CTLA4-Mediated Immunosuppression in Glioblastoma is Associated with the Infiltration of Macrophages in the Tumor Microenvironment

Shedding light on function of long non-coding RNAs (lncRNAs) in glioblastoma

The brain tumors and especially glioblastoma, are affecting life of many people worldwide and due to their high mortality and morbidity, their treatment is of importance and has gained attention in recent years. The abnormal expression of genes is commonly observed in GBM and long non-coding RNAs (lncRNAs) have demonstrated dysregulation in this tumor. LncRNAs have length more than 200 nucleotides and they have been located in cytoplasm and nucleus. The current review focuses on the role of lncRNAs in GBM. There two types of lncRNAs in GBM including tumor-promoting and tumor-suppressor lncRNAs and overexpression of oncogenic lncRNAs increases progression of GBM. LncRNAs can regulate proliferation, cell cycle arrest and metastasis of GBM cells. Wnt, STAT3 and EZH2 are among the molecular pathways affected by lncRNAs in GBM and for regulating metastasis of GBM cells, these RNA molecules mainly affect EMT mechanism. LncRNAs are involved in drug resistance and can induce resistance of GBM cells to temozolomide chemotherapy. Furthermore, lncRNAs stimulate radio-resistance in GBM cells. LncRNAs increase PD-1 expression to mediate immune evasion. LncRNAs can be considered as diagnostic and prognostic tools in GBM and researchers have developed signature from lncRNAs in GBM.

CTLA4 expression profiles and their association with clinical outcomes of breast cancer: a systemic review

Purpose

The cytotoxic T-lymphocyte-associated protein 4 (CTLA4) is involved in the progression of various cancers, but its biological roles in breast cancer (BRCA) remain unclear. Therefore, we performed a systematic multiomic analysis to expound on the prognostic value and underlying mechanism of CTLA4 in BRCA.

Methods

We assessed the effect of CTLA4 expression on BRCA using a variety of bioinformatics platforms, including Oncomine, GEPIA, UALCAN, PrognoScan database, Kaplan-Meier plotter, and R2: Kaplan-Meier scanner.

Results

CTLA4 was highly expressed in BRCA tumor tissue compared to normal tissue (P < 0.01). The CTLA4 messenger RNA levels in BRCA based on BRCA subtypes of Luminal, human epidermal growth factor receptor 2, and triple-negative BRCA were considerably higher than in normal tissues (P < 0.001). However, the overexpression of CTLA4 was associated with a better prognosis in BRCA (P < 0.001) and was correlated with clinicopathological characteristics including age, T stage, estrogen receptors, progesterone receptors, and prediction analysis of microarray 50 (P < 0.01). The infiltration of multiple immune cells was associated with increased CTLA4 expression in BRCA (P < 0.001). CTLA4 was highly enriched in antigen binding, immunoglobulin complexes, lymphocyte-mediated immunity, and cytokine-cytokine receptor interaction.

Conclusion

This study provides suggestive evidence of the prognostic role of CTLA4 in BRCA, which may be a therapeutic target for BRCA. Furthermore, CTLA4 may influence BRCA prognosis through antigen binding, immunoglobulin complexes, lymphocyte-mediated immunity, and cytokine-cytokine receptor interaction. These findings help us understand how CTLA4 plays a role in BRCA and set the stage for more research.

A Roadmap of CAR-T-Cell Therapy in Glioblastoma: Challenges and Future Perspectives

Glioblastoma (GBM) is the most common primary malignant brain tumor, with a median overall survival of less than 2 years and a nearly 100% mortality rate under standard therapy that consists of surgery followed by combined radiochemotherapy. Therefore, new therapeutic strategies are urgently needed. The success of chimeric antigen receptor (CAR) T cells in hematological cancers has prompted preclinical and clinical investigations into CAR-T-cell treatment for GBM. However, recent trials have not demonstrated any major success. Here, we delineate existing challenges impeding the effectiveness of CAR-T-cell therapy for GBM, encompassing the cold (immunosuppressive) microenvironment, tumor heterogeneity, T-cell exhaustion, local and systemic immunosuppression, and the immune privilege inherent to the central nervous system (CNS) parenchyma. Additionally, we deliberate on the progress made in developing next-generation CAR-T cells and novel innovative approaches, such as low-intensity pulsed focused ultrasound, aimed at surmounting current roadblocks in GBM CAR-T-cell therapy.

