The mighty mouse: genetically engineered mouse models in cancer drug development

Lipids as Regulators of Cellular Senescence

Lipids are key macromolecules that perform a multitude of biological functions ranging from maintaining structural integrity of membranes, energy storage, to signaling molecules. Unsurprisingly, variations in lipid composition and its levels can influence the functional and physiological state of the cell and its milieu. Cellular senescence is a permanent state of cell cycle arrest and is a hallmark of the aging process, as well as several age-related pathologies. Senescent cells are often characterized by alterations in morphology, metabolism, chromatin remodeling and exhibit a complex pro-inflammatory secretome (SASP). Recent studies have shown that the regulation of specific lipid species play a critical role in senescence. Indeed, some lipid species even contribute to the low-grade inflammation associated with SASP. Many protein regulators of senescence have been well characterized and are associated with lipid metabolism. However, the link between critical regulators of cellular senescence and senescence-associated lipid changes is yet to be elucidated. Here we systematically review the current knowledge on lipid metabolism and dynamics of cellular lipid content during senescence. We focus on the roles of major players of senescence in regulating lipid metabolism. Finally, we explore the future prospects of lipid research in senescence and its potential to be targeted as senotherapeutics.

Synthetic Matrix Scaffolds Engineer the In Vivo Tumor Immune Microenvironment for Immunotherapy Screening

Immunotherapy has emerged as one of the most powerful anti-cancer therapies but is stymied by the limits of existing preclinical models with respect to disease latency and reproducibility. Additionally, the influence of differing immune microenvironments within tumors observed clinically and associated with immunotherapeutic resistance cannot be tuned to facilitate drug testing workflows without changing model system or laborious genetic approaches. To address this testing platform gap in the immune oncology drug development pipeline, the authors deploy engineered biomaterials as scaffolds to increase tumor formation rate, decrease disease latency, and diminish variability of immune infiltrates into tumors formed from murine mammary carcinoma cell lines implanted into syngeneic mice. By altering synthetic gel formulations that reshape infiltrating immune cells within the tumor, responsiveness of the same tumor model to varying classes of cancer immunotherapies, including in situ vaccination with a molecular adjuvant and immune checkpoint blockade, diverge. These results demonstrate the significant role the local immune microenvironment plays in immunotherapeutic response. These engineered tumor immune microenvironments therefore improve upon the limitations of current breast tumor models used for immune oncology drug screening to enable immunotherapeutic testing relevant to the variability in tumor immune microenvironments underlying immunotherapeutic resistance seen in human patients.

Current hurdles to the translation of nanomedicines from bench to the clinic

The field of nanomedicine has significantly influenced research areas such as drug delivery, diagnostics, theranostics, and regenerative medicine; however, the further development of this field will face significant challenges at the regulatory level if related guidance remains unclear and unconsolidated. This review describes those features and pathways crucial to the clinical translation of nanomedicine and highlights considerations for early-stage product development. These include identifying those critical quality attributes of the drug product essential for activity and safety, appropriate analytical methods (physical, chemical, biological) for characterization, important process parameters, and adequate pre-clinical models. Additional concerns include the evaluation of batch-to-batch consistency and considerations regarding scaling up that will ensure a successful reproducible manufacturing process. Furthermore, we advise close collaboration with regulatory agencies from the early stages of development to assure an aligned position to accelerate the development of future nanomedicines.

Advances in Surface Enhanced Raman Spectroscopy for in Vivo Imaging in Oncology

In the last two decades, the application of surface enhanced Raman scattering (SERS) nanoparticles for preclinical cancer imaging has attracted increasing attention. Raman imaging with SERS nanoparticles offers unparalleled sensitivity, providing a platform for molecular targeting, and granting multiplexed and multimodal imaging capabilities. Recent progress has been facilitated not only by the optimization of the SERS contrast agents themselves, but also by the developments in Raman imaging approaches and instrumentation. In this article, we review the principles of Raman scattering and SERS, present advances in Raman instrumentation specific to cancer imaging, and discuss the biological means of ensuring selective in vivo uptake of SERS contrast agents for targeted, multiplexed, and multimodal imaging applications. We offer our perspective on areas that must be addressed in order to facilitate the clinical translation of SERS contrast agents for in vivo imaging in oncology.

Role of Senescence and Aging in SARS-CoV-2 Infection and COVID-19 Disease

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in a global pandemic associated with substantial morbidity and mortality worldwide, with particular risk for severe disease and mortality in the elderly population. SARS-CoV-2 infection is driven by a pathological hyperinflammatory response which results in a dysregulated immune response. Current advancements in aging research indicates that aging pathways have fundamental roles in dictating healthspan in addition to lifespan. Our review discusses the aging immune system and highlights that senescence and aging together, play a central role in COVID-19 pathogenesis. In our review, we primarily focus on the immune system response to SARS-CoV-2 infection, the interconnection between severe COVID-19, immunosenescence, aging, vaccination, and the emerging problem of Long-COVID. We hope to highlight the importance of identifying specific senescent endotypes (or "sendotypes"), which can used as determinants of COVID-19 severity and mortality. Indeed, identified sendotypes could be therapeutically exploited for therapeutic intervention. We highlight that senolytics, which eliminate senescent cells, can target aging-associated pathways and therefore are proving attractive as potential therapeutic options to alleviate symptoms, prevent severe infection, and reduce mortality burden in COVID-19 and thus ultimately enhance healthspan.

