Genetically engineered mouse models in oncology research and cancer medicine

Imaging Hallmarks of Sarcoma Progression Via X-ray Computed Tomography: Beholding the Flower of Evil

Simple Summary

Sarcomas represent the largest group of rare solid tumors that arise from mesenchymal stem cells and are a leading cause of cancer death in individuals younger than 20 years of age. There is an immediate need for the development of an algorithm for the early accurate diagnosis of sarcomas due to the high rate of diagnostic inaccuracy, which reaches up to 30%. X-ray computed tomography is a non-invasive imaging technique used to obtain detailed internal images of the human or animal body in clinical practice and preclinical studies. We summarized the main imaging features of soft tissue and bone sarcomas, and noted the development of new molecular markers to reach tumor type-specific imaging. Also, we demonstrated the possibility of the use X-ray computed microtomography for non-destructive 3D visualization of sarcoma progression in preclinical studies. Finding correlations between X-ray computed tomography modalities and the results of the histopathological specimen examination may significantly increase the accuracy of diagnostics, which leads to the initiation of appropriate management in a timely manner and, consequently, to improved outcomes.

Abstract

Sarcomas are a leading cause of cancer death in individuals younger than 20 years of age and represent the largest group of rare solid tumors. To date, more than 100 morphological subtypes of sarcomas have been described, among which epidemiology, clinical features, management, and prognosis differ significantly. Delays and errors in the diagnosis of sarcomas limit the number of effective therapeutic modalities and catastrophically worsen the prognosis. Therefore, the development of an algorithm for the early accurate diagnosis of sarcomas seems to be as important as the development of novel therapeutic advances. This literature review aims to summarize the results of recent investigations regarding the imaging of sarcoma progression based on the use of X-ray computed tomography (CT) in preclinical studies and in current clinical practice through the lens of cancer hallmarks. We attempted to summarize the main CT imaging features of soft-tissue and bone sarcomas. We noted the development of new molecular markers with high specificity to antibodies and chemokines, which are expressed in particular sarcoma subtypes to reach tumor type-specific imaging. We demonstrate the possibility of the use of X-ray computed microtomography (micro-CT) for non-destructive 3D visualization of solid tumors by increasing the visibility of soft tissues with X-ray scattering agents. Based on the results of recent studies, we hypothesize that micro-CT enables the visualization of neovascularization and stroma formation in sarcomas at high-resolution in vivo and ex vivo, including the novel techniques of whole-block and whole-tissue imaging. Finding correlations between CT, PET/CT, and micro-CT imaging features, the results of the histopathological specimen examination and clinical outcomes may significantly increase the accuracy of soft-tissue and bone tumor diagnostics, which leads to the initiation of appropriate histotype-specific management in a timely manner and, consequently, to improved outcomes.

Lessons learned from immunological characterization of nanomaterials at the Nanotechnology Characterization Laboratory

Nanotechnology carriers have become common in pharmaceutical products because of their benefits to drug delivery, including reduced toxicities and improved efficacy of active pharmaceutical ingredients due to targeted delivery, prolonged circulation time, and controlled payload release. While available examples of reduced drug toxicity through formulation using a nanocarrier are encouraging, current data also demonstrate that nanoparticles may change a drug’s biodistribution and alter its toxicity profile. Moreover, individual components of nanoparticles and excipients commonly used in formulations are often not immunologically inert and contribute to the overall immune responses to nanotechnology-formulated products. Said immune responses may be beneficial or adverse depending on the indication, dose, dose regimen, and route of administration. Therefore, comprehensive toxicology studies are of paramount importance even when previously known drugs, components, and excipients are used in nanoformulations. Recent data also suggest that, despite decades of research directed at hiding nanocarriers from the immune recognition, the immune system’s inherent property of clearing particulate materials can be leveraged to improve the therapeutic efficacy of drugs formulated using nanoparticles. Herein, I review current knowledge about nanoparticles’ interaction with the immune system and how these interactions contribute to nanotechnology-formulated drug products’ safety and efficacy through the lens of over a decade of nanoparticle characterization at the Nanotechnology Characterization Laboratory.

A multi-omic analysis of MCF10A cells provides a resource for integrative assessment of ligand-mediated molecular and phenotypic responses

The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix proteins. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods ( synapse.org/LINCS_MCF10A ). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes. Beyond these analyses, this dataset will serve as a resource for the broader scientific community to mine for biological insights, to compare signals carried across distinct molecular modalities, and to develop new computational methods for integrative data analysis.

Establishment of a ccRCC patient-derived chick chorioallantoic membrane model for drug testing

Clear cell renal cell carcinoma (ccRCC) is an aggressive subtype of renal cell carcinoma accounting for the majority of deaths in kidney cancer patients. Advanced ccRCC has a high mortality rate as most patients progress and develop resistance to currently approved targeted therapies, highlighting the ongoing need for adequate drug testing models to develop novel therapies. Current animal models are expensive and time-consuming. In this study, we investigated the use of the chick chorioallantoic membrane (CAM), a rapid and cost-effective model, as a complementary drug testing model for ccRCC. Our results indicated that tumor samples from ccRCC patients can be successfully cultivated on the chick chorioallantoic membrane (CAM) within 7 days while retaining their histopathological characteristics. Furthermore, treatment of ccRCC xenografts with sunitinib, a tyrosine kinase inhibitor used for the treatment of metastatic RCC, allowed us to evaluate differential responses of individual patients. Our results indicate that the CAM model is a complementary in vivo model that allows for rapid and cost-effective evaluation of ccRCC patient response to drug therapy. Therefore, this model has the potential to become a useful platform for preclinical evaluation of new targeted therapies for the treatment of ccRCC.

Role of Nanotechnology in Overcoming the Multidrug Resistance in Cancer Therapy: A Review

Cancer is one of the leading causes of morbidity and mortality around the globe and is likely to become the major cause of global death in the coming years. As per World Health Organization (WHO) report, every year there are over 10 and 9 million new cases and deaths from this disease. Chemotherapy, radiotherapy, and surgery are the three basic approaches to treating cancer. These approaches are aiming at eradicating all cancer cells with minimum off-target effects on other cell types. Most drugs have serious adverse effects due to the lack of target selectivity. On the other hand, resistance to already available drugs has emerged as a major obstacle in cancer chemotherapy, allowing cancer to proliferate irrespective of the chemotherapeutic agent. Consequently, it leads to multidrug resistance (MDR), a growing concern in the scientific community. To overcome this problem, in recent years, nanotechnology-based drug therapies have been explored and have shown great promise in overcoming resistance, with most nano-based drugs being explored at the clinical level. Through this review, we try to explain various mechanisms involved in multidrug resistance in cancer and the role nanotechnology has played in overcoming or reversing this resistance.