Signature Construction and Disulfidptosis-Related Molecular Cluster Identification for Better Prediction of Prognosis in Glioma

Disulfidptosis is a newly discovered form of regulatory cell death. However, the identification of disulfidptosis-related molecular subtypes and potential biomarkers in gliomas and their prognostic predictive potential need to be further elucidated. RNA sequencing profiles and the relevant clinical data were obtained from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). Disulfidptosis-related clusters were identified by unsupervised clustering analysis. Immune cell infiltration analysis and drug sensitivity analysis were used to explore the differences between clusters. Gene set enrichment analysis (GSEA) of differential genes between clusters was performed to explore the potential biological functions and signaling. A disulfidptosis-related scoring system (DRSS) was constructed based on a combined COX and LASSO analysis. Mendelian randomization (MR) analyses were used to further explore the causal relationship between levels of genes in DRSS and an increased risk of glioma. A prognosis nomogram was constructed based on the DRSS and 3 clinical features (age, WHO stage, and IDH status). The accuracy and stability of the prognosis nomogram were also validated in different cohorts. We identified two clusters that exhibited different prognoses, drug sensitivity profiles, and tumor microenvironment infiltration profiles. The overall survival (OS) of Cluster2 was significantly better than Cluster1. Cluster1 had an overall greater infiltration of immune cells compared to Cluster2. However, the Monocytes, activated B cells had higher infiltration abundance in Cluster2. GSEA results showed significant enrichment of immune-related biological processes in Cluster1, while Cluster2 was more enriched for functions related to neurotransmission and regulation. PER3, RAB34, NKX3-2, GPX7, FRA10AC1, and TGIF1 were finally included to construct DRSS. DRSS was independently related to prognosis. There was a significant difference in overall survival between the low-risk score group and the high-risk score group. Among six genes in DRSS, GPX7 levels were demonstrated to have a causal relationship with an increased risk of glioma. GPX7 may become a more promising biomarker for gliomas. The prognosis nomogram constructed based on the DRSS and three clinical features has considerable potential for predicting the prognosis of patients with glioma. Free online software for implementing this nomogram was established:  https://yekun-zhuang.shinyapps.io/DynNomapp/ . Our study established a novel glioma classification based on the disulfidptosis-related molecular subtypes. We constructed the DRSS and the prognosis nomogram to accurately stratify the prognosis of glioma patients. GPX7 was identified as a more promising biomarker for glioma. We provide important insights into the treatment and prognosis of gliomas.

Predictive value of procollagen c-protease enhancer protein on the prognosis of glioma patients

Procollagen c-protease enhancer protein (PCOLCE) performs an essential action in improving the recreation of procollagen c-protease and promoting the reconstruction of extracellular matrix. High PCOLCE expression was associated with a negative prognosis of stomach cancer, ovarian cancer, and osteosarcoma. The goal of this work is to investigate the function of PCOLCE in glioma. Multiple bioinformatics techniques have been employed to investigate the roles of PCOLCE in glioma, consisting of the correlation between PCOLCE and prognosis, immune checkpoints, immune cell infiltrates, and tumor microenvironment (TME). The gene ontology (GO) annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to assess the potential function of PCOLCE in glioma. PCOLCE was found to be increased in glioma. We revealed that PCOLCE was a potential prognostic factor and related to tumor grade. Up-regulated PCOLCE was related to poor prognosis in lower-grade glioma (LGG), glioblastoma multiforme (GBM), and recurrent glioma. PCOLCE was correlated with immune cell infiltration, particularly B cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells (DCs) in LGG, and DCs infiltration in GBM. PCOLCE was co-expressed with many genes related to the immune and the immune checkpoint. In addition, glioma patients with low expression of PCOLCE had a higher response to the immunological checkpoint blockade (ICB). Additionally, PCOLCE may exert its roles via several immune-related biological processes or pathways, such as leukocyte migration, activation of T cells, adaptive immune response, neutrophil-mediated immunity, NF-κB, and TNF signaling pathways. In conclusion, PCOLCE may be a new immune-related gene and regulate tumor development through immunological pathways.

