Immune Checkpoint Targeted Therapy in Glioma: Status and Hopes

B7-H4 reduces the infiltration of CD8+T cells and induces their anti-tumor dysfunction in gliomas

B7-H4 is a promising immune checkpoint molecule in tumor immunotherapy. Our previous study showed that high B7-H4 expression was strongly correlated with deficiency in tumor infiltrated lymphocytes (TILs) in glioma patients. On this basis, we investigated the impact of B7-H4 on CD8+TILs in gliomas and the associated molecular mechanism here. B7-H4-positive tumor samples (n=129) from our glioma cohort were used to assess B7-H4 expression and CD8+TIL quantification by immunohistochemistry. CD8+TILs from five glioma patients cultured with B7-H4 protein were used to evaluate anti-tumor dysfunction by flow cytometry and ELISpot. An orthotopic murine glioma model was used to investigate the role of B7-H4 in glioma CD8+TILs by immunohisto- chemistry and flow cytometry. CD8+TILs from glioma patients cultured with B7-H4 protein were used to explore the potential molecular mechanism by RNA sequencing and western blot. Our results showed that glioma CD8+TIL density was negatively correlated with B7-H4 expression both in glioma patient cohort (P < 0.05) and orthotopic glioma murine model (P < 0.01). B7-H4 also lowered the expression of CD137 and CD103 (P < 0.05 for both) in glioma CD8+TILs and reduced their secretion of the anti-tumor cytokines IFN-γ and TNF-α (P < 0.01 for both) in a dose-dependent manner. Furthermore, B7-H4 was found to induce early dysfunction of glioma CD8+TILs by downregulating the phosphorylation of AKT and eNOS (P < 0.05 for both). In conclusion, B7-H4 reduced the infiltration of glioma CD8+TILs and induced an anti-tumor dysfunction phenotype. B7-H4 may also impair the anti-tumor function of glioma CD8+TILs via the AKT-eNOS pathway. These results indicated that B7-H4 may serve as a potential target in future glioma immunotherapy.

IDO1 Inhibitor RY103 Suppresses Trp-GCN2-Mediated Angiogenesis and Counters Immunosuppression in Glioblastoma

Glioma is characterized by strong immunosuppression and excessive angiogenesis. Based on existing reports, it can be speculated that the resistance to anti-angiogenic drug vascular endothelial growth factor A (VEGFA) antibody correlates to the induction of novel immune checkpoint indoleamine 2,3-dioxygenase 1 (IDO1), while IDO1 has also been suggested to be related to tumor angiogenesis. Herein, we aim to clarify the potential role of IDO1 in glioma angiogenesis and the mechanism behind it. Bioinformatic analyses showed that the expressions of IDO1 and angiogenesis markers VEGFA and CD34 were positively correlated and increased with pathological grade in glioma. IDO1-overexpression-derived-tryptophan depletion activated the general control nonderepressible 2 (GCN2) pathway and upregulated VEGFA in glioma cells. The tube formation ability of angiogenesis model cells could be inhibited by IDO1 inhibitors and influenced by the activity and expression of IDO1 in condition medium. A significant increase in serum VEGFA concentration and tumor CD34 expression was observed in IDO1-overexpressing GL261 subcutaneous glioma-bearing mice. IDO1 inhibitor RY103 showed positive anti-tumor efficacy, including the anti-angiogenesis effect and upregulation of natural killer cells in GL261 glioma-bearing mice. As expected, the combination of RY103 and anti-angiogenesis agent sunitinib was proved to be a better therapeutic strategy than either monotherapy.

Recent advances in biomimetic strategies for the immunotherapy of glioblastoma

Immunotherapy is regarded as one of the most promising approaches for treating tumors, with a multitude of immunotherapeutic thoughts currently under consideration for the lethal glioblastoma (GBM). However, issues with immunotherapeutic agents, such as limited in vivo stability, poor blood-brain barrier (BBB) penetration, insufficient GBM targeting, and represented monotherapy, have hindered the success of immunotherapeutic interventions. Moreover, even with the aid of conventional drug delivery systems, outcomes remain suboptimal. Biomimetic strategies seek to overcome these formidable drug delivery challenges by emulating nature's intelligent structures and functions. Leveraging the variety of biological structures and functions, biomimetic drug delivery systems afford a versatile platform with enhanced biocompatibility for the co-delivery of diverse immunotherapeutic agents. Moreover, their inherent capacity to traverse the BBB and home in on GBM holds promise for augmenting the efficacy of GBM immunotherapy. Thus, this review begins by revisiting the various thoughts and agents on immunotherapy for GBM. Then, the barriers to successful GBM immunotherapy are analyzed, and the corresponding biomimetic strategies are explored from the perspective of function and structure. Finally, the clinical translation's current state and prospects of biomimetic strategy are addressed. This review aspires to provide fresh perspectives on the advancement of immunotherapy for GBM.

Clinical significance of immune-related antigen CD58 in gliomas and analysis of its potential core related gene clusters

Background

The clinical significance of immune-related antigen CD58 in gliomas remains uncertain. The aim of this study was to examine the clinical importance and possible core related genes of CD58 in gliomas.

Methods

Pan-cancer analysis was to observe the association between CD58 and different tumors, glioma RNA sequencing data and clinical sample analyses were used to observe the relationship between CD58 and glioma, shRNA interference models were to observe the impact of CD58 on glioma cell function, and four glioma datasets and two online analysis platforms were used to explore the core related genes affecting the correlation between CD58 and glioma.

Results

High CD58 expression was associated with worse prognosis in various tumors and higher malignancy in glioma. Down regulation of CD58 expression was linked to decreased proliferation, increased apoptosis, and reduced metastasis in glioma cells. The pathways involved in CD58-related effects were enriched for immune cell adhesion and immune factor activation, and the core genes were CASP1, CCL2, IL18, MYD88, PTPRC, and TLR2. The signature of CD58 and its core-related genes showed superior predictive power for glioma prognosis.

Conclusion

High CD58 expression is correlated with more malignant glioma types, and also an independent risk factor for mortality in glioma. CD58 and its core-related genes may serve as novel biomarkers for diagnosing and treating glioma.

Treatment advances in high-grade gliomas

High-grade gliomas (HGG) pose significant challenges in modern tumour therapy due to the distinct biological properties and limitations of the blood-brain barrier. This review discusses recent advancements in HGG treatment, particularly in the context of immunotherapy and cellular therapy. Initially, treatment strategies focus on targeting tumour cells guided by the molecular characteristics of various gliomas, encompassing chemotherapy, radiotherapy and targeted therapy for enhanced precision. Additionally, technological enhancements are augmenting traditional treatment modalities. Furthermore, immunotherapy, emphasising comprehensive tumour management, has gained widespread attention. Immune checkpoint inhibitors, vaccines and CAR-T cells exhibit promising efficacy against recurrent HGG. Moreover, emerging therapies such as tumour treating fields (TTFields) offer additional treatment avenues for patients with HGG. The combination of diverse treatments holds promise for improving the prognosis of HGG, particularly in cases of recurrence.

Integrated profiling identifies ferredoxin 1 as an immune-related biomarker of malignant phenotype in glioma

Background

Glioma, a highly resistant and recurrent type of central nervous system tumor, poses a significant challenge in terms of effective drug treatments and its associated mortality rates. Despite the discovery of Ferredoxin 1 (FDX1) as a crucial participant in cuproptosis, an innovative mechanism of cellular demise, its precise implications for glioma prognosis and tumor immune infiltration remain inadequately elucidated.

Methods

To analyze pan-cancer data, we employed multiple public databases. Gene expression evaluation was performed using tissue microarray (TMA) and single-cell sequencing data. Furthermore, four different approaches were employed to assess the prognostic importance of FDX1 in glioma. We conducted the analysis of differential expression genes (DEGs) and Gene Set Enrichment Analysis (GSEA) to identify immune-related predictive signaling pathways. Somatic mutations were assessed using Tumor Mutation Burden (TMB) and waterfall plots. Immune cell infiltration was evaluated with five different algorithms. Furthermore, we performed in vitro investigations to evaluate the biological roles of FDX1 in glioma.

Results

Glioma samples exhibited upregulation of FDX1, which in turn predicted poor prognosis and was positively associated with unfavorable clinicopathological characteristics. Notably, the top four enriched signaling pathways were immune-related, and the discovery revealed a connection between the expression of FDX1 and the frequency of mutations or the TMB. The FDX1_high group exhibited heightened infiltration of immune cells, and there existed a direct association between the expression of FDX1 and the regulation of immune checkpoint. In vitro experiments demonstrated that FDX1 knockdown reduced proliferation, migration, invasion and transition from G2 to M phase in glioma cells.

Conclusion

In glioma, FDX1 demonstrated a positive association with the advancement of malignancy and changes in the infiltration of immune cells.