Predictive validity in drug discovery: what it is, why it matters and how to improve it

Successful drug discovery is like finding oases of safety and efficacy in chemical and biological deserts. Screens in disease models, and other decision tools used in drug research and development (R&D), point towards oases when they score therapeutic candidates in a way that correlates with clinical utility in humans. Otherwise, they probably lead in the wrong direction. This line of thought can be quantified by using decision theory, in which 'predictive validity' is the correlation coefficient between the output of a decision tool and clinical utility across therapeutic candidates. Analyses based on this approach reveal that the detectability of good candidates is extremely sensitive to predictive validity, because the deserts are big and oases small. Both history and decision theory suggest that predictive validity is under-managed in drug R&D, not least because it is so hard to measure before projects succeed or fail later in the process. This article explains the influence of predictive validity on R&D productivity and discusses methods to evaluate and improve it, with the aim of supporting the application of more effective decision tools and catalysing investment in their creation.

Investigation of early neoplastic transformation and premalignant biology using genetically engineered organoid models

Organoid modeling is a powerful, robust and efficient technology faithfully preserving physiological and pathological characteristics of tissues of origin. Recently, substantial advances have been made in applying genetically engineered organoid models to study early tumorigenesis and premalignant biology. These efforts promise to identify novel avenues for early cancer detection, intervention and prevention. Here, we highlight significant advancements in the functional characterization of early genomic and epigenomic events during neoplastic evolution using organoid modeling, discuss the application of the lineage-tracing methodology in organoids to study cancer cells-of-origin, and review future opportunities for further development and improvement of organoid modeling of cancer precursors.

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

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

Harnessing preclinical models for the interrogation of ovarian cancer

Ovarian cancer (OC) is a heterogeneous malignancy with various etiology, histopathology, and biological feature. Despite accumulating understanding of OC in the post-genomic era, the preclinical knowledge still undergoes limited translation from bench to beside, and the prognosis of ovarian cancer has remained dismal over the past 30 years. Henceforth, reliable preclinical model systems are warranted to bridge the gap between laboratory experiments and clinical practice. In this review, we discuss the status quo of ovarian cancer preclinical models which includes conventional cell line models, patient-derived xenografts (PDXs), patient-derived organoids (PDOs), patient-derived explants (PDEs), and genetically engineered mouse models (GEMMs). Each model has its own strengths and drawbacks. We focus on the potentials and challenges of using these valuable tools, either alone or in combination, to interrogate critical issues with OC.

In Vivo Oncolytic Virotherapy in Murine Models of Hepatocellular Carcinoma: A Systematic Review

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality worldwide. Current therapies often provide marginal survival benefits at the expense of undesirable side effects. Oncolytic viruses represent a novel strategy for the treatment of HCC due to their inherent ability to cause direct tumor cell lysis while sparing normal tissue and their capacity to stimulate potent immune responses directed against uninfected tumor cells and distant metastases. Oncolytic virotherapy (OVT) is a promising cancer treatment, but before it can become a standard option in practice, several challenges-systemic viral delivery optimization/enhancement, inter-tumoral virus dispersion, anti-cancer immunity cross-priming, and lack of artificial model systems-need to be addressed. Addressing these will require an in vivo model that accurately mimics the tumor microenvironment and allows the scientific community to design a more precise and accurate OVT. Due to their close physiologic resemblance to humans, murine cancer models are the likely preferred candidates. To provide an accurate assessment of the current state of in vivo OVT in HCC, we have reviewed a comprehensively searched body of work using murine in vivo HCC models for OVT.

Critical evaluation of an autologous peripheral blood mononuclear cell-based humanized cancer model

The use of humanized mouse models for oncology is rapidly expanding. Autologous patient-derived systems are particularly attractive as they can model the human cancer's heterogeneity and immune microenvironment. In this study, we developed an autologous humanized mouse cancer model by engrafting NSG mice with patient-derived xenografts and infused matched peripheral blood mononuclear cells (PBMCs). We first defined the time course of xenogeneic graft-versus-host-disease (xGVHD) and determined that only minimal xGVHD was observed for up to 8 weeks. Next, colorectal and pancreatic cancer patient-derived xenograft bearing NSG mice were infused with 5x106 human PBMCS for development of the humanized cancer models (iPDX). Early after infusion of human PBMCs, iPDX mice demonstrated engraftment of human CD4+ and CD8+ T cells in the blood of both colorectal and pancreatic cancer patient-derived models that persisted for up to 8 weeks. At the end of the experiment, iPDX xenografts maintained the features of the primary human tumor including tumor grade and cell type. The iPDX tumors demonstrated infiltration of human CD3+ cells with high PD-1 expression although we observed significant intra and inter- model variability. In summary, the iPDX models reproduced key features of the corresponding human tumor. The observed variability and high PD-1 expression are important considerations that need to be addressed in order to develop a reproducible model system.

Three-dimensional in vitro culture models in oncology research

Cancer is a multifactorial disease that is responsible for 10 million deaths per year. The intra- and inter-heterogeneity of malignant tumors make it difficult to develop single targeted approaches. Similarly, their diversity requires various models to investigate the mechanisms involved in cancer initiation, progression, drug resistance and recurrence. Of the in vitro cell-based models, monolayer adherent (also known as 2D culture) cell cultures have been used for the longest time. However, it appears that they are often less appropriate than the three-dimensional (3D) cell culture approach for mimicking the biological behavior of tumor cells, in particular the mechanisms leading to therapeutic escape and drug resistance. Multicellular tumor spheroids are widely used to study cancers in 3D, and can be generated by a multiplicity of techniques, such as liquid-based and scaffold-based 3D cultures, microfluidics and bioprinting. Organoids are more complex 3D models than multicellular tumor spheroids because they are generated from stem cells isolated from patients and are considered as powerful tools to reproduce the disease development in vitro. The present review provides an overview of the various 3D culture models that have been set up to study cancer development and drug response. The advantages of 3D models compared to 2D cell cultures, the limitations, and the fields of application of these models and their techniques of production are also discussed.

