Single-cell chromatin accessibility profiling of glioblastoma identifies an invasive cancer stem cell population associated with lower survival

Cellular diversity through space and time: adding new dimensions to GBM therapeutic development

The current median survival for glioblastoma (GBM) patients is only about 16 months, with many patients succumbing to the disease in just a matter of months, making it the most common and aggressive primary brain cancer in adults. This poor outcome is, in part, due to the lack of new treatment options with only one FDA-approved treatment in the last decade. Advances in sequencing techniques and transcriptomic analyses have revealed a vast degree of heterogeneity in GBM, from inter-patient diversity to intra-tumoral cellular variability. These cutting-edge approaches are providing new molecular insights highlighting a critical role for the tumor microenvironment (TME) as a driver of cellular plasticity and phenotypic heterogeneity. With this expanded molecular toolbox, the influence of TME factors, including endogenous (e.g., oxygen and nutrient availability and interactions with non-malignant cells) and iatrogenically induced (e.g., post-therapeutic intervention) stimuli, on tumor cell states can be explored to a greater depth. There exists a critical need for interrogating the temporal and spatial aspects of patient tumors at a high, cell-level resolution to identify therapeutically targetable states, interactions and mechanisms. In this review, we discuss advancements in our understanding of spatiotemporal diversity in GBM with an emphasis on the influence of hypoxia and immune cell interactions on tumor cell heterogeneity. Additionally, we describe specific high-resolution spatially resolved methodologies and their potential to expand the impact of pre-clinical GBM studies. Finally, we highlight clinical attempts at targeting hypoxia- and immune-related mechanisms of malignancy and the potential therapeutic opportunities afforded by single-cell and spatial exploration of GBM patient specimens.

VC-resist glioblastoma cell state: vessel co-option as a key driver of chemoradiation resistance

Glioblastoma (GBM) is a highly lethal type of cancer. GBM recurrence following chemoradiation is typically attributed to the regrowth of invasive and resistant cells. Therefore, there is a pressing need to gain a deeper understanding of the mechanisms underlying GBM resistance to chemoradiation and its ability to infiltrate. Using a combination of transcriptomic, proteomic, and phosphoproteomic analyses, longitudinal imaging, organotypic cultures, functional assays, animal studies, and clinical data analyses, we demonstrate that chemoradiation and brain vasculature induce cell transition to a functional state named VC-Resist (vessel co-opting and resistant cell state). This cell state is midway along the transcriptomic axis between proneural and mesenchymal GBM cells and is closer to the AC/MES1-like state. VC-Resist GBM cells are highly vessel co-opting, allowing significant infiltration into the surrounding brain tissue and homing to the perivascular niche, which in turn induces even more VC-Resist transition. The molecular and functional characteristics of this FGFR1-YAP1-dependent GBM cell state, including resistance to DNA damage, enrichment in the G2M phase, and induction of senescence/stemness pathways, contribute to its enhanced resistance to chemoradiation. These findings demonstrate how vessel co-option, perivascular niche, and GBM cell plasticity jointly drive resistance to therapy during GBM recurrence.

CellSTAR: a comprehensive resource for single-cell transcriptomic annotation

Large-scale studies of single-cell sequencing and biological experiments have successfully revealed expression patterns that distinguish different cell types in tissues, emphasizing the importance of studying cellular heterogeneity and accurately annotating cell types. Analysis of gene expression profiles in these experiments provides two essential types of data for cell type annotation: annotated references and canonical markers. In this study, the first comprehensive database of single-cell transcriptomic annotation resource (CellSTAR) was thus developed. It is unique in (a) offering the comprehensive expertly annotated reference data for annotating hundreds of cell types for the first time and (b) enabling the collective consideration of reference data and marker genes by incorporating tens of thousands of markers. Given its unique features, CellSTAR is expected to attract broad research interests from the technological innovations in single-cell transcriptomics, the studies of cellular heterogeneity & dynamics, and so on. It is now publicly accessible without any login requirement at: https://idrblab.org/cellstar.

StemnesScoRe: an R package to estimate the stemness of glioma cancer cells at single-cell resolution

Background/aim

Glioblastoma is the most heterogeneous and the most difficult-to-treat type of brain tumor and one of the deadliest among all cancers. The high plasticity of glioma cancer stem cells and the resistance they develop against multiple modalities of therapy, along with their high heterogeneity, are the main challenges faced during treatment of glioblastoma. Therefore, a better understanding of the stemness characteristics of glioblastoma cells is needed. With the development of various single-cell technologies and increasing applications of machine learning, indices based on transcriptomic and/or epigenomic data have been developed to quantitatively measure cellular states and stemness. In this study, we aimed to develop a glioma-specific stemness score model using scATAC-seq data for the first time.

Materials and methods

We first applied three powerful machine-learning algorithms, i.e. random forest, gradient boosting, and extreme gradient boosting, to glioblastoma scRNA-seq data to discover the most important genes associated with cellular states. We then identified promoter and enhancer regions associated with these genes. After downloading the scATAC-seq peaks and their read counts for each patient, we identified the overlapping regions between the single-cell peaks and the peaks of genes obtained through machine-learning algorithms. Then we calculated read counts that were mapped to these overlapping regions. We finally developed a model capable of estimating the stemness score for each glioma cell using overlapping regions and the importance of genes predictive of glioblastoma cellular states. We also created an R package, accessible to all researchers regardless of their coding proficiency.

