Spatially resolved multi-omics deciphers bidirectional tumor-host interdependence in glioblastoma

The emerging role of artificial intelligence in neuropathology: Where are we and where do we want to go?

The field of neuropathology, a subspecialty of pathology which studies the diseases affecting the nervous system, is experiencing significant changes due to advancements in artificial intelligence (AI). Traditionally reliant on histological methods and clinical correlations, neuropathology is now experiencing a revolution due to the development of AI technologies like machine learning (ML) and deep learning (DL). These technologies enhance diagnostic accuracy, optimize workflows, and enable personalized treatment strategies. AI algorithms excel at analyzing histopathological images, often revealing subtle morphological changes missed by conventional methods. For example, deep learning models applied to digital pathology can effectively differentiate tumor grades and detect rare pathologies, leading to earlier and more precise diagnoses. Progress in neuroimaging is another helpful tool of AI, as enhanced analysis of MRI and CT scans supports early detection of neurodegenerative diseases. By identifying biomarkers and progression patterns, AI aids in timely therapeutic interventions, potentially slowing disease progression. In molecular pathology, AI's ability to analyze complex genomic data helps uncover the genetic and molecular basis of neuropathological conditions, facilitating personalized treatment plans. AI-driven automation streamlines routine diagnostic tasks, allowing pathologists to focus on complex cases, especially in settings with limited resources. This review explores AI's integration into neuropathology, highlighting its current applications, benefits, challenges, and future directions.

The Three Pillars of Glioblastoma: A Systematic Review and Novel Analysis of Multi-Omics and Clinical Data

Glioblastoma is the most fatal and common malignant brain tumor, excluding metastasis and with a median survival of approximately one year. While solid tumors benefit from newly approved drugs, immunotherapy, and prevention, none of these scenarios are opening for glioblastoma. The key to unlocking the peculiar features of glioblastoma is observing its molecular and anatomical features tightly entangled with the host's central nervous system (CNS). In June 2024, we searched the PUBMED electronic database. Data collection and analysis were conducted independently by two reviewers. Results: A total of 215 articles were identified, and 192 were excluded based on inclusion and exclusion criteria. The remaining 23 were used for collecting divergent molecular pathways and anatomical features of glioblastoma. The analysis of the selected papers revealed a multifaced tumor with extreme variability and cellular reprogramming that are observable within the same patient. All the variability of glioblastoma could be clustered into three pillars to dissect the physiology of the tumor: 1. necrotic core; 2. vascular proliferation; 3. CNS infiltration. These three pillars support glioblastoma survival, with a pivotal role of the neurovascular unit, as supported by the most recent paper published by experts in the field.

Integration of multi-omics data revealed the orphan CpG islands and enhancer-dominated c is-regulatory network in glioma

The complex transcriptional regulatory network leads to the poor prognosis of glioma. The role of orphan CpG islands (oCGIs) in the transcriptional regulatory network has been overlooked. We conducted a comprehensive exploration of the cis-regulatory roles of oCGIs and enhancers by integrating multi-omics data. Direct regulation of target genes by oCGIs or enhancers is of great importance in the cis-regulatory network. Furthermore, based on single-cell multi-omics data, we found that the highly activated cis-regulatory network in cluster 2 (C2) sustains the high proliferative potential of glioma cells. The upregulation of oCGIs and enhancers related genes in C2 results in glioma patients exhibiting resistance to radiotherapy and chemotherapy. These findings were further validated through glioma cell line related experiments. Our study offers insight into the pathogenesis of glioma and provides a strategy to treat this challenging disease.

Remote Neuroinflammation in Newly Diagnosed Glioblastoma Correlates with Unfavorable Clinical Outcome

PURPOSE

Current therapy strategies still provide only limited success in the treatment of glioblastoma, the most frequent primary brain tumor in adults. In addition to the characterization of the tumor microenvironment, global changes in the brain of patients with glioblastoma have been described. However, the impact and molecular signature of neuroinflammation distant of the primary tumor site have not yet been thoroughly elucidated.

EXPERIMENTAL DESIGN

We performed translocator protein (TSPO)-PET in patients with newly diagnosed glioblastoma (n = 41), astrocytoma WHO grade 2 (n = 7), and healthy controls (n = 20) and compared TSPO-PET signals of the non-lesion (i.e., contralateral) hemisphere. Back-translation into syngeneic SB28 glioblastoma mice was used to characterize Pet alterations on a cellular level. Ultimately, multiplex gene expression analyses served to profile immune cells in remote brain.

RESULTS

Our study revealed elevated TSPO-PET signals in contralateral hemispheres of patients with newly diagnosed glioblastoma compared to healthy controls. Contralateral TSPO was associated with persisting epileptic seizures and shorter overall survival independent of the tumor phenotype. Back-translation into syngeneic glioblastoma mice pinpointed myeloid cells as the predominant source of contralateral TSPO-PET signal increases and identified a complex immune signature characterized by myeloid cell activation and immunosuppression in distant brain regions.

CONCLUSIONS

Neuroinflammation within the contralateral hemisphere can be detected with TSPO-PET imaging and associates with poor outcome in patients with newly diagnosed glioblastoma. The molecular signature of remote neuroinflammation promotes the evaluation of immunomodulatory strategies in patients with detrimental whole brain inflammation as reflected by high TSPO expression.

Spatial oncology: Translating contextual biology to the clinic

Microscopic examination of cells in their tissue context has been the driving force behind diagnostic histopathology over the past two centuries. Recently, the rise of advanced molecular biomarkers identified through single cell profiling has increased our understanding of cellular heterogeneity in cancer but have yet to significantly impact clinical care. Spatial technologies integrating molecular profiling with microenvironmental features are poised to bridge this translational gap by providing critical in situ context for understanding cellular interactions and organization. Here, we review how spatial tools have been used to study tumor ecosystems and their clinical applications. We detail findings in cell-cell interactions, microenvironment composition, and tissue remodeling for immune evasion and therapeutic resistance. Additionally, we highlight the emerging role of multi-omic spatial profiling for characterizing clinically relevant features including perineural invasion, tertiary lymphoid structures, and the tumor-stroma interface. Finally, we explore strategies for clinical integration and their augmentation of therapeutic and diagnostic approaches.

Integrative multi-omics analysis unveils the connection between transcriptomic characteristics associated with mitochondria and the tumor immune microenvironment in lower-grade gliomas

Lower-grade gliomas (LGGs) exhibit diverse clinical behaviors and varying immune infiltration levels. Mitochondria have been implicated in numerous cancer pathogenesis and development, including LGGs. However, the precise biological functions of mitochondrial genes in shaping the immune landscape and the prognostic significance of LGGs remain elusive. Utilizing the Mito-Carta3.0 database, we curated a total of 1136 genes implicated in mitochondrial functions. By leveraging the expression profiles of 1136 genes related to mitochondria, we successfully categorized LGGs into four distinctive mitochondria-related transcriptome (MRT) subtypes. Our thorough analysis conclusively demonstrated that these subtypes exhibited marked disparities. To enable a personalized and integrated evaluation of LGG patients, we developed a prognostic signature known as MRT-related prognostic signature (MTRS). MTRS demonstrated correlation with mitochondria-related transcriptome (MRT) subtypes, allowing the assessment of patients' prognosis and immune microenvironment. We conducted a detailed exploration of the single-cell distribution of MTRS in lower-grade gliomas and verified the core genes of MTRS within the spatial transcriptome of these tumors. Furthermore, our study pinpointed MGME1 as the pivotal gene in the model, functioning as an oncogene that exerts influence on cell proliferation and migration capabilities. Our research highlights the importance of mitochondrial transcriptomic features in LGGs, offering paths for tailored therapies.

