Glioma progression is shaped by genetic evolution and microenvironment interactions

AllergoOncology: Biomarkers and refined classification for research in the allergy and glioma nexus-A joint EAACI-EANO position paper

Epidemiological studies have explored the relationship between allergic diseases and cancer risk or prognosis in AllergoOncology. Some studies suggest an inverse association, but uncertainties remain, including in IgE-mediated diseases and glioma. Allergic disease stems from a Th2-biased immune response to allergens in predisposed atopic individuals. Allergic disorders vary in phenotype, genotype and endotype, affecting their pathophysiology. Beyond clinical manifestation and commonly used clinical markers, there is ongoing research to identify novel biomarkers for allergy diagnosis, monitoring, severity assessment and treatment. Gliomas, the most common and diverse brain tumours, have in parallel undergone changes in classification over time, with specific molecular biomarkers defining glioma subtypes. Gliomas exhibit a complex tumour-immune interphase and distinct immune microenvironment features. Immunotherapy and targeted therapy hold promise for primary brain tumour treatment, but require more specific and effective approaches. Animal studies indicate allergic airway inflammation may delay glioma progression. This collaborative European Academy of Allergy and Clinical Immunology (EAACI) and European Association of Neuro-Oncology (EANO) Position Paper summarizes recent advances and emerging biomarkers for refined allergy and adult-type diffuse glioma classification to inform future epidemiological and clinical studies. Future research is needed to enhance our understanding of immune-glioma interactions to ultimately improve patient prognosis and survival.

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.

A longer time to relapse is associated with a larger increase in differences between paired primary and recurrent IDH wild-type glioblastomas at both the transcriptomic and genomic levels

Glioblastoma (GBM) is the most common malignant brain tumor in adults, which remains incurable and often recurs rapidly after initial therapy. While large efforts have been dedicated to uncover genomic/transcriptomic alternations associated with the recurrence of GBMs, the evolutionary trajectories of matched pairs of primary and recurrent (P-R) GBMs remain largely elusive. It remains challenging to identify genes associated with time to relapse (TTR) and construct a stable and effective prognostic model for predicting TTR of primary GBM patients. By integrating RNA-sequencing and genomic data from multiple datasets of patient-matched longitudinal GBMs of isocitrate dehydrogenase wild-type (IDH-wt), here we examined the associations of TTR with heterogeneities between paired P-R GBMs in gene expression profiles, tumor mutation burden (TMB), and microenvironment. Our results revealed a positive correlation between TTR and transcriptomic/genomic differences between paired P-R GBMs, higher percentages of non-mesenchymal-to-mesenchymal transition and mesenchymal subtype for patients with a short TTR than for those with a long TTR, a high correlation between paired P-R GBMs in gene expression profiles and TMB, and a negative correlation between the fitting level of such a paired P-R GBM correlation and TTR. According to these observations, we identified 55 TTR-associated genes and thereby constructed a seven-gene (ZSCAN10, SIGLEC14, GHRHR, TBX15, TAS2R1, CDKL1, and CD101) prognostic model for predicting TTR of primary IDH-wt GBM patients using univariate/multivariate Cox regression analyses. The risk scores estimated by the model were significantly negatively correlated with TTR in the training set and two independent testing sets. The model also segregated IDH-wt GBM patients into two groups with significantly divergent progression-free survival outcomes and showed promising performance for predicting 1-, 2-, and 3-year progression-free survival rates in all training and testing sets. Our findings provide new insights into the molecular understanding of GBM progression at recurrence and potential targets for therapeutic treatments.

Villosol reverses 5-FU resistance in colorectal cancer by inhibiting the CDKN2A gene regulated TP53-PI3K/Akt signaling axis

ETHNOPHARMACOLOGICAL RELEVANCE

Patrinia villosa (Juss.) (PV) is the drug of choice in traditional Chinese medicine for the treatment of colorectal cancer (CRC) and has achieved reliable efficacy in clinic. Villosol is the active ingredient in PV. However, the molecular mechanism by which Villosol reverses chemoresistance in CRC remains unclear.

AIM OF THE STUDY

Analysis of the molecular mechanism by which Villosol, the active ingredient of PV, reverses CRC/5-FU resistance through modulation of the CDKN2A gene was validated by network pharmacology techniques and experiments.

MATERIALS AND METHODS

We identified CDKN2A as a gene associated with 5-FU resistance through gene chip analysis. Next, we conducted a series of functional analyses in cell lines, animal samples, and xenograft models to investigate the role, clinical significance, and abnormal regulatory mechanisms of CDKN2A in 5-FU resistance in CRC. In addition, we screened and obtained a raw ingredient called Villosol, which targets CDKN2A, and investigated its pharmacological effects.

RESULTS

Analysis of CRC cells and animal samples showed that the upregulation of CDKN2A expression was strongly associated with 5-FU resistance. CRC cells overexpressing CDKN2A showed reduced sensitivity to 5-FU and enhanced tumor biology in vitro. Inhibition of aberrant activation of CDKN2A enhances the expression of TP53. Mechanistically, overexpression of CDKN2A activates the PI3K/Akt pathway and induces resistance to 5-FU. Villosol inhibited CDKN2A, and CRC/5-FU cells regained sensitivity to 5-FU. Villosol effectively reverses 5-FU resistance through the CDKN2A-TP53-PI3K/Akt axis.

CONCLUSION

Changes in CDKN2A gene expression can be used to predict the response of CRC patients to 5-FU therapy. Additionally, inhibiting CDKN2A activation with Villosol may present a new approach to overcoming 5-FU resistance in clinical settings.

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

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

Integrated Proteogenomics Uncover Mechanisms of Glioblastoma Evolution, Pointing to Novel Therapeutic Targets

Nearly all glioblastoma (GBM) patients relapse following standard treatment and eventually succumb to disease. While large-scale, integrated multiomic studies have tremendously advanced the understanding of primary GBM at the cellular and molecular level, the posttherapeutic trajectory and biological properties of recurrent GBM remain poorly understood. This knowledge gap was addressed in a recent Cancer Cell article in which Kim and colleagues report on a highly integrative proteogenomic analysis performed on 123 matched primary and recurrent GBMs that uncovered a dramatic evolutionary shift from a proliferative state at initial diagnosis to the activation of neuronal and synaptogenic pathways at recurrence following therapy. Neuronal transition was characterized by posttranslational activation of WNT/PCP signaling and BRAF kinase, while many canonical oncogenic pathways, and EGFR in particular, were downregulated. Parallel multiomics analyses of patient-derived xenograft (PDX) models corroborated this evolutionary trajectory, allowing in vivo experiments for translational significance. Notably, targeting BRAF kinase disrupted both the neuronal transition and migration capabilities of recurrent gliomas, which were key characteristics of posttreatment progression. Furthermore, combining BRAF inhibitor vemurafenib with temozolomide prolonged survival in PDX models. Overall, the results reveal novel biological mechanisms of GBM evolution and therapy resistance, and suggest promising therapeutic intervention.

EPHB2 as a key mediator of glioma progression: Insights from microenvironmental receptor ligand-related prognostic gene signature

Malignant gliomas, characterized by pronounced heterogeneity, a complex microenvironment, and a propensity for relapse and drug resistaniguree, pose significant challenges in oncology. This study aimed to investigate the prognostic value of Ligand and Receptor related genes (LRRGs) within the glioma microenvironment. An intersection of 71 ligand-related genes (LRGs) and 2628 receptor-related genes (RRGs) yielded a total of 69 LRRGs. Utilizing the least absolute shrinkage and selection operator (LASSO) regression analysis, a prognostic RiskScore model comprising 28 LRRGs was constructed. The model demonstrated robust prognostic value, further validated in the TCGA-GBMLGG dataset. Subsequent analyses included differential gene expression, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment (GSEA), and gene set variation (GSVA) within RiskScore groups. Additionally, evaluations of PPI, mRNA-RBP, mRNA-TF, and mRNA-drug interaction networks were conducted. Four hub genes were identified through differential expression analysis of the 28 LRRGs across various GSE datasets. A multivariate Cox prognostic model was constructed for nomogram analysis, gene mutation analysis, and related expression distribution. This study underscores the role of LRRGs in intercellular communication within the glioma microenvironment and identifies four hub genes crucial for prognostic assessment in clinical glioma patients. These findings offer a potential evaluation framework for glioma patients, enhancing our understanding of the disease and informing future therapeutic strategies.

