-associated death in the United States. Understanding the pathophysiology of PDAC tumorigenesis and metastases is crucial toward developing new therapeutics. One of the challenges in cancer research is generating in vivo models that closely recapitulate the genomic, histological, and clinical characteristics of human tumors. An ideal model for PDAC not only captures the tumor and stromal environment of human disease, but also allows for mutational control and is easy to reproduce in terms of time and cost. In this review, we highlight evolution of in vivo models for PDAC including spontaneous tumors models (i.e., chemical induction, genetic modification, viral delivery), implantation models including patient derived xenografts (PDX), and humanized PDX. We discuss the implementation of each system and evaluate the benefits and shortcomings of these models. Overall, this review provides a broad overview of prior and current techniques of in vivo PDAC modeling and their associated challenges.

Cell specificity of Manganese-enhanced MRI signal in the cerebellum.

Magnetic Resonance Imaging (MRI) resolution continues to improve, making it important to understand the cellular basis for different MRI contrast mechanisms. Manganese-enhanced MRI (MEMRI) produces layer-specific contrast throughout the brain enabling in vivo visualization of cellular cytoarchitecture, particularly in the cerebellum. Due to the unique geometry of the cerebellum, especially near the midline, 2D MEMRI images can be acquired from a relatively thick slice by averaging through areas of uniform morphology and cytoarchitecture to produce very high-resolution visualization of sagittal planes. In such images, MEMRI hyperintensity is uniform in thickness throughout the anterior-posterior axis of sagittal sections and is centrally located in the cerebellar cortex. These signal features suggested that the Purkinje cell layer, which houses the cell bodies of the Purkinje cells and the Bergmann glia, is the source of hyperintensity. Despite this circumstantial evidence, the cellular source of MRI contrast has been difficult to define. In this study, we quantified the effects of selective ablation of Purkinje cells or Bergmann glia on cerebellar MEMRI signal to determine whether signal could be assigned to one cell type. We found that the Purkinje cells, not the Bergmann glia, are the primary of source of the enhancement in the Purkinje cell layer. This cell-ablation strategy should be useful for determining the cell specificity of other MRI contrast mechanisms.

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.

Mass Spectrometry-Based Tissue Imaging of the Tumor Microenvironment.

Multiplex ion beam imaging (MIBI) and imaging mass cytometry (IMC) enable highly multiplexed antibody (40+) staining of frozen or formalin fixed, paraffin-embedded (FFPE) human or murine tissues through detection of metal ions liberated from primary antibodies by time-of-flight mass spectrometry (TOF). These methods make detection of more than 50 targets theoretically possible while maintaining spatial orientation. As such, they are ideal tools to identify the multiple immune, epithelial, and stromal cell subsets in the tumor microenvironment and to characterize spatial relationships and tumor-immune status in either murine models or human samples. This chapter summarizes methods for antibody conjugation and validation, staining, and preliminary data collection using IMC or MIBI in both human and mouse pancreatic adenocarcinoma samples. These protocols are intended to facilitate use of these complex platforms in not only tissue-based tumor immunology studies but also tissue-based oncology or immunology studies more broadly.

Specific Targeting and Labeling of Colonic Polyps in CPC-APC Mice with Mucin 5AC Fluorescent Antibodies: A Model for Detection of Early Colon Cancer.

Poor visualization of polyps can limit colorectal cancer screening. Fluorescent antibodies to mucin5AC (MUC5AC), a glycoprotein upregulated in adenomas and colorectal cancer, could improve screening colonoscopy polyp detection rate. Adenomatous polyposis coli flox mice with a Cdx2-Cre transgene (CPC-APC) develop colonic polyps that contain both dysplastic and malignant tissue. Mice received MUC5AC-IR800 or IRdye800 as a control IV and were sacrificed after 48 h for near-infrared imaging of their colons. A polyp-to-background ratio (PBR) was calculated for each polyp by dividing the mean fluorescence intensity of the polyp by the mean fluorescence intensity of the background tissue. The mean 25 µg PBR was 1.70 (±0.56); the mean 50 µg PBR was 2.64 (±0.97); the mean 100 µg PBR was 3.32 (±1.33); and the mean 150 µg PBR was 3.38 (±0.87). The mean PBR of the dye-only control was 2.22 (±1.02), significantly less than the 150 µg arm (p-value 0.008). The present study demonstrates the ability of fluorescent anti-MUC5AC antibodies to specifically target and label colonic polyps containing high-grade dysplasia and intramucosal adenocarcinoma in CPC-APC mice. This technology can potentially improve the detection rate and decrease the miss rate of advanced colonic neoplasia and early cancer at colonoscopy.

Cross-Dataset Single-Cell Analysis Identifies Temporal Alterations in Cell Populations of Primary Pancreatic Tumor and Liver Metastasis.

Pancreatic ductal adenocarcinoma (PDAC) has a unique tumor microenvironment composed of various cell populations such as cancer cells, cancer-associated fibroblasts (CAFs), immune cells, and endothelial cells. Recently, single-cell RNA-sequencing analysis (scRNA-seq) has systemically revealed the genomic profiles of these cell populations in PDAC. However, the direct comparison of cell population composition and genomic profile between primary tumors (at both early- and late-stage) and metastatic tumors of PDAC is still lacking. In this study, we combined and analyzed recent scRNA-seq datasets of transgenic KPC mouse models with autochthonous PDAC and matched liver metastasis, revealing the unique tumor ecosystem and cell composition of liver metastasis in contrast to primary PDAC. Metastatic PDAC tumors harbor distinct cancer cell subpopulations from primary tumors. Several unique markers, including HMGA1, were identified for metastasis-enriched cancer cell subpopulations. Furthermore, metastatic tumors reveal significantly enriched granulocytic myeloid-derived suppressor cells (G-MDSCs), mature neutrophils, and granulocyte-myeloid progenitors (GMPs). A common GMP population across primary tumors, liver metastases, and healthy bone marrow was identified as the putative cell origin of tumor-associated neutrophils/granulocytes.

Distinct mesenchymal cell states mediate prostate cancer progression.

Alterations in tumor stroma influence prostate cancer progression and metastatic potential. However, the molecular underpinnings of this stromal-epithelial crosstalk are largely unknown. Here, we compare mesenchymal cells from four genetically engineered mouse models (GEMMs) of prostate cancer representing different stages of the disease to their wild-type (WT) counterparts by single-cell RNA sequencing (scRNA-seq) and, ultimately, to human tumors with comparable genotypes. We identified 8 transcriptionally and functionally distinct stromal populations responsible for common and GEMM-specific transcriptional programs. We show that stromal responses are conserved in mouse models and human prostate cancers with the same genomic alterations. We noted striking similarities between the transcriptional profiles of the stroma of murine models of advanced disease and those of of human prostate cancer bone metastases. These profiles were then used to build a robust gene signature that can predict metastatic progression in prostate cancer patients with localized disease and is also associated with progression-free survival independent of Gleason score. Taken together, this offers new evidence that stromal microenvironment mediates prostate cancer progression, further identifying tissue-based biomarkers and potential therapeutic targets of aggressive and metastatic disease.

Tumor-Suppressive Functions of the Aryl Hydrocarbon Receptor (AhR) and AhR as a Therapeutic Target in Cancer.

The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor involved in regulating a wide range of biological responses. A diverse array of xenobiotics and endogenous small molecules bind to the receptor and drive unique phenotypic responses. Due in part to its role in mediating toxic responses to environmental pollutants, AhR activation has not been traditionally viewed as a viable therapeutic approach. Nonetheless, the expression and activation of AhR can inhibit the proliferation, migration, and survival of cancer cells, and many clinically approved drugs transcriptionally activate AhR. Identification of novel select modulators of AhR-regulated transcription that promote tumor suppression is an active area of investigation. The development of AhR-targeted anticancer agents requires a thorough understanding of the molecular mechanisms driving tumor suppression. Here, we summarized the tumor-suppressive mechanisms regulated by AhR with an emphasis on the endogenous functions of the receptor in opposing carcinogenesis. In multiple different cancer models, the deletion of AhR promotes increased tumorigenesis, but a precise understanding of the molecular cues and the genetic targets of AhR involved in this process is lacking. The intent of this review was to synthesize the evidence supporting AhR-dependent tumor suppression and distill insights for development of AhR-targeted cancer therapeutics.

Visualizing WNT signaling in mammalian systems.

WNT/CTNNB1 signaling plays a critical role in the development of all multicellular animals. Here, we include both the embryonic stages, during which tissue morphogenesis takes place, and the postnatal stages of development, during which tissue homeostasis occurs. Thus, embryonic development concerns lineage development and cell fate specification, while postnatal development involves tissue maintenance and regeneration. Multiple tools are available to researchers who want to investigate, and ideally visualize, the dynamic and pleiotropic involvement of WNT/CTNNB1 signaling in these processes. Here, we discuss and evaluate the decisions that researchers need to make in identifying the experimental system and appropriate tools for the specific question they want to address, covering different types of WNT/CTNNB1 reporters in cells and mice. At a molecular level, advanced quantitative imaging techniques can provide spatio-temporal information that cannot be provided by traditional biochemical assays. We therefore also highlight some recent studies to show their potential in deciphering the complex and dynamic mechanisms that drive WNT/CTNNB1 signaling.

Nuclear PTEN's Functions in Suppressing Tumorigenesis: Implications for Rare Cancers.

Phosphatase and tensin homolog (PTEN) encodes a tumor-suppressive phosphatase with both lipid and protein phosphatase activity. The tumor-suppressive functions of PTEN are lost through a variety of mechanisms across a wide spectrum of human malignancies, including several rare cancers that affect pediatric and adult populations. Originally discovered and characterized as a negative regulator of the cytoplasmic, pro-oncogenic phosphoinositide-3-kinase (PI3K) pathway, PTEN is also localized to the nucleus where it can exert tumor-suppressive functions in a PI3K pathway-independent manner. Cancers can usurp the tumor-suppressive functions of PTEN to promote oncogenesis by disrupting homeostatic subcellular PTEN localization. The objective of this review is to describe the changes seen in PTEN subcellular localization during tumorigenesis, how PTEN enters the nucleus, and the spectrum of impacts and consequences arising from disrupted PTEN nuclear localization on tumor promotion. This review will highlight the immediate need in understanding not only the cytoplasmic but also the nuclear functions of PTEN to gain more complete insights into how important PTEN is in preventing human cancers.