Identification of Immune Cell Infiltration and Immune-Related Genes in the Tumor Microenvironment of Glioblastomas

Immunological processes of enhancers and suppressors of long non-coding RNAs associated with brain tumors and inflammation

Immunological processes, such as inflammation, can both cause tumor suppression and cancer progression. Moreover, deregulated levels of long non-coding RNA (lncRNA) expression in the brain may cause inflammation and lead to the growth of tumors. Like other biological processes, the immune system's role in cancer is complicated, varies, and can help or hurt the cancer's maintenance. According to research, inflammation and brain cancer are correlated via several signaling pathways. A variety of lncRNAs have recently been revealed to influence cancer by modulating inflammatory pathways. As a result, lncRNAs have the potential to influence carcinogenesis, tumor formation, or tumor suppression via an increase or decrease in inflammation functions. Although the study and targeting of lncRNAs have made great progress in the treatment of cancer, there are definitely limitations and challenges. Using new technologies like nanocarriers and cell-penetrating peptides (CPPs) to target treatments without hurting healthy body tissues has shown to be very effective. In this review article, we have collected significantly related lncRNAs and their inhibitory or stimulating roles in inflammation and brain cancer for the first time. However, there are limitations, such as side effects and damage to normal tissues. With the advancement of new targeting technologies, these lncRNAs may be candidates for the specific targeting therapy of brain cancers by limiting inflammation or stimulating the immune system against them in the future.

An atlas of causal and mechanistic drivers of interpatient heterogeneity in glioma

Grade IV glioma, formerly known as glioblastoma multiforme (GBM) is the most aggressive and lethal type of brain tumor, and its treatment remains challenging in part due to extensive interpatient heterogeneity in disease driving mechanisms and lack of prognostic and predictive biomarkers. Using mechanistic inference of node-edge relationship (MINER), we have analyzed multiomics profiles from 516 patients and constructed an atlas of causal and mechanistic drivers of interpatient heterogeneity in GBM (gbmMINER). The atlas has delineated how 30 driver mutations act in a combinatorial scheme to causally influence a network of regulators (306 transcription factors and 73 miRNAs) of 179 transcriptional "programs", influencing disease progression in patients across 23 disease states. Through extensive testing on independent patient cohorts, we share evidence that a machine learning model trained on activity profiles of programs within gbmMINER significantly augments risk stratification, identifying patients who are super-responders to standard of care and those that would benefit from 2 nd line treatments. In addition to providing mechanistic hypotheses regarding disease prognosis, the activity of programs containing targets of 2 nd line treatments accurately predicted efficacy of 28 drugs in killing glioma stem-like cells from 43 patients. Our findings demonstrate that interpatient heterogeneity manifests from differential activities of transcriptional programs, providing actionable strategies for mechanistically characterizing GBM from a systems perspective and developing better prognostic and predictive biomarkers for personalized medicine.

Identification of novel hub genes for Alzheimer's disease associated with the hippocampus using WGCNA and differential gene analysis

Background

Alzheimer's disease (AD) is a common, refractory, progressive neurodegenerative disorder in which cognitive and memory deficits are highly correlated with abnormalities in hippocampal brain regions. There is still a lack of hippocampus-related markers for AD diagnosis and prevention.

Methods

Differently expressed genes were identified in the gene expression profile GSE293789 in the hippocampal brain region. Enrichment analyses GO, KEGG, and GSEA were used to identify biological pathways involved in the DEGs and AD-related group. WGCNA was used to identify the gene modules that are highly associated with AD in the samples. The intersecting genes of the genes in DEGs and modules were extracted and the top ten ranked hub genes were identified. Finally GES48350 was used as a validation cohort to predict the diagnostic efficacy of hub genes.

Results

From GSE293789, 225 DEGs were identified, which were mainly associated with calcium response, glutamatergic synapses, and calcium-dependent phospholipid-binding response. WGCNA analysis yielded dark green and bright yellow modular genes as the most relevant to AD. From these two modules, 176 genes were extracted, which were taken to be intersected with DEGs, yielding 51 intersecting genes. Then 10 hub genes were identified in them: HSPA1B, HSPB1, HSPA1A, DNAJB1, HSPB8, ANXA2, ANXA1, SOX9, YAP1, and AHNAK. Validation of these genes was found to have excellent diagnostic performance.

Conclusion

Ten AD-related hub genes in the hippocampus were identified, contributing to further understanding of AD development in the hippocampus and development of targets for therapeutic prevention.

APOBEC3C is a novel target for the immune treatment of lower-grade gliomas

BACKGROUND

Apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC) type 3C (A3C) has been identified as a cancer molecular biomarker in the past decade. However, the practical role of A3C in lower-grade gliomas (LGGs) in improving the clinical outcome remains unclear. This study aims to discuss the function of A3C in immunotherapy in LGGs.

METHODS

The RNA-Sequencing (RNA-seq) and corresponding clinical data were extracted from UCSC Xena and the results were verified in the Chinese Glioma Genome Atlas (CGGA). Weighted gene co-expression network analysis (WGCNA) was used for screening A3C-related genes. Comprehensive bioinformation analyses were performed and multiple levels of expression, survival rate, and biological functions were assessed to explore the functions of A3C.

RESULTS

A3C expression was significantly higher in LGGs than in normal tissues but lower than in glioblastoma (GBM), indicating its role as an independent prognosis predictor for LGGs. Twenty-eight A3C-related genes were found with WGCNA for unsupervised clustering analysis and three modification patterns with different outcomes and immune cell infiltration were identified. A3C and the A3C score were also correlated with immune cell infiltration and the expression of immune checkpoints. In addition, the A3C score was correlated with increased sensitivity to chemotherapy. Single-cell RNA (scRNA) analysis indicated that A3C most probably expresses on immune cells, such as T cells, B cells and macrophage.