Spatiotemporal modeling reveals high-resolution invasion states in glioblastoma

BACKGROUND

Diffuse invasion of glioblastoma cells through normal brain tissue is a key contributor to tumor aggressiveness, resistance to conventional therapies, and dismal prognosis in patients. A deeper understanding of how components of the tumor microenvironment (TME) contribute to overall tumor organization and to programs of invasion may reveal opportunities for improved therapeutic strategies.

RESULTS

Towards this goal, we apply a novel computational workflow to a spatiotemporally profiled GBM xenograft cohort, leveraging the ability to distinguish human tumor from mouse TME to overcome previous limitations in the analysis of diffuse invasion. Our analytic approach, based on unsupervised deconvolution, performs reference-free discovery of cell types and cell activities within the complete GBM ecosystem. We present a comprehensive catalogue of 15 tumor cell programs set within the spatiotemporal context of 90 mouse brain and TME cell types, cell activities, and anatomic structures. Distinct tumor programs related to invasion align with routes of perivascular, white matter, and parenchymal invasion. Furthermore, sub-modules of genes serving as program network hubs are highly prognostic in GBM patients.

CONCLUSION

The compendium of programs presented here provides a basis for rational targeting of tumor and/or TME components. We anticipate that our approach will facilitate an ecosystem-level understanding of the immediate and long-term consequences of such perturbations, including the identification of compensatory programs that will inform improved combinatorial therapies.

Targeting axonal guidance dependencies in glioblastoma with ROBO1 CAR T cells

Resistance to genotoxic therapies and tumor recurrence are hallmarks of glioblastoma (GBM), an aggressive brain tumor. In this study, we investigated functional drivers of post-treatment recurrent GBM through integrative genomic analyses, genome-wide genetic perturbation screens in patient-derived GBM models and independent lines of validation. Specific genetic dependencies were found consistent across recurrent tumor models, accompanied by increased mutational burden and differential transcript and protein expression compared to its primary GBM predecessor. Our observations suggest a multi-layered genetic response to drive tumor recurrence and implicate PTP4A2 (protein tyrosine phosphatase 4A2) as a modulator of self-renewal, proliferation and tumorigenicity in recurrent GBM. Genetic perturbation or small-molecule inhibition of PTP4A2 acts through a dephosphorylation axis with roundabout guidance receptor 1 (ROBO1) and its downstream molecular players, exploiting a functional dependency on ROBO signaling. Because a pan-PTP4A inhibitor was limited by poor penetrance across the blood-brain barrier in vivo, we engineered a second-generation chimeric antigen receptor (CAR) T cell therapy against ROBO1, a cell surface receptor enriched across recurrent GBM specimens. A single dose of ROBO1-targeted CAR T cells doubled median survival in cell-line-derived xenograft (CDX) models of recurrent GBM. Moreover, in CDX models of adult lung-to-brain metastases and pediatric relapsed medulloblastoma, ROBO1 CAR T cells eradicated tumors in 50-100% of mice. Our study identifies a promising multi-targetable PTP4A-ROBO1 signaling axis that drives tumorigenicity in recurrent GBM, with potential in other malignant brain tumors.

Single-cell and spatial omics unravel the spatiotemporal biology of tumour border invasion and haematogenous metastasis

Solid tumours exhibit a well-defined architecture, comprising a differentiated core and a dynamic border that interfaces with the surrounding tissue. This border, characterised by distinct cellular morphology and molecular composition, serves as a critical determinant of the tumour's invasive behaviour. Notably, the invasive border of the primary tumour represents the principal site for intravasation of metastatic cells. These cells, known as circulating tumour cells (CTCs), function as 'seeds' for distant dissemination and display remarkable heterogeneity. Advancements in spatial sequencing technology are progressively unveiling the spatial biological features of tumours. However, systematic investigations specifically targeting the characteristics of the tumour border remain scarce. In this comprehensive review, we illuminate key biological insights along the tumour body-border-haematogenous metastasis axis over the past five years. We delineate the distinctive landscape of tumour invasion boundaries and delve into the intricate heterogeneity and phenotype of CTCs, which orchestrate haematogenous metastasis. These insights have the potential to explain the basis of tumour invasion and distant metastasis, offering new perspectives for the development of more complex and precise clinical interventions and treatments.

Defining and modeling dynamic spatial heterogeneity within tumor microenvironments

Many solid tumors exhibit significant genetic, cellular, and biophysical heterogeneity which dynamically evolves during disease progression and after treatment. This constant flux in cell composition, phenotype, spatial relationships, and tissue properties poses significant challenges in accurately diagnosing and treating patients. Much of the complexity lies in unraveling the molecular changes in different tumor compartments, how they influence one another in space and time and where vulnerabilities exist that might be appropriate to target therapeutically. Recent advances in spatial profiling tools and technologies are enabling new insight into the underlying biology of complex tumors, creating a greater understanding of the intricate relationship between cell types, states, and the microenvironment. Here we reflect on some recent discoveries in this area, where the key knowledge and technology gaps lie, and the advancements in spatial measurements and in vitro models for the study of spatial intratumoral heterogeneity.

Advances in spatial multi-omics in tumors

Single-cell techniques have convincingly demonstrated that tumor tissue usually contains multiple genetically defined cell subclones with different gene mutation sets as well as various transcriptional profiles, but the spatial heterogeneity of the microenvironment and the macrobiological characteristics of the tumor ecosystem have not been described. For the past few years, spatial multi-omics technologies have revealed the cellular interactions, microenvironment, and even systemic tumor-host interactions in the tumor ecosystem at the spatial level, which can not only improve classical therapies such as surgery, radiotherapy, and chemotherapy but also promote the development of emerging targeted therapies in immunotherapy. Here, we review some emerging spatial omics techniques in cancer research and therapeutic applications and propose prospects for their future development.

Neural Influences on Tumor Progression Within the Central Nervous System

For decades, researchers have studied how brain tumors, the immune system, and drugs interact. With the advances in cancer neuroscience, which centers on defining and therapeutically targeting nervous system-cancer interactions, both within the local tumor microenvironment (TME) and on a systemic level, the subtle relationship between neurons and tumors in the central nervous system (CNS) has been deeply studied. Neurons, as the executors of brain functional activities, have been shown to significantly influence the emergence and development of brain tumors, including both primary and metastatic tumors. They engage with tumor cells via chemical or electrical synapses, directly regulating tumors or via intricate coupling networks, and also contribute to the TME through paracrine signaling, secreting proteins that exert regulatory effects. For instance, in a study involving a mouse model of glioblastoma, the authors observed a 42% increase in tumor volume when neuronal activity was stimulated, compared to controls (p < 0.01), indicating a direct correlation between neural activity and tumor growth. These thought-provoking results offer promising new strategies for brain tumor therapies, highlighting the potential of neuronal modulation to curb tumor progression. Future strategies may focus on developing drugs to inhibit or neutralize proteins and other bioactive substances secreted by neurons, break synaptic connections and interactions between infiltrating cells and tumor cells, as well as disrupt electrical coupling within glioma cell networks. By harnessing the insights gained from this research, we aspire to usher in a new era of brain tumor therapies that are both more potent and precise.

