Patient-derived organoids and orthotopic xenografts of primary and recurrent gliomas represent relevant patient avatars for precision oncology

Evolution of Preclinical Models for Glioblastoma Modelling and Drug Screening

PURPOSE OF REVIEW

Isocitrate dehydrogenase wild-type glioblastoma is an extremely aggressive and fatal primary brain tumour, characterised by extensive heterogeneity and diffuse infiltration of brain parenchyma. Despite multimodal treatment and diverse research efforts to develop novel therapies, there has been limited success in improving patient outcomes. Constructing physiologically relevant preclinical models is essential to optimising drug screening processes and identifying more effective treatments.

RECENT FINDINGS

Traditional in-vitro models have provided critical insights into glioblastoma pathophysiology; however, they are limited in their ability to recapitulate the complex tumour microenvironment and its interactions with surrounding cells. In-vivo models offer a more physiologically relevant context, but often do not fully represent human pathology, are expensive, and time-consuming. These limitations have contributed to the low translational success of therapies from trials to clinic. Organoid and glioblastoma-on-a-chip technology represent significant advances in glioblastoma modelling and enable the replication of key features of the human tumour microenvironment, including its structural, mechanical, and biochemical properties. Organoids provide a 3D system that captures cellular heterogeneity and tumour architecture, while microfluidic chips offer dynamic systems capable of mimicking vascularisation and nutrient exchange. Together, these technologies hold tremendous potential for high throughput drug screening and personalised, precision medicine. This review explores the evolution of preclinical models in glioblastoma modelling and drug screening, emphasising the transition from traditional systems to more advanced organoid and microfluidic platforms. Furthermore, it aims to evaluate the advantages and limitations of both traditional and next-generation models, investigating their combined potential to address current challenges by integrating complementary aspects of specific models and techniques.

AMP-activated protein kinase mediates adaptation of glioblastoma cells to conditions of the tumor microenvironment

AMP-activated protein kinase (AMPK) is an energy sensor that regulates cellular metabolic activity. We hypothesized that in glioblastoma (GB), AMPK plays a pivotal role in balancing metabolism under conditions of the tumor microenvironment with fluctuating and often low nutrient and oxygen availability. Impairment of this network could thus interfere with tumor progression. AMPK activity was modulated genetically by CRISPR/Cas9-based double knockout (DKO) of the catalytic α1 and α2 subunits in human GB cells and effects were confirmed by pharmacological AMPK inhibition using BAY3827 and an inactive control compound in primary GB cell cultures. We found that metabolic adaptation of GB cells under energy stress conditions (hypoxia, glucose deprivation) was dependent on AMPK and accordingly that AMPK DKO cells were more vulnerable to glucose deprivation or inhibition of glycolysis and sensitized to hypoxia-induced cell death. This effect was rescued by reexpression of the AMPK α2 subunit. Similar results were observed using the selective pharmacological AMPK inhibitor BAY3827. Mitochondrial biogenesis was regulated AMPK-dependently with a reduced mitochondrial mass and mitochondrial membrane potential in AMPK DKO GB cells. In vivo, AMPK DKO GB cells showed impaired tumor growth and tumor formation in CAM assays as well as in an orthotopic glioma mouse model. Our study highlights the importance of AMPK for GB cell adaptation towards energy depletion and emphasizes the role of AMPK for tumor formation in vivo. Moreover, we identified mitochondria as central downstream effectors of AMPK signaling. The development of AMPK inhibitors could open opportunities for the treatment of hypoxic tumors.

PDX models for functional precision oncology and discovery science

Precision oncology relies on detailed molecular analysis of how diverse tumours respond to various therapies, with the aim to optimize treatment outcomes for individual patients. Patient-derived xenograft (PDX) models have been key to preclinical validation of precision oncology approaches, enabling the analysis of each tumour's unique genomic landscape and testing therapies that are predicted to be effective based on specific mutations, gene expression patterns or signalling abnormalities. To extend these standard precision oncology approaches, the field has strived to complement the otherwise static and often descriptive measurements with functional assays, termed functional precision oncology (FPO). By utilizing diverse PDX and PDX-derived models, FPO has gained traction as an effective preclinical and clinical tool to more precisely recapitulate patient biology using in vivo and ex vivo functional assays. Here, we explore advances and limitations of PDX and PDX-derived models for precision oncology and FPO. We also examine the future of PDX models for precision oncology in the age of artificial intelligence. Integrating these two disciplines could be the key to fast, accurate and cost-effective treatment prediction, revolutionizing oncology and providing patients with cancer with the most effective, personalized treatments.

Adenoviral delivery of the CIITA transgene induces T-cell-mediated killing in glioblastoma organoids

The immunosuppressive nature of the tumor microenvironment poses a significant challenge to effective immunotherapies against glioblastoma (GB). Boosting the immune response is critical for successful therapy. Here, we adopted a cancer gene therapy approach to induce T-cell-mediated killing of the tumor through increased activation of the immune system. Patient-based three-dimensional (3D) GB models were infected with a replication-deficient adenovirus (AdV) armed with the class II major histocompatibility complex (MHC-II) transactivator (CIITA) gene (Ad-CIITA). Successful induction of surface MHC-II was achieved in infected GB cell lines and primary human GB organoids. Infection with an AdV carrying a mutant form of CIITA with a single amino acid substitution resulted in cytoplasmic accumulation of CIITA without subsequent MHC-II expression. Co-culture of infected tumor cells with either peripheral blood mononuclear cells (PBMCs) or isolated T-cells led to dramatic breakdown of GB organoids. Intriguingly, both wild-type and mutant Ad-CIITA, but not unarmed AdV, triggered immune-mediated tumor cell death in the co-culture system, suggesting an at least partially MHC-II-independent process. We further show that the observed cancer cell killing requires the presence of either CD8+ or CD4+ T-cells and direct contact between GB and immune cells. We did not, however, detect evidence of activation of canonical T-cell-mediated cell death pathways. Although the precise mechanism remains to be determined, these findings highlight the potential of AdV-mediated CIITA delivery to enhance T-cell-mediated immunity against GB.

Opportunities and challenges for patient-derived models of brain tumors in functional precision medicine

Here, we review a growing paradigm shift from genomics-based precision medicine toward functional precision medicine, which evaluates therapeutic efficacy by directly treating living patient tumors ex vivo to better predict patient-specific responses to treatment. We discuss several classes of patient-derived models of central nervous system tumors, highlighting unique features of each. Each class of models holds promise to improve treatment selection, prolong survival, and enhance patient outcomes.

The Hallmarks of Predictive Oncology

SIGNIFICANCE

As the field of artificial intelligence evolves rapidly, these hallmarks are intended to capture fundamental, complementary concepts necessary for the progress and timely adoption of predictive modeling in precision oncology. Through these hallmarks, we hope to establish standards and guidelines that enable the symbiotic development of artificial intelligence and precision oncology.