CONCLUSIONS

A3C is an immune-related prognostic biomarker in LGGs. Developing drugs to block A3C could enhance the efficiency of immunotherapy and improve disease survival.Abbreviation: A3C: Apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC) type 3C; LGGs: lower-grade gliomas; CGGA: Chinese Glioma Genome Atlas; WGCNA: Weighted gene co-expression network analysis; scRNA: Single-cell RNA; HGG: higher-grade glioma; OS: overall survival; TME: tumor microenvironment; KM: Kaplan-Meier; PFI: progression-free interval; IDH: isocitrate dehydrogenase; ROC: receiver operating characteristic; GS: gene significance; MM: module membership; TIMER: Tumor IMmune Estimation Resource; GSVA: gene set variation analysis; ssGSEA: single-sample gene-set enrichment analysis; PCA: principal component analysis; AUC: area under ROC curve; HAVCR2: hepatitis A virus cellular receptor 2; PDCD1: programmed cell death 1; PDCD1LG2: PDCD1 ligand 2; PTPRC: protein tyrosine phosphatase receptor type C; ACC: Adrenocortical carcinoma; BLCA: Bladder Urothelial Carcinoma;BRCA: Breast invasive carcinoma; CESC: Cervical squamous cell carcinoma and endocervical adenocarcinoma; CHOLCholangiocarcinoma; COADColon adenocarcinoma; DLBC: Lymphoid Neoplasm Diffuse Large B-cell Lymphoma; ESCA: Esophageal carcinoma; GBM: Glioblastoma multiforme; HNSC: Head and Neck squamous cell carcinoma; KICH: Kidney Chromophobe; KIRC: Kidney renal clear cell carcinoma; KIRP: Kidney renal papillary cell carcinoma; LAML: Acute Myeloid Leukemia; LGG: Brain Lower Grade Glioma; LIHC: Liver hepatocellular carcinoma; LUAD: Lung adenocarcinoma; LUSC: Lung squamous cell carcinoma; MESO: Mesothelioma; OV: Ovarian serous cystadenocarcinoma; PAAD: Pancreatic adenocarcinoma; PCPG: Pheochromocytoma and Paraganglioma; PRAD: Prostate adenocarcinoma; READ: Rectum adenocarcinoma; SARC: Sarcoma; SKCM: Skin Cutaneous Melanoma; STAD: Stomach adenocarcinoma; TGCT: Testicular Germ Cell Tumors; THCA: Thyroid carcinoma; THYM: Thymoma; UCEC: Uterine Corpus Endometrial Carcinoma; UCS: Uterine Carcinosarcoma; UVM: Uveal Melanoma.

Comprehensive analysis of PSMD family members and validation of PSMD9 as a potential therapeutic target in human glioblastoma

AIMS

PSMD family members, as important components of the 26S proteasome, are well known to be involved in protein degradation. However, their role in glioblastoma (GBM) has not been rigorously investigated. We aimed to perform systematic analysis of the expression signature, prognostic significance and functions of PSMD family genes in GBM to reveal potential prognostic markers and new therapeutic targets among PSMD family members.

METHODS

In this study, we systemically analyzed PSMD family members in terms of their expression profiles, prognostic implications, DNA methylation levels, and genetic alterations; the relationships between their expression levels and immune infiltration and drug sensitivity; and their potential functional enrichment in GBM through bioinformatics assessment. Moreover, in vitro and in vivo experiments were used to validate the biological functions of PSMD9 and its targeted therapeutic effect in GBM.

RESULTS

The mRNA levels of PSMD5/8/9/10/11/13/14 were higher in GBM than in normal brain tissues, and the mRNA levels of PSMD1/4/5/8/9/11/12 were higher in high-grade glioma (WHO grade III & IV) than in low-grade glioma (WHO grade II). High mRNA expression of PSMD2/6/8/9/12/13/14 and low mRNA expression of PSMD7 were associated with poor overall survival (OS). Multivariate Cox regression analysis identified PSMD2/5/6/8/9/10/11/12 as independent prognostic factors for OS prediction. In addition, the protein-protein interaction network and gene set enrichment analysis results suggested that PSMD family members and their interacting molecules were involved in the regulation of the cell cycle, cell invasion and migration, and other biological processes in GBM. In addition, knockdown of PSMD9 inhibited cell proliferation, invasion and migration and induced G2/M cell cycle arrest in LN229 and A172 GBM cells. Moreover, PSMD9 promoted the malignant progression of GBM in vivo. GBM cell lines with high PSMD9 expression were more resistant to panobinostat, a potent deacetylase inhibitor, than those with low PSMD9 expression. In vitro and in vivo experiments further validated that PSMD9 overexpression rescued the GBM inhibitory effect of panobinostat.

CONCLUSION

This study provides new insights into the value of the PSMD family in human GBM diagnosis and prognosis evaluation, and we further identified PSMD9 as a potential therapeutic target. These findings may lead to the development of effective therapeutic strategies for GBM.

Immune-related lncRNAs signature and radiomics signature predict the prognosis and immune microenvironment of glioblastoma multiforme

BACKGROUND

Glioblastoma multiforme (GBM) is the most common primary malignant brain tumor in adults. This study aimed to construct immune-related long non-coding RNAs (lncRNAs) signature and radiomics signature to probe the prognosis and immune infiltration of GBM patients.

METHODS

We downloaded GBM RNA-seq data and clinical information from The Cancer Genome Atlas (TCGA) project database, and MRI data were obtained from The Cancer Imaging Archive (TCIA). Then, we conducted a cox regression analysis to establish the immune-related lncRNAs signature and radiomics signature. Afterward, we employed a gene set enrichment analysis (GSEA) to explore the biological processes and pathways. Besides, we used CIBERSORT to estimate the abundance of tumor-infiltrating immune cells (TIICs). Furthermore, we investigated the relationship between the immune-related lncRNAs signature, radiomics signature and immune checkpoint genes. Finally, we constructed a multifactors prognostic model and compared it with the clinical prognostic model.

RESULTS

We identified four immune-related lncRNAs and two radiomics features, which show the ability to stratify patients into high-risk and low-risk groups with significantly different survival rates. The risk score curves and Kaplan-Meier curves confirmed that the immune-related lncRNAs signature and radiomics signature were a novel independent prognostic factor in GBM patients. The GSEA suggested that the immune-related lncRNAs signature were involved in L1 cell adhesion molecular (L1CAM) interactions and the radiomics signature were involved signaling by Robo receptors. Besides, the two signatures was associated with the infiltration of immune cells. Furthermore, they were linked with the expression of critical immune genes and could predict immunotherapy's clinical response. Finally, the area under the curve (AUC) (0.890,0.887) and C-index (0.737,0.817) of the multifactors prognostic model were greater than those of the clinical prognostic model in both the training and validation sets, indicated significantly improved discrimination.