Spatial metabolomics highlights metabolic reprogramming in acute myeloid leukemia mice through creatine pathway

Acute myeloid leukemia (AML) is recognized as an aggressive cancer that is characterized by significant metabolic reprogramming. Here, we applied spatial metabolomics to achieve high-throughput, in situ identification of metabolites within the liver metastases of AML mice. Alterations at metabolite and protein levels were further mapped out and validated by integrating untargeted metabolomics and proteomics. This study showed a downregulation in arginine's contribution to polyamine biosynthesis and urea cycle, coupled with an upregulation of the creatine metabolism. The upregulation of creatine synthetases Gatm and Gamt, as well as the creatine transporter Slc6a8, resulted in a marked accumulation of creatine within tumor foci. This process further enhances oxidative phosphorylation and glycolysis of leukemia cells, thereby boosting ATP production to foster proliferation and infiltration. Importantly, we discovered that inhibiting Slc6a8 can counter these detrimental effects, offering a new strategy for treating AML by targeting metabolic pathways.

The spatial multi-omics revolution in cancer therapy: Precision redefined

Spatially resolved multi-omics revolutionizes cancer therapy by decoding the cellular and molecular heterogeneity of the tumor microenvironment through spatial coordinates. This commentary discusses the roles of spatial multi-omics in identifying precise therapeutic targets and predicting treatment responses while also highlighting the challenges that impede its integration into precision medicine.

SMAC mimetic drives microglia phenotype and glioblastoma immune microenvironment

Tumor-associated macrophages/microglia (TAMs) are highly plastic and heterogeneous immune cells that can be immune-supportive or tumor-supportive depending of the microenvironment. TAMs are the most abundant immune cells in glioblastoma (GB), and play a key role in immunosuppression. Therefore, TAMs reprogramming toward immune-supportive cells is a promising strategy to overcome immunosuppression. By leveraging scRNAseq human GB databases, we identified that Inhibitor of Apoptosis Proteins (IAP) were expressed by TAMs. To investigate their role in TAMs-related immunosuppression, we antagonized IAP using the central nervous system permeant SMAC mimetic GDC-0152 (SMg). On explants and cultured immune cells isolated from human GB samples, SMg modified TAMs activity. We showed that SMg treatment promoted microglia pro-apoptotic and anti-tumoral function via caspase-3 pro-inflammatory cleavage and the inhibition of tumoroids growth. Then we designed a relevant immunogenic mouse GB model to decipher the spatio-temporal densities, distribution, phenotypes and function of TAMs with or without SMg treatment. We used 3D imaging techniques, a transgenic mouse with fluorescent TAM subsets and mass cytometry. We confirmed that SMg promoted microglia activation, antigen-presenting function and tumor infiltration. In addition, we observed a remodeling of blood vessels, a decrease in anti-inflammatory macrophages and an increased level of monocytes and their mo-DC progeny. This remodeling of the TAM landscape is associated with an increase in CD8 T cell density and activation. Altogether, these results demonstrated that SMg drives the immunosuppressive basal microglia toward an active phenotype with pro-apoptotic and anti-tumoral function and modifies the GB immune landscape. This identifies IAP as targets of choice for a potential mechanism-based therapeutic strategy and SMg as a promising molecule for this application.

The burgeoning spatial multi-omics in human gastrointestinal cancers

The development and progression of diseases in multicellular organisms unfold within the intricate three-dimensional body environment. Thus, to comprehensively understand the molecular mechanisms governing individual development and disease progression, precise acquisition of biological data, including genome, transcriptome, proteome, metabolome, and epigenome, with single-cell resolution and spatial information within the body's three-dimensional context, is essential. This foundational information serves as the basis for deciphering cellular and molecular mechanisms. Although single-cell multi-omics technology can provide biological information such as genome, transcriptome, proteome, metabolome, and epigenome with single-cell resolution, the sample preparation process leads to the loss of spatial information. Spatial multi-omics technology, however, facilitates the characterization of biological data, such as genome, transcriptome, proteome, metabolome, and epigenome in tissue samples, while retaining their spatial context. Consequently, these techniques significantly enhance our understanding of individual development and disease pathology. Currently, spatial multi-omics technology has played a vital role in elucidating various processes in tumor biology, including tumor occurrence, development, and metastasis, particularly in the realms of tumor immunity and the heterogeneity of the tumor microenvironment. Therefore, this article provides a comprehensive overview of spatial transcriptomics, spatial proteomics, and spatial metabolomics-related technologies and their application in research concerning esophageal cancer, gastric cancer, and colorectal cancer. The objective is to foster the research and implementation of spatial multi-omics technology in digestive tumor diseases. This review will provide new technical insights for molecular biology researchers.

Glioblastoma cells increase expression of notch signaling and synaptic genes within infiltrated brain tissue

Glioblastoma remains one of the deadliest brain malignancies. First-line therapy consists of maximal surgical tumor resection, accompanied by chemotherapy and radiotherapy. Malignant cells escape surgical resection by migrating into the surrounding healthy brain tissue, where they give rise to the recurrent tumor. Based on gene expression, tumor cores can be subtyped into mesenchymal, proneural, and classical tumors, each being associated with differences in genetic alterations and cellular composition. In contrast, the adjacent brain parenchyma where infiltrating malignant cells escape surgical resection is less characterized in patients. Using spatial transcriptomics (n = 11), we show that malignant cells within proneural or mesenchymal tumor cores display spatially organized differences in gene expression, although such differences decrease within the infiltrated brain tissue. Malignant cells residing in infiltrated brain tissue have increased expression of genes related to neurodevelopmental pathways and glial cell differentiation. Our findings provide an updated view of the spatial landscape of glioblastomas and further our understanding of the malignant cells that infiltrate the healthy brain, providing new avenues for the targeted therapy of these cells after surgical resection.

Modulation of blood-tumor barrier transcriptional programs improves intra-tumoral drug delivery and potentiates chemotherapy in GBM

Glioblastoma (GBM) is the most common malignant primary brain tumor. GBM has an extremely poor prognosis and new treatments are badly needed. Efficient drug delivery to GBM is a major obstacle as the blood-brain barrier (BBB) prevents passage of the majority of cancer drugs into the brain. It is also recognized that the blood-brain tumor barrier (BTB) in the growing tumor represents a challenge. The BTB is heterogeneous and poorly characterized, but similar to the BBB it can prevent therapeutics from reaching effective intra-tumoral doses, dramatically hindering their potential. Here, we identified a 12-gene signature associated with the BTB, with functions related to vasculature development, morphogenesis and cell migration. We identified CDH5 as a core molecule in this set and confirmed its over-expression in GBM vasculature using spatial transcriptomics of GBM patient specimens. We found that the indirubin-derivative, 6-bromoindirubin acetoxime (BIA), could downregulate CDH5 and other BTB signature genes, causing endothelial barrier disruption in endothelial monolayers and BBB 3D spheroids in vitro. Treatment of tumor-bearing mice with BIA enabled increased intra-tumoral accumulation of the BBB non-penetrant chemotherapeutic drug cisplatin and potentiated cisplatin-mediated DNA damage by targeting DNA repair pathways. Finally, using an injectable BIA nanoparticle formulation, PPRX-1701, we significantly improved the efficacy of cisplatin in patient-derived GBM xenograms and prolonged their survival. Overall, our work reveals potential targets at the BTB for improved chemotherapy delivery and the bifunctional properties of BIA as a BTB modulator and potentiator of chemotherapy, supporting its further development.