CHRNA9 as a New Prognostic Marker and Potential Therapeutic Target in Glioma

Background: The nicotinic acetylcholine receptor (nAChR) subunit alpha-9 (CHRNA9) is a unique cholinergic receptor, which is involved in tumor proliferation, apoptosis, metastasis and chemotherapy resistance. However, the correlation between the expression level of CHRNA9 in glioma and the clinical features and prognosis of glioma patients has not been clarified. The aim of this study was to verify the expression level of CHRNA9 in glioma and its effect on prognosis by bioinformatics methods. Methods: The RNA-seq data of glioma and normal samples were obtained from the TCGA and GTEx databases. Bioinformatics methods were utilized to analyze the differential expression of CHRNA9 between tumor samples and normal samples. The potential association between CHRNA9 and the clinicopathological features of glioma patients was also investigated. The Kaplan-Meier method and Cox regression were utilized to analyze the relationship between CHRNA9 expression level and survival time and prognostic value of glioma patients. Enrichment analysis was applied to predict gene function and signaling pathways associated with CHRNA9. Experimental verification was performed using tumor tissues and paracancerous tissues from glioma patients. Results: The results of bioinformatics analysis showed that the expression of CHRNA9 was increased in glioma tissues, correlating with poor prognosis and reduced patient survival time. Enrichment analysis suggested that CHRNA9 may interact with the JAK/STAT pathway. CHRNA9 was also found to be abnormally expressed in various other tumors and associated with the expression levels of numerous immune checkpoints in glioma. The findings from the analysis of clinical samples revealed that the expression levels of both mRNA and protein of CHRNA9 in glioma tissues were higher than those in paracancerous tissues. Similarly, the mRNA expression levels of STAT3, IL-6, and TNF-α, which are crucial factors in the STAT3 pathway, were elevated in glioma tissues compared to paracancerous tissues. Conclusion: CHRNA9 is a potential prognostic marker and immunotherapy target for glioma, with its mechanism of action potentially linked to the STAT3 pathway.

Redox-responsive polymer micelles co-encapsulating immune checkpoint inhibitors and chemotherapeutic agents for glioblastoma therapy

Immunotherapy with immune checkpoint blockade (ICB) for glioblastoma (GBM) is promising but its clinical efficacy is seriously challenged by the blood-tumor barrier (BTB) and immunosuppressive tumor microenvironment. Here, anti-programmed death-ligand 1 antibodies (aPD-L1) are loaded into a redox-responsive micelle and the ICB efficacy is further amplified by paclitaxel (PTX)-induced immunogenic cell death (ICD) via a co-encapsulation approach for the reinvigoration of local anti-GBM immune responses. Consequently, the micelles cross the BTB and are retained in the reductive tumor microenvironment without altering the bioactivity of aPD-L1. The ICB efficacy is enhanced by the aPD-L1 and PTX combination with suppression of primary and recurrent GBM, accumulation of cytotoxic T lymphocytes, and induction of long-lasting immunological memory in the orthotopic GBM-bearing mice. The co-encapsulation approach facilitating efficient antibody delivery and combining with chemotherapeutic agent-induced ICD demonstrate that the chemo-immunotherapy might reprogram local immunity to empower immunotherapy against GBM.

Molecular and immunological features of TREM1 and its emergence as a prognostic indicator in glioma

Triggering receptor expressed on myeloid cells 1 (TREM1), which belongs to the Ig-like superfamily expressed on myeloid cells, is reportedly involved in various diseases but has rarely been studied in glioma. In this study, the prognostic value and functional roles of TREM2 in glioma were analyzed. TERM1 was observed to be significantly upregulated in GBM compared to in other grade gliomas and was associated with poor prognosis. Increased TREM1 accompanied distinct mutation and amplification of driver oncogenes. Moreover, gene ontology and KEGG analyses showed that TREM1 might play a role in immunologic biological processes in glioma. TREM1 was also found to be tightly correlated with immune checkpoint molecules. xCell research revealed a link between TREM1 expression and multiple immune cell types, especially monocytes and macrophages. Single-cell analysis and immunofluorescence results showed that macrophages expressed TREM1. In vitro, inhibition of TREM1 signaling could result in a decrease in tumor-promoting effects of monocytes/TAMs. In summary, TREM1 may be a potential independent prognostic factor and immune target, which might provide new avenues to improve the efficacy of immunotherapy in glioma patients.

Identification of SRSF10 as a promising prognostic biomarker with functional significance among SRSFs for glioma

AIMS

The serine/arginine-rich splicing factor (SRSF) protein family members are essential mediators of the alternative splicing (AS) regulatory network, which is tightly implicated in cancer progression. However, the expression, clinical correlation, immune infiltration, and prognostic value of SRSFs in gliomas remain unclear.

MATERIALS AND METHODS

Glioma samples were extracted from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) datasets. Several databases, such as HPA, DAVID, UALCAN were used to comprehensively explore the roles of SRSFs. In addition, experimental validation of SRSF10 was also conducted.

KEY FINDINGS

Here, we found the expression alterations of the SRSF family in glioma samples using data from the TCGA and CGGA_325 datasets. Among the 12 genes, most were found to be closely associated with glioma clinical features, which linked to poor prognosis in glioma patients. Interestingly, survival analysis identified only SRSF10 as a potential independent risk prognostic biomarker for glioma patients. Immune analysis indicated that glioma patients with high SRSF10 expression may respond well to immunotherapies targeting immune checkpoint (ICP) genes. Finally, knocking down SRSF10 reduced glioma cell viability, induced G1 cell cycle arrest, and induced the exclusion of bcl-2-associated transcription factor 1 (BCLAF1) exon 5a.

SIGNIFICANCE

Overall, this study uncovers the oncogenic roles of most SRSF family members in glioma, with the exception of SRSF5, while highlighting SRSF10 as a potential novel independent prognostic biomarker for glioma.

Caveolin-1 promotes glioma proliferation and metastasis by enhancing EMT via mediating PAI-1 activation and its correlation with immune infiltrates

Glioma is typically characterized by a poor prognosis and is associated with a decline in the quality of life as the disease advances. However, the development of effective therapies for glioma has been inadequate. Caveolin-1 (CAV-1) is a membrane protein that plays a role in caveolae formation and interacts with numerous signaling proteins, compartmentalizing them in caveolae and frequently exerting direct control over their activity through binding to its scaffolding domain. Although CAV-1 is a vital regulator of tumour progression, its role in glioma remains unclear. Our findings indicated that the knockdown of CAV-1 significantly inhibits the proliferation and metastasis of glioma. Subsequent mechanistic investigations demonstrated that CAV-1 promotes proliferation and metastasis by activating the photoshatidylinositol 3-kinase/protein kinase B (PI3K/Akt) signaling pathway. Furthermore, we demonstrated that CAV-1 overexpression upregulates the expression of serpin peptidase inhibitor, class E, member 1 (SERPINE1, also known as PAI-1), which serves as a marker for the epithelial-mesenchymal transition (EMT) process. Further research showed that PAI-1 knockdown abolished the CAV-1 mediated activation of PI3K/Akt signaling pathway. In glioma tissues, CAV-1 expression exhibited a correlation with unfavorable prognosis and immune infiltration among glioma patients. In summary, our study provided evidence that CAV-1 activates the PI3K/Akt signaling pathway by upregulating PAI-1, thereby promoting the proliferation and metastasis of glioma through enhanced epithelial-mesenchymal transition (EMT) and angiogenesis, and CAV-1 is involved in the immune infiltration.

A novel immunogenic cell death-related gene risk signature can identify biomarkers of gliomas and predict the immunotherapeutic response

Immunogenic cell death (ICD) is a type of cell death that plays a pivotal role in immunity. Recent studies have identified the critical role of ICD in glioma treatment. This study aimed to use ICD-associated differentially expressed genes (ICD-DEGs) to predict survival of glioma patients. We investigated the relationship between clinical prognosis and the date-to-clinical prognosis of 1,721 glioma patients by examining the expression, methylation, and mutation status of ICD-related genes (IRGs) in these patients. Our prediction of survival in glioma patients was based on three risk genes, and we explored the association between these genes and clinical outcomes. Additionally, IRG expression was used to stratify glioma patients. We further examined the relationship among the three subgroups in terms of immune microenvironment heterogeneity and immunotherapy response. In addition, this study also included analyses of histograms and sensitivity to antitumor drugs. The expression of these genes was externally validated by RT-qPCR, Western blot (WB), and immunohistochemistry (IHC) in glioma and normal brain tissue. Our findings reveal that most IRGs are overexpressed in glioma tumor tissues, and this high expression was confirmed through histological validation. We successfully developed predictive models for three prognostic genes associated with ICD. These models not only predict survival in glioma but also correlate with the tumor's immune microenvironment. Finally, using consensus clustering, we identified three ICD-associated subtypes. Notably, patients with the C3 subtype showed high levels of immune cell infiltration, whereas those with the C1 subtype exhibited lower levels of immune cell infiltration. We successfully developed an innovative IRG-based systematic approach for evaluating glioma patients. This stratification in experimental studies opens new avenues for prognosis and assessing immunotherapy responses in glioma patients. Our study demonstrates the effectiveness of this approach in treating glioma, potentially paving the way for more promising and effective therapeutic strategies in the future.

Targeted Glioma Therapy-Clinical Trials and Future Directions

Glioblastoma multiforme (GBM) is the most common type of glioma, with a median survival of 14.6 months post-diagnosis. Understanding the molecular profile of such tumors allowed the development of specific targeted therapies toward GBM, with a major role attributed to tyrosine kinase receptor inhibitors and immune checkpoint inhibitors. Targeted therapeutics are drugs that work by specific binding to GBM-specific or overexpressed markers on the tumor cellular surface and therefore contain a recognition moiety linked to a cytotoxic agent, which produces an antiproliferative effect. In this review, we have summarized the available information on the targeted therapeutics used in clinical trials of GBM and summarized current obstacles and advances in targeted therapy concerning specific targets present in GBM tumor cells, outlined efficacy endpoints for major classes of investigational drugs, and discussed promising strategies towards an increase in drug efficacy in GBM.

