Single-cell transcriptome analysis of lineage diversity in high-grade glioma

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.

Neural network learning defines glioblastoma features to be of neural crest perivascular or radial glia lineages

Glioblastoma is believed to originate from nervous system cells; however, a putative origin from vessel-associated progenitor cells has not been considered. We deeply single-cell RNA-sequenced glioblastoma progenitor cells of 18 patients and integrated 710 bulk tumors and 73,495 glioma single cells of 100 patients to determine the relation of glioblastoma cells to normal brain cell types. A novel neural network-based projection of the developmental trajectory of normal brain cells uncovered two principal cell-lineage features of glioblastoma, neural crest perivascular and radial glia, carrying defining methylation patterns and survival differences. Consistently, introducing tumorigenic alterations in naïve human brain perivascular cells resulted in brain tumors. Thus, our results suggest that glioblastoma can arise from the brains' vasculature, and patients with such glioblastoma have a significantly poorer outcome.

Glioma progression is shaped by genetic evolution and microenvironment interactions

The factors driving therapy resistance in diffuse glioma remain poorly understood. To identify treatment-associated cellular and genetic changes, we analyzed RNA and/or DNA sequencing data from the temporally separated tumor pairs of 304 adult patients with isocitrate dehydrogenase (IDH)-wild-type and IDH-mutant glioma. Tumors recurred in distinct manners that were dependent on IDH mutation status and attributable to changes in histological feature composition, somatic alterations, and microenvironment interactions. Hypermutation and acquired CDKN2A deletions were associated with an increase in proliferating neoplastic cells at recurrence in both glioma subtypes, reflecting active tumor growth. IDH-wild-type tumors were more invasive at recurrence, and their neoplastic cells exhibited increased expression of neuronal signaling programs that reflected a possible role for neuronal interactions in promoting glioma progression. Mesenchymal transition was associated with the presence of a myeloid cell state defined by specific ligand-receptor interactions with neoplastic cells. Collectively, these recurrence-associated phenotypes represent potential targets to alter disease progression.

Single-Cell Transcriptomics Revealed Subtype-Specific Tumor Immune Microenvironments in Human Glioblastomas

Human glioblastoma (GBM), the most aggressive brain tumor, comprises six major subtypes of malignant cells, giving rise to both inter-patient and intra-tumor heterogeneity. The interaction between different tumor subtypes and non-malignant cells to collectively shape a tumor microenvironment has not been systematically characterized. Herein, we sampled the cellular milieu of surgically resected primary tumors from 7 GBM patients using single-cell transcriptome sequencing. A lineage relationship analysis revealed that a neural-progenitor-2-like (NPC2-like) state with high metabolic activity was associated with the tumor cells of origin. Mesenchymal-1-like (MES1-like) and mesenchymal-2-like (MES2-like) tumor cells correlated strongly with immune infiltration and chronic hypoxia niche responses. We identified four subsets of tumor-associated macrophages/microglia (TAMs), among which TAM-1 co-opted both acute and chronic hypoxia-response signatures, implicated in tumor angiogenesis, invasion, and poor prognosis. MES-like GBM cells expressed the highest number of M2-promoting ligands compared to other cellular states while all six states were associated with TAM M2-type polarization and immunosuppression via a set of 10 ligand–receptor signaling pathways. Our results provide new insights into the differential roles of GBM cell subtypes in the tumor immune microenvironment that may be deployed for patient stratification and personalized treatment.

Roles of the m6A Modification of RNA in the Glioblastoma Microenvironment as Revealed by Single-Cell Analyses

Purpose

Glioblastoma multiforme (GBM) is a common and aggressive form of brain tumor. The N⁶-methyladenosine (m⁶A) mRNA modification plays multiple roles in many biological processes and disease states. However, the relationship between m⁶A modifications and the tumor microenvironment in GBM remains unclear, especially at the single-cell level.

Experimental Design

Single-cell and bulk RNA-sequencing data were acquired from the GEO and TCGA databases, respectively. We used bioinformatics and statistical tools to analyze associations between m⁶A regulators and multiple factors.

Results

HNRNPA2B1 and HNRNPC were extensively expressed in the GBM microenvironment. m⁶A regulators promoted the stemness state in GBM cancer cells. Immune-related BP terms were enriched in modules of m⁶A-related genes. Cell communication analysis identified genes in the GALECTIN signaling network in GBM samples, and expression of these genes (LGALS9, CD44, CD45, and HAVCR2) correlated with that of m⁶A regulators. Validation experiments revealed that MDK in MK signaling network promoted migration and immunosuppressive polarization of macrophage. Expression of m⁶A regulators correlated with ICPs in GBM cancer cells, M2 macrophages and T/NK cells. Bulk RNA-seq analysis identified two expression patterns (low m⁶A/high ICP and high m⁶A/low ICP) with different predicted immune infiltration and responses to ICP inhibitors. A predictive nomogram model to distinguish these 2 clusters was constructed and validated with excellent performance.

Conclusion

At the single-cell level, m⁶A modification facilitates the stemness state in GBM cancer cells and promotes an immunosuppressive microenvironment through ICPs and the GALECTIN signaling pathway network. And we also identified two m⁶A-ICP expression patterns. These findings could lead to novel treatment strategies for GBM patients.

MYBL2 accelerates epithelial-mesenchymal transition and hepatoblastoma metastasis via the Smad/SNAI1 pathway

Hepatoblastoma (HB) accounts for the majority of hepatic malignancies in children. Although the prognosis of patients with HB has improved in past decades, metastasis is an indicator of poor overall survival. Herein, we applied single-cell RNA sequencing to explore the transcriptomic profiling of 25,264 metastatic cells isolated from the lungs of two patients with HB. The transcriptomes uncovered the heterogeneity of malignant cells after metastatic lung colonization, and these cells had varied expression signatures associated with the cell cycle, epithelial-mesenchymal plasticity, and hepatic differentiation. Single-cell regulatory network inference and clustering (SCENIC) was utilized to identify the co-expressed transcriptional factors which regulated and represented the different cell states. We further screened the key factor by bioinformatics analysis and found that MYBL2 upregulation was significantly associated with metastasis and poor prognosis. The relationship between ectopic MYBL2 and metastasis was subsequently proved by immunohistochemistry (IHC) of HB tissues, and the functions of MYBL2 in promoting proliferation, migration, and epithelial-to-mesenchymal transition (EMT) were verified by in vitro and in vivo assays. Importantly, the levels of Smad2/3 phosphorylation and SNAI1 expression were increased in MYBL2-transfected cells. Consequently, these results indicated that the MYBL2-controlled Smad/SNAI1 pathway induced EMT and promoted HB tumorigenesis and metastasis.

Integrated analysis of single-cell and bulk RNA sequencing data reveals a pan-cancer stemness signature predicting immunotherapy response

BACKGROUND

Although immune checkpoint inhibitor (ICI) is regarded as a breakthrough in cancer therapy, only a limited fraction of patients benefit from it. Cancer stemness can be the potential culprit in ICI resistance, but direct clinical evidence is lacking.

METHODS

Publicly available scRNA-Seq datasets derived from ICI-treated patients were collected and analyzed to elucidate the association between cancer stemness and ICI response. A novel stemness signature (Stem.Sig) was developed and validated using large-scale pan-cancer data, including 34 scRNA-Seq datasets, The Cancer Genome Atlas (TCGA) pan-cancer cohort, and 10 ICI transcriptomic cohorts. The therapeutic value of Stem.Sig genes was further explored using 17 CRISPR datasets that screened potential immunotherapy targets.

RESULTS

Cancer stemness, as evaluated by CytoTRACE, was found to be significantly associated with ICI resistance in melanoma and basal cell carcinoma (both P < 0.001). Significantly negative association was found between Stem.Sig and anti-tumor immunity, while positive correlations were detected between Stem.Sig and intra-tumoral heterogenicity (ITH) / total mutational burden (TMB). Based on this signature, machine learning model predicted ICI response with an AUC of 0.71 in both validation and testing set. Remarkably, compared with previous well-established signatures, Stem.Sig achieved better predictive performance across multiple cancers. Moreover, we generated a gene list ranked by the average effect of each gene to enhance tumor immune response after genetic knockout across different CRISPR datasets. Then we matched Stem.Sig to this gene list and found Stem.Sig significantly enriched 3% top-ranked genes from the list (P = 0.03), including EMC3, BECN1, VPS35, PCBP2, VPS29, PSMF1, GCLC, KXD1, SPRR1B, PTMA, YBX1, CYP27B1, NACA, PPP1CA, TCEB2, PIGC, NR0B2, PEX13, SERF2, and ZBTB43, which were potential therapeutic targets.

