Antioxidant network-based signatures cluster glioblastoma into distinct redox-resistant phenotypes.

Introduction: Aberrant reactive oxygen species (ROS) production is one of the hallmarks of cancer. During their growth and dissemination, cancer cells control redox signaling to support protumorigenic pathways. As a consequence, cancer cells become reliant on major antioxidant systems to maintain a balanced redox tone, while avoiding excessive oxidative stress and cell death. This concept appears especially relevant in the context of glioblastoma multiforme (GBM), the most aggressive form of brain tumor characterized by significant heterogeneity, which contributes to treatment resistance and tumor recurrence. From this viewpoint, this study aims to investigate whether gene regulatory networks can effectively capture the diverse redox states associated with the primary phenotypes of GBM. Methods: In this study, we utilized publicly available GBM datasets along with proprietary bulk sequencing data. Employing computational analysis and bioinformatics tools, we stratified GBM based on their antioxidant capacities and evaluated the distinctive functionalities and prognostic values of distinct transcriptional networks in silico. Results: We established three distinct transcriptional co-expression networks and signatures (termed clusters C1, C2, and C3) with distinct antioxidant potential in GBM cancer cells. Functional analysis of each cluster revealed that C1 exhibits strong antioxidant properties, C2 is marked with a discrepant inflammatory trait and C3 was identified as the cluster with the weakest antioxidant capacity. Intriguingly, C2 exhibited a strong correlation with the highly aggressive mesenchymal subtype of GBM. Furthermore, this cluster holds substantial prognostic importance: patients with higher gene set variation analysis (GSVA) scores of the C2 signature exhibited adverse outcomes in overall and progression-free survival. Conclusion: In summary, we provide a set of transcriptional signatures that unveil the antioxidant potential of GBM, offering a promising prognostic application and a guide for therapeutic strategies in GBM therapy.

Recent advancements in tumour microenvironment landscaping for target selection and response prediction in immune checkpoint therapies achieved through spatial protein multiplexing analysis.

Immune checkpoint therapies have significantly advanced cancer treatment. Nevertheless, the high costs and potential adverse effects associated with these therapies highlight the need for better predictive biomarkers to identify patients who are most likely to benefit from treatment. Unfortunately, the existing biomarkers are insufficient to identify such patients. New high-dimensional spatial technologies have emerged as a valuable tool for discovering novel biomarkers by analysing multiple protein markers at a single-cell resolution in tissue samples. These technologies provide a more comprehensive map of tissue composition, cell functionality, and interactions between different cell types in the tumour microenvironment. In this review, we provide an overview of how spatial protein-based multiplexing technologies have fuelled biomarker discovery and advanced the field of immunotherapy. In particular, we will focus on how these technologies contributed to (i) characterise the tumour microenvironment, (ii) understand the role of tumour heterogeneity, (iii) study the interplay of the immune microenvironment and tumour progression, (iv) discover biomarkers for immune checkpoint therapies (v) suggest novel therapeutic strategies.

Patient-derived glioblastoma organoids reflect tumor heterogeneity and treatment sensitivity.

Background: Treatment resistance and tumor relapse are the primary causes of mortality in glioblastoma (GBM), with intratumoral heterogeneity playing a significant role. Patient-derived cancer organoids have emerged as a promising model capable of recapitulating tumor heterogeneity. Our objective was to develop patient-derived GBM organoids (PGO) to investigate treatment response and resistance. Methods: GBM samples were used to generate PGOs and analyzed using whole-exome sequencing (WES) and single-cell karyotype sequencing. PGOs were subjected to temozolomide (TMZ) to assess viability. Bulk RNA sequencing was performed before and after TMZ. Results: WES analysis on individual PGOs cultured for 3 time points (1-3 months) showed a high inter-organoid correlation and retention of genetic variants (range 92.3%-97.7%). Most variants were retained in the PGO compared to the tumor (range 58%-90%) and exhibited similar copy number variations. Single-cell karyotype sequencing demonstrated preservation of genetic heterogeneity. Single-cell multiplex immunofluorescence showed maintenance of cellular states. TMZ treatment of PGOs showed a differential response, which largely corresponded with MGMT promoter methylation. Differentially expressed genes before and after TMZ revealed an upregulation of the JNK kinase pathway. Notably, the combination treatment of a JNK kinase inhibitor and TMZ demonstrated a synergistic effect. Conclusions: Overall, these findings demonstrate the robustness of PGOs in retaining the genetic and phenotypic heterogeneity in culture and the application of measuring clinically relevant drug responses. These data show that PGOs have the potential to be further developed into avatars for personalized adaptive treatment selection and actionable drug target discovery and as a platform to study GBM biology.

