Longitudinal assessment of tumor development using cancer avatars derived from genetically engineered pluripotent stem cells

Advancing Glioblastoma Research with Innovative Brain Organoid-Based Models

Glioblastoma (GBM) is a relatively rare but highly aggressive form of brain cancer characterized by rapid growth, invasiveness, and resistance to standard therapies. Despite significant progress in understanding its molecular and cellular mechanisms, GBM remains one of the most challenging cancers to treat due to its high heterogeneity and complex tumor microenvironment. To address these obstacles, researchers have employed a range of models, including in vitro cell cultures and in vivo animal models, but these often fail to replicate the complexity of GBM. As a result, there has been a growing focus on refining these models by incorporating human-origin cells, along with advanced genetic techniques and stem cell-based bioengineering approaches. In this context, a variety of GBM models based on brain organoids were developed and confirmed to be clinically relevant and are contributing to the advancement of GBM research at the preclinical level. This review explores the preparation and use of brain organoid-based models to deepen our understanding of GBM biology and to explore novel therapeutic approaches. These innovative models hold significant promise for improving our ability to study this deadly cancer and for advancing the development of more effective treatments.

Brain tumors and induced pluripotent stem cell technology: a systematic review of the literature

Background

Induced pluripotent stem cells (iPSCs) provide a novel approach to studying the pathophysiology of brain tumors and assessing various therapeutic techniques with greater precision. This study aims to systematically review the existing literature to critically analyze and synthesize current research findings. The objective is to evaluate the role of iPSCs in understanding brain tumors and in the development of innovative treatment strategies.

Methods

We systematically reviewed existing articles that utilized iPSC technology to assess either the pathophysiology of brain tumors or therapeutic techniques, following the standards of Preferred Reporting Items for Systematic review and Meta-Analysis guidelines. Key terms were comprehensively searched in electronic databases, including PubMed, EMBASE, and Scopus. Articles were screened based on specific inclusion and exclusion criteria. Ultimately, 22 relevant articles were chosen, and their data were extracted.

Results

The summary of findings for each selected article was organized into two general categories: "Methods of Generating iPSCs" and "Applications of iPSCs." The methods of iPSC generation, including transfection and transduction, as well as the types of viral or non-viral vectors used, were extracted and reported for each study. Additionally, the main aims of the selected studies, whether modeling or therapeutic approaches, were gathered and reported in the results section.

Conclusion

iPSC technology is a novel vehicle that brings new solutions to overcome difficulties in brain tumor studies. In vivo and in vitro models generated from iPSCs provide suitable platforms to investigate the pathophysiology of brain tumors more precisely. Also, iPSCs have been utilized in various studies to examine how different antitumor agents may affect the target cells.

Cell-Based Glioma Models for Anticancer Drug Screening: From Conventional Adherent Cell Cultures to Tumor-Specific Three-Dimensional Constructs

Gliomas are a group of primary brain tumors characterized by their aggressive nature and resistance to treatment. Infiltration of surrounding normal tissues limits surgical approaches, wide inter- and intratumor heterogeneity hinders the development of universal therapeutics, and the presence of the blood-brain barrier reduces the efficiency of their delivery. As a result, patients diagnosed with gliomas often face a poor prognosis and low survival rates. The spectrum of anti-glioma drugs used in clinical practice is quite narrow. Alkylating agents are often used as first-line therapy, but their effectiveness varies depending on the molecular subtypes of gliomas. This highlights the need for new, more effective therapeutic approaches. Standard drug-screening methods involve the use of two-dimensional cell cultures. However, these models cannot fully replicate the conditions present in real tumors, making it difficult to extrapolate the results to humans. We describe the advantages and disadvantages of existing glioma cell-based models designed to improve the situation and build future prospects to make drug discovery comprehensive and more effective for each patient according to personalized therapy paradigms.

Integration of Computational Pipeline to Streamline Efficacious Drug Nomination and Biomarker Discovery in Glioblastoma

Glioblastoma multiforme (GBM) is the deadliest, most heterogeneous, and most common brain cancer in adults. Not only is there an urgent need to identify efficacious therapeutics, but there is also a great need to pair these therapeutics with biomarkers that can help tailor treatment to the right patient populations. We built patient drug response models by integrating patient tumor transcriptome data with high-throughput cell line drug screening data as well as Bayesian networks to infer relationships between patient gene expression and drug response. Through these discovery pipelines, we identified agents of interest for GBM to be effective across five independent patient cohorts and in a mouse avatar model: among them are a number of MEK inhibitors (MEKis). We also predicted phosphoglycerate dehydrogenase enzyme (PHGDH) gene expression levels to be causally associated with MEKi efficacy, where knockdown of this gene increased tumor sensitivity to MEKi and overexpression led to MEKi resistance. Overall, our work demonstrated the power of integrating computational approaches. In doing so, we quickly nominated several drugs with varying known mechanisms of action that can efficaciously target GBM. By simultaneously identifying biomarkers with these drugs, we also provide tools to select the right patient populations for subsequent evaluation.

RNA splicing analysis deciphers developmental hierarchies and reveals therapeutic targets in adult glioma

Widespread alterations in RNA alternative splicing (AS) have been identified in adult gliomas. However, their regulatory mechanism, biological significance, and therapeutic potential remain largely elusive. Here, using a computational approach with both bulk and single-cell RNA-Seq, we uncover a prognostic AS signature linked with neural developmental hierarchies. Using advanced iPSC glioma models driven by glioma driver mutations, we show that this AS signature could be enhanced by EGFRvIII and inhibited by in situ IDH1 mutation. Functional validations of 2 isoform switching events in CERS5 and MPZL1 show regulations of sphingolipid metabolism and SHP2 signaling, respectively. Analysis of upstream RNA binding proteins reveals PTBP1 as a key regulator of the AS signature where targeting of PTBP1 suppresses tumor growth and promotes the expression of a neuron marker TUJ1 in glioma stem-like cells. Overall, our data highlights the role of AS in affecting glioma malignancy and heterogeneity and its potential as a therapeutic vulnerability for treating adult gliomas.