Spatial control of gene expression in flies using bacterially derived binary transactivation systems

Controlling gene expression is an instrumental tool for biotechnology, as it enables the dissection of gene function, affording precise spatial-temporal resolution. To generate this control, binary transactivational systems have been used employing a modular activator consisting of a DNA binding domain(s) fused to activation domain(s). For fly genetics, many binary transactivational systems have been exploited in vivo; however, as the study of complex problems often requires multiple systems that can be used in parallel, there is a need to identify additional bipartite genetic systems. To expand this molecular genetic toolbox, we tested multiple bacterially derived binary transactivational systems in Drosophila melanogaster including the p-CymR operon from Pseudomonas putida, PipR operon from Streptomyces coelicolor, TtgR operon from Pseudomonas putida and the VanR operon from Caulobacter crescentus. Our work provides the first characterization of these systems in an animal model in vivo. For each system, we demonstrate robust tissue-specific spatial transactivation of reporter gene expression, enabling future studies to exploit these transactivational systems for molecular genetic studies.

Influences of the 3D microenvironment on cancer cell behaviour and treatment responsiveness: A recent update on lung, breast and prostate cancer models

The majority of in vitro studies assessing cancer treatments are performed in two-dimensional (2D) monolayers and are subsequently validated in in vivo animal models. However, 2D models fail to accurately model the tumour microenvironment. Furthermore, animal models are not directly applicable to mimic the human scenario. Three-dimensional (3D) culture models may help to address the discrepancies of 2D and animal models. When cancer cells escape the primary tumour, they can invade at distant organs building secondary tumours, called metastasis. The development of metastasis leads to a dramatic decrease in the life expectancy of patients. Therefore, 3D systems to model the microenvironment of metastasis have also been developed. Several studies have demonstrated changes in cell behaviour and gene expression when cells are cultured in 3D compared to 2D and concluded a better comparability to cells in vivo. Of special importance is the effect seen in response to anti-cancer treatments as models are built primarily to serve as drug-testing platforms. This review highlights these changes between cancer cells grown in 2D and 3D models for some of the most common cancers including lung, breast and prostate tumours. In addition to models aiming to mimic the primary tumour site, the effects of 3D cell culturing in bone metastasis models are also described. STATEMENT OF SIGNIFICANCE: Most in vitro studies in cancer research are performed in 2D and are subsequently validated in in vivo animal models. However, both models possess numerous limitations: 2D models fail to accurately model the tumour microenvironment while animal models are expensive, time-consuming and can differ considerably from humans. It is accepted that the cancer microenvironment plays a critical role in the disease, thus, 3D models have been proposed as a potential solution to address the discrepancies of 2D and animal models. This review highlights changes in cell behaviour, including proliferation, gene expression and chemosensitivity, between cancer cells grown in 2D and 3D models for some of the most common cancers including lung, breast and prostate cancer as well as bone metastasis.

Mouse models of glioblastoma for the evaluation of novel therapeutic strategies

Glioblastoma (GBM) is an incurable brain tumor with a median survival of approximately 15 months despite an aggressive standard of care that includes surgery, chemotherapy, and ionizing radiation. Mouse models have advanced our understanding of GBM biology and the development of novel therapeutic strategies for GBM patients. However, model selection is crucial when testing developmental therapeutics, and each mouse model of GBM has unique advantages and disadvantages that can influence the validity and translatability of experimental results. To shed light on this process, we discuss the strengths and limitations of 3 types of mouse GBM models in this review: syngeneic models, genetically engineered mouse models, and xenograft models, including traditional xenograft cell lines and patient-derived xenograft models.

Drug discovery oncology in a mouse: concepts, models and limitations

The utilization of suitable mouse models is a critical step in the drug discovery oncology workflow as their generation and use are important for target identification and validation as well as toxicity and efficacy assessments. Current murine models have been instrumental in furthering insights into the mode of action of drugs before transitioning into the clinic. Recent advancements in genome editing with the development of the CRISPR/Cas9 system and the possibility of applying such technology directly in vivo have expanded the toolkit of preclinical models available. In this review, a brief presentation of the current models used in drug discovery will be provided with a particular emphasis on the novel CRISPR/Cas9 models.

Engineering chromosome rearrangements in cancer

The identification of large chromosomal rearrangements in cancers has multiplied exponentially over the last decade. These complex and often rare genomic events have traditionally been challenging to study, in part owing to lack of tools that efficiently engineer disease-associated inversions, deletions and translocations in model systems. The emergence and refinement of genome editing technologies, such as CRISPR, have significantly expanded our ability to generate and interrogate chromosomal aberrations to better understand the networks that govern cancer growth. Here we review how existing technologies are employed to faithfully model cancer-associated chromosome rearrangements in the laboratory, with the ultimate goal of developing more accurate pre-clinical models of and therapeutic strategies for cancers driven by these genomic events.

Summary: Chromosome rearrangements can be potent cancer drivers and effective therapeutic targets. Here, we review how genome-editing technologies can be exploited to engineer and study complex structural variants, and identify new treatment options.

Generation of a Tetracycline Regulated Mouse Model of MYC-Induced T-Cell Acute Lymphoblastic Leukemia

The tetracycline regulatory system provides a tractable strategy to interrogate the role of oncogenes in the initiation, maintenance, and regression of tumors through both spatial and temporal control of expression. This approach has several potential advantages over conventional methods to generate genetically engineered mouse models. First, continuous constitutive overexpression of an oncogene can be lethal to the host impeding further study. Second, constitutive overexpression fails to model adult onset of disease. Third, constitutive deletion does not permit, whereas conditional overexpression of an oncogene enables the study of the consequences of restoring expression of an oncogene back to endogenous levels. Fourth, the conditional activation of oncogenes enables examination of specific and/or developmental state-specific consequences.Hence, by allowing precise control of when and where a gene is expressed, the tetracycline regulatory system provides an ideal approach for the study of putative oncogenes in the initiation as well as the maintenance of tumorigenesis and the examination of the mechanisms of oncogene addiction. In this protocol, we describe the methods involved in the development of a conditional mouse model of MYC-induced T-cell acute lymphoblastic leukemia.