Single-cell profiling and zebrafish avatars reveal LGALS1 as immunomodulating target in glioblastoma.

Glioblastoma (GBM) remains the most malignant primary brain tumor, with a median survival rarely exceeding 2 years. Tumor heterogeneity and an immunosuppressive microenvironment are key factors contributing to the poor response rates of current therapeutic approaches. GBM-associated macrophages (GAMs) often exhibit immunosuppressive features that promote tumor progression. However, their dynamic interactions with GBM tumor cells remain poorly understood. Here, we used patient-derived GBM stem cell cultures and combined single-cell RNA sequencing of GAM-GBM co-cultures and real-time in vivo monitoring of GAM-GBM interactions in orthotopic zebrafish xenograft models to provide insight into the cellular, molecular, and spatial heterogeneity. Our analyses revealed substantial heterogeneity across GBM patients in GBM-induced GAM polarization and the ability to attract and activate GAMs-features that correlated with patient survival. Differential gene expression analysis, immunohistochemistry on original tumor samples, and knock-out experiments in zebrafish subsequently identified LGALS1 as a primary regulator of immunosuppression. Overall, our work highlights that GAM-GBM interactions can be studied in a clinically relevant way using co-cultures and avatar models, while offering new opportunities to identify promising immune-modulating targets.

The tumor micro-environment in pediatric glioma: friend or foe?

Brain tumors are the leading cause of morbidity and mortality related to cancer in children, where high-grade glioma harbor the worst prognosis. It has become obvious that pediatric glioma differs significantly from their adult counterparts, rendering extrapolations difficult. Curative options for several types of glioma are lacking, albeit ongoing research efforts and clinical trials. As already proven in the past, inter- and intratumoral heterogeneity plays an important role in the resistance to therapy and thus implicates morbidity and mortality for these patients. However, while less studied, the tumor micro-environment (TME) adds another level of heterogeneity. Knowledge gaps exist on how the TME interacts with the tumor cells and how the location of the various cell types in the TME influences tumor growth and the response to treatment. Some studies identified the presence of several (immune) cell types as prognostic factors, but often lack a deeper understanding of the underlying mechanisms, possibly leading to contradictory findings. Although the TME in pediatric glioma is regarded as "cold", several treatment options are emerging, with the TME being the primary target of treatment. Therefore, it is crucial to study the TME of pediatric glioma, so that the interactions between TME, tumoral cells and therapeutics can be better understood before, during and after treatment. In this review, we provide an overview of the available insights into the composition and role of the TME across different types of pediatric glioma. Moreover, where possible, we provide a framework on how a particular TME may influence responses to conventional- and/or immunotherapy.

TMEM106B is a receptor mediating ACE2-independent SARS-CoV-2 cell entry.

SARS-CoV-2 is associated with broad tissue tropism, a characteristic often determined by the availability of entry receptors on host cells. Here, we show that TMEM106B, a lysosomal transmembrane protein, can serve as an alternative receptor for SARS-CoV-2 entry into angiotensin-converting enzyme 2 (ACE2)-negative cells. Spike substitution E484D increased TMEM106B binding, thereby enhancing TMEM106B-mediated entry. TMEM106B-specific monoclonal antibodies blocked SARS-CoV-2 infection, demonstrating a role of TMEM106B in viral entry. Using X-ray crystallography, cryogenic electron microscopy (cryo-EM), and hydrogen-deuterium exchange mass spectrometry (HDX-MS), we show that the luminal domain (LD) of TMEM106B engages the receptor-binding motif of SARS-CoV-2 spike. Finally, we show that TMEM106B promotes spike-mediated syncytium formation, suggesting a role of TMEM106B in viral fusion. Together, our findings identify an ACE2-independent SARS-CoV-2 infection mechanism that involves cooperative interactions with the receptors heparan sulfate and TMEM106B.