Spatial multi-omics: deciphering technological landscape of integration of multi-omics and its applications

The emergence of spatial multi-omics has helped address the limitations of single-cell sequencing, which often leads to the loss of spatial context among cell populations. Integrated analysis of the genome, transcriptome, proteome, metabolome, and epigenome has enhanced our understanding of cell biology and the molecular basis of human diseases. Moreover, this approach offers profound insights into the interactions between intracellular and intercellular molecular mechanisms involved in the development, physiology, and pathogenesis of human diseases. In this comprehensive review, we examine current advancements in multi-omics technologies, focusing on their evolution and refinement over the past decade, including improvements in throughput and resolution, modality integration, and accuracy. We also discuss the pivotal contributions of spatial multi-omics in revealing spatial heterogeneity, constructing detailed spatial atlases, deciphering spatial crosstalk in tumor immunology, and advancing translational research and cancer therapy through precise spatial mapping.

Inferring histology-associated gene expression gradients in spatial transcriptomic studies

Spatially resolved transcriptomics has revolutionized RNA studies by aligning RNA abundance with tissue structure, enabling direct comparisons between histology and gene expression. Traditional approaches to identifying signature genes often involve preliminary data grouping, which can overlook subtle expression patterns in complex tissues. We present Spatial Gradient Screening, an algorithm which facilitates the supervised detection of histology-associated gene expression patterns without prior data grouping. Utilizing spatial transcriptomic data along with single-cell deconvolution from injured mouse cortex, and TCR-seq data from brain tumors, we compare our methodology to standard differential gene expression analysis. Our findings illustrate both the advantages and limitations of cluster-free detection of gene expression, offering more profound insights into the spatial architecture of transcriptomes. The algorithm is embedded in SPATA2, an open-source framework written in R, which provides a comprehensive set of tools for investigating gene expression within tissue.

Hypoxia-induced complement component 3 promotes aggressive tumor growth in the glioblastoma microenvironment

Glioblastoma (GBM) is the most aggressive form of glioma with a high rate of relapse despite intensive treatment. Tumor recurrence is tightly linked to radio-resistance, which in turn is associated with hypoxia. Here, we discovered a strong link between hypoxia and local complement signaling using publicly available bulk, single-cell, and spatially resolved transcriptomic data from patients with GBM. Complement component 3 (C3) and the receptor C3AR1 were both associated with aggressive disease and shorter survival in human glioma. In a genetically engineered mouse model of GBM, we found C3 specifically in hypoxic tumor areas. In vitro, we found an oxygen level-dependent increase in C3 and C3AR1 expression in response to hypoxia in several GBM and stromal cell types. C3a induced M2 polarization of cultured microglia and macrophages in a C3aR-dependent fashion. Targeting C3aR using the antagonist SB290157 prolonged survival of glioma-bearing mice both alone and in combination with radiotherapy while reducing the number of M2-polarized macrophages. Our findings establish a strong link between hypoxia and complement pathways in GBM and support a role of hypoxia-induced C3a/C3aR signaling as a contributor to glioma aggressiveness by regulating macrophage polarization.

Towards Digital Quantification of Ploidy from Pan-Cancer Digital Pathology Slides using Deep Learning

Abnormal DNA ploidy, found in numerous cancers, is increasingly being recognized as a contributor in driving chromosomal instability, genome evolution, and the heterogeneity that fuels cancer cell progression. Furthermore, it has been linked with poor prognosis of cancer patients. While next-generation sequencing can be used to approximate tumor ploidy, it has a high error rate for near-euploid states, a high cost and is time consuming, motivating alternative rapid quantification methods. We introduce PloiViT, a transformer-based model for tumor ploidy quantification that outperforms traditional machine learning models, enabling rapid and cost-effective quantification directly from pathology slides. We trained PloiViT on a dataset of fifteen cancer types from The Cancer Genome Atlas and validated its performance in multiple independent cohorts. Additionally, we explored the impact of self-supervised feature extraction on performance. PloiViT, using self-supervised features, achieved the lowest prediction error in multiple independent cohorts, exhibiting better generalization capabilities. Our findings demonstrate that PloiViT predicts higher ploidy values in aggressive cancer groups and patients with specific mutations, validating PloiViT potential as complementary for ploidy assessment to next-generation sequencing data. To further promote its use, we release our models as a user-friendly inference application and a Python package for easy adoption and use.

Distinct tumor-TAM interactions in IDH-stratified glioma microenvironments unveiled by single-cell and spatial transcriptomics

Tumor-associated macrophages (TAMs) residing in the tumor microenvironment (TME) are characterized by their pivotal roles in tumor progression, antitumor immunity, and TME remodeling. However, a thorough comparative characterization of tumor-TAM crosstalk across IDH-defined categories of glioma remains elusive, likely contributing to mixed outcomes in clinical trials. We delineated the phenotypic heterogeneity of TAMs across IDH-stratified gliomas. Notably, two TAM subsets with a mesenchymal phenotype were enriched in IDH-WT glioblastoma (GBM) and correlated with poorer patient survival and reduced response to anti-PD-1 immune checkpoint inhibitor (ICI). We proposed SLAMF9 receptor as a potential therapeutic target. Inference of gene regulatory networks identified PPARG, ELK1, and MXI1 as master transcription factors of mesenchymal BMD-TAMs. Our analyses of reciprocal tumor-TAM interactions revealed distinct crosstalk in IDH-WT tumors, including ANXA1-FPR1/3, FN1-ITGAVB1, VEGFA-NRP1, and TNFSF12-TNFRSF12A with known contribution to immunosuppression, tumor proliferation, invasion and TAM recruitment. Spatially resolved transcriptomics further elucidated the architectural organization of highlighted communications. Furthermore, we demonstrated significant upregulation of ANXA1, FN1, NRP1, and TNFRSF12A genes in IDH-WT tumors using bulk RNA-seq and RT-qPCR. Longitudinal expression analysis of candidate genes revealed no difference between primary and recurrent tumors indicating that the interactive network of malignant states with TAMs does not drastically change upon recurrence. Collectively, our study offers insights into the unique cellular composition and communication of TAMs in glioma TME, revealing novel vulnerabilities for therapeutic interventions in IDH-WT GBM.