Glioblastoma evolution and heterogeneity from a 3D whole-tumor perspective

Treatment failure for the lethal brain tumor glioblastoma (GBM) is attributed to intratumoral heterogeneity and tumor evolution. We utilized 3D neuronavigation during surgical resection to acquire samples representing the whole tumor mapped by 3D spatial coordinates. Integrative tissue and single-cell analysis revealed sources of genomic, epigenomic, and microenvironmental intratumoral heterogeneity and their spatial patterning. By distinguishing tumor-wide molecular features from those with regional specificity, we inferred GBM evolutionary trajectories from neurodevelopmental lineage origins and initiating events such as chromothripsis to emergence of genetic subclones and spatially restricted activation of differential tumor and microenvironmental programs in the core, periphery, and contrast-enhancing regions. Our work depicts GBM evolution and heterogeneity from a 3D whole-tumor perspective, highlights potential therapeutic targets that might circumvent heterogeneity-related failures, and establishes an interactive platform enabling 360° visualization and analysis of 3D spatial patterns for user-selected genes, programs, and other features across whole GBM tumors.

Interconversion of Cancer Cells and Induced Pluripotent Stem Cells

Cancer cells, especially cancer stem cells (CSCs), share many molecular features with induced pluripotent stem cells (iPSCs) that enable the derivation of induced pluripotent cancer cells by reprogramming malignant cells. Conversely, normal iPSCs can be converted into cancer stem-like cells with the help of tumor microenvironment components and genetic manipulation. These CSC models can be utilized in oncogenic initiation and progression studies, understanding drug resistance, and developing novel therapeutic strategies. This review summarizes the role of pluripotency factors in the stemness, tumorigenicity, and therapeutic resistance of cancer cells. Different methods to obtain iPSC-derived CSC models are described with an emphasis on exposure-based approaches. Culture in cancer cell-conditioned media or cocultures with cancer cells can convert normal iPSCs into cancer stem-like cells, aiding the examination of processes of oncogenesis. We further explored the potential of reprogramming cancer cells into cancer-iPSCs for mechanistic studies and cancer dependencies. The contributions of genetic, epigenetic, and tumor microenvironment factors can be evaluated using these models. Overall, integrating iPSC technology into cancer stem cell research holds significant promise for advancing our knowledge of cancer biology and accelerating the development of innovative and tailored therapeutic interventions.

TGF-β and BMP signaling are associated with the transformation of glioblastoma to gliosarcoma and then osteosarcoma

Background

Gliosarcoma, an isocitrate dehydrogenase wildtype (IDH-WT) variant of glioblastoma, is defined by clonal biphasic differentiation into gliomatous and sarcomatous components. While the transformation from a glioblastoma to gliosarcoma is uncommon, the subsequent transformation to osteosarcoma is rare but may provide additional insights into the biology of these typically distinct cancers. We observed a patient initially diagnosed with glioblastoma, that differentiated into gliosarcoma at recurrence, and further evolved to osteosarcoma at the second relapse. Our objective was to characterize the molecular mechanisms of tumor progression associated with this phenotypic transformation.

Methods

Tumor samples were collected at all 3 stages of disease and RNA sequencing was performed to capture their transcriptomic profiles. Sequential clonal evolution was confirmed by the maintenance of an identical PTEN mutation throughout the tumor differentiation using the TSO500 gene panel. Publicly available datasets and the Nanostring nCounter technology were used to validate the results.

Results

The glioblastoma tumor from this patient possessed mixed features of all 3 TCGA-defined transcriptomic subtypes of an IDH-WT glioblastoma and a proportion of osteosarcoma signatures were upregulated in the original tumor. Analysis showed that enhanced transforming growth factor-β (TGF-β) and bone morphogenic protein signaling was associated with tumor transformation. Regulatory network analysis revealed that TGF-β family signaling committed the lineage tumor to osteogenesis by stimulating the expression of runt-related transcription factor 2 (RUNX2), a master regulator of bone formation.

Conclusions

This unusual clinical case provided an opportunity to explore the modulators of longitudinal sarcomatous transformation, potentially uncovering markers indicating predisposition to this change and identification of novel therapeutic targets.

Exploring the promising potential of induced pluripotent stem cells in cancer research and therapy

The advent of iPSCs has brought about a significant transformation in stem cell research, opening up promising avenues for advancing cancer treatment. The formation of cancer is a multifaceted process influenced by genetic, epigenetic, and environmental factors. iPSCs offer a distinctive platform for investigating the origin of cancer, paving the way for novel approaches to cancer treatment, drug testing, and tailored medical interventions. This review article will provide an overview of the science behind iPSCs, the current limitations and challenges in iPSC-based cancer therapy, the ethical and social implications, and the comparative analysis with other stem cell types for cancer treatment. The article will also discuss the applications of iPSCs in tumorigenesis, the future of iPSCs in tumorigenesis research, and highlight successful case studies utilizing iPSCs in tumorigenesis research. The conclusion will summarize the advancements made in iPSC-based tumorigenesis research and the importance of continued investment in iPSC research to unlock the full potential of these cells.