CONCLUSIONS

We revealed a robust link between cancer stemness and immunotherapy resistance and developed a promising signature, Stem.Sig, which showed increased performance in comparison to other signatures regarding ICI response prediction. This signature could serve as a competitive tool for patient selection of immunotherapy. Meanwhile, our study potentially paves the way for overcoming immune resistance by targeting stemness-associated genes.

Cell type and gene expression deconvolution with BayesPrism enables Bayesian integrative analysis across bulk and single-cell RNA sequencing in oncology

Inferring single-cell compositions and their contributions to global gene expression changes from bulk RNA sequencing (RNA-seq) datasets is a major challenge in oncology. Here we develop Bayesian cell proportion reconstruction inferred using statistical marginalization (BayesPrism), a Bayesian method to predict cellular composition and gene expression in individual cell types from bulk RNA-seq, using patient-derived, scRNA-seq as prior information. We conduct integrative analyses in primary glioblastoma, head and neck squamous cell carcinoma and skin cutaneous melanoma to correlate cell type composition with clinical outcomes across tumor types, and explore spatial heterogeneity in malignant and nonmalignant cell states. We refine current cancer subtypes using gene expression annotation after exclusion of confounding nonmalignant cells. Finally, we identify genes whose expression in malignant cells correlates with macrophage infiltration, T cells, fibroblasts and endothelial cells across multiple tumor types. Our work introduces a new lens to accurately infer cellular composition and expression in large cohorts of bulk RNA-seq data.

Association of Elevated Expression Levels of COL4A1 in Stromal Cells with an Immunosuppressive Tumor Microenvironment in Low-Grade Glioma, Pancreatic Adenocarcinoma, Skin Cutaneous Melanoma, and Stomach Adenocarcinoma

Aberrant expression of collagen type IV alpha chain 1 (COL4A1) can influence tumor cell behavior. To examine the association of COL4A1 expression in the tumor microenvironment (TME) with tumor progression, we performed bioinformatics analyses of The Cancer Genome Atlas RNA sequencing and RNA microarray datasets available in public databases and identified upregulated COL4A1 expression in most examined tumor types compared to their normal counterparts. The elevated expression of COL4A1 was correlated with low survival rates of patients with low-grade glioma, pancreatic adenocarcinoma, skin cutaneous melanoma, and stomach adenocarcinoma, thus suggesting its potential use as a biomarker for the poor prognosis of these tumors. However, COL4A1 was mostly expressed in adjacent stromal cells, such as cancer-associated fibroblasts (CAFs) and endothelial cells. Additionally, COL4A1 expression was highly correlated with the signatures of CAFs and endothelial cells in all four tumor types. The expression of marker genes for the infiltration of pro-tumoral immune cells, such as Treg, M2, and TAM, and those of immunosuppressive cytokines exhibited very strong positive correlations with COL4A1 expression. Collectively, our data suggest that COL4A1 overexpression in stromal cells may be a potential regulator of tumor-supporting TME composition associated with poor prognosis.

The landscape of receptor-mediated precision cancer combination therapy via a single-cell perspective

Mining a large cohort of single-cell transcriptomics data, here we employ combinatorial optimization techniques to chart the landscape of optimal combination therapies in cancer. We assume that each individual therapy can target any one of 1269 genes encoding cell surface receptors, which may be targets of CAR-T, conjugated antibodies or coated nanoparticle therapies. We find that in most cancer types, personalized combinations composed of at most four targets are then sufficient for killing at least 80% of tumor cells while sparing at least 90% of nontumor cells in the tumor microenvironment. However, as more stringent and selective killing is required, the number of targets needed rises rapidly. Emerging individual targets include PTPRZ1 for brain and head and neck cancers and EGFR in multiple tumor types. In sum, this study provides a computational estimate of the identity and number of targets needed in combination to target cancers selectively and precisely.

Intra-tumor heterogeneity is often associated with resistance to targeted therapy, requiring the design of combinatorial therapies. Here, based on tumor single-cell transcriptomic datasets, the authors develop a computational approach to identify optimal combinatorial treatments targeting membrane receptors for cancer therapy.

CD44-Mediated Poor Prognosis in Glioma Is Associated With M2-Polarization of Tumor-Associated Macrophages and Immunosuppression

Background

Glioma is the most common primary brain tumor with a poor prognosis. Key genes that are negatively related to prognosis may provide the therapy targets to cure glioma. To clarify the role of CD44 in glioma, we explored its function at bulk-transcriptome, spatial and single-cell transcriptome levels.

Methods

In total, expression profiles with survival data of whole-grade glioma from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA), RNA-seq data with anatomic information of glioblastoma (GBM) from the Ivy Glioblastoma Atlas Project, RNA-sequencing (RNA-seq) data from recurrent GBM receiving adjuvant anti-PD-1 immunotherapy accessed through GSE121810, and single-cell RNA-seq data of GBM under accession GSE103224 were enrolled in this study. CD44-specific findings were further analyzed by R language.

Results

CD44 is positively correlated with WHO grade of malignancy and is negatively related to prognosis in glioma. Meanwhile, CD44 predominantly expresses in GBM mesenchymal subtype, and gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses reveal that CD44 positively coexpressed genes are closely related to glioma immunity. Moreover, CD44+ cells mainly distribute in perinecrotic region with high expression of immune factors. At single-cell resolution, only malignant tumor cells, tumor-associated macrophages (TAMs), and T cells express CD44 in GBM. CD44+ malignant tumor cells are in mesenchymal-1-like (MES1-like) cellular state, and CD44+ TAMs are in M2 phenotype. CD44+ T cells have high expression of both PD-1 and PD-L1. CD44 and its directly interacted inhibitory immunomodulators are upregulated in patients with nonresponder recurrent GBM treated with PD-1 blockade therapy.

Conclusion

Our work demonstrates that CD44, a new M2 TAM biomarker, is involved in immune suppressor and promote glioma progression in glioma microenvironment. These results expand our understanding of CD44-specific clinical and immune features in glioma.

Single cell RNA sequencing reveals differentiation related genes with drawing implications in predicting prognosis and immunotherapy response in gliomas

Differentiation states of glioma cells correlated with prognosis and tumor-immune microenvironment (TIME) in patients with gliomas. We aimed to identify differentiation related genes (DRGs) for predicting the prognosis and immunotherapy response in patients with gliomas. We identified three differentiation states and the corresponding DRGs in glioma cells through single-cell transcriptomics analysis. Based on the DRGs, we separated glioma patients into three clusters with distinct clinicopathological features in combination with bulk RNA-seq data. Weighted correlation network analysis, univariate cox regression analysis and least absolute shrinkage and selection operator analysis were involved in the construction of the prognostic model based on DRGs. Distinct clinicopathological characteristics, TIME, immunogenomic patterns and immunotherapy responses were identified across three clusters. A DRG signature composing of 12 genes were identified for predicting the survival of glioma patients and nomogram model integrating the risk score and multi-clinicopathological factors were constructed for clinical practice. Patients in high-risk group tended to get shorter overall survival and better response to immune checkpoint blockage therapy. We obtained 9 candidate drugs through comprehensive analysis of the differentially expressed genes between the low and high-risk groups in the model. Our findings indicated that the risk score may not only contribute to the determination of prognosis but also facilitate in the prediction of immunotherapy response in glioma patients.

Quiescent human glioblastoma cancer stem cells drive tumor initiation, expansion, and recurrence following chemotherapy

We test the hypothesis that glioblastoma harbors quiescent cancer stem cells that evade anti-proliferative therapies. Functional characterization of spontaneous glioblastomas from genetically engineered mice reveals essential quiescent stem-like cells that can be directly isolated from tumors. A derived quiescent cancer-stem-cell-specific gene expression signature is enriched in pre-formed patient GBM xenograft single-cell clusters that lack proliferative gene expression. A refined human 118-gene signature is preserved in quiescent single-cell populations from primary and recurrent human glioblastomas. The F3 cell-surface receptor mRNA, expressed in the conserved signature, identifies quiescent tumor cells by antibody immunohistochemistry. F3-antibody-sorted glioblastoma cells exhibit stem cell gene expression, enhance self-renewal in culture, drive tumor initiation and serial transplantation, and reconstitute tumor heterogeneity. Upon chemotherapy, the spared cancer stem cell pool becomes activated and accelerates transition to proliferation. These results help explain conventional treatment failure and lay a conceptual framework for alternative therapies.