Patient-derived cancer models: Valuable platforms for anticancer drug testing

Molecularly targeted treatments and immunotherapy are cornerstones in oncology, with demonstrated efficacy across different tumor types. Nevertheless, the overwhelming majority metastatic disease is incurable due to the onset of drug resistance. Preclinical models including genetically engineered mouse models, patient-derived xenografts and two- and three-dimensional cell cultures have emerged as a useful resource to study mechanisms of cancer progression and predict efficacy of anticancer drugs. However, variables including tumor heterogeneity and the complexities of the microenvironment can impair the faithfulness of these platforms. Here, we will discuss advantages and limitations of these preclinical models, their applicability for drug testing and in co-clinical trials and potential strategies to increase their reliability in predicting responsiveness to anticancer medications.

Golden Syrian Hamster Models for Cancer Research

The golden Syrian hamster (Mesocricetus auratus) has long been a valuable rodent model of human diseases, especially infectious and metabolic diseases. Hamsters have also been valuable models of several chemically induced cancers such as the DMBA-induced oral cheek pouch cancer model. Recently, with the application of CRISPR/Cas9 genetic engineering technology, hamsters can now be gene targeted as readily as mouse models. This review describes the phenotypes of three gene-targeted knockout (KO) hamster cancer models, TP53, KCNQ1, and IL2RG. Notably, these hamster models demonstrate cancer phenotypes not observed in mouse KOs. In some cases, the cancers that arise in the KO hamster are similar to cancers that arise in humans, in contrast with KO mice that do not develop the cancers. An example is the development of aggressive acute myelogenous leukemia (AML) in TP53 KO hamsters. The review also presents a discussion of the relative strengths and weaknesses of mouse cancer models and hamster cancer models and argues that there are no perfect rodent models of cancer and that the genetically engineered hamster cancer models can complement mouse models and expand the suite of animal cancer models available for the development of new cancer therapies.

Mesenchymal tumor organoid models recapitulate rhabdomyosarcoma subtypes

Rhabdomyosarcomas (RMS) are mesenchyme-derived tumors and the most common childhood soft tissue sarcomas. Treatment is intense, with a nevertheless poor prognosis for high-risk patients. Discovery of new therapies would benefit from additional preclinical models. Here, we describe the generation of a collection of 19 pediatric RMS tumor organoid (tumoroid) models (success rate of 41%) comprising all major subtypes. For aggressive tumors, tumoroid models can often be established within 4-8 weeks, indicating the feasibility of personalized drug screening. Molecular, genetic, and histological characterization show that the models closely resemble the original tumors, with genetic stability over extended culture periods of up to 6 months. Importantly, drug screening reflects established sensitivities and the models can be modified by CRISPR/Cas9 with TP53 knockout in an embryonal RMS model resulting in replicative stress drug sensitivity. Tumors of mesenchymal origin can therefore be used to generate organoid models, relevant for a variety of preclinical and clinical research questions.

Challenges and opportunities in metastatic breast cancer treatments: Nano-drug combinations delivered preferentially to metastatic cells may enhance therapeutic response

Despite advances in breast cancer treatments and related 5-year survival outcomes, metastatic breast cancer cures remain elusive. The current standard of care includes a combination of surgery, radiation therapy and drug therapy. However, even the most advanced procedures and treatments do not prevent breast cancer recurrence and metastasis. Once metastasis occurs, patient prognosis is poor. Recent elucidation of the spatiotemporal transit of metastatic cancer cells from primary tumor sites to distant sites provide an opportunity to integrate knowledge of drug disposition in our effort to enhance drug localization and exposure in cancer laden tissues . Novel technologies have been developed, but could be further refined to facilitate the distribution of drugs to target cancer cells and tissues. The purpose of this review is to highlight the challenges in metastatic breast cancer treatment and focus on novel drug combination and nanotechnology approaches to overcome the challenges. With improved definition of metastatic tissue target, directed localization and retention of multiple, pharmacologically active drugs to tissues and cells of interest may overcome the limitations in breast cancer treatment that may lead to a cure for breast cancer.

Targeting lactate dehydrogenase B-dependent mitochondrial metabolism affects tumor initiating cells and inhibits tumorigenesis of non-small cell lung cancer by inducing mtDNA damage

Once considered a waste product of anaerobic cellular metabolism, lactate has been identified as a critical regulator of tumorigenesis, maintenance, and progression. The putative primary function of lactate dehydrogenase B (LDHB) is to catalyze the conversion of lactate to pyruvate; however, its role in regulating metabolism during tumorigenesis is largely unknown. To determine whether LDHB plays a pivotal role in tumorigenesis, we performed 2D and 3D in vitro experiments, utilized a conventional xenograft tumor model, and developed a novel genetically engineered mouse model (GEMM) of non-small cell lung cancer (NSCLC), in which we combined an LDHB deletion allele with an inducible model of lung adenocarcinoma driven by the concomitant loss of p53 (also known as Trp53) and expression of oncogenic KRAS (G12D) (KP). Here, we show that epithelial-like, tumor-initiating NSCLC cells feature oxidative phosphorylation (OXPHOS) phenotype that is regulated by LDHB-mediated lactate metabolism. We show that silencing of LDHB induces persistent mitochondrial DNA damage, decreases mitochondrial respiratory complex activity and OXPHOS, resulting in reduced levels of mitochondria-dependent metabolites, e.g., TCA intermediates, amino acids, and nucleotides. Inhibition of LDHB dramatically reduced the survival of tumor-initiating cells and sphere formation in vitro, which can be partially restored by nucleotide supplementation. In addition, LDHB silencing reduced tumor initiation and growth of xenograft tumors. Furthermore, we report for the first time that homozygous deletion of LDHB significantly reduced lung tumorigenesis upon the concomitant loss of Tp53 and expression of oncogenic KRAS without considerably affecting the animal's health status, thereby identifying LDHB as a potential target for NSCLC therapy. In conclusion, our study shows for the first time that LDHB is essential for the maintenance of mitochondrial metabolism, especially nucleotide metabolism, demonstrating that LDHB is crucial for the survival and proliferation of NSCLC tumor-initiating cells and tumorigenesis.