Integrative analysis of transcriptome and proteome profiles in primary and recurrent glioblastoma

PURPOSE

Glioblastoma (GBM) is the most common and aggressive primary brain tumor characterized by poor prognosis and high recurrence. The underlying molecular mechanism that drives tumor progression and recurrence is unclear. This study is intended to look for molecular and biological changes that play a key role in GBM recurrence.

EXPERIMENTAL DESIGN

An integrative transcriptomic and proteomic analysis was performed on three primary GBM and three recurrent GBM tissues. Omics analyses were conducted using label-free quantitative proteomics and whole transcriptome sequencing.

RESULTS

A significant difference was found between primary GBM and recurrent GBM at the transcriptional level. Similar to other omics studies of cancer, a weak overlap was observed between transcriptome and proteome, and Procollagen C-Endopeptidase Enhancer 2 (PCOLCE2) was observed to be upregulated at mRNA and protein levels. Analysis of public cancer database revealed that high expression of PCOLCE2 is associated with poor prognosis of patients with GBM and that it may be a potential prognostic indicator. Functional and environmental enrichment analyses revealed significantly altered signaling pathways related to energy metabolism, including mitochondrial ATP synthesis-coupled electron transport and oxidative phosphorylation.

CONCLUSIONS AND CLINICAL RELEVANCE

This study provides new insights into the recurrence process of GBM through combined transcriptomic and proteomic analyses, complementing the existing GBM transcriptomic and proteomic data and suggesting that integrated multi-omics analyses may reveal new disease features of GBM.

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

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

Integration of 3D bioprinting and multi-algorithm machine learning identified glioma susceptibilities and microenvironment characteristics

Glioma, with its heterogeneous microenvironments and genetic subtypes, presents substantial challenges for treatment prediction and development. We integrated 3D bioprinting and multi-algorithm machine learning as a novel approach to enhance the assessment and understanding of glioma treatment responses and microenvironment characteristics. The bioprinted patient-derived glioma tissues successfully recapitulated molecular properties and drug responses of native tumors. We then developed GlioML, a machine learning workflow incorporating nine distinct algorithms and a weighted ensemble model that generated robust gene expression-based predictors, each reflecting the diverse action mechanisms of various compounds and drugs. The ensemble model superseded the performance of all individual algorithms across diverse in vitro systems, including sphere cultures, complex 3D bioprinted multicellular models, and 3D patient-derived tissues. By integrating bioprinting, the evaluative scope of the treatment expanded to T cell-related therapy and anti-angiogenesis targeted therapy. We identified promising compounds and drugs for glioma treatment and revealed distinct immunosuppressive or angiogenic myeloid-infiltrated tumor microenvironments. These insights pave the way for enhanced therapeutic development for glioma and potentially for other cancers, highlighting the broad application potential of this integrative and translational approach.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Hypofractionated stereotactic re-irradiation for progressive glioblastoma: twelve years' experience of a single center

PURPOSE

We aimed to evaluate the prognostic factors and the role of stereotactic radiotherapy (SRT) as a re-irradiation technique in the management of progressive glioblastoma.

METHODS

The records of 77 previously irradiated glioblastoma patients who progressed and received second course hypofractionated SRT (1-5 fractions) between 2009 and 2022 in our department were evaluated retrospectively. Statistical Package for the Social Sciences (SPSS) version 23.0 (IBM, Armonk, NY, USA) was utilized for all statistical analyses.

RESULTS

The median time to progression from the end of initial radiotherapy was 14 months (range, 6-68 months). The most common SRT schedule was 30 Gy (range, 18-50 Gy) in 5 fractions (range, 1-5 fractions). The median follow-up after SRT was 9 months (range, 3-80 months). One-year overall (OS) and progression-free survival (PFS) rates after SRT were 46% and 35%, respectively. Re-irradiation dose and the presence of pseudoprogression were both significant independent positive prognostic factors for both OS (p = 0.009 and p = 0.04, respectively) and PFS (p = 0.008 and p = 0.04, respectively). For PFS, progression-free interval > 14 months was also a prognostic factor (p = 0.04). The treatment was well tolerated without significant acute toxicity. During follow-up, radiation necrosis was observed in 17 patients (22%), and 14 (82%) of them were asymptomatic.

CONCLUSION

Hypofractionated SRT is an effective treatment approach for patients with progressive glioblastoma. Younger patients who progressed later than 14 months, received higher SRT doses, and experienced pseudoprogression following SRT had improved survival rates.

Radiotherapy Resistance of 3D Bioprinted Glioma via ITGA2/p-AKT Signaling Pathway

Due to the inherent radiation tolerance, patients who suffered from glioma frequently encounter tumor recurrence and malignant progression within the radiation target area, ultimately succumbing to treatment ineffectiveness. The precise mechanism underlying radiation tolerance remains elusive due to the dearth of in vitro models and the limitations associated with animal models. Therefore, a bioprinted glioma model is engineered, characterized the phenotypic traits in vitro, and the radiation tolerance compared to 2D ones when subjected to X-ray radiation is assessed. By comparing the differential gene expression profiles between the 2D and 3D glioma model, identify functional genes, and analyze distinctions in gene expression patterns. Results showed that 3D glioma models exhibited substantial alterations in the expression of genes associated with the stromal microenvironment, notably a significant increase in the radiation tolerance gene ITGA2 (integrin subunit A2). In 3D glioma models, the knockdown of ITGA2 via shRNA resulted in reduced radiation tolerance in glioma cells and concomitant inhibition of the p-AKT pathway. Overall, 3D bioprinted glioma model faithfully recapitulates the in vivo tumor microenvironment (TME) and exhibits enhanced resistance to radiation, mediated through the ITGA2/p-AKT pathway. This model represents a superior in vitro platform for investigating glioma radiotherapy tolerance.

The Next Chapter in Immunotherapy and Radiation Combination Therapy: Cancer-Specific Perspectives

Immunotherapeutic agents have revolutionized cancer treatment over the past decade. However, most patients fail to respond to immunotherapy alone. A growing body of preclinical studies highlights the potential for synergy between radiation therapy and immunotherapy, but the outcomes of clinical studies have been mixed. This review summarizes the current state of immunotherapy and radiation combination therapy across cancers, highlighting existing challenges and promising areas for future investigation.