The Eclectic Nature of Glioma-Infiltrating Macrophages and Microglia

Glioblastomas (GBMs) are complex ecosystems composed of highly multifaceted tumor and myeloid cells capable of responding to different environmental pressures, including therapies. Recent studies have uncovered the diverse phenotypical identities of brain-populating myeloid cells. Differences in the immune proportions and phenotypes within tumors seem to be dictated by molecular features of glioma cells. Furthermore, increasing evidence underscores the significance of interactions between myeloid cells and glioma cells that allow them to evolve in a synergistic fashion to sustain tumor growth. In this review, we revisit the current understanding of glioma-infiltrating myeloid cells and their dialogue with tumor cells in consideration of their increasing recognition in response and resistance to immunotherapies as well as the immune impact of the current chemoradiotherapy used to treat gliomas.

Unravelling glioblastoma heterogeneity by means of single-cell RNA sequencing

Glioblastoma (GBM) is the most invasive and deadliest brain cancer in adults. Its inherent heterogeneity has been designated as the main cause of treatment failure. Thus, a deeper understanding of the diversity that shapes GBM pathobiology is of utmost importance. Single-cell RNA sequencing (scRNA-seq) technologies have begun to uncover the hidden composition of complex tumor ecosystems. Herein, a semi-systematic search of reference literature databases provided all existing publications using scRNA-seq for the investigation of human GBM. We compared and discussed findings from these works to build a more robust and unified knowledge base. All aspects ranging from inter-patient heterogeneity to intra-tumoral organization, cancer stem cell diversity, clonal mosaicism, and the tumor microenvironment (TME) are comprehensively covered in this report. Tumor composition not only differs across patients but also involves a great extent of heterogeneity within itself. Spatial and cellular heterogeneity can reveal tumor evolution dynamics. In addition, the discovery of distinct cell phenotypes might lead to the development of targeted treatment approaches. In conclusion, scRNA-seq expands our knowledge of GBM heterogeneity and helps to unravel putative therapeutic targets.

ERK1/2 phosphorylation predicts survival following anti-PD-1 immunotherapy in recurrent glioblastoma

Only a subset of recurrent glioblastoma (rGBM) responds to anti-PD-1 immunotherapy. Previously, we reported enrichment of BRAF/PTPN11 mutations in 30% of rGBM that responded to PD-1 blockade. Given that BRAF and PTPN11 promote MAPK/ERK signaling, we investigated whether activation of this pathway is associated with response to PD-1 inhibitors in rGBM, including patients that do not harbor BRAF/PTPN11 mutations. Here we show that immunohistochemistry for ERK1/2 phosphorylation (p-ERK), a marker of MAPK/ERK pathway activation, is predictive of overall survival following adjuvant PD-1 blockade in two independent rGBM patient cohorts. Single-cell RNA-sequencing and multiplex immunofluorescence analyses revealed that p-ERK was mainly localized in tumor cells and that high-p-ERK GBMs contained tumor-infiltrating myeloid cells and microglia with elevated expression of MHC class II and associated genes. These findings indicate that ERK1/2 activation in rGBM is predictive of response to PD-1 blockade and is associated with a distinct myeloid cell phenotype.

Lentiviral-Induced Spinal Cord Gliomas in Rat Model

Intramedullary spinal cord tumors are a rare and understudied cancer with poor treatment options and prognosis. Our prior study used a combination of PDGF-B, HRAS, and p53 knockdown to induce the development of high-grade glioma in the spinal cords of minipigs. In this study, we evaluate the ability of each vector alone and combinations of vectors to produce high-grade spinal cord gliomas. Eight groups of rats (n = 8/group) underwent thoracolumbar laminectomy and injection of lentiviral vector in the lateral white matter of the spinal cord. Each group received a different combination of lentiviral vectors expressing PDGF-B, a constitutively active HRAS mutant, or shRNA targeting p53, or a control vector. All animals were monitored once per week for clinical deficits for 98 days. Tissues were harvested and analyzed using hematoxylin and eosin (H&E) and immunohistochemical (IHC) staining. Rats injected with PDGF-B+HRAS+sh-p53 (triple cocktail) exhibited statistically significant declines in all behavioral measures (Basso Beattie Bresnahan scoring, Tarlov scoring, weight, and survival rate) over time when compared to the control. Histologically, all groups except the control and those injected with sh-p53 displayed the development of tumors at the injection site, although there were differences in the rate of tumor growth and the histopathological features of the lesions between groups. Examination of immunohistochemistry revealed rats receiving triple cocktail displayed the largest and most significant increase in the Ki67 proliferation index and GFAP positivity than any other group. PDGF-B+HRAS also displayed a significant increase in the Ki67 proliferation index. Rats receiving PDGF-B alone and PDGF-B+ sh-p53 displayed more a significant increase in SOX2-positive staining than in any other group. We found that different vector combinations produced differing high-grade glioma models in rodents. The combination of all three vectors produced a model of high-grade glioma more efficiently and aggressively with respect to behavioral, physiological, and histological characteristics than the rest of the vector combinations. Thus, the present rat model of spinal cord glioma may potentially be used to evaluate therapeutic strategies in the future.

Protein kinase Cι and SRC signaling define reciprocally related subgroups of glioblastoma with distinct therapeutic vulnerabilities

We report that atypical protein kinase Cι (PKCι) is an oncogenic driver of glioblastoma (GBM). Deletion or inhibition of PKCι significantly impairs tumor growth and prolongs survival in murine GBM models. GBM cells expressing elevated PKCι signaling are sensitive to PKCι inhibitors, whereas those expressing low PKCι signaling exhibit active SRC signaling and sensitivity to SRC inhibitors. Resistance to the PKCι inhibitor auranofin is associated with activated SRC signaling and response to a SRC inhibitor, whereas resistance to a SRC inhibitor is associated with activated PKCι signaling and sensitivity to auranofin. Interestingly, PKCι- and SRC-dependent cells often co-exist in individual GBM tumors, and treatment of GBM-bearing mice with combined auranofin and SRC inhibitor prolongs survival beyond either drug alone. Thus, we identify PKCι and SRC signaling as distinct therapeutic vulnerabilities that are directly translatable into an improved treatment for GBM.

Competitive binding of E3 ligases TRIM26 and WWP2 controls SOX2 in glioblastoma

The pluripotency transcription factor SOX2 is essential for the maintenance of glioblastoma stem cells (GSC), which are thought to underlie tumor growth, treatment resistance, and recurrence. To understand how SOX2 is regulated in GSCs, we utilized a proteomic approach and identified the E3 ubiquitin ligase TRIM26 as a direct SOX2-interacting protein. Unexpectedly, we found TRIM26 depletion decreased SOX2 protein levels and increased SOX2 polyubiquitination in patient-derived GSCs, suggesting TRIM26 promotes SOX2 protein stability. Accordingly, TRIM26 knockdown disrupted the SOX2 gene network and inhibited both self-renewal capacity as well as in vivo tumorigenicity in multiple GSC lines. Mechanistically, we found TRIM26, via its C-terminal PRYSPRY domain, but independent of its RING domain, stabilizes SOX2 protein by directly inhibiting the interaction of SOX2 with WWP2, which we identify as a bona fide SOX2 E3 ligase in GSCs. Our work identifies E3 ligase competition as a critical mechanism of SOX2 regulation, with functional consequences for GSC identity and maintenance.

SOX2 is required for the maintenance of glioblastoma stem cells (GSCs). Here the authors identify that the RING family E3 ubiquitin ligase TRIM26 promotes SOX2 stability in a non-canonical ligase-independent manner and thus, increases the tumorigenicity of GSCs.