Advances in culture methods for acute myeloid leukemia research

Conventional suspension cultures have been used in Acute Myeloid Leukemia (AML) research to study its biology as well as to screen any drug molecules, since its inception. Co-culture models of AML cells and other stromal cells as well as 3 dimensional (3D) culture models have gained much attention recently. These culture models try to recapitulate the tumour microenvironment and are found to be more suitable than suspension cultures. Though animal models are being used, they require more time, effort and facilities and hence, it is essential to develop cell culture models for high-throughput screening of drugs. Here, we discuss a new co-culture model developed by our research group involving acute myeloid leukemia (AML) cells and stimulated macrophages. Other studies on co-culture systems and relevance of 3D culture in leukemic research in understanding the pathology and treatment of leukemia are also reviewed.

Establishment and characterization of an ovarian yolk sac tumor patient-derived xenograft model

OBJECTIVE

The lack of appropriate preclinical models of ovarian yolk sac tumor (OYST) is currently hindering the pursuit of new methods of treatment and investigation of the pathogenesis of the disease. We developed and characterized an OYST patient-derived xenograft (PDX) model in this study.

METHODS

Tumor fragments from a patient with an OYST were implanted subcutaneously into BALB/c Nude mice. Engrafted xenografts were compared with the original tumor according to histology, immunohistochemistry, humanized identified, and drug efficacy testing with in vivo treatment programs.

RESULTS

There was a high degree of histologic and immunohistochemical (IHC) resemblance between the established PDX model and its corresponding human tumors. Bleomycin, etoposide, and cisplatin (JEB) chemotherapy regimens were effective in clinical patients and were effective in the OYST PDX model; therefore, the effect of PDX intervention was consistent with clinical outcomes of OYSTs.

CONCLUSION

We have successfully established an OYST PDX model. This OYST model preserves the basic molecular features of the primary human tumor, thereby providing a valuable method to preclinically evaluate new treatments and explore disease pathogenesis.

Large-scale pharmacogenomic studies and drug response prediction for personalized cancer medicine

The response rate of most anti-cancer drugs is limited because of the high heterogeneity of cancer and the complex mechanism of drug action. Personalized treatment that stratifies patients into subgroups using molecular biomarkers is promising to improve clinical benefit. With the accumulation of preclinical models and advances in computational approaches of drug response prediction, pharmacogenomics has made great success over the last 20 years and is increasingly used in the clinical practice of personalized cancer medicine. In this article, we first summarize FDA-approved pharmacogenomic biomarkers and large-scale pharmacogenomic studies of preclinical cancer models such as patient-derived cell lines, organoids, and xenografts. Furthermore, we comprehensively review the recent developments of computational methods in drug response prediction, covering network, machine learning, and deep learning technologies and strategies to evaluate immunotherapy response. In the end, we discuss challenges and propose possible solutions for further improvement.

Quantitative In Vivo Analyses Reveal a Complex Pharmacogenomic Landscape in Lung Adenocarcinoma

The lack of knowledge about the relationship between tumor genotypes and therapeutic responses remains one of the most critical gaps in enabling the effective use of cancer therapies. Here, we couple a multiplexed and quantitative experimental platform with robust statistical methods to enable pharmacogenomic mapping of lung cancer treatment responses in vivo. The complex map of genotype-specific treatment responses uncovered that over 20% of possible interactions show significant resistance or sensitivity. Known and novel interactions were identified, and one of these interactions, the resistance of KEAP1-mutant lung tumors to platinum therapy, was validated using a large patient response data set. These results highlight the broad impact of tumor suppressor genotype on treatment responses and define a strategy to identify the determinants of precision therapies. SIGNIFICANCE: An experimental and analytical framework to generate in vivo pharmacogenomic maps that relate tumor genotypes to therapeutic responses reveals a surprisingly complex map of genotype-specific resistance and sensitivity.

Porcine pancreatic ductal epithelial cells transformed with KRASG12D and SV40T are tumorigenic

We describe our initial studies in the development of an orthotopic, genetically defined, large animal model of pancreatic cancer. Primary pancreatic epithelial cells were isolated from pancreatic duct of domestic pigs. A transformed cell line was generated from these primary cells with oncogenic KRAS and SV40T. The transformed cell lines outperformed the primary and SV40T immortalized cells in terms of proliferation, population doubling time, soft agar growth, transwell migration and invasion. The transformed cell line grew tumors when injected subcutaneously in nude mice, forming glandular structures and staining for epithelial markers. Future work will include implantation studies of these tumorigenic porcine pancreatic cell lines into the pancreas of allogeneic and autologous pigs. The resultant large animal model of pancreatic cancer could be utilized for preclinical research on diagnostic, interventional, and therapeutic technologies.

Computationally guided high-throughput design of self-assembling drug nanoparticles

Nanoformulations of therapeutic drugs are transforming our ability to effectively deliver and treat a myriad of conditions. Often, however, they are complex to produce and exhibit low drug loading, except for nanoparticles formed via co-assembly of drugs and small molecular dyes, which display drug-loading capacities of up to 95%. There is currently no understanding of which of the millions of small-molecule combinations can result in the formation of these nanoparticles. Here we report the integration of machine learning with high-throughput experimentation to enable the rapid and large-scale identification of such nanoformulations. We identified 100 self-assembling drug nanoparticles from 2.1 million pairings, each including one of 788 candidate drugs and one of 2,686 approved excipients. We further characterized two nanoparticles, sorafenib-glycyrrhizin and terbinafine-taurocholic acid both ex vivo and in vivo. We anticipate that our platform can accelerate the development of safer and more efficacious nanoformulations with high drug-loading capacities for a wide range of therapeutics.

Microvascularized tumor organoids-on-chips: advancing preclinical drug screening with pathophysiological relevance

Recent developments of organoids engineering and organ-on-a-chip microfluidic technologies have enabled the recapitulation of the major functions and architectures of microscale human tissue, including tumor pathophysiology. Nevertheless, there remain challenges in recapitulating the complexity and heterogeneity of tumor microenvironment. The integration of these engineering technologies suggests a potential strategy to overcome the limitations in reconstituting the perfusable microvascular system of large-scale tumors conserving their key functional features. Here, we review the recent progress of in vitro tumor-on-a-chip microfluidic technologies, focusing on the reconstruction of microvascularized organoid models to suggest a better platform for personalized cancer medicine.