Molecular diversity in isocitrate dehydrogenase-wild-type glioblastoma

In the dynamic landscape of glioblastoma, the 2021 World Health Organization Classification of Central Nervous System tumours endeavoured to establish biological homogeneity, yet isocitrate dehydrogenase-wild-type (IDH-wt) glioblastoma persists as a tapestry of clinical and molecular diversity. Intertumoural heterogeneity in IDH-wt glioblastoma presents a formidable challenge in treatment strategies. Recent strides in genetics and molecular biology have enhanced diagnostic precision, revealing distinct subtypes and invasive patterns that influence survival in patients with IDH-wt glioblastoma. Genetic and molecular biomarkers, such as the overexpression of neurofibromin 1, phosphatase and tensin homolog and/or cyclin-dependent kinase inhibitor 2A, along with specific immune cell abundance and neurotransmitters, correlate with favourable outcomes. Conversely, increased expression of epidermal growth factor receptor tyrosine kinase, platelet-derived growth factor receptor alpha and/or vascular endothelial growth factor receptor, coupled with the prevalence of glioma stem cells, tumour-associated myeloid cells, regulatory T cells and exhausted effector cells, signifies an unfavourable prognosis. The methylation status of O6-methylguanine-DNA methyltransferase and the influence of microenvironmental factors and neurotransmitters further shape treatment responses. Understanding intertumoural heterogeneity is complemented by insights into intratumoural dynamics and cellular interactions within the tumour microenvironment. Glioma stem cells and immune cell composition significantly impact progression and outcomes, emphasizing the need for personalized therapies targeting pro-tumoural signalling pathways and resistance mechanisms. A successful glioblastoma management demands biomarker identification, combination therapies and a nuanced approach considering intratumoural variability. These advancements herald a transformative era in glioblastoma comprehension and treatment.

Integrated proteogenomic characterization of glioblastoma evolution

The evolutionary trajectory of glioblastoma (GBM) is a multifaceted biological process that extends beyond genetic alterations alone. Here, we perform an integrative proteogenomic analysis of 123 longitudinal glioblastoma pairs and identify a highly proliferative cellular state at diagnosis and replacement by activation of neuronal transition and synaptogenic pathways in recurrent tumors. Proteomic and phosphoproteomic analyses reveal that the molecular transition to neuronal state at recurrence is marked by post-translational activation of the wingless-related integration site (WNT)/ planar cell polarity (PCP) signaling pathway and BRAF protein kinase. Consistently, multi-omic analysis of patient-derived xenograft (PDX) models mirror similar patterns of evolutionary trajectory. Inhibition of B-raf proto-oncogene (BRAF) kinase impairs both neuronal transition and migration capability of recurrent tumor cells, phenotypic hallmarks of post-therapy progression. Combinatorial treatment of temozolomide (TMZ) with BRAF inhibitor, vemurafenib, significantly extends the survival of PDX models. This study provides comprehensive insights into the biological mechanisms of glioblastoma evolution and treatment resistance, highlighting promising therapeutic strategies for clinical intervention.

A longitudinal single-cell and spatial multiomic atlas of pediatric high-grade glioma

Pediatric high-grade glioma (pHGG) is an incurable central nervous system malignancy that is a leading cause of pediatric cancer death. While pHGG shares many similarities to adult glioma, it is increasingly recognized as a molecularly distinct, yet highly heterogeneous disease. In this study, we longitudinally profiled a molecularly diverse cohort of 16 pHGG patients before and after standard therapy through single-nucleus RNA and ATAC sequencing, whole-genome sequencing, and CODEX spatial proteomics to capture the evolution of the tumor microenvironment during progression following treatment. We found that the canonical neoplastic cell phenotypes of adult glioblastoma are insufficient to capture the range of tumor cell states in a pediatric cohort and observed differential tumor-myeloid interactions between malignant cell states. We identified key transcriptional regulators of pHGG cell states and did not observe the marked proneural to mesenchymal shift characteristic of adult glioblastoma. We showed that essential neuromodulators and the interferon response are upregulated post-therapy along with an increase in non-neoplastic oligodendrocytes. Through in vitro pharmacological perturbation, we demonstrated novel malignant cell-intrinsic targets. This multiomic atlas of longitudinal pHGG captures the key features of therapy response that support distinction from its adult counterpart and suggests therapeutic strategies which are targeted to pediatric gliomas.

Single-cell nanobiopsy enables multigenerational longitudinal transcriptomics of cancer cells

Single-cell RNA sequencing has revolutionized our understanding of cellular heterogeneity, but routine methods require cell lysis and fail to probe the dynamic trajectories responsible for cellular state transitions, which can only be inferred. Here, we present a nanobiopsy platform that enables the injection of exogenous molecules and multigenerational longitudinal cytoplasmic sampling from a single cell and its progeny. The technique is based on scanning ion conductance microscopy (SICM) and, as a proof of concept, was applied to longitudinally profile the transcriptome of single glioblastoma (GBM) brain tumor cells in vitro over 72 hours. The GBM cells were biopsied before and after exposure to chemotherapy and radiotherapy, and our results suggest that treatment either induces or selects for more transcriptionally stable cells. We envision the nanobiopsy will contribute to transforming standard single-cell transcriptomics from a static analysis into a dynamic assay.

Dietary Restriction Improves Perioperative Neurocognitive Disorders by Inhibiting Neuroinflammation and Gut Microbial Dysbiosis

Anesthesia/surgery have been identified as potential factors contributing to perioperative neurocognitive disorders, with a notably heightened risk observed in aging populations. One of the primary drivers of this impairment is believed to be neuroinflammation, specifically inflammation of hippocampal microglia. Dietary restriction has demonstrated a favorable impact on cognitive impairment across various disorders, primarily by quelling neuroinflammation. However, the precise influence of dietary restriction on perioperative neurocognitive disorders remains to be definitively ascertained. This investigation aims to explore the effects of dietary restriction on perioperative neurocognitive disorders and propose innovative therapeutic strategies for their management. The model of perioperative neurocognitive disorder was induced through exploratory laparotomy under isoflurane anesthesia. Cognitive performance was evaluated using the open field test, Barnes maze test, and fear conditioning test. The enzyme-linked immunosorbent assay (ELISA) was employed to quantify concentrations of interleukin-1β (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) in both serum and hippocampal samples. The Western blot technique was utilized to assess expression levels of hippocampal PSD 95, Synaptophysin, TLR4, MyD88, and NF-kB p65. Microglial polarization was gauged using a combination of reverse transcription quantitative polymerase chain reaction (RT-qPCR) and immunofluorescence labeling techniques. We conducted 16S rRNA sequencing to investigate the impact of dietary restriction on the intestinal flora of aged mice following anesthesia/surgery. Our findings indicate that dietary restrictions have the potential to ameliorate anesthesia/surgery-induced cognitive dysfunction. This effect is achieved through the modulation of gut microbiota, suppression of inflammatory responses in hippocampal microglia, and facilitation of neuronal repair and regeneration.

The Epigenetic Evolution of Glioma Is Determined by the IDH1 Mutation Status and Treatment Regimen

Tumor adaptation or selection is thought to underlie therapy resistance in glioma. To investigate longitudinal epigenetic evolution of gliomas in response to therapeutic pressure, we performed an epigenomic analysis of 132 matched initial and recurrent tumors from patients with IDH-wildtype (IDHwt) and IDH-mutant (IDHmut) glioma. IDHwt gliomas showed a stable epigenome over time with relatively low levels of global methylation. The epigenome of IDHmut gliomas showed initial high levels of genome-wide DNA methylation that was progressively reduced to levels similar to those of IDHwt tumors. Integration of epigenomics, gene expression, and functional genomics identified HOXD13 as a master regulator of IDHmut astrocytoma evolution. Furthermore, relapse of IDHmut tumors was accompanied by histologic progression that was associated with survival, as validated in an independent cohort. Finally, the initial cell composition of the tumor microenvironment varied between IDHwt and IDHmut tumors and changed differentially following treatment, suggesting increased neoangiogenesis and T-cell infiltration upon treatment of IDHmut gliomas. This study provides one of the largest cohorts of paired longitudinal glioma samples with epigenomic, transcriptomic, and genomic profiling and suggests that treatment of IDHmut glioma is associated with epigenomic evolution toward an IDHwt-like phenotype.

SIGNIFICANCE

Standard treatments are related to loss of DNA methylation in IDHmut glioma, resulting in epigenetic activation of genes associated with tumor progression and alterations in the microenvironment that resemble treatment-naïve IDHwt glioma.