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

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

CancerSCEM: a database of single-cell expression map across various human cancers

With the proliferating studies of human cancers by single-cell RNA sequencing technique (scRNA-seq), cellular heterogeneity, immune landscape and pathogenesis within diverse cancers have been uncovered successively. The exponential explosion of massive cancer scRNA-seq datasets in the past decade are calling for a burning demand to be integrated and processed for essential investigations in tumor microenvironment of various cancer types. To fill this gap, we developed a database of Cancer Single-cell Expression Map (CancerSCEM, https://ngdc.cncb.ac.cn/cancerscem), particularly focusing on a variety of human cancers. To date, CancerSCE version 1.0 consists of 208 cancer samples across 28 studies and 20 human cancer types. A series of uniformly and multiscale analyses for each sample were performed, including accurate cell type annotation, functional gene expressions, cell interaction network, survival analysis and etc. Plus, we visualized CancerSCEM as a user-friendly web interface for users to browse, search, online analyze and download all the metadata as well as analytical results. More importantly and unprecedentedly, the newly-constructed comprehensive online analyzing platform in CancerSCEM integrates seven analyze functions, where investigators can interactively perform cancer scRNA-seq analyses. In all, CancerSCEM paves an informative and practical way to facilitate human cancer studies, and also provides insights into clinical therapy assessments.

Multiomics Analysis Reveals the Prognostic Non-tumor Cell Landscape in Glioblastoma Niches

A comprehensive characterization of non-tumor cells in the niches of primary glioblastoma is not fully established yet. This study aims to present an overview of non-malignant cells in the complex microenvironment of glioblastoma with detailed characterizations of their prognostic effects. We curate 540 gene signatures covering a total of 64 non-tumor cell types. Cell type-specific expression patterns are interrogated by normalized enrichment score across four large gene expression profiling cohorts of glioblastoma with a total number of 967 cases. The glioblastoma multiforms (GBMs) in each cohort are hierarchically clustered into negative or positive immune response classes with significantly different overall survival. Our results show that astrocytes, macrophages, monocytes, NKTs, and MSC are risk factors, while CD8 T cells, CD8 naive T cells, and plasma cells are protective factors. Moreover, we find that the immune system and organogenesis are uniformly enriched in negative immune response clusters, in contrast to the enrichment of nervous system in positive immune response clusters. Mesenchymal differentiation is also observed in the negative immune response clusters. High enrichment status of macrophages in negative immune response clusters is independently validated by analyzing scRNA-seq data from eight high-grade gliomas, revealing that negative immune response samples comprised 46.63 to 55.12% of macrophages, whereas positive immune response samples comprised only 1.70 to 8.12%, with IHC staining of samples from six short-term and six long-term survivors of GBMs confirming the results.

An integrated pipeline for comprehensive analysis of immune cells in human brain tumor clinical samples

Human tissue samples represent an invaluable source of information for the analysis of disease-specific cellular alterations and their variation between different pathologies. In cancer research, advancing a comprehensive understanding of the unique characteristics of individual tumor types and their microenvironment is of considerable importance for clinical translation. However, investigating human brain tumor tissue is challenging due to the often-limited availability of surgical specimens. Here we describe a multimodule integrated pipeline for the processing of freshly resected human brain tumor tissue and matched blood that enables analysis of the tumor microenvironment, with a particular focus on the tumor immune microenvironment (TIME). The protocol maximizes the information yield from limited tissue and includes both the preservation of bulk tissue, which can be performed within 1 h following surgical resection, as well as tissue dissociation for an in-depth characterization of individual TIME cell populations, which typically takes several hours depending on tissue quantity and further downstream processing. We also describe integrated modules for immunofluorescent staining of sectioned tissue, bulk tissue genomic analysis and fluorescence- or magnetic-activated cell sorting of digested tissue for subsequent culture or transcriptomic analysis by RNA sequencing. Applying this pipeline, we have previously described the overall TIME landscape across different human brain malignancies, and were able to delineate disease-specific alterations of tissue-resident versus recruited macrophage populations. This protocol will enable researchers to use this pipeline to address further research questions regarding the tumor microenvironment.

Single-cell multimodal glioma analyses identify epigenetic regulators of cellular plasticity and environmental stress response

Glioma intratumoral heterogeneity enables adaptation to challenging microenvironments and contributes to therapeutic resistance. We integrated 914 single-cell DNA methylomes, 55,284 single-cell transcriptomes and bulk multi-omic profiles across 11 adult IDH mutant or IDH wild-type gliomas to delineate sources of intratumoral heterogeneity. We showed that local DNA methylation disorder is associated with cell-cell DNA methylation differences, is elevated in more aggressive tumors, links with transcriptional disruption and is altered during the environmental stress response. Glioma cells under in vitro hypoxic and irradiation stress increased local DNA methylation disorder and shifted cell states. We identified a positive association between genetic and epigenetic instability that was supported in bulk longitudinally collected DNA methylation data. Increased DNA methylation disorder associated with accelerated disease progression and recurrently selected DNA methylation changes were enriched for environmental stress response pathways. Our work identified an epigenetically facilitated adaptive stress response process and highlights the importance of epigenetic heterogeneity in shaping therapeutic outcomes.

Glioblastoma Genetic Drivers Dictate the Function of Tumor-Associated Macrophages/Microglia and Responses to CSF1R Inhibition

BACKGROUND

Tumor-associated macrophages/microglia (TAMs) are prominent microenvironment components in human glioblastoma (GBM) that are potential targets for anti-tumor therapy. However, TAM depletion by CSF1R inhibition showed mixed results in clinical trials. We hypothesized that GBM subtype-specific tumor microenvironment convey distinct sensitivities to TAM targeting.

METHODS

We generated syngeneic PDGFB-driven and RAS-driven GBM models that resemble proneural-like and mesenchymal-like gliomas, and determined the effect of TAM targeting by CSF1R inhibitor PLX3397 on glioma growth. We also investigated the co-targeting of TAMs and angiogenesis on PLX3397-resistant RAS-driven GBM. Using single-cell transcriptomic profiling, we further explored differences in tumor microenvironment cellular compositions and functions in PDGFB- and RAS-driven gliomas.

RESULTS

We found that growth of PDGFB-driven tumors was markedly inhibited by PLX3397. In contrast, depletion of TAMs at the early phase accelerated RAS-driven tumor growth and had no effects on other proneural and mesenchymal GBM models. In addition, PLX3397-resistant RAS-driven tumors did not respond to PI3K signaling inhibition. Single-cell transcriptomic profiling revealed that PDGFB-driven gliomas induced expansion and activation of pro-tumor microglia, whereas TAMs in mesenchymal RAS-driven GBM were enriched in pro-inflammatory and angiogenic signaling. Co-targeting of TAMs and angiogenesis decreased cell proliferation and changed the morphology of RAS-driven gliomas.

CONCLUSIONS

Our work identify functionally distinct TAM subpopulations in the growth of different glioma subtypes. Notably, we uncover a potential responsiveness of resistant mesenchymal-like gliomas to combined anti-angiogenic therapy and CSF1R inhibition. These data highlight the importance of characterization of the microenvironment landscape in order to optimally stratify patients for TAM-targeted therapy.

Pro-inflammatory and proliferative microglia drive progression of glioblastoma

Scant understanding of the glioblastoma microenvironment and molecular bases hampers development of efficient treatment strategies. Analyses of gene signatures of human gliomas demonstrate that the SETD2 mutation is correlated with poor prognosis of IDH1/2 wild-type (IDH-WT) adult glioblastoma patients. To better understand the crosstalk between SETD2 mutant (SETD2-mut) glioblastoma cells and the tumor microenvironment, we leverage single-cell transcriptomics to comprehensively map cellular populations in glioblastoma. In this study, we identify a specific subtype of high-grade glioma-associated microglia (HGG-AM). Further analysis shows that transforming growth factor (TGF)-β1 derived from SETD2-mut/IDH-WT tumor cells activates HGG-AM, exhibiting pro-inflammation and proliferation signatures. Particularly, HGG-AM secretes interleukin (IL)-1β via the apolipoprotein E (ApoE)-mediated NLRP1 inflammasome, thereby promoting tumor progression. HGG-AM present extensive proliferation and infiltration to supplement the activated microglia pool. Notably, TGF-β1/TβRI depletion dramatically reduces HGG-AM density and suppresses tumor growth. Altogether, our studies identify a specific microglia subpopulation and establish the cellular basis of interactions between HGG-AM and glioblastoma cells.