Mechanisms of Cellular Senescence: Cell Cycle Arrest and Senescence Associated Secretory Phenotype

Cellular senescence is a stable cell cycle arrest that can be triggered in normal cells in response to various intrinsic and extrinsic stimuli, as well as developmental signals. Senescence is considered to be a highly dynamic, multi-step process, during which the properties of senescent cells continuously evolve and diversify in a context dependent manner. It is associated with multiple cellular and molecular changes and distinct phenotypic alterations, including a stable proliferation arrest unresponsive to mitogenic stimuli. Senescent cells remain viable, have alterations in metabolic activity and undergo dramatic changes in gene expression and develop a complex senescence-associated secretory phenotype. Cellular senescence can compromise tissue repair and regeneration, thereby contributing toward aging. Removal of senescent cells can attenuate age-related tissue dysfunction and extend health span. Senescence can also act as a potent anti-tumor mechanism, by preventing proliferation of potentially cancerous cells. It is a cellular program which acts as a double-edged sword, with both beneficial and detrimental effects on the health of the organism, and considered to be an example of evolutionary antagonistic pleiotropy. Activation of the p53/p21^WAF1/CIP1 and p16^INK4A/pRB tumor suppressor pathways play a central role in regulating senescence. Several other pathways have recently been implicated in mediating senescence and the senescent phenotype. Herein we review the molecular mechanisms that underlie cellular senescence and the senescence associated growth arrest with a particular focus on why cells stop dividing, the stability of the growth arrest, the hypersecretory phenotype and how the different pathways are all integrated.

Olaparib increases the therapeutic index of hemithoracic irradiation compared with hemithoracic irradiation alone in a mouse lung cancer model

Background

The radiosensitising effect of the poly(ADP-ribose) polymerase inhibitor olaparib on tumours has been reported. However, its effect on normal tissues in combination with radiation has not been well studied. Herein, we investigated the therapeutic index of olaparib combined with hemithoracic radiation in a urethane-induced mouse lung cancer model.

Methods

To assess tolerability, A/J mice were treated with olaparib plus whole thorax radiation (13 Gy), body weight changes were monitored and normal tissue effects were assessed by histology. In anti-tumour (intervention) studies, A/J mice were injected with urethane to induce lung tumours, and were then treated with olaparib alone, left thorax radiation alone or the combination of olaparib plus left thorax radiation at 8 weeks (early intervention) or 18 weeks (late intervention) after urethane injection. Anti-tumour efficacy and normal tissue effects were assessed by visual inspection, magnetic resonance imaging and histology.

Results

Enhanced body weight loss and oesophageal toxicity were observed when olaparib was combined with whole thorax but not hemithorax radiation. In both the early and late intervention studies, olaparib increased the anti-tumour effects of hemithoracic irradiation without increasing lung toxicity.

Conclusions

The addition of olaparib increased the therapeutic index of hemithoracic radiation in a mouse model of lung cancer.

Advanced nanomedicine and cancer: Challenges and opportunities in clinical translation

Cancer has reached pandemic dimensions in the whole world. Although current medicine offers multiple treatment options against cancer, novel therapeutic strategies are needed due to the low specificity of chemotherapeutic drugs, undesired side effects and the presence of different incurable types of cancer. Among these new strategies, nanomedicine arises as an encouraging approach towards personalized medicine with high potential for present and future cancer patients. Therefore, nanomedicine aims to develop novel tools with wide potential in cancer treatment, imaging or even theranostic purposes. Even though numerous preclinical studies have been published with successful preliminary results, promising nanosystems have to face multiple obstacles before adoption in clinical practice as safe options for patients with cancer. In this MiniReview, we provide a short overview on the latest advances in current nanomedicine approaches, challenges and promising strategies towards more accurate cancer treatment.

Blueprint for cancer research: Critical gaps and opportunities

We are experiencing a revolution in cancer. Advances in screening, targeted and immune therapies, big data, computational methodologies, and significant new knowledge of cancer biology are transforming the ways in which we prevent, detect, diagnose, treat, and survive cancer. These advances are enabling durable progress in the goal to achieve personalized cancer care. Despite these gains, more work is needed to develop better tools and strategies to limit cancer as a major health concern. One persistent gap is the inconsistent coordination among researchers and caregivers to implement evidence-based programs that rely on a fuller understanding of the molecular, cellular, and systems biology mechanisms underpinning different types of cancer. Here, the authors integrate conversations with over 90 leading cancer experts to highlight current challenges, encourage a robust and diverse national research portfolio, and capture timely opportunities to advance evidence-based approaches for all patients with cancer and for all communities.

Respiratory Motion Mitigation and Repeatability of Two Diffusion-Weighted MRI Methods Applied to a Murine Model of Spontaneous Pancreatic Cancer