Strategies to enhance drug delivery to solid tumors by harnessing the EPR effects and alternative targeting mechanisms

The Enhanced Permeability and Retention (EPR) effect has been recognized as the central paradigm in tumor-targeted delivery in the last decades. In the wake of this concept, nanotechnologies have reached phenomenal levels in research. However, clinical tumors display a poor manifestation of EPR effect. Factors including tumor heterogeneity, complicating tumor microenvironment, and discrepancies between laboratory models and human tumors largely contribute to poor efficiency in tumor-targeted delivery and therapeutic failure in clinical translation. In this article, approaches for evaluation of EPR effect in human tumor were overviewed as guidance to employ EPR effect for cancer treatment. Strategies to augment EPR-mediated tumoral delivery are discussed in different dimensions including enhancement of vascular permeability, depletion of tumor extracellular matrix and optimization of nanoparticle design. Besides, the recent development in alternative tumor-targeted delivery mechanisms are highlighted including transendothelial pathway, endogenous cell carriers and non-immunogenic bacteria-mediated delivery. In addition, the emerging preclinical models better reflect human tumors are introduced. Finally, more rational applications of EPR effect in other disease and field are proposed. This article elaborates on fundamental reasons for the gaps between theoretical expectation and clinical outcomes, attempting to provide some perspective directions for future development of cancer nanomedicines in this still evolving landscape.

CAR T Cell Locomotion in Solid Tumor Microenvironment

The promising outcomes of chimeric antigen receptor (CAR) T cell therapy in hematologic malignancies potentiates its capability in the fight against many cancers. Nevertheless, this immunotherapy modality needs significant improvements for the treatment of solid tumors. Researchers have incrementally identified limitations and constantly pursued better CAR designs. However, even if CAR T cells are armed with optimal killer functions, they must overcome and survive suppressive barriers imposed by the tumor microenvironment (TME). In this review, we will discuss in detail the important role of TME in CAR T cell trafficking and how the intrinsic barriers contribute to an immunosuppressive phenotype and cancer progression. It is of critical importance that preclinical models can closely recapitulate the in vivo TME to better predict CAR T activity. Animal models have contributed immensely to our understanding of human diseases, but the intensive care for the animals and unreliable representation of human biology suggest in vivo models cannot be the sole approach to CAR T cell therapy. On the other hand, in vitro models for CAR T cytotoxic assessment offer valuable insights to mechanistic studies at the single cell level, but they often lack in vivo complexities, inter-individual heterogeneity, or physiologically relevant spatial dimension. Understanding the advantages and limitations of preclinical models and their applications would enable more reliable prediction of better clinical outcomes.

Tumour invasion and dissemination

Activating invasion and metastasis are one of the primary hallmarks of cancer, the latter representing the leading cause of death in cancer patients. Whilst many advances in this area have been made in recent years, the process of cancer dissemination and the underlying mechanisms governing invasion are still poorly understood. Cancer cells exhibit multiple invasion strategies, including switching between modes of invasion and plasticity in response to therapies, surgical interventions and environmental stimuli. The ability of cancer cells to switch migratory modes and their inherent plasticity highlights the critical challenge preventing the successful design of cancer and anti-metastatic therapies. This mini-review presents current knowledge on the critical models of tumour invasion and dissemination. We also discuss the current issues surrounding current treatments and arising therapeutic opportunities. We propose that the establishment of novel approaches to study the key biological mechanisms underlying the metastatic cascade is critical in finding novel targets that could ultimately lead to complete inhibition of cancer cell invasion and dissemination.

Biomarkers and 3D models predicting response to immune checkpoint blockade in head and neck cancer (Review)

Immunotherapy has evolved into a powerful tool in the fight against a number of types of cancer, including head and neck squamous cell carcinomas (HNSCC). Although checkpoint inhibition (CPI) has definitely enriched the treatment options for advanced stage HNSCC during the past decade, the percentage of patients responding to treatment is widely varying between 14-32% in second-line setting in recurrent or metastatic HNSCC with a sporadic durability. Clinical response and, consecutively, treatment success remain unpredictable in most of the cases. One potential factor is the expression of target molecules of the tumor allowing cancer cells to acquire therapy resistance mechanisms. Accordingly, analyzing and modeling the complexity of the tumor microenvironment (TME) is key to i) stratify subgroups of patients most likely to respond to CPI and ii) to define new combinatorial treatment regimens. Particularly in a heterogeneous disease such as HNSCC, thoroughly studying the interactions and crosstalking between tumor and TME cells is one of the biggest challenges. Sophisticated 3D models are therefore urgently needed to be able to validate such basic science hypotheses and to test novel immuno-oncologic treatment regimens in consideration of the individual biology of each tumor. The present review will first summarize recent findings on immunotherapy, predictive biomarkers, the role of the TME and signaling cascades eliciting during CPI. Second, it will highlight the significance of current promising approaches to establish HNSCC 3D models for new immunotherapies. The results are encouraging and indicate that data obtained from patient-specific tumors in a dish might be finally translated into personalized immuno-oncology.

In Vivo Modeling of Human Breast Cancer Using Cell Line and Patient-Derived Xenografts

Historically, human breast cancer has been modeled largely in vitro using long-established cell lines primarily in two-dimensional culture, but also in three-dimensional cultures of varying cellular and molecular complexities. A subset of cell line models has also been used in vivo as cell line-derived xenografts (CDX). While outstanding for conducting detailed molecular analysis of regulatory mechanisms that may function in vivo, results of drug response studies using long-established cell lines have largely failed to translate clinically. In an attempt to address this shortcoming, many laboratories have succeeded in developing clinically annotated patient-derived xenograft (PDX) models of human cancers, including breast, in a variety of host systems. While immunocompromised mice are the predominant host, the immunocompromised rat and pig, zebrafish, as well as the chicken egg chorioallantoic membrane (CAM) have also emerged as potential host platforms to help address perceived shortcomings of immunocompromised mice. With any modeling platform, the two main issues to be resolved are criteria for "credentialing" the models as valid models to represent human cancer, and utility with respect to the ability to generate clinically relevant translational research data. Such data are beginning to emerge, particularly with the activities of PDX consortia such as the NCI PDXNet Program, EuroPDX, and the International Breast Cancer Consortium, as well as a host of pharmaceutical companies and contract research organizations (CRO). This review focuses primarily on these important aspects of PDX-related research, with a focus on breast cancer.