Single-Cell Transcriptomics of Glioblastoma Reveals a Unique Tumor Microenvironment and Potential Immunotherapeutic Target Against Tumor-Associated Macrophage

Background

The main immune cells in GBM are tumor-associated macrophages (TAMs). Thus far, the studies investigating the activation status of TAM in GBM are mainly limited to bulk RNA analyses of individual tumor biopsies. The activation states and transcriptional signatures of TAMs in GBM remain poorly characterized.

Methods

We comprehensively analyzed single-cell RNA-sequencing data, covering a total of 16,201 cells, to clarify the relative proportions of the immune cells infiltrating GBMs. The origin and TAM states in GBM were characterized using the expression profiles of differential marker genes. The vital transcription factors were examined by SCENIC analysis. By comparing the variable gene expression patterns in different clusters and cell types, we identified components and characteristics of TAMs unique to each GBM subtype. Meanwhile, we interrogated the correlation between SPI1 expression and macrophage infiltration in the TCGA-GBM dataset.

Results

The expression patterns of TMEM119 and MHC-II can be utilized to distinguish the origin and activation states of TAMs. In TCGA-Mixed tumors, almost all TAMs were bone marrow-derived macrophages. The TAMs in TCGA-proneural tumors were characterized by primed microglia. A different composition was observed in TCGA-classical tumors, which were infiltrated by repressed microglia. Our results further identified SPI1 as a crucial regulon and potential immunotherapeutic target important for TAM maturation and polarization in GBM.

Conclusions

We describe the immune landscape of human GBM at a single-cell level and define a novel categorization scheme for TAMs in GBM. The immunotherapy against SPI1 would reprogram the immune environment of GBM and enhance the treatment effect of conventional chemotherapy drugs.

hiPSC Modeling of Lineage-Specific Smooth Muscle Cell Defects Caused by TGFBR1A230T Variant, and its Therapeutic Implications for Loeys-Dietz Syndrome

Background: Loeys-Dietz Syndrome (LDS) is an inherited disorder predisposing individuals to thoracic aortic aneurysm and dissection (TAAD). Currently, there are no medical treatments except surgical resection. Although the genetic basis of LDS is well-understood, molecular mechanisms underlying the disease remain elusive impeding the development of a therapeutic strategy. In addition, aortic smooth muscle cells (SMC) have heterogenous embryonic origins depending on their spatial location, and lineage-specific effects of pathogenic variants on SMC function, likely causing regionally constrained LDS manifestations, have been unexplored. Methods: We identified an LDS family with a dominant pathogenic variant in TGFBR1 gene (TGFBR1^A230T) causing aortic root aneurysm and dissection. To accurately model the molecular defects caused by this mutation, we used human-induced pluripotent stem cells (hiPSC) from subject with normal aorta to generate hiPSC carrying TGFBR1^A230T, and corrected the mutation in patient-derived hiPSC using CRISPR-Cas9 gene editing. Following their lineage-specific SMC differentiation through cardiovascular progenitor cell (CPC) and neural crest stem cell (NCSC) lineages, we employed conventional molecular techniques and single-cell RNA-sequencing (scRNA-seq) to characterize the molecular defects. The resulting data led to subsequent molecular and functional rescue experiments employing Activin A and rapamycin. Results: Our results indicate the TGFBR1^A230T mutation impairs contractile transcript and protein levels, and function in CPC-SMC, but not in NCSC-SMC. ScRNA-seq results implicate defective differentiation even in TGFBR1^A230T/+ CPC-SMC including disruption of SMC contraction, and extracellular matrix formation. Comparison of patient-derived and mutation-corrected cells supported the contractile phenotype observed in the mutant CPC-SMC. TGFBR1^A230T selectively disrupted SMAD3 and AKT activation in CPC-SMC, and led to increased cell proliferation. Consistently, scRNA-seq revealed molecular similarities between a loss-of-function SMAD3 mutation (SMAD3^c.652delA/+) and TGFBR1^A230T/+. Lastly, combination treatment with Activin A and rapamycin during or after SMC differentiation significantly improved the mutant CPC-SMC contractile gene expression, and function; and rescued the mechanical properties of mutant CPC-SMC tissue constructs. Conclusions: This study reveals that a pathogenic TGFBR1 variant causes lineage-specific SMC defects informing the etiology of LDS-associated aortic root aneurysm. As a potential pharmacological strategy, our results highlight a combination treatment with Activin A and rapamycin that can rescue the SMC defects caused by the variant.

A deep convolutional neural network for segmentation of whole-slide pathology images identifies novel tumour cell-perivascular niche interactions that are associated with poor survival in glioblastoma

BACKGROUND

Glioblastoma is the most aggressive type of brain cancer with high-levels of intra- and inter-tumour heterogeneity that contribute to its rapid growth and invasion within the brain. However, a spatial characterisation of gene signatures and the cell types expressing these in different tumour locations is still lacking.

METHODS

We have used a deep convolutional neural network (DCNN) as a semantic segmentation model to segment seven different tumour regions including leading edge (LE), infiltrating tumour (IT), cellular tumour (CT), cellular tumour microvascular proliferation (CTmvp), cellular tumour pseudopalisading region around necrosis (CTpan), cellular tumour perinecrotic zones (CTpnz) and cellular tumour necrosis (CTne) in digitised glioblastoma histopathological slides from The Cancer Genome Atlas (TCGA). Correlation analysis between segmentation results from tumour images together with matched RNA expression data was performed to identify genetic signatures that are specific to different tumour regions.

RESULTS

We found that spatially resolved gene signatures were strongly correlated with survival in patients with defined genetic mutations. Further in silico cell ontology analysis along with single-cell RNA sequencing data from resected glioblastoma tissue samples showed that these tumour regions had different gene signatures, whose expression was driven by different cell types in the regional tumour microenvironment. Our results further pointed to a key role for interactions between microglia/pericytes/monocytes and tumour cells that occur in the IT and CTmvp regions, which may contribute to poor patient survival.

CONCLUSIONS

This work identified key histopathological features that correlate with patient survival and detected spatially associated genetic signatures that contribute to tumour-stroma interactions and which should be investigated as new targets in glioblastoma. The source codes and datasets used are available in GitHub: https://github.com/amin20/GBM_WSSM .

Spliceosome-regulated RSRP1-dependent NF-κB activation promotes the glioblastoma mesenchymal phenotype

BACKGROUND

The glioblastoma (GBM) mesenchymal (MES) phenotype, induced by NF-κB activation, is characterized by aggressive tumour progression and poor clinical outcomes. Our previous analysis indicated that MES GBM has a unique alternative splicing (AS) pattern; however, the underlying mechanism remains obscure. We aimed to reveal how splicing regulation contributes to MES phenotype promotion in GBM.

METHODS

We screened novel candidate splicing factors that participate in NF-κB activation and MES phenotype promotion in GBM. In vitro and in vivo assays were used to explore the function of RSRP1 in MES GBM.

RESULTS

Here, we identified that arginine/serine-rich protein 1 (RSRP1) promotes the MES phenotype by facilitating GBM cell invasion and apoptosis resistance. Proteomic, transcriptomic and functional analyses confirmed that RSRP1 regulates AS in MES GBM through mediating spliceosome assembly. One RSRP1-regulated AS event resulted in skipping PARP6 exon 18 to form truncated, oncogenic PARP6-s. This isoform was unable to effectively suppress NF-κB. Co-treatment of cultured GBM cells and GBM tumour-bearing mice with spliceosome and NF-κB inhibitors exerted a synergistic effect on MES GBM growth.

CONCLUSION

We identified a novel mechanism through which RSRP1-dependent splicing promotes the GBM MES phenotype. Targeting AS via RSRP1-related spliceosomal factors might constitute a promising treatment for GBM.

Single-cell characterization of macrophages in glioblastoma reveals MARCO as a mesenchymal pro-tumor marker

BACKGROUND

Macrophages are the most common infiltrating immune cells in gliomas and play a wide variety of pro-tumor and anti-tumor roles. However, the different subpopulations of macrophages and their effects on the tumor microenvironment remain poorly understood.

METHODS

We combined new and previously published single-cell RNA-seq data from 98,015 single cells from a total of 66 gliomas to profile 19,331 individual macrophages.