Serpin family H member 1 and its related collagen gene network are the potential prognostic biomarkers and anticancer targets for glioma

Serpin family H member 1 (SERPINH1) is responsible for encoding the protein known as heat shock protein 47, which functions as a molecular chaperone specific to collagen (COL). This protein has been identified as a potential therapeutic target for COL-related disorders. In this study, we aimed to investigate the role of SERPINH1 in the tumorigenicity of gliomas. To achieve this, we utilized various bioinformatics tools to analyze gene expression, overall survival, protein-protein interactions, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and Gene Set Enrichment Analysis (GSEA). Based on The Cancer Genome Atlas database revealed that SERPINH1 and four COL family members (COL1A1, COL3A1, COL4A1, and COL4A2) expression are significantly upregulated in glioma tissues compared with normal nontumor tissues. GO, KEGG, and GSEA analyses exhibited that SERPINH1 is implicated in the establishment and degradation of COL-containing extracellular matrix (ECM), focal adhesion, and ECM-receptor interaction in glioma. SERPINH1 is an independent prognostic factor, exhibiting a positive association with the augmentation of neutrophils and macrophages, as well as the manifestation of immune checkpoint molecules within glioma. Experimental assessments conducted both in vitro and in vivo demonstrated that the suppression of SERPINH1 impeded the migratory, invasive, and proliferative capacities of glioma cells, while concurrently fostering cellular apoptosis. Consequently, SERPINH1 emerges as an oncogenic gene and an independent prognostic marker for glioma, potentially facilitating the advancement of immunotherapeutic interventions for the treatment of glioma.

Leveraging a disulfidptosis‑related lncRNAs signature for predicting the prognosis and immunotherapy of glioma

BACKGROUND

Gliomas, a prevalent form of primary brain tumors, are linked with a high mortality rate and unfavorable prognoses. Disulfidptosis, an innovative form of programmed cell death, has received scant attention concerning disulfidptosis-related lncRNAs (DRLs). The objective of this investigation was to ascertain a prognostic signature utilizing DRLs to forecast the prognosis and treatment targets of glioma patients.

METHODS

RNA-seq data were procured from The Cancer Genome Atlas database. Disulfidptosis-related genes were compiled from prior research. An analysis of multivariate Cox regression and the least absolute selection operator was used to construct a risk model using six DRLs. The risk signature's performance was evaluated via Kaplan-Meier survival curves and receiver operating characteristic curves. Additionally, functional analysis was carried out using GO, KEGG, and single-sample GSEA to investigate the biological functions and immune infiltration. The research also evaluated tumor mutational burden, therapeutic drug sensitivity, and consensus cluster analysis. Reverse transcription quantitative PCR was conducted to validate the expression level of DRLs.

RESULTS

A prognostic signature comprising six DRLs was developed to predict the prognosis of glioma patients. High-risk patients had significantly shorter overall survival than low-risk patients. The robustness of the risk model was validated by receiver operating characteristic curves and subgroup survival analysis. Risk model was used independently as a prognostic indicator for the glioma patients. Notably, the low-risk patients displayed a substantial decrease in the immune checkpoints, the proportion of immune cells, ESTIMATE and immune score. IC50 values from the different risk groups allowed us to discern three drugs for the treatment of glioma patients. Lastly, the potential clinical significance of six DRLs was determined.

CONCLUSIONS

A novel six DRLs signature was developed to predict prognosis and may provide valuable insights for patients with glioma seeking novel immunotherapy and targeted therapy.

Identification of immune-related hub genes and construction of an immune-related gene prognostic index for low-grade glioma

Low-grade glioma (LGG) poses significant management challenges and has a dismal prognosis. While immunotherapy has shown significant promise in cancer treatment, its progress in glioma has confronted with challenges. In our study, we aimed to develop an immune-related gene prognostic index (IRGPI) which could be used to evaluate the response and efficacy of LGG patients with immunotherapy. We included a total of 529 LGG samples from TCGA database and 1152 normal brain tissue samples from the GTEx database. Immune-related differentially expressed genes (DEGs) were screened. Then, we used weighted gene co-expression network analysis (WGCNA) to identify immune-related hub genes in LGG patients and performed Cox regression analysis to construct an IRGPI. The median IRGPI was used as the cut-off value to categorize LGG patients into IRGPI-high and low subgroups, and the molecular and immune mechanism in IRGPI-defined subgroups were analysed. Finally, we explored the relationship between IRGPI-defined subgroups and immunotherapy related indicators in patients after immunotherapy. Three genes (RHOA, NFKBIA and CCL3) were selected to construct the IRGPI. In a survival analysis using TCGA cohort as a training set, patients in the IRGPI-low subgroup had a better OS than those in IRGPI-high subgroup, consistent with the results in CGGA cohort. The comprehensive results showed that IRGPI-low subgroup had a more abundant activated immune cell population and lower TIDE score, higher MSI, higher TMB score, lower T cell dysfunction score, more likely benefit from ICIs therapy. IRGPI is a promising biomarker in the field of LGG ICIs therapy to distinguish the prognosis, the molecular and immunological characteristics of patients.

Unexpected Transient Glioblastoma Regression in a Patient Previously Treated with Bacillus Calmette-Guérin Therapy: A Case Report and Immunomodulatory Effects Hypothesis

(1) Background: Glioblastoma multiforme (GBM) is a highly aggressive brain tumor with limited treatment options and poor prognosis. Bacillus Calmette-Guérin (BCG), a live attenuated strain of Mycobacterium bovis, has been used as an immunotherapeutic agent in bladder cancer and has shown non-specific beneficial effects. This report presents a unique case of GBM regression following BCG therapy for bladder cancer, suggesting the potential systemic immunomodulatory effects of BCG on GBM. (2) Case Presentation: A 67-year-old male with a history of bladder cancer treated with BCG presented with neurological symptoms. Imaging revealed two GBM lesions, and surgery was performed to remove one. Subsequently, the patient experienced complete tumor regression after initial stability. (3) Conclusions: This case highlights the potential of BCG or other immunotherapies in GBM treatment and underscores the need for further research. Understanding the immunomodulatory effects of BCG on GBM could lead to innovative therapies for this devastating disease; although, overcoming the immune evasion mechanisms in the brain is a significant challenge. Further investigation is warranted to explore this promising avenue of research.

Interaction, immune infiltration characteristics and prognostic modeling of efferocytosis-related subtypes in glioblastoma

BACKGROUND

Efferocytosis is a biological process in which phagocytes remove apoptotic cells and vesicles from tissues. This process is initiated by the release of inflammatory mediators from apoptotic cells and plays a crucial role in resolving inflammation. The signals associated with efferocytosis have been found to regulate the inflammatory response and the tumor microenvironment (TME), which promotes the immune escape of tumor cells. However, the role of efferocytosis in glioblastoma multiforme (GBM) is not well understood and requires further investigation.

METHODS

In this study, we conducted a comprehensive analysis of 22 efferocytosis-related genes (ERGs) by searching for studies related to efferocytosis. Using bulk RNA-Seq and single-cell sequencing data, we analyzed the expression and mutational characteristics of these ERGs. By using an unsupervised clustering algorithm, we obtained ERG clusters from 549 GBM patients and evaluated the immune infiltration characteristics of each cluster. We then identified differential genes (DEGs) in the two ERG clusters and classified GBM patients into different gene clusters using univariate cox analysis and unsupervised clustering algorithms. Finally, we utilized the Boruta algorithm to screen for prognostic genes and reduce dimensionality, and the PCA algorithm was applied to create a novel efferocytosis-related scoring system.

RESULTS

Differential expression of ERGs in glioma cell lines and normal cells was analyzed by rt-PCR. Cell function experiments, on the other hand, validated TIMD4 as a tumor risk factor in GBM. We found that different ERG clusters and gene clusters have distinct prognostic and immune infiltration profiles. The ERG signature we developed provides insight into the tumor microenvironment of GBM. Patients with lower ERG scores have a better survival rate and a higher likelihood of benefiting from immunotherapy.

CONCLUSIONS

Our novel efferocytosis-related signature has the potential to be used in clinical practice for risk stratification of GBM patients and for selecting individuals who are likely to respond to immunotherapy. This can help clinicians design appropriate targeted therapies before initiating clinical treatment.

GPR37 expression as a prognostic marker in gliomas: a bioinformatics-based analysis

BACKGROUND

Gliomas are the most frequently diagnosed primary brain tumors, and are associated with multiple molecular aberrations during their development and progression. GPR37 is an orphan G protein-coupled receptor (GPCR) that is implicated in different physiological pathways in the brain, and has been linked to various malignancies. The aim of this study was to explore the relationship between GPR37 gene expression and the clinicopathological factors, patient prognosis, tumor-infiltrating immune cell signature GSEA and methylation levels in glioma.

METHODS

We explored the diagnostic value, clinical relevance, and molecular function of GPR37 in glioma using TCGA, STRING, cBioPortal, Tumor Immunity Estimation Resource (TIMER) database and MethSurv databases. Besides, the "ssGSEA" algorithm was conducted to estimate immune cells infiltration abundance, with 'ggplot2' package visualizing the results. Immunohistochemical staining of clinical samples were used to verify the speculations of bioinformatics analysis.

RESULTS

GPR37 expression was significantly higher in the glioma tissues compared to the normal brain tissues, and was linked to poor prognosis. Functional annotation of GPR37 showed enrichment of ether lipid metabolism, fat digestion and absorption, and histidine metabolism. In addition, GSEA showed that GPR37 was positively correlated to the positive regulation of macrophage derived foam cell differentiation, negative regulation of T cell receptor signaling pathway, neuroactive ligand receptor interaction, calcium signaling pathway, and negatively associated with immunoglobulin complex, immunoglobulin complex circulating, ribosome and spliceosome mediated by circulating immunoglobulin etc. TIMER2.0 and ssGSEA showed that GPR37 expression was significantly associated with the infiltration of T cells, CD8 T cell, eosinophils, macrophages, neutrophils, NK CD56dim cells, NK cells, plasmacytoid DCs (pDCs), T helper cells and T effector memory (Tem) cells. In addition, high GPR37 expression was positively correlated with increased infiltration of M2 macrophages, which in turn was associated with poor prognosis. Furthermore, GPR37 was positively correlated with various immune checkpoints (ICPs). Finally, hypomethylation of the GPR37 promoter was associated with its high expression levels and poor prognosis in glioma.