Modeling brain and neural crest neoplasms with human pluripotent stem cells

Pluripotent stem cells offer unique avenues to study human-specific aspects of disease and are a highly versatile tool in cancer research. Oncogenic processes and developmental programs often share overlapping transcriptomic and epigenetic signatures, which can be reactivated in induced pluripotent stem cells. With the emergence of brain organoids, the ability to recapitulate brain development and structure has vastly improved, making in vitro models more realistic and hence more suitable for biomedical modeling. This review highlights recent research and current challenges in human pluripotent stem cell modeling of brain and neural crest neoplasms, and concludes with a call for more rigorous quality control and for the development of models for rare tumor subtypes.

Biomaterial-based in vitro 3D modeling of glioblastoma multiforme

Adult-onset brain cancers, such as glioblastomas, are particularly lethal. People with glioblastoma multiforme (GBM) do not anticipate living for more than 15 months if there is no cure. The results of conventional treatments over the past 20 years have been underwhelming. Tumor aggressiveness, location, and lack of systemic therapies that can penetrate the blood-brain barrier are all contributing factors. For GBM treatments that appear promising in preclinical studies, there is a considerable rate of failure in phase I and II clinical trials. Unfortunately, access becomes impossible due to the intricate architecture of tumors. In vitro, bioengineered cancer models are currently being used by researchers to study disease development, test novel therapies, and advance specialized medications. Many different techniques for creating in vitro systems have arisen over the past few decades due to developments in cellular and tissue engineering. Later-stage research may yield better results if in vitro models that resemble brain tissue and the blood-brain barrier are used. With the use of 3D preclinical models made available by biomaterials, researchers have discovered that it is possible to overcome these limitations. Innovative in vitro models for the treatment of GBM are possible using biomaterials and novel drug carriers. This review discusses the benefits and drawbacks of 3D in vitro glioblastoma modeling systems.

The function of histone methylation and acetylation regulators in GBM pathophysiology

Glioblastoma (GBM) is the most common and lethal primary brain malignancy and is characterized by a high degree of intra and intertumor cellular heterogeneity, a starkly immunosuppressive tumor microenvironment, and nearly universal recurrence. The application of various genomic approaches has allowed us to understand the core molecular signatures, transcriptional states, and DNA methylation patterns that define GBM. Histone posttranslational modifications (PTMs) have been shown to influence oncogenesis in a variety of malignancies, including other forms of glioma, yet comparatively less effort has been placed on understanding the transcriptional impact and regulation of histone PTMs in the context of GBM. In this review we discuss work that investigates the role of histone acetylating and methylating enzymes in GBM pathogenesis, as well as the effects of targeted inhibition of these enzymes. We then synthesize broader genomic and epigenomic approaches to understand the influence of histone PTMs on chromatin architecture and transcription within GBM and finally, explore the limitations of current research in this field before proposing future directions for this area of research.

Modeling nervous system tumors with human stem cells and organoids

Nervous system cancers are the 10th leading cause of death worldwide, many of which are difficult to diagnose and exhibit varying degrees of treatment resistance. The limitations of existing cancer models, such as patient-derived xenograft (PDX) models and genetically engineered mouse (GEM) models, call for the development of novel preclinical cancer models to more faithfully mimic the patient's cancer and offer additional insights. Recent advances in human stem cell biology, organoid, and genome-editing techniques allow us to model nervous system tumors in three types of next-generation tumor models: cell-of-origin models, tumor organoids, and 3D multicellular coculture models. In this review, we introduced and compared different human stem cell/organoid-derived models, and comprehensively summarized and discussed the recently developed models for various primary tumors in the central and peripheral nervous systems, including glioblastoma (GBM), H3K27M-mutant Diffuse Midline Glioma (DMG) and H3G34R-mutant High-grade Glioma (HGG), Low-grade Glioma (LGG), Neurofibromatosis Type 1 (NF1), Neurofibromatosis Type 2 (NF2), Medulloblastoma (MB), Atypical Teratoid/rhabdoid Tumor (AT/RT), and meningioma. We further compared these models with PDX and GEM models, and discussed the opportunities and challenges of precision nervous cancer modeling with human stem cells and organoids.

Modeling Human Brain Tumors and the Microenvironment Using Induced Pluripotent Stem Cells

Brain cancer is a group of diverse and rapidly growing malignancies that originate in the central nervous system (CNS) and have a poor prognosis. The complexity of brain structure and function makes brain cancer modeling extremely difficult, limiting pathological studies and therapeutic developments. Advancements in human pluripotent stem cell technology have opened a window of opportunity for brain cancer modeling, providing a wealth of customizable methods to simulate the disease in vitro. This is achieved with the advent of genome editing and genetic engineering technologies that can simulate germline and somatic mutations found in human brain tumors. This review investigates induced pluripotent stem cell (iPSC)-based approaches to model human brain cancer. The applications of iPSCs as renewable sources of individual brain cell types, brain organoids, blood-brain barrier (BBB), and brain tumor models are discussed. The brain tumor models reviewed are glioblastoma and medulloblastoma. The iPSC-derived isogenic cells and three-dimensional (3D) brain cancer organoids combined with patient-derived xenografts will enhance future compound screening and drug development for these deadly human brain cancers.