Respiratory motion and increased susceptibility effects at high magnetic fields pose challenges for quantitative diffusion-weighted MRI (DWI) of a mouse abdomen on preclinical MRI systems. We demonstrate the first application of radial k-space-sampled (RAD) DWI of a mouse abdomen using a genetically engineered mouse model of pancreatic ductal adenocarcinoma (PDAC) on a 4.7 T preclinical scanner equipped with moderate gradient capability. RAD DWI was compared with the echo-planar imaging (EPI)-based DWI method with similar voxel volumes and acquisition times over a wide range of b-values (0.64, 535, 1071, 1478, and 2141 mm²/s). The repeatability metrics are assessed in a rigorous test-retest study (n = 10 for each DWI protocol). The four-shot EPI DWI protocol leads to higher signal-to-noise ratio (SNR) in diffusion-weighted images with persisting ghosting artifacts, whereas the RAD DWI protocol produces relatively artifact-free images over all b-values examined. Despite different degrees of motion mitigation, both RAD DWI and EPI DWI allow parametric maps of apparent diffusion coefficients (ADC) to be produced, and the ADC of the PDAC tumor estimated by the two methods are 1.3 ± 0.24 and 1.5 ± 0.28 × 10^-3 mm²/s, respectively (p = 0.075, n = 10), and those of a water phantom are 3.2 ± 0.29 and 2.8 ± 0.15 × 10^-3 mm²/s, respectively (p = 0.001, n = 10). Bland-Altman plots and probability density function reveal good repeatability for both protocols, whose repeatability metrics do not differ significantly. In conclusion, RAD DWI enables a more effective respiratory motion mitigation but lower SNR, while the performance of EPI DWI is expected to improve with more advanced gradient hardware.

Differential Effects of Trp53 Alterations in Murine Colorectal Cancer

BACKGROUND

Colorectal cancer (CRC) development is a multi-step process resulting in the accumulation of genetic alterations. Despite its high incidence, there are currently no mouse models that accurately recapitulate this process and mimic sporadic CRC. We aimed to develop and characterize a genetically engineered mouse model (GEMM) of Apc/Kras/Trp53 mutant CRC, the most frequent genetic subtype of CRC.

METHODS

Tumors were induced in mice with conditional mutations or knockouts in Apc, Kras, and Trp53 by a segmental adeno-cre viral infection, monitored via colonoscopy and characterized on multiple levels via immunohistochemistry and next-generation sequencing.

RESULTS

The model accurately recapitulates human colorectal carcinogenesis clinically, histologically and genetically. The Trp53 R172H hotspot mutation leads to significantly increased metastatic capacity. The effects of Trp53 alterations, as well as the response to treatment of this model, are similar to human CRC. Exome sequencing revealed spontaneous protein-modifying alterations in multiple CRC-related genes and oncogenic pathways, resulting in a genetic landscape resembling human CRC.

CONCLUSIONS

This model realistically mimics human CRC in many aspects, allows new insights into the role of TP53 in CRC, enables highly predictive preclinical studies and demonstrates the value of GEMMs in current translational cancer research and drug development.

Current status and future outlook for patient-derived cancer models from a rare cancer research perspective

Rare cancers are a group of approximately 200 malignancies with extremely low incidences and with a wide variety of genotypes and phenotypes. Collectively, they are more common than any single malignancy. However, given the small numbers of individuals diagnosed with rare cancers, it is difficult to design clinical trials with sufficient patient numbers. Therefore, few effective anticancer drugs have been developed, and evidence‐based medicine is not always feasible for rare cancers. Consequently, their clinical outcomes are generally poorer. Cancer research requires adequate models that faithfully recapitulate molecular features and reproduce treatment responses of the original tumors. Such models allow us to focus on more efficacious drugs in the clinical studies. For rare cancers, patient‐derived cancer models are particularly important because the enrollment of sufficient patients is rarely attainable within a reasonable period of time. However, extremely few models are available for rare cancers. For example, cell lines and xenografts are available for only a limited number of histological subtypes of sarcomas; therefore, most sarcoma research is performed without such models, and a lack of adequate cancer models causes a lag in therapeutic development. The establishment of novel rare cancer models will dramatically facilitate rare cancer research and treatment development in the near future. This review focuses on the status of patient‐derived rare cancer models and discusses their pivotal problems and possibilities, using sarcomas as a representative rare cancer type. Multi‐institutional collaboration will help address the scarcity of patient‐derived rare cancer models.

Antibody-drug conjugates: an evolving approach for melanoma treatment

Melanoma continues to be an aggressive and deadly form of skin cancer while therapeutic options are continuously developing in an effort to provide long-term solutions for patients. Immunotherapeutic strategies incorporating antibody-drug conjugates (ADCs) have seen varied levels of success across tumor types and represent a promising approach for melanoma. This review will explore the successes of FDA-approved ADCs to date compared to the ongoing efforts of melanoma-targeting ADCs. The challenges and opportunities for future therapeutic development are also examined to distinguish how ADCs may better impact individuals with malignancies such as melanoma.

Development and characterization of patient-derived xenografts from non-small cell lung cancer brain metastases

Non-small cell lung cancer (NSCLC) brain metastasis cell lines and in vivo models are not widely accessible. Herein we report on a direct-from patient-derived xenograft (PDX) model system of NSCLC brain metastases with genomic annotation useful for translational and mechanistic studies. Both heterotopic and orthotopic intracranial xenografts were established and RNA and DNA sequencing was performed on patient and matching tumors. Morphologically, strong retention of cytoarchitectural features was observed between original patient tumors and PDXs. Transcriptome and mutation analysis revealed high correlation between matched patient and PDX samples with more than more than 95% of variants detected being retained in the matched PDXs. PDXs demonstrated response to radiation, response to selumetinib in tumors harboring KRAS G12C mutations and response to savolitinib in a tumor with MET exon 14 skipping mutation. Savolitinib also demonstrated in vivo radiation enhancement in our MET exon 14 mutated PDX. Early passage cell strains showed high consistency between patient and PDX tumors. Together, these data describe a robust human xenograft model system for investigating NSCLC brain metastases. These PDXs and cell lines show strong phenotypic and molecular correlation with the original patient tumors and provide a valuable resource for testing preclinical therapeutics.