Transcriptional and spatial profiling of the kidney allograft unravels a central role for FcyRIII+ innate immune cells in rejection.

Rejection remains the main cause of premature graft loss after kidney transplantation, despite the use of potent immunosuppression. This highlights the need to better understand the composition and the cell-to-cell interactions of the alloreactive inflammatory infiltrate. Here, we performed droplet-based single-cell RNA sequencing of 35,152 transcriptomes from 16 kidney transplant biopsies with varying phenotypes and severities of rejection and without rejection, and identified cell-type specific gene expression signatures for deconvolution of bulk tissue. A specific association was identified between recipient-derived FCGR3A+ monocytes, FCGR3A+ NK cells and the severity of intragraft inflammation. Activated FCGR3A+ monocytes overexpressed CD47 and LILR genes and increased paracrine signaling pathways promoting T cell infiltration. FCGR3A+ NK cells overexpressed FCRL3, suggesting that antibody-dependent cytotoxicity is a central mechanism of NK-cell mediated graft injury. Multiplexed immunofluorescence using 38 markers on 18 independent biopsy slides confirmed this role of FcγRIII+ NK and FcγRIII+ nonclassical monocytes in antibody-mediated rejection, with specificity to the glomerular area. These results highlight the central involvement of innate immune cells in the pathogenesis of allograft rejection and identify several potential therapeutic targets that might improve allograft longevity.

Single-cell molecular profiling using ex vivo functional readouts fuels precision oncology in glioblastoma.

BACKGROUND: Functional profiling of freshly isolated glioblastoma (GBM) cells is being evaluated as a next-generation method for precision oncology. While promising, its success largely depends on the method to evaluate treatment activity which requires sufficient resolution and specificity. METHODS: Here, we describe the 'precision oncology by single-cell profiling using ex vivo readouts of functionality' (PROSPERO) assay to evaluate the intrinsic susceptibility of high-grade brain tumor cells to respond to therapy. Different from other assays, PROSPERO extends beyond life/death screening by rapidly evaluating acute molecular drug responses at single-cell resolution. RESULTS: The PROSPERO assay was developed by correlating short-term single-cell molecular signatures using mass cytometry by time-of-flight (CyTOF) to long-term cytotoxicity readouts in representative patient-derived glioblastoma cell cultures (n = 14) that were exposed to radiotherapy and the small-molecule p53/MDM2 inhibitor AMG232. The predictive model was subsequently projected to evaluate drug activity in freshly resected GBM samples from patients (n = 34). Here, PROSPERO revealed an overall limited capacity of tumor cells to respond to therapy, as reflected by the inability to induce key molecular markers upon ex vivo treatment exposure, while retaining proliferative capacity, insights that were validated in patient-derived xenograft (PDX) models. This approach also allowed the investigation of cellular plasticity, which in PDCLs highlighted therapy-induced proneural-to-mesenchymal (PMT) transitions, while in patients' samples this was more heterogeneous. CONCLUSION: PROSPERO provides a precise way to evaluate therapy efficacy by measuring molecular drug responses using specific biomarker changes in freshly resected brain tumor samples, in addition to providing key functional insights in cellular behavior, which may ultimately complement standard, clinical biomarker evaluations.

Multiomics and spatial mapping characterizes human CD8+ T cell states in cancer.