Results

Our results showed that mesenchymal-like stem cells display higher stemness scores compared to neural-progenitor-, oligodendrocyte-progenitor-, and astrocyte-like cells.

Conclusion

scATAC-seq can be used to assess heterogeneity in glioblastoma and identify cells with high stemness characteristics. The package is publicly available at https://github.com/Necla/StemnesScoRe and includes documentation with implementation of a real-data experiment.

A Bayesian method to infer copy number clones from single-cell RNA and ATAC sequencing

Single-cell RNA and ATAC sequencing technologies enable the examination of gene expression and chromatin accessibility in individual cells, providing insights into cellular phenotypes. In cancer research, it is important to consistently analyze these states within an evolutionary context on genetic clones. Here we present CONGAS+, a Bayesian model to map single-cell RNA and ATAC profiles onto the latent space of copy number clones. CONGAS+ clusters cells into tumour subclones with similar ploidy, rendering straightforward to compare their expression and chromatin profiles. The framework, implemented on GPU and tested on real and simulated data, scales to analyse seamlessly thousands of cells, demonstrating better performance than single-molecule models, and supporting new multi-omics assays. In prostate cancer, lymphoma and basal cell carcinoma, CONGAS+ successfully identifies complex subclonal architectures while providing a coherent mapping between ATAC and RNA, facilitating the study of genotype-phenotype maps and their connection to genomic instability.

Rewiring of the promoter-enhancer interactome and regulatory landscape in glioblastoma orchestrates gene expression underlying neurogliomal synaptic communication

Chromatin organization controls transcription by modulating 3D-interactions between enhancers and promoters in the nucleus. Alterations in epigenetic states and 3D-chromatin organization result in gene expression changes contributing to cancer. Here, we map the promoter-enhancer interactome and regulatory landscape of glioblastoma, the most aggressive primary brain tumour. Our data reveals profound rewiring of promoter-enhancer interactions, chromatin accessibility and redistribution of histone marks in glioblastoma. This leads to loss of long-range regulatory interactions and overall activation of promoters, which orchestrate changes in the expression of genes associated to glutamatergic synapses, axon guidance, axonogenesis and chromatin remodelling. SMAD3 and PITX1 emerge as major transcription factors controlling genes related to synapse organization and axon guidance. Inhibition of SMAD3 and neuronal activity stimulation cooperate to promote proliferation of glioblastoma cells in co-culture with glutamatergic neurons, and in mice bearing patient-derived xenografts. Our findings provide mechanistic insight into the regulatory networks that mediate neurogliomal synaptic communication.

Kunitz-type protease inhibitor TFPI2 remodels stemness and immunosuppressive tumor microenvironment in glioblastoma

Glioblastoma (GBM) tumors consist of multiple cell populations, including self-renewing glioblastoma stem cells (GSCs) and immunosuppressive microglia. Here we identified Kunitz-type protease inhibitor TFPI2 as a critical factor connecting these cell populations and their associated GBM hallmarks of stemness and immunosuppression. TFPI2 promotes GSC self-renewal and tumor growth via activation of the c-Jun N-terminal kinase-signal transducer and activator of transcription (STAT)3 pathway. Secreted TFPI2 interacts with its functional receptor CD51 on microglia to trigger the infiltration and immunosuppressive polarization of microglia through activation of STAT6 signaling. Inhibition of the TFPI2-CD51-STAT6 signaling axis activates T cells and synergizes with anti-PD1 therapy in GBM mouse models. In human GBM, TFPI2 correlates positively with stemness, microglia abundance, immunosuppression and poor prognosis. Our study identifies a function for TFPI2 and supports therapeutic targeting of TFPI2 as an effective strategy for GBM.

Decoding Cancer Evolution: Integrating Genetic and Non-Genetic Insights

The development of cancer begins with cells transitioning from their multicellular nature to a state akin to unicellular organisms. This shift leads to a breakdown in the crucial regulators inherent to multicellularity, resulting in the emergence of diverse cancer cell subpopulations that have enhanced adaptability. The presence of different cell subpopulations within a tumour, known as intratumoural heterogeneity (ITH), poses challenges for cancer treatment. In this review, we delve into the dynamics of the shift from multicellularity to unicellularity during cancer onset and progression. We highlight the role of genetic and non-genetic factors, as well as tumour microenvironment, in promoting ITH and cancer evolution. Additionally, we shed light on the latest advancements in omics technologies that allow for in-depth analysis of tumours at the single-cell level and their spatial organization within the tissue. Obtaining such detailed information is crucial for deepening our understanding of the diverse evolutionary paths of cancer, allowing for the development of effective therapies targeting the key drivers of cancer evolution.

The Transcriptional and Epigenetic Landscape of Cancer Cell Lineage Plasticity

Lineage plasticity, a process whereby cells change their phenotype to take on a different molecular and/or histologic identity, is a key driver of cancer progression and therapy resistance. Although underlying genetic changes within the tumor can enhance lineage plasticity, it is predominantly a dynamic process controlled by transcriptional and epigenetic dysregulation. This review explores the transcriptional and epigenetic regulators of lineage plasticity and their interplay with other features of malignancy, such as dysregulated metabolism, the tumor microenvironment, and immune evasion. We also discuss strategies for the detection and treatment of highly plastic tumors.

SIGNIFICANCE

Lineage plasticity is a hallmark of cancer and a critical facilitator of other oncogenic features such as metastasis, therapy resistance, dysregulated metabolism, and immune evasion. It is essential that the molecular mechanisms of lineage plasticity are elucidated to enable the development of strategies to effectively target this phenomenon. In this review, we describe key transcriptional and epigenetic regulators of cancer cell plasticity, in the process highlighting therapeutic approaches that may be harnessed for patient benefit.