CONCLUSIONS

We identified the immune-related lncRNAs signature and tradiomics signature that can predict the outcomes, immune cell infiltration, and immunotherapy response in patients with GBM.

E2F3/5/8 serve as potential prognostic biomarkers and new therapeutic direction for human bladder cancer

OBJECTS

Human bladder cancer (BC) is the most common urogenital system malignancy. E2F transcription factors (E2Fs) have been reported to be involved in the growth of various cancers. However, the expression patterns, prognostic value and immune infiltration in the tumor microenvironment of the 8 E2Fs in BC have yet fully to be explored.

METHODS AND STRATEGY

We investigated the differential expression of E2Fs in BC patients, the prognostic value and correlation with immune infiltration by analyzing a range of databases.

RESULTS

We found that the mRNA expression levels of E2F1/2/3/4/5/7/8 were significantly higher in BC patients than that of control tissues. And the increased mRNA expression levels of all E2Fs were associated with tumor stage of BC. The survival analysis revealed that the elevated mRNA expression levels of E2F3/5/8 were significantly correlated with the overall survival (OS) of BC patients. And the genetic changes of E2Fs in BC patients were associated with shorter overall survival (OS) and progression-free survival (PFS). In addition, we revealed that the E2F3/5/8 expressions were closely correlated with tumor-infiltrating lymphocytes (TILs).

CONCLUSIONS

E2F3/5/8 might serve as promising prognostic biomarkers and new therapeutic direction for BC patients.

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.

The Role of γδ T-Lymphocytes in Glioblastoma: Current Trends and Future Directions

Cell-based immunotherapy for glioblastoma (GBM) encounters major challenges due to the infiltration-resistant and immunosuppressive tumor microenvironment (TME). γδ T cells, unconventional T cells expressing the characteristic γδ T cell receptor, have demonstrated promise in overcoming these challenges, suggesting great immunotherapeutic potential. This review presents the role of γδ T cells in GBM and proposes several research avenues for future studies. Using the PubMed, ScienceDirect, and JSTOR databases, we performed a review of the literature studying the biology of γδ T cells and their role in GBM treatment. We identified 15 studies focused on γδ T cells in human GBM. Infiltrative γδ T cells can incite antitumor immune responses in certain TMEs, though rapid tumor progression and TME hypoxia may impact the extent of tumor suppression. In the studies, available findings have shown both the potential for robust antitumor activity and the risk of protumor activity. While γδ T cells have potential as a therapeutic agent against GBM, the technical challenges of extracting, isolating, and expanding γδ T cells, and the activation of antitumoral versus protumoral cascades, remain barriers to their application. Overcoming these limitations may transform γδ T cells into a promising immunotherapy in GBM.

Modelling 3D Tumour Microenvironment In Vivo: A Tool to Predict Cancer Fate

Recently, many studies demonstrated the fundamental role of the tumour microenvironment (TME) in cancer progression. Here, we describe a method to visualize in 3D the behaviour of tumours in zebrafish embryos. We highlight two major actors of the TME, macrophages and vessels. This valuable tool is transposable to Patient-Derived Xenograft imaging in order to predict the fate of malignant tumours according to the dynamics of their TME.

HOXD9 is a potential prognostic biomarker involved in immune microenvironment of glioma

BACKGROUND

Glioma is the prevailing malignant tumor affecting the brain and central nervous system, constituting over 80% of all malignant brain tumors. HOXD9 has been implicated in the development of glioma, but the specific mechanism of its influence on glioma pathogenesis remains incompletely understood. The purpose of this study was to investigate the role of HOXD9 in glioma and examine the changes in HOXD9 expression during the progression of glioma, thus contributing new insights into the pathogenesis of glioma.

METHODS

Glioma samples from the Cancer Gene Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) datasets were included in this study. Variations in HOXD9 expression in gliomas between different subgroups of multiple clinical characteristics were explored, and the expression was validated in glioma samples using qRT-PCR and western blotting. Next, the impact of HOXD9 on the prognosis of gliomas was explored by survival analysis, receiver operating characteristic curve, and nomogram plots. Subsequently, the association between HOXD9 and the tumor immune microenvironment was explored using the ssGSEA algorithm and the ESTIMATE algorithm. Then, immune-related pathways associated with HOXD9 were determined by differential express analysis and GSEA. Finally, HOXD9-related genomic alterations were identified.

RESULTS

HOXD9 expression is upregulated and correlated with malignant properties in glioma. Similarly, our validation results showed significantly upregulated protein and mRNA levels of HOXD9 in glioma brain tissues. In addition, high HOXD9 expression was indicative of a poor prognosis for glioma patients. Additionally, elevated HOXD9 levels were associated with reduced tumor purity and higher levels of immune invasion. Finally, HOXD9 was significantly associated with genomic alterations.

CONCLUSION

Overall, this study has unveiled a significant association between HOXD9 and the prognosis and survival of glioma patients. Our findings highlight the potential of HOXD9 as a prognostic biomarker, implicating its role in influencing the glioma immune microenvironment.

Cuproptosis-related gene expression is associated with immune infiltration and CD47/CD24 expression in glioblastoma, and a risk score based on these genes can predict the survival and prognosis of patients

Introduction

Glioblastoma (GBM) is the most invasive type of glioma, is insensitive to radiotherapy and chemotherapy, and has high proliferation and invasive ability, with a 5-year survival rate of <5%. Cuproptosis-related genes (CRGs) have been successfully used to predict the prognosis of many types of tumors. However, the relationship between cuproptosis and GBM remains unclear.

Methods

Here, we sought to identify CRGs in GBM and elucidate their role in the tumor immune microenvironment and prognosis. To that aim, changes in CRGs in The Cancer Genome Atlas (TCGA) transcriptional and Gene Expression Omnibus (GEO) datasets (GEO4290 and GEO15824) were characterized, and the expression patterns of these genes were analyzed.