Patient-derived glioblastoma organoids as real-time avatars for assessing responses to clinical CAR-T cell therapy

Patient-derived tumor organoids have been leveraged for disease modeling and preclinical studies but rarely applied in real time to aid with interpretation of patient treatment responses in clinics. We recently demonstrated early efficacy signals in a first-in-human, phase 1 study of dual-targeting chimeric antigen receptor (CAR)-T cells (EGFR-IL13Rα2 CAR-T cells) in patients with recurrent glioblastoma. Here, we analyzed six sets of patient-derived glioblastoma organoids (GBOs) treated concurrently with the same autologous CAR-T cell products as patients in our phase 1 study. We found that CAR-T cell treatment led to target antigen reduction and cytolysis of tumor cells in GBOs, the degree of which correlated with CAR-T cell engraftment detected in patients' cerebrospinal fluid (CSF). Furthermore, cytokine release patterns in GBOs mirrored those in patient CSF samples over time. Our findings highlight a unique trial design and GBOs as a valuable platform for real-time assessment of CAR-T cell bioactivity and insights into immunotherapy efficacy.

A systematic review on the culture methods and applications of 3D tumoroids for cancer research and personalized medicine

Cancer is a highly heterogeneous disease, and thus treatment responses vary greatly between patients. To improve therapy efficacy and outcome for cancer patients, more representative and patient-specific preclinical models are needed. Organoids and tumoroids are 3D cell culture models that typically retain the genetic and epigenetic characteristics, as well as the morphology, of their tissue of origin. Thus, they can be used to understand the underlying mechanisms of cancer initiation, progression, and metastasis in a more physiological setting. Additionally, co-culture methods of tumoroids and cancer-associated cells can help to understand the interplay between a tumor and its tumor microenvironment. In recent years, tumoroids have already helped to refine treatments and to identify new targets for cancer therapy. Advanced culturing systems such as chip-based fluidic devices and bioprinting methods in combination with tumoroids have been used for high-throughput applications for personalized medicine. Even though organoid and tumoroid models are complex in vitro systems, validation of results in vivo is still the common practice. Here, we describe how both animal- and human-derived tumoroids have helped to identify novel vulnerabilities for cancer treatment in recent years, and how they are currently used for precision medicine.

Technological advances in clinical individualized medication for cancer therapy: from genes to whole organism

Efforts have been made to leverage technology to accurately identify tumor characteristics and predict how each cancer patient may respond to medications. This involves collecting data from various sources such as genomic data, histological information, functional drug profiling, and drug metabolism using techniques like polymerase chain reaction, sanger sequencing, next-generation sequencing, fluorescence in situ hybridization, immunohistochemistry staining, patient-derived tumor xenograft models, patient-derived organoid models, and therapeutic drug monitoring. The utilization of diverse detection technologies in clinical practice has made "individualized treatment" possible, but the desired level of accuracy has not been fully attained yet. Here, we briefly summarize the conventional and state-of-the-art technologies contributing to individualized medication in clinical settings, aiming to explore therapy options enhancing clinical outcomes.

Recent advances in development and delivery of non-viral nucleic acid therapeutics for brain tumor therapy

High grade gliomas (HGG) are a group of CNS tumors refractory to currently existing therapies, which routinely leads to early recurrence and a dismal prognosis. Recent advancements in nucleic acid-based therapy using a wide variety of different molecular targets and non-viral nanocarrier systems suggest that this approach holds significant potential to meet the urgent demand for improved therapeutic options for the treatment of these tumors. This review provides a comprehensive and up-to-date overview on the current landscape and progress of preclinical and clinical developments in this rapidly evolving and exciting field of research, including optimized nanocarrier delivery systems, promising therapeutic targets and tailor-made therapeutic strategies for individualized HGG patient treatment.

MiRNAs as major players in brain health and disease: current knowledge and future perspectives

MicroRNAs are regulators of gene expression and their dysregulation can lead to various diseases. MicroRNA-135 (MiR-135) exhibits brain-specific expression, and performs various functions such as neuronal morphology, neural induction, and synaptic function in the human brain. Dysfunction of miR-135 has been reported in brain tumors, and neurodegenerative and neurodevelopmental disorders. Several reports show downregulation of miR-135 in glioblastoma, indicating its tumor suppressor role in the pathogenesis of brain tumors. In this review, by performing in silico analysis of molecular targets of miR-135, we reveal the significant pathways and processes modulated by miR-135. We summarize the biological significance, roles, and signaling pathways of miRNAs in general, with a focus on miR-135 in different neurological diseases including brain tumors, and neurodegenerative and neurodevelopmental disorders. We also discuss methods, limitations, and potential of glioblastoma organoids in recapitulating disease initiation and progression. We highlight the promising therapeutic potential of miRNAs as antitumor agents for aggressive human brain tumors including glioblastoma.

Analysis of Clinical Success and Molecular Mechanisms of Action of Novel Anti-glioblastoma Drugs: A Review

BACKGROUND

Gliomas and glioblastomas (GBM) are common primary malignant brain tumors, which are highly malignant and have a poor prognosis. The presence of cancer stem cells with unrestricted proliferative capacity and ability to generate glial neoplastic cells, the diffuse nature of GBM, and other specific factors of GBM contribute to poor results of drug therapy in patients with GBM. Despite the worldwide efforts to improve the treatment, many novel anti-GBM drugs are active just in vitro, in silico, and in preclinical trials, and they sometimes demonstrate poor or no activity in clinical trials. In this paper, we have casually selected and analyzed the most promising evidence-based results related to glioblastoma treatment at FDA and Clinical Trials.gov databases. It was observed that the most prospective trend in the development of anti-GBM drugs is combination therapy vs. monotherapy. Our analysis of clinical trials has allowed us to predict that the most promising combination therapy that has shown the best results in patient's surveillance should include drugs that block different growth-promoting signals in glioblastoma cells and that are activated by the V600E BRAF mutation. One drug should inhibit signals from the BRAF protein, whereas the second drug in combination should inhibit signals from the MEK protein.

METHODS

The content of this review is based on information obtained from PubMed, ClinicalTrials.- gov, and the U.S. Food and Drug Administration (https://www.fda.gov/). In ClinicalTrials.gov, we retrieved studies published from January 1, 2015. In the data search, "Glioblastoma" was used as the keyword. A study was deleted if it studied remedies for concomitant tumor diseases, as well as if it did not include descriptions of treatment methods and/or if GBM was not mentioned. The analysis of the effectiveness of treatment was carried out according to the increasing overall survival in GBM patients, compared to the gold standard for this cancer.

RESULTS

GBM patients treated with novel immunotherapy agents and drugs acting on epigenetic factors and receptor tyrosine kinase inhibitors have shown encouraging potential for future development in clinic. However, combinations of drugs have led to more significant improvements in the results and an increase in life expectancy of patients. For example, the combination of nivolumab and ipilimumab showed a 72% increase in life expectancy compared to using nivolumab alone (9.8 vs. 16.85).