RESULTS

Unsupervised clustering revealed a pro-tumor subpopulation of bone marrow-derived macrophages characterized by the scavenger receptor MARCO, which is almost exclusively found in IDH1-wild-type glioblastomas. Previous studies have implicated MARCO as an unfavorable marker in melanoma and non-small cell lung cancer; here, we find that bulk MARCO expression is associated with worse prognosis and mesenchymal subtype. Furthermore, MARCO expression is significantly altered over the course of treatment with anti-PD1 checkpoint inhibitors in a response-dependent manner, which we validate with immunofluorescence imaging.

CONCLUSIONS

These findings illustrate a novel macrophage subpopulation that drives tumor progression in glioblastomas and suggest potential therapeutic targets to prevent their recruitment.

Deconvolution of cell type-specific drug responses in human tumor tissue with single-cell RNA-seq

BACKGROUND

Preclinical studies require models that recapitulate the cellular diversity of human tumors and provide insight into the drug sensitivities of specific cellular populations. The ideal platform would enable rapid screening of cell type-specific drug sensitivities directly in patient tumor tissue and reveal strategies to overcome intratumoral heterogeneity.

METHODS

We combine multiplexed drug perturbation in acute slice culture from freshly resected tumors with single-cell RNA sequencing (scRNA-seq) to profile transcriptome-wide drug responses in individual patients. We applied this approach to drug perturbations on slices derived from six glioblastoma (GBM) resections to identify conserved drug responses and to one additional GBM resection to identify patient-specific responses.

RESULTS

We used scRNA-seq to demonstrate that acute slice cultures recapitulate the cellular and molecular features of the originating tumor tissue and the feasibility of drug screening from an individual tumor. Detailed investigation of etoposide, a topoisomerase poison, and the histone deacetylase (HDAC) inhibitor panobinostat in acute slice cultures revealed cell type-specific responses across multiple patients. Etoposide has a conserved impact on proliferating tumor cells, while panobinostat treatment affects both tumor and non-tumor populations, including unexpected effects on the immune microenvironment.

CONCLUSIONS

Acute slice cultures recapitulate the major cellular and molecular features of GBM at the single-cell level. In combination with scRNA-seq, this approach enables cell type-specific analysis of sensitivity to multiple drugs in individual tumors. We anticipate that this approach will facilitate pre-clinical studies that identify effective therapies for solid tumors.

What are the applications of single-cell RNA sequencing in cancer research: a systematic review

Single-cell RNA sequencing (scRNA-seq) is a tool for studying gene expression at the single-cell level that has been widely used due to its unprecedented high resolution. In the present review, we outline the preparation process and sequencing platforms for the scRNA-seq analysis of solid tumor specimens and discuss the main steps and methods used during data analysis, including quality control, batch-effect correction, normalization, cell cycle phase assignment, clustering, cell trajectory and pseudo-time reconstruction, differential expression analysis and gene set enrichment analysis, as well as gene regulatory network inference. Traditional bulk RNA sequencing does not address the heterogeneity within and between tumors, and since the development of the first scRNA-seq technique, this approach has been widely used in cancer research to better understand cancer cell biology and pathogenetic mechanisms. ScRNA-seq has been of great significance for the development of targeted therapy and immunotherapy. In the second part of this review, we focus on the application of scRNA-seq in solid tumors, and summarize the findings and achievements in tumor research afforded by its use. ScRNA-seq holds promise for improving our understanding of the molecular characteristics of cancer, and potentially contributing to improved diagnosis, prognosis, and therapeutics.

A Drug Screening Pipeline Using 2D and 3D Patient-Derived In Vitro Models for Pre-Clinical Analysis of Therapy Response in Glioblastoma

Glioblastoma is one of the most common and lethal types of primary brain tumor. Despite aggressive treatment with chemotherapy and radiotherapy, tumor recurrence within 6-9 months is common. To overcome this, more effective therapies targeting cancer cell stemness, invasion, metabolism, cell death resistance and the interactions of tumor cells with their surrounding microenvironment are required. In this study, we performed a systematic review of the molecular mechanisms that drive glioblastoma progression, which led to the identification of 65 drugs/inhibitors that we screened for their efficacy to kill patient-derived glioma stem cells in two dimensional (2D) cultures and patient-derived three dimensional (3D) glioblastoma explant organoids (GBOs). From the screening, we found a group of drugs that presented different selectivity on different patient-derived in vitro models. Moreover, we found that Costunolide, a TERT inhibitor, was effective in reducing the cell viability in vitro of both primary tumor models as well as tumor models pre-treated with chemotherapy and radiotherapy. These results present a novel workflow for screening a relatively large groups of drugs, whose results could lead to the identification of more personalized and effective treatment for recurrent glioblastoma.

Topography of transcriptionally active chromatin in glioblastoma

Molecular profiling of the most aggressive brain tumor glioblastoma (GBM) on the basis of gene expression, DNA methylation, and genomic variations advances both cancer research and clinical diagnosis. The enhancer architectures and regulatory circuitries governing tumor-intrinsic transcriptional diversity and subtype identity are still elusive. Here, by mapping H3K27ac deposition, we analyze the active regulatory landscapes across 95 GBM biopsies, 12 normal brain tissues, and 38 cell line counterparts. Analyses of differentially regulated enhancers and super-enhancers uncovered previously unrecognized layers of intertumor heterogeneity. Integrative analysis of variant enhancer loci and transcriptome identified topographies of transcriptional enhancers and core regulatory circuitries in four molecular subtypes of primary tumors: AC1-mesenchymal, AC1-classical, AC2-proneural, and AC3-proneural. Moreover, this study reveals core oncogenic dependency on super-enhancer-driven transcriptional factors, long noncoding RNAs, and druggable targets in GBM. Through profiling of transcriptional enhancers, we provide clinically relevant insights into molecular classification, pathogenesis, and therapeutic intervention of GBM.

Premalignant Oligodendrocyte Precursor Cells Stall in a Heterogeneous State of Replication Stress Prior to Gliomagenesis

Cancer evolves from premalignant clones that adopt unusual cell states to achieve transformation. We previously pinpointed the oligodendrocyte precursor cell (OPC) as a cell of origin for glioma, but the early changes of mutant OPCs during premalignancy remained unknown. Using mice engineered for inducible Nf1-Trp53 loss in OPCs, we acutely isolated labeled mutant OPCs by laser-capture microdissection, determined global gene-expression changes by bulk RNA sequencing, and compared with cell-state fluctuations at the single-cell level by stochastic profiling, which uses RNA-sequencing measurements from random pools of 10 mutant cells. At 12 days after Nf1-Trp53 deletion, bulk differences were mostly limited to mitotic hallmarks and genes for ribosome biosynthesis, and stochastic profiling revealed a spectrum of stem-progenitor (Axl, Aldh1a1), proneural, and mesenchymal states as potential starting points for gliomagenesis. At 90 days, bulk sequencing detected few differentially expressed transcripts, whereas stochastic profiling revealed cell states for neurons and mural cells that do not give rise to glial tumors, suggesting cellular dead-ends for gliomagenesis. Importantly, mutant OPCs that strongly expressed key effectors of nonsense-mediated decay (Upf3b) and homology-dependent DNA repair (Rad51c, Slx1b, Ercc4) were identified along with DNA-damage markers, suggesting transcription-associated replication stress. Analysis of 10-cell transcriptomes at 90 days identified a locus of elevated gene expression containing an additional repair endonuclease (Mus81) and Rin1, a Ras-Raf antagonist and possible counterbalance to Nf1 loss, which was microdeleted or downregulated in gliomas at 150 days. These hidden cell-state variations uncover replication stress as a potential bottleneck that must be resolved for glioma initiation. SIGNIFICANCE: Profiling premalignant cell states in a mouse model of glioma uncovers regulatory heterogeneity in glioma cells-of-origin and defines a state of replication stress that precedes tumor initiation.See related articles by Singh and colleagues, p. 1840 and Schaff and colleagues, p. 1853.

3D-printed microplate inserts for long term high-resolution imaging of live brain organoids

BACKGROUND

Organoids are a reliable model used in the study of human brain development and under pathological conditions. However, current methods for brain organoid culture generate tissues that range from 0.5 to 2 mm of size, which need to be constantly agitated to allow proper oxygenation. The culture conditions are, therefore, not suitable for whole-brain organoid live imaging, required to study developmental processes and disease progression within physiologically relevant time frames (i.e. days, weeks, months).