CONCLUSION

GPR37 had diagnostic and prognostic value in glioma. The possible biological mechanisms of GPR37 provide novel insights into the clinical diagnosis and treatment of glioma.

Unveiling Novel Avenues in mTOR-Targeted Therapeutics: Advancements in Glioblastoma Treatment

The mTOR signaling pathway plays a pivotal and intricate role in the pathogenesis of glioblastoma, driving tumorigenesis and proliferation. Mutations or deletions in the PTEN gene constitutively activate the mTOR pathway by expressing growth factors EGF and PDGF, which activate their respective receptor pathways (e.g., EGFR and PDGFR). The convergence of signaling pathways, such as the PI3K-AKT pathway, intensifies the effect of mTOR activity. The inhibition of mTOR has the potential to disrupt diverse oncogenic processes and improve patient outcomes. However, the complexity of the mTOR signaling, off-target effects, cytotoxicity, suboptimal pharmacokinetics, and drug resistance of the mTOR inhibitors pose ongoing challenges in effectively targeting glioblastoma. Identifying innovative treatment strategies to address these challenges is vital for advancing the field of glioblastoma therapeutics. This review discusses the potential targets of mTOR signaling and the strategies of target-specific mTOR inhibitor development, optimized drug delivery system, and the implementation of personalized treatment approaches to mitigate the complications of mTOR inhibitors. The exploration of precise mTOR-targeted therapies ultimately offers elevated therapeutic outcomes and the development of more effective strategies to combat the deadliest form of adult brain cancer and transform the landscape of glioblastoma therapy.

PLEKHA4 is a novel prognostic biomarker that reshapes the tumor microenvironment in lower-grade glioma

Background

Lower-grade glioma (LGG) is a primary intracranial tumor that carry a high risk of malignant transformation and limited therapeutic options. Emerging evidence indicates that the tumor microenvironment (TME) is a superior predictor for tumor progression and therapy response. PLEKHA4 has been demonstrated to be a biomarker for LGG that correlate with immune infiltration. However, the fundamental mechanism by which PLEKHA4 contributes to LGG is still poorly understood.

Methods

Multiple bioinformatic tools, including Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA2), Shiny Methylation Analysis Resource Tool (SMART), etc., were incorporated to analyze the PLEKHA4. ESTIMATE, ssGSEA, CIBERSORT, TIDE and CellMiner algorithms were employed to determine the association of PLEKHA4 with TME, immunotherapy response and drug sensitivities. Immunohistochemistry (IHC)-based tissue microarrays and M2 macrophage infiltration assay were conducted to verify their associations.

Results

PLEKHA4 expression was found to be dramatically upregulated and strongly associated with unfavorable overall survival (OS) and disease-specific survival (DSS) in LGG patients, as well as their poor clinicopathological characteristics. Cox regression analysis identified that PLEKHA4 was an independent prognostic factor. Methylation analysis revealed that DNA methylation correlates with PLEKHA4 expression and indicates a better outcome in LGG. Moreover, PLEKHA4 was remarkably correlated with immune responses and TME remodeling, as evidenced by its positive correlation with particular immune marker subsets and the putative infiltration of immune cells. Surprisingly, the proportion of M2 macrophages in TME was strikingly higher than others, inferring that PLEKHA4 may regulate the infiltration and polarization of M2 macrophages. Evidence provided by IHC-based tissue microarrays and M2 macrophage infiltration assay further validated our findings. Moreover, PLEKHA4 expression was found to be significantly correlated with chemokines, interleukins, and their receptors, further supporting the critical role of PLEKHA4 in reshaping the TME. Additionally, we found that PLEKHA4 expression was closely associated with drug sensitivities and immunotherapy responses, indicating that PLEKHA4 expression also had potential clinical significance in guiding immunotherapy and chemotherapy in LGG.

Conclusion

PLEKHA4 plays a pivotal role in reshaping the TME of LGG patients, and may serve as a potential predictor for LGG prognosis and therapy.

Combining single-cell sequencing and spatial transcriptome sequencing to identify exosome-related features of glioblastoma and constructing a prognostic model to identify BARD1 as a potential therapeutic target for GBM patients

Background

Glioblastoma (GBM) is a malignant primary brain tumor. This study focused on exploring the exosome-related features of glioblastoma to better understand its cellular composition and molecular characteristics.

Methods

Single-cell RNA sequencing (scRNA-seq) and spatial transcriptome RNA sequencing (stRNA-seq) were used to analyze the heterogeneity of glioblastomas. After data integration, cell clustering, and annotation, five algorithms were used to calculate scores for exosome-related genes(ERGs). Cell trajectory analysis and intercellular communication analysis were performed to explore exosome-related communication patterns. Spatial transcriptome sequencing data were analyzed to validate the findings. To further utilize exosome-related features to aid in clinical decision-making, a prognostic model was constructed using GBM's bulk RNA-seq.

Results

Different cell subpopulations were observed in GBM, with Monocytes/macrophages and malignant cells in tumor samples showing higher exosome-related scores. After identifying differentially expressed ERGs in malignant cells, pseudotime analysis revealed the cellular status of malignant cells during development. Intercellular communication analysis highlighted signaling pathways and ligand-receptor interactions. Spatial transcriptome sequencing confirmed the high expression of exosome-related gene features in the tumor core region. A prognostic model based on six ERGs was shown to be predictive of overall survival and immunotherapy outcome in GBM patients. Finally, based on the results of scRNA-seq and prognostic modeling as well as a series of cell function experiments, BARD1 was identified as a novel target for the treatment of GBM.

Conclusion

This study provides a comprehensive understanding of the exosome-related features of GBM in both scRNA-seq and stRNA-seq, with malignant cells with higher exosome-related scores exhibiting stronger communication with Monocytes/macrophages. In terms of spatial data, highly scored malignant cells were also concentrated in the tumor core region. In bulk RNA-seq, patients with a high exosome-related index exhibited an immunosuppressive microenvironment, which was accompanied by a worse prognosis as well as immunotherapy outcomes. Prognostic models constructed using ERGs are expected to be independent prognostic indicators for GBM patients, with potential implications for personalized treatment strategies for GBM. Knockdown of BARD1 in GBM cell lines reduces the invasive and value-added capacity of tumor cells, and thus BARD1-positively expressing malignant cells are a risk factor for GBM patients.

A Four-Gene Panel for the Prediction of Prognosis and Immune Cell Enrichment in Gliomas

BACKGROUNDS

Gliomas is a deadly disease without effective therapy. Although immunotherapy has provided novel choices for glioma treatment, the curative efficacy is unsatisfactory due to the complex immune micro-environment and the heterogeneity of the disease. Therefore, it is urgent to identify effective biomarkers and therapeutic targets.

METHODS

Overall survival, gene ontology (GO), Kyoto Encyclopedia of Genes, and Genomes (KEGG) enrichment analysis, Gene Set Enrichment Analysis (GSEA) and immune infiltration were analyzed by bioinformatics software with The Cancer Genome Atlas (TCGA) database.

RESULTS

Based on the TCGA database and protein-protein interaction (PPI) analysis revealed a four-gene panels [DNA topoisomerase II alpha (TOP2A); ribonucleotide reductase regulatory subunit M2 (RRM2); kinesin family member 20 A (KIF20A) and DLG associated protein 5 (DLGAP5)], which correlated with poor prognosis, including overall survival (OS), disease specific survival (DSS) and progress free interval (PFI), mitosis, cell cycle, Th2 cells and macrophages enrichment. The four-gene panels correlates with the biomarkers of Th2 cells, macrophages tumor-associated macrophages (TAMs) and the immune checkpoint molecules in gliomas.

CONCLUSION

The four-gene panels represented a novel prognostic indicator and potential therapeutic target for the treatment of glioma. In addition, the four-gene panels might contribute to enhance the efficacy of immunotherapy in glioma.

Construction and validation of an immune infiltration-related risk model for predicting prognosis and immunotherapy response in low grade glioma

BACKGROUND

Low grade glioma (LGG) is considered a heterogeneous tumor with highly variable survival and limited efficacy of immunotherapy. To identify high-risk subsets and apply immunotherapy effectively in LGG, the status and function of immune infiltration in the glioma microenvironment must be explored.

METHODS

Four independent glioma cohorts comprising 1,853 patients were enrolled for bioinformatics analysis. We used ConsensusClusterPlus to cluster patients into four different immune subtypes based on immune infiltration. The immune-infiltration signature (IIS) was constructed by LASSO regression analysis. Somatic mutation and copy number variation (CNV) analyses were performed to explore genomic and transcriptomic traits in the high- and low- risk groups. The correlation between response to programmed cell death 1 (PD-1) blockade and the IIS risk score was confirmed in an in vivo glioma model.

RESULTS

Patients were clustered into four different immune subtypes based on immune infiltration, and the high immune infiltration subtype was associated with worse survival in LGG. The high immune infiltration subtype had stronger inflammatory response, immune response and immune cell chemotaxis. The IIS, consisting of EMP3, IQGAP2, METTL7B, SLC1A6 and TNFRSF11B, could predict LGG malignant progression, which was validated with internal clinical samples. M2 macrophage infiltration positively correlated with the IIS risk score. The high-risk group had significantly more somatic mutations and CNVs. The IIS risk score was related to immunomodulatory molecules and could predict immunotherapy clinical benefit. In vivo, immunotherapy-sensitive glioma model exhibited higher IIS risk score and more infiltration of immune cells, especially M2 macrophages. The IIS risk score was decreased in an immunotherapy-sensitive glioma model after anti-PD1 immunotherapy.