Pioneering models of pediatric brain tumors

Among children and adolescents in the United States (0 to 19 years old), brain and other central nervous system tumors are the second most common types of cancers, surpassed in incidence only by leukemias. Despite significant progress in the diagnosis and treatment modalities, brain cancer remains the leading cause of death in the pediatric population. There is an obvious unfulfilled need to streamline the therapeutic strategies and improve survival for these patients. For that purpose, preclinical models play a pivotal role. Numerous models are currently used in pediatric brain tumor research, including genetically engineered mouse models, patient-derived xenografts and cell lines, and newer models that utilize novel technologies such as genome engineering and organoids. Furthermore, extensive studies by the Children's Brain Tumor Network (CBTN) researchers and others have revealed multiomic landscapes of variable pediatric brain tumors. Combined with such integrative data, these novel technologies have enabled numerous applicable models. Genome engineering, including CRISPR/Cas9, expanded the flexibility of modeling. Models generated through genome engineering enabled studying particular genetic alterations in clean isogenic backgrounds, facilitating the dissection of functional mechanisms of those mutations in tumor biology. Organoids have been applied to study tumor-to-tumor-microenvironment interactions and to address developmental aspects of tumorigenesis, which is essential in some pediatric brain tumors. Other modalities, such as humanized mouse models, could potentially be applied to pediatric brain tumors. In addition to current valuable models, such novel models are anticipated to expedite functional tumor biology study and establish effective therapeutics for pediatric brain tumors.

Leveraging extrachromosomal DNA to fine-tune trials of targeted therapy for glioblastoma: opportunities and challenges

Glioblastoma evolution is facilitated by intratumour heterogeneity, which poses a major hurdle to effective treatment. Evidence indicates a key role for oncogene amplification on extrachromosomal DNA (ecDNA) in accelerating tumour evolution and thus resistance to treatment, particularly in glioblastomas. Oncogenes contained within ecDNA can reach high copy numbers and expression levels, and their unequal segregation can result in more rapid copy number changes in response to therapy than is possible through natural selection of intrachromosomal genomic loci. Notably, targeted therapies inhibiting oncogenic pathways have failed to improve glioblastoma outcomes. In this Perspective, we outline reasons for this disappointing lack of clinical translation and present the emerging evidence implicating ecDNA as an important driver of tumour evolution. Furthermore, we suggest that through detection of ecDNA, patient selection for clinical trials of novel agents can be optimized to include those most likely to benefit based on current understanding of resistance mechanisms. We discuss the challenges to successful translation of this approach, including accurate detection of ecDNA in tumour tissue with novel technologies, development of faithful preclinical models for predicting the efficacy of novel agents in the presence of ecDNA oncogenes, and understanding the mechanisms of ecDNA formation during cancer evolution and how they could be attenuated therapeutically. Finally, we evaluate the feasibility of routine ecDNA characterization in the clinic and how this process could be integrated with other methods of molecular stratification to maximize the potential for clinical translation of precision medicines.

The Oncogenesis of Glial Cells in Diffuse Gliomas and Clinical Opportunities

Glioma is the most common and lethal intrinsic primary tumor of the brain. Its controversial origins may contribute to its heterogeneity, creating challenges and difficulties in the development of therapies. Among the components constituting tumors, glioma stem cells are highly plastic subpopulations that are thought to be the site of tumor initiation. Neural stem cells/progenitor cells and oligodendrocyte progenitor cells are possible lineage groups populating the bulk of the tumor, in which gene mutations related to cell-cycle or metabolic enzymes dramatically affect this transformation. Novel approaches have revealed the tumor-promoting properties of distinct tumor cell states, glial, neural, and immune cell populations in the tumor microenvironment. Communication between tumor cells and other normal cells manipulate tumor progression and influence sensitivity to therapy. Here, we discuss the heterogeneity and relevant functions of tumor cell state, microglia, monocyte-derived macrophages, and neurons in glioma, highlighting their bilateral effects on tumors. Finally, we describe potential therapeutic approaches and targets beyond standard treatments.

What 'translating science' can learn from 'translating languages'

One of the most important steps in drug discovery is the translation of preclinical data to humans. However, the term 'translation' has numerous connotations and, often, different stakeholders literally speak different languages. Learning from many years of experience and new concepts in language translation could increase the success rate in translating biomedical research. Beyond being bilingual, this includes applying the concept of functional equivalence, the main characteristic of a good translation. Given that function is defined by the source language text, starting with the patient has advantages over the classical bench-to-bedside approach. Good translators need transfer competence, including knowledge of the limitations of translation. As with languages, computer-assisted translation(-al research) could support increasing functional equivalence and, thus, translation success.

Human induced pluripotent stem cell engineering establishes a humanized mouse platform for pediatric low-grade glioma modeling

A major obstacle to identifying improved treatments for pediatric low-grade brain tumors (gliomas) is the inability to reproducibly generate human xenografts. To surmount this barrier, we leveraged human induced pluripotent stem cell (hiPSC) engineering to generate low-grade gliomas (LGGs) harboring the two most common pediatric pilocytic astrocytoma-associated molecular alterations, NF1 loss and KIAA1549:BRAF fusion. Herein, we identified that hiPSC-derived neuroglial progenitor populations (neural progenitors, glial restricted progenitors and oligodendrocyte progenitors), but not terminally differentiated astrocytes, give rise to tumors retaining LGG histologic features for at least 6 months in vivo. Additionally, we demonstrated that hiPSC-LGG xenograft formation requires the absence of CD4 T cell-mediated induction of astrocytic Cxcl10 expression. Genetic Cxcl10 ablation is both necessary and sufficient for human LGG xenograft development, which additionally enables the successful long-term growth of patient-derived pediatric LGGs in vivo. Lastly, MEK inhibitor (PD0325901) treatment increased hiPSC-LGG cell apoptosis and reduced proliferation both in vitro and in vivo. Collectively, this study establishes a tractable experimental humanized platform to elucidate the pathogenesis of and potential therapeutic opportunities for childhood brain tumors.