Potential value of expression of receptor accessory protein 4 for evaluating the prognosis of lower-grade glioma patients

BACKGROUND

REEP4 is involved in the regulation of the biological process of mitosis. Lower grade glioma (LGG), as a malignant tumor, is accompanied by abnormalities in mitosis, but there have been no reports of REEP4 so far.

METHODS

We collected transcriptome data, DNA methylation data and the clinical characteristics of thousands of patients with LGG. Various big data analysis methods and molecular biology experiments were employed to reveal the impact of REEP4 on the pathological process of LGG.

RESULTS

It was found that the expression of REEP4 was significantly elevated and negatively regulated by its methylation site. Therefore, both the high expression of REEP4 and low methylation state of cg16311504 showed that the patients are correlated with lower patient survival rate. In addition, high REEP4 expression participates in the regulation of various cancer-related cellular signaling pathways, such as the cell cycle, MAPK signaling pathway, NOD-like receptor signaling pathway, etc. More importantly, the level of immune cell infiltration significantly increased in the high expression group of REEP4 in the LGG tumor microenvironment and REEP4 has a high positive correlation with PD-L1 and other immune checkpoints.

CONCLUSIONS

In brief, this study is the first to introduce REEP4 in malignant tumors, which can be used as an independent risk factor that participates in the malignant process of LGG. More importantly, REEP4 has the potential to become a new star in the field of anti-tumor treatment.

From glioma gloom to immune bloom: unveiling novel immunotherapeutic paradigms-a review

In tumor therapeutics, the transition from conventional cytotoxic drugs to targeted molecular therapies, such as those targeting receptor tyrosine kinases, has been pivotal. Despite this progress, the clinical outcomes have remained modest, with glioblastoma patients' median survival stagnating at less than 15 months. This underscores the urgent need for more specialized treatment strategies. Our review delves into the progression toward immunomodulation in glioma treatment. We dissect critical discoveries in immunotherapy, such as spotlighting the instrumental role of tumor-associated macrophages, which account for approximately half of the immune cells in the glioma microenvironment, and myeloid-derived suppressor cells. The complex interplay between tumor cells and the immune microenvironment has been explored, revealing novel therapeutic targets. The uniqueness of our review is its exhaustive approach, synthesizing current research to elucidate the intricate roles of various molecules and receptors within the glioma microenvironment. This comprehensive synthesis not only maps the current landscape but also provides a blueprint for refining immunotherapy for glioma, signifying a paradigm shift toward leveraging immune mechanisms for improved patient prognosis.

Construction of a prognosis model of head and neck squamous cell carcinoma pyroptosis and an analysis of immuno-phenotyping based on bioinformatics

Background

Head and neck squamous cell carcinoma (HNSCC) is currently the sixth most common cancer worldwide, and its prevalence and recurrence rates are gradually increasing. To study the relationship between HNSCC and cell pyroptosis and provide new treatment options for HNSCC, a prognostic model of pyroptosis-related genes (PRGs) was established to predict the prognosis of patients with HNSCC, and an immune correlation analysis was performed.

Methods

A total of 53 PRGs were selected. We comprehensively analyzed the role of these PRGs in HNSCC through multiple omics data-set integration. We then identified two different molecular subtypes and found that changes in multi-layer PRGs were associated with clinicopathological characteristics, prognosis, and tumor microenvironment cell-infiltration characteristics in patients. Next, prognostic models were generated for nine PRGs; that is, cytotoxic T lymphocyte antigen 4 (CTLA4), V-set and immunoglobulin domain containing 4 (VSIG4), heparin-binding-epidermal growth factor (HBEGF), aquaporin-1 (AQP1), sodium channel epithelial 1 subunit delta (SCNN1D), argininosuccinate synthase 1 (ASS1), family with sequence similarity 83 member (FAM83), cyclin dependent kinase inhibitor 2A (CDKN2A), and serine protease inhibitor Kazal 6 (SPINK6). Finally, a risk-score model was constructed, and the Kaplan-Meier method was used to evaluate overall survival. In addition, the immune environment and drug sensitivity were analyzed.