CONCLUSION

Different immune subtypes of LGG had unique immune cell infiltration characteristics, and the high immune infiltration subtype was associated with immunosuppressive signaling pathways. A novel IIS prognostic model based on immune infiltration status was constructed for immunophenotypic classification, risk stratification, prognostication and immunotherapy response prediction in LGG.

Allomelanin-based biomimetic nanotherapeutics for orthotopic glioblastoma targeted photothermal immunotherapy

Immune checkpoint blockade (ICB) therapy has shown great potential in the treatment of malignant tumors, but its therapeutic effect on glioblastoma (GBM) is unsatisfactory because of the low immunogenicity and T cell infiltration, as well as the presence of blood-brain barrier (BBB) that blocks most of ICB agents to the GBM tissues. Herein, we developed a biomimetic nanoplatform of AMNP@CLP@CCM for GBM-targeted photothermal therapy (PTT) and ICB synergistic therapy by loading immune checkpoint inhibitor CLP002 into the allomelanin nanoparticles (AMNPs) and followed by coating cancer cell membranes (CCM). The resulting AMNP@CLP@CCM can successfully cross the BBB and deliver CLP002 to GBM tissues due to the homing effect of CCM. As a natural photothermal conversion agent, AMNPs are used for tumor PTT. The increased local temperature by PTT not only enhances BBB penetration but also upregulates the PD-L1 level on GBM cells. Importantly, PTT can effectively stimulate immunogenic cell death to induce tumor-associated antigen exposure and promote T lymphocyte infiltration, which can further amplify the antitumor immune responses of GBM cells to CLP002-mediated ICB therapy, resulting in significant growth inhibition of the orthotopic GBM. Therefore, AMNP@CLP@CCM has great potential for the treatment of orthotopic GBM by PTT and ICB synergistic therapy. STATEMENT OF SIGNIFICANCE: The effect of ICB therapy on GBM is limited by the low immunogenicity and insufficient T-cell infiltration. Here we developed a biomimetic nanoplatform of AMNP@CLP@CCM for GBM-targeted PTT and ICB synergistic therapy. In this nanoplatform, AMNPs are used as both photothermal conversion agents for PTT and nanocarriers for CLP002 delivery. PTT not only enhances BBB penetration but also upregulates the PD-L1 level on GBM cells by increasing local temperature. Additionally, PTT also induces tumor-associated antigen exposure and promotes T lymphocyte infiltration to amplify the antitumor immune responses of GBM cells to CLP002-mediated ICB therapy, resulting in significant growth inhibition of the orthotopic GBM. Thus, this nanoplatform holds great potential for orthotopic GBM treatment.

Natural Products for the Immunotherapy of Glioma

Glioma immunotherapy has attracted increasing attention since the immune system plays a vital role in suppressing tumor growth. Immunotherapy strategies are already being tested in clinical trials, such as immune checkpoint inhibitors (ICIs), vaccines, chimeric antigen receptor T-cell (CAR-T cell) therapy, and virus therapy. However, the clinical application of these immunotherapies is limited due to their tremendous side effects and slight efficacy caused by glioma heterogeneity, antigen escape, and the presence of glioma immunosuppressive microenvironment (GIME). Natural products have emerged as a promising and safe strategy for glioma therapy since most of them possess excellent antitumor effects and immunoregulatory properties by reversing GIME. This review summarizes the status of current immunotherapy strategies for glioma, including their obstacles. Then we discuss the recent advancement of natural products for glioma immunotherapy. Additionally, perspectives on the challenges and opportunities of natural compounds for modulating the glioma microenvironment are also illustrated.

CDYL knockdown reduces glioma development through an antitumor immune response in the tumor microenvironment

Gliomas are highly prevalent and aggressive brain tumors. Growing evidence shows that epigenetic changes are closely related to cancer development. Here we report the roles of Chromodomain Y-like (CDYL), an important epigenetic transcriptional corepressor in the central nervous system in glioma progression. We found that CDYL was highly expressed in glioma tissues and cell lines. CDYL knockdown decreased cell mobility in vitro and significantly reduced tumor burden in the xenograft mouse in vivo. RNA sequencing analysis revealed the upregulation of immune pathways after CDYL knockdown, as well as chemokine (C-C motif) ligand 2 (CCL2) and chemokine (C-X-C motif) ligand 12. The immunohistochemistry staining and macrophage polarization assays showed increased infiltration of M1-like tumor-associated macrophages/microglia (TAMs) while decreased infiltration of M2-like TAMs after CDYL knockdown in vivo and in vitro. Following the in situ TAMs depletion or CCL2 antibody neutralization, the tumor-suppressive role of CDYL knockdown was abolished. Collectively, our results show that CDYL knockdown suppresses glioma progression, which is associated with CCL2-recruited monocytes/macrophages and the polarization of M1-like TAMs in the tumor microenvironment, indicating CDYL as a promising target for glioma treatment.

Pan-cancer analysis of TASL: a novel immune infiltration-related biomarker for tumor prognosis and immunotherapy response prediction

BACKGROUND

New immunotherapeutic strategies based on predictors are urgently needed. Toll-like receptor adaptor interacting with SLC15A4 on the lysosome (TASL) was recently confirmed to fulfill an important role in the innate immune response. However, whether TASL is involved in tumor development and immunotherapy response prediction has not been reported.

METHODS

TCGA and GTEx were used to yield transcriptional, genetic, and epigenetic levels of TASL in 33 cancer types. CIBERSORT was used to explore the correlation between TASL expression and multiple immune-related signatures and tumor-infiltrating immune cell content in different cancer types. The ability of TASL to predict tumor immunotherapy response was analyzed in seven datasets. Finally, we tested TASL expression in human glioma cell lines and tissue samples and analyzed its correlation with clinicopathological parameters.

RESULTS

TASL is widely heterogeneous at the transcriptional, genetic, and epigenetic levels. High TASL expression is an independent poor prognostic factor for immune "cold" tumor Low-Grade Glioma (LGG) but an opposite factor for "hot" tumors Lung Adenocarcinoma (LUAD) and Skin Cutaneous Melanoma (SKCM). TASL may affect tumor immune infiltration by mediating tumor-infiltrating lymphocytes and tumor-associated macrophages. It may differentially affect the prognosis of the three cancers by regulating the immunosuppressive microenvironment in LGG and the immunostimulatory microenvironment in LUAD and SKCM. High TASL expression is a potential biomarker for the positive response to immunotherapy in cancers such as SKCM and was also experimentally confirmed to be positively associated with adverse clinicopathological features of gliomas.

CONCLUSION

TASL expression is an independent prognostic factor for LGG, LUAD, and SKCM. High TASL expression is a potential biomarker for the positive response to immunotherapy in certain cancer types such as SKCM. Further basic studies focusing on TASL expression and tumor immunotherapy are urgently needed.

Immunostimulant In Situ Fibrin Gel for Post-operative Glioblastoma Treatment by Macrophage Reprogramming and Photo-Chemo-Immunotherapy

Tumor recurrence remains the leading cause of treatment failure following surgical resection of glioblastoma (GBM). M2-like tumor-associated macrophages (TAMs) infiltrating the tumor tissue promote tumor progression and seriously impair the efficacy of chemotherapy and immunotherapy. In addition, designing drugs capable of crossing the blood-brain barrier and eliciting the applicable organic response is an ambitious challenge. Here, we propose an injectable nanoparticle-hydrogel system that uses doxorubicin (DOX)-loaded mesoporous polydopamine (MPDA) nanoparticles encapsulated in M1 macrophage-derived nanovesicles (M1NVs) as effectors and fibrin hydrogels as in situ delivery vehicles. In vivo fluorescence imaging shows that the hydrogel system triggers photo-chemo-immunotherapy to destroy remaining tumor cells when delivered to the tumor cavity of a model of subtotal GBM resection. Concomitantly, the result of flow cytometry indicated that M1NVs comprehensively improved the immune microenvironment by reprogramming M2-like TAMs to M1-like TAMs. This hydrogel system combined with a near-infrared laser effectively promoted the continuous infiltration of T cells, restored T cell effector function, inhibited the infiltration of myeloid-derived suppressor cells and regulatory T cells, and thereby exhibited a strong antitumor immune response and significantly inhibited tumor growth. Hence, MPDA-DOX-NVs@Gel (MD-NVs@Gel) presents a unique clinical strategy for the treatment of GBM recurrence.

The cell senescence regulator p16 is a promising cancer prognostic and immune check-point inhibitor (ICI) therapy biomarker

Cyclin-dependent kinase inhibitor 2A (CDKN2A) encodes the cell senescence regulator protein p16. The expression of p16 raises in cell senescence and has a nuclear regulation in cell aging. Meanwhile, it's also reported to inhibit the aggression of several cancers. But its clinical application and role in cancer immunotherapy needs further investigation. We collected the transcriptional data of pan-cancer and normal human tissues from The Cancer Genome Atlas and the Genotype-Tissue Expression databases. CBioPortal webtool was employed to mine the genomic alteration status of CDKN2A across cancers. Kaplan-Meier method and univariate Cox regression were performed for prognostic assessments across cancers, respectively. Gene Set Enrichment Analysis is the main method used to search the associated cancer hallmarks associated with CDKN2A. TIMER2.0 was used to analyze the immune cell infiltration relevance with CDKN2A in pan-cancer. The associations between CDKN2A and immunotherapy biomarkers or regulators were performed by spearman correlation analysis. We found CDKN2A is overexpressed in most cancers and exhibits prognosis predictive ability in various cancers. In addition, it is significantly correlated with immune-activated hallmarks, cancer immune cell infiltrations and immunoregulators. The most interesting finding is that CDKN2A can significantly predict anti-PDL1 therapy response. Finally, specific inhibitors which correlated with CDKN2A expression in different cancer types were also screened by using Connectivity Map (CMap) tool. The results revealed that CDKN2A acts as a robust cancer prognostic and immunotherapy biomarker. Its function in the regulation of cancer cell senescence might shape the tumor microenvironment and contribute to its predictive ability of immunotherapy.