RESULTS

Here we designed 3D-printed microplate inserts adaptable to standard 24 multi-well plates, which allow the growth of multiple organoids in pre-defined and fixed XYZ coordinates. This innovation facilitates high-resolution imaging of whole-cerebral organoids, allowing precise assessment of organoid growth and morphology, as well as cell tracking within the organoids, over long periods. We applied this technology to track neocortex development through neuronal progenitors in brain organoids, as well as the movement of patient-derived glioblastoma stem cells within healthy brain organoids.

CONCLUSIONS

This new bioengineering platform constitutes a significant advance that permits long term detailed analysis of whole-brain organoids using multimodal inverted fluorescence microscopy.

Perspective of mesenchymal transformation in glioblastoma

Despite aggressive multimodal treatment, glioblastoma (GBM), a grade IV primary brain tumor, still portends a poor prognosis with a median overall survival of 12–16 months. The complexity of GBM treatment mainly lies in the inter- and intra-tumoral heterogeneity, which largely contributes to the treatment-refractory and recurrent nature of GBM. By paving the road towards the development of personalized medicine for GBM patients, the cancer genome atlas classification scheme of GBM into distinct transcriptional subtypes has been considered an invaluable approach to overcoming this heterogeneity. Among the identified transcriptional subtypes, the mesenchymal subtype has been found associated with more aggressive, invasive, angiogenic, hypoxic, necrotic, inflammatory, and multitherapy-resistant features than other transcriptional subtypes. Accordingly, mesenchymal GBM patients were found to exhibit worse prognosis than other subtypes when patients with high transcriptional heterogeneity were excluded. Furthermore, identification of the master mesenchymal regulators and their downstream signaling pathways has not only increased our understanding of the complex regulatory transcriptional networks of mesenchymal GBM, but also has generated a list of potent inhibitors for clinical trials. Importantly, the mesenchymal transition of GBM has been found to be tightly associated with treatment-induced phenotypic changes in recurrence. Together, these findings indicate that elucidating the governing and plastic transcriptomic natures of mesenchymal GBM is critical in order to develop novel and selective therapeutic strategies that can improve both patient care and clinical outcomes. Thus, the focus of our review will be on the recent advances in the understanding of the transcriptome of mesenchymal GBM and discuss microenvironmental, metabolic, and treatment-related factors as critical components through which the mesenchymal signature may be acquired. We also take into consideration the transcriptomic plasticity of GBM to discuss the future perspectives in employing selective therapeutic strategies against mesenchymal GBM.

A distinct microglial subset at the tumor-stroma interface of glioma

The characterization of the tumor microenvironment (TME) in high grade gliomas (HGG) has generated significant interest in an effort to understand how neoplastic lesions in the central nervous system (CNS) are supported and to devise novel therapeutic targets. The TME of the CNS contains unique and specialized cells, including the resident myeloid cells, microglia. Myeloid involvement in HGG, such as glioblastoma, is associated with poor outcomes. Glioma-associated microglia and infiltrating monocytes/macrophages (GAM) accumulate within the neoplastic lesion where they facilitate tumor growth and drive immunosuppression. However, it has been difficult to differentiate whether microglia and macrophages have similar or distinct roles in pathology, and if the spatial organization of these cells informs outcomes. Here, we characterize the tumor-stroma border and identify peritumoral GAM (PGAM) as a unique subpopulation of GAM. Using data mining and analyses of samples derived from both murine and human sources we show that PGAM exhibit a pro-inflammatory and chemotactic phenotype that is associated with peripheral monocyte recruitment, and decreased overall survival. PGAM act as a unique subset of GAM at the tumor-stroma interface. We define a novel gene signature to identify these cells and suggest that PGAM constitute a cellular target of the TME.

Involvement of the Catecholamine Pathway in Glioblastoma Development

Glioblastoma (GBM) is the most aggressive tumor of the central nervous system (CNS). The standard of care improves the overall survival of patients only by a few months. Explorations of new therapeutic targets related to molecular properties of the tumor are under way. Even though neurotransmitters and their receptors normally function as mediators of interneuronal communication, growing data suggest that these molecules are also involved in modulating the development and growth of GBM by acting on neuronal and glioblastoma stem cells. In our previous DNA CpG methylation studies, gene ontology analyses revealed the involvement of the monoamine pathway in sequential GBM. In this follow-up study, we quantitated the expression levels of four selected catecholamine pathway markers (alpha 1D adrenergic receptor-ADRA1D; adrenergic beta receptor kinase 1 or G protein-coupled receptor kinase 2-ADRBK1/GRK2; dopamine receptor D2-DRD2; and synaptic vesicle monoamine transporter-SLC18A2) by immunohistochemistry, and compared the histological scores with the methylation levels within the promoters + genes of these markers in 21 pairs of sequential GBM and in controls. Subsequently, we also determined the promoter and gene methylation levels of the same markers in an independent database cohort of sequential GBM pairs. These analyses revealed partial inverse correlations between the catecholamine protein expression and promoter + gene methylation levels, when the tumor and control samples were compared. However, we found no differences in the promoter + gene methylation levels of these markers in either our own or in the database primary-recurrent GBM pairs, despite the higher protein expression of all markers in the primary samples. This observation suggests that regulation of catecholamine expression is only partially related to CpG methylation within the promoter + gene regions, and additional mechanisms may also influence the expression of these markers in progressive GBM. These analyses underscore the involvement of certain catecholamine pathway markers in GBM development and suggest that these molecules mediating or modulating tumor growth merit further exploration.

Insights Gained from Single-Cell Analysis of Immune Cells in the Tumor Microenvironment

Understanding tumor immune microenvironments is critical for identifying immune modifiers of cancer progression and developing cancer immunotherapies. Recent applications of single-cell RNA sequencing (scRNA-seq) in dissecting tumor microenvironments have brought important insights into the biology of tumor-infiltrating immune cells, including their heterogeneity, dynamics, and potential roles in both disease progression and response to immune checkpoint inhibitors and other immunotherapies. This review focuses on the advances in knowledge of tumor immune microenvironments acquired from scRNA-seq studies across multiple types of human tumors, with a particular emphasis on the study of phenotypic plasticity and lineage dynamics of immune cells in the tumor environment. We also discuss several imminent questions emerging from scRNA-seq observations and their potential solutions on the horizon.

CHARTS: a web application for characterizing and comparing tumor subpopulations in publicly available single-cell RNA-seq data sets

BACKGROUND

Single-cell RNA-seq (scRNA-seq) enables the profiling of genome-wide gene expression at the single-cell level and in so doing facilitates insight into and information about cellular heterogeneity within a tissue. This is especially important in cancer, where tumor and tumor microenvironment heterogeneity directly impact development, maintenance, and progression of disease. While publicly available scRNA-seq cancer data sets offer unprecedented opportunity to better understand the mechanisms underlying tumor progression, metastasis, drug resistance, and immune evasion, much of the available information has been underutilized, in part, due to the lack of tools available for aggregating and analysing these data.

RESULTS

We present CHARacterizing Tumor Subpopulations (CHARTS), a web application for exploring publicly available scRNA-seq cancer data sets in the NCBI's Gene Expression Omnibus. More specifically, CHARTS enables the exploration of individual gene expression, cell type, malignancy-status, differentially expressed genes, and gene set enrichment results in subpopulations of cells across tumors and data sets. Along with the web application, we also make available the backend computational pipeline that was used to produce the analyses that are available for exploration in the web application.

CONCLUSION

CHARTS is an easy to use, comprehensive platform for exploring single-cell subpopulations within tumors across the ever-growing collection of public scRNA-seq cancer data sets. CHARTS is freely available at charts.morgridge.org.

Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities

The transcriptomic classification of glioblastoma (GBM) has failed to predict survival and therapeutic vulnerabilities. A computational approach for unbiased identification of core biological traits of single cells and bulk tumors uncovered four tumor cell states and GBM subtypes distributed along neurodevelopmental and metabolic axes, classified as proliferative/progenitor, neuronal, mitochondrial and glycolytic/plurimetabolic. Each subtype was enriched with biologically coherent multiomic features. Mitochondrial GBM was associated with the most favorable clinical outcome. It relied exclusively on oxidative phosphorylation for energy production, whereas the glycolytic/plurimetabolic subtype was sustained by aerobic glycolysis and amino acid and lipid metabolism. Deletion of the glucose-proton symporter SLC45A1 was the truncal alteration most significantly associated with mitochondrial GBM, and the reintroduction of SLC45A1 in mitochondrial glioma cells induced acidification and loss of fitness. Mitochondrial, but not glycolytic/plurimetabolic, GBM exhibited marked vulnerability to inhibitors of oxidative phosphorylation. The pathway-based classification of GBM informs survival and enables precision targeting of cancer metabolism.

Polyamines drive myeloid cell survival by buffering intracellular pH to promote immunosuppression in glioblastoma

Glioblastoma is characterized by the robust infiltration of immunosuppressive tumor-associated myeloid cells (TAMCs). It is not fully understood how TAMCs survive in the acidic tumor microenvironment to cause immunosuppression in glioblastoma. Metabolic and RNA-seq analysis of TAMCs revealed that the arginine-ornithine-polyamine axis is up-regulated in glioblastoma TAMCs but not in tumor-infiltrating CD8+ T cells. Active de novo synthesis of highly basic polyamines within TAMCs efficiently buffered low intracellular pH to support the survival of these immunosuppressive cells in the harsh acidic environment of solid tumors. Administration of difluoromethylornithine (DFMO), a clinically approved inhibitor of polyamine generation, enhanced animal survival in immunocompetent mice by causing a tumor-specific reduction of polyamines and decreased intracellular pH in TAMCs. DFMO combination with immunotherapy or radiotherapy further enhanced animal survival. These findings indicate that polyamines are used by glioblastoma TAMCs to maintain normal intracellular pH and cell survival and thus promote immunosuppression during tumor evolution.

Case Report: Single-Cell Transcriptomic Analysis of an Anaplastic Oligodendroglioma Post Immunotherapy

Glioma is the most common primary malignant brain tumor with a poor prognosis. Immune checkpoint inhibitors have been of great interest in investigation of glioma treatments. Here, we report single-cell transcriptomic analyses of two tumor areas from an oligodendroglioma taken from a patient who had multiple tumor recurrences, following several chemotherapies and radiation treatments. The patient subsequently received nivolumab and was considered have disease progression based on conventional diagnostic imaging after two cycles of treatment. He underwent a debulking surgical resection and pathological diagnosis was recurrent disease. During the surgery, tumor tissues were also collected from the enhancing and non-enhancing areas for a scRNAseq analysis to investigate the tumor microenvironment of these radiographically divergent areas. The scRNAseq analysis reveals a plethora of immune cells, suggesting that the increased mass observed on MRI may be partially a result of immune cell infiltration. The patient continued to receive immunotherapy after a short course of palliative radiation and remained free of disease progression for at least 12 months after the last surgery, suggesting a sustained response to immunotherapy. The scRNAseq analysis indicated that the radiological progression was in large part due to immune cell infiltrate and continued immunotherapy led to a positive clinical outcome in a patient who would have otherwise been admitted to hospice care with halting of immunotherapy. Our study demonstrates the potential of scRNAseq analyses in understanding the tumor microenvironment, which may assist the clinical decision-making process for challenging glioma cases following immunotherapy.

Dissecting the Invasion-Associated Long Non-coding RNAs Using Single-Cell RNA-Seq Data of Glioblastoma

Glioblastoma (GBM) is characterized by rapid and lethal infiltration of brain tissue, which is the primary cause of treatment failure and deaths for GBM. Therefore, understanding the molecular mechanisms of tumor cell invasion is crucial for the treatment of GBM. In this study, we dissected the single-cell RNA-seq data of 3345 cells from four patients and identified dysregulated genes including long non-coding RNAs (lncRNAs), which were involved in the development and progression of GBM. Based on co-expression network analysis, we identified a module (M1) that significantly overlapped with the largest number of dysregulated genes and was confirmed to be associated with GBM invasion by integrating EMT signature, experiment-validated invasive marker and pseudotime trajectory analysis. Further, we denoted invasion-associated lncRNAs which showed significant correlations with M1 and revealed their gradually increased expression levels along the tumor cell invasion trajectory, such as VIM-AS1, WWTR1-AS1, and NEAT1. We also observed the contribution of higher expression of these lncRNAs to poorer survival of GBM patients. These results were mostly recaptured in another validation data of 7930 single cells from 28 GBM patients. Our findings identified lncRNAs that played critical roles in regulating or controlling cell invasion and migration of GBM and provided new insights into the molecular mechanisms underlying GBM invasion as well as potential targets for the treatment of GBM.

Convection Enhanced Delivery of Topotecan for Gliomas: A Single-Center Experience

A key limitation to glioma treatment involves the blood brain barrier (BBB). Convection enhanced delivery (CED) is a technique that uses a catheter placed directly into the brain parenchyma to infuse treatments using a pressure gradient. In this manuscript, we describe the physical principles behind CED along with the common pitfalls and methods for optimizing convection. Finally, we highlight our institutional experience using topotecan CED for the treatment of malignant glioma.

Integrated Proteogenomic Characterization across Major Histological Types of Pediatric Brain Cancer

We report a comprehensive proteogenomics analysis, including whole-genome sequencing, RNA sequencing, and proteomics and phosphoproteomics profiling, of 218 tumors across 7 histological types of childhood brain cancer: low-grade glioma (n = 93), ependymoma (32), high-grade glioma (25), medulloblastoma (22), ganglioglioma (18), craniopharyngioma (16), and atypical teratoid rhabdoid tumor (12). Proteomics data identify common biological themes that span histological boundaries, suggesting that treatments used for one histological type may be applied effectively to other tumors sharing similar proteomics features. Immune landscape characterization reveals diverse tumor microenvironments across and within diagnoses. Proteomics data further reveal functional effects of somatic mutations and copy number variations (CNVs) not evident in transcriptomics data. Kinase-substrate association and co-expression network analysis identify important biological mechanisms of tumorigenesis. This is the first large-scale proteogenomics analysis across traditional histological boundaries to uncover foundational pediatric brain tumor biology and inform rational treatment selection.

Nanoparticles for Stem Cell Therapy Bioengineering in Glioma

Gliomas are a dismal disease associated with poor survival and high morbidity. Current standard treatments have reached a therapeutic plateau even after combining maximal safe resection, radiation, and chemotherapy. In this setting, stem cells (SCs) have risen as a promising therapeutic armamentarium, given their intrinsic tumor homing as well as their natural or bioengineered antitumor properties. The interplay between stem cells and other therapeutic approaches such as nanoparticles holds the potential to synergize the advantages from the combined therapeutic strategies. Nanoparticles represent a broad spectrum of synthetic and natural biomaterials that have been proven effective in expanding diagnostic and therapeutic efforts, either used alone or in combination with immune, genetic, or cellular therapies. Stem cells have been bioengineered using these biomaterials to enhance their natural properties as well as to act as their vehicle when anticancer nanoparticles need to be delivered into the tumor microenvironment in a very precise manner. Here, we describe the recent developments of this new paradigm in the treatment of malignant gliomas.

Digital microfluidic isolation of single cells for -Omics

We introduce Digital microfluidic Isolation of Single Cells for -Omics (DISCO), a platform that allows users to select particular cells of interest from a limited initial sample size and connects single-cell sequencing data to their immunofluorescence-based phenotypes. Specifically, DISCO combines digital microfluidics, laser cell lysis, and artificial intelligence-driven image processing to collect the contents of single cells from heterogeneous populations, followed by analysis of single-cell genomes and transcriptomes by next-generation sequencing, and proteomes by nanoflow liquid chromatography and tandem mass spectrometry. The results described herein confirm the utility of DISCO for sequencing at levels that are equivalent to or enhanced relative to the state of the art, capable of identifying features at the level of single nucleotide variations. The unique levels of selectivity, context, and accountability of DISCO suggest potential utility for deep analysis of any rare cell population with contextual dependencies.

Multi-Omic approaches are a powerful way for obtaining in-depth understanding of a cell’s state. Here the authors present DISCO, combining digital microfluidics, laser cell lysis, and artificial intelligence-driven image processing to analyze single-cell genomes, transcriptomes and proteomes in a mixed population.