1p/19q co-deletion status is associated with distinct tumor-associated macrophage infiltration in IDH mutated lower-grade gliomas

Insights of immune cell heterogeneity, tumor-initiated subtype transformation, drug resistance, treatment and detecting technologies in glioma microenvironment

BACKGROUND

With the gradual understanding of glioma development and the immune microenvironment, many immune cells have been discovered. Despite the growing comprehension of immune cell functions and the clinical application of immunotherapy, the precise roles and characteristics of immune cell subtypes, how glioma induces subtype transformation of immune cells and its impact on glioma progression have yet to be understood.

AIM OF THE REVIEW

In this review, we comprehensively center on the four major immune cells within the glioma microenvironment, particularly neutrophils, macrophages, lymphocytes, myeloid-derived suppressor cells (MDSCs), and other significant immune cells. We discuss (1) immune cell subtype markers, (2) glioma-induced immune cell subtype transformation, (3) the mechanisms of each subtype influencing chemotherapy resistance, (4) therapies targeting immune cells, and (5) immune cell-associated single-cell sequencing. Eventually, we identified the characteristics of immune cell subtypes in glioma, comprehensively summarized the exact mechanism of glioma-induced immune cell subtype transformation, and concluded the progress of single-cell sequencing in exploring immune cell subtypes in glioma.

KEY SCIENTIFIC CONCEPTS OF REVIEW

In conclusion, we have analyzed the mechanism of chemotherapy resistance detailly, and have discovered prospective immunotherapy targets, excavating the potential of novel immunotherapies approach that synergistically combines radiotherapy, chemotherapy, and surgery, thereby paving the way for improved immunotherapeutic strategies against glioma and enhanced patient outcomes.

Efficient diagnosis of IDH-mutant gliomas: 1p/19qNET assesses 1p/19q codeletion status using weakly-supervised learning

Accurate identification of molecular alterations in gliomas is crucial for their diagnosis and treatment. Although, fluorescence in situ hybridization (FISH) allows for the observation of diverse and heterogeneous alterations, it is inherently time-consuming and challenging due to the limitations of the molecular method. Here, we report the development of 1p/19qNET, an advanced deep-learning network designed to predict fold change values of 1p and 19q chromosomes and classify isocitrate dehydrogenase (IDH)-mutant gliomas from whole-slide images. We trained 1p/19qNET on next-generation sequencing data from a discovery set (DS) of 288 patients and utilized a weakly-supervised approach with slide-level labels to reduce bias and workload. We then performed validation on an independent validation set (IVS) comprising 385 samples from The Cancer Genome Atlas, a comprehensive cancer genomics resource. 1p/19qNET outperformed traditional FISH, achieving R2 values of 0.589 and 0.547 for the 1p and 19q arms, respectively. As an IDH-mutant glioma classifier, 1p/19qNET attained AUCs of 0.930 and 0.837 in the DS and IVS, respectively. The weakly-supervised nature of 1p/19qNET provides explainable heatmaps for the results. This study demonstrates the successful use of deep learning for precise determination of 1p/19q codeletion status and classification of IDH-mutant gliomas as astrocytoma or oligodendroglioma. 1p/19qNET offers comparable results to FISH and provides informative spatial information. This approach has broader applications in tumor classification.

Wnt signaling regulates MFSD2A-dependent drug delivery through endothelial transcytosis in glioma

BACKGROUND

Systemic delivery of anti-tumor therapeutic agents to brain tumors is thwarted by the blood-brain barrier (BBB), an organotypic specialization of brain endothelial cells (ECs). A failure of pharmacological compounds to cross BBB is one culprit for the dismal prognosis of glioblastoma (GBM) patients. Identification of novel vascular targets to overcome the challenges posed by the BBB in tumors for GBM treatment is urgently needed.

METHODS

Temozolomide (TMZ) delivery was investigated in CT2A and PDGFB-driven RCAS/tv-a orthotopic glioma models. Transcriptome analysis was performed on ECs from murine gliomas. Mfsd2a deficient, Cav1 deficient, and Mfsd2a EC-specific inducible mice were developed to study the underlying molecular mechanisms.

RESULTS

We demonstrated that inhibiting Wnt signaling by LGK974 could increase TMZ delivery and sensitize glioma to chemotherapy in both murine glioma models. Transcriptome analysis of ECs from murine gliomas revealed that Wnt signaling inhibition enhanced vascular transcytosis as indicated by the upregulation of PLVAP and downregulation of MFSD2A. Mfsd2a deficiency in mice enhances TMZ delivery in tumors, whereas constitutive expression of Mfsd2a in ECs suppresses the enhanced TMZ delivery induced by Wnt pathway inhibition in murine glioma. In addition, Wnt signaling inhibition enhanced caveolin-1 (Cav1)-positive caveolae-mediated transcytosis in tumor ECs. Moreover, Wnt signaling inhibitor or Mfsd2a deficiency fails to enhance TMZ penetration in tumors from Cav1-deficient mice.