Moving beyond descriptive studies: harnessing metabolomics to elucidate the molecular mechanisms underpinning host-microbiome phenotypes

Advances in technology and software have radically expanded the scope of metabolomics studies and allow us to monitor a broad transect of central carbon metabolism in routine studies. These increasingly sophisticated tools have shown that many human diseases are modulated by microbial metabolism. Despite this, it remains surprisingly difficult to move beyond these statistical associations and identify the specific molecular mechanisms that link dysbiosis to the progression of human disease. This difficulty stems from both the biological intricacies of host-microbiome dynamics as well as the analytical complexities inherent to microbiome metabolism research. The primary objective of this review is to examine the experimental and computational tools that can provide insights into the molecular mechanisms at work in host-microbiome interactions and to highlight the undeveloped frontiers that are currently holding back microbiome research from fully leveraging the benefits of modern metabolomics.

Emerging drug targets for triple-negative breast cancer: A guided tour of the preclinical landscape

INTRODUCTION

Triple-negative breast cancer (TNBC) is the most fatal molecular subtype of breast cancer because of its aggressiveness and resistance to chemotherapy. FDA-approved therapies for TNBC are limited to poly(ADP-ribose) polymerase inhibitors, immune checkpoint inhibitors, and trophoblast cell surface antigen 2-targeted antibody-drug conjugate. Therefore, developing a novel effective targeted therapy for TNBC is an urgent unmet need.

AREAS COVERED

In this narrative review, we discuss emerging targets for TNBC treatment discovered in early translational studies. We focus on cancer cell membrane molecules, hyperactive intracellular signaling pathways, and the tumor microenvironment (TME) based on their druggability, therapeutic potency, specificity to TNBC, and application in immunotherapy.

EXPERT OPINION

The significant challenges in the identification and validation of TNBC-associated targets are 1) application of appropriate genetic, molecular, and immunological approaches for modulating the target, 2) establishment of a proper mouse model that accurately represents the human immune TME, 3) TNBC molecular heterogeneity, and 4) failure translation of preclinical findings to clinical practice. To overcome those difficulties, future research needs to apply novel technology, such as single-cell RNA sequencing, thermostable group II intron reverse transcriptase sequencing, and humanized mouse models. Further, combination treatment targeting multiple pathways in both the TNBC tumor and its TME is essential for effective disease control.

Ex Vivo Organoid Model of Adenovirus-Cre Mediated Gene Deletions in Mouse Urothelial Cells

Bladder cancer is an understudied area, particularly in genetically engineered mouse models (GEMMs). Inbred GEMMs with tissue-specific Cre and loxP sites have been the gold standards for conditional or inducible gene targeting. To provide faster and more efficient experimental models, an ex vivo organoid culture system is developed using adenovirus Cre and normal urothelial cells carrying multiple loxP alleles of the tumor suppressors Trp53, Pten, and Rb1. Normal urothelial cells are enzymatically disassociated from four bladders of triple floxed mice (Trp53f/f: Ptenf/f: Rb1f/f). The urothelial cells are transduced ex vivo with adenovirus-Cre driven by a CMV promoter (Ad5CMVCre). The transduced bladder organoids are cultured, propagated, and characterized in vitro and in vivo. PCR is used to confirm gene deletions in Trp53, Pten, and Rb1. Immunofluorescence (IF) staining of organoids demonstrates positive expression of urothelial lineage markers (CK5 and p63). The organoids are injected subcutaneously into host mice for tumor expansion and serial passages. The immunohistochemistry (IHC) of xenografts exhibits positive expression of CK7, CK5, and p63 and negative expression of CK8 and Uroplakin 3. In summary, adenovirus-mediated gene deletion from mouse urothelial cells engineered with loxP sites is an efficient method to rapidly test the tumorigenic potential of defined genetic alterations.

Obesity-Associated Cancers: Evidence from Studies in Mouse Models

Obesity, one of the major problems in modern human society, is correlated with various diseases, including type 2 diabetes mellitus (T2DM). In particular, epidemiological and experimental evidence indicates that obesity is closely linked to at least 13 different types of cancer. The mechanisms that potentially explain the link between obesity and cancer include hyperactivation of the IGF pathway, metabolic dysregulation, dysfunctional angiogenesis, chronic inflammation, and interaction between pro-inflammatory cytokines, endocrine hormones, and adipokines. However, how the largely uniform morbidity of obesity leads to different types of cancer still needs to be investigated. To study the link between obesity and cancer, researchers have commonly used preclinical animal models, particularly mouse models. These models include monogenic models of obesity (e.g., ob/ob and db/db mice) and genetically modified mouse models of human cancers (e.g., Kras-driven pancreatic cancer, Apc-mutated colorectal cancer, and Her2/neu-overexpressing breast cancer). The experimental results obtained using these mouse models revealed strong evidence of a link between obesity and cancer and suggested their underlying mechanisms.

Models of Renal Cell Carcinoma Used to Investigate Molecular Mechanisms and Develop New Therapeutics

Modeling renal cell carcinoma is critical to investigating tumor biology and therapeutic mechanisms. Multiple systems have been developed to represent critical components of the tumor and its surrounding microenvironment. Prominent in vitro models include traditional cell cultures, 3D organoid models, and microphysiological devices. In vivo models consist of murine patient derived xenografts or genetically engineered mice. Each system has unique advantages as well as limitations and researchers must thoroughly understand each model to properly investigate research questions. This review addresses common model systems for renal cell carcinoma and critically evaluates their performance and ability to measure tumor characteristics.

Advanced Strategies for Therapeutic Targeting of Wild-Type and Mutant p53 in Cancer

TP53 is a tumor suppressor gene that encodes a sequence-specific DNA-binding transcription factor activated by stressful stimuli; it upregulates target genes involved in growth suppression, cell death, DNA repair, metabolism, among others. TP53 is the most frequently mutated gene in tumors, with mutations not only leading to loss-of-function (LOF), but also gain-of-function (GOF) that promotes tumor progression, and metastasis. The tumor-specific status of mutant p53 protein has suggested it is a promising target for cancer therapy. We summarize the current progress of targeting wild-type and mutant p53 for cancer therapy through biotherapeutic and biopharmaceutical methods for (1) boosting p53 activity in cancer, (2) p53-dependent and p53-independent strategies for targeting p53 pathway functional restoration in p53-mutated cancer, (3) targeting p53 in immunotherapy, and (4) combination therapies targeting p53, p53 checkpoints, or mutant p53 for cancer therapy.