CONCLUSION

Combining anti-GBM drugs appears to be a key direction for increasing treatment effectiveness and overall survival. Radiotherapy of GBM can increase the effect of combination drug therapy.

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.

Current research status of Raman spectroscopy in glioma detection

Glioma is the most common primary tumor of the nervous system. Conventional diagnostic methods for glioma often involve time-consuming or reliance on externally introduced materials. Consequently, there is an urgent need for rapid and reliable diagnostic techniques. Raman spectroscopy has emerged as a promising tool, offering rapid, accurate, and label-free analysis with high sensitivity and specificity in biomedical applications. In this review, the fundamental principles of Raman spectroscopy have been introduced, and then the progress of applying Raman spectroscopy in biomedical studies has been summarized, including the identification and typing of glioma. The challenges encountered in the clinical application of Raman spectroscopy for glioma have been discussed, and the prospects have also been envisioned.

Vaccine-based immunotherapy and related preclinical models for glioma

Glioma, the most common primary malignant tumor in the central nervous system (CNS), lacks effective treatments, and >60% of cases are glioblastoma (GBM), the most aggressive form. Despite advances in immunotherapy, GBM remains highly resistant. Approaches that target tumor antigens expedite the development of immunotherapies, including personalized tumor-specific vaccines, patient-specific target selection, dendritic cell (DC) vaccines, and chimeric antigen receptor (CAR) and T cell receptor (TCR) T cells. Recent studies show promising results in treating GBM and lower-grade glioma (LGG), fostering hope for future immunotherapy. This review discusses tumor vaccines against glioma, preclinical models in immunological research, and the role of CD4+ T cells in vaccine-induced antitumor immunity. We also summarize clinical approaches, challenges, and future research for creating more effective vaccines.

Integrated analysis of single-cell RNA-seq and bulk RNA-seq reveals immune suppression subtypes and establishes a novel signature for determining the prognosis in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is the most common histological type of lung cancer with lower survival rates. Recent advancements in targeted therapies and immunotherapies targeting immune checkpoints have achieved remarkable success, there is still a large percentage of LUAD that lacks available therapeutic options. Due to tumor heterogeneity, the diagnosis and treatment of LUAD are challenging. Exploring the biology of LUAD and identifying new biomarker and therapeutic targets options are essential.

METHOD

We performed single-cell RNA sequencing (scRNA-seq) of 6 paired primary and adjacent LUAD tissues, and integrative omics analysis of the scRNA-seq, bulk RNA-seq and whole-exome sequencing data revealed molecular subtype characteristics. Our experimental results confirm that CDC25C gene can serve as a potential marker for poor prognosis in LUAD.

RESULTS

We investigated aberrant gene expression in diverse cell types in LUAD via the scRNA-seq data. Moreover, multi-omics clustering revealed four subgroups defined by transcriptional profile and molecular subtype 4 (MS4) with poor survival probability, and immune cell infiltration signatures revealed that MS4 tended to be the immunosuppressive subtype. Our study revealed that the CDC25C gene can be a distinct prognostic biomarker that indicates immune infiltration levels and response to immunotherapy in LUAD patients. Our experimental results concluded that CDC25C expression affects lung cancer cell invasion and migration, might play a key role in regulating Epithelial-Mesenchymal Transition (EMT) pathways.

CONCLUSIONS

Our multi-omics result revealed a comprehensive set of molecular attributes associated with prognosis-related genes in LUAD at the cellular and tissue level. Identification of a subtype of immunosuppressive TME and prognostic signature for LUAD. We identified the cell cycle regulation gene CDC25C affects lung cancer cell invasion and migration, which can be used as a potential biomarker for LUAD.

Deep intravital brain tumor imaging enabled by tailored three-photon microscopy and analysis

Intravital 2P-microscopy enables the longitudinal study of brain tumor biology in superficial mouse cortex layers. Intravital microscopy of the white matter, an important route of glioblastoma invasion and recurrence, has not been feasible, due to low signal-to-noise ratios and insufficient spatiotemporal resolution. Here, we present an intravital microscopy and artificial intelligence-based analysis workflow (Deep3P) that enables longitudinal deep imaging of glioblastoma up to a depth of 1.2 mm. We find that perivascular invasion is the preferred invasion route into the corpus callosum and uncover two vascular mechanisms of glioblastoma migration in the white matter. Furthermore, we observe morphological changes after white matter infiltration, a potential basis of an imaging biomarker during early glioblastoma colonization. Taken together, Deep3P allows for a non-invasive intravital investigation of brain tumor biology and its tumor microenvironment at subcortical depths explored, opening up opportunities for studying the neuroscience of brain tumors and other model systems.

consICA: an R package for robust reference-free deconvolution of multi-omics data

Motivation

Deciphering molecular signals from omics data helps understanding cellular processes and disease progression. Effective algorithms for extracting these signals are essential, with a strong emphasis on robustness and reproducibility.

Results

R/Bioconductor package consICA implements consensus independent component analysis (ICA)-a data-driven deconvolution method to decompose heterogeneous omics data and extract features suitable for patient stratification and multimodal data integration. The method separates biologically relevant molecular signals from technical effects and provides information about the cellular composition and biological processes. Build-in annotation, survival analysis, and report generation provide useful tools for the interpretation of extracted signals. The implementation of parallel computing in the package ensures efficient analysis using modern multicore systems. The package offers a reproducible and efficient data-driven solution for the analysis of complex molecular profiles, with significant implications for cancer research.

Availability and implementation

The package is implemented in R and available under MIT license at Bioconductor (https://bioconductor.org/packages/consICA) or at GitHub (https://github.com/biomod-lih/consICA).

Progress in clinical diagnosis and treatment of colorectal cancer with rare genetic variants

Targeted therapy is crucial for advanced colorectal cancer (CRC) positive for genetic drivers. With advances in deep sequencing technology and new targeted drugs, existing standard molecular pathological detection systems and therapeutic strategies can no longer meet the requirements for careful management of patients with advanced CRC. Thus, rare genetic variations require diagnosis and targeted therapy in clinical practice. Rare gene mutations, amplifications, and rearrangements are usually associated with poor prognosis and poor response to conventional therapy. This review summarizes the clinical diagnosis and treatment of rare genetic variations, in genes including erb-b2 receptor tyrosine kinase 2 (ERBB2), B-Raf proto-oncogene, serine/threonine kinase (BRAF), ALK receptor tyrosine kinase/ROS proto-oncogene 1, receptor tyrosine kinase (ALK/ROS1), neurotrophic receptor tyrosine kinases (NTRKs), ret proto-oncogene (RET), fibroblast growth factor receptor 2 (FGFR2), and epidermal growth factor receptor (EGFR), to enhance understanding and identify more accurate personalized treatments for patients with rare genetic variations.