Results

A risk score based on CRG expression characteristics could predict the survival and prognosis of patients with GBM and was significantly associated with immune infiltration levels and the expression of CD47 and CD24, which are immune checkpoints of the "don't eat me "signal. Furthermore, we found that the CDKN2A gene may predict GBM sensitivity and resistance to drugs.

Discussion

Our findings suggest that CRGs play a crucial role in GBM outcomes and provide new insights into CRG-related target drugs/molecules for cancer prevention and treatment.

Identification of cell death-related biomarkers and immune infiltration in ischemic stroke between male and female patients

Background

Stroke is the second leading cause of death and the third leading cause of disability worldwide, with ischemic stroke (IS) being the most prevalent. A substantial number of irreversible brain cell death occur in the short term, leading to impairment or death in IS. Limiting the loss of brain cells is the primary therapy target and a significant clinical issue for IS therapy. Our study aims to establish the gender specificity pattern from immune cell infiltration and four kinds of cell-death perspectives to improve IS diagnosis and therapy.

Methods

Combining and standardizing two IS datasets (GSE16561 and GSE22255) from the GEO database, we used the CIBERSORT algorithm to investigate and compare the immune cell infiltration in different groups and genders. Then, ferroptosis-related differently expressed genes (FRDEGs), pyroptosis-related DEGs (PRDEGs), anoikis-related DEGs (ARDEGs), and cuproptosis-related DEGs (CRDEGs) between the IS patient group and the healthy control group were identified in men and women, respectively. Machine learning (ML) was finally used to generate the disease prediction model for cell death-related DEGs (CDRDEGs) and to screen biomarkers related to cell death involved in IS.

Results

Significant changes were observed in 4 types of immune cells in male IS patients and 10 types in female IS patients compared with healthy controls. In total, 10 FRDEGs, 11 PRDEGs, 3 ARDEGs, and 1 CRDEG were present in male IS patients, while 6 FRDEGs, 16 PRDEGs, 4 ARDEGs, and 1 CRDEG existed in female IS patients. ML techniques indicated that the best diagnostic model for both male and female patients was the support vector machine (SVM) for CDRDEG genes. SVM's feature importance analysis demonstrated that SLC2A3, MMP9, C5AR1, ACSL1, and NLRP3 were the top five feature-important CDRDEGs in male IS patients. Meanwhile, the PDK4, SCL40A1, FAR1, CD163, and CD96 displayed their overwhelming influence on female IS patients.

Conclusion

These findings contribute to a better knowledge of immune cell infiltration and their corresponding molecular mechanisms of cell death and offer distinct clinically relevant biological targets for IS patients of different genders.

Evaluation of Radiosensitization and Cytokine Modulation by Differentially PEGylated Gold Nanoparticles in Glioblastoma Cells

Glioblastoma (GBM) is known as the most aggressive type of malignant brain tumour, with an extremely poor prognosis of approximately 12 months following standard-of-care treatment with surgical resection, radiotherapy (RT), and temozolomide treatment. Novel RT-drug combinations are urgently needed to improve patient outcomes. Gold nanoparticles (GNPs) have demonstrated significant preclinical potential as radiosensitizers due to their unique physicochemical properties and their ability to pass the blood-brain barrier. The modification of GNP surface coatings with poly(ethylene) glycol (PEG) confers several therapeutic advantages including immune avoidance and improved cellular localisation. This study aimed to characterise both the radiosensitizing and immunomodulatory properties of differentially PEGylated GNPs in GBM cells in vitro. Two GBM cell lines were used, U-87 MG and U-251 MG. The radiobiological response was evaluated by clonogenic assay, immunofluorescent staining of 53BP1 foci, and flow cytometry. Changes in the cytokine expression levels were quantified by cytokine arrays. PEGylation improved the radiobiological efficacy, with double-strand break induction being identified as an underlying mechanism. PEGylated GNPs also caused the greatest boost in RT immunogenicity, with radiosensitization correlating with a greater upregulation of inflammatory cytokines. These findings demonstrate the radiosensitizing and immunostimulatory potential of ID11 and ID12 as candidates for RT-drug combination in future GBM preclinical investigations.

IGFBP3 induced by the TGF-β/EGFRvIII transactivation contributes to the malignant phenotype of glioblastoma

Dual or multi-targets therapy targeting epidermal growth factor receptor variant III (EGFRvIII) and other molecular may relax the constraint for glioblastoma (GBM), putting forward the urgent requirement of finding candidate molecules. Here, the insulin-like growth factor binding protein-3 (IGFBP3) was considered a candidate, whereas the mechanisms of IGFBP3 production remain unclear. We treated GBM cells with exogenous transforming growth factor β (TGF-β) to simulate the microenvironment. We found that TGF-β and EGFRvIII transactivation induced the activation of transcription factor c-Jun, which specifically bound to the promoter region of IGFBP3 through Smad2/3 and ERK1/2 pathways and promoted the production and secretion of IGFBP3. IGFBP3 knockdown inhibited the activation of TGF-β and EGFRvIII signals and the malignant behaviors triggered by them in vitro and in vivo. Collectively, our results indicated a positive feedback loop of p-EGFRvIII/IGFBP3 under administration of TGF-β, blocking IGFBP3 may be an additional target in EGFRvIII-expressing GBM-selective therapeutic strategy.

Identification of INSRR as an immune-related gene in the tumor microenvironment of glioblastoma by integrated bioinformatics analysis

Gliomas are the most common malignant tumors in the central nervous system. The tumor microenvironment (TME) plays a crucial role in tumor proliferation, invasion, angiogenesis, and immune escape. However, little is known about TME in gliomas. The purpose of this study was to explore the biomarkers associated with TME in glioblastoma (GBM) to predict immunotherapy effectiveness and prognosis in patients. Based on RNA-seq transcriptome data and clinical features of 1222 samples (113 normal samples and 1109 tumor samples) in The Cancer Genome Atlas (TCGA) database, the ImmuneScore, StromalScore, and ESTIMATEScore were calculated by ESTIMATE algorithm. The differentially expressed genes (DEGs) and differentially mutated genes (DMGs) were determined in the TCGA GBM cohort. Furthermore, gene set enrichment analysis (GSEA) was used to investigate the enrichment pathways of INSRR genes with abnormal expression. The proportion of tumor-infiltrating immune cells (TIICs) was evaluated by CIBERSORT. Frequent mutations of TP53, EGFR, and PTEN occurred in high and low immune scores. The cross-analysis of DEGs and DMGs revealed that INSRR was an immune-related biomarker in the TCGA GBM cohort. According to GSEA, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway with INSRR abnormal expression were IgA-produced intestinal immune network and Alzheimer's disease, oxidative phosphorylation, and Parkinson's disease, respectively. Additionally, INSRR expression was correlated with dendritic cells activated, dendritic cells resting, T cells CD8, and T cell gamma delta. INSRR is associated with the immune microenvironment in GBM and is used as a biomarker to predict immune invasion.