Hepatocellular carcinoma

Liver cancer remains a global health challenge, with an estimated incidence of >1 million cases by 2025. Hepatocellular carcinoma (HCC) is the most common form of liver cancer and accounts for ~90% of cases. Infection by hepatitis B virus and hepatitis C virus are the main risk factors for HCC development, although non-alcoholic steatohepatitis associated with metabolic syndrome or diabetes mellitus is becoming a more frequent risk factor in the West. Moreover, non-alcoholic steatohepatitis-associated HCC has a unique molecular pathogenesis. Approximately 25% of all HCCs present with potentially actionable mutations, which are yet to be translated into the clinical practice. Diagnosis based upon non-invasive criteria is currently challenged by the need for molecular information that requires tissue or liquid biopsies. The current major advancements have impacted the management of patients with advanced HCC. Six systemic therapies have been approved based on phase III trials (atezolizumab plus bevacizumab, sorafenib, lenvatinib, regorafenib, cabozantinib and ramucirumab) and three additional therapies have obtained accelerated FDA approval owing to evidence of efficacy. New trials are exploring combination therapies, including checkpoint inhibitors and tyrosine kinase inhibitors or anti-VEGF therapies, or even combinations of two immunotherapy regimens. The outcomes of these trials are expected to change the landscape of HCC management at all evolutionary stages.

Microengineered 3D Tumor Models for Anti-Cancer Drug Discovery in Female-Related Cancers

The burden of cancer continues to increase in society and negatively impacts the lives of numerous patients. Due to the high cost of current treatment strategies, there is a crucial unmet need to develop inexpensive preclinical platforms to accelerate the process of anti-cancer drug discovery to improve outcomes in cancer patients, most especially in female patients. Many current methods employ expensive animal models which not only present ethical concerns but also do not often accurately predict human physiology and the outcomes of anti-cancer drug responsiveness. Conventional treatment approaches for cancer generally include systemic therapy after a surgical procedure. Although this treatment technique is effective, the outcome is not always positive due to various complex factors such as intratumor heterogeneity and confounding factors within the tumor microenvironment (TME). Patients who develop metastatic disease still have poor prognosis. To that end, recent efforts have attempted to use 3D microengineered platforms to enhance the predictive power and efficacy of anti-cancer drug screening, ultimately to develop personalized therapies. Fascinating features of microengineered assays, such as microfluidics, have led to the advancement in the development of the tumor-on-chip technology platforms, which have shown tremendous potential for meaningful and physiologically relevant anti-cancer drug discovery and screening. Three dimensional microscale models provide unprecedented ability to unveil the biological complexities of cancer and shed light into the mechanism of anti-cancer drug resistance in a timely and resource efficient manner. In this review, we discuss recent advances in the development of microengineered tumor models for anti-cancer drug discovery and screening in female-related cancers. We specifically focus on female-related cancers to draw attention to the various approaches being taken to improve the survival rate of women diagnosed with cancers caused by sex disparities. We also briefly discuss other cancer types like colon adenocarcinomas and glioblastoma due to their high rate of occurrence in females, as well as the high likelihood of sex-biased mutations which complicate current treatment strategies for women. We highlight recent advances in the development of 3D microscale platforms including 3D tumor spheroids, microfluidic platforms as well as bioprinted models, and discuss how they have been utilized to address major challenges in the process of drug discovery, such as chemoresistance, intratumor heterogeneity, drug toxicity, etc. We also present the potential of these platform technologies for use in high-throughput drug screening approaches as a replacements of conventional assays. Within each section, we will provide our perspectives on advantages of the discussed platform technologies.

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

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

Modeling human pancreatic ductal adenocarcinoma for translational research: current options, challenges, and prospective directions

Pancreatic ductal adenocarcinoma (PDAC) is a devastating malignancy with one of the lowest survival rates. Early detection, an improved understanding of tumor biology, and novel therapeutic discoveries are needed in order to improve overall patient survival. Scientific progress towards meeting these goals relies upon accurate modeling of the human disease. From two-dimensional (2D) cell lines to the advanced modeling available today, we aim to characterize the critical tools in efforts to further understand PDAC biology. The National Center for Biotechnology Information's PubMed and the Elsevier's SCOPUS were used to perform a comprehensive literature review evaluating preclinical human-derived PDAC models. Keywords included pancreatic cancer, PDAC, preclinical models, KRAS mutations, xenograft, co-culturing fibroblasts, co-culturing lymphocytes and PDAC immunotherapy Initial search was limited to articles about PDAC and was then expanded to include other gastrointestinal malignancies where information may complement our effort. A supervised review of the key literature's references was utilized to augment the capture of relevant data. The discovery and refinement of techniques enabling immortalized 2D cell culture provided the cornerstone for modern cancer biology research. Cell lines have been widely used to represent PDAC in vitro but are limited in capacity to model three-dimensional (3D) tumor attributes and interactions within the tumor microenvironment. Xenografts are an alternative method to model PDAC with improved capacity to understand certain aspects of 3D tumor biology in vivo while limited by the use of immunodeficient mice. Advances of in vitro modeling techniques have led to 3D organoid models for PDAC biology. Co-culturing models in the 3D environment have been proposed as an efficient modeling system for improving upon the limitations encountered in the standard 2D and xenograft tumor models. The integrated network of cells and stroma that comprise PDAC in vivo need to be accurately depicted ex vivo to continue to make progress in this disease. Recapitulating the complex tumor microenvironment in a preclinical model of human disease is an outstanding and urgent need in PDAC. Definitive characterization of available human models for PDAC serves to further the core mission of pancreatic cancer translational research.