Cell-specific cross-talk proteomics reveals cathepsin B signaling as a driver of glioblastoma malignancy near the subventricular zone

Glioblastoma (GBM) is the most prevalent and aggressive malignant primary brain tumor. GBM proximal to the lateral ventricles (LVs) is more aggressive, potentially because of subventricular zone contact. Despite this, cross-talk between GBM and neural stem/progenitor cells (NSC/NPCs) is not well understood. Using cell-specific proteomics, we show that LV-proximal GBM prevents neuronal maturation of NSCs through induction of senescence. In addition, GBM brain tumor-initiating cells (BTICs) increase expression of cathepsin B (CTSB) upon interaction with NPCs. Lentiviral knockdown and recombinant protein experiments reveal that both cell-intrinsic and soluble CTSB promote malignancy-associated phenotypes in BTICs. Soluble CTSB stalls neuronal maturation in NPCs while promoting senescence, providing a link between LV-tumor proximity and neurogenesis disruption. Last, we show LV-proximal CTSB up-regulation in patients, showing the relevance of this cross-talk in human GBM biology. These results demonstrate the value of proteomic analysis in tumor microenvironment research and provide direction for new therapeutic strategies in GBM.

Robust analysis of allele-specific copy number alterations from scRNA-seq data with XClone

Somatic copy number alterations (CNAs) are major mutations that contribute to the development and progression of various cancers. Despite a few computational methods proposed to detect CNAs from single-cell transcriptomic data, the technical sparsity of such data makes it challenging to identify allele-specific CNAs, particularly in complex clonal structures. In this study, we present a statistical method, XClone, that strengthens the signals of read depth and allelic imbalance by effective smoothing on cell neighborhood and gene coordinate graphs to detect haplotype-aware CNAs from scRNA-seq data. By applying XClone to multiple datasets with challenging compositions, we demonstrated its ability to robustly detect different types of allele-specific CNAs and potentially indicate whole genome duplication, therefore enabling the discovery of corresponding subclones and the dissection of their phenotypic impacts.

ARF4-mediated retrograde trafficking as a driver of chemoresistance in glioblastoma

BACKGROUND

Cellular functions hinge on the meticulous orchestration of protein transport, both spatially and temporally. Central to this process is retrograde trafficking, responsible for targeting proteins to the nucleus. Despite its link to many diseases, the implications of retrograde trafficking in glioblastoma (GBM) are still unclear.

METHODS

To identify genetic drivers of TMZ resistance, we conducted comprehensive CRISPR-knockout screening, revealing ADP-ribosylation factor 4 (ARF4), a regulator of retrograde trafficking, as a major contributor.

RESULTS

Suppressing ARF4 significantly enhanced TMZ sensitivity in GBM patient-derived xenograft (PDX) models, leading to improved survival rates (P < .01) in both primary and recurrent lines. We also observed that TMZ exposure stimulates ARF4-mediated retrograde trafficking. Proteomics analysis of GBM cells with varying levels of ARF4 unveiled the influence of this pathway on EGFR signaling, with increased nuclear trafficking of EGFR observed in cells with ARF4 overexpression and TMZ treatment. Additionally, spatially resolved RNA-sequencing of GBM patient tissues revealed substantial correlations between ARF4 and crucial nuclear EGFR (nEGFR) downstream targets, such as MYC, STAT1, and DNA-PK. Decreased activity of DNA-PK, a DNA repair protein downstream of nEGFR signaling that contributes to TMZ resistance, was observed in cells with suppressed ARF4 levels. Notably, treatment with DNA-PK inhibitor, KU-57788, in mice with a recurrent PDX line resulted in prolonged survival (P < .01), highlighting the promising therapeutic implications of targeting proteins reliant on ARF4-mediated retrograde trafficking.

CONCLUSIONS

Our findings demonstrate that ARF4-mediated retrograde trafficking contributes to the development of TMZ resistance, cementing this pathway as a viable strategy to overcome chemoresistance in GBM.

Glioblastoma Neurovascular Progenitor Orchestrates Tumor Cell Type Diversity

Glioblastoma (GBM) is the deadliest form of primary brain tumor with limited treatment options. Recent studies have profiled GBM tumor heterogeneity, revealing numerous axes of variation that explain the molecular and spatial features of the tumor. Here, we seek to bridge descriptive characterization of GBM cell type heterogeneity with the functional role of individual populations within the tumor. Our lens leverages a gene program-centric meta-atlas of published transcriptomic studies to identify commonalities between diverse tumors and cell types in order to decipher the mechanisms that drive them. This approach led to the discovery of a tumor-derived stem cell population with mixed vascular and neural stem cell features, termed a neurovascular progenitor (NVP). Following in situ validation and molecular characterization of NVP cells in GBM patient samples, we characterized their function in vivo. Genetic depletion of NVP cells resulted in altered tumor cell composition, fewer cycling cells, and extended survival, underscoring their critical functional role. Clonal analysis of primary patient tumors in a human organoid tumor transplantation system demonstrated that the NVP has dual potency, generating both neuronal and vascular tumor cells. Although NVP cells comprise a small fraction of the tumor, these clonal analyses demonstrated that they strongly contribute to the total number of cycling cells in the tumor and generate a defined subset of the whole tumor. This study represents a paradigm by which cell type-specific interrogation of tumor populations can be used to study functional heterogeneity and therapeutically targetable vulnerabilities of GBM.

Mass spectrometry imaging for spatially resolved multi-omics molecular mapping

The recent upswing in the integration of spatial multi-omics for conducting multidimensional information measurements is opening a new chapter in biological research. Mapping the landscape of various biomolecules including metabolites, proteins, nucleic acids, etc., and even deciphering their functional interactions and pathways is believed to provide a more holistic and nuanced exploration of the molecular intricacies within living systems. Mass spectrometry imaging (MSI) stands as a forefront technique for spatially mapping the metabolome, lipidome, and proteome within diverse tissue and cell samples. In this review, we offer a systematic survey delineating different MSI techniques for spatially resolved multi-omics analysis, elucidating their principles, capabilities, and limitations. Particularly, we focus on the advancements in methodologies aimed at augmenting the molecular sensitivity and specificity of MSI; and depict the burgeoning integration of MSI-based spatial metabolomics, lipidomics, and proteomics, encompassing the synergy with other imaging modalities. Furthermore, we offer speculative insights into the potential trajectory of MSI technology in the future.

A Self-Cascade Penetrating Brain Tumor Immunotherapy Mediated by Near-Infrared II Cell Membrane-Disrupting Nanoflakes via Detained Dendritic Cells

Immunotherapy can potentially suppress the highly aggressive glioblastoma (GBM) by promoting T lymphocyte infiltration. Nevertheless, the immune privilege phenomenon, coupled with the generally low immunogenicity of vaccines, frequently hampers the presence of lymphocytes within brain tumors, particularly in brain tumors. In this study, the membrane-disrupted polymer-wrapped CuS nanoflakes that can penetrate delivery to deep brain tumors via releasing the cell-cell interactions, facilitating the near-infrared II (NIR II) photothermal therapy, and detaining dendritic cells for a self-cascading immunotherapy are developed. By convection-enhanced delivery, membrane-disrupted amphiphilic polymer micelles (poly(methoxypoly(ethylene glycol)-benzoic imine-octadecane, mPEG-b-C18) with CuS nanoflakes enhances tumor permeability and resides in deep brain tumors. Under low-power NIR II irradiation (0.8 W/cm2), the intense heat generated by well-distributed CuS nanoflakes actuates the thermolytic efficacy, facilitating cell apoptosis and the subsequent antigen release. Then, the positively charged polymer after hydrolysis of the benzoic-imine bond serves as an antigen depot, detaining autologous tumor-associated antigens and presenting them to dendritic cells, ensuring sustained immune stimulation. This self-cascading penetrative immunotherapy amplifies the immune response to postoperative brain tumors but also enhances survival outcomes through effective brain immunotherapy.