The PTEN-associated immune prognostic signature reveals the landscape of the tumor microenvironment in glioblastoma

Glioblastoma (GBM) is a common brain tumor with a complex and diverse tumor microenvironment (TME). As PTEN mutation is the most common mutation in GBM, we aimed to investigate how PTEN mutation regulates the immune response in GBM TME and thus affects the prognosis of GBM patients. In this study, we conducted a comprehensive analysis of multiple levels of data, including whole-exome sequencing (WES), transcriptome RNA sequencing, patient survival and immune signatures, to study the relationship between PTEN mutation and TME in GBM. We developed an immune-related prognostic signature (IPS) based on the PTEN-associated immune-related genes (IRGs), and the IPS exhibited a powerful prognosis prediction capacity in different GBM cohorts. A scoring nomogram based on the IPS was also established for clinical application. In addition, the correlations of the IPS with tumor immune cell infiltration and immune checkpoints were systematically analyzed. This study illustrates the influence of PTEN mutation on the immune microenvironment of GBM. Our IPS, which is sensitive to PTEN mutation status, can enhance the prognosis prediction ability for GBM patients and provides potential targets for immunotherapy.

Glioma-associated microglia/macrophages (GAMs) in glioblastoma: Immune function in the tumor microenvironment and implications for immunotherapy

Glioma is a mixed solid tumor composed of neoplastic and non-neoplastic components. Glioma-associated macrophages and microglia (GAMs) are crucial elements of the glioma tumor microenvironment (TME), regulating tumor growth, invasion, and recurrence. GAMs are also profoundly influenced by glioma cells. Recent studies have revealed the intricate relationship between TME and GAMs. In this updated review, we provide an overview of the interaction between glioma TME and GAMs based on previous studies. We also summarize a series of immunotherapies targeting GAMs, including clinical trials and preclinical studies. Specifically, we discuss the origin of microglia in the central nervous system and the recruitment of GAMs in the glioma background. We also cover the mechanisms through which GAMs regulate various processes associated with glioma development, such as invasiveness, angiogenesis, immunosuppression, recurrence, etc. Overall, GAMs play a significant role in the tumor biology of glioma, and a better understanding of the interaction between GAMs and glioma could catalyze the development of new and effective immunotherapies for this deadly malignancy.

Nucleotide-Binding Oligomerization Domain (NOD)-Like Receptor Subfamily C (NLRC) as a Prognostic Biomarker for Glioblastoma Multiforme Linked to Tumor Microenvironment: A Bioinformatics, Immunohistochemistry, and Machine Learning-Based Study

Purpose

Glioblastoma multiforme (GBM) remains the deadliest primary brain tumor. We aimed to illuminate the role of nucleotide-binding oligomerization domain (NOD)-like receptor subfamily C (NLRC) in GBM.

Patients and Methods

Based on public database data (mainly The Cancer Genome Atlas [TCGA]), we performed bioinformatics analysis to visually evaluate the role and mechanism of NLRCs in GBM. Then, we validated our findings in a glioma tissue microarray (TMA) by immunohistochemistry (IHC), and the prognostic value of NOD1 was assessed via random forest (RF) models.

Results

In GBM tissues, the expression of NLRC members was significantly increased, which was related to the low survival rate of GBM. Additionally, Cox regression analysis revealed that the expression of NOD1 (among NLRCs) served as an independent prognostic marker. A nomogram based on multivariate analysis proved the effective predictive performance of NOD1 in GBM. Enrichment analysis showed that high expression of NOD1 could regulate extracellular structure, cell adhesion, and immune response to promote tumor progression. Then, immune infiltration analysis showed that NOD1 overexpression correlated with an enhanced immune response. Then, in a glioma TMA, the results of IHC revealed that the increase in NOD1 expression indicated high recurrence and poor prognosis of human glioma. Furthermore, the expression level of NOD1 showed good prognostic value in the TMA cohort via RF.

Conclusion

The value of NOD1 as a biomarker for GBM was demonstrated. The possible mechanisms may lie in the regulatory role of NLRC-related pathways in the tumor microenvironment.

CD4+ conventional T cells-related genes signature is a prognostic indicator for ovarian cancer

Introduction

It is believed that ovarian cancer (OC) is the most deadly form of gynecological cancer despite its infrequent occurrence, which makes it one of the most salient public health concerns. Clinical and preclinical studies have revealed that intratumoral CD4+ T cells possess cytotoxic capabilities and were capable of directly killing cancer cells. This study aimed to identify the CD4+ conventional T cells-related genes (CD4TGs) with respect to the prognosis in OC.

Methods

We obtained the transcriptome and clinical data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. CD4TGs were first identified from single-cell datasets, then univariate Cox regression was used to screen prognosis-related genes, LASSO was conducted to remove genes with coefficient zero, and multivariate Cox regression was used to calculate riskscore and to construct the CD4TGs risk signature. Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, time-dependent receiver operating characteristics (ROC), decision curve analysis (DCA), nomogram, and calibration were made to verify and evaluate the risk signature. Gene set enrichment analyses (GSEA) in risk groups were conducted to explore the tightly correlated pathways with the risk group. The role of riskscore has been further explored in the tumor microenvironment (TME), immunotherapy, and chemotherapy. A risk signature with 11 CD4TGs in OC was finally established in the TCGA database and furtherly validated in several GEO cohorts.