Prognostic role of the pretreatment systemic immune-inflammation index in patients with glioma: A meta-analysis

Background

The systemic immune-inflammation index (SII) has been recognized as the indicator that reflects the status of immune responses. The SII is related to the prognostic outcome of many malignancies, whereas its role in gliomas is controversial. For patients with glioma, we, therefore, conducted a meta-analysis to determine if the SII has a prognostic value.

Methods

Studies relevant to this topic were searched from 16 October 2022 in several databases. In patients with glioma, the relation of the SII level with the patient prognosis was analyzed based on hazard ratios (HRs) as well as corresponding 95% confidence intervals (CIs). Moreover, subgroup analysis was conducted to examine a possible heterogeneity source.

Results

There were eight articles involving 1,426 cases enrolled in the present meta-analysis. The increased SII level predicted the dismal overall survival (OS) (HR = 1.81, 95% CI = 1.55–2.12, p &lt; 0.001) of glioma cases. Furthermore, an increased SII level also predicted the prognosis of progression-free survival (PFS) (HR = 1.87, 95% CI = 1.44–2.43, p &lt; 0.001) in gliomas. An increased SII was significantly associated with a Ki-67 index of ≥30% (OR = 1.72, 95% CI = 1.10–2.69, p = 0.017). However, a high SII was not correlated with gender (OR = 1.05, 95% CI = 0.78–1.41, p = 0.734), KPS score (OR = 0.64, 95% CI = 0.17–2.37, p = 0.505), or symptom duration (OR 1.22, 95% CI 0.37–4.06, p = 0.745).

Conclusion

There was a significant relation between an increased SII level with poor OS and the PFS of glioma cases. Moreover, patients with glioma with a high SII value have a positive relationship with a Ki-67 of ≥30%.

Prognostic RNA-editing signature predicts immune functions and therapy responses in gliomas

Background: RNA-editing refers to post-transcriptional transcript alterations that lead to the formation of protein isoforms and the progression of various tumors. However, little is known about its roles in gliomas. Aim: The aim of this study is to identify prognosis-related RNA-editing sites (PREs) in glioma, and to explore their specific effects on glioma and potential mechanisms of action. Methods: Glioma genomic and clinical data were obtained from TCGA database and SYNAPSE platform. The PREs was identified with regression analyses and the corresponding prognostic model was evaluated with survival analysis and receiver operating characteristic curve. Functional enrichment of differentially expressed genes between risk groups was performed to explore action mechanisms. The CIBERSORT, ssGSEA, gene set variation analysis, and ESTIMATE algorithms were employed to assess the association between PREs risk score and variations of tumor microenvironment, immune cell infiltration, immune checkpoints, and immune responses. The maftools and pRRophetic packages were used to evaluate tumor mutation burden and predict drug sensitivity. Results: A total of thirty-five RNA-editing sites were identified as prognosis-related in glioma. Functional enrichment implied variation of immune-related pathways between groups. Notably, glioma samples with higher PREs risk score exhibited higher immune score, lower tumor purity, increased infiltration of macrophage and regulatory T cells, suppressed NK cell activation, elevated immune function score, upregulated immune checkpoint gene expression, and higher tumor mutation burden, all of which implied worse response to immune therapy. Finally, high-risk glioma samples are more sensitive to Z-LLNle-CHO and temozolomide, while the low-risk ones respond better to Lisitinib. Conclusion: We identified a PREs signature of thirty-five RNA editing sites and calculated their corresponding risk coefficients. Higher total signature risk score indicates worse prognosis and worse immune response and lower sensitivity to immune therapy. The novel PREs signature could help risk stratification, immunotherapy response prediction, individualized treatment strategy-making for glioma patients, and development of novel therapeutic approaches.

Development of prognostic indicator based on NAD+ metabolism related genes in glioma

Background

Studies have shown that Nicotinamide adenine dinucleotide (NAD+) metabolism can promote the occurrence and development of glioma. However, the specific effects and mechanisms of NAD+ metabolism in glioma are unclear and there were no systematic researches about NAD+ metabolism related genes to predict the survival of patients with glioma.

Methods

The research was performed based on expression data of glioma cases in the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Firstly, TCGA-glioma cases were classified into different subtypes based on 49 NAD+ metabolism-related genes (NMRGs) by consensus clustering. NAD+ metabolism-related differentially expressed genes (NMR-DEGs) were gotten by intersecting the 49 NMRGs and differentially expressed genes (DEGs) between normal and glioma samples. Then a risk model was built by Cox analysis and the least shrinkage and selection operator (LASSO) regression analysis. The validity of the model was verified by survival curves and receiver operating characteristic (ROC) curves. In addition, independent prognostic analysis of the risk model was performed by Cox analysis. Then, we also identified different immune cells, HLA family genes and immune checkpoints between high and low risk groups. Finally, the functions of model genes at single-cell level were also explored.

Results

Consensus clustering classified glioma patients into two subtypes, and the overall survival (OS) of the two subtypes differed. A total of 11 NAD+ metabolism-related differentially expressed genes (NMR-DEGs) were screened by overlapping 5,995 differentially expressed genes (DEGs) and 49 NAD+ metabolism-related genes (NMRGs). Next, four model genes, PARP9, BST1, NMNAT2, and CD38, were obtained by Cox regression and least absolute shrinkage and selection operator (Lasso) regression analyses and to construct a risk model. The OS of high-risk group was lower. And the area under curves (AUCs) of Receiver operating characteristic (ROC) curves were >0.7 at 1, 3, and 5 years. Cox analysis showed that age, grade G3, grade G4, IDH status, ATRX status, BCR status, and risk Scores were reliable independent prognostic factors. In addition, three different immune cells, Mast cells activated, NK cells activated and B cells naive, 24 different HLA family genes, such as HLA-DPA1 and HLA-H, and 8 different immune checkpoints, such as ICOS, LAG3, and CD274, were found between the high and low risk groups. The model genes were significantly relevant with proliferation, cell differentiation, and apoptosis.

Conclusion

The four genes, PARP9, BST1, NMNAT2, and CD38, might be important molecular biomarkers and therapeutic targets for glioma patients.

Transcription factor ZBTB42 is a novel prognostic factor associated with immune cell infiltration in glioma

Background: ZBTB42 is a transcription factor that belongs to the ZBTB transcript factor family and plays an important role in skeletal muscle development. Dysregulation of ZBTB42 expression can lead to a variety of diseases. However, the function of ZBTB42 in glioma development has not been studied by now. Methods: We analyzed the expression of ZBTB42 in LGG and GBM via the The Cancer Genome Atlas CGA and Chinese Glioma Genome Atlas database. Gene Ontology, KEGG, and GSVA analyses were performed to illustrate ZBTB42-related pathways. ESTIMATE and CIBERSORT were applied to calculate the immune score and immune cell proportion in glioma. One-class logistic regression OCLR algorithm was used to study the stemness of glioma. Multivariate Cox analysis was employed to detect the prognostic value of five ZBTB42-related genes. Results: Our results show that ZBTB42 is highly expressed in glioma and may be a promising prognostic factor for Low Grade Glioma and GBM. In addition, ZBTB42 is related to immune cell infiltration and may play a role in the immune suppression microenvironment. What's more, ZBTB42 is correlated with stem cell markers and positively associated with glioma stemness. Finally, a five genes nomogram based on ZBTB42 was constructed and has an effective prognosis prediction ability. Conclusion: We identify that ZBTB42 is a prognostic biomarker for Low Grade Glioma and GBM and its function is related to the suppressive tumor microenvironment and stemness of glioma.

Role of B7 family members in glioma: Promising new targets for tumor immunotherapy

Glioma, is a representative type of intracranial tumor among adults, usually has a weak prognosis and limited treatment options. Traditional therapies, including surgery, chemotherapy, and radiotherapy, have had little impact on patient survival time. Immunotherapies designed to target the programmed cell death protein 1 (PD-1)/programmed death ligand 1 (PD-L1) signaling pathway have successfully treated various human cancers, informing the development of similar therapies for glioma. However, anti-PD-L1 response rates remain limited in glioma patients. Thus, exploring novel checkpoints targeting additional immunomodulatory pathways for activating durable antitumor immune responses and improving glioma outcomes is needed. Researchers have identified other B7 family checkpoint molecules, including PD-L2, B7-H2, B7-H3, B7-H4, and B7-H6. The current review article evaluates the expression of all 10 reported members of the B7 family in human glioma using The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) data, as well as summarizes studies evaluating the clinical meanings and functions of B7 family molecules in gliomas. B7 family checkpoints may contribute to different immunotherapeutic management options for glioma patients.

Necroptosis-related lncRNAs: establishment of a gene module and distinction between the cold and hot tumors in glioma

Background

Gliomas are the most common primary tumors of the central nervous system and portend a poor prognosis. The efficacy of emerging and promising immunotherapies varies significantly among individuals. Distinction and transformation of cold and hot tumors may improve the antitumor efficacy of immunotherapy.