Spatial Dissection of the Immune Landscape of Solid Tumors to Advance Precision Medicine

Chemotherapeutics, radiation, targeted therapeutics, and immunotherapeutics each demonstrate clinical benefits for a small subset of patients with solid malignancies. Immune cells infiltrating the tumor and the surrounding stroma play a critical role in shaping cancer progression and modulating therapy response. They do this by interacting with the other cellular and molecular components of the tumor microenvironment. Spatial multi-omics technologies are rapidly evolving. Currently, such technologies allow high-throughput RNA and protein profiling and retain geographical information about the tumor microenvironment cellular architecture and the functional phenotype of tumor, immune, and stromal cells. An in-depth spatial characterization of the heterogeneous tumor immune landscape can improve not only the prognosis but also the prediction of therapy response, directing cancer patients to more tailored and efficacious treatments. This review highlights recent advancements in spatial transcriptomics and proteomics profiling technologies and the ways these technologies are being applied for the dissection of the immune cell composition in solid malignancies in order to further both basic research in oncology and the implementation of precision treatments in the clinic.

Integration of spatial and single-cell data across modalities with weakly linked features

Although single-cell and spatial sequencing methods enable simultaneous measurement of more than one biological modality, no technology can capture all modalities within the same cell. For current data integration methods, the feasibility of cross-modal integration relies on the existence of highly correlated, a priori 'linked' features. We describe matching X-modality via fuzzy smoothed embedding (MaxFuse), a cross-modal data integration method that, through iterative coembedding, data smoothing and cell matching, uses all information in each modality to obtain high-quality integration even when features are weakly linked. MaxFuse is modality-agnostic and demonstrates high robustness and accuracy in the weak linkage scenario, achieving 20~70% relative improvement over existing methods under key evaluation metrics on benchmarking datasets. A prototypical example of weak linkage is the integration of spatial proteomic data with single-cell sequencing data. On two example analyses of this type, MaxFuse enabled the spatial consolidation of proteomic, transcriptomic and epigenomic information at single-cell resolution on the same tissue section.

Mapping myeloid cell function: Spatial diversity in tumor and neuronal microenvironment

In this issue of Cancer Cell, Zhong et al. explore the dual role of TREM2 in glioblastoma-associated myeloid cells, demonstrating its function in promoting inflammation at the tumor-neural interface and suppression within the tumor core, influenced by the local microenvironment. These findings open up promising prospects for advancements in neuro-oncological immunotherapy.

Identification of a gene expression signature of vascular invasion and recurrence in stage I lung adenocarcinoma via bulk and spatial transcriptomics

Microscopic vascular invasion (VI) is predictive of recurrence and benefit from lobectomy in stage I lung adenocarcinoma (LUAD) but is difficult to assess in resection specimens and cannot be accurately predicted prior to surgery. Thus, new biomarkers are needed to identify this aggressive subset of stage I LUAD tumors. To assess molecular and microenvironment features associated with angioinvasive LUAD we profiled 162 resected stage I tumors with and without VI by RNA-seq and explored spatial patterns of gene expression in a subset of 15 samples by high-resolution spatial transcriptomics (stRNA-seq). Despite the small size of invaded blood vessels, we identified a gene expression signature of VI from the bulk RNA-seq discovery cohort (n=103) and found that it was associated with VI foci, desmoplastic stroma, and high-grade patterns in our stRNA-seq data. We observed a stronger association with high-grade patterns from VI+ compared with VI- tumors. Using the discovery cohort, we developed a transcriptomic predictor of VI, that in an independent validation cohort (n=60) was associated with VI (AUROC=0.86; p=5.42×10-6) and predictive of recurrence-free survival (HR=1.98; p=0.024), even in VI- LUAD (HR=2.76; p=0.003). To determine our VI predictor's robustness to intra-tumor heterogeneity we used RNA-seq data from multi-region sampling of stage I LUAD cases in TRACERx, where the predictor scores showed high correlation (R=0.87, p<2.2×10-16) between two randomly sampled regions of the same tumor. Our study suggests that VI-associated gene expression changes are detectable beyond the site of intravasation and can be used to predict the presence of VI. This may enable the prediction of angioinvasive LUAD from biopsy specimens, allowing for more tailored medical and surgical management of stage I LUAD.

Spatial transcriptomics in cancer research and potential clinical impact: a narrative review

Spatial transcriptomics (ST) provides novel insights into the tumor microenvironment (TME). ST allows the quantification and illustration of gene expression profiles in the spatial context of tissues, including both the cancer cells and the microenvironment in which they are found. In cancer research, ST has already provided novel insights into cancer metastasis, prognosis, and immunotherapy responsiveness. The clinical precision oncology application of next-generation sequencing (NGS) and RNA profiling of tumors relies on bulk methods that lack spatial context. The ability to preserve spatial information is now possible, as it allows us to capture tumor heterogeneity and multifocality. In this narrative review, we summarize precision oncology, discuss tumor sequencing in the clinic, and review the available ST research methods, including seqFISH, MERFISH (Vizgen), CosMx SMI (NanoString), Xenium (10x), Visium (10x), Stereo-seq (STOmics), and GeoMx DSP (NanoString). We then review the current ST literature with a focus on solid tumors organized by tumor type. Finally, we conclude by addressing an important question: how will spatial transcriptomics ultimately help patients with cancer?

Spatial genomic, biochemical and cellular mechanisms underlying meningioma heterogeneity and evolution

Intratumor heterogeneity underlies cancer evolution and treatment resistance, but targetable mechanisms driving intratumor heterogeneity are poorly understood. Meningiomas are the most common primary intracranial tumors and are resistant to all medical therapies, and high-grade meningiomas have significant intratumor heterogeneity. Here we use spatial approaches to identify genomic, biochemical and cellular mechanisms linking intratumor heterogeneity to the molecular, temporal and spatial evolution of high-grade meningiomas. We show that divergent intratumor gene and protein expression programs distinguish high-grade meningiomas that are otherwise grouped together by current classification systems. Analyses of matched pairs of primary and recurrent meningiomas reveal spatial expansion of subclonal copy number variants associated with treatment resistance. Multiplexed sequential immunofluorescence and deconvolution of meningioma spatial transcriptomes using cell types from single-cell RNA sequencing show decreased immune infiltration, decreased MAPK signaling, increased PI3K-AKT signaling and increased cell proliferation, which are associated with meningioma recurrence. To translate these findings to preclinical models, we use CRISPR interference and lineage tracing approaches to identify combination therapies that target intratumor heterogeneity in meningioma cell co-cultures.