Results

High riskscore was significantly associated with a poorer prognosis and proven to be an independent prognostic biomarker by multivariate Cox regression. The 1-, 3-, and 5-year ROC values, DCA curve, nomogram, and calibration results confirmed the excellent prediction power of this model. Compared with the reported risk models, our model showed better performance. The patients were grouped into high-risk and low-risk subgroups according to the riskscore by the median value. The low-risk group patients tended to exhibit a higher immune infiltration, immune-related gene expression and were more sensitive to immunotherapy and chemotherapy.

Discussion

Collectively, our findings of the prognostic value of CD4TGs in prognosis and immune response, provided valuable insights into the molecular mechanisms and clinical management of OC.

Prognosis-correlated Systems Involving Characteristic Diagnostic Gene Sets for Survival Analysis on Glioma

As the most prevalent brain tumor, glioma is malignant with poor prognostic outcomes. As a result, it is of great importance to detect biomarkers for glioma diagnosis and prognosis. In this study, we determined grade-based characteristic gene clusters with gradual expression following grade change, including 1479 down- and 526 up-regulated genes. Combined interaction among proteins originating from these genes was analyzed, and hub genes were exhibited after GSEA enrichment, containing 12 and 11 genes which were correlated with prognostic outcomes, named as unfavorable and favorable gene sets, respectively. The GSVA score of each gene set was calculated and divided into high/low groups; we observed that cases in the low score group had better outcomes than the high score group based on the GSVA of the unfavorable set, while with favorable GSVA score, the low group had poorer outcomes than the high group. Eventually, we compared a variety of infiltrating immune cells between low/high GSVA subgroup, showing various immune cell types (B cell naive, activated mast cells, resting CD4 memory T cell, and so on) with opposite proportion. And interestingly, these cell types also accounted for a contrary percentage between unfavorable and favorable conditions. In conclusion, these two hub gene sets are of good importance as an evaluation system for clinical grade classification and prognosis prediction.

Exploring the Correlation of Abnormal CXCL9 Expression with Immune Infiltration in Glioma and Patient Prognosis Based on TCGA and GTEx Databases

In this study, we intend to identify key immune-related genes (IRGs) in gliomas using the TCGA and GTEx databases. Following collection of the RNA-seq data of lower-grade glioma (LGG) and glioblastoma (GBM) patients from the TCGA and GTEx databases, the differentially expressed IRGs (DE-IRGs) were screened. The ESTIMATE algorithm was utilized to evaluate StromalScore and ImmuneScore of LGG and GBM samples and a multifactorial Cox risk model was constructed to identify the related risk genes. The core IRGs of LGG and GBM were screened through a PPI network, followed by exploration of their correlation with glioma prognosis. The relationship between IRGs and immune cells in LGG and GBM was detected. In vitro assays were performed to detect the effect of CXCL9 on glioma cell development. We screened 403 and 492 DE-IRGs in LGG and GBM. StromalScore and ImmuneScore were related to overall survival in LGG, but not in GBM. CXCL9 was identified as a core gene in LGG and GBM and shared association with the prognosis of gliomas. Furthermore, a correlation was found between CXCL9 and immune infiltration of LGG and GBM. Glioma cell proliferation and invasion could be inhibited by silencing of CXCL9. Overall, CXCL9 is correlated to the prognosis of glioma patients and may accelerate glioma development via immune regulation.

Machine learning-based identification of SOX10 as an immune regulator of macrophage in gliomas

Gliomas, originating from the glial cells, are the most lethal type of primary tumors in the central nervous system. Standard treatments like surgery have not significantly improved the prognosis of glioblastoma patients. Recently, immune therapy has become a novel and effective option. As a conserved group of transcriptional regulators, the Sry-type HMG box (SOX) family has been proved to have a correlation with numerous diseases. Based on the large-scale machine learning, we found that the SOX family, with significant immune characteristics and genomic profiles, can be divided into two distinct clusters in gliomas, among which SOX10 was identified as an excellent immune regulator of macrophage in gliomas. The high expression of SOX10 is related to a shorter OS in LGG, HGG, and pan-cancer groups but benefited from the immunotherapy. It turned out in single-cell sequencing that SOX10 is high in neurons, M1 macrophages, and neural stem cells. Also, macrophages are found to be elevated in the SOX10 high-expression group. SOX10 has a positive correlation with macrophage cytokine production and negative regulation of macrophages' chemotaxis and migration. In conclusion, our study demonstrates the outstanding cluster ability of the SOX family, indicating that SOX10 is an immune regulator of macrophage in gliomas, which can be an effective target for glioma immunotherapy.

The immunosuppressive microenvironment and immunotherapy in human glioblastoma

Glioblastoma multiforme (GBM) is the most malignant intracranial tumor in adults, characterized by extensive infiltrative growth, high vascularization, and resistance to multiple therapeutic approaches. Among the many factors affecting the therapeutic effect, the immunosuppressive GBM microenvironment that is created by cells and associated molecules via complex mechanisms plays a particularly important role in facilitating evasion of the tumor from the immune response. Accumulating evidence is also revealing a close association of the gut microbiota with the challenges in the treatment of GBM. The gut microbiota establishes a connection with the central nervous system through bidirectional signals of the gut-brain axis, thus affecting the occurrence and development of GBM. In this review, we discuss the key immunosuppressive components in the tumor microenvironment, along with the regulatory mechanism of the gut microbiota involved in immunity and metabolism in the GBM microenvironment. Lastly, we concentrate on the immunotherapeutic strategies currently under investigation, which hold promise to overcome the hurdles of the immunosuppressive tumor microenvironment and improve the therapeutic outcome for patients with GBM.

The CNS mononuclear phagocyte system in health and disease

CNS-resident macrophages-including parenchymal microglia and border-associated macrophages (BAMs)-contribute to neuronal development and health, vascularization, and tissue integrity at steady state. Border-patrolling mononuclear phagocytes such as dendritic cells and monocytes confer important immune functions to the CNS, protecting it from pathogenic threats including aberrant cell growth and brain malignancies. Even though we have learned much about the contribution of lymphocytes to CNS pathologies, a better understanding of differential roles of tissue-resident and -invading phagocytes is slowly emerging. In this perspective, we propose that in CNS neuroinflammatory diseases, tissue-resident macrophages (TRMs) contribute to the clearing of debris and resolution of inflammation, whereas blood-borne phagocytes are drivers of immunopathology. We discuss the remaining challenges to resolve which specialized mononuclear phagocyte populations are driving or suppressing immune effector function, thereby potentially dictating the outcome of autoimmunity or brain cancer.