Methods and Results

In this study, we constructed a necroptosis-related lncRNA module based on public databases. The association of this module with survival was assessed using the Cox regression, Kaplan-Meier survival analysis, and nomogram, external validation was also conducted in another public database. Furthermore, we performed gene set enrichment analysis (GSEA), immune checkpoint and tumor microenvironment analysis, and in vitro qRT-PCR validation. Finally, we clustered all samples into 2 clusters based on the expression of model lncRNAs and identified cluster 1 as cold tumors with fewer infiltrating T cells.

Conclusions

Identifying cold and hot tumors by necroptosis-related lncRNAs can help available immunotherapeutic strategies to achieve efficacy in the precise treatment of individuals. Prior treatment failure can be overcome by targeting necroptosis-related lncRNAs.

Clinicopathological and prognostic significance of COX-2 in glioma patients: a meta-analysis

BACKGROUND

In recent years, cyclooxygenase-2 (COX-2) has been identified as a cancer stem cell (CSC) marker in gliomas. Nevertheless, the clinical and prognostic significance of COX-2 in glioma patients remains controversial.

OBJECTIVE

To evaluate the correlation of COX-2 with the prognosis in glioma patients.

METHODS

Eligible studies on this subject were included, and pooled odd ratios (ORs) and hazard ratios (HRs) with 95% confidence intervals (95%CIs) were estimated. Publication bias was assessed through funnel plots, and heterogeneity and sensitivity were analyzed as well.

RESULTS

In the present study, 11 articles with a total of 641 patients were included. The high expression of COX-2 in glioma patients was negatively associated with overall survival (OS) (n = 11; HR = 2.26; 95%CI = 1.79-2.86), and the subgroup analysis showed no differences in OS between Asian (n = 5; HR = 2.16; 95%CI = 1.57-2.97) and non-Asian (n = 6; HR = 2.39; 95%CI = 1.69-3.38) glioma patients. The Begg funnel plots test indicated that there was no evident risk of publication bias in the meta-analysis.

CONCLUSION

The present study suggests that COX-2 could be recommended as a useful pathological and prognostic biomarker in the clinical practice.

Dendritic cell vaccines improve the glioma microenvironment: Influence, challenges, and future directions

INTRODUCTION

Gliomas, especially the glioblastomas, are one of the most aggressive intracranial tumors with poor prognosis. This might be explained by the heterogeneity of tumor cells and the inhibitory immunological microenvironment. Dendritic cells (DCs), as the most potent in vivo functional antigen-presenting cells, link innate immunity with adaptive immunity. However, their function is suppressed in gliomas. Therefore, overcoming the dysfunction of DCs in the TME might be critical to treat gliomas.

METHOD

In this paper we proposed the specificity of the glioma microenvironment, analyzed the pathways leading to the dysfunction of DCs in tumor microenvironment of patients with glioma, summarized influence of DC-based immunotherapy on the tumor microenvironment and proposed new development directions and possible challenges of DC vaccines.

RESULT

DC vaccines can improve the immunosuppressive microenvironment of glioma patients. It will bring good treatment prospects to patients. We also proposed new development directions and possible challenges of DC vaccines, thus providing an integrated understanding of efficacy on DC vaccines for glioma treatment.

The role of a cuproptosis-related prognostic signature in colon cancer tumor microenvironment and immune responses

Background: Colon adenocarcinoma (COAD) is a common malignant tumor of the digestive tract with poor clinical outcomes. Cuproptosis is a novel cell death mechanism and linked to mitochondrial respiration. However, the role of cuproptosis in colon cancer tumor microenvironment (TME) and immune responses remains unknown.

Methods: We conducted difference analysis to identify the differential expressed cuproptosis-related genes (CRGs). According to the CRGs, the TCGA-COAD samples were categorized using consensus clustering. The LASSO regression analysis was utilized to develop the cuproptosis-related signature. We then verified the model reliability by Kaplan–Meier, PCA, and ROC analysis. The GES39582 cohort served as the validation set. GO and KEGG functional analyses were conducted to investigate the underlying mechanism. We compared the infiltration levels of immune cells, the expression levels of immune checkpoints, and microsatellite instability (MSI) status between the high- and low-risk groups. Additionally, the relationships between the risk signature and immune cells and cancer stem cell (CSC) were analyzed.

Results: Finally, we identified 9 differentially expressed CRGs in COAD. According to the expression of CRGs, the TCGA-COAD samples were separated into two clusters. The 11-gene signature was established by LASSO, and it had excellent predictive power for COAD prognosis. Besides, we used the GSE39582 cohort to validate the prognostic value of the model. GO and KEGG results demonstrated that the survival differences between two risk groups was mainly linked to the extracellular matrix (ECM). Further immune characterization analysis showed the significant differences in the immune cell infiltration and immune responses between two risk groups.

Conclusion: Overall, the novel cuproptosis-related signature was able to accurately predict COAD prognosis and played important roles in COAD tumor microenvironment and immune responses.

A Composite Bioinformatic Analysis to Explore Endoplasmic Reticulum Stress-Related Prognostic Marker and Potential Pathogenic Mechanisms in Glioma by Integrating Multiomics Data

In recent years, abnormal endoplasmic reticulum stress (ERS) response, as an important regulator of immunity, may play a vital role in the occurrence, development, and treatment of glioma. Weighted correlation network analysis (WGCNA) based on six glioma datasets was used to screen eight prognostic-related differentially expressed ERS-related genes (PR-DE-ERSGs) and to construct a prognostic model. BMP2 and HEY2 were identified as protective factors (HR < 1), and NUP107, DRAM1, F2R, PXDN, RNF19A, and SCG5 were identified as risk factors for glioma (HR > 1). QRT-PCR further supported significantly higher DRAM1 and lower SCG5 relative mRNA expression in gliomas. Our model has demonstrated excellent performance in predicting the prognosis of glioma patients from numerous datasets. In addition, the model shows good stability in multiple tests. Our model also shows broad clinical promise in predicting drug treatment effects. More immune cells/processes in the high-risk population with poor prognosis illustrate the importance of the tumor immunosuppressive environment in glioma. The potential role of the HEY2-based competitive endogenous RNA (ceRNA) regulatory network in glioma was validated and revealed the possible important role of glycolysis in glioma ERS. IDH1 and TP53 mutations with better prognosis were strongly associated with the risk score and PR-DE-ERSGs expression in the model. mDNAsi was also closely related to the risk score and clinical characteristics.

A Composite Bioinformatic Analysis to Explore Endoplasmic Reticulum Stress-Related Prognostic Marker and Potential Pathogenic Mechanisms in Glioma by Integrating Multiomics Data

In recent years, abnormal endoplasmic reticulum stress (ERS) response, as an important regulator of immunity, may play a vital role in the occurrence, development, and treatment of glioma. Weighted correlation network analysis (WGCNA) based on six glioma datasets was used to screen eight prognostic-related differentially expressed ERS-related genes (PR-DE-ERSGs) and to construct a prognostic model. BMP2 and HEY2 were identified as protective factors (HR < 1), and NUP107, DRAM1, F2R, PXDN, RNF19A, and SCG5 were identified as risk factors for glioma (HR > 1). QRT-PCR further supported significantly higher DRAM1 and lower SCG5 relative mRNA expression in gliomas. Our model has demonstrated excellent performance in predicting the prognosis of glioma patients from numerous datasets. In addition, the model shows good stability in multiple tests. Our model also shows broad clinical promise in predicting drug treatment effects. More immune cells/processes in the high-risk population with poor prognosis illustrate the importance of the tumor immunosuppressive environment in glioma. The potential role of the HEY2-based competitive endogenous RNA (ceRNA) regulatory network in glioma was validated and revealed the possible important role of glycolysis in glioma ERS. IDH1 and TP53 mutations with better prognosis were strongly associated with the risk score and PR-DE-ERSGs expression in the model. mDNAsi was also closely related to the risk score and clinical characteristics.

A Composite Bioinformatic Analysis to Explore Endoplasmic Reticulum Stress-Related Prognostic Marker and Potential Pathogenic Mechanisms in Glioma by Integrating Multiomics Data

In recent years, abnormal endoplasmic reticulum stress (ERS) response, as an important regulator of immunity, may play a vital role in the occurrence, development, and treatment of glioma. Weighted correlation network analysis (WGCNA) based on six glioma datasets was used to screen eight prognostic-related differentially expressed ERS-related genes (PR-DE-ERSGs) and to construct a prognostic model. BMP2 and HEY2 were identified as protective factors (HR < 1), and NUP107, DRAM1, F2R, PXDN, RNF19A, and SCG5 were identified as risk factors for glioma (HR > 1). QRT-PCR further supported significantly higher DRAM1 and lower SCG5 relative mRNA expression in gliomas. Our model has demonstrated excellent performance in predicting the prognosis of glioma patients from numerous datasets. In addition, the model shows good stability in multiple tests. Our model also shows broad clinical promise in predicting drug treatment effects. More immune cells/processes in the high-risk population with poor prognosis illustrate the importance of the tumor immunosuppressive environment in glioma. The potential role of the HEY2-based competitive endogenous RNA (ceRNA) regulatory network in glioma was validated and revealed the possible important role of glycolysis in glioma ERS. IDH1 and TP53 mutations with better prognosis were strongly associated with the risk score and PR-DE-ERSGs expression in the model. mDNAsi was also closely related to the risk score and clinical characteristics.