Limonin ameliorates dextran sulfate sodium-induced chronic colitis in mice by inhibiting PERK-ATF4-CHOP pathway of ER stress and NF-κB signaling

Inflammatory bowel disease (IBD) is a chronic gastrointestinal inflammation regulated by intricate mechanisms. Limonin, a natural tetracyclic triterpenoid compound, possesses multiple bioactivities including anti-inflammation, anti-cancer and so on. However, the therapeutic potential and the underlying mechanism of limonin on IBD remain unclear. Here, we probe into the effect of limonin on chronic colitis induced by dextran sulfate sodium (DSS) and illustrated the potential mechanisms. We found that limonin relieved the risk and severity of DSS-induced chronic colitis in mice through various aspects including increasing body weight and colon length, decreasing the mortality rate, inhibiting MPO activity and improving colon pathology. Limonin also decreased the production of proinflammatory cytokines TNF-α, IL-1β, IL-6 and the expression of inflammatory proteins COX-2, iNOS in colon tissues from DSS-induced colitis mice. Moreover, limonin attenuated DSS-induced chronic colitis by inhibiting PERK-ATF4-CHOP pathway of endoplasmic reticulum (ER) stress and NF-κB signaling. In vitro, limonin not only decreased LPS-induced higher production of pro-inflammatory cytokines and inflammatory proteins mentioned above by inhibiting NF-κB signaling in macrophage cells RAW264.7, but also suppressed PERK-ATF4-CHOP pathway of ER stress. In summary, our study demonstrated that limonin mitigated DSS-induced chronic colitis via inhibiting PERK-ATF4-CHOP pathway of ER stress and NF-κB signaling. All of this study provides the possibility for limonin as an effective drug for chronic colitis of IBD in the future.

Process and Workflow for Preparation of Disparate Mouse Tissues for Proteomic Analysis

We investigated the effect of homogenization strategy and protein precipitation on downstream protein quantitation using multiple reaction monitoring mass spectrometry (MRM-MS). Our objective was to develop a workflow capable of processing disparate tissue types with high throughput, minimal variability, and maximum purity. Similar abundances of endogenous proteins were measured in nine different mouse tissues regardless of the homogenization method used; however, protein precipitation had strong positive effects on several targets. The best throughput was achieved by lyophilizing tissues to dryness, followed by homogenization via bead-beating without sample buffer. Finally, the effect of tissue perfusion prior to dissection and collection was explored in 20 mouse tissues. MRM-MS showed decreased abundances of blood-related proteins in perfused tissues; however, complete removal was not achieved. Concentrations of nonblood proteins were largely unchanged, although significantly higher variances were observed for proteins from the perfused lung, indicating that perfusion may not be suitable for this organ. We present a simple yet effective tissue processing workflow consisting of harvest of fresh nonperfused tissue, novel lyophilization and homogenization by bead-beating, and protein precipitation. This workflow can be applied to a range of mouse tissues with the advantages of simplicity, minimal manual manipulation of samples, use of commonly available equipment, and high sample quality.

Cucurbitacin mediated regulation of deregulated oncogenic signaling cascades and non-coding RNAs in different cancers: Spotlight on JAK/STAT, Wnt/β-catenin, mTOR, TRAIL-mediated pathways

Research over decades has enabled us in developing a better understanding of the multifaceted and heterogeneous nature of cancer. High-throughput technologies have helped the researchers in unraveling of the underlying mechanisms which centrally regulate cancer onset, metastasis and drug resistance. Our rapidly expanding knowledge about signal transduction cascade has added another layer of complexity to already complicated nature of cancer. Deregulation of cell signaling pathways played a linchpin role in carcinogenesis and metastasis. Cucurbitacins have gained tremendous attention because of their remarkable pharmacological properties and considerable ability to mechanistically modulate myriad of cell signaling pathways in different cancers. In this review, we have attempted to provide a mechanistic and comprehensive analysis of regulation of oncogenic pathways by cucurbitacins in different cancers. We have partitioned this review into separate sections for exclusive analysis of each signaling pathway and critical assessment of the knowledge gaps. In this review, we will summarize most recent and landmark developments related to regulation of Wnt/β-catenin, JAK/STAT, mTOR, VEGFR, EGFR and Hippo pathway by cucurbitacins. Moreover, we will also address how cucurbitacins regulate DNA damage repair pathway and TRAIL-driven signaling in various cancers. However, there are still outstanding questions related to regulation of SHH/GLI, TGF/SMAD and Notch-driven pathway by cucurbitacins in different cancers. Future studies must converge on the analysis of full-fledge potential of cucurbitacins by in-depth analysis of these pathways and how these pathways can be therapeutically targeted by cucurbitacins.

Π electron-stabilized polymeric micelles potentiate docetaxel therapy in advanced-stage gastrointestinal cancer

Gastrointestinal (GI) cancers are among the most lethal malignancies. The treatment of advanced-stage GI cancer involves standard chemotherapeutic drugs, such as docetaxel, as well as targeted therapeutics and immunomodulatory agents, all of which are only moderately effective. We here show that Π electron-stabilized polymeric micelles based on PEG-b-p(HPMAm-Bz) can be loaded highly efficiently with docetaxel (loading capacity up to 23 wt%) and potentiate chemotherapy responses in multiple advanced-stage GI cancer mouse models. Complete cures and full tumor regression were achieved upon intravenously administering micellar docetaxel in subcutaneous gastric cancer cell line-derived xenografts (CDX), as well as in CDX models with intraperitoneal and lung metastases. Nanoformulated docetaxel also outperformed conventional docetaxel in a patient-derived xenograft (PDX) model, doubling the extent of tumor growth inhibition. Furthermore, micellar docetaxel modulated the tumor immune microenvironment in CDX and PDX tumors, increasing the ratio between M1-and M2-like macrophages, and toxicologically, it was found to be very well-tolerated. These findings demonstrate that Π electron-stabilized polymeric micelles loaded with docetaxel hold significant potential for the treatment of advanced-stage GI cancers.

Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions

The dense network of interconnected cellular signalling responses that are quantifiable in peripheral immune cells provides a wealth of actionable immunological insights. Although high-throughput single-cell profiling techniques, including polychromatic flow and mass cytometry, have matured to a point that enables detailed immune profiling of patients in numerous clinical settings, the limited cohort size and high dimensionality of data increase the possibility of false-positive discoveries and model overfitting. We introduce a generalizable machine learning platform, the immunological Elastic-Net (iEN), which incorporates immunological knowledge directly into the predictive models. Importantly, the algorithm maintains the exploratory nature of the high-dimensional dataset, allowing for the inclusion of immune features with strong predictive capabilities even if not consistent with prior knowledge. In three independent studies our method demonstrates improved predictions for clinically relevant outcomes from mass cytometry data generated from whole blood, as well as a large simulated dataset. The iEN is available under an open-source licence.