Recent research advances of the biomimetic tumor microenvironment and regulatory factors on microfluidic devices: A systematic review

Tumor microenvironment is a multicomponent system consisting of tumor cells, noncancer cells, extracellular matrix, and signaling molecules, which hosts tumor cells with integrated biophysical and biochemical elements. Because of its critical involvement in tumor genesis, invasion, metastasis, and resistance, the tumor microenvironment is emerging as a hot topic of tumor biology and a prospective therapeutic target. Unfortunately, the complex of microenvironment modeling in vitro is technically challenging and does not effectively generalize the local tumor tissue milieu. Recently, significant advances in microfluidic technologies have provided us with an approach to imitate physiological systems that can be utilized to mimic the characterization of tumor responses with pathophysiological relevance in vitro. In this review, we highlight the recent progress and innovations in microfluidic technology that facilitates the tumor microenvironment study. We also discuss the progress and future perspective of microfluidic bionic approaches with high efficiency for the study of tumor microenvironment and the challenges encountered in cancer research, drug discovery, and personalized therapy.

Clinical Translation of Neutrophil Imaging and Its Role in Cancer

Neutrophils are the first line of defense against pathogens and abnormal cells. They regulate many biological processes such as infections and inflammation. Increasing evidence demonstrated a role for neutrophils in cancer, where different subpopulations have been found to possess both pro- or anti-tumorigenic functions in the tumor microenvironment. In this review, we discuss the phenotypic and functional diversity of neutrophils in cancer, their prognostic significance, and therapeutic relevance in human and preclinical models. Molecular imaging methods are increasingly used to probe neutrophil biology in vivo, as well as the cellular changes that occur during tumor progression and over the course of treatment. This review will discuss the role of neutrophil imaging in oncology and the lessons that can be drawn from imaging in infectious diseases and inflammatory disorders. The major factors to be considered when developing imaging techniques and biomarkers for neutrophils in cancer are reviewed. Finally, the potential clinical applications and the limitations of each method are discussed, as well as the challenges for future clinical translation.

Novel Mouse Models for Cancer Immunology

Mouse models for the study of cancer immunology provide excellent systems in which to test biological mechanisms of the immune response against cancer. Historically, these models have been designed to have different strengths based on the current major research questions at the time. As such, many mouse models of immunology used today were not originally developed to study questions currently plaguing the relatively new field of cancer immunology, but instead have been adapted for such purposes. In this review, we discuss various mouse model of cancer immunology in a historical context as a means to provide a fuller perspective of each model's strengths. From this outlook, we discuss the current state of the art and strategies for tackling future modeling challenges.

Monitoring Immune Cell Function Through Optical Imaging: a Review Highlighting Transgenic Mouse Models

Transgenic mouse models have facilitated research of human diseases and validation of therapeutic approaches. Inclusion of optical reporter genes (fluorescent or bioluminescent genes) in the targeting vectors used to develop such models makes in vivo imaging of cellular and molecular events possible, from the microscale to the macroscale. In particular, transgenic mouse models expressing optical reporter genes allowed accurately distinguishing immune cell types from trafficking in vivo using intravital microscopy or whole-body optical imaging. Besides lineage tracing and trafficking of different subsets of immune cells, the ability to monitor the function of immune cells is of pivotal importance for investigating the effects of immunotherapies against cancer. Here, we introduce the reader to state-of-the-art approaches to develop transgenics, optical imaging techniques, and several notable examples of transgenic mouse models developed for immunology research by critically highlighting the models that allow the following of immune cell function.

Leukemia's Next Top Model? Syngeneic Models to Advance Adoptive Cellular Therapy

In recent years, there has been an emphasis on harnessing the immune system for therapeutic interventions. Adoptive cell therapies (ACT) have emerged as an effective option for B-cell derived hematological malignancies. Despite remarkable successes with ACT, immune dysregulation and the leukemia microenvironment can critically alter clinical responses. Therefore, preclinical modeling can contribute to the advancement of ACT for leukemias. Human xenografts, the current mainstay of ACT in vivo models, cannot evaluate the impact of the immunosuppressive leukemia microenvironment on adoptively transferred cells. Syngeneic mouse models utilize murine tumor models and implant them into immunocompetent mice. This provides an alternative model, reducing the need for complicated breeding strategies while maintaining a matched immune system, stromal compartment, and leukemia burden. Syngeneic models that evaluate ACT have analyzed the complexity of cytotoxic T lymphocytes, T cell receptor transgenics, and chimeric antigen receptors. This review examines the immunosuppressive features of the leukemia microenvironment, discusses how preclinical modeling helps predict ACT associated toxicities and dysfunction, and explores publications that have employed syngeneic modeling in ACT studies for the improvement of therapy for leukemias.

CRISPR somatic genome engineering and cancer modeling in the mouse pancreas and liver

Genetically engineered mouse models (GEMMs) transformed the study of organismal disease phenotypes but are limited by their lengthy generation in embryonic stem cells. Here, we describe methods for rapid and scalable genome engineering in somatic cells of the liver and pancreas through delivery of CRISPR components into living mice. We introduce the spectrum of genetic tools, delineate viral and nonviral CRISPR delivery strategies and describe a series of applications, ranging from gene editing and cancer modeling to chromosome engineering or CRISPR multiplexing and its spatio-temporal control. Beyond experimental design and execution, the protocol describes quantification of genetic and functional editing outcomes, including sequencing approaches, data analysis and interpretation. Compared to traditional knockout mice, somatic GEMMs face an increased risk for mouse-to-mouse variability because of the higher experimental demands of the procedures. The robust protocols described here will help unleash the full potential of somatic genome manipulation. Depending on the delivery method and envisaged application, the protocol takes 3-5 weeks.