Clinically relevant immunological biomarkers that discriminate between diverse hypofunctional states of tumor-associated CD8+ T cells remain disputed. Using multiomics analysis of CD8+ T cell features across multiple patient cohorts and tumor types, we identified tumor niche-dependent exhausted and other types of hypofunctional CD8+ T cell states. CD8+ T cells in "supportive" niches, like melanoma or lung cancer, exhibited features of tumor reactivity-driven exhaustion (CD8+ TEX). These included a proficient effector memory phenotype, an expanded T cell receptor (TCR) repertoire linked to effector exhaustion signaling, and a cancer-relevant T cell-activating immunopeptidome composed of largely shared cancer antigens or neoantigens. In contrast, "nonsupportive" niches, like glioblastoma, were enriched for features of hypofunctionality distinct from canonical exhaustion. This included immature or insufficiently activated T cell states, high wound healing signatures, nonexpanded TCR repertoires linked to anti-inflammatory signaling, high T cell-recognizable self-epitopes, and an antiproliferative state linked to stress or prodeath responses. In situ spatial mapping of glioblastoma highlighted the prevalence of dysfunctional CD4+:CD8+ T cell interactions, whereas ex vivo single-cell secretome mapping of glioblastoma CD8+ T cells confirmed negligible effector functionality and a promyeloid, wound healing-like chemokine profile. Within immuno-oncology clinical trials, anti-programmed cell death protein 1 (PD-1) immunotherapy facilitated glioblastoma's tolerogenic disparities, whereas dendritic cell (DC) vaccines partly corrected them. Accordingly, recipients of a DC vaccine for glioblastoma had high effector memory CD8+ T cells and evidence of antigen-specific immunity. Collectively, we provide an atlas for assessing different CD8+ T cell hypofunctional states in immunogenic versus nonimmunogenic cancers.

Reduced Levels of Misfolded and Aggregated Mutant p53 by Proteostatic Activation.

In malignant cancer, excessive amounts of mutant p53 often lead to its aggregation, a feature that was recently identified as druggable. Here, we describe that induction of a heat shock-related stress response mediated by Foldlin, a small-molecule tool compound, reduces the protein levels of misfolded/aggregated mutant p53, while contact mutants or wild-type p53 remain largely unaffected. Foldlin also prevented the formation of stress-induced p53 nuclear inclusion bodies. Despite our inability to identify a specific molecular target, Foldlin also reduced protein levels of aggregating SOD1 variants. Finally, by screening a library of 778 FDA-approved compounds for their ability to reduce misfolded mutant p53, we identified the proteasome inhibitor Bortezomib with similar cellular effects as Foldlin. Overall, the induction of a cellular heat shock response seems to be an effective strategy to deal with pathological protein aggregation. It remains to be seen however, how this strategy can be translated to a clinical setting.

ALK Amplification and Rearrangements Are Recurrent Targetable Events in Congenital and Adult Glioblastoma.

PURPOSE: Anaplastic lymphoma kinase (ALK) aberrations have been identified in pediatric-type infant gliomas, but their occurrence across age groups, functional effects, and treatment response has not been broadly established. EXPERIMENTAL DESIGN: We performed a comprehensive analysis of ALK expression and genomic aberrations in both newly generated and retrospective data from 371 glioblastomas (156 adult, 205 infant/pediatric, and 10 congenital) with in vitro and in vivo validation of aberrations. RESULTS: ALK aberrations at the protein or genomic level were detected in 12% of gliomas (45/371) in a wide age range (0-80 years). Recurrent as well as novel ALK fusions (LRRFIP1-ALK, DCTN1-ALK, PRKD3-ALK) were present in 50% (5/10) of congenital/infant, 1.4% (3/205) of pediatric, and 1.9% (3/156) of adult GBMs. ALK fusions were present as the only candidate driver in congenital/infant GBMs and were sometimes focally amplified. In contrast, adult ALK fusions co-occurred with other oncogenic drivers. No activating ALK mutations were identified in any age group. Novel and recurrent ALK rearrangements promoted STAT3 and ERK1/2 pathways and transformation in vitro and in vivo. ALK-fused GBM cellular and mouse models were responsive to ALK inhibitors, including in patient cells derived from a congenital GBM. Relevant to the treatment of infant gliomas, we showed that ALK protein appears minimally expressed in the forebrain at perinatal stages, and no gross effects on perinatal brain development were seen in pregnant mice treated with the ALK inhibitor ceritinib. CONCLUSIONS: These findings support use of brain-penetrant ALK inhibitors in clinical trials across infant, pediatric, and adult GBMs. See related commentary by Mack and Bertrand, p. 2567.

Severe COVID-19 patients display hyper-activated NK cells and NK cell-platelet aggregates.

COVID-19 is characterised by a broad spectrum of clinical and pathological features. Natural killer (NK) cells play an important role in innate immune responses to viral infections. Here, we analysed the phenotype and activity of NK cells in the blood of COVID-19 patients using flow cytometry, single-cell RNA-sequencing (scRNA-seq), and a cytotoxic killing assay. In the plasma of patients, we quantified the main cytokines and chemokines. Our cohort comprises COVID-19 patients hospitalised in a low-care ward unit (WARD), patients with severe COVID-19 disease symptoms hospitalised in intensive care units (ICU), and post-COVID-19 patients, who were discharged from hospital six weeks earlier. NK cells from hospitalised COVID-19 patients displayed an activated phenotype with substantial differences between WARD and ICU patients and the timing when samples were taken post-onset of symptoms. While NK cells from COVID-19 patients at an early stage of infection showed increased expression of the cytotoxic molecules perforin and granzyme A and B, NK cells from patients at later stages of COVID-19 presented enhanced levels of IFN-γ and TNF-α which were measured ex vivo in the absence of usual in vitro stimulation. These activated NK cells were phenotyped as CD49a+CD69a+CD107a+ cells, and their emergence in patients correlated to the number of neutrophils, and plasma IL-15, a key cytokine in NK cell activation. Despite lower amounts of cytotoxic molecules in NK cells of patients with severe symptoms, majority of COVID-19 patients displayed a normal cytotoxic killing of Raji tumour target cells. In vitro stimulation of patients blood cells by IL-12+IL-18 revealed a defective IFN-γ production in NK cells of ICU patients only, indicative of an exhausted phenotype. ScRNA-seq revealed, predominantly in patients with severe COVID-19 disease symptoms, the emergence of an NK cell subset with a platelet gene signature that we identified by flow and imaging cytometry as aggregates of NK cells with CD42a+CD62P+ activated platelets. Post-COVID-19 patients show slow recovery of NK cell frequencies and phenotype. Our study points to substantial changes in NK cell phenotype during COVID-19 disease and forms a basis to explore the contribution of platelet-NK cell aggregates to antiviral immunity against SARS-CoV-2 and disease pathology.

Functional Precision Oncology: The Next Frontier to Improve Glioblastoma Outcome?

Glioblastoma remains the most malignant and intrinsically resistant brain tumour in adults. Despite intensive research over the past few decades, through which numerous potentially druggable targets have been identified, virtually all clinical trials of the past 20 years have failed to improve the outcome for the vast majority of GBM patients. The observation that small subgroups of patients displayed a therapeutic response across several unsuccessful clinical trials suggests that the GBM patient population probably consists of multiple subgroups that probably all require a distinct therapeutic approach. Due to extensive inter- and intratumoral heterogeneity, assigning the right therapy to each patient remains a major challenge. Classically, bulk genetic profiling would be used to identify suitable therapies, although the success of this approach remains limited due to tumor heterogeneity and the absence of direct relationships between mutations and therapy responses in GBM. An attractive novel strategy aims at implementing methods for functional precision oncology, which refers to the evaluation of treatment efficacies and vulnerabilities of (ex vivo) living tumor cells in a highly personalized way. Such approaches are currently being implemented for other cancer types by providing rapid, translatable information to guide patient-tailored therapeutic selections. In this review, we discuss the current state of the art of transforming technologies, tools and challenges for functional precision oncology and how these could improve therapy selection for GBM patients.

Next-Generation Pathology Using Multiplexed Immunohistochemistry: Mapping Tissue Architecture at Single-Cell Level.

Single-cell omics aim at charting the different types and properties of all cells in the human body in health and disease. Over the past years, myriads of cellular phenotypes have been defined by methods that mostly required cells to be dissociated and removed from their original microenvironment, thus destroying valuable information about their location and interactions. Growing insights, however, are showing that such information is crucial to understand complex disease states. For decades, pathologists have interpreted cells in the context of their tissue using low-plex antibody- and morphology-based methods. Novel technologies for multiplexed immunohistochemistry are now rendering it possible to perform extended single-cell expression profiling using dozens of protein markers in the spatial context of a single tissue section. The combination of these novel technologies with extended data analysis tools allows us now to study cell-cell interactions, define cellular sociology, and describe detailed aberrations in tissue architecture, as such gaining much deeper insights in disease states. In this review, we provide a comprehensive overview of the available technologies for multiplexed immunohistochemistry, their advantages and challenges. We also provide the principles on how to interpret high-dimensional data in a spatial context. Similar to the fact that no one can just "read" a genome, pathological assessments are in dire need of extended digital data repositories to bring diagnostics and tissue interpretation to the next level.