Results

This study showed that pyroptosis is closely related to HNSCC. The scores generated by the risk markers based on the new nine PRGs were identified as independent risk factors for predicting HNSCC. The differentially expressed genes between the low- and high-risk groups were further found to be related to the tumor immune cells and pathways. In addition, the risk score was found to be significantly correlated with chemosensitivity.

Conclusions

Our comprehensive analysis of PRGs revealed their potential role in the tumor immune microenvironment, clinicopathological characteristics, and prognosis. These findings may improve our understanding of pyroptosis in HNSCC and may provide new ideas for evaluating prognosis and developing more effective immunotherapy strategies.

Small Molecule Tyrosine Kinase Inhibitors (TKIs) for Glioblastoma Treatment

In the last decade, many small molecules, usually characterized by heterocyclic scaffolds, have been designed and synthesized as tyrosine kinase inhibitors (TKIs). Among them, several compounds have been tested at preclinical and clinical levels to treat glioblastoma multiforme (GBM). GBM is the most common and aggressive type of cancer originating in the brain and has an unfavorable prognosis, with a median survival of 15-16 months and a 5-year survival rate of 5%. Despite recent advances in treating GBM, it represents an incurable disease associated with treatment resistance and high recurrence rates. For these reasons, there is an urgent need for the development of new pharmacological agents to fight this malignancy. In this review, we reported the compounds published in the last five years, which showed promising activity in GBM preclinical models acting as TKIs. We grouped the compounds based on the targeted kinase: first, we reported receptor TKIs and then, cytoplasmic and peculiar kinase inhibitors. For each small molecule, we included the chemical structure, and we schematized the interaction with the target for some representative compounds with the aim of elucidating the mechanism of action. Finally, we cited the most relevant clinical trials.

Tumour-associated macrophages: versatile players in the tumour microenvironment

Tumour-Associated Macrophages (TAMs) are one of the pivotal components of the tumour microenvironment. Their roles in the cancer immunity are complicated, both pro-tumour and anti-cancer activities are reported, including not only angiogenesis, extracellular matrix remodeling, immunosuppression, drug resistance but also phagocytosis and tumour regression. Interestingly, TAMs are highly dynamic and versatile in solid tumours. They show anti-cancer or pro-tumour activities, and interplay between the tumour microenvironment and cancer stem cells and under specific conditions. In addition to the classic M1/M2 phenotypes, a number of novel dedifferentiation phenomena of TAMs are discovered due to the advanced single-cell technology, e.g., macrophage-myofibroblast transition (MMT) and macrophage-neuron transition (MNT). More importantly, emerging information demonstrated the potential of TAMs on cancer immunotherapy, suggesting by the therapeutic efficiency of the checkpoint inhibitors and chimeric antigen receptor engineered cells based on macrophages. Here, we summarized the latest discoveries of TAMs from basic and translational research and discussed their clinical relevance and therapeutic potential for solid cancers.

Noninvasive radiomic analysis of enhanced CT predicts CTLA4 expression and prognosis in head and neck squamous cell carcinoma

Developing a radiomic model to predict CTLA4 expression levels and assessing its prognostic accuracy for patients. Medical imaging data were sourced from the TCIA database, while transcriptome sequencing data were derived from the TCGA database. We utilized a linear kernel SVM algorithm to develop a radiomic model for predicting CTLA4 gene expression. We then assessed the model's clinical relevance using survival and Cox regression analyses. Performance evaluations of the model were illustrated through ROC, PR, calibration, and decision curves. (1) Bioinformatics analysis: Kaplan-Meier curves indicated that increased CTLA4 expression correlates with enhanced overall survival (OS) (p < 0.001). Both univariate and multivariate analyses revealed that high CTLA4 expression served as a protective factor for OS (HR = 0.562, 95% CI 0.427-0.741, p < 0.001). (2) Radiomics evaluation: the ROC curve demonstrated that the AUC for the SVM radiomics model was 0.766 in the training set and 0.742 in the validation set. The calibration curve affirmed that the model's prediction probability for high gene expression aligns with the actual outcomes. Furthermore, decision curve analysis (DCA) indicated that our model boasts robust clinical applicability. CTLA4 expression level serves as an independent prognostic factor for HNSCCs. Using enhanced CT images, the SVM radiomic model effectively predicts CTLA4 expression levels. As a result, this model offers strong prognostic insights for HNSCCs, guiding precise diagnosis, treatment, and assisting in clinical decision-making.