Integration of single-cell RNA sequencing and spatial transcriptomics to reveal the glioblastoma heterogeneity

Glioblastoma (GBM), a deadly brain tumor, is still one of a few lasting challenges of contemporary oncology. Current therapies fail to significantly improve patient survival due to GBM tremendous genetic, transcriptomic, immunological, and sex-dependent heterogeneity. Over the years, clinical differences between males and females were characterized. For instance, higher incidence of GBM in males or distinct responses to cancer chemotherapy and immunotherapy between males and females have been noted. Despite the introduction of single-cell RNA sequencing and spatial transcriptomics, these differences were not further investigated as studies were focused only on revealing the general picture of GBM heterogeneity. Hence, in this mini-review, we summarized the current state of knowledge on GBM heterogeneity revealed by single-cell RNA sequencing and spatial transcriptomics with regard to genetics, immunology, and sex-dependent differences. Additionally, we highlighted future research directions which would fill the gap of knowledge on the impact of patient's sex on the disease outcome.

Integration of single-cell RNA sequencing and spatial transcriptomics to reveal the glioblastoma heterogeneity

Glioblastoma (GBM), a deadly brain tumor, is still one of the few lasting challenges of contemporary oncology. Current therapies fail to significantly improve patient survival due to GBM's tremendous genetic, transcriptomic, immunological, and sex-dependent heterogeneity. Over the years, clinical differences between males and females were characterized. For instance, higher incidence of GBM in males or distinct responses to cancer chemotherapy and immunotherapy between males and females have been noted. However, despite the introduction of single-cell RNA sequencing and spatial transcriptomics, these differences were not further investigated as studies were focused only on exposing the general picture of GBM heterogeneity. Hence, in this study, we summarized the current state of knowledge on GBM heterogeneity exposed by single-cell RNA sequencing and spatial transcriptomics with regard to genetics, immunology, and sex-dependent differences. Additionally, we highlighted future research directions which would fill the gap of knowledge on the impact of patient's sex on the disease outcome.

Comprehensive analyses of a tumor-infiltrating lymphocytes-related gene signature regarding the prognosis and immunologic features for immunotherapy in bladder cancer on the basis of WGCNA

Tumor-infiltrating lymphocyte (TIL) is a class of cells with important immune functions and plays a crucial role in bladder cancer (BCa). Several studies have shown the clinical significance of TIL in predicting the prognosis and immunotherapy efficacy. TIL-related gene module was screened utilizing weighted gene coexpression network analysis. We screened eight TIL-related genes utilizing univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) Cox regression analysis, and multivariate Cox regression analysis. Then, we established a TIL-related signature model containing the eight selected genes and subsequently classified all patients into two groups, that is, the high-risk as well as low-risk groups. Gene mutation status, prognosis, immune cell infiltration, immune subtypes, TME, clinical features, and immunotherapy response were assessed among different risk subgroups. The results affirmed that the TIL-related signature model was a reliable predictor of overall survival (OS) for BCa and was determined as an independent risk factor for BCa patients in two cohorts. Moreover, the risk score was substantially linked to age, tumor staging, TNM stage, and pathological grade. And there were different mutational profiles, biological pathways, immune scores, stromal scores, and immune cell infiltration in the tumor microenvironment (TME) between the two risk groups. In particular, immune checkpoint genes’ expression was remarkably different between the two risk groups, with patients belonging to the low-risk group responding better to immune checkpoint inhibition (ICI) therapy. In conclusion, our study demonstrates that the TIL-related model was a reliable signature in anticipating prognosis, immune status, and immunotherapy response, which can help in screening patients who respond to immunotherapy.

The prognostic value of the preoperative inflammatory index on the survival of glioblastoma patients

OBJECTIVES

The growth and development of tumors are closely related to the initiation and amplification of the inflammatory response. Various inflammatory biomarkers had attained growing attention for nearly two decades and were discovered strongly associated with cancer patients' prognosis, indicating that systemic inflammatory response is possibly essential to cancer progression. However, little was known about the sensitive biomarkers associated with the detection, persistence, treatment, and prognosis of GBM. Hence, the retrospective research endeavored to evaluate the prognostic value of preoperative inflammatory biomarkers in patients with GBM who initially received standardized treatment.

METHODS

The 232 glioblastoma patients eligible who were admitted to Qilu Hospitals in Shandong Province from January 2014 to January 2018 were collected for this analysis. Inflammatory markers, including the systemic immune-inflammation index (SII), systemic immune response index (SIRI), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), monocyte-lymphocyte ratio (MLR), and albumin/globulin ratio (AGR), were designed. Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method, and we calculated the area under the ROC curve to determine the AUC value. Besides, we used the Cox proportional hazard model to estimate the relationship between variables and PFS and OS. The statistical differences between variables and PFS and OS were tested through the log-rank test. What is more, the LR method was used to perform Cox multiple regression analysis. The results were represented by hazard ratio (HR), 95% CI, any 2-tailed P < 0.01 was accepted as statistically different.

RESULTS

The multivariate Cox proportional hazard model presented that SII ≥ 659.1 was an independent risk factor affecting OS (HR = 2.238, 95% CI = 1.471-3.406, P < 0.001) and postoperative PFS (HR = 2.000, 95% CI = 1.472-2.716, P < 0.001) in GBM patients. The 1-, 3-, and 5-year OS of the SII < 659.1 group was 70.8%, 26.9%, and 14.1%, respectively, while the 1- and 3-year OS of the SII ≥ 659.1 group was 37.5% and 11.5% (P < 0.001). The 1-, 3-, and 5-year PFS of the SII < 659.1 group was 36.3%, 19.6%, and 13%, respectively, while the 1-year PFS of the SII ≥ 659.1 group was 11.3% (P < 0.001). Results of patients' clinical and pathological characteristics paraded that in comparison to the lower SII group, the higher SII group had significantly inferior Karnofsky Performance Scale (KPS) scores (P < 0.001) and more frequent cystic changes of the tumors (P < 0.001), whereas the values of SIRI, NLR, PLR, MLR, and AGR were low.