CONCLUSIONS

These results demonstrated that Wnt signaling regulates MFSD2A-dependent TMZ delivery through a caveolae-mediated EC transcytosis pathway. Our findings identify Wnt signaling as a promising therapeutic target to improve drug delivery for GBM treatment.

New insights into the Immune TME of adult-type diffuse gliomas

PURPOSE OF REVIEW

Adult-type diffuse gliomas are highly heterogeneous tumors. Bulk transcriptome analyses suggested that the composition of the tumor microenvironment (TME) corresponds to genetic and clinical features. In this review, we highlight novel findings on the intratumoral heterogeneity of IDH-wildtype and IDH-mutant gliomas characterized at single-cell resolution, and emphasize the mechanisms shaping the immune TME and therapeutic implications.

RECENT FINDINGS

Emergent evidence indicates that in addition to genetic drivers, epigenetic mechanisms and microenvironmental factors influence the glioma subtypes. Interactions between glioma and immune cells contribute to immune evasion, particularly in aggressive tumors. Spatial and temporal heterogeneity of malignant and immune cell subpopulations is high in recurrent gliomas. IDH-wildtype and IDH-mutant tumors display distinctive changes in their myeloid and lymphoid compartments, and D-2HG produced by IDH-mutant cells impacts the immune TME.

SUMMARY

The comprehensive dissection of the intratumoral ecosystem of human gliomas using single-cell and spatial transcriptomic approaches advances our understanding of the mechanisms underlying the immunosuppressed state of the TME, supports the prognostic value of tumor-associated macrophages and microglial cells, and sheds light on novel therapeutic options.

The roles of IDH1 in tumor metabolism and immunity

IDH1 is a key metabolic enzyme for cellular respiration in the tricarboxylic acid (TCA) cycle that can convert isocitrate into α-ketoglutarate (α-KG) and generate NADPH. The reduction of IDH1 may affect dioxygenase activity and damage the body's detoxification mechanism. Many studies have shown that IDH1 is closely related to the occurrence and development of tumors, and the changes in IDH1 expression levels or gene mutations have appeared in many tumor tissues and produced a series of metabolic and immunity changes at the same time. To better understand the relationship between IDH1 and tumor development, this article reviews the latest advances in IDH1 and tumor metabolism, tumor immunity, IDH1 regulatory mechanisms and IDH1 target inhibitors.

Targeting tumor-associated macrophages for the immunotherapy of glioblastoma: Navigating the clinical and translational landscape

Tumor-associated macrophages (TAMs) can directly clear tumor cells and enhance the phagocytic ability of immune cells. An abundance of TAMs at the site of the glioblastoma tumor indicates that TAM-targeting immunotherapy could represent a potential form of treatment for this aggressive cancer. Herein, we discuss: i) the dynamic role of TAMs in glioblastoma; ii) describe the formation of the immunosuppressive tumor microenvironment; iii) summarize the latest clinical trial data that reveal how TAM function can be regulated in favor tumor eradication; and lastly, iv) evaluate the implications of existing and novel translational approaches for treating glioblastoma in clinical practice.

Construction and validation of an angiogenesis-related gene expression signature associated with clinical outcome and tumor immune microenvironment in glioma

Background: Glioma is the most prevalent malignant intracranial tumor. Many studies have shown that angiogenesis plays a crucial role in glioma tumorigenesis, metastasis, and prognosis. In this study, we conducted a comprehensive analysis of angiogenesis-related genes (ARGs) in glioma.

Methods: RNA-sequencing data of glioma patients were obtained from TCGA and CGGA databases. Via consensus clustering analysis, ARGs in the sequencing data were distinctly classified into two subgroups. We performed univariate Cox regression analysis to determine prognostic differentially expressed ARGs and least absolute shrinkage and selection operator Cox regression to construct a 14-ARG risk signature. The CIBERSORT algorithm was used to explore immune cell infiltration, and the ESTIMATE algorithm was applied to calculate immune and stromal scores.

Results: We found that the 14-ARG signature reflected the infiltration characteristics of different immune cells in the tumor immune microenvironment. Additionally, total tumor mutational burden increased significantly in the high-risk group. We combined the 14-ARG signature with patient clinicopathological data to construct a nomogram for predicting 1-, 3-, and 5-year overall survival with good accuracy. The predictive value of the prognostic model was verified in the CGGA cohort. SPP1 was a potential biomarker of glioma risk and was involved in the proliferation, invasion, and angiogenesis of glioma cells.