Identification of a 6-RBP gene signature for a comprehensive analysis of glioma and ischemic stroke: Cognitive impairment and aging-related hypoxic stress

There is mounting evidence that ischemic cerebral infarction contributes to vascular cognitive impairment and dementia in elderly. Ischemic stroke and glioma are two majorly fatal diseases worldwide, which promote each other's development based on some common underlying mechanisms. As a post-transcriptional regulatory protein, RNA-binding protein is important in the development of a tumor and ischemic stroke (IS). The purpose of this study was to search for a group of RNA-binding protein (RBP) gene markers related to the prognosis of glioma and the occurrence of IS, and elucidate their underlying mechanisms in glioma and IS. First, a 6-RBP (POLR2F, DYNC1H1, SMAD9, TRIM21, BRCA1, and ERI1) gene signature (RBPS) showing an independent overall survival prognostic prediction was identified using the transcriptome data from TCGA-glioma cohort (n = 677); following which, it was independently verified in the CGGA-glioma cohort (n = 970). A nomogram, including RBPS, 1p19q codeletion, radiotherapy, chemotherapy, grade, and age, was established to predict the overall survival of patients with glioma, convenient for further clinical transformation. In addition, an automatic machine learning classification model based on radiomics features from MRI was developed to stratify according to the RBPS risk. The RBPS was associated with immunosuppression, energy metabolism, and tumor growth of gliomas. Subsequently, the six RBP genes from blood samples showed good classification performance for IS diagnosis (AUC = 0.95, 95% CI: 0.902–0.997). The RBPS was associated with hypoxic responses, angiogenesis, and increased coagulation in IS. Upregulation of SMAD9 was associated with dementia, while downregulation of POLR2F was associated with aging-related hypoxic stress. Irf5/Trim21 in microglia and Taf7/Trim21 in pericytes from the mouse cerebral cortex were identified as RBPS-related molecules in each cell type under hypoxic conditions. The RBPS is expected to serve as a novel biomarker for studying the common mechanisms underlying glioma and IS.

The mechanism of formononetin/calycosin compound optimizing the effects of temozolomide on C6 malignant glioma based on metabolomics and network pharmacology

The complex of formononetin and calycosin (FMN/CAL) shows a synergistic effect on temozolomide in the treatment of malignant glioma, however the mechanism is unclear. We investigated the mechanism through means of metabolomics, network pharmacology and molecular biology. FMN/CAL enhanced the inhibition of TMZ on the growth and infiltration of C6 glioma. The metabolomic results showed that the TMZ sensitization of FMN/CAL mainly involved 5 metabolic pathways and 4 metabolites in cells, 1 metabolic pathway and 2 metabolites in tumor tissues, and 7 metabolic pathways and 8 metabolites in serum. Further network pharmacological analysis revealed that NOS2 was a potential target for FMN/CAL to regulate the metabolism in TMZ-treated C6 glioma cells, serums and tissues, and TNF-α was another potential target identified in tissues. FMN/CAL down-regulated the expression of NOS2 in tumor cells and tissues, and reduced the secretion of TNF-α in tumor region. FMN/CAL promoted TMZ-induced C6 cell apoptosis by inhibiting NOS2, but the inhibition of cell vitality and migration was not through NOS2. Our work revealed that FMN/CAL can increase the sensitivity of malignant glioma to TMZ by inhibiting NOS2-dependent cell survival, which provides a basis for the application of this combination in adjuvant treatment of glioma.

Identification of a Signature for Predicting Prognosis and Immunotherapy Response in Patients with Glioma

Glioma is a deadly tumor that accounts for the vast majority of brain tumors. Thus, it is important to elucidate the molecular pathogenesis and potential diagnostic and prognostic biomarkers of glioma. In the present study, gene expression profiles of GSE2223 were obtained from the Gene Expression Omnibus (GEO) database. Core modules and hub genes related to glioma were identified using weighted gene coexpression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis of differentially expressed genes (DEGs). After a series of database screening tests, we identified 11 modules during glioma progression, followed by six hub genes (RAB3A, TYROBP, SYP, CAMK2A, VSIG4, and GABRA1) that can predict the prognosis of glioma and were validated in glioma tissues by qRT-PCR. The CIBERSORT algorithm was used to analyze the difference of immune cell infiltration between the glioma and control groups. Finally, Identification VSIG4 for immunotherapy response in patients with glioma demonstrating utility for immunotherapy research.

The copper-associated protein STEAP2 correlated with glioma prognosis and immune infiltration

High-grade glioma is characterized by cell heterogeneity, gene mutations, and poor prognosis. Abnormal copper homeostasis affects the pathogenesis of glioma, but the underlying mechanisms and involved proteins are unknown. Here, we selected 90 copper-related proteins and verified their expression differences in glioma and normal tissues in the TCGA cohort followed by GO and KEGG clustering analyses. We then developed and validated a prognostic model. Moreover, we examined the mutation burden of copper-related proteins and discussed the differences in the immune microenvironment in the high- and low-risk groups. Furthermore, we focused on STEAP2 and demonstrated that STEAP2 expression was relatively low in tumor tissues compared to normal tissues, implying a favorable prognosis. Our findings provide a foundation for future research targeting copper-related proteins and their immune microenvironment to improve prognosis and responses to immunotherapy.

A cuproptosis-related lncRNAs signature for prognosis, chemotherapy, and immune checkpoint blockade therapy of low-grade glioma

Cuproptosis is a new type of cell death that is associated with mitochondrial respiration of the tricarboxylic acid cycle. Previous studies showed that long non-coding RNAs (lncRNAs) regulated low-grade glioma (LGG) progression. However, the potential applications of cuproptosis-related lncRNAs (CRLs) in LGG were not explored. A comprehensive analysis was performed in The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) cohorts. We first screened two distinct cuproptosis subtypes based on prognostic CRLs using consensus clustering. To facilitate individualized survival prediction in LGG, we constructed a prognostic signature (including CRNDE, HAR1A, and FAM181A-AS1) in the TCGA dataset. The prognostic signature exhibited excellent predictive ability and reliability, which was validated in the CGGA_325 and CGGA_693 datasets. Notably, patients in the high-risk group had increased immune cell infiltration and expression of immune checkpoints, which indicated that they may benefit more from immune checkpoint blockade (ICB) therapy. Finally, the prognostic signature screened the population with sensitivity to chemotherapy and ICB therapy. In summary, this study initially explored the mechanism of CRLs in LGG and provides some insights into chemotherapy and ICB therapy of LGG.

Construction and validation of a glioblastoma prognostic model based on immune-related genes

Background

Glioblastoma multiforme (GBM) is a common malignant brain tumor with high mortality. It is urgently necessary to develop a new treatment because traditional approaches have plateaued.

Purpose

Here, we identified an immune-related gene (IRG)-based prognostic signature to comprehensively define the prognosis of GBM.

Methods

Glioblastoma samples were selected from the Chinese Glioma Genome Atlas (CGGA). We retrieved IRGs from the ImmPort data resource. Univariate Cox regression and LASSO Cox regression analyses were used to develop our predictive model. In addition, we constructed a predictive nomogram integrating the independent predictive factors to determine the one-, two-, and 3-year overall survival (OS) probabilities of individuals with GBM. Additionally, the molecular and immune characteristics and benefits of ICI therapy were analyzed in subgroups defined based on our prognostic model. Finally, the proteins encoded by the selected genes were identified with liquid chromatography-tandem mass spectrometry and western blotting (WB).

Results

Six IRGs were used to construct the predictive model. The GBM patients were categorized into a high-risk group and a low-risk group. High-risk group patients had worse survival than low-risk group patients, and stronger positive associations with multiple tumor-related pathways, such as angiogenesis and hypoxia pathways, were found in the high-risk group. The high-risk group also had a low IDH1 mutation rate, high PTEN mutation rate, low 1p19q co-deletion rate and low MGMT promoter methylation rate. In addition, patients in the high-risk group showed increased immune cell infiltration, more aggressive immune activity, higher expression of immune checkpoint genes, and less benefit from immunotherapy than those in the low-risk group. Finally, the expression levels of TNC and SSTR2 were confirmed to be significantly associated with patient prognosis by protein mass spectrometry and WB.

Conclusion

Herein, a robust predictive model based on IRGs was developed to predict the OS of GBM patients and to aid future clinical research.

Predictive value of PIMREG in the prognosis and response to immune checkpoint blockade of glioma patients

Glioma is the most common primary brain tumor in the human brain. The present study was designed to explore the expression of PIMREG in glioma and its relevance to the clinicopathological features and prognosis of glioma patients. The correlations of PIMREG with the infiltrating levels of immune cells and its relevance to the response to immunotherapy were also investigated. PIMREG expression in glioma was analyzed based on the GEO, TCGA, and HPA databases. Kaplan–Meier survival analysis was used to examine the predictive value of PIMREG for the prognosis of patients with glioma. The correlation between the infiltrating levels of immune cells in glioma and PIMREG was analyzed using the CIBERSORT algorithm and TIMRE database. The correlation between PIMREG and immune checkpoints and its correlation with the patients’ responses to immunotherapy were analyzed using R software and the GEPIA dataset. Cell experiments were conducted to verify the action of PIMREG in glioma cell migration and invasion. We found that PIMREG expression was upregulated in gliomas and positively associated with WHO grade. High PIMREG expression was correlated with poor prognosis of LGG, prognosis of all WHO grade gliomas, and prognosis of recurrent gliomas. PIMREG was related to the infiltration of several immune cell types, such as M1 and M2 macrophages, monocytes and CD8+ T cells. Moreover, PIMREG was correlated with immune checkpoints in glioma and correlated with patients’ responses to immunotherapy. KEGG pathway enrichment and GO functional analysis illustrated that PIMREG was related to multiple tumor- and immune-related pathways. In conclusion, PIMREG overexpression in gliomas is associated with poor prognosis of patients with glioma and is related to immune cell infiltrates and the responses to immunotherapy.