A prognostic neural epigenetic signature in high-grade glioma

Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is limited. We present an epigenetically defined neural signature of glioblastoma that independently predicts patients' survival. We use reference signatures of neural cells to deconvolve tumor DNA and classify samples into low- or high-neural tumors. High-neural glioblastomas exhibit hypomethylated CpG sites and upregulation of genes associated with synaptic integration. Single-cell transcriptomic analysis reveals a high abundance of malignant stemcell-like cells in high-neural glioblastoma, primarily of the neural lineage. These cells are further classified as neural-progenitor-cell-like, astrocyte-like and oligodendrocyte-progenitor-like, alongside oligodendrocytes and excitatory neurons. In line with these findings, high-neural glioblastoma cells engender neuron-to-glioma synapse formation in vitro and in vivo and show an unfavorable survival after xenografting. In patients, a high-neural signature is associated with decreased overall and progression-free survival. High-neural tumors also exhibit increased functional connectivity in magnetencephalography and resting-state magnet resonance imaging and can be detected via DNA analytes and brain-derived neurotrophic factor in patients' plasma. The prognostic importance of the neural signature was further validated in patients diagnosed with diffuse midline glioma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant. High-neural gliomas likely require a maximized surgical resection approach for improved outcomes.

Innovations in dedicated PET instrumentation: from the operating room to specimen imaging

This review casts a spotlight on intraoperative positron emission tomography (PET) scanners and the distinctive challenges they confront. Specifically, these systems contend with the necessity of partial coverage geometry, essential for ensuring adequate access to the patient. This inherently leans them towards limited-angle PET imaging, bringing along its array of reconstruction and geometrical sensitivity challenges. Compounding this, the need for real-time imaging in navigation systems mandates rapid acquisition and reconstruction times. For these systems, the emphasis is on dependable PET image reconstruction (without significant artefacts) while rapid processing takes precedence over the spatial resolution of the system. In contrast, specimen PET imagers are unburdened by the geometrical sensitivity challenges, thanks to their ability to leverage full coverage PET imaging geometries. For these devices, the focus shifts: high spatial resolution imaging takes precedence over rapid image reconstruction. This review concurrently probes into the technical complexities of both intraoperative and specimen PET imaging, shedding light on their recent designs, inherent challenges, and technological advancements.

CD19 CAR-expressing iPSC-derived NK cells effectively enhance migration and cytotoxicity into glioblastoma by targeting to the pericytes in tumor microenvironment

In cancer immunotherapy, chimeric antigen receptors (CARs) targeting specific antigens have become a powerful tool for cell-based therapy. CAR-natural killer (NK) cells offer selective anticancer lysis with reduced off-tumor toxicity compared to CAR-T cells, which is beneficial in the heterogeneous milieu of solid tumors. In the tumor microenvironment (TME) of glioblastoma (GBM), pericytes not only support tumor growth but also contribute to immune evasion, underscoring their potential as therapeutic targets in GBM treatment. Given this context, our study aimed to target the GBM TME, with a special focus on pericytes expressing CD19, to evaluate the potential effectiveness of CD19 CAR-iNK cells against GBM. We performed CD19 CAR transduction in induced pluripotent stem cell-derived NK (iNK) cells. To determine whether CD19 CAR targets the TME pericytes in GBM, we developed GBM-blood vessel assembloids (GBVA) by fusing GBM spheroids with blood vessel organoids. When co-cultured with GBVA, CD19 CAR-iNK cells migrated towards the pericytes surrounding the GBM. Using a microfluidic chip, we demonstrated CD19 CAR-iNK cells' targeted action and cytotoxic effects in a perfusion-like environment. GBVA xenografts recapitulated the TME including human CD19-positive pericytes, thereby enabling the application of an in vivo model for validating the efficacy of CD19 CAR-iNK cells against GBM. Compared to GBM spheroids, the presence of pericytes significantly enhanced CD19 CAR-iNK cell migration towards GBM and reduced proliferation. These results underline the efficacy of CD19 CAR-iNK cells in targeting pericytes within the GBM TME, suggesting their potential therapeutic value for GBM treatment.

Understanding glioblastoma at the single-cell level: Recent advances and future challenges

Glioblastoma, the most aggressive and prevalent form of primary brain tumor, is characterized by rapid growth, diffuse infiltration, and resistance to therapies. Intrinsic heterogeneity and cellular plasticity contribute to its rapid progression under therapy; therefore, there is a need to fully understand these tumors at a single-cell level. Over the past decade, single-cell transcriptomics has enabled the molecular characterization of individual cells within glioblastomas, providing previously unattainable insights into the genetic and molecular features that drive tumorigenesis, disease progression, and therapy resistance. However, despite advances in single-cell technologies, challenges such as high costs, complex data analysis and interpretation, and difficulties in translating findings into clinical practice persist. As single-cell technologies are developed further, more insights into the cellular and molecular heterogeneity of glioblastomas are expected, which will help guide the development of personalized and effective therapies, thereby improving prognosis and quality of life for patients.

Glioblastoma-instructed microglia transition to heterogeneous phenotypic states with phagocytic and dendritic cell-like features in patient tumors and patient-derived orthotopic xenografts

BACKGROUND

A major contributing factor to glioblastoma (GBM) development and progression is its ability to evade the immune system by creating an immune-suppressive environment, where GBM-associated myeloid cells, including resident microglia and peripheral monocyte-derived macrophages, play critical pro-tumoral roles. However, it is unclear whether recruited myeloid cells are phenotypically and functionally identical in GBM patients and whether this heterogeneity is recapitulated in patient-derived orthotopic xenografts (PDOXs). A thorough understanding of the GBM ecosystem and its recapitulation in preclinical models is currently missing, leading to inaccurate results and failures of clinical trials.

METHODS

Here, we report systematic characterization of the tumor microenvironment (TME) in GBM PDOXs and patient tumors at the single-cell and spatial levels. We applied single-cell RNA sequencing, spatial transcriptomics, multicolor flow cytometry, immunohistochemistry, and functional studies to examine the heterogeneous TME instructed by GBM cells. GBM PDOXs representing different tumor phenotypes were compared to glioma mouse GL261 syngeneic model and patient tumors.

RESULTS

We show that GBM tumor cells reciprocally interact with host cells to create a GBM patient-specific TME in PDOXs. We detected the most prominent transcriptomic adaptations in myeloid cells, with brain-resident microglia representing the main population in the cellular tumor, while peripheral-derived myeloid cells infiltrated the brain at sites of blood-brain barrier disruption. More specifically, we show that GBM-educated microglia undergo transition to diverse phenotypic states across distinct GBM landscapes and tumor niches. GBM-educated microglia subsets display phagocytic and dendritic cell-like gene expression programs. Additionally, we found novel microglial states expressing cell cycle programs, astrocytic or endothelial markers. Lastly, we show that temozolomide treatment leads to transcriptomic plasticity and altered crosstalk between GBM tumor cells and adjacent TME components.

CONCLUSIONS

Our data provide novel insights into the phenotypic adaptation of the heterogeneous TME instructed by GBM tumors. We show the key role of microglial phenotypic states in supporting GBM tumor growth and response to treatment. Our data place PDOXs as relevant models to assess the functionality of the TME and changes in the GBM ecosystem upon treatment.