Use of Patient-Derived Organoids as a Treatment Selection Model for Colorectal Cancer: A Narrative Review

Simple Summary

Colorectal cancer (CRC) is the third most common type of cancer globally. Despite successful treatment, it has a 40% chance of recurrence within five years after surgery. While neoadjuvant chemotherapy is offered for stage IV cancers, it comes with a risk of resistance and disease progression. CRC tumors vary biologically, recur frequently, and pose a significant risk for cancer-related mortality, making it increasingly relevant to develop methods to study personalized treatment. A tumor organoid is a miniature, multicellular, and 3D replica of a tumor in vitro that retains its characteristics. Here, we discuss the current methods of culturing organoids and the correlation of drug response in organoids with clinical responses in patients. This helps us to determine whether organoids can be used for treatment selection in a clinical setting. Based on the studies included, there was a strong correlation between treatment responses of organoids and clinical treatment responses.

Abstract

Surgical resection is the mainstay in intended curative treatment of colorectal cancer (CRC) and may be accompanied by adjuvant chemotherapy. However, 40% of the patients experience recurrence within five years of treatment, highlighting the importance of improved, personalized treatment options. Monolayer cell cultures and murine models, which are generally used to study the biology of CRC, are associated with certain drawbacks; hence, the use of organoids has been emerging. Organoids obtained from tumors display similar genotypic and phenotypic characteristics, making them ideal for investigating individualized treatment strategies and for integration as a core platform to be used in prediction models. Here, we review studies correlating the clinical response in patients with CRC with the therapeutic response in patient-derived organoids (PDO), as well as the limitations and potentials of this model. The studies outlined in this review reported strong associations between treatment responses in the PDO model and clinical treatment responses. However, as PDOs lack the tumor microenvironment, they do not genuinely account for certain crucial characteristics that influence therapeutic response. To this end, we reviewed studies investigating PDOs co-cultured with tumor-infiltrating lymphocytes. This model is a promising method allowing evaluation of patient-specific tumors and selection of personalized therapies. Standardized methodologies must be implemented to reach a “gold standard” for validating the use of this model in larger cohorts of patients. The introduction of this approach to a clinical scenario directing neoadjuvant treatment and in other curative and palliative treatment strategies holds incredible potential for improving personalized treatment and its outcomes.

Proteomic profiling reveals antitumor effects of RT2 peptide on a human colon carcinoma xenograft mouse model

A comparative study of human colon HCT-116 xenograft in nude mice treated with and without peptide RT2 at high doses is performed along with a label-free proteomic analysis of the tissue in order to understand the potential mechanisms by which RT2 acts in vivo against colorectal tumors. RT2 displays no significant systematic toxicity, but reduces tumor growth after either intraperitoneal or intratumoral injection demonstrating it is a safe and efficacious antitumor agent in vivo. Of the 3196 proteins identified by label-free proteomics, 61 proteins appear only in response to RT2 and are involved in cellular processes largely localized in the cells and cell parts. Some of the proteins identified, including CFTR, Wnt7a, TIA1, PADI2, NRBP2, GADL1, LZIC, TLR6, and GPR37, have been reported to suppress tumor growth and are associated with cell proliferation, invasion, metastasis, angiogenesis, apoptosis, and immune evasion. Our work supports their role as tumor biomarkers and reveals RT2 has a complex mechanism of action in vivo.

Power in Numbers: Harnessing Combinatorial and Integrated Screens to Advance Nanomedicine

Nanocarriers have significant potential to advance personalized medicine through targeted drug delivery. However, to date, efforts to improve nanoparticle accumulation at target disease sites have largely failed to translate clinically, stemming from an incomplete understanding of nano-bio interactions. While progress has been made to evaluate the effects of specific physical and chemical nanoparticle properties on trafficking and uptake, there is much to be gained from controlling these properties singularly and in combination to determine their interactions with different cell types. We and others have recently begun leveraging library-based nanoparticle screens to study structure-function relationships of lipid- and polymer-based drug delivery systems to guide nanoparticle design. These combinatorial screening efforts are showing promise in leading to the successful identification of critical characteristics that yield improved and specific accumulation at target sites. However, there is a crucial need to equally consider the influence of biological complexity on nanoparticle delivery, particularly in the context of clinical translation. For example, tissue and cellular heterogeneity presents an additional dimension to nanoparticle trafficking, uptake, and accumulation; applying imaging and screening tools as well as bioinformatics may further expand our understanding of how nanoparticles engage with cells and tissues. Given recent advances in the fields of omics and machine learning, there is substantial promise to revolutionize nanocarrier development through the use of integrated screens, harnessing the combinatorial parameter space afforded both by nanoparticle libraries and clinically annotated biological data sets in combination with high throughput in vivo studies.

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.

Synthesis of Novel Suramin Analogs With Anti-Proliferative Activity via FGF1 and FGFRD2 Blockade

A promising approach in cancer therapy is the inhibition of cell proliferation using small molecules. In this study, we report the synthesis of suramin derivatives and their applications. We used NMR spectroscopy and docking simulations to confirm binding sites and three-dimensional models of the ligand-protein complex. The WST-1 assay was used to assess cell viability and cell proliferation in vitro to evaluate the inhibition of protein-protein interactions and to investigate the anti-proliferative activities in a breast cancer cell line. All the suramin derivatives showed anti-proliferative activity by blocking FGF1 binding to its receptor FGFRD2. The dissociation constant was measured by fluorescence spectroscopy. The suramin compound derivatives synthesized herein show potential as novel therapeutic agents for their anti-proliferative activity via the inhibition of protein-protein interactions. The cytotoxicity of these suramin derivatives was lower than that of the parent suramin compound, which may be considered a significant advancement in this field. Thus, these novel suramin derivatives may be considered superior anti-metastasis molecules than those of suramin.

Reprogramming Mouse Oviduct Epithelial Cells Using In Vivo Electroporation and CRISPR/Cas9-Mediated Genetic Manipulation

Advances in gene editing tools such as CRISPR/Cas9 have made precise in vivo gene editing possible, opening up avenues of research into somatic cell reprograming to study adult stem cells, homeostasis, and malignant transformation. Here we describe a method for CRISPR/Cas9 mediated in vivo gene editing, in combination with Cre-based lineage tracing via electroporation in the mouse oviduct. This method facilitates the delivery of multiple plasmids into oviduct epithelial cells, sufficient for studying homeostasis and generation of high-grade serous ovarian cancer (HGSOC) models.