Mapping the Immune Landscape in Metastatic Melanoma Reveals Localized Cell-Cell Interactions That Predict Immunotherapy Response.

While immune checkpoint-based immunotherapy (ICI) shows promising clinical results in patients with cancer, only a subset of patients responds favorably. Response to ICI is dictated by complex networks of cellular interactions between malignant and nonmalignant cells. Although insights into the mechanisms that modulate the pivotal antitumoral activity of cytotoxic T cells (Tcy) have recently been gained, much of what has been learned is based on single-cell analyses of dissociated tumor samples, resulting in a lack of critical information about the spatial distribution of relevant cell types. Here, we used multiplexed IHC to spatially characterize the immune landscape of metastatic melanoma from responders and nonresponders to ICI. Such high-dimensional pathology maps showed that Tcy gradually evolve toward an exhausted phenotype as they approach and infiltrate the tumor. Moreover, a key cellular interaction network functionally linked Tcy and PD-L1+ macrophages. Mapping the respective spatial distributions of these two cell populations predicted response to anti-PD-1 immunotherapy with high confidence. These results suggest that baseline measurements of the spatial context should be integrated in the design of predictive biomarkers to identify patients likely to benefit from ICI. SIGNIFICANCE: This study shows that spatial characterization can address the challenge of finding efficient biomarkers, revealing that localization of macrophages and T cells in melanoma predicts patient response to ICI. See related commentary by Smalley and Smalley, p. 3198.

Immunogenic cell death and its therapeutic or prognostic potential in high-grade glioma.

Immunogenic cell death (ICD) has emerged as a key component of therapy-induced anti-tumor immunity. Over the past few years, ICD was found to play a pivotal role in a wide variety of novel and existing treatment modalities. The clinical application of these techniques in cancer treatment is still in its infancy. Glioblastoma (GBM) is the most lethal primary brain tumor with a dismal prognosis despite maximal therapy. The development of new therapies in this aggressive type of tumors remains highly challenging partially due to the cold tumor immune environment. GBM could therefore benefit from ICD-based therapies stimulating the anti-tumor immune response. In what follows, we will describe the mechanisms behind ICD and the ICD-based (pre)clinical advances in anticancer therapies focusing on GBM.

Multiplexed Immunohistochemistry and Digital Pathology as the Foundation for Next-Generation Pathology in Melanoma: Methodological Comparison and Future Clinical Applications.

The state-of-the-art for melanoma treatment has recently witnessed an enormous revolution, evolving from a chemotherapeutic, "one-drug-for-all" approach, to a tailored molecular- and immunological-based approach with the potential to make personalized therapy a reality. Nevertheless, methods still have to improve a lot before these can reliably characterize all the tumoral features that make each patient unique. While the clinical introduction of next-generation sequencing has made it possible to match mutational profiles to specific targeted therapies, improving response rates to immunotherapy will similarly require a deep understanding of the immune microenvironment and the specific contribution of each component in a patient-specific way. Recent advancements in artificial intelligence and single-cell profiling of resected tumor samples are paving the way for this challenging task. In this review, we provide an overview of the state-of-the-art in artificial intelligence and multiplexed immunohistochemistry in pathology, and how these bear the potential to improve diagnostics and therapy matching in melanoma. A major asset of in-situ single-cell profiling methods is that these preserve the spatial distribution of the cells in the tissue, allowing researchers to not only determine the cellular composition of the tumoral microenvironment, but also study tissue sociology, making inferences about specific cell-cell interactions and visualizing distinctive cellular architectures - all features that have an impact on anti-tumoral response rates. Despite the many advantages, the introduction of these approaches requires the digitization of tissue slides and the development of standardized analysis pipelines which pose substantial challenges that need to be addressed before these can enter clinical routine.