Developing Bottom-Up Induced Pluripotent Stem Cell Derived Solid Tumor Models Using Precision Genome Editing Technologies

Advances in genome and tissue engineering have spurred significant progress and opportunity for innovation in cancer modeling. Human induced pluripotent stem cells (iPSCs) are an established and powerful tool to study cellular processes in the context of disease-specific genetic backgrounds; however, their application to cancer has been limited by the resistance of many transformed cells to undergo successful reprogramming. Here, we review the status of human iPSC modeling of solid tumors in the context of genetic engineering, including how base and prime editing can be incorporated into "bottom-up" cancer modeling, a term we coined for iPSC-based cancer models using genetic engineering to induce transformation. This approach circumvents the need to reprogram cancer cells while allowing for dissection of the genetic mechanisms underlying transformation, progression, and metastasis with a high degree of precision and control. We also discuss the strengths and limitations of respective engineering approaches and outline experimental considerations for establishing future models.

Functional genomics and the future of iPSCs in disease modeling

Induced pluripotent stem cells (iPSCs) are valuable in disease modeling because of their potential to expand and differentiate into virtually any cell type and recapitulate key aspects of human biology. Functional genomics are genome-wide studies that aim to discover genotype-phenotype relationships, thereby revealing the impact of human genetic diversity on normal and pathophysiology. In this review, we make the case that human iPSCs (hiPSCs) are a powerful tool for functional genomics, since they provide an in vitro platform for the study of population genetics. We describe cutting-edge tools and strategies now available to researchers, including multi-omics technologies, advances in hiPSC culture techniques, and innovations in drug development. Functional genomics approaches based on hiPSCs hold great promise for advancing drug discovery, disease etiology, and the impact of genetic variation on human biology.

Pharmacological targeting of the tumor–immune symbiosis in glioblastoma

Glioblastoma (GBM) is the most common and highly lethal form of primary brain tumor in adults. The median survival of GBM patients is approximately 14-16 months despite multimodal therapies. Emerging evidence has substantiated the critical role of symbiotic interactions between GBM cells and noncancerous immune cells (e.g., myeloid cells and T cells) in regulating tumor progression and therapy resistance. Approaches to target the tumor-immune symbiosis have emerged as a promising therapeutic strategy for GBM. Here, we review the recent developments for pharmacological targeting of the GBM-immune symbiosis and highlight the role of such strategies to improve the effectiveness of immunotherapies in GBM.

Rat and Mouse Brain Tumor Models for Experimental Neuro-Oncology Research

Rodent brain tumor models have been useful for developing effective therapies for glioblastomas (GBMs). In this review, we first discuss the 3 most commonly used rat brain tumor models, the C6, 9L, and F98 gliomas, which are all induced by repeated injections of nitrosourea to adult rats. The C6 glioma arose in an outbred Wistar rat and its potential to evoke an alloimmune response is a serious limitation. The 9L gliosarcoma arose in a Fischer rat and is strongly immunogenic, which must be taken into consideration when using it for therapy studies. The F98 glioma may be the best of the 3 but it does not fully recapitulate human GBMs because it is weakly immunogenic. Next, we discuss a number of mouse models. The first are human patient-derived xenograft gliomas in immunodeficient mice. These have failed to reproduce the tumor-host interactions and microenvironment of human GBMs. Genetically engineered mouse models recapitulate the molecular alterations of GBMs in an immunocompetent environment and “humanized” mouse models repopulate with human immune cells. While the latter are rarely isogenic, expensive to produce, and challenging to use, they represent an important advance. The advantages and limitations of each of these brain tumor models are discussed. This information will assist investigators in selecting the most appropriate model for the specific focus of their research.

Progenitor cells derived from gene-engineered human induced pluripotent stem cells as synthetic cancer cell alternatives for in vitro pharmacology

Limitations in genetic stability and recapitulating accurate physiological disease properties challenge the utility of patient-derived (PD) cancer models for reproducible and translational research. We have genetically engineered a portfolio of isogenic human induced pluripotent stem cells (hiPSCs) with different pan-cancer relevant oncoprotein signatures followed by differentiation into lineage-committed progenitor cells. Characterization on molecular and biological level validated successful stable genetic alterations in pluripotency state as well as upon differentiation to prove the functionality of our approach Meanwhile proposing core molecular networks possibly involved in early dysregulation of stem cell homeostasis, the application of our cell systems in comparative substance testing indicates the potential for cancer research such as identification of augmented therapy resistance of stem cells in response to activation of distinct oncogenic signatures. This article is protected by copyright. All rights reserved.

Autologous humanized mouse models of iPSC-derived tumors enable characterization and modulation of cancer-immune cell interactions

Modeling the tumor-immune cell interactions in humanized mice is complex and limits drug development. Here, we generated easily accessible tumor models by transforming either primary skin fibroblasts or induced pluripotent stem cell-derived cell lines injected in immune-deficient mice reconstituted with human autologous immune cells. Our results showed that fibroblastic, hepatic, or neural tumors were all efficiently infiltrated and partially or totally rejected by autologous immune cells in humanized mice. Characterization of tumor-immune infiltrates revealed high expression levels of the dysfunction markers Tim3 and PD-1 in T cells and an enrichment in regulatory T cells, suggesting rapid establishment of immunomodulatory phenotypes. Inhibition of PD-1 by Nivolumab in humanized mice resulted in increased immune cell infiltration and a slight decrease in tumor growth. We expect that these versatile and accessible cancer models will facilitate preclinical studies and the evaluation of autologous cancer immunotherapies across a range of different tumor cell types.