Recent advances in patient-derived tumor organoids for reconstructing TME of head and neck cancer

BACKGROUND

The differences between existing preclinical models and the tumor microenvironment in vivo are one of the significant challenges hindering cancer therapy development. Patient-derived tumor organoids (PDTO) can highly retain tumor heterogeneity. Thus, it provides a more reliable platform for research in tumor biology, new drug screening, and precision medicine.

METHODS

We conducted a systematic review to summarise the characteristics of the existing preclinical models, the advantages of patient-derived tumor organoids in reconstructing the tumor microenvironment, and the latest research progress. Moreover, this study deciphers organoid culture technology in the clinical precision treatment of head and neck cancer to achieve better transformation. Studies were identified through a comprehensive search of Ovid MEDLINE (Wolters Kluwer), PubMed (National Library of Medicine), web of Science (Thomson Reuters) and, Scopus (Elsevier) databases, without publication date or language restrictions.

RESULTS

In tumor development, the interaction between cellular and non-cellular components in the tumor microenvironment (TME) has a crucial role. Co-culture, Air-liquid interface culture, microfluidics, and decellularized matrix have depicted great potential in reconstructing the tumor microenvironment and simulating tumor genesis, development, and metastasis.

CONCLUSION

An accurate determination of stromal cells, immune cells, and extracellular matrix can be achieved by reconstructing the head and neck cancer tumor microenvironment using the PDTO model. Moreover, the interaction between head and neck cancer cells can also play an essential role in implementing the individualized precision treatment of head and neck cancer.

Cancer organoids: A platform in basic and translational research

An accumulation of previous work has established organoids as good preclinical models of human tumors, facilitating translation from basic research to clinical practice. They are changing the paradigm of preclinical cancer research because they can recapitulate the heterogeneity and pathophysiology of human cancers and more closely approximate the complex tissue environment and structure found in clinical tumors than in vitro cell lines and animal models. However, the potential applications of cancer organoids remain to be comprehensively summarized. In the review, we firstly describe what is currently known about cancer organoid culture and then discuss in depth the basic mechanisms, including tumorigenesis and tumor metastasis, and describe recent advances in patient-derived tumor organoids (PDOs) for drug screening and immunological studies. Finally, the present challenges faced by organoid technology in clinical practice and its prospects are discussed. This review highlights that organoids may offer a novel therapeutic strategy for cancer research.

The dopamine receptor D1 inhibitor, SKF83566, suppresses GBM stemness and invasion through the DRD1-c-Myc-UHRF1 interactions

BACKGROUND

Extensive local invasion of glioblastoma (GBM) cells within the central nervous system (CNS) is one factor that severely limits current treatments. The aim of this study was to uncover genes involved in the invasion process, which could also serve as therapeutic targets. For the isolation of invasive GBM cells from non-invasive cells, we used a three-dimensional organotypic co-culture system where glioma stem cell (GSC) spheres were confronted with brain organoids (BOs). Using ultra-low input RNA sequencing (ui-RNA Seq), an invasive gene signature was obtained that was exploited in a therapeutic context.

METHODS

GFP-labeled tumor cells were sorted from invasive and non-invasive regions within co-cultures. Ui-RNA sequencing analysis was performed to find a gene cluster up-regulated in the invasive compartment. This gene cluster was further analyzed using the Connectivity MAP (CMap) database. This led to the identification of SKF83566, an antagonist of the D1 dopamine receptor (DRD1), as a candidate therapeutic molecule. Knockdown and overexpression experiments were performed to find molecular pathways responsible for the therapeutic effects of SKF83566. Finally, the effects of SKF83566 were validated in orthotopic xenograft models in vivo.

RESULTS

Ui-RNA seq analysis of three GSC cell models (P3, BG5 and BG7) yielded a set of 27 differentially expressed genes between invasive and non-invasive cells. Using CMap analysis, SKF83566 was identified as a selective inhibitor targeting both DRD1 and DRD5. In vitro studies demonstrated that SKF83566 inhibited tumor cell proliferation, GSC sphere formation, and invasion. RNA sequencing analysis of SKF83566-treated P3, BG5, BG7, and control cell populations yielded a total of 32 differentially expressed genes, that were predicted to be regulated by c-Myc. Of these, the UHRF1 gene emerged as the most downregulated gene following treatment, and ChIP experiments revealed that c-Myc binds to its promoter region. Finally, SKF83566, or stable DRD1 knockdown, inhibited the growth of orthotopic GSC (BG5) derived xenografts in nude mice.

CONCLUSIONS

DRD1 contributes to GBM invasion and progression by regulating c-Myc entry into the nucleus that affects the transcription of the UHRF1 gene. SKF83566 inhibits the transmembrane protein DRD1, and as such represents a candidate small therapeutic molecule for GBMs.

Magnetic resonance imaging-guided intracranial resection of glioblastoma tumors in patient-derived orthotopic xenografts leads to clinically relevant tumor recurrence

BACKGROUND

Preclinical in vivo cancer models are essential tools for investigating tumor progression and response to treatment prior to clinical trials. Although treatment modalities are regularly assessed in mice upon tumor growth in vivo, surgical resection remains challenging, particularly in the orthotopic site. Here, we report a successful surgical resection of glioblastoma (GBM) in patient-derived orthotopic xenografts (PDOXs).

METHODS

We derived a cohort of 46 GBM PDOX models that faithfully recapitulate human disease in mice. We assessed the detection and quantification of intracranial tumors using magnetic resonance imaging (MRI).To evaluate feasibility of surgical resection in PDOXs, we selected two models representing histopathological features of GBM tumors, including diffuse growth into the mouse brain. Surgical resection in the mouse brains was performed based on MRI-guided coordinates. Survival study followed by MRI and immunohistochemistry-based evaluation of recurrent tumors allowed for assessment of clinically relevant parameters.

RESULTS

We demonstrate the utility of MRI for the noninvasive assessment of in vivo tumor growth, preoperative programming of resection coordinates and follow-up of tumor recurrence. We report tumor detection by MRI in 90% of GBM PDOX models (36/40), of which 55% (22/40) can be reliably quantified during tumor growth. We show that a surgical resection protocol in mice carrying diffuse primary GBM tumors in the brain leads to clinically relevant outcomes. Similar to neurosurgery in patients, we achieved a near total to complete extent of tumor resection, and mice with resected tumors presented significantly increased survival. The remaining unresected GBM cells that invaded the normal mouse brain prior to surgery regrew tumors with similar histopathological features and tumor microenvironments to the primary tumors.

CONCLUSIONS

Our data positions GBM PDOXs developed in mouse brains as a valuable preclinical model for conducting therapeutic studies that involve surgical tumor resection. The high detectability of tumors by MRI across a substantial number of PDOX models in mice will allow for scalability of our approach toward specific tumor types for efficacy studies in precision medicine-oriented approaches. Additionally, these models hold promise for the development of enhanced image-guided surgery protocols.

Glioblastoma-instructed microglia transition to heterogeneous phenotypic states with phagocytic and dendritic cell-like features in patient tumors and patient-derived orthotopic xenografts

Background

A major contributing factor to glioblastoma (GBM) development and progression is its ability to evade the immune system by creating an immune-suppressive environment, where GBM-associated myeloid cells, including resident microglia and peripheral monocyte-derived macrophages, play critical pro-tumoral roles. However, it is unclear whether recruited myeloid cells are phenotypically and functionally identical in GBM patients and whether this heterogeneity is recapitulated in patient-derived orthotopic xenografts (PDOXs). A thorough understanding of the GBM ecosystem and its recapitulation in preclinical models is currently missing, leading to inaccurate results and failures of clinical trials.

Methods

Here, we report systematic characterization of the tumor microenvironment (TME) in GBM PDOXs and patient tumors at the single-cell and spatial levels. We applied single-cell RNA-sequencing, spatial transcriptomics, multicolor flow cytometry, immunohistochemistry and functional studies to examine the heterogeneous TME instructed by GBM cells. GBM PDOXs representing different tumor phenotypes were compared to glioma mouse GL261 syngeneic model and patient tumors.

Results

We show that GBM tumor cells reciprocally interact with host cells to create a GBM patient-specific TME in PDOXs. We detected the most prominent transcriptomic adaptations in myeloid cells, with brain-resident microglia representing the main population in the cellular tumor, while peripheral-derived myeloid cells infiltrated the brain at sites of blood-brain barrier disruption. More specifically, we show that GBM-educated microglia undergo transition to diverse phenotypic states across distinct GBM landscapes and tumor niches. GBM-educated microglia subsets display phagocytic and dendritic cell-like gene expression programs. Additionally, we found novel microglial states expressing cell cycle programs, astrocytic or endothelial markers. Lastly, we show that temozolomide treatment leads to transcriptomic plasticity and altered crosstalk between GBM tumor cells and adjacent TME components.

Conclusions

Our data provide novel insights into the phenotypic adaptation of the heterogeneous TME instructed by GBM tumors. We show the key role of microglial phenotypic states in supporting GBM tumor growth and response to treatment. Our data place PDOXs as relevant models to assess the functionality of the TME and changes in the GBM ecosystem upon treatment.

Synergistic effect of cryptotanshinone and temozolomide treatment against human glioblastoma cells

Glioblastoma multiforme (GBM) is a complex disease to treat owing to its profound chemoresistance. Therefore, we evaluated the combined effect and therapeutic efficacy of temozolomide (TMZ), a potent alkylating agent and the current gold standard therapy for GBM, and cryptotanshinone (CTS), which inhibits glioma cell proliferation in GBM cells. Using LN229 and U87-MG human GBM cells in a short-term stimulation in vitro model, the cytotoxic and anti-proliferative effects of single and combined treatment with 4 μM CTS and 200 μM TMZ were investigated. Furthermore, cell viability, DNA damage, apoptosis rate, and signal transducer and activator of transcription 3 (STAT3) protein were measured using cytotoxic assay, comet assay, flow cytometry, and western blotting analysis, respectively. The two drugs' synergistic interaction was validated using the synergy score. We found that the anti-proliferative effects of combination therapy using the two drugs were greater than that of each agent used alone (CTS or TMZ). Western blot analysis indicated that treatment of GBM cells with CTS combined with TMZ more significantly decreased the expression of MGMT and STAT3, than that with TMZ alone. Combined treatment with CTS and TMZ might be an effective option to overcome the chemoresistance of GBM cells in a long-term treatment strategy.

Patient- and xenograft-derived organoids recapitulate pediatric brain tumor features and patient treatments

Brain tumors are the leading cause of cancer-related death in children. Experimental in vitro models that faithfully capture the hallmarks and tumor heterogeneity of pediatric brain cancers are limited and hard to establish. We present a protocol that enables efficient generation, expansion, and biobanking of pediatric brain cancer organoids. Utilizing our protocol, we have established patient-derived organoids (PDOs) from ependymomas, medulloblastomas, low-grade glial tumors, and patient-derived xenograft organoids (PDXOs) from medulloblastoma xenografts. PDOs and PDXOs recapitulate histological features, DNA methylation profiles, and intratumor heterogeneity of the tumors from which they were derived. We also showed that PDOs can be xenografted. Most interestingly, when subjected to the same routinely applied therapeutic regimens, PDOs respond similarly to the patients. Taken together, our study highlights the potential of PDOs and PDXOs for research and translational applications for personalized medicine.

A Prediction Model for Deciphering Intratumoral Heterogeneity Derived from the Microglia/Macrophages of Glioma Using Non-Invasive Radiogenomics

Microglia and macrophages play a major role in glioma immune responses within the glioma microenvironment. We aimed to construct a prognostic prediction model for glioma based on microglia/macrophage-correlated genes. Additionally, we sought to develop a non-invasive radiogenomics approach for risk stratification evaluation. Microglia/macrophage-correlated genes were identified from four single-cell datasets. Hub genes were selected via lasso-Cox regression, and risk scores were calculated. The immunological characteristics of different risk stratifications were assessed, and radiomics models were constructed using corresponding MRI imaging to predict risk stratification. We identified eight hub genes and developed a relevant risk score formula. The risk score emerged as a significant prognostic predictor correlated with immune checkpoints, and a relevant nomogram was drawn. High-risk groups displayed an active microenvironment associated with microglia/macrophages. Furthermore, differences in somatic mutation rates, such as IDH1 missense variant and TP53 missense variant, were observed between high- and low-risk groups. Lastly, a radiogenomics model utilizing five features from magnetic resonance imaging (MRI) T2 fluid-attenuated inversion recovery (Flair) effectively predicted the risk groups under a random forest model. Our findings demonstrate that risk stratification based on microglia/macrophages can effectively predict prognosis and immune functions in glioma. Moreover, we have shown that risk stratification can be non-invasively predicted using an MRI-T2 Flair-based radiogenomics model.

Preclinical glioma models in neuro-oncology: enhancing translational research

PURPOSE OF REVIEW

Gliomas represent approximately 25% of all primary brain and other central nervous system (CNS) tumors and 81% of malignant tumors. Unfortunately, standard treatment approaches for most CNS cancers have shown limited improvement in patient survival rates.

RECENT FINDINGS

The current drug development process has been plagued by high failure rates, leading to a shift towards human disease models in biomedical research. Unfortunately, suitable preclinical models for brain tumors have been lacking, hampering our understanding of tumor initiation processes and the discovery of effective treatments. In this review, we will explore the diverse preclinical models employed in neuro-oncology research and their contributions to translational science.

SUMMARY

By utilizing a combination of these preclinical models and fostering interdisciplinary collaborations, researchers can deepen their understanding of glioma brain tumors and develop novel therapeutic strategies to combat these devastating diseases. These models offer promising prospects for personalized and efficacious treatments for these challenging malignancies. Although it is unrealistic to fully replicate the complexity of the human body in vitro, the ultimate goal should be to achieve the closest possible resemblance to the clinical context.