Glioblastoma biomarkers in urinary extracellular vesicles reveal the potential for a 'liquid gold' biopsy

BACKGROUND

Biomarkers that reflect glioblastoma tumour activity and treatment response are urgently needed to help guide clinical management, particularly for recurrent disease. As the urinary system is a major clearance route of circulating extracellular vesicles (EVs; 30-1000 nm nanoparticles) we explored whether sampling urinary-EVs could serve as a simple and non-invasive liquid biopsy approach for measuring glioblastoma-associated biomarkers.

METHODS

Fifty urine specimens (15-60 ml) were collected from 24 catheterised glioblastoma patients immediately prior to primary (n = 17) and recurrence (n = 7) surgeries, following gross total resection (n = 9), and from age/gender-matched healthy participants (n = 14). EVs isolated by differential ultracentrifugation were characterised and extracted proteomes were analysed by high-resolution data-independent acquisition liquid chromatography tandem mass spectrometry (DIA-LC-MS/MS).

RESULTS

Overall, 6857 proteins were confidently identified in urinary-EVs (q-value ≤ 0.01), including 94 EV marker proteins. Glioblastoma-specific proteomic signatures were determined, and putative urinary-EV biomarkers corresponding to tumour burden and recurrence were identified (FC ≥ | 2 | , adjust p-val≤0.05, AUC > 0.9).

CONCLUSION

In-depth DIA-LC-MS/MS characterisation of urinary-EVs substantiates urine as a viable source of glioblastoma biomarkers. The promising 'liquid gold' biomarker panels described here warrant further investigation.

Impact of tissue-agnostic approvals on management of primary brain tumors

Novel tissue-agnostic therapeutics targeting driver mutations in tumor cells have been recently approved by FDA, driven by basket trials that have demonstrated their efficacy and safety across diverse tumor histology. However, the relative rarity of primary brain tumors (PBTs) has limited their representation in early trials of tissue-agnostic medications. Thus, consensus continues to evolve regarding utility of tissue-agnostic medications in routine practice for PBTs, a diverse group of neoplasms characterized by limited treatment options and unfavorable prognoses. We describe current and potential impact of tissue-agnostic approvals on management of PBTs. We discuss data from clinical trials for PBTs regarding tissue-agnostic targets, including BRAFV600E, neurotrophic tyrosine receptor kinase (NTRK) fusions, microsatellite instability-high (MSI-High), mismatch repair deficiency (dMMR), and high tumor mutational burden (TMB-H), in context of challenges in managing PBTs. Described are additional tissue-agnostic targets that hold promise for benefiting patients with PBTs, including RET fusion, fibroblast growth factor receptor (FGFR), ERBB2/HER2, and KRASG12C, and TP53Y220C.

Multimodal neuro-nanotechnology: Challenging the existing paradigm in glioblastoma therapy

Integrating multimodal neuro- and nanotechnology-enabled precision immunotherapies with extant systemic immunotherapies may finally provide a significant breakthrough for combatting glioblastoma (GBM). The potency of this approach lies in its ability to train the immune system to efficiently identify and eradicate cancer cells, thereby creating anti-tumor immune memory while minimizing multi-mechanistic immune suppression. A critical aspect of these therapies is the controlled, spatiotemporal delivery of structurally defined nanotherapeutics into the GBM tumor microenvironment (TME). Architectures such as spherical nucleic acids or poly(beta-amino ester)/dendrimer-based nanoparticles have shown promising results in preclinical models due to their multivalency and abilities to activate antigen-presenting cells and prime antigen-specific T cells. These nanostructures also permit systematic variation to optimize their distribution, TME accumulation, cellular uptake, and overall immunostimulatory effects. Delving deeper into the relationships between nanotherapeutic structures and their performance will accelerate nano-drug development and pave the way for the rapid clinical translation of advanced nanomedicines. In addition, the efficacy of nanotechnology-based immunotherapies may be enhanced when integrated with emerging precision surgical techniques, such as laser interstitial thermal therapy, and when combined with systemic immunotherapies, particularly inhibitors of immune-mediated checkpoints and immunosuppressive adenosine signaling. In this perspective, we highlight the potential of emerging treatment modalities, combining advances in biomedical engineering and neurotechnology development with existing immunotherapies to overcome treatment resistance and transform the management of GBM. We conclude with a call to action for researchers to leverage these technologies and accelerate their translation into the clinic.

Identifying PLAUR as a Pivotal Gene of Tumor Microenvironment and Regulating Mesenchymal Phenotype of Glioblastoma

The mesenchymal (MES) phenotype of glioblastoma (GBM) is the most aggressive and therapy-resistant subtype of GBM. The MES phenotype transition during tumor progression results from both tumor-intrinsic genetic alterations and tumor-extrinsic microenvironmental factors. In this study, we sought to identify genes that can modulate the MES phenotype via both mechanisms. By integrating weighted gene co-expression network analysis (WGCNA) and the differential expression analysis of hypoxia-immunosuppression-related genes, we identified the plasminogen activator, urokinase receptor (PLAUR) as the hub gene. Functional enrichment analysis and GSVA analysis demonstrated that PLAUR was associated with the MES phenotype of glioma and the hypoxia-immunosuppression-related microenvironmental components. Single-cell sequencing analysis revealed that PLAUR mediated the ligand-receptor interaction between tumor-associated macrophages (TAMs) and glioma cells. Functional experiments in vitro with cell lines or primary glioma cells and xenograft models using BALB/c nude mice confirmed the role of PLAUR in promoting the MES phenotype of GBM. Our findings indicate that PLAUR regulates both glioma cells and tumor cell-extrinsic factors that favor the MES phenotype and suggest that PLAUR might be a potential target for GBM therapy.

Glioblastoma-Associated Mesenchymal Stem/Stromal Cells and Cancer-Associated Fibroblasts: Partners in Crime?

Tumor-associated mesenchymal stem/stromal cells (TA-MSCs) have been recognized as attractive therapeutic targets in several cancer types, due to their ability to enhance tumor growth and angiogenesis and their contribution to an immunosuppressive tumor microenvironment (TME). In glioblastoma (GB), mesenchymal stem cells (MSCs) seem to be recruited to the tumor site, where they differentiate into glioblastoma-associated mesenchymal stem/stromal cells (GA-MSCs) under the influence of tumor cells and the TME. GA-MSCs are reported to exert important protumoral functions, such as promoting tumor growth and invasion, increasing angiogenesis, stimulating glioblastoma stem cell (GSC) proliferation and stemness, mediating resistance to therapy and contributing to an immunosuppressive TME. Moreover, they could act as precursor cells for cancer-associated fibroblasts (CAFs), which have recently been identified in GB. In this review, we provide an overview of the different functions exerted by GA-MSCs and CAFs and the current knowledge on the relationship between these cell types. Increasing our understanding of the interactions and signaling pathways in relevant models might contribute to future regimens targeting GA-MSCs and GB-associated CAFs to inhibit tumor growth and render the TME less immunosuppressive.

IDHwt glioblastomas can be stratified by their transcriptional response to standard treatment, with implications for targeted therapy

BACKGROUND

Glioblastoma (GBM) brain tumors lacking IDH1 mutations (IDHwt) have the worst prognosis of all brain neoplasms. Patients receive surgery and chemoradiotherapy but tumors almost always fatally recur.