Discovery of Targets for Cancer Immunoprevention

Antibodies against autologous tumor-associated antigens have been demonstrated as being useful biomarkers for early cancer diagnosis and prognosis. They have several advantages such as long half-life (7-30 days depending on subtiter of Ig), inherent stability in patients' blood due to not being subjected to proteolysis, well-studied biochemical properties, and their easy detections via secondary antibodies or antigens. Moreover, they can be easily screened in the serum using a noninvasive approach. Consequently, many technical approaches have been developed to study autoantibodies. We used serological proteome analysis (SERPA) for analyzing antibodies in pancreatic cancer patients' sera, and the technique will be discussed in detail. SERPA has several advantages over other approaches currently used such as SEREX (serological analysis of tumor antigens by recombinant cDNA expression cloning) and phage display. SEREX involves the construction of a lambda phage cDNA library from tumor samples to infect bacteria. While library construction is a quite laborious and time-consuming procedure in SEREX, detection of posttranslational modifications that could be fundamental for antibody recognition is a major limitation of both SEREX and phage display techniques. SERPA avoids the time-consuming construction of cDNA libraries. In addition, since it does not rely on bacterial expression of antigens, antigens will have their usual posttranslational modifications preventing false-positive or -negative results in autoantibody profiling.

Immuno-oncology trends: preclinical models, biomarkers, and clinical development

The landscape in immuno-oncology (I-O) has undergone profound changes since its early beginnings up through the rapid advances happening today. The current drug development pipeline consists of thousands of potential I-O therapies and therapy combinations, many of which are being evaluated in clinical trials. The efficient and successful development of these assets requires the investment in and utilization of appropriate tools and technologies that can facilitate the rapid transitions from preclinical evaluation through clinical development. These tools include (i) appropriate preclinical models, (ii) biomarkers of pharmacodynamic, predictive and monitoring utility, and (iii) evolving clinical trial designs that allow rapid and efficient evaluation during the development process. This article provides an overview of how novel discoveries and insights into each of these three areas have the potential to further address the clinical management needs for patients with cancer.

Organoids as research models for hepatocellular carcinoma

Organoid culture is an emerging research tool that has proved tremendously useful in a multitude of aspects, one of which is cancer research. They largely overcome the limitations of previous cancer models by their faithful recapitulation of the in vivo biology, while still remaining amenable to perturbations. Using a cocktail of biologicals that mimic the stem cell niche signaling, hepatocellular carcinoma (HCC) organoids could be generated from tissue samples of both human and murine origin. Existing reports show that HCC organoids retain key characteristics of their parental tumor tissue, including the histological architecture, genomic landscape, expression profile and intra-tumor heterogeneity. There is ongoing effort to establish living biobanks of patient-derived cancer organoids, annotated with multi-omics data and clinical data, and they can be particularly valuable in stratification of HCC subtypes, pre-clinical drug discovery and personalized medicine. In the future, efforts in the standardization of procedures and nomenclature, refinement of protocols, as well as engineering of the culture systems will enable scientists to unleash the full potential of organoid technology.

Impact of cancer cell-intrinsic features on neutrophil behavior

Neutrophils are multifaceted innate immune cells that play a significant role in the progression of cancer by exerting both pro- and anti-tumorigenic functions. The crosstalk between cancer cells and neutrophils is complex and emerging evidence is pointing at cancer cell-intrinsic programs regulating neutrophil abundance, phenotype and function. Cancer cell-derived soluble mediators are key players in modulating the interaction with neutrophils. Here, we review how intrinsic features of cancer cells, including cancer cell genetics, epigenetics, signaling, and metabolism, manipulate neutrophil behavior and how to target these processes to impact cancer progression. A molecular understanding of cancer cell-intrinsic properties that shape the crosstalk with neutrophils will provide novel therapeutic strategies for personalized immunomodulation in cancer patients.

Capturing cancer evolution using genetically engineered mouse models (GEMMs)

Initiating from a single cell, cancer undergoes clonal evolution, leading to a high degree of intratumor heterogeneity (ITH). The arising genetic heterogeneity between cancer cells is influenced by exogenous and endogenous forces that shape the composition of clones within tumors. Preclinical mouse models have provided a valuable tool for understanding cancer, helping to build a fundamental understanding of tumor initiation, progression, and metastasis. Until recently, genetically engineered mouse models (GEMMS) of cancer had lacked the genetic diversity found in human tumors, in which evolution may be driven by long-term carcinogen exposure and DNA damage. However, advances in sequencing technology and in our understanding of the drivers of genetic instability have given us the knowledge to generate new mouse models, offering an approach to functionally explore mechanisms of tumor evolution.

Scientific Validation and Clinical Application of Lung Cancer Organoids

Lung cancer organoid (LCO) is a novel model of lung cancer that facilitates drug screening. However, the success rate of LCOs varies from 7% to 87%, and the culture medium compositions are markedly different. Airway organoid media can be used for LCO cultures, but this promotes the overgrowth of normal cell organoids especially in LCOs from intrapulmonary lesions. Several modified media are specifically utilized for promoting the cancer cell's growth. For culturing high-purity LCOs, cancer cells from metastatic lesions and malignant effusions are used. Recently, single-cell RNA sequencing has identified previously unknown cell populations in the lungs and lung cancer. This sequencing technology can be used to validate whether the LCO recapitulates the heterogeneity and functional hierarchy of the primary tumor. Several groups have attempted to culture LCOs with mesenchymal cells and immune cells to recapitulate the tumor microenvironment. Disease modeling using LCO provides novel insight into the pathophysiology of lung cancer and enables high-throughput screening for drug discovery and prognosis prediction. An LCO model would help to identify new concepts as a basis for lung cancer targeting by discovering innovative therapeutic targets.

Preclinical Solid Tumor Models to Study Novel Therapeutics in Brain Metastases

Metastases are the most common malignancy of the adult central nervous system and are becoming an increasingly troubling problem in oncology largely due to the lack of successful therapeutic options. The limited selection of treatments is a result of the currently poor understanding of the biological mechanisms of metastatic development, which in turn is difficult to achieve because of limited preclinical models that can accurately represent the clinical progression of metastasis. Described in this article are in vitro and in vivo model systems that are used to enhance the understanding of metastasis and to identify new therapies for the treatment of brain metastasis. © 2021 Wiley Periodicals LLC.