Decoding key cell sub-populations and molecular alterations in glioblastoma at recurrence by single-cell analysis

Glioblastoma (GBM) is the most frequent malignant brain tumor, the relapse of which is unavoidable following standard treatment. However, the effective treatment for recurrent GBM is lacking, necessitating the understanding of key mechanisms driving tumor recurrence and the identification of new targets for intervention. Here, we integrated single-cell RNA-sequencing data spanning 36 patient-matched primary and recurrent GBM (pGBM and rGBM) specimens, with 6 longitudinal GBM spatial transcriptomics to explore molecular alterations at recurrence, with each cell type characterized in parallel. Genes involved in extracellular matrix (ECM) organization are preferentially enriched in rGBM cells, and MAFK is highlighted as a potential regulator. Notably, we uncover a unique subpopulation of GBM cells that is much less detected in pGBM and highly expresses ECM and mesenchyme related genes, suggesting it may contribute to the molecular transition of rGBM. Further regulatory network analysis reveals that transcription factors, such as NFATC4 and activator protein 1 members, may function as hub regulators. All non-tumor cells alter their specific sets of genes as well and certain subgroups of myeloid cells appear to be physically associated with the mesenchyme-like GBM subpopulation. Altogether, our study provides new insights into the molecular understanding of GBM relapse and candidate targets for rGBM treatment.

Glioblastoma Mesenchymal Transition and Invasion are Dependent on a NF-κB/BRD2 Chromatin Complex

Glioblastoma (GBM) represents the most aggressive subtype of glioma, noted for its profound invasiveness and molecular heterogeneity. The mesenchymal (MES) transcriptomic subtype is frequently associated with therapy resistance, rapid recurrence, and increased tumor-associated macrophages. Notably, activation of the NF-κB pathway and alterations in the PTEN gene are both associated with this malignant transition. Although PTEN aberrations have been shown to be associated with enhanced NF-κB signaling, the relationships between PTEN, NF-κB and MES transition are poorly understood in GBM. Here, we show that PTEN regulates the chromatin binding of bromodomain and extraterminal (BET) family proteins, BRD2 and BRD4, mediated by p65/RelA localization to the chromatin. By utilizing patient-derived glioblastoma stem cells and CRISPR gene editing of the RELA gene, we demonstrate a crucial role for RelA lysine 310 acetylation in recruiting BET proteins to chromatin for MES gene expression and GBM cell invasion upon PTEN loss. Remarkably, we found that BRD2 is dependent on chromatin associated acetylated RelA for its recruitment to MES gene promoters and their expression. Furthermore, loss of BRD2 results in the loss of MES signature, accompanied by an enrichment of proneural signature and enhanced therapy responsiveness. Finally, we demonstrate that disrupting the NFκB/BRD2 interaction with a brain penetrant BET-BD2 inhibitor reduces mesenchymal gene expression, GBM invasion, and therapy resistance in GBM models. This study uncovers the role of hitherto unexplored PTEN-NF-κB-BRD2 pathway in promoting MES transition and suggests inhibiting this complex with BET-BD2 specific inhibitors as a therapeutic approach to target the MES phenotype in GBM.

Glioblastoma heterogeneity at single cell resolution

Glioblastoma (GBM) is one of the deadliest types of cancer and highly refractory to chemoradiation and immunotherapy. One of the main reasons for this resistance to therapy lies within the heterogeneity of the tumor and its associated microenvironment. The vast diversity of cell states, composition of cells, and phenotypical characteristics makes it difficult to accurately classify GBM into distinct subtypes and find effective therapies. The advancement of sequencing technologies in recent years has further corroborated the heterogeneity of GBM at the single cell level. Recent studies have only begun to elucidate the different cell states present in GBM and how they correlate with sensitivity to therapy. Furthermore, it has become clear that GBM heterogeneity not only depends on intrinsic factors but also strongly differs between new and recurrent GBM, and treatment naïve and experienced patients. Understanding and connecting the complex cellular network that underlies GBM heterogeneity will be indispensable in finding new ways to tackle this deadly disease. Here, we present an overview of the multiple layers of GBM heterogeneity and discuss novel findings in the age of single cell technologies.

Integrated analysis of single-cell chromatin state and transcriptome identified common vulnerability despite glioblastoma heterogeneity

In 2021, the World Health Organization reclassified glioblastoma, the most common form of adult brain cancer, into isocitrate dehydrogenase (IDH)-wild-type glioblastomas and grade IV IDH mutant (G4 IDHm) astrocytomas. For both tumor types, intratumoral heterogeneity is a key contributor to therapeutic failure. To better define this heterogeneity, genome-wide chromatin accessibility and transcription profiles of clinical samples of glioblastomas and G4 IDHm astrocytomas were analyzed at single-cell resolution. These profiles afforded resolution of intratumoral genetic heterogeneity, including delineation of cell-to-cell variations in distinct cell states, focal gene amplifications, as well as extrachromosomal circular DNAs. Despite differences in IDH mutation status and significant intratumoral heterogeneity, the profiled tumor cells shared a common chromatin structure defined by open regions enriched for nuclear factor 1 transcription factors (NFIA and NFIB). Silencing of NFIA or NFIB suppressed in vitro and in vivo growths of patient-derived glioblastomas and G4 IDHm astrocytoma models. These findings suggest that despite distinct genotypes and cell states, glioblastoma/G4 astrocytoma cells share dependency on core transcriptional programs, yielding an attractive platform for addressing therapeutic challenges associated with intratumoral heterogeneity.