RESULTS

Using RNA sequencing data from 107 pairs of pre- and post-standard treatment locally recurrent IDHwt GBM tumors, we identify two responder subtypes based on longitudinal changes in gene expression. In two thirds of patients, a specific subset of genes is upregulated from primary to recurrence (Up responders), and in one third, the same genes are downregulated (Down responders), specifically in neoplastic cells. Characterization of the responder subtypes indicates subtype-specific adaptive treatment resistance mechanisms that are associated with distinct changes in the tumor microenvironment. In Up responders, recurrent tumors are enriched in quiescent proneural GBM stem cells and differentiated neoplastic cells, with increased interaction with the surrounding normal brain and neurotransmitter signaling, whereas Down responders commonly undergo mesenchymal transition. ChIP-sequencing data from longitudinal GBM tumors suggests that the observed transcriptional reprogramming could be driven by Polycomb-based chromatin remodeling rather than DNA methylation.

CONCLUSIONS

We show that the responder subtype is cancer-cell intrinsic, recapitulated in in vitro GBM cell models, and influenced by the presence of the tumor microenvironment. Stratifying GBM tumors by responder subtype may lead to more effective treatment.

A clinically applicable connectivity signature for glioblastoma includes the tumor network driver CHI3L1

Tumor microtubes (TMs) connect glioma cells to a network with considerable relevance for tumor progression and therapy resistance. However, the determination of TM-interconnectivity in individual tumors is challenging and the impact on patient survival unresolved. Here, we establish a connectivity signature from single-cell RNA-sequenced (scRNA-Seq) xenografted primary glioblastoma (GB) cells using a dye uptake methodology, and validate it with recording of cellular calcium epochs and clinical correlations. Astrocyte-like and mesenchymal-like GB cells have the highest connectivity signature scores in scRNA-sequenced patient-derived xenografts and patient samples. In large GB cohorts, TM-network connectivity correlates with the mesenchymal subtype and dismal patient survival. CHI3L1 gene expression serves as a robust molecular marker of connectivity and functionally influences TM networks. The connectivity signature allows insights into brain tumor biology, provides a proof-of-principle that tumor cell TM-connectivity is relevant for patients' prognosis, and serves as a robust prognostic biomarker.

Identification and validation of a glycolysis-related taxonomy for improving outcomes in glioma

BACKGROUND

Reprogramming of glucose metabolism is a prominent abnormal energy metabolism in glioma. However, the efficacy of treatments targeting glycolysis varies among patients. The present study aimed to classify distinct glycolysis subtypes (GS) of glioma, which may help to improve the therapy response.

METHODS

The expression profiles of glioma were downloaded from public datasets to perform an enhanced clustering analysis to determine the GS. A total of 101 combinations based on 10 machine learning algorithms were performed to screen out the most valuable glycolysis-related glioma signature (GGS). Through RSF and plsRcox algorithms, adrenomedullin (ADM) was eventually obtained as the most significant glycolysis-related gene for prognostic prediction in glioma. Furthermore, drug sensitivity analysis, molecular docking, and in vitro experiments were utilized to verify the efficacy of ADM and ingenol mebutate (IM).

RESULTS

Glioma patients were classified into five distinct GS (GS1-GS5), characterized by varying glycolytic metabolism levels, molecular expression, immune cell infiltration, immunogenic modulators, and clinical features. Anti-CTLA4 and anti-PD-L1 antibodies significantly improved the prognosis for GS2 and GS5, respectively. ADM has been identified as a potential biomarker for targeted glycolytic therapy in glioma patients. In vitro experiments demonstrated that IM inhibited glioma cell progression by inhibiting ADM.

CONCLUSION

This study elucidates that evaluating GS is essential for comprehending the heterogeneity of glioma, which is pivotal for predicting immune cell infiltration (ICI) characterization, prognosis, and personalized immunotherapy regimens. We also explored the glycolysis-related genes ADM and IM to develop a theoretical framework for anti-tumor strategies targeting glycolysis.

[Tumor-host cell interaction in the microenvironment: new target points for treatment?]

BACKGROUND

Primary brain tumors and metastases in the central nervous system (CNS) are characterized by their unique microenvironment, which interacts with neuronal structures and influences structural and adaptive immunity.

OBJECTIVE

How significant are various tumor-host interactions from a prognostic and therapeutic perspective?

MATERIAL AND METHOD

A literature search was carried out for relevant articles on the topic: microenvironment glioblastoma or metastasis through PubMed and Medline.

RESULTS

Modern high-throughput methods, such as spatial and single-cell resolution molecular characterization of tumors and their microenvironment enable a detailed mapping of changes and adaptation of individual cells within the microenvironment of tumors; however, treatment approaches based on altered tumor-host cell interactions, such as immune modeling, cell-based treatment methods or checkpoint inhibition have so far not shown any significant advantages for survival.

CONCLUSION

A deeper understanding of the complex immune landscape and the microenvironment of metastases of the CNS and intracerebral tumors is essential to optimize future treatment strategies.

Glioblastoma vaccines: past, present, and opportunities

Glioblastoma (GBM) is one of the most lethal central nervous systems (CNS) tumours in adults. As supplements to standard of care (SOC), various immunotherapies improve the therapeutic effect in other cancers. Among them, tumour vaccines can serve as complementary monotherapy or boost the clinical efficacy with other immunotherapies, such as immune checkpoint blockade (ICB) and chimeric antigen receptor T cells (CAR-T) therapy. Previous studies in GBM therapeutic vaccines have suggested that few neoantigens could be targeted in GBM due to low mutation burden, and single-peptide therapeutic vaccination had limited efficacy in tumour control as monotherapy. Combining diverse antigens, including neoantigens, tumour-associated antigens (TAAs), and pathogen-derived antigens, and optimizing vaccine design or vaccination strategy may help with clinical efficacy improvement. In this review, we discussed current GBM therapeutic vaccine platforms, evaluated and potential antigenic targets, current challenges, and perspective opportunities for efficacy improvement.

A multidimensional atlas of human glioblastoma-like organoids reveals highly coordinated molecular networks and effective drugs

Recent advances in the genomics of glioblastoma (GBM) led to the introduction of molecular neuropathology but failed to translate into treatment improvement. This is largely attributed to the genetic and phenotypic heterogeneity of GBM, which are considered the major obstacle to GBM therapy. Here, we use advanced human GBM-like organoid (LEGO: Laboratory Engineered Glioblastoma-like Organoid) models and provide an unprecedented comprehensive characterization of LEGO models using single-cell transcriptome, DNA methylome, metabolome, lipidome, proteome, and phospho-proteome analysis. We discovered that genetic heterogeneity dictates functional heterogeneity across molecular layers and demonstrates that NF1 mutation drives mesenchymal signature. Most importantly, we found that glycerol lipid reprogramming is a hallmark of GBM, and several targets and drugs were discovered along this line. We also provide a genotype-based drug reference map using LEGO-based drug screen. This study provides new human GBM models and a research path toward effective GBM therapy.

Temporal change of DNA methylation subclasses between matched newly diagnosed and recurrent glioblastoma

The longitudinal transition of phenotypes is pivotal in glioblastoma treatment resistance and DNA methylation emerged as an important tool for classifying glioblastoma phenotypes. We aimed to characterize DNA methylation subclass heterogeneity during progression and assess its clinical impact. Matched tissues from 47 glioblastoma patients were subjected to DNA methylation profiling, including CpG-site alterations, tissue and serum deconvolution, mass spectrometry, and immunoassay. Effects of clinical characteristics on temporal changes and outcomes were studied. Among 47 patients, 8 (17.0%) had non-matching classifications at recurrence. In the remaining 39 cases, 28.2% showed dominant DNA methylation subclass transitions, with 72.7% being a mesenchymal subclass. In general, glioblastomas with a subclass transition showed upregulated metabolic processes. Newly diagnosed glioblastomas with mesenchymal transition displayed increased stem cell-like states and decreased immune components at diagnosis and exhibited elevated immune signatures and cytokine levels in serum. In contrast, tissue of recurrent glioblastomas with mesenchymal transition showed increased immune components but decreased stem cell-like states. Survival analyses revealed comparable outcomes for patients with and without subclass transitions. This study demonstrates a temporal heterogeneity of DNA methylation subclasses in 28.2% of glioblastomas, not impacting patient survival. Changes in cell state composition associated with subclass transition may be crucial for recurrent glioblastoma targeted therapies.