Progress in building clinically relevant patient-derived tumor xenograft models for cancer research

Patient-derived tumor xenograft (PDX) models, a method involving the surgical extraction of tumor tissues from cancer patients and subsequent transplantation into immunodeficient mice, have emerged as a pivotal approach in translational research, particularly in advancing precision medicine. As the first stage of PDX development, the patient-derived orthotopic xenograft (PDOX) models implant tumor tissue in mice in the corresponding anatomical locations of the patient. The PDOX models have several advantages, including high fidelity to the original tumor, heightened drug sensitivity, and an elevated rate of successful transplantation. However, the PDOX models present significant challenges, requiring advanced surgical techniques and resource-intensive imaging technologies, which limit its application. And then, the humanized mouse models, as well as the zebrafish models, were developed. Humanized mouse models contain a human immune environment resembling the tumor and immune system interplay. The humanized mouse models are a hot topic in PDX model research. Regarding zebrafish patient-derived tumor xenografts (zPDX) and patient-derived organoids (PDO) as promising models for studying cancer and drug discovery, zPDX models are used to transplant tumors into zebrafish as novel personalized medical animal models with the advantage of reducing patient waiting time. PDO models provide a cost-effective approach for drug testing that replicates the in vivo environment and preserves important tumor-related information for patients. The present review highlights the functional characteristics of each new phase of PDX and provides insights into the challenges and prospective developments in this rapidly evolving field.

Ex vivo drug sensitivity screening predicts response to temozolomide in glioblastoma patients and identifies candidate biomarkers

BACKGROUND

Patient-derived glioma stem-like cells (GSCs) have become the gold-standard in neuro-oncological research; however, it remains to be established whether loss of in situ microenvironment affects the clinically-predictive value of this model. We implemented a GSC monolayer system to investigate in situ-in vitro molecular correspondence and the relationship between in vitro and patient response to temozolomide (TMZ).

METHODS

DNA/RNA-sequencing was performed on 56 glioblastoma tissues and 19 derived GSC cultures. Sensitivity to TMZ was screened across 66 GSC cultures. Viability readouts were related to clinical parameters of corresponding patients and whole-transcriptome data.

RESULTS

Tumour DNA and RNA sequences revealed strong similarity to corresponding GSCs despite loss of neuronal and immune interactions. In vitro TMZ screening yielded three response categories which significantly correlated with patient survival, therewith providing more specific prediction than the binary MGMT marker. Transcriptome analysis identified 121 genes related to TMZ sensitivity of which 21were validated in external datasets.

CONCLUSION

GSCs retain patient-unique hallmark gene expressions despite loss of their natural environment. Drug screening using GSCs predicted patient response to TMZ more specifically than MGMT status, while transcriptome analysis identified potential biomarkers for this response. GSC drug screening therefore provides a tool to improve drug development and precision medicine for glioblastoma.

Can Organoid Model Reveal a Key Role of Extracellular Vesicles in Tumors? A Comprehensive Review of the Literature

Extracellular vesicles (EVs) are small membrane-bound vesicles that are released by cells into the extracellular environment. The role of EVs in tumors has been extensively studied, and they have been shown to play a crucial role in tumor growth, progression, and metastasis. Past research has mainly used 2D-cultured cell line models to investigate the role of EVs in tumors, which poorly simulate the tumor microenvironment. Organoid technology has gradually matured in recent years. Organoids are similar in composition and behavior to physiological cells and have the potential to recapitulate the architecture and function of the original tissue. It has been widely used in organogenesis, drug screening, gene editing, precision medicine and other fields. The integration of EVs and organoids has the potential to revolutionize the field of cancer research and represents a promising avenue for advancing our understanding of cancer biology and the development of novel therapeutic strategies. Here, we aimed to present a comprehensive overview of studies using organoids to study EVs in tumors.

Histological analysis of invasive glioblastoma organoids embedded in a 3D collagen matrix

Organoids are unique tools to mimic how tumors evolve in a 3D environment. Here, we present a protocol to embed spheroids invading a 3D matrix into a paraffin mold. We describe steps for preparing spheroids, collagen and agarose inclusion, and paraffinization. We then detail procedures for sectioning, staining, and visualization. This protocol allows histological identification of markers expressed in cells escaping the tumor. For complete details on the use and execution of this protocol, please refer to Guyon et al. (2022).1.

Recent advancements and theranostics strategies in glioblastoma therapy

Glioblastoma (GBM) is the most aggressive and lethal malignant brain tumor, and it is challenging to cure with surgery and treatment. The prevention of permanent brain damage and tumor invasion, which is the ultimate cause of recurrence, are major obstacles in GBM treatment. Besides, emerging treatment modalities and newer genetic findings are helping to understand and manage GBM in patients. Accordingly, researchers are focusing on advanced nanomaterials-based strategies for tackling the various problems associated with GBM. In this context, researchers explored novel strategies with various alternative treatment approaches such as early detection techniques and theranostics approaches. In this review, we have emphasized the recent advancement of GBM cellular models and their roles in designing GBM therapeutics. We have added a special emphasis on the novel genetic and drug target findings as well as strategies for early detection. Besides, we have discussed various theranostic approaches such as hyperthermia therapy, phototherapy and image-guided therapy. Approaches utilized for targeted drug delivery to the GBM were also discussed. This article also describes the recentin vivo, in vitroandex vivoadvances using innovative theranostic approaches.

Epigenetic neural glioblastoma enhances synaptic integration and predicts therapeutic vulnerability

Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is nascent. We present an epigenetically defined neural signature of glioblastoma that independently affects patients' survival. We use reference signatures of neural cells to deconvolve tumor DNA and classify samples into low- or high-neural tumors. High-neural glioblastomas exhibit hypomethylated CpG sites and upregulation of genes associated with synaptic integration. Single-cell transcriptomic analysis reveals high abundance of stem cell-like malignant cells classified as oligodendrocyte precursor and neural precursor cell-like in high-neural glioblastoma. High-neural glioblastoma cells engender neuron-to-glioma synapse formation in vitro and in vivo and show an unfavorable survival after xenografting. In patients, a high-neural signature associates with decreased survival as well as increased functional connectivity and can be detected via DNA analytes and brain-derived neurotrophic factor in plasma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant.