Microenvironment-Driven Dynamic Chromatin Changes in Glioblastoma Recapitulate Early Neural Development at Single-Cell Resolution

The tumor microenvironment is necessary for recapitulating the intratumoral heterogeneity and cell state plasticity found in human primary glioblastoma (GBM). Conventional models do not accurately recapitulate the spectrum of GBM cellular states, hindering elucidation of the underlying transcriptional regulation of these states. Using our glioblastoma cerebral organoid model, we profiled the chromatin accessibility of 28,040 single cells in five patient-derived glioma stem cell lines. Integration of paired epigenomes and transcriptomes within the context of tumor-normal host cell interactions was used to probe the gene-regulatory networks underlying individual GBM cellular states in a way not readily possible in other in vitro models. These analyses identified the epigenetic underpinnings of GBM cellular states and characterized dynamic chromatin changes reminiscent of early neural development that underlie GBM cell state transitions. Despite large differences between tumors, a shared cellular compartment made up of neural progenitor-like cells and outer radial glia-like cells was observed. Together, these results shed light on the transcriptional regulation program in GBM and offer novel therapeutic targets across a broad range of genetically heterogenous GBMs.

SIGNIFICANCE

Single-cell analyses elucidate the chromatin landscape and transcriptional regulation of glioblastoma cellular states and identify a radial glia-like population, providing potential targets to disrupt cell states and improve therapeutic efficacy.

Applying single cell multi-omic analyses to understand treatment resistance in pediatric high grade glioma

Despite improvements in cancer patient outcomes seen in the past decade, tumor resistance to therapy remains a major impediment to achieving durable clinical responses. Intratumoral heterogeneity related to genetic, epigenetic, transcriptomic, proteomic, and metabolic differences between individual cancer cells has emerged as a driver of therapeutic resistance. This cell to cell heterogeneity can be assessed using single cell profiling technologies that enable the identification of tumor cell clones that exhibit similar defining features like specific mutations or patterns of DNA methylation. Single cell profiling of tumors before and after treatment can generate new insights into the cancer cell characteristics that confer therapeutic resistance by identifying intrinsically resistant sub-populations that survive treatment and by describing new cellular features that emerge post-treatment due to tumor cell evolution. Integrative, single cell analytical approaches have already proven advantageous in studies characterizing treatment-resistant clones in cancers where pre- and post-treatment patient samples are readily available, such as leukemia. In contrast, little is known about other cancer subtypes like pediatric high grade glioma, a class of heterogeneous, malignant brain tumors in children that rapidly develop resistance to multiple therapeutic modalities, including chemotherapy, immunotherapy, and radiation. Leveraging single cell multi-omic technologies to analyze naïve and therapy-resistant glioma may lead to the discovery of novel strategies to overcome treatment resistance in brain tumors with dismal clinical outcomes. In this review, we explore the potential for single cell multi-omic analyses to reveal mechanisms of glioma resistance to therapy and discuss opportunities to apply these approaches to improve long-term therapeutic response in pediatric high grade glioma and other brain tumors with limited treatment options.

Investigating cellular heterogeneity at the single-cell level by the flexible and mobile extrachromosomal circular DNA

Extrachromosomal circular DNA (eccDNA) is a special class of DNA derived from linear chromosomes. It coexists independently with linear chromosomes in the nucleus. eccDNA has been identified in multiple organisms, including Homo sapiens, and has been shown to play important roles relevant to tumor progression and drug resistance. To date, computational tools developed for eccDNA detection are only applicable to bulk tissue. Investigating eccDNA at the single-cell level using a computational approach will elucidate the heterogeneous and cell-type-specific landscape of eccDNA within cellular context. Here, we performed the first eccDNA analysis at the single-cell level using data generated by single-cell Assay for Transposase-Accessible Chromatin with sequencing (scATAC-seq) in adult and pediatric glioblastoma (GBM) samples. Glioblastoma multiforme (GBM) is an aggressive tumor of the central nervous system with a poor prognosis. Our analysis provides an overview of cellular origins, genomic distribution, as well as the differential regulations between linear and circular genome under disease- and cell-type-specific conditions across the open chromatin regions in GBM. We focused on some eccDNA elements that are potential mobile enhancers acting in a trans-regulation manner. In summary, this pilot study revealed novel eccDNA features in the cellular context of brain tumor, supporting the strong need for eccDNA investigation at the single-cell level.

Utility of the Cerebral Organoid Glioma 'GLICO' Model for Screening Applications

Glioblastoma, a grade IV astrocytoma, is regarded as the most aggressive primary brain tumour with an overall median survival of 16.0 months following the standard treatment regimen of surgical resection, followed by radiotherapy and chemotherapy with temozolomide. Despite such intensive treatment, the tumour almost invariably recurs. This poor prognosis has most commonly been attributed to the initiation, propagation, and differentiation of cancer stem cells. Despite the unprecedented advances in biomedical research over the last decade, the current in vitro models are limited at preserving the inter- and intra-tumoural heterogeneity of primary tumours. The ability to understand and manipulate complex cancers such as glioblastoma requires disease models to be clinically and translationally relevant and encompass the cellular heterogeneity of such cancers. Therefore, brain cancer research models need to aim to recapitulate glioblastoma stem cell function, whilst remaining amenable for analysis. Fortunately, the recent development of 3D cultures has overcome some of these challenges, and cerebral organoids are emerging as cutting-edge tools in glioblastoma research. The opportunity to generate cerebral organoids via induced pluripotent stem cells, and to perform co-cultures with patient-derived cancer stem cells (GLICO model), has enabled the analysis of cancer development in a context that better mimics brain tissue architecture. In this article, we review the recent literature on the use of patient-derived glioblastoma organoid models and their applicability for drug screening, as well as provide a potential workflow for screening using the GLICO model. The proposed workflow is practical for use in most laboratories with accessible materials and equipment, a good first pass, and no animal work required. This workflow is also amenable for analysis, with separate measures of invasion, growth, and viability.