CONCLUSIONS

SII is an independent inflammatory indicator for predicting the prognosis of GBM patients after receiving initially standardized treatments.

Quaking but not parkin is the major tumor suppressor in 6q deleted region in glioblastoma

Glioblastoma (GBM) is a high-grade, aggressive brain tumor with dismal median survival time of 15 months. Chromosome 6q (Ch6q) is a hotspot of genomic alterations, which is commonly deleted or hyper-methylated in GBM. Two neighboring genes in this region, QKI and PRKN have been appointed as tumor suppressors in GBM. While a genetically modified mouse model (GEMM) of GBM has been successfully generated with Qk deletion in the central nervous system (CNS), in vivo genetic evidence supporting the tumor suppressor function of Prkn has not been established. In the present study, we generated a mouse model with Prkn-null allele and conditional Trp53 and Pten deletions in the neural stem cells (NSCs) and compared the tumorigenicity of this model to our previous GBM model with Qk deletion within the same system. We find that Qk but not Prkn is the potent tumor suppressor in the frequently altered Ch6q region in GBM.

Identification of personalized neoantigen-based vaccines and immune subtype characteristic analysis of glioblastoma based on abnormal alternative splicing

The development of personalized neoantigen-based vaccines in cancer immunotherapy has shown promise. In this study, a large-scale bioinformatics analysis was performed to identify potential GBM-associated neoantigens based on abnormal alternative splicing, and then screen suitable patients for vaccination. Gene expression profiles and clinical information were collected from TCGA. We filtered the percent-spliced-in (PSI) spectrum of alternative splicing events in the dataset to identify abnormal alternative splicing events. MAF package was used to identify and analyse tumour mutation burden (TMB) in cancer samples. Tumour Immune Estimation Resource (TIMER) was used to calculate and visualize the infiltration of antigen presenting cells (APCs). In addition, consistent clustering algorithm utilized to identify immune subtypes of GBM. Five potential tumour neoantigens (LRP1, TCF12, DERL3, WIPI2, and TSHZ3) were identified in GBM by selecting genes both with abnormal alternative splicing (upregulated) and gene frameshift mutations, in which LRP1 was significantly associated with APCs. According to the expressions of five potential tumour neoantigens, 160 patients with GBM were divided into three immune subtypes. Patients in cluster3 exhibited good prognoses. Furthermore, the characteristics, including TMB, abnormal alternative splicing events, immune activity, immune cells proportion, and association with tumour biomarkers, were unique in each immune subtypes. The characteristics of cluster3 illustrated that cluster3 participants were more suitable candidates for vaccination. LRP1 was identified as a potential neoantigen for immunotherapy against GBM, and patients in cluster3 were more suitable for vaccination. Our findings provide important guidance for the development of novel neoantigens and therapeutic targets in patients with GBM.

C1R, CCL2, and TNFRSF1A Genes in Coronavirus Disease-COVID-19 Pathway Serve as Novel Molecular Biomarkers of GBM Prognosis and Immune Infiltration

Glioblastoma multiforme (GBM) is a prevalent intracranial brain tumor associated with a high rate of recurrence and treatment difficulty. The prediction of novel molecular biomarkers through bioinformatics analysis may provide new clues into early detection and eventual treatment of GBM. Here, we used data from the GTEx and TCGA databases to identify 1923 differentially expressed genes (DEGs). GO and KEGG analyses indicated that DEGs were significantly enriched in immune response and coronavirus disease-COVID-19 pathways. Survival analyses revealed a significant correlation between high expression of C1R, CCL2, and TNFRSF1A in the coronavirus disease-COVID-19 pathway and the poor survival in GBM patients. Cell experiments indicated that the mRNA expression levels of C1R, CCL2, and TNFRSF1A in GBM cells were very high. Immune infiltration analysis revealed a significant difference in the proportion of immune cells in tumor and normal tissue, and the expression levels of C1R, CCL2, and TNFRSF1A were associated with immune cell infiltration of GBM. Additionally, the protein-protein interaction networks of C1R, CCL2, and TNFRSF1A involved a total of 65 nodes and 615 edges. These results suggest that C1R, CCL2, and TNFRSF1A may be used as molecular biomarkers of prognosis and immune infiltration in GBM patients in the future.

TRP Family Genes Are Differently Expressed and Correlated with Immune Response in Glioma

(1) Background: glioma is the most prevalent primary tumor of the human central nervous system and accompanies extremely poor prognosis in patients. The transient receptor potential (TRP) channels family consists of six different families, which are closely associated with cancer cell proliferation, differentiation, migration, and invasion. TRP family genes play an essential role in the development of tumors. Nevertheless, the function of these genes in gliomas is not fully understood. (2) Methods: we analyze the gene expression data of 28 TRP family genes in glioma patients through bioinformatic analysis. (3) Results: the study showed the aberrations of TRP family genes were correlated to prognosis in glioma. Then, we set enrichment analysis and selected 10 hub genes that may play an important role in glioma. Meanwhile, the expression of 10 hub genes was further established according to different grades, survival time, IDH mutation status, and 1p/19q codeletion status. We found that TRPC1, TRPC3, TRPC4, TRPC5, TRPC6, MCOLN1, MCOLN2, and MCOLN3 were significantly correlated to the prognosis in glioma patients. Furthermore, we illustrated that the expression of hub genes was associated with immune activation and immunoregulators (immunoinhibitors, immunostimulators, and MHC molecules) in glioma. (4) Conclusions: we proved that TRP family genes are promising immunotherapeutic targets and potential clinical biomarkers in patients with glioma.

An Integrated Immune-Related Bioinformatics Analysis in Glioma: Prognostic Signature’s Identification and Multi-Omics Mechanisms’ Exploration

As the traditional treatment for glioma, the most common central nervous system malignancy with poor prognosis, the efficacy of high-intensity surgery combined with radiotherapy and chemotherapy is not satisfