Search Results (41)

Radon (Rn) exposure has a strong association with lung cancer risk and is influenced by epigenetic modifications. To investigate the characterization of DNA methylation (DNAm) episignatures for radon-induced lung cancer, we detected the specific changes in DNAm in blood and lung tissues using reduced representation bisulfite sequencing (RRBS). We identified the differentially methylated regions (DMRs) induced by radon exposure. The bioinformatics analysis of the DMR-mapped genes revealed that pathways in cancer were affected by radon exposure. Among them, the DNAm episignatures of MAPK10, PLCG1, PLCβ3 and PIK3R2 were repeated between lung tissue and blood, and validated by the MassArray. In addition, radon exposure promoted lung cancer development in the genetic engineering mouse model (GEMM), accompanied by decreased MAPK10 and increased PLCG1, PLCβ3, and PIK3R2 with mRNA and protein levels. Conclusively, radon exposure significantly changes the genomic DNAm patterns in lung tissue and blood. The DNAm episignatures of MAPK10, PLCG1, PLCβ3 and PIK3R2 have a significant influence on radon-induced lung cancer. This brings a new perspective to understanding the pathways involved in radon-induced lung cancer and offers potential targets for developing blood-based biomarkers and epigenetic therapeutics. Full article

Pediatric high-grade gliomas (pHGGs), particularly diffuse midline gliomas (DMGs), are among the most lethal brain tumors due to poor survival and resistance to therapies. DMGs possess a distinct genetic profile, primarily driven by hallmark mutations such as H3K27M, ACVR1, and PDGFRA mutations/amplifications and TP53 inactivation, all of which contribute to tumor biology and therapeutic resistance. Developing physiologically relevant preclinical models that replicate both tumor biology and the tumor microenvironment (TME) is critical for advancing effective treatments. This review highlights recent progress in in vitro, ex vivo, and in vivo models, including patient-derived brain organoids, genetically engineered mouse models (GEMMs), and region-specific midline organoids incorporating SHH, BMP, and FGF2/8/19 signaling to model pontine gliomas. Key genetic alterations can now be introduced using lipofectamine-mediated transfection, PiggyBac plasmid systems, and CRISPR-Cas9, allowing the precise study of tumor initiation, progression, and therapy resistance. These models enable the investigation of TME interactions, including immune responses, neuronal infiltration, and therapeutic vulnerabilities. Future advancements involve developing immune-competent organoids, integrating vascularized networks, and applying multi-omics platforms like single-cell RNA sequencing and spatial transcriptomics to dissect tumor heterogeneity and lineage-specific vulnerabilities. These innovative approaches aim to enhance drug screening, identify new therapeutic targets, and accelerate personalized treatments for pediatric gliomas. Full article

Pancreatic cancer is characterized by late diagnosis, therapy resistance, and poor prognosis, necessitating the exploration of early carcinogenesis and prevention methods. Preclinical mouse models have evolved from cell line-based to human tumor tissue- or organoid-derived xenografts, now to humanized mouse models and genetically engineered mouse models (GEMMs). GEMMs, primarily driven by oncogenic Kras mutations and tumor suppressor gene alterations, offer a realistic platform for investigating pancreatic cancer initiation, progression, and metastasis. The incorporation of inducible somatic mutations and CRISPR-Cas9 screening methods has expanded their utility. To better recapitulate tumor initiation triggered by inflammatory cues, common pancreatic risk factors are being integrated into model designs. This approach aims to decipher the role of environmental factors as secondary or parallel triggers of tumor initiation alongside oncogenic burdens. Emerging models exploring pancreatitis, obesity, diabetes, and other risk factors offer significant translational potential. This review describes current mouse models for studying pancreatic carcinogenesis, their combination with inflammatory factors, and their utility in evaluating pathogenesis, providing guidance for selecting the most suitable models for pancreatic cancer research. Full article

Breast cancer (BC) is among the most common neoplasms globally and is the leading cause of cancer-related mortality in women. Despite significant advancements in prevention, early diagnosis, and treatment strategies made over the past two decades, breast cancer continues to pose a significant global health challenge. One of the major obstacles in the clinical management of breast cancer patients is the high intertumoral and intratumoral heterogeneity that influences disease progression and therapeutic outcomes. The inability of preclinical experimental models to replicate this diversity has hindered the comprehensive understanding of BC pathogenesis and the development of new therapeutic strategies. An ideal experimental model must recapitulate every aspect of human BC to maintain the highest predictive validity. Therefore, a thorough understanding of each model’s inherent characteristics and limitations is essential to bridging the gap between basic research and translational medicine. In this context, omics technologies serve as powerful tools for establishing comparisons between experimental models and human tumors, which may help address BC heterogeneity and vulnerabilities. This review examines the BC models currently used in preclinical research, including cell lines, patient-derived organoids (PDOs), organ-on-chip technologies, carcinogen-induced mouse models, genetically engineered mouse models (GEMMs), and xenograft mouse models. We emphasize the advantages and disadvantages of each model and outline the most important applications of omics techniques to aid researchers in selecting the most relevant model to address their specific research questions. Full article

Patient-centered precision oncology strives to deliver individualized cancer care. In lung cancer, preclinical models and technological innovations have become critical in advancing this approach. Preclinical models enable deeper insights into tumor biology and enhance the selection of appropriate systemic therapies across chemotherapy, targeted therapies, immunotherapies, antibody–drug conjugates, and emerging investigational treatments. While traditional human lung cancer cell lines offer a basic framework for cancer research, they often lack the tumor heterogeneity and intricate tumor–stromal interactions necessary to accurately predict patient-specific clinical outcomes. Patient-derived xenografts (PDXs), however, retain the original tumor’s histopathology and genetic features, providing a more reliable model for predicting responses to systemic therapeutics, especially molecularly targeted therapies. For studying immunotherapies and antibody–drug conjugates, humanized PDX mouse models, syngeneic mouse models, and genetically engineered mouse models (GEMMs) are increasingly utilized. Despite their value, these in vivo models are costly, labor-intensive, and time-consuming. Recently, patient-derived lung cancer organoids (LCOs) have emerged as a promising in vitro tool for functional precision oncology studies. These LCOs demonstrate high success rates in growth and maintenance, accurately represent the histology and genomics of the original tumors and exhibit strong correlations with clinical treatment responses. Further supported by advancements in imaging, spatial and single-cell transcriptomics, proteomics, and artificial intelligence, these preclinical models are reshaping the landscape of drug development and functional precision lung cancer research. This integrated approach holds the potential to deliver increasingly accurate, personalized treatment strategies, ultimately enhancing patient outcomes in lung cancer. Full article

Familial pancreatic cancer (FPC) represents a significant yet underexplored area in pancreatic cancer research. Basic research efforts are notably limited, and when present, they are predominantly centered on the BRCA1 and BRCA2 mutations due to the scarcity of other genetic variants associated with FPC, leading to a limited understanding of the broader genetic landscape of FPC. This review examines the current state of FPC research, focusing on the molecular mechanisms driving pancreatic ductal adenocarcinoma (PDAC) progression. It highlights the role of homologous recombination (HR) and its therapeutic exploitation via synthetic lethality with PARP inhibitors in BRCA1/2-deficient tumors. The review discusses various pre-clinical models of FPC, including conventional two-dimensional (2D) cell lines, patient-derived organoids (PDOs), patient-derived xenografts (PDXs), and genetically engineered mouse models (GEMMs), as well as new advancements in FPC research. Full article

Pediatric high-grade gliomas (pHGG) are malignant and usually fatal central nervous system (CNS) WHO Grade 4 tumors. The majority of pHGG consist of diffuse midline gliomas (DMG), H3.3 or H3.1 K27 altered, or diffuse hemispheric gliomas (DHG) (H3.3 G34-mutant). Due to diffuse tumor infiltration of eloquent brain areas, especially for DMG, surgery has often been limited and chemotherapy has not been effective, leaving fractionated radiation to the involved field as the current standard of care. pHGG has only been classified as molecularly distinct from adult HGG since 2012 through Next-Generation sequencing approaches, which have shown pHGG to be epigenetically regulated and specific tumor sub-types to be representative of dysregulated differentiating cells. To translate discovery research into novel therapies, improved pre-clinical models that more adequately represent the tumor biology of pHGG are required. This review will summarize the molecular characteristics of different pHGG sub-types, with a specific focus on histone K27M mutations and the dysregulated gene expression profiles arising from these mutations. Current and emerging pre-clinical models for pHGG will be discussed, including commonly used patient-derived cell lines and in vivo modeling techniques, encompassing patient-derived xenograft murine models and genetically engineered mouse models (GEMMs). Lastly, emerging techniques to model CNS tumors within a human brain environment using brain organoids through co-culture will be explored. As models that more reliably represent pHGG continue to be developed, targetable biological and genetic vulnerabilities in the disease will be more rapidly identified, leading to better treatments and improved clinical outcomes. Full article

Pancreatic ductal adenocarcinoma (PDAC) is a devastating malignant disease with a dismal prognosis. In the past decades, a plethora of genetically engineered mouse models (GEMMs) with autochthonous pancreatic tumor development have greatly facilitated studies of pancreatic cancer. Commonly used GEMMs of PDAC often harbor the oncogenic KRAS driver mutation (Kras^G12D), in combination with either p53 mutation by knock-in strategy (Trp53^R172H) or p53 loss by conditional knockout (Trp53^cKO) strategy, in pancreatic cell lineages. However, the systematic comparison of the tumor microenvironment between Kras^G12D; Trp53^R172H (KP^mut) mouse models and Kras^G12D; Trp53^cKO (KP^loss) mouse models is still lacking. In this study, we conducted cross-dataset single-cell RNA-sequencing (scRNA-seq) analyses to compare the pancreatic tumor microenvironment from KP^mut mouse models and KP^loss mouse models, especially focusing on the cell compositions and transcriptomic phenotypes of major cell types including cancer cells, B cells, T cells, granulocytes, myeloid cells, cancer-associated fibroblasts, and endothelial cells. We identified the similarities and differences between KP^mut and KP^loss mouse models, revealing the effects of p53 mutation and p53 loss on oncogenic KRAS-driven pancreatic tumor progression. Full article

The ability to create genetically engineered mouse models (GEMMs) has exponentially increased our understanding of many areas of biology. Musculoskeletal biology is no exception. In this review, we will first discuss the historical development of GEMMs and how these developments have influenced musculoskeletal disease research. This review will also update our 2008 review that appeared in BONEKey, a journal that is no longer readily available online. We will first review the historical development of GEMMs in general, followed by a particular emphasis on the ability to perform tissue-specific (conditional) knockouts focusing on musculoskeletal tissues. We will then discuss how the development of CRISPR/Cas-based technologies during the last decade has revolutionized the generation of GEMMs. Full article

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. Full article

Atrx loss was recently ascertained as insufficient to drive pancreatic neuroendocrine tumour (PanNET) formation in mice islets. We have identified a preponderant role of Atrx in the endocrine dysfunction in a Rip-Cre;Atrx^KO genetically engineered mouse model (GEMM). To validate the impact of a different Cre-driver line, we used similar methodologies and characterised the Pdx1-Cre;Atrx^KO (P.Atrx^KO) GEMM to search for PanNET formation and endocrine fitness disruption for a period of up to 24 months. Male and female mice presented different phenotypes. Compared to P.Atrx^WT, P.Atrx^HOM males were heavier during the entire study period, hyperglycaemic between 3 and 12 mo., and glucose intolerant only from 6 mo.; in contrast, P.Atrx^HOM females started exhibiting increased weight gains later (after 6 mo.), but diabetes or glucose intolerance was detected by 3 mo. Overall, all studied mice were overweight or obese from early ages, which challenged the histopathological evaluation of the pancreas and liver, especially after 12 mo. Noteworthily, losing Atrx predisposed mice to an increase in intrapancreatic fatty infiltration (FI), peripancreatic fat deposition, and macrovesicular steatosis. As expected, no animal developed PanNETs. An obese diabetic GEMM of disrupted Atrx is presented as potentially useful for metabolic studies and as a putative candidate for inserting additional tumourigenic genetic events. Full article

Preclinical imaging is a critical component in translational research with significant complexities in workflow and site differences in deployment. Importantly, the National Cancer Institute’s (NCI) precision medicine initiative emphasizes the use of translational co-clinical oncology models to address the biological and molecular bases of cancer prevention and treatment. The use of oncology models, such as patient-derived tumor xenografts (PDX) and genetically engineered mouse models (GEMMs), has ushered in an era of co-clinical trials by which preclinical studies can inform clinical trials and protocols, thus bridging the translational divide in cancer research. Similarly, preclinical imaging fills a translational gap as an enabling technology for translational imaging research. Unlike clinical imaging, where equipment manufacturers strive to meet standards in practice at clinical sites, standards are neither fully developed nor implemented in preclinical imaging. This fundamentally limits the collection and reporting of metadata to qualify preclinical imaging studies, thereby hindering open science and impacting the reproducibility of co-clinical imaging research. To begin to address these issues, the NCI co-clinical imaging research program (CIRP) conducted a survey to identify metadata requirements for reproducible quantitative co-clinical imaging. The enclosed consensus-based report summarizes co-clinical imaging metadata information (CIMI) to support quantitative co-clinical imaging research with broad implications for capturing co-clinical data, enabling interoperability and data sharing, as well as potentially leading to updates to the preclinical Digital Imaging and Communications in Medicine (DICOM) standard. Full article

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. Full article

Genetically engineered mouse models (GEMMs) and patient-derived xenograft mouse models (PDXs) can recapitulate important biological features of cancer. They are often part of precision medicine studies in a co-clinical setting, in which therapeutic investigations are conducted in patients and in parallel (or sequentially) in cohorts of GEMMs or PDXs. Employing radiology-based quantitative imaging in these studies allows in vivo assessment of disease response in real time, providing an important opportunity to bridge precision medicine from the bench to the bedside. The Co-Clinical Imaging Research Resource Program (CIRP) of the National Cancer Institute focuses on the optimization of quantitative imaging methods to improve co-clinical trials. The CIRP supports 10 different co-clinical trial projects, spanning diverse tumor types, therapeutic interventions, and imaging modalities. Each CIRP project is tasked to deliver a unique web resource to support the cancer community with the necessary methods and tools to conduct co-clinical quantitative imaging studies. This review provides an update of the CIRP web resources, network consensus, technology advances, and a perspective on the future of the CIRP. The presentations in this special issue of Tomography were contributed by the CIRP working groups, teams, and associate members. Full article

The availability of high-fidelity animal models for oncology research has grown enormously in recent years, enabling preclinical studies relevant to prevention, diagnosis, and treatment of cancer to be undertaken. This has led to increased opportunities to conduct co-clinical trials, which are studies on patients that are carried out parallel to or sequentially with animal models of cancer that mirror the biology of the patients’ tumors. Patient-derived xenografts (PDX) and genetically engineered mouse models (GEMM) are considered to be the models that best represent human disease and have high translational value. Notably, one element of co-clinical trials that still needs significant optimization is quantitative imaging. The National Cancer Institute has organized a Co-Clinical Imaging Resource Program (CIRP) network to establish best practices for co-clinical imaging and to optimize translational quantitative imaging methodologies. This overview describes the ten co-clinical trials of investigators from eleven institutions who are currently supported by the CIRP initiative and are members of the Animal Models and Co-clinical Trials (AMCT) Working Group. Each team describes their corresponding clinical trial, type of cancer targeted, rationale for choice of animal models, therapy, and imaging modalities. The strengths and weaknesses of the co-clinical trial design and the challenges encountered are considered. The rich research resources generated by the members of the AMCT Working Group will benefit the broad research community and improve the quality and translational impact of imaging in co-clinical trials. Full article