The current landscape of immunotherapy for pediatric brain tumors

Pediatric central nervous system tumors are the most common solid malignancies in childhood, and aggressive therapy often leads to long-term sequelae in survivors, making these tumors challenging to treat. Immunotherapy has revolutionized prospects for many cancer types in adults, but the intrinsic complexity of treating pediatric patients and the scarcity of clinical studies of children to inform effective approaches have hampered the development of effective immunotherapies in pediatric settings. Here, we review recent advances and ongoing challenges in pediatric brain cancer immunotherapy, as well as considerations for efficient clinical translation of efficacious immunotherapies into pediatric settings.

Pediatric brain tumors as a developmental disease

PURPOSE OF REVIEW

Brain tumors are the most frequent solid cancer in the pediatric population. Owing to the rarity of environmental clues about their origin, it is tempting to consider these neoplasms as developmental processes gone awry. Our review will explore the heuristic power of this hypothesis and the influence of these findings on the clinical management.

RECENT FINDING

A more accurate description of cancer predisposition syndrome has shown their frequent association with developmental abnormalities. Several genes involved in pediatric brain tumor oncogenesis are involved in developmental processes. Modeling of several pediatric brain tumor in cerebral organoids, mimicking embryonal stage of brain development, indicates that early events during brain development create the conditions necessary for their oncogenesis.

SUMMARY

The onset of multiple brain tumor types early in life suggests a functional relationship between brain development and oncogenesis. A growing body of evidence seems to support the hypothesis that some of the main developmental steps in the brain can be highjacked by the tumors during their initiation. Collaborations between neuroscientists and oncologists should provide room for improvement in the knowledge for these neoplasms.

Charting oncogenicity of genes and variants across lineages via multiplexed screens in teratomas

Deconstructing tissue-specific effects of genes and variants on proliferation is critical to understanding cellular transformation and systematically selecting cancer therapeutics. This requires scalable methods for multiplexed genetic screens tracking fitness across time, across lineages, and in a suitable niche, since physiological cues influence functional differences. Towards this, we present an approach, coupling single-cell cancer driver screens in teratomas with hit enrichment by serial teratoma reinjection, to simultaneously screen drivers across multiple lineages in vivo. Using this system, we analyzed population shifts and lineage-specific enrichment for 51 cancer associated genes and variants, profiling over 100,000 cells spanning over 20 lineages, across two rounds of serial reinjection. We confirmed that c-MYC alone or combined with myristoylated AKT1 potently drives proliferation in progenitor neural lineages, demonstrating signatures of malignancy. Additionally, mutant MEK1 S218D/S222D provides a proliferative advantage in mesenchymal lineages like fibroblasts. Our method provides a powerful platform for multi-lineage longitudinal study of oncogenesis.

High-resolution positron emission microscopy of patient-derived tumor organoids

Tumor organoids offer new opportunities for translational cancer research, but unlike animal models, their broader use is hindered by the lack of clinically relevant imaging endpoints. Here, we present a positron-emission microscopy method for imaging clinical radiotracers in patient-derived tumor organoids with spatial resolution 100-fold better than clinical positron emission tomography (PET). Using this method, we quantify 18F-fluorodeoxyglucose influx to show that patient-derived tumor organoids recapitulate the glycolytic activity of the tumor of origin, and thus, could be used to predict therapeutic response in vitro. Similarly, we measure sodium-iodine symporter activity using 99mTc- pertechnetate and find that the iodine uptake pathway is functionally conserved in organoids derived from thyroid carcinomas. In conclusion, organoids can be imaged using clinical radiotracers, which opens new possibilities for identifying promising drug candidates and radiotracers, personalizing treatment regimens, and incorporating clinical imaging biomarkers in organoid-based co-clinical trials.

Testing the Stability of Drug Resistance on Cryopreserved, Gene-Engineered Human Induced Pluripotent Stem Cells

Human induced pluripotent stem cells (hiPSCs) have emerged as a powerful tool for in vitro modelling of diseases with broad application in drug development or toxicology testing. These assays usually require large quantities of hiPSC, which can entail long-term storage via cryopreservation of the same cell charges. However, it is essential that cryopreservation does not oppose durable changes on the cells. In this project, we characterize one parameter of functionality of one that is well established in the field, in a different research context, an applied hiPSC line (iPS11), namely their resistance to a medium size library of chemo interventions (>160 drugs). We demonstrate that cells, before and after cryopreservation, do not change their relative overall drug response phenotypes, as defined by identification of the top 20 interventions causing dose-dependent reduction of cell growth. Importantly, also frozen cells that are exogenously enforced for stable overexpression of oncogenes myelocytomatosis (cMYC) or tumor protein 53 mutation (TP53R175H), respectively, are not changed in their relative top 20 drugs response compared to their non-frozen counterparts. Taken together, our results support iPSCs as a reliable in vitro platform for in vitro pharmacology, further raising hopes that this technology supports biomarker-associated drug development. Given the general debate on ethical and economic problems associated with the reproducibly crisis in biomedicine, our results may be of interest to a wider audience beyond stem cell research.

PTEN deficiency leads to proteasome addiction: a novel vulnerability in glioblastoma

BACKGROUND

Glioblastoma (GBM) is the most common primary brain tumor in adults with a median survival of approximately 15 months; therefore, more effective treatment options for GBM are required. To identify new drugs targeting GBMs, we performed a high-throughput drug screen using patient-derived neurospheres cultured to preferentially retain their glioblastoma stem cell (GSC) phenotype.