Glioblastoma modeling with 3D organoids: progress and challenges

Glioblastoma (GBM) is the most aggressive adult primary brain tumor with nearly universal treatment resistance and recurrence. The mainstay of therapy remains maximal safe surgical resection followed by concurrent radiation therapy and temozolomide chemotherapy. Despite intensive investigation, alternative treatment options, such as immunotherapy or targeted molecular therapy, have yielded limited success to achieve long-term remission. This difficulty is partly due to the lack of pre-clinical models that fully recapitulate the intratumoral and intertumoral heterogeneity of GBM and the complex tumor microenvironment. Recently, GBM 3D organoids originating from resected patient tumors, genetic manipulation of induced pluripotent stem cell (iPSC)-derived brain organoids and bio-printing or fusion with non-malignant tissues have emerged as novel culture systems to portray the biology of GBM. Here, we highlight several methodologies for generating GBM organoids and discuss insights gained using such organoid models compared to classic modeling approaches using cell lines and xenografts. We also outline limitations of current GBM 3D organoids, most notably the difficulty retaining the tumor microenvironment, and discuss current efforts for improvements. Finally, we propose potential applications of organoid models for a deeper mechanistic understanding of GBM and therapeutic development.

Radiation Sensitivity: The Rise of Predictive Patient-Derived Cancer Models

Patient-derived cancer models have been used for decades to improve our understanding of cancer and test anticancer treatments. Advances in radiation delivery have made these models more attractive for studying radiation sensitizers and understanding an individual patient's radiation sensitivity. Advances in the use of patient-derived cancer models lead to a more clinically relevant outcome, although many questions remain regarding the optimal use of patient-derived xenografts and patient-derived spheroid cultures. The use of patient-derived cancer models as personalized predictive avatars through mouse and zebrafish models is discussed, and the advantages and disadvantages of patient-derived spheroids are reviewed. In addition, the use of large repositories of patient-derived models to develop predictive algorithms to guide treatment selection is discussed. Finally, we review methods for establishing patient-derived models and identify key factors that influence their use as both avatars and models of cancer biology.

Organoids: The current status and biomedical applications

Organoids are three-dimensional (3D) miniaturized versions of organs or tissues that are derived from cells with stem potential and can self-organize and differentiate into 3D cell masses, recapitulating the morphology and functions of their in vivo counterparts. Organoid culture is an emerging 3D culture technology, and organoids derived from various organs and tissues, such as the brain, lung, heart, liver, and kidney, have been generated. Compared with traditional bidimensional culture, organoid culture systems have the unique advantage of conserving parental gene expression and mutation characteristics, as well as long-term maintenance of the function and biological characteristics of the parental cells in vitro. All these features of organoids open up new opportunities for drug discovery, large-scale drug screening, and precision medicine. Another major application of organoids is disease modeling, and especially various hereditary diseases that are difficult to model in vitro have been modeled with organoids by combining genome editing technologies. Herein, we introduce the development and current advances in the organoid technology field. We focus on the applications of organoids in basic biology and clinical research, and also highlight their limitations and future perspectives. We hope that this review can provide a valuable reference for the developments and applications of organoids.

Personalized Medicine in Brain Gliomas: Targeted Therapy, Patient-Derived Tumor Models (Review)

Gliomas are the most common type of primary malignant brain tumors. The choice of treatments for these tumors was quite limited for many years, and therapy results generally remain still unsatisfactory. Recently, a significant breakthrough in the treatment of many forms of cancer occurred when personalized targeted therapies were introduced which inhibit tumor growth by affecting a specific molecular target. Another trend gaining popularity in oncology is the creation of patient-derived tumor models which can be used for drug screening to select the optimal therapy regimen. Molecular and genetic mechanisms of brain gliomas growth are considered, consisting of individual components which could potentially be exposed to targeted drugs. The results of the literature review show a higher efficacy of the personalized approach to the treatment of individual patients compared to the use of standard therapies. However, many unresolved issues remain in the area of predicting the effectiveness of a particular drug therapy regimen. The main hopes in solving this issue are set on the use of patient-derived tumor models, which can be used in one-stage testing of a wide range of antitumor drugs.

Expert opinion on translational research for advanced glioblastoma treatment

Malignant gliomas are known to be one of the most difficult diseases to diagnose and treat because of the infiltrative growth pattern, rapid progression, and poor prognosis. Many antitumor drugs are not ideal for the treatment of gliomas due to the blood-brain barrier. Temozolomide (TMZ) is a DNA alkylating agent that can cross the blood-brain barrier. As the only first-line chemotherapeutic drug for malignant gliomas at present, TMZ is widely utilized to provide a survival benefit; however, some patients are inherently insensitive to TMZ. In addition, patients could develop acquired resistance during TMZ treatment, which limits antitumor efficacy. To clarify the mechanism underlying TMZ resistance, numerous studies have provided multilevel solutions, such as improving the effective concentration of TMZ in tumors and developing novel small molecule drugs. This review discusses the in-depth mechanisms underlying TMZ drug resistance, thus aiming to provide possibilities for the establishment of personalized therapeutic strategies against malignant gliomas and the accelerated development and transformation of new targeted drugs.

Modeling glioblastoma complexity with organoids for personalized treatments

Glioblastoma (GBM) remains a fatal diagnosis despite the current standard of care of maximal surgical resection, radiation, and temozolomide (TMZ) therapy. One aspect that impedes drug development is the lack of an appropriate model representative of the complexity of patient tumors. Brain organoids derived from cell culture techniques provide a robust, easily manipulatable, and high-throughput model for GBM. In this review, we highlight recent progress in developing GBM organoids (GBOs) with a focus on generating the GBM microenvironment (i.e., stem cells, vasculature, and immune cells) recapitulating human disease. Finally, we also discuss the use of organoids as a screening tool in drug development for GBM.

A review of protocols for brain organoids and applications for disease modeling

Recent breakthroughs in human stem cell technologies have enabled the generation of 3D brain organoid platforms for modeling human neurodevelopment and disease. Here, we review advances in brain organoid development, approaches for generating whole-brain or cerebral organoids and region-specific brain organoids, and their applications in disease modeling. We present a comprehensive overview of various brain organoid generation protocols, including culture steps, media, timelines, and technical considerations associated with each protocol, and highlight the advantages and disadvantages of each protocol. We also discuss the current limitations as well as increasing sophistication of brain organoid technology, and future directions for the field. These insights provide a valuable assessment of multiple commonly used brain organoid models and main considerations for investigators who are considering implementing brain organoid technologies in their laboratories.

From cells to organoids: The evolution of blood-brain barrier technology for modelling drug delivery in brain cancer

Brain cancer remains the deadliest cancer. The blood-brain barrier (BBB) is impenetrable to most drugs and is a complex 3D network of multiple cell types including endothelial cells, astrocytes, and pericytes. In brain cancers, the BBB becomes disrupted during tumor progression and forms the blood-brain tumor barrier (BBTB). To advance therapeutic development, there is a critical need for physiologically relevant BBB in vitro models. 3D cell systems are emerging as valuable preclinical models to accelerate discoveries for diseases. Given the versatility and capability of 3D cell models, their potential for modelling the BBB and BBTB is reviewed. Technological advances of BBB models and challenges of in vitro modelling the BBTB, and application of these models as tools for assessing therapeutics and nano drug delivery, are discussed. Quantitative, in vitro BBB models that are predictive of effective brain cancer therapies will be invaluable for accelerating advancing new treatments to the clinic.