A prognostic matrix code defines functional glioblastoma phenotypes and niches

Interactions among tumor, immune and vascular niches play major roles in driving glioblastoma (GBM) malignancy and treatment responses. The composition, heterogeneity, and localization of extracellular core matrix proteins (CMPs) that mediate such interactions, however, are not well understood. Here, we characterize functional and clinical relevance of genes encoding CMPs in GBM at bulk, single cell, and spatial anatomical resolution. We identify a "matrix code" for genes encoding CMPs whose expression levels categorize GBM tumors into matrisome-high and matrisome-low groups that correlate with worse and better patient survival, respectively. The matrisome enrichment is associated with specific driver oncogenic alterations, mesenchymal state, infiltration of pro-tumor immune cells and immune checkpoint gene expression. Anatomical and single cell transcriptome analyses indicate that matrisome gene expression is enriched in vascular and leading edge/infiltrative anatomic structures that are known to harbor glioma stem cells driving GBM progression. Finally, we identified a 17-gene matrisome signature that retains and further refines the prognostic value of genes encoding CMPs and, importantly, potentially predicts responses to PD1 blockade in clinical trials for GBM. The matrisome gene expression profiles provide potential biomarkers of functionally relevant GBM niches that contribute to mesenchymal-immune cross talk and patient stratification which could be applied to optimize treatment responses.

Immunotherapeutic Approaches for the Treatment of Glioblastoma Multiforme: Mechanism and Clinical Applications

Glioma is one of the most aggressive types of primary brain tumor with a high-grade glioma known as glioblastoma multiforme (GBM). Patients diagnosed with GBM usually have an overall survival rate of less than 18 months after conventional therapy. This bleak prognosis underlines the need to consider new therapeutic interventions for GBM treatment to overcome current treatment limitations. By highlighting different immunotherapeutic approaches currently in preclinical and clinical trials, including immune checkpoint inhibitors, chimeric antigen receptors T cells, natural killer cells, vaccines, and combination therapy, this review aims to discuss the mechanisms, benefits, and limitations of immunotherapy in treating GBM patients.

The value of basement membrane-associated genes in the prognosis and immune regulation of glioma

Gliomas have a high incidence rate in central nervous tumors. Although many breakthroughs have been made in the pathogenesis and treatment of glioma, the recurrence and metastasis rates of patients have not been improved based on the uniqueness of glioma. Glioma destroys the surrounding basement membrane (BM), leading to local infiltration, resulting in the corresponding clinical and neurological symptoms. Therefore, exploring the biological roles played by BM associated genes in glioma is particularly necessary for a comprehensive understanding of the biological processes of glioma and its treatment. Differential expression and univariate COX regression analyses were used to identify the basement membrane genes (BMGs) to be included in the model. LASSO regression was used to construct the BMG model. The Kaplan-Meier (KM) survival analysis model was used to assess the prognosis discrimination between training sets, validation sets, and clinical subgroups. Receiver-operating characteristic (ROC) analysis was used to test the prognostic efficacy of the model. Use calibration curves to verify the accuracy of nomograms. Gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), and gene set enrichment analysis (GSEA) were used to analyze the function and pathway enrichment among the model groups. ESTIMATE and other 7 algorithms including CIBERSORT were used to evaluate the immune microenvironment. "pRRophetic" was used to evaluate drug sensitivity. This study demonstrated that high-risk genes (LAMB4, MMP1, MMP7) promote glioma progression and negatively correlate with patient prognosis. In the tumor microenvironment (TME), high-risk genes have increased scores of macrophages, neutrophils, immune checkpoints, chemokines, and chemokine receptors. This study suggests that BMGs, especially high-risk-related genes, are potential sites for glioma therapy, a new prospect for comprehensively understanding the molecular mechanism of glioma.