scAB detects multiresolution cell states with clinical significance by integrating single-cell genomics and bulk sequencing data

Although single-cell sequencing has provided a powerful tool to deconvolute cellular heterogeneity of diseases like cancer, extrapolating clinical significance or identifying clinically-relevant cells remains challenging. Here, we propose a novel computational method scAB, which integrates single-cell genomics data with clinically annotated bulk sequencing data via a knowledge- and graph-guided matrix factorization model. Once combined, scAB provides a coarse- and fine-grain multiresolution perspective of phenotype-associated cell states and prognostic signatures previously not visible by single-cell genomics. We use scAB to enhance live cancer single-cell RNA-seq data, identifying clinically-relevant previously unrecognized cancer and stromal cell subsets whose signatures show a stronger poor-survival association. The identified fine-grain cell subsets are associated with distinct cancer hallmarks and prognosis power. Furthermore, scAB demonstrates its utility as a biomarker identification tool, with the ability to predict immunotherapy, drug responses and survival when applied to melanoma single-cell RNA-seq datasets and glioma single-cell ATAC-seq datasets. Across multiple single-cell and bulk datasets from different cancer types, we also demonstrate the superior performance of scAB in generating prognosis signatures and survival predictions over existing models. Overall, scAB provides an efficient tool for prioritizing clinically-relevant cell subsets and predictive signatures, utilizing large publicly available databases to improve prognosis and treatments.

Systematic analysis of the effects of genetic variants on chromatin accessibility to decipher functional variants in non-coding regions

Genome-wide association study (GWAS) has identified thousands of single nucleotide polymorphisms (SNPs) associated with complex diseases and traits. However, deciphering the functions of these SNPs still faces challenges. Recent studies have shown that SNPs could alter chromatin accessibility and result in differences in tumor susceptibility between individuals. Therefore, systematically analyzing the effects of SNPs on chromatin accessibility could help decipher the functions of SNPs, especially those in non-coding regions. Using data from The Cancer Genome Atlas (TCGA), chromatin accessibility quantitative trait locus (caQTL) analysis was conducted to estimate the associations between genetic variants and chromatin accessibility. We analyzed caQTLs in 23 human cancer types and identified 9,478 caQTLs in breast carcinoma (BRCA). In BRCA, these caQTLs tend to alter the binding affinity of transcription factors, and open chromatin regions regulated by these caQTLs are enriched in regulatory elements. By integrating with eQTL data, we identified 141 caQTLs showing a strong signal for colocalization with eQTLs. We also identified 173 caQTLs in genome-wide association studies (GWAS) loci and inferred several possible target genes of these caQTLs. By performing survival analysis, we found that ~10% caQTLs potentially influence the prognosis of patients. To facilitate access to relevant data, we developed a user-friendly data portal, BCaQTL (http://gong_lab.hzau.edu.cn/caqtl_database), for data searching and downloading. Our work may facilitate fine-map regulatory mechanisms underlying risk loci of cancer and discover the biomarkers or therapeutic targets for cancer prognosis. The BCaQTL database will be an important resource for genetic and epigenetic studies.

Roles of Chromatin Remodelling and Molecular Heterogeneity in Therapy Resistance in Glioblastoma

Simple Summary

We review the role of chromatin and epigenetic dysregulation in therapy resistance in glioblastoma. We discuss how epigenetic and genetic forces may cooperate to programme functional cell states that are inherently resistant to therapy. Targeting epigenetic factors that are dysregulated in this malignancy could, therefore, improve clinical outcomes for patients. We highlight some preclinical and clinical compounds that were tested or are currently being explored for glioblastoma. Lastly, we present our thoughts on the requirements for the development of next-generation epigenetic therapies.

Abstract

Cancer stem cells (CSCs) represent a therapy-resistant reservoir in glioblastoma (GBM). It is now becoming clear that epigenetic and chromatin remodelling programs link the stemlike behaviour of CSCs to their treatment resistance. New evidence indicates that the epigenome of GBM cells is shaped by intrinsic and extrinsic factors, including their genetic makeup, their interactions and communication with other neoplastic and non-neoplastic cells, including immune cells, and their metabolic niche. In this review, we explore how all these factors contribute to epigenomic heterogeneity in a tumour and the selection of therapy-resistant cells. Lastly, we discuss current and emerging experimental platforms aimed at precisely understanding the epigenetic mechanisms of therapy resistance that ultimately lead to tumour relapse. Given the growing arsenal of drugs that target epigenetic enzymes, our review addresses promising preclinical and clinical applications of epidrugs to treat GBM, and possible mechanisms of resistance that need to be overcome.

Characterizing the biology of primary brain tumors and their microenvironment via single-cell profiling methods

Genomic and transcriptional heterogeneity is prevalent among the most common and aggressive primary brain tumors in children and adults. Over the past 20 years, advances in bioengineering, biochemistry and bioinformatics have enabled the development of an array of techniques to study tumor biology at single-cell resolution. The application of these techniques to study primary brain tumors has helped advance our understanding of their intra-tumoral heterogeneity and uncover new insights regarding their co-option of developmental programs and signaling from their microenvironment to promote tumor proliferation and invasion. These insights are currently being harnessed to develop new therapeutic approaches. Here we provide an overview of current single-cell techniques and discuss relevant biology and therapeutic insights uncovered by their application to primary brain tumors in children and adults.

Exploring glioblastoma stem cell heterogeneity: Immune microenvironment modulation and therapeutic opportunities

Despite its growing use in cancer treatment, immunotherapy has been virtually ineffective in clinical trials for gliomas. The inherently cold tumor immune microenvironment (TIME) in gliomas, characterized by a high ratio of pro-tumor to anti-tumor immune cell infiltrates, acts as a seemingly insurmountable barrier to immunotherapy. Glioma stem cells (GSCs) within these tumors are key contributors to this cold TIME, often functioning indirectly through activation and recruitment of pro-tumor immune cell types. Furthermore, drivers of GSC plasticity and heterogeneity (e.g., reprogramming transcription factors, epigenetic modifications) are associated with induction of immunosuppressive cell states. Recent studies have identified GSC-intrinsic mechanisms, including functional mimicry of immune suppressive cell types, as key determinants of anti-tumor immune escape. In this review, we cover recent advancements in our understanding of GSC-intrinsic mechanisms that modulate GSC-TIME interactions and discuss cutting-edge techniques and bioinformatics platforms available to study immune modulation at high cellular resolution with exploration of both malignant (i.e., GSC) and non-malignant (i.e., immune) cell fractions. Finally, we provide insight into the therapeutic opportunities for targeting immunomodulatory GSC-intrinsic mechanisms to potentiate immunotherapy response in gliomas.

Brain cancer stem cells: resilience through adaptive plasticity and hierarchical heterogeneity

Malignant brain tumours are complex ecosystems containing neoplastic and stromal components that generate adaptive and evolutionarily driven aberrant tissues in the central nervous system. Brain cancers are cultivated by a dynamic population of stem-like cells that enforce intratumoural heterogeneity and respond to intrinsic microenvironment or therapeutically guided insults through proliferation, plasticity and restructuring of neoplastic and stromal components. Far from a rigid hierarchy, heterogeneous neoplastic populations transition between cellular states with differential self-renewal capacities, endowing them with powerful resilience. Here we review the biological machinery used by brain tumour stem cells to commandeer tissues in the intracranial space, evade immune responses and resist chemoradiotherapy. Through recent advances in single-cell sequencing, improved models to investigate the role of the tumour microenvironment and a deeper understanding of the fundamental role of the immune system in cancer biology, we are now better equipped to explore mechanisms by which these processes can be exploited for therapeutic benefit.

Single cell cancer epigenetics

Bulk sequencing methodologies have allowed us to make great progress in cancer research. Unfortunately, these techniques lack the resolution to fully unravel the epigenetic mechanisms that govern tumor heterogeneity. Consequently, many novel single cell-sequencing methodologies have been developed over the past decade, allowing us to explore the epigenetic components that regulate different aspects of cancer heterogeneity, namely: clonal heterogeneity, tumor microenvironment (TME), spatial organization, intratumoral differentiation programs, metastasis, and resistance mechanisms. In this review, we explore the different sequencing techniques that enable researchers to study different aspects of epigenetics (DNA methylation, chromatin accessibility, histone modifications, DNA-protein interactions, and chromatin 3D architecture) at the single cell level, their potential applications in cancer, and their current technical limitations.

Integrative multi-omics approach to targeted therapy for glioblastoma

This review describes recent technological advances applied to glioblastoma (GBM), a brain tumor with dismal prognosis. International consortial efforts suggest the presence of molecular subtypes within histologically identical GBM tumors. This emphasizes that future treatment decisions should no longer be made based solely on morphological analyses, but must now take into consideration such molecular and cellular heterogeneity. The use of single-cell technologies has advanced our understanding and assignation of functional subtypes revealing therapeutic vulnerabilities. Our team has developed stratification approaches in the past few years, and we have been able to identify patient cohorts enriched for various signaling pathways. Importantly, our Glioportal brain tumor resource has been established under the National Neuroscience Institute Tissue Bank in 2021. This resource offers preclinical capability to validate working hypotheses established from patient clinical datasets. This review highlights recent developments with the ultimate goal of assigning functional meaning to molecular subtypes, revealing therapeutic vulnerabilities.

Cell-lineage controlled epigenetic regulation in glioblastoma stem cells determines functionally distinct subgroups and predicts patient survival

There is ample support for developmental regulation of glioblastoma stem cells. To examine how cell lineage controls glioblastoma stem cell function, we present a cross-species epigenome analysis of mouse and human glioblastoma stem cells. We analyze and compare the chromatin-accessibility landscape of nine mouse glioblastoma stem cell cultures of three defined origins and 60 patient-derived glioblastoma stem cell cultures by assay for transposase-accessible chromatin using sequencing. This separates the mouse cultures according to cell of origin and identifies three human glioblastoma stem cell clusters that show overlapping characteristics with each of the mouse groups, and a distribution along an axis of proneural to mesenchymal phenotypes. The epigenetic-based human glioblastoma stem cell clusters display distinct functional properties and can separate patient survival. Cross-species analyses reveals conserved epigenetic regulation of mouse and human glioblastoma stem cells. We conclude that epigenetic control of glioblastoma stem cells primarily is dictated by developmental origin which impacts clinically relevant glioblastoma stem cell properties and patient survival.

The epigenetic regulation of glioblastoma stem cell (GSC) function remains poorly understood. Here, the authors compare the chromatin accessibility landscape of GSC cultures from mice and patients and suggest that the epigenome of GSCs is cell lineage-regulated and could predict patient survival.

Cancer cell heterogeneity and plasticity: A paradigm shift in glioblastoma

Phenotypic plasticity has emerged as a major contributor to intra-tumoral heterogeneity and treatment resistance in cancer. Increasing evidence shows that glioblastoma (GBM) cells display prominent intrinsic plasticity and reversibly adapt to dynamic microenvironmental conditions. Limited genetic evolution at recurrence further suggests that resistance mechanisms also largely operate at the phenotypic level. Here we review recent literature underpinning the role of GBM plasticity in creating gradients of heterogeneous cells including those that carry cancer stem cell (CSC) properties. A historical perspective from the hierarchical to the nonhierarchical concept of CSCs towards the recent appreciation of GBM plasticity is provided. Cellular states interact dynamically with each other and with the surrounding brain to shape a flexible tumor ecosystem, which enables swift adaptation to external pressure including treatment. We present the key components regulating intra-tumoral phenotypic heterogeneity and the equilibrium of phenotypic states, including genetic, epigenetic, and microenvironmental factors. We further discuss plasticity in the context of intrinsic tumor resistance, where a variable balance between preexisting resistant cells and adaptive persisters leads to reversible adaptation upon treatment. Innovative efforts targeting regulators of plasticity and mechanisms of state transitions towards treatment-resistant states are needed to restrict the adaptive capacities of GBM.

Glial and myeloid heterogeneity in the brain tumour microenvironment

Brain cancers carry bleak prognoses, with therapeutic advances helping only a minority of patients over the past decade. The brain tumour microenvironment (TME) is highly immunosuppressive and differs from that of other malignancies as a result of the glial, neural and immune cell populations that constitute it. Until recently, the study of the brain TME was limited by the lack of methods to de-convolute this complex system at the single-cell level. However, novel technical approaches have begun to reveal the immunosuppressive and tumour-promoting properties of distinct glial and myeloid cell populations in the TME, identifying new therapeutic opportunities. Here, we discuss the immune modulatory functions of microglia, monocyte-derived macrophages and astrocytes in brain metastases and glioma, highlighting their disease-associated heterogeneity and drawing from the insights gained by studying these malignancies and other neurological disorders. Lastly, we consider potential approaches for the therapeutic modulation of the brain TME.

Epigenetic encoding, heritability and plasticity of glioma transcriptional cell states

Single-cell RNA sequencing has revealed extensive transcriptional cell state diversity in cancer, often observed independently of genetic heterogeneity, raising the central question of how malignant cell states are encoded epigenetically. To address this, here we performed multiomics single-cell profiling-integrating DNA methylation, transcriptome and genotype within the same cells-of diffuse gliomas, tumors characterized by defined transcriptional cell state diversity. Direct comparison of the epigenetic profiles of distinct cell states revealed key switches for state transitions recapitulating neurodevelopmental trajectories and highlighted dysregulated epigenetic mechanisms underlying gliomagenesis. We further developed a quantitative framework to directly measure cell state heritability and transition dynamics based on high-resolution lineage trees in human samples. We demonstrated heritability of malignant cell states, with key differences in hierarchal and plastic cell state architectures in IDH-mutant glioma versus IDH-wild-type glioblastoma, respectively. This work provides a framework anchoring transcriptional cancer cell states in their epigenetic encoding, inheritance and transition dynamics.

Cancer cell states and emergent properties of the dynamic tumor system

Phenotypic heterogeneity within malignant cells of a tumor is emerging as a key property of tumorigenesis. Recent work using single-cell transcriptomics has led to the identification of distinct cancer cell states across a range of cancer types, but their functional relevance and the advantage that they provide to the tumor as a system remain elusive. We present here a definition of cancer cell states in terms of coherently and differentially expressed gene modules and review the origins, dynamics, and impact of states on the tumor system as a whole. The spectrum of cell states taken on by a malignant population may depend on cellular lineage, epigenetic history, genetic mutations, or environmental cues, which has implications for the relative stability or plasticity of individual states. Finally, evidence has emerged that malignant cells in different states may cooperate or compete within a tumor niche, thereby providing an evolutionary advantage to the tumor through increased immune evasion, drug resistance, or invasiveness. Uncovering the mechanisms that govern the origin and dynamics of cancer cell states in tumorigenesis may shed light on how heterogeneity contributes to tumor fitness and highlight vulnerabilities that can be exploited for therapy.

Deregulation of Transcriptional Enhancers in Cancer

Simple Summary

One of the major challenges in cancer treatments is the dynamic adaptation of tumor cells to cancer therapies. In this regard, tumor cells can modify their response to environmental cues without altering their DNA sequence. This cell plasticity enables cells to undergo morphological and functional changes, for example, during the process of tumour metastasis or when acquiring resistance to cancer therapies. Central to cell plasticity, are the dynamic changes in gene expression that are controlled by a set of molecular switches called enhancers. Enhancers are DNA elements that determine when, where and to what extent genes should be switched on and off. Thus, defects in enhancer function can disrupt the gene expression program and can lead to tumour formation. Here, we review how enhancers control the activity of cancer-associated genes and how defects in these regulatory elements contribute to cell plasticity in cancer. Understanding enhancer (de)regulation can provide new strategies for modulating cell plasticity in tumour cells and can open new research avenues for cancer therapy.