Comprehensive characterization and database construction of immune repertoire in the largest Chinese glioma cohort

Immune receptor repertoire is valuable for developing immunotherapeutic interventions, but remains poorly understood across glioma subtypes including IDH wild type, IDH mutation without 1p/19q codeletion (IDHmut-noncodel) and IDH mutation with 1p/19q codeletion (IDHmut-codel). We assembled over 320,000 TCR/BCR clonotypes from the largest glioma cohort of 913 RNA sequencing samples in the Chinese population, finding that immune repertoire diversity was more prominent in the IDH wild type (the most aggressive glioma). Fewer clonotypes were shared within each glioma subtype, indicating high heterogeneity of the immune repertoire. The TRA-CDR3 was longer in private than in public clonotypes in IDH wild type. CDR3 variable motifs had higher proportions of hydrophobic residues in private than in public clonotypes, suggesting private CDR3 sequences have greater potential for tumor antigen recognition. Finally, we developed GTABdb, a web-based database designed for hosting, exploring, visualizing, and analyzing glioma immune repertoire. Our study will facilitate developing glioma immunotherapy.

Glioma-Immune Cell Crosstalk in Tumor Progression

Glioma progression is a complex process controlled by molecular factors that coordinate the crosstalk between tumor cells and components of the tumor microenvironment (TME). Among these, immune cells play a critical role in cancer survival and progression. The complex interplay between cancer cells and the immune TME influences the outcome of immunotherapy and other anti-cancer therapies. Here, we present an updated view of the pro- and anti-tumor activities of the main myeloid and lymphocyte cell populations in the glioma TME. We review the underlying mechanisms involved in crosstalk between cancer cells and immune cells that enable gliomas to evade the immune system and co-opt these cells for tumor growth. Lastly, we discuss the current and experimental therapeutic options being developed to revert the immunosuppressive activity of the glioma TME. Knowledge of the complex interplay that elapses between tumor and immune cells may help develop new combination treatments able to overcome tumor immune evasion mechanisms and enhance response to immunotherapies.

IL4I1 in M2-like macrophage promotes glioma progression and is a promising target for immunotherapy

Background

Glioma is the prevailing malignant intracranial tumor, characterized by an abundance of macrophages. Specifically, the infiltrating macrophages often display the M2 subtype and are known as tumor-associated macrophages (TAMs). They have a critical role in promoting the oncogenic properties of tumor cells. Interleukin-4-induced-1 (IL4I1) functions as an L-phenylalanine oxidase, playing a key part in regulating immune responses and the progression of various tumors. However, there is limited understanding of the IL4I1-mediated cross-talk function between TAMs and glioma cell in the glioma microenvironment.

Methods

TCGA, GTEx, and HPA databases were applied to assess the IL4I1 expression, clinical characteristics, and prognostic value of pan-cancer. The link between IL4I1 levels and the prognosis, methylation, and immune checkpoints (ICs) in gliomas were explored through Kaplan-Meier curve, Cox regression, and Spearman correlation analyses. The IL4I1 levels and their distribution were investigated by single-cell analysis and the TIMER 2 database. Additionally, validation of IL4I1 expression was performed by WB, RT-qPCR, IHC, and IF. Co-culture models between glioma cells and M2-like macrophages were used to explore the IL4I1-mediated effects on tumor growth, invasion, and migration of glioma cells. Moreover, the function of IL4I1 on macrophage polarization was evaluated by ELISA, RT-qPCR, WB, and siRNA transfection.

Results

Both transcriptome and protein levels of IL4I1 were increased obviously in various tumor types, and correlated with a dismal prognosis. Specifically, IL4I1 was implicated in aggressive progression and a dismal prognosis for patients with glioma. A negative association was noticed between the glioma grade and DNA promoter methylation of IL4I1. Enrichment analyses in glioma patients suggested that IL4I1 was linked to cytokine and immune responses, and was positively correlated with ICs. Single-cell analysis, molecular experiments, and in vitro assays showed that IL4I1 was significantly expressed in TAMs. Importantly, co-culture models proved that IL4I1 significantly promoted the invasion and migration of glioma cells, and induced the polarization of M2-like macrophages.

Conclusion

IL4I1 could be a promising immunotherapy target for selective modulation of TAMs and stands as a novel macrophage-related prognostic biomarker in glioma.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

ssMutPA: single-sample mutation-based pathway analysis approach for cancer precision medicine

BACKGROUND

Single-sample pathway enrichment analysis is an effective approach for identifying cancer subtypes and pathway biomarkers, facilitating the development of precision medicine. However, the existing approaches focused on investigating the changes in gene expression levels but neglected somatic mutations, which play a crucial role in cancer development.

FINDINGS

In this study, we proposed a novel single-sample mutation-based pathway analysis approach (ssMutPA) to infer individualized pathway activities by integrating somatic mutation data and the protein-protein interaction network. For each sample, ssMutPA first uses local and global weighted strategies to evaluate the effects of genes from mutations according to the network topology and then calculates a single-sample mutation-based pathway enrichment score (ssMutPES) to reflect the accumulated effect of mutations of each pathway. To illustrate the performance of ssMutPA, we applied it to 33 cancer cohorts from The Cancer Genome Atlas database and revealed patient stratification with significantly different prognosis in each cancer type based on the ssMutPES profiles. We also found that the identified characteristic pathways with high overlap across different cancers could be used as potential prognosis biomarkers. Moreover, we applied ssMutPA to 2 melanoma cohorts with immunotherapy and identified a subgroup of patients who may benefit from therapy.

CONCLUSIONS

We provided evidence that ssMutPA could infer mutation-based individualized pathway activity profiles and complement the current individualized pathway analysis approaches focused on gene expression data, which may offer the potential for the development of precision medicine. ssMutPA is available at https://CRAN.R-project.org/package=ssMutPA.

Deep learning links localized digital pathology phenotypes with transcriptional subtype and patient outcome in glioblastoma

BACKGROUND

Deep learning has revolutionized medical image analysis in cancer pathology, where it had a substantial clinical impact by supporting the diagnosis and prognostic rating of cancer. Among the first available digital resources in the field of brain cancer is glioblastoma, the most common and fatal brain cancer. At the histologic level, glioblastoma is characterized by abundant phenotypic variability that is poorly linked with patient prognosis. At the transcriptional level, 3 molecular subtypes are distinguished with mesenchymal-subtype tumors being associated with increased immune cell infiltration and worse outcome.

RESULTS

We address genotype-phenotype correlations by applying an Xception convolutional neural network to a discovery set of 276 digital hematozylin and eosin (H&E) slides with molecular subtype annotation and an independent The Cancer Genome Atlas-based validation cohort of 178 cases. Using this approach, we achieve high accuracy in H&E-based mapping of molecular subtypes (area under the curve for classical, mesenchymal, and proneural = 0.84, 0.81, and 0.71, respectively; P < 0.001) and regions associated with worse outcome (univariable survival model P < 0.001, multivariable P = 0.01). The latter were characterized by higher tumor cell density (P < 0.001), phenotypic variability of tumor cells (P < 0.001), and decreased T-cell infiltration (P = 0.017).

CONCLUSIONS

We modify a well-known convolutional neural network architecture for glioblastoma digital slides to accurately map the spatial distribution of transcriptional subtypes and regions predictive of worse outcome, thereby showcasing the relevance of artificial intelligence-enabled image mining in brain cancer.