A prognostic matrix code defines functional glioblastoma phenotypes and niches

Interactions among tumor, immune and vascular niches play major roles in driving glioblastoma (GBM) malignancy and treatment responses. The composition, heterogeneity, and localization of extracellular core matrix proteins (CMPs) that mediate such interactions, however, are not well understood. Here, we characterize functional and clinical relevance of genes encoding CMPs in GBM at bulk, single cell, and spatial anatomical resolution. We identify a "matrix code" for genes encoding CMPs whose expression levels categorize GBM tumors into matrisome-high and matrisome-low groups that correlate with worse and better survival, respectively, of patients. The matrisome enrichment is associated with specific driver oncogenic alterations, mesenchymal state, infiltration of pro-tumor immune cells and immune checkpoint gene expression. Anatomical and single cell transcriptome analyses indicate that matrisome gene expression is enriched in vascular and leading edge/infiltrative anatomic structures that are known to harbor glioma stem cells driving GBM progression. Finally, we identified a 17-gene matrisome signature that retains and further refines the prognostic value of genes encoding CMPs and, importantly, potentially predicts responses to PD1 blockade in clinical trials for GBM. The matrisome gene expression profiles may provide biomarkers of functionally relevant GBM niches that contribute to mesenchymal-immune cross talk and patient stratification to optimize treatment responses.

Immunotherapy in glioblastoma treatment: Current state and future prospects

Glioblastoma remains as the most common and aggressive malignant brain tumor, standing with a poor prognosis and treatment prospective. Despite the aggressive standard care, such as surgical resection and chemoradiation, median survival rates are low. In this regard, immunotherapeutic strategies aim to become more attractive for glioblastoma, considering its recent advances and approaches. In this review, we provide an overview of the current status and progress in immunotherapy for glioblastoma, going through the fundamental knowledge on immune targeting to promising strategies, such as Chimeric antigen receptor T-Cell therapy, immune checkpoint inhibitors, cytokine-based treatment, oncolytic virus and vaccine-based techniques. At last, it is discussed innovative methods to overcome diverse challenges, and future perspectives in this area.

Differences of macrophages in the tumor microenvironment as an underlying key factor in glioma patients

Background

Macrophages, the major immune cells in glioma microenvironment, are closely related to tumor prognosis. Further studies are needed to investigate macrophages, which will be helpful to fully understand the role of it and early achieve clinical translation.

Methods

A total of 1334 glioma cases were enrolled in this study from 3 databases. In our works, the single cell cohorts from GSE89567, GSE84465, and the Chinese Glioma Genome Atlas (CGGA) datasets were used to analyze the key genes of macrophage. The bulk sequencing data from the Cancer Genome Atlas (TCGA) and CGGA datasets were respectively divided into the training set and validation set to test prognostic value of the key genes from single cell analysis.

Results

Quantitative and functional differences significantly emerge in macrophage clusters between LGG and GBM. Firstly, we used the Seurat R package to identify 281 genes differentially expressed genes in macrophage clusters between LGG and GBM. Furthermore, based on these genes, we developed a predictive risk model to predict prognosis and reflect the immune microenvironment in glioma. The risk score calculation formula was yielded as follows: Risk score = (0.11 × EXPMACC1) + (−0.31 × EXPOTUD1) + (−0.09 × EXPTCHH) + (0.26 × EXPADPRH) + (-0.40× EXPABCG2) + (0.21 × EXPPLBD1) + (0.12 × EXPANG) + (0.29 × EXPQPCT). The risk score was independently related to prognosis. Further, significant differences existed in immunological characteristics between the low- and high-risk score groups. What is more, mutation analysis found different genomic patterns associated with the risk score.

Conclusion

This study further confirms that the proportion of macrophage infiltration is not only significantly different, but the function of them is also different. The signature, identified from the differentially expressed macrophage-related genes impacts poor prognosis and short overall survival and may act as therapeutic targets in the future.

Phosphoserine phosphatase as an indicator for survival through potentially influencing the infiltration levels of immune cells in neuroblastoma

Introduction: Metabolic deregulation, a hallmark of cancer, fuels cancer cell growth and metastasis. Phosphoserine phosphatase (PSPH), an enzyme of the serine metabolism pathway, has been shown to affect patients’ prognosis in many cancers but its significance in neuroblastoma remains unknown. Here, we show that the functional role and potential mechanism of PSPH and it is correlated with survival of neuroblastoma patients.