Cardiac and lung endothelial cells in response to fluid shear stress on physiological matrix stiffness and composition

OBJECTIVE

Preconditioning of endothelial cells from different vascular beds has potential value for re-endothelialization and implantation of engineered tissues. Understanding how substrate stiffness and composition affects tissue-specific cell response to shear stress will aid in successful endothelialization of engineered tissues. We developed a platform to test biomechanical and biochemical stimuli.

METHODS

A novel polydimethylsiloxane-based parallel plate flow chamber enabled application of laminar fluid shear stress of 2 dynes/cm² for 12 hours to microvascular cardiac and lung endothelial cells cultured on cardiac and lung-derived extracellular matrix. Optical imaging of cells was used to quantify cell changes in cell alignment. Analysis of integrin expression was performed using flow cytometry.

RESULTS

Application of fluid shear stress caused the greatest cell alignment in cardiac endothelial cells seeded on polystyrene and lung endothelial cells on polydimethylsiloxane. This resulted in elongation of the lung endothelial cells. α_v and β₃ integrin expression decreased after application of shear stress in both cell types.

CONCLUSION

Substrate stiffness plays an important role in regulating tissue-specific endothelial response to shear stress, which may be due to differences in their native microenvironments. Furthermore, cardiac and lung endothelial cell response to shear stress was significantly regulated by the type of coating used.

Transgenic zebrafish for modeling hepatocellular carcinoma

Liver cancer is the third leading cause of cancer‐related deaths throughout the world, and more than 0.6 million people die from liver cancer annually. Therefore, novel therapeutic strategies to eliminate malignant cells from liver cancer patients are urgently needed. Recent advances in high‐throughput genomic technologies have identified de novo candidates for oncogenes and pharmacological targets. However, testing and understanding the mechanism of oncogenic transformation as well as probing the kinetics and therapeutic responses of spontaneous tumors in an intact microenvironment require in vivo examination using genetically modified animal models. The zebrafish (Danio rerio) has attracted increasing attention as a new model for studying cancer biology since the organs in the model are strikingly similar to human organs and the model can be genetically modified in a short time and at a low cost. This review summarizes the current knowledge of epidemiological data and genetic alterations in hepatocellular carcinoma (HCC), zebrafish models of HCC, and potential therapeutic strategies for targeting HCC based on knowledge from the models.

The role of telomeres and telomerase in the senescence of postmitotic cells

Senescence is a process related to the stopping of divisions and changes leading the cell to the SASP phenotype. Permanent senescence of many SASP cells contributes to faster aging of the body and development of age-related diseases due to the release of pro-inflammatory factors. Both mitotically active and non-dividing cells can undergo senescence as a result of activation of different molecular pathways. Telomeres, referred to as the molecular clock, direct the dividing cell into the aging pathway when reaching a critical length. In turn, the senescence of postmitotic cells depends not on the length of telomeres, but their functionality. Dysfunctional telomeres are responsible for triggering the signaling of DNA damage response (DDR). Telomerase subunits in post-mitotic cells translocate between the nucleus, cytoplasm and mitochondria, participating in the regulation of their activity. Among other things, they contribute to the reduction of reactive oxygen species generation, which leads to telomere dysfunction and, consequently, senescence. Some proteins of the shelterin complex also play a protective role by inhibiting senescence-initiating kinases and limiting ROS production by mitochondria.

Human-Derived Model Systems in Gynecological Cancer Research

The human female reproductive tract (FRT) is a complex system that combines series of organs, including ovaries, fallopian tubes, uterus, cervix, vagina, and vulva; each of which possesses unique cellular characteristics and functions. This versatility, in turn, allows for the development of a wide range of epithelial gynecological cancers with distinct features. Thus, reliable model systems are required to better understand the diverse mechanisms involved in the regional pathogenesis of the reproductive tract and improve treatment strategies. Here, we review the current human-derived model systems available to study the multitude of gynecological cancers, including ovarian, endometrial, cervical, vaginal, and vulvar cancer, and the recent advances in the push towards personalized therapy.

Comparing the fate of brain metastatic breast cancer cells in different immune compromised mice with cellular magnetic resonance imaging

Metastasis is the leading cause of mortality in breast cancer patients, with brain metastases becoming increasingly prevalent. Studying this disease is challenging due to the limited experimental models and methods available. Here, we used iron-based cellular MRI to track the fate of a mammary carcinoma cell line (MDA-MB-231-BR) in vivo to characterize the growth of brain metastases in the nude and severely immune-compromised NOD/SCID/ILIIrg-/- (NSG) mouse. Nude and NSG mice received injections of iron-labeled MDA-MB-231-BR cells. Images were acquired with a 3T MR system and assessed for signal voids and metastases. The percentage of signal voids and the number and volume of metastases were quantified. Ex vivo imaging of the liver, histology, and immunofluorescence labeling was performed. Brain metastases grew more rapidly in NSG mice. At day 21 post cell injection, the average number of brain tumors in NSG mice was approximately four times greater than in nude mice. The persistence of iron-labeled cells, visualized as signal voids by MRI, was also examined. The percentage of voids decreased significantly over time for both nude and NSG mice. Body images revealed that the NSG mice also had metastases in the liver, lungs, and lymph nodes while tumors were only detected in the brains of nude mice. This work demonstrates the advantages of using the highly immune-compromised NSG mouse to study breast cancer metastasis, treatments aimed at inhibiting metastasis and outgrowth of breast cancer metastases in multiple organs, and the role that imaging can play toward credentialing these models that cannot be done with other in vitro or histopathologic methods alone.