Localization of protoporphyrin IX during glioma-resection surgery via paired stimulated Raman histology and fluorescence microscopy

The most widely used fluorophore in glioma-resection surgery, 5-aminolevulinic acid (5-ALA), is thought to cause the selective accumulation of fluorescent protoporphyrin IX (PpIX) in tumour cells. Here we show that the clinical detection of PpIX can be improved via a microscope that performs paired stimulated Raman histology and two-photon excitation fluorescence microscopy (TPEF). We validated the technique in fresh tumour specimens from 115 patients with high-grade gliomas across four medical institutions. We found a weak negative correlation between tissue cellularity and the fluorescence intensity of PpIX across all imaged specimens. Semi-supervised clustering of the TPEF images revealed five distinct patterns of PpIX fluorescence, and spatial transcriptomic analyses of the imaged tissue showed that myeloid cells predominate in areas where PpIX accumulates in the intracellular space. Further analysis of external spatially resolved metabolomics, transcriptomics and RNA-sequencing datasets from glioblastoma specimens confirmed that myeloid cells preferentially accumulate and metabolize PpIX. Our findings question 5-ALA-induced fluorescence in glioma cells and show how 5-ALA and TPEF imaging can provide a window into the immune microenvironment of gliomas.

Single-cell and spatial transcriptomics analysis of human adrenal aging

OBJECTIVE

The human adrenal cortex comprises three functionally and structurally distinct layers that produce layer-specific steroid hormones. With aging, the human adrenal cortex undergoes functional and structural alteration or "adrenal aging", leading to the unbalanced production of steroid hormones. Given the marked species differences in adrenal biology, the underlying mechanisms of human adrenal aging have not been sufficiently studied. This study was designed to elucidate the mechanisms linking the functional and structural alterations of the human adrenal cortex.

METHODS

We conducted single-cell RNA sequencing and spatial transcriptomics analysis of the aged human adrenal cortex.

RESULTS

The data of this study suggest that the layer-specific alterations of multiple signaling pathways underlie the abnormal layered structure and layer-specific changes in steroidogenic cells. We also highlighted that macrophages mediate age-related adrenocortical cell inflammation and senescence.

CONCLUSIONS

This study is the first detailed analysis of the aged human adrenal cortex at single-cell resolution and helps to elucidate the mechanism of human adrenal aging, thereby leading to a better understanding of the pathophysiology of age-related disorders associated with adrenal aging.

Evidences of neurological injury caused by COVID-19 from glioma tissues and glioma organoids

INTRODUCTION

Despite the extensive neurological symptoms induced by COVID-19 and the identification of SARS-CoV-2 in post-mortem brain samples from COVID-19 patients months after death, the precise mechanisms of SARS-CoV-2 invasion into the central nervous system remain unclear due to the lack of research models.

METHODS

We collected glioma tissue samples from glioma patients who had a recent history of COVID-19 and examined the presence of the SARS-CoV-2 spike protein. Subsequently, spatial transcriptomic analyses were conducted on normal brain tissues, glioma tissues, and glioma tissues from glioma patients with recent COVID-19 history. Additionally, single-cell sequencing data from both glioma tissues and glioma organoids were collected and analyzed. Glioma organoids were utilized to evaluate the efficacy of potential COVID-19 blocking agents.

RESULTS

Glioma tissues from glioma patients with recent COVID-19 history exhibited the presence of the SARS-CoV-2 spike protein. Differences between glioma tissues from glioma patients who had a recent history of COVID-19 and healthy brain tissues primarily manifested in neuronal cells. Notably, neuronal cells within glioma tissues of COVID-19 history demonstrated heightened susceptibility to Alzheimer's disease, depression, and synaptic dysfunction, indicative of neuronal aberrations. Expressions of SARS-CoV-2 entry factors were confirmed in both glioma tissues and glioma organoids. Moreover, glioma organoids were susceptible to pseudo-SARS-CoV-2 infection and the infections could be partly blocked by the potential COVID-19 drugs.

CONCLUSIONS

Gliomas had inherent traits that render them susceptible to SARS-CoV-2 infection, leading to their representability of COVID-19 neurological symptoms. This established a biological foundation for the rationality and feasibility of utilization of glioma organoids as research and blocking drug testing model in SARS-CoV-2 infection within the central nervous system.

Multimodal decoding of human liver regeneration

The liver has a unique ability to regenerate1,2; however, in the setting of acute liver failure (ALF), this regenerative capacity is often overwhelmed, leaving emergency liver transplantation as the only curative option3-5. Here, to advance understanding of human liver regeneration, we use paired single-nucleus RNA sequencing combined with spatial profiling of healthy and ALF explant human livers to generate a single-cell, pan-lineage atlas of human liver regeneration. We uncover a novel ANXA2+ migratory hepatocyte subpopulation, which emerges during human liver regeneration, and a corollary subpopulation in a mouse model of acetaminophen (APAP)-induced liver regeneration. Interrogation of necrotic wound closure and hepatocyte proliferation across multiple timepoints following APAP-induced liver injury in mice demonstrates that wound closure precedes hepatocyte proliferation. Four-dimensional intravital imaging of APAP-induced mouse liver injury identifies motile hepatocytes at the edge of the necrotic area, enabling collective migration of the hepatocyte sheet to effect wound closure. Depletion of hepatocyte ANXA2 reduces hepatocyte growth factor-induced human and mouse hepatocyte migration in vitro, and abrogates necrotic wound closure following APAP-induced mouse liver injury. Together, our work dissects unanticipated aspects of liver regeneration, demonstrating an uncoupling of wound closure and hepatocyte proliferation and uncovering a novel migratory hepatocyte subpopulation that mediates wound closure following liver injury. Therapies designed to promote rapid reconstitution of normal hepatic microarchitecture and reparation of the gut-liver barrier may advance new areas of therapeutic discovery in regenerative medicine.

A Review of the Application of Spatial Transcriptomics in Neuroscience

Since spatial transcriptomics can locate and distinguish the gene expression of functional genes in special regions and tissue, it is important for us to investigate the brain development, the development mechanism of brain diseases, and the relationship between brain structure and function in Neuroscience (or Brain science). While previous studies have introduced the crucial spatial transcriptomic techniques and data analysis methods, there are few studies to comprehensively overview the key methods, data resources, and technological applications of spatial transcriptomics in Neuroscience. For these reasons, we first investigate several common spatial transcriptomic data analysis approaches and data resources. Second, we introduce the applications of the spatial transcriptomic data analysis approaches in Neuroscience. Third, we summarize the integrating spatial transcriptomics with other technologies in Neuroscience. Finally, we discuss the challenges and future research directions of spatial transcriptomics in Neuroscience.

A prognostic neural epigenetic signature in high-grade glioma

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

The Role of Mesenchymal Reprogramming in Malignant Clonal Evolution and Intra-Tumoral Heterogeneity in Glioblastoma

Glioblastoma (GBM) is the most common yet uniformly fatal adult brain cancer. Intra-tumoral molecular and cellular heterogeneities are major contributory factors to therapeutic refractoriness and futility in GBM. Molecular heterogeneity is represented through molecular subtype clusters whereby the proneural (PN) subtype is associated with significantly increased long-term survival compared to the highly resistant mesenchymal (MES) subtype. Furthermore, it is universally recognized that a small subset of GBM cells known as GBM stem cells (GSCs) serve as reservoirs for tumor recurrence and progression. The clonal evolution of GSC molecular subtypes in response to therapy drives intra-tumoral heterogeneity and remains a critical determinant of GBM outcomes. In particular, the intra-tumoral MES reprogramming of GSCs using current GBM therapies has emerged as a leading hypothesis for therapeutic refractoriness. Preventing the intra-tumoral divergent evolution of GBM toward the MES subtype via new treatments would dramatically improve long-term survival for GBM patients and have a significant impact on GBM outcomes. In this review, we examine the challenges of the role of MES reprogramming in the malignant clonal evolution of glioblastoma and provide future perspectives for addressing the unmet therapeutic need to overcome resistance in GBM.