Patients and Methods: The TARGET dataset (n = 151) and our hospital-based cases (n = 55) were used for assessing the expression level of PSPH associated with survival in neuroblastoma patients, respectively. Then, in vitro experiments were performed to define the role of PSPH in neuroblastoma. The ESTIMATE and TIMER algorithms were utilized to examine the correlation between PSPH expression level and abundance of immune cells. Further, Kaplan-Meier survival analysis was performed to evaluate the effect of both PSPH and immune cells on patients’ prognosis.

Results: High expression of PSPH was significantly associated with unfavorable overall survival (OS) and event-free survival (EFS) in both the TARGET dataset and our hospital-based cases, and was an independent predictor of OS (hazard ratio, 2.00; 95% confidence intervals, 1.21–3.30, p = 0.0067). In vitro experiments showed that high expression of PSPH significantly promoted cell growth and metastasis. Further, the ESTIMATE result suggested that high expression level of PSPH was negatively associated with low stromal and ESTIMATE score. Specifically, high PSPH expression was found to be negatively associated with CD8⁺ T cell, macrophages and neutrophils, which negatively affected survival of neuroblastoma patients (p < 0.0001, p = 0.0005, and p = 0.0004, respectively).

Conclusion: These findings suggested that PSPH expression could be a promising indicator for prognosis and immunotherapy in neuroblastoma patients by potentially influencing infiltration levels of immune cells.

Clinical Characterization and Prognostic Value of TPM4 and Its Correlation with Epithelial–Mesenchymal Transition in Glioma

Tropomyosin 4 (TPM4) has been reported as an oncogenic gene across different malignancies. However, the role of TPM4 in glioma remains unclear. This study aimed to determine the clinical characterization and prognostic value of TPM4 in gliomas. Transcriptome expression and clinical information were collected from the CGGA and TCGA datasets, which included 998 glioma patients. ScRNA-seq data were obtained from CGGA. R software was utilized for statistical analyses. There was a positive correlation between TPM4 and WHO grades. IDH-wildtype and mesenchymal subtype gliomas were accompanied by TPM4 upregulation. GO and GSEA analysis suggested that TPM4 was profoundly associated with epithelial-to-mesenchymal transition (EMT). Subsequent GSVA revealed a robust correlation between TPM4 and three signaling pathways of EMT (hypoxia, TGF-β, PI3K/AKT). Furthermore, TPM4 showed a synergistic effect with mesenchymal biomarkers, particularly with N-cadherin, Slug, Snail, TWIST1, and vimentin. ScRNA-seq analysis suggested that higher TPM4 was mainly attributed to tumor cells and macrophages and associated with tumor cell progression and macrophage polarization. Finally, high TPM4 was significantly associated with unfavorable outcomes. In conclusion, our findings indicate that TPM4 is significantly correlated with more malignant characteristics of gliomas, potentially through involvement in EMT. TPM4 could predict worse survival for patients with glioma.

Comprehensive Analysis of the Brain-Expressed X-Link Protein Family in Glioblastoma Multiforme

Glioblastoma multiforme (GBM) is the most common, malignant, and deadly primary brain tumor in adults. Brain-expressed X-link (BEX) protein family is involved in tumorigenesis. Here, we have explored the biological function and the prognostic value of the BEX family in GBM. Differentially expressed BEX genes between GBM and normal tissue were screened by using The Cancer Genome Atlas (TCGA) database. Univariate and multivariate Cox regression analyses identified the prognosis‐related genes BEX1, BEX2, and BEX4, which were involved in the regulation of immune response. The results of correlation analysis and protein–protein interaction network (PPI network) showed that there was a significant correlation between the BEX family and TCEAL family in GBM. Furthermore, the expression of transcription elongation factor A (SII)-like (TCEAL) family is generally decreased in GBM and related to poor prognosis. With the use of the least absolute shrinkage and selection operator (LASSO) Cox regression, a prognostic model including the BEX family and TCEAL family was built to accurately predict the likelihood of overall survival (OS) in GBM patients. Therefore, we demonstrated that the BEX family and TCEAL family possessed great potential as therapeutic targets and prognostic biomarkers in GBM. Further investigations in large‐scale, multicenter, and prospective clinical cohorts are needed to confirm the prognostic model developed in our study.