Abstract

Epigenetic regulations can shape a cell’s identity by reversible modifications of the chromatin that ultimately control gene expression in response to internal and external cues. In this review, we first discuss the concept of cell plasticity in cancer, a process that is directly controlled by epigenetic mechanisms, with a particular focus on transcriptional enhancers as the cornerstone of epigenetic regulation. In the second part, we discuss mechanisms of enhancer deregulation in adult stem cells and epithelial-to-mesenchymal transition (EMT), as two paradigms of cell plasticity that are dependent on epigenetic regulation and serve as major sources of tumour heterogeneity. Finally, we review how genetic variations at enhancers and their epigenetic modifiers contribute to tumourigenesis, and we highlight examples of cancer drugs that target epigenetic modifications at enhancers.

Exploiting Single-Cell Tools in Gene and Cell Therapy

Single-cell molecular tools have been developed at an incredible pace over the last five years as sequencing costs continue to drop and numerous molecular assays have been coupled to sequencing readouts. This rapid period of technological development has facilitated the delineation of individual molecular characteristics including the genome, transcriptome, epigenome, and proteome of individual cells, leading to an unprecedented resolution of the molecular networks governing complex biological systems. The immense power of single-cell molecular screens has been particularly highlighted through work in systems where cellular heterogeneity is a key feature, such as stem cell biology, immunology, and tumor cell biology. Single-cell-omics technologies have already contributed to the identification of novel disease biomarkers, cellular subsets, therapeutic targets and diagnostics, many of which would have been undetectable by bulk sequencing approaches. More recently, efforts to integrate single-cell multi-omics with single cell functional output and/or physical location have been challenging but have led to substantial advances. Perhaps most excitingly, there are emerging opportunities to reach beyond the description of static cellular states with recent advances in modulation of cells through CRISPR technology, in particular with the development of base editors which greatly raises the prospect of cell and gene therapies. In this review, we provide a brief overview of emerging single-cell technologies and discuss current developments in integrating single-cell molecular screens and performing single-cell multi-omics for clinical applications. We also discuss how single-cell molecular assays can be usefully combined with functional data to unpick the mechanism of cellular decision-making. Finally, we reflect upon the introduction of spatial transcriptomics and proteomics, its complementary role with single-cell RNA sequencing (scRNA-seq) and potential application in cellular and gene therapy.

A Systems Approach to Brain Tumor Treatment

Brain tumors are among the most lethal tumors. Glioblastoma, the most frequent primary brain tumor in adults, has a median survival time of approximately 15 months after diagnosis or a five-year survival rate of 10%; the recurrence rate is nearly 90%. Unfortunately, this prognosis has not improved for several decades. The lack of progress in the treatment of brain tumors has been attributed to their high rate of primary therapy resistance. Challenges such as pronounced inter-patient variability, intratumoral heterogeneity, and drug delivery across the blood-brain barrier hinder progress. A comprehensive, multiscale understanding of the disease, from the molecular to the whole tumor level, is needed to address the intratumor heterogeneity resulting from the coexistence of a diversity of neoplastic and non-neoplastic cell types in the tumor tissue. By contrast, inter-patient variability must be addressed by subtyping brain tumors to stratify patients and identify the best-matched drug(s) and therapies for a particular patient or cohort of patients. Accomplishing these diverse tasks will require a new framework, one involving a systems perspective in assessing the immense complexity of brain tumors. This would in turn entail a shift in how clinical medicine interfaces with the rapidly advancing high-throughput (HTP) technologies that have enabled the omics-scale profiling of molecular features of brain tumors from the single-cell to the tissue level. However, several gaps must be closed before such a framework can fulfill the promise of precision and personalized medicine for brain tumors. Ultimately, the goal is to integrate seamlessly multiscale systems analyses of patient tumors and clinical medicine. Accomplishing this goal would facilitate the rational design of therapeutic strategies matched to the characteristics of patients and their tumors. Here, we discuss some of the technologies, methodologies, and computational tools that will facilitate the realization of this vision to practice.

From sorting to sequencing in the molecular era: the evolution of the cancer stem cell model in medulloblastoma

The cancer stem cell (CSC) model posits that tumors contain subpopulations that display defining features of normal stem cells including self-renewal capacity and differentiation. Tumor cells exhibiting these features are now considered to be responsible for tumor propagation and drug resistance in a wide variety of cancers. Therefore, the identification of robust CSC markers and characterization of CSC-specific molecular signatures may lead to the identification of novel therapeutics that selectively abolish this clinically relevant cell population while preserving normal tissue. Brain tumor researchers have been at the forefront of the CSC field. From initial in vitro cell sorting experiments to the sophisticated bioinformatic technologies that now exquisitely resolve primary brain tumors at a single-cell level, recent glioma and medulloblastoma (MB) studies have integrated developmental state with genomic and transcriptome data to identify the spectrum of cell types that may drive tumor progression. This review will examine the last two decades of CSC studies in the field. Seminal discoveries, emerging controversies, and outstanding questions will be covered with a particular focus on MB, the most common malignant primary brain tumor in children.