Conclusion: In conclusion, we established and validated a novel ARG risk signature that independently predicted the clinical outcomes of glioma patients and was associated with the tumor immune microenvironment.

New insights from the single-cell level: Tumor associated macrophages heterogeneity and personalized therapy

Tumor-associated macrophages (TAMs) are important immune cells in the tumor microenvironment, and their invasion in tumors is closely related to poor prognosis. Although TAMs are recognized as therapeutic targets, their heterogeneity makes studying tumor mechanism and developing drugs targeting TAMs difficult. The study of TAMs heterogeneity can be used to analyze the mechanism of tumor progression and drug resistance, and may provide possible treatment strategies for cancer patients. Single-cell RNA sequencing (scRNA-seq) can reveal the RNA expression profile for each TAM to distinguish heterogeneity, thereby providing a more efficient detection method and more accurate information for TAM-related studies. In this review, by summarizing the research progress in macrophage heterogeneity and other aspects of scRNA-seq over the past five years, we introduced the development of scRNA-seq technology and its application status in solid tumors, analyzed the advantages and selections of scRNA-seq in TAMs, and summarized the detailed specific research fields. To explore the mechanism of tumor progression and drug intervention from single cell level will provide new perspective for personalized treatment strategies targeting macrophages.

Siglec-9, a Putative Immune Checkpoint Marker for Cancer Progression Across Multiple Cancer Types

Siglec-9, a cell surface transmembrane receptor mainly expressed on B cells, CD56⁺ NK cells, and CD4⁺ and CD8⁺ T cells, is strongly related to the tumor immune microenvironment. However, the expression pattern of Siglec-9 and its prognostic potential have not been investigated in a pan-cancer perspective. This study aimed to explore the association of Siglec-9 with prognosis, tumor stage, molecular subtype, and the immune microenvironment in pan-cancer. The mRNA expression of Siglec-9 was obtained from The Cancer Genome Atlas (TCGA), the Broad Institute Cancer Cell Line Encyclopedia (CCLE), and Genotype-Tissue Expression (GTEx). The relationship between Siglec-9 mRNA expression and prognosis was evaluated by the Kaplan–Meier analysis. The correlation between Siglec-9 and tumor-infiltrating immune cells, immune subtype, and molecular subtype was evaluated on Tumor Immune Estimation Resource (TIMER) and Integrated Repository Portal for Tumor-Immune System Interactions (TISIDB). The correlation between Siglec-9 expression and immune checkpoint, mismatch repair (MMR), DNA methyltransferase (DNMT), tumor mutation burden (TMB), and microsatellite instability (MSI) was also analyzed. It showed that Siglec-9 expression was significantly altered in most TCGA tumors. Siglec-9 expression was associated with the prognosis of patients with adrenocortical carcinoma (ACC), lung adenocarcinoma (LUSC), thymoma (THYM), colon adenocarcinoma (COAD), glioblastoma multiforme (GBM), prostate adenocarcinoma (PRAD), esophageal carcinoma (ESCA), and brain lower-grade glioma (LGG). Particularly, increased Siglec-9 expression was strongly correlated with poor prognosis in LGG. Correlation between Siglec-9 expression and tumor stage was also observed in various cancers. In addition, Siglec-9 was positively associated with infiltration of immune cells including neutrophils, dendritic cells (DCs), macrophage, and CD4⁺ and CD8⁺ T cells. Moreover, a significant correlation between Siglec-9 and MSI, TMB, MMR, DNMT, immune checkpoint, immune subtype, molecular subtype, and immunomodulators was observed in multiple cancers. Specifically, poor prognostic value and strong correlation to immune cell infiltration were verified with the LGG dataset from the Chinese Glioma Genome Atlas (CGGA). These findings indicated that Siglec-9 can be a novel biomarker and a potential target for cancer immunotherapy.

Immune Infiltration Associated MAN2B1 Is a Novel Prognostic Biomarker for Glioma

Mannosidase Alpha Class 2B Member 1 (MAN2B1) gene encodes lysosomal alpha-d-mannosidase involved in the ordered degradation of N-linked glycoproteins. Alteration in MAN2B1 has been proved to be accountable for several diseases. However, the relationship between MAN2B1 and glioma malignancy remains unclear. In this study, RNA-seq data from The Cancer Genome Atlas and the Chinese Glioma Genome Atlas datasets were analyzed to explore the correlation between MAN2B1 and clinicopathological features, prognosis, and somatic mutations in gliomas. We found that MAN2B1 was elevated in glioma and was correlated with malignant clinical and molecular features. Upregulated expression of MAN2B1 is prognostic for poor outcomes in glioma patients. Different frequencies of somatic mutations were found in gliomas between high and low MAN2B1 expression. Real-time quantitative polymerase chain reaction, western blot, and immunohistochemistry staining from glioma patient samples and cell lines were used to validate bioinformatic findings. Functional enrichment analysis showed that MAN2B1 was involved in immune and inflammation processes. Moreover, MAN2B1 expression was strongly correlated with M2 macrophages and weakly correlated with M1 macrophages. Further analysis confirmed that MAN2B1 was closely associated with the markers of M2 macrophages and tumor-associated macrophages. Taken together, MAN2B1 is a potential prognostic biomarker in glioma and associates with immune infiltration.