METHODS

High-throughput drug screening was performed on GSCs followed by a dose-response assay of the 5 identified original "hits." A PI3K/mTOR dependency to a proteasome inhibitor (carfilzomib), was confirmed by genetic and pharmacologic experiments. Proteasome Inhibition Response Signatures were derived from proteomic and bioinformatic analysis. Molecular mechanism of action was determined using three-dimensional (3D) GBM-organoids and preclinical orthotopic models.

RESULTS

We found that GSCs were highly sensitive to proteasome inhibition due to an underlying dependency on an increased protein synthesis rate, and loss of autophagy, associated with PTEN loss and activation of the PI3K/mTOR pathway. In contrast, combinatory inhibition of autophagy and the proteasome resulted in enhanced cytotoxicity specifically in GSCs that did express PTEN. Finally, proteasome inhibition specifically increased cell death markers in 3D GBM-organoids, suppressed tumor growth, and increased survival of mice orthotopically engrafted with GSCs. As perturbations of the PI3K/mTOR pathway occur in nearly 50% of GBMs, these findings suggest that a significant fraction of these tumors could be vulnerable to proteasome inhibition.

CONCLUSIONS

Proteasome inhibition is a potential synthetic lethal therapeutic strategy for GBM with proteasome addiction due to a high protein synthesis rate and autophagy deficiency.

The Impact of Assay Design on Medicinal Chemistry: Case Studies

GRAPHICAL ABSTRACT

Translational Research in the Era of Precision Medicine: Where We Are and Where We Will Go

The advent of Precision Medicine has globally revolutionized the approach of translational research suggesting a patient-centric vision with therapeutic choices driven by the identification of specific predictive biomarkers of response to avoid ineffective therapies and reduce adverse effects. The spread of "multi-omics" analysis and the use of sensors, together with the ability to acquire clinical, behavioral, and environmental information on a large scale, will allow the digitization of the state of health or disease of each person, and the creation of a global health management system capable of generating real-time knowledge and new opportunities for prevention and therapy in the individual person (high-definition medicine). Real world data-based translational applications represent a promising alternative to the traditional evidence-based medicine (EBM) approaches that are based on the use of randomized clinical trials to test the selected hypothesis. Multi-modality data integration is necessary for example in precision oncology where an Avatar interface allows several simulations in order to define the best therapeutic scheme for each cancer patient.

The Many Facets of Therapy Resistance and Tumor Recurrence in Glioblastoma

Glioblastoma (GBM) is the most lethal type of primary brain cancer. Standard care using chemo- and radio-therapy modestly increases the overall survival of patients; however, recurrence is inevitable, due to treatment resistance and lack of response to targeted therapies. GBM therapy resistance has been attributed to several extrinsic and intrinsic factors which affect the dynamics of tumor evolution and physiology thus creating clinical challenges. Tumor-intrinsic factors such as tumor heterogeneity, hypermutation, altered metabolomics and oncologically activated alternative splicing pathways change the tumor landscape to facilitate therapy failure and tumor progression. Moreover, tumor-extrinsic factors such as hypoxia and an immune-suppressive tumor microenvironment (TME) are the chief causes of immunotherapy failure in GBM. Amid the success of immunotherapy in other cancers, GBM has occurred as a model of resistance, thus focusing current efforts on not only alleviating the immunotolerance but also evading the escape mechanisms of tumor cells to therapy, caused by inter- and intra-tumoral heterogeneity. Here we review the various mechanisms of therapy resistance in GBM, caused by the continuously evolving tumor dynamics as well as the complex TME, which cumulatively contribute to GBM malignancy and therapy failure; in an attempt to understand and identify effective therapies for recurrent GBM.

Tumor cell plasticity, heterogeneity, and resistance in crucial microenvironmental niches in glioma

Both the perivascular niche (PVN) and the integration into multicellular networks by tumor microtubes (TMs) have been associated with progression and resistance to therapies in glioblastoma, but their specific contribution remained unknown. By long-term tracking of tumor cell fate and dynamics in the live mouse brain, differential therapeutic responses in both niches are determined. Both the PVN, a preferential location of long-term quiescent glioma cells, and network integration facilitate resistance against cytotoxic effects of radiotherapy and chemotherapy—independently of each other, but with additive effects. Perivascular glioblastoma cells are particularly able to actively repair damage to tumor regions. Population of the PVN and resistance in it depend on proficient NOTCH1 expression. In turn, NOTCH1 downregulation induces resistant multicellular networks by TM extension. Our findings identify NOTCH1 as a central switch between the PVN and network niche in glioma, and demonstrate robust cross-compensation when only one niche is targeted.

Whether the perivascular niche (PVN) and the integration into multicellular networks by tumor microtubes (TMs) have a different role in glioblastoma progression and resistance to therapies is currently unclear. Here, the authors, by long-term tracking of individual glioma, demonstrate that both niches can partially compensate for each other and that glioma cells localized in both niches are resistant to radio- and chemotherapy.

Sequential fate-switches in stem-like cells drive the tumorigenic trajectory from human neural stem cells to malignant glioma

Glioblastoma (GBM) is an incurable and highly heterogeneous brain tumor, originating from human neural stem/progenitor cells (hNSCs/hNPCs) years ahead of diagnosis. Despite extensive efforts to characterize hNSCs and end-stage GBM at bulk and single-cell levels, the de novo gliomagenic path from hNSCs is largely unknown due to technical difficulties in early-stage sampling and preclinical modeling. Here, we established two highly penetrant hNSC-derived malignant glioma models, which resemble the histopathology and transcriptional heterogeneity of human GBM. Integrating time-series analyses of whole-exome sequencing, bulk and single-cell RNA-seq, we reconstructed gliomagenic trajectories, and identified a persistent NSC-like population at all stages of tumorigenesis. Through trajectory analyses and lineage tracing, we showed that tumor progression is primarily driven by multi-step transcriptional reprogramming and fate-switches in the NSC-like cells, which sequentially generate malignant heterogeneity and induce tumor phenotype transitions. We further uncovered stage-specific oncogenic cascades, and among the candidate genes we functionally validated C1QL1 as a new glioma-promoting factor. Importantly, the neurogenic-to-gliogenic switch in NSC-like cells marks an early stage characterized by a burst of oncogenic alterations, during which transient AP-1 inhibition is sufficient to inhibit gliomagenesis. Together, our results reveal previously undercharacterized molecular dynamics and fate choices driving de novo gliomagenesis from hNSCs, and provide a blueprint for potential early-stage treatment/diagnosis for GBM.