Hypoxia-induced TREM1 promotes mesenchymal-like states of glioma stem cells via alternatively activating tumor-associated macrophages

The mesenchymal subtype of glioblastoma (GBM) cells characterized by aggressive invasion and therapeutic resistance is thought to be dependent on cell-intrinsic alteration and extrinsic cellular crosstalk. Tumor-associated macrophages (TAMs) are pivotal in tumor progression, chemo-resistance, angiogenesis, and stemness maintenance. However, the impact of TAMs on the shifts in glioma stem cells (GSCs) states remains largely uncovered. Herein, we showed that the triggering receptor expressed on myeloid cells-1 (TREM1) preferentially expressed by M2-like TAMs and induced GSCs into mesenchymal-like states by modulating the secretion of TGFβ2, which activated the TGFβR/SMAD2/3 signaling in GSCs. Furthermore, we demonstrated that TREM1 was transcriptionally regulated by HIF1a under the hypoxic environment and thus promoted an immunosuppressive type of TAMs via activating the TLR2/AKT/mTOR/c-MYC axis. Collectively, this study reveals that cellular communication between TAMs and GSCs through the TREM1-mediated TGFβ2/TGFβR axis is involved in the mesenchymal-like transitions of GSCs. Our study provides valuable insights into the regulatory mechanisms between the tumor immune microenvironment and the malignant characteristics of GBM, which can lead to potential novel strategies targeting TAMs for tumor control.

Spatial analysis of recurrent glioblastoma reveals perivascular niche organization

Tumor evolution is driven by genetic variation; however, it is the tumor microenvironment (TME) that provides the selective pressure contributing to evolution in cancer. Despite high histopathological heterogeneity within glioblastoma (GBM), the most aggressive brain tumor, the interactions between the genetically distinct GBM cells and the surrounding TME are not fully understood. To address this, we analyzed matched primary and recurrent GBM archival tumor tissues with imaging-based techniques aimed to simultaneously evaluate tumor tissues for the presence of hypoxic, angiogenic, and inflammatory niches, extracellular matrix (ECM) organization, TERT promoter mutational status, and several oncogenic amplifications on the same slide and location. We found that the relationships between genetic and TME diversity are different in primary and matched recurrent tumors. Interestingly, the texture of the ECM, identified by label-free reflectance imaging, was predictive of single-cell genetic traits present in the tissue. Moreover, reflectance of ECM revealed structured organization of the perivascular niche in recurrent GBM, enriched in immunosuppressive macrophages. Single-cell spatial transcriptomics further confirmed the presence of the niche-specific macrophage populations and identified interactions between endothelial cells, perivascular fibroblasts, and immunosuppressive macrophages. Our results underscore the importance of GBM tissue organization in tumor evolution and highlight genetic and spatial dependencies.

Hypoxia coordinates the spatial landscape of myeloid cells within glioblastoma to affect survival

Myeloid cells are highly prevalent in glioblastoma (GBM), existing in a spectrum of phenotypic and activation states. We now have limited knowledge of the tumor microenvironment (TME) determinants that influence the localization and the functions of the diverse myeloid cell populations in GBM. Here, we have utilized orthogonal imaging mass cytometry with single-cell and spatial transcriptomic approaches to identify and map the various myeloid populations in the human GBM tumor microenvironment (TME). Our results show that different myeloid populations have distinct and reproducible compartmentalization patterns in the GBM TME that is driven by tissue hypoxia, regional chemokine signaling, and varied homotypic and heterotypic cellular interactions. We subsequently identified specific tumor subregions in GBM, based on composition of identified myeloid cell populations, that were linked to patient survival. Our results provide insight into the spatial organization of myeloid cell subpopulations in GBM, and how this is predictive of clinical outcome.

Differential gene expression analysis of spatial transcriptomic experiments using spatial mixed models

Spatial transcriptomics (ST) assays represent a revolution in how the architecture of tissues is studied by allowing for the exploration of cells in their spatial context. A common element in the analysis is delineating tissue domains or "niches" followed by detecting differentially expressed genes to infer the biological identity of the tissue domains or cell types. However, many studies approach differential expression analysis by using statistical approaches often applied in the analysis of non-spatial scRNA data (e.g., two-sample t-tests, Wilcoxon's rank sum test), hence neglecting the spatial dependency observed in ST data. In this study, we show that applying linear mixed models with spatial correlation structures using spatial random effects effectively accounts for the spatial autocorrelation and reduces inflation of type-I error rate observed in non-spatial based differential expression testing. We also show that spatial linear models with an exponential correlation structure provide a better fit to the ST data as compared to non-spatial models, particularly for spatially resolved technologies that quantify expression at finer scales (i.e., single-cell resolution).

Identification of hypoxic macrophages in glioblastoma with therapeutic potential for vasculature normalization

Monocyte-derived tumor-associated macrophages (Mo-TAMs) intensively infiltrate diffuse gliomas with remarkable heterogeneity. Using single-cell transcriptomics, we chart a spatially resolved transcriptional landscape of Mo-TAMs across 51 patients with isocitrate dehydrogenase (IDH)-wild-type glioblastomas or IDH-mutant gliomas. We characterize a Mo-TAM subset that is localized to the peri-necrotic niche and skewed by hypoxic niche cues to acquire a hypoxia response signature. Hypoxia-TAM destabilizes endothelial adherens junctions by activating adrenomedullin paracrine signaling, thereby stimulating a hyperpermeable neovasculature that hampers drug delivery in glioblastoma xenografts. Accordingly, genetic ablation or pharmacological blockade of adrenomedullin produced by Hypoxia-TAM restores vascular integrity, improves intratumoral concentration of the anti-tumor agent dabrafenib, and achieves combinatorial therapeutic benefits. Increased proportion of Hypoxia-TAM or adrenomedullin expression is predictive of tumor vessel hyperpermeability and a worse prognosis of glioblastoma. Our findings highlight Mo-TAM diversity and spatial niche-steered Mo-TAM reprogramming in diffuse gliomas and indicate potential therapeutics targeting Hypoxia-TAM to normalize tumor vasculature.

Integrative spatial analysis reveals a multi-layered organization of glioblastoma

Glioma contains malignant cells in diverse states. Here, we combine spatial transcriptomics, spatial proteomics, and computational approaches to define glioma cellular states and uncover their organization. We find three prominent modes of organization. First, gliomas are composed of small local environments, each typically enriched with one major cellular state. Second, specific pairs of states preferentially reside in proximity across multiple scales. This pairing of states is consistent across tumors. Third, these pairwise interactions collectively define a global architecture composed of five layers. Hypoxia appears to drive the layers, as it is associated with a long-range organization that includes all cancer cell states. Accordingly, tumor regions distant from any hypoxic/necrotic foci and tumors that lack hypoxia such as low-grade IDH-mutant glioma are less organized. In summary, we provide a conceptual framework for the organization of cellular states in glioma, highlighting hypoxia as a long-range tissue organizer.