Uncovering a Key Role of ETS1 on Vascular Abnormality in Glioblastoma

Glioblastoma (GBM) is the most aggressive type of brain tumor. Microvascular proliferation and abnormal vasculature are the hallmarks of the GBM, aggravating disease progression and increasing patient morbidity. Here, we uncovered a key role of ETS1 on vascular abnormality in glioblastoma. ETS1 was upregulated in endothelial cells from human tumors compared to endothelial cells from paired control brain tissue. Knockdown of Ets1 in mouse brain endothelial cells inhibited cell migration and proliferation, and suppressed expression of genes associated with vascular abnormality in GBM. ETS1 upregulation in tumor ECs was dependent on TGFβ signaling, and targeting TGFβ signaling by inhibitor decreased tumor angiogenesis and vascular abnormality in CT-2A glioma model. Our results identified ETS1 as a key factor regulating tumor angiogenesis, and suggested that TGFβ inhibition may suppress the vascular abnormality driven by ETS1.

Single-Cell Omics in Dissecting Immune Microenvironment of Malignant Gliomas-Challenges and Perspectives

Single-cell technologies allow precise identification of tumor composition at the single-cell level, providing high-resolution insights into the intratumoral heterogeneity and transcriptional activity of cells in the tumor microenvironment (TME) that previous approaches failed to capture. Malignant gliomas, the most common primary brain tumors in adults, are genetically heterogeneous and their TME consists of various stromal and immune cells playing an important role in tumor progression and responses to therapies. Previous gene expression or immunocytochemical studies of immune cells infiltrating TME of malignant gliomas failed to dissect their functional phenotypes. Single-cell RNA sequencing (scRNA-seq) and cytometry by time-of-flight (CyTOF) are powerful techniques allowing quantification of whole transcriptomes or >30 protein targets in individual cells. Both methods provide unprecedented resolution of TME. We summarize the findings from these studies and the current state of knowledge of a functional diversity of immune infiltrates in malignant gliomas with different genetic alterations. A precise definition of functional phenotypes of myeloid and lymphoid cells might be essential for designing effective immunotherapies. Single-cell omics studies have identified crucial cell subpopulations and signaling pathways that promote tumor progression, influence patient survival or make tumors vulnerable to immunotherapy. We anticipate that the widespread usage of single-cell omics would allow rational design of oncoimmunotherapeutics.

Uncovering a Distinct Gene Signature in Endothelial Cells Associated With Contrast Enhancement in Glioblastoma

Purpose

Glioblastoma (GBM) is the most aggressive and lethal type of brain tumors. Magnetic resonance imaging (MRI) has been commonly used for GBM diagnosis. Contrast enhancement (CE) on T1-weighted sequences are presented in nearly all GBM as a result of high vascular permeability in glioblastomas. Although several radiomics studies indicated that CE is associated with distinct molecular signatures in tumors, the effects of vascular endothelial cells, the key component of blood brain barrier (BBB) controlling vascular permeability, on CE have not been thoroughly analyzed.

Methods

Endothelial cell enriched genes have been identified using transcriptome data from 128 patients by a systematic method based on correlation analysis. Distinct endothelial cell enriched genes associated with CE were identified by analyzing difference of correlation score between CE-high and CE–low GBM cases. Immunohistochemical staining was performed on in-house patient cohort to validate the selected genes associated with CE. Moreover, a survival analysis was conducted to uncover the relation between CE and patient survival.

Results

We illustrated that CE is associated with distinct vascular molecular imprints characterized by up-regulation of pro-inflammatory genes and deregulation of BBB related genes. Among them, PLVAP is up-regulated, whereas TJP1 and ABCG2 are down-regulated in the vasculature of GBM with high CE. In addition, we found that the high CE is associated with poor prognosis and GBM mesenchymal subtype.

Conclusion

We provide an additional insight to reveal the molecular trait for CE in MRI images with special focus on vascular endothelial cells, linking CE with BBB disruption in the molecular level. This study provides a potential new direction that may be applied for the treatment optimization based on MRI features.