Repurposing of pexidartinib for microglia depletion and renewal

Pexidartinib (PLX3397) is a small molecule receptor tyrosine kinase inhibitor of colony stimulating factor 1 receptor (CSF1R) with moderate selectivity over other members of the platelet derived growth factor receptor family. It is approved for treatment of tenosynovial giant cell tumors (TGCT). CSF1R is highly expressed by microglia, which are macrophages of the central nervous system (CNS) that defend the CNS against injury and pathogens and contribute to synapse development and plasticity. Challenged by pathogens, apoptotic cells, debris, or inflammatory molecules they adopt a responsive state to propagate the inflammation and eventually return to a homeostatic state. The phenotypic switch may fail, and disease-associated microglia contribute to the pathophysiology in neurodegenerative or neuropsychiatric diseases or long-lasting detrimental brain inflammation after brain, spinal cord or nerve injury or ischemia/hemorrhage. Microglia also contribute to the growth permissive tumor microenvironment of glioblastoma (GBM). In rodents, continuous treatment for 1-2 weeks via pexidartinib food pellets leads to a depletion of microglia and subsequent repopulation from the remaining fraction, which is aided by peripheral monocytes that search empty niches for engraftment. The putative therapeutic benefit of such microglia depletion or forced renewal has been assessed in almost any rodent model of CNS disease or injury or GBM with heterogeneous outcomes, but a tendency of partial beneficial effects. So far, microglia monitoring e.g. via positron emission imaging is not standard of care for patients receiving Pexidartinib (e.g. for TGCT), so that the depletion and repopulation efficiency in humans is still largely unknown. Considering the virtuous functions of microglia, continuous depletion is likely no therapeutic option but short-lasting transient partial depletion to stimulate microglia renewal or replace microglia in genetic disease in combination with e.g. stem cell transplantation or as part of a multimodal concept in treatment of glioblastoma appears feasible. The present review provides an overview of the preclinical evidence pro and contra microglia depletion as a therapeutic approach.

Frequent Alzheimer's disease neuropathological change in patients with glioblastoma

Background

The incidence of brain cancer and neurodegenerative diseases is increasing with a demographic shift towards aging populations. Biological parallels have been observed between glioblastoma and Alzheimer's disease (AD), which converge on accelerated brain aging. Here, we aimed to map the cooccurrence of AD neuropathological change (ADNC) in the tumor-adjacent cortex of patients with glioblastoma.

Methods

Immunohistochemical screening of AD markers amyloid beta (Abeta), amyloid precursor protein (APP), and hyperphosphorylated tau (pTau) was conducted in 420 tumor samples of 205 patients. For each cortex area, we quantified ADNC, neurons, tumor cells, and microglia.

Results

Fifty-two percent of patients (N = 106/205) showed ADNC (Abeta and pTau, Abeta or pTau) in the tumor-adjacent cortex, with histological patterns widely consistent with AD. ADNC was positively correlated with patient age and varied spatially according to Thal phases and Braak stages. It decreased with increasing tumor cell infiltration (P < .0001) and was independent of frequent expression of APP in neuronal cell bodies (N = 182/205) and in tumor necrosis-related axonal spheroids (N = 195/205; P = .46). Microglia response was most present in tumor cell infiltration plus ADNC, being further modulated by patient age and sex. ADNC did not impact patient survival in the present cohort.

Conclusions

Our findings highlight the frequent presence of ADNC in the glioblastoma vicinity, which was linked to patient age and tumor location. The cooccurrence of AD and glioblastoma seemed stochastic without clear spatial relation. ADNC did not impact patient survival in our cohort.

Antigen presentation deficiency, mesenchymal differentiation, and resistance to immunotherapy in the murine syngeneic CT2A tumor model

Background

The GL261 and CT2A syngeneic tumor lines are frequently used as immunocompetent orthotopic mouse models of human glioblastoma (huGBM) but demonstrate distinct differences in their responses to immunotherapy.

Methods

To decipher the cell-intrinsic mechanisms that drive immunotherapy resistance in CT2A-luc and to define the aspects of human cancer biology that these lines can best model, we systematically compared their characteristics using whole exome and transcriptome sequencing, and protein analysis through immunohistochemistry, Western blot, flow cytometry, immunopeptidomics, and phosphopeptidomics.

Results

The transcriptional profiles of GL261-luc2 and CT2A-luc tumors resembled those of some huGBMs, despite neither line sharing the essential genetic or histologic features of huGBM. Both models exhibited striking hypermutation, with clonal hotspot mutations in RAS genes (Kras p.G12C in GL261-luc2 and Nras p.Q61L in CT2A-luc). CT2A-luc distinctly displayed mesenchymal differentiation, upregulated angiogenesis, and multiple defects in antigen presentation machinery (e.g. Tap1 p.Y488C and Psmb8 p.A275P mutations) and interferon response pathways (e.g. copy number losses of loci including IFN genes and reduced phosphorylation of JAK/STAT pathway members). The defect in MHC class I expression could be overcome in CT2A-luc by interferon-γ treatment, which may underlie the modest efficacy of some immunotherapy combinations. Additionally, CT2A-luc demonstrated substantial baseline secretion of the CCL-2, CCL-5, and CCL-22 chemokines, which play important roles as myeloid chemoattractants.

Conclusion

Although the clinical contexts that can be modeled by GL261 and CT2A for huGBM are limited, CT2A may be an informative model of immunotherapy resistance due to its deficits in antigen presentation machinery and interferon response pathways.

Wnt inhibition alleviates resistance to immune checkpoint blockade in glioblastoma

Wnt signaling plays a critical role in the progression and treatment outcome of glioblastoma (GBM). Here, we identified WNT7b as a heretofore unknown mechanism of resistance to immune checkpoint inhibition (αPD1) in GBM patients and murine models. Acquired resistance to αPD1 was found to be associated with the upregulation of Wnt7b and β-catenin protein levels in GBM in patients and in a clinically relevant, stem-rich GBM model. Combining the porcupine inhibitor WNT974 with αPD1 prolonged the survival of GBM-bearing mice. However, this combination had a dichotomous response, with a subset of tumors showing refractoriness. WNT974 and αPD1 expanded a subset of DC3-like dendritic cells (DCs) and decreased the granulocytic myeloid-derived suppressor cells (gMDSCs) in the tumor microenvironment (TME). By contrast, monocytic MDSCs (mMDSCs) increased, while T-cell infiltration remained unchanged, suggesting potential TME-mediated resistance. Our preclinical findings warrant the testing of Wnt7b/β-catenin combined with αPD1 in GBM patients with elevated Wnt7b/β-catenin signaling.

Therapeutic Targeting of Glioblastoma and the Interactions with Its Microenvironment

Glioblastoma (GBM) is the most common primary malignant brain tumour, and it confers a dismal prognosis despite intensive multimodal treatments. Whilst historically, research has focussed on the evolution of GBM tumour cells themselves, there is growing recognition of the importance of studying the tumour microenvironment (TME). Improved characterisation of the interaction between GBM cells and the TME has led to a better understanding of therapeutic resistance and the identification of potential targets to block these escape mechanisms. This review describes the network of cells within the TME and proposes treatment strategies for simultaneously targeting GBM cells, the surrounding immune cells, and the crosstalk between them.

Clinical Value of a Nomogram Model Based on Apparent Diffusion Coefficient Values Within 1 cm of the Tumor Cavity to Predict Postoperative Progression of Glioma

OBJECTIVE

To explore the clinical value of constructing a nomogram model based on apparent diffusion coefficient values within 1 cm of the residual tumor cavity to predict the postoperative progression of gliomas.

METHODS

Clinical data of patients with glioma who underwent surgery were retrospectively retrieved from the First Hospital of Qinhuangdao. The mean apparent diffusion coefficient (mADC) was measured using a picture archiving and communication system. The Kaplan-Meier survival curve was constructed with the optimal mADC threshold determined by the X-tile. A nomogram was developed based on the independent risk factors determined using the Cox proportional hazards model (Cox regression model) to predict the progression of postoperative glioma. A receiver operating characteristic curve was drawn to evaluate the prediction accuracy of the model, and decision curve analysis was performed to assess the clinical value of the nomogram.

RESULTS

There was good agreement between the mADC values of the 2 repeated measurements before and after, with a consistency correlation coefficient of 0.83. Multivariate Cox regression analysis showed that peritumoral mADC values, degree of peritumoral enhancement, age, pathological grading, and degree of tumor resection were independent risk factors for predicting postoperative progression of glioma (all P < 0.05). The receiver operating characteristic curves of the nomogram predicting 1, 2, and 3 years postoperative progression were 0.86, 0.82, and 0.91, respectively. The calibration curve showed good consistency between the observed and predicted values in the model. The curve showed that the nomogram model has a good clinical application value.

CONCLUSIONS

The peritumoral mADC values, degree of peritumoral enhancement, age, pathological grade, and degree of tumor resection were independent factors affecting the postoperative progression of glioma. The nomogram model established for the first time based on mADC values within 1 cm of the tumor can predict the postoperative condition of patients with glioma intuitively and comprehensively. It can provide a relatively accurate prediction tool for neurosurgeons to individualize the evaluation of survival and prognosis, and formulate treatment plans for patients.

Unveiling the Influence of Tumor Microenvironment and Spatial Heterogeneity on Temozolomide Resistance in Glioblastoma Using an Advanced Human In Vitro Model of the Blood-Brain Barrier and Glioblastoma

Glioblastoma (GBM) is the most common primary malignant brain cancer in adults with a dismal prognosis. Temozolomide (TMZ) is the first-in-line chemotherapeutic; however, resistance is frequent and multifactorial. While many molecular and genetic factors have been linked to TMZ resistance, the role of the solid tumor morphology and the tumor microenvironment, particularly the blood-brain barrier (BBB), is unknown. Here, the authors investigate these using a complex in vitro model for GBM and its surrounding BBB. The model recapitulates important clinical features such as a dense tumor core with tumor cells that invade along the perivascular space; and a perfusable BBB with a physiological permeability and morphology that is altered in the presence of a tumor spheroid. It is demonstrated that TMZ sensitivity decreases with increasing cancer cell spatial organization, and that the BBB can contribute to TMZ resistance. Proteomic analysis with next-generation low volume sample workflows of these cultured microtissues revealed potential clinically relevant proteins involved in tumor aggressiveness and TMZ resistance, demonstrating the utility of complex in vitro models for interrogating the tumor microenvironment and therapy validation.

Neuroscience and oncology: state-of-the-art and new perspectives

PURPOSE OF REVIEW

Emerging discoveries suggest that both the central (CNS) and peripheral (PNS) nervous system are an important driver of cancer initiation, promotion, dissemination, and therapy resistance, not only in the brain but also in multiple cancer types throughout the body. This article highlights the most recent developments in this emerging field of research over the last year and provides a roadmap for the future, emphasizing its translational potential.

RECENT FINDINGS

Excitatory synapses between neurons and cancer cells that drive growth and invasion have been detected and characterized. In addition, a plethora of paracrine, mostly tumor-promoting neuro-cancer interactions are reported, and a neuro-immuno-cancer axis emerges. Cancer cell-intrinsic neural properties, and cancer (therapy) effects on the nervous system that cause morbidity in patients and can establish harmful feedback loops receive increasing attention. Despite the relative novelty of these findings, therapies that inhibit key mechanisms of this neuro-cancer crosstalk are developed, and already tested in clinical trials, largely by repurposing of approved drugs.

SUMMARY

Neuro-cancer interactions are manyfold, have multiple clinical implications, and can lead to novel neuroscience-instructed cancer therapies and improved therapies of neurological dysfunctions and cancer pain. The development of biomarkers and identification of most promising therapeutic targets is crucial.

Neuron-oligodendroglial interactions in health and malignant disease

Experience sculpts brain structure and function. Activity-dependent modulation of the myelinated infrastructure of the nervous system has emerged as a dimension of adaptive change during childhood development and in adulthood. Myelination is a richly dynamic process, with neuronal activity regulating oligodendrocyte precursor cell proliferation, oligodendrogenesis and myelin structural changes in some axonal subtypes and in some regions of the nervous system. This myelin plasticity and consequent changes to conduction velocity and circuit dynamics can powerfully influence neurological functions, including learning and memory. Conversely, disruption of the mechanisms mediating adaptive myelination can contribute to cognitive impairment. The robust effects of neuronal activity on normal oligodendroglial precursor cells, a putative cellular origin for many forms of glioma, indicates that dysregulated or 'hijacked' mechanisms of myelin plasticity could similarly promote growth in this devastating group of brain cancers. Indeed, neuronal activity promotes the pathogenesis of many forms of glioma in preclinical models through activity-regulated paracrine factors and direct neuron-to-glioma synapses. This synaptic integration of glioma into neural circuits is central to tumour growth and invasion. Thus, not only do neuron-oligodendroglial interactions modulate neural circuit structure and function in the healthy brain, but neuron-glioma interactions also have important roles in the pathogenesis of glial malignancies.

Tumor heterogeneity and tumor-microglia interactions in primary and recurrent IDH1-mutant gliomas

The isocitrate dehydrogenase (IDH) gene is recurrently mutated in adult diffuse gliomas. IDH-mutant gliomas are categorized into oligodendrogliomas and astrocytomas, each with unique pathological features. Here, we use single-nucleus RNA and ATAC sequencing to compare the molecular heterogeneity of these glioma subtypes. In addition to astrocyte-like, oligodendrocyte progenitor-like, and cycling tumor subpopulations, a tumor population enriched for ribosomal genes and translation elongation factors is primarily present in oligodendrogliomas. Longitudinal analysis of astrocytomas indicates that the proportion of tumor subpopulations remains stable in recurrent tumors. Analysis of tumor-associated microglia/macrophages (TAMs) reveals significant differences between oligodendrogliomas, with astrocytomas harboring inflammatory TAMs expressing phosphorylated STAT1, as confirmed by immunohistochemistry. Furthermore, inferred receptor-ligand interactions between tumor subpopulations and TAMs may contribute to TAM state diversity. Overall, our study sheds light on distinct tumor populations, TAM heterogeneity, TAM-tumor interactions in IDH-mutant glioma subtypes, and the relative stability of tumor subpopulations in recurrent astrocytomas.

High-sensitive spatially resolved T cell receptor sequencing with SPTCR-seq

Spatial resolution of the T cell repertoire is essential for deciphering cancer-associated immune dysfunction. Current spatially resolved transcriptomic technologies are unable to directly annotate T cell receptors (TCR). We present spatially resolved T cell receptor sequencing (SPTCR-seq), which integrates optimized target enrichment and long-read sequencing for highly sensitive TCR sequencing. The SPTCR computational pipeline achieves yield and coverage per TCR comparable to alternative single-cell TCR technologies. Our comparison of PCR-based and SPTCR-seq methods underscores SPTCR-seq's superior ability to reconstruct the entire TCR architecture, including V, D, J regions and the complementarity-determining region 3 (CDR3). Employing SPTCR-seq, we assess local T cell diversity and clonal expansion across spatially discrete niches. Exploration of the reciprocal interaction of the tumor microenvironmental and T cells discloses the critical involvement of NK and B cells in T cell exhaustion. Integrating spatially resolved omics and TCR sequencing provides as a robust tool for exploring T cell dysfunction in cancers and beyond.