The Organoid Era Permits the Development of New Applications to Study Glioblastoma

Glioblastoma (GB) is the most frequent and aggressive type of glioma. The lack of reliable GB models, together with its considerable clinical heterogeneity, has impaired a comprehensive investigation of the mechanisms that lead to tumorigenesis, cancer progression, and response to treatments. Recently, 3D cultures have opened the possibility to overcome these challenges and cerebral organoids are emerging as a leading-edge tool in GB research. The opportunity to easily engineer brain organoids via gene editing and to perform co-cultures with patient-derived tumor spheroids has enabled the analysis of cancer development in a context that better mimics brain tissue architecture. Moreover, the establishment of biobanks from GB patient-derived organoids represents a crucial starting point to improve precision medicine therapies. This review exemplifies relevant aspects of 3D models of glioblastoma, with a specific focus on organoids and their involvement in basic and translational research.

SMARCB1 loss interacts with neuronal differentiation state to block maturation and impact cell stability

Atypical teratoid rhabdoid tumors (ATRTs) are challenging pediatric brain cancers that are predominantly associated with inactivation of the gene SMARCB1, a conserved subunit of the chromatin remodeling BAF complex, which has known contributions to developmental processes. To identify potential interactions between SMARCB1 loss and the process of neural development, we introduced an inducible SMARCB1 loss-of-function system into human induced pluripotent stem cells (iPSCs) that were subjected to either directed neuronal differentiation or differentiation into cerebral organoids. Using this system, we identified substantial differences in the downstream effects of SMARCB1 loss depending on differentiation state and identified an interaction between SMARCB1 loss and neural differentiation pressure that causes a resistance to terminal differentiation and a defect in maintenance of a normal cell state. Our results provide insight into how SMARCB1 loss might interact with neural development in the process of ATRT tumorigenesis.

"Reprogram Enablement" as an Assay for Identifying Early Oncogenic Pathways by Their Ability to Allow Neoplastic Cells to Reacquire an Epiblast State

One approach to understanding how tissue-specific cancers emerge is to determine the requirements for “reprograming” such neoplastic cells back to their developmentally normal primordial pre-malignant epiblast-like pluripotent state and then scrutinizing their spontaneous reconversion to a neoplasm, perhaps rendering salient the earliest pivotal oncogenic pathway(s) (before other aberrations accumulate in the adult tumor). For the prototypical malignancy anaplastic thyroid carcinoma (ATC), we found that tonic RAS reduction was obligatory for reprogramming cancer cells to a normal epiblast-emulating cells, confirmed by changes in their transcriptomic and epigenetic profiles, loss of neoplastic behavior, and ability to derive normal somatic cells from their “epiblast organoids.” Without such suppression, ATCs re-emerged from the clones. Hence, for ATC, RAS inhibition was its “reprogram enablement” (RE) factor. Each cancer likely has its own RE factor; identifying it may illuminate pre-malignant risk markers, better classifications, therapeutic targets, and tissue-specification of a previously pluripotent, now neoplastic, cell.

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The factors for reprogramming a cancer cell to an epiblast-like cell can be assayed

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“Reprogram enablement” can yield insights into the earliest pivotal oncogenic steps

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For anaplastic thyroid carcinoma, RAS inhibition was obligatory for reprograming

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Each tissue-specific cancer will have its own reprogramming enablement requirement

Genome Engineering Evolves Brain Tumor Modeling

Genome engineering using programmable nucleases such as transcription activator-like effector nuclease (TALEN), and clustered regularly interspaced short palindromic repeat-associated protein nine facilitated the introduction of genetic alterations at specific genomic sites in various cell types. These tools have been applied to cancer modeling to understand the pathogenic effects of the growing catalog of mutations found in human cancers. Pertaining to brain tumors, neural progenitor cells derived from human induced pluripotent stem cells (iPSCs) engineered with different combinations of genetic driver mutations observed in distinct molecular subtypes of glioblastomas, the most common form of primary brain cancer in adults, give rise to brain tumors when engrafted orthotopically in mice. These glioblastoma models recapitulate the transcriptomic signature of each molecular subtype and authentically resemble pathobiology of glioblastoma, including inter- and intra-tumor heterogeneity, chromosomal aberrations, and extrachromosomal DNA amplifications. Similar engineering with genetic mutations found in medulloblastoma and atypical teratoid rhabdoid tumors in iPSCs have led to genetically trackable models that bear clinical relevance to these pediatric brain tumors. These models have contributed to improved comprehension of the genetic causation of tumorigenesis and offered a novel platform for therapeutic discovery. Studied in the context of three-dimensional cerebral organoids, these models have aided in the study of tumor invasion as well as therapeutic responses. In summary, modeling brain tumors through genome engineering enables not only the establishment of authentic tumor avatars driven by bona fide genetic mutations observed in patient samples but also facilitates functional investigations of particular genetic alterations in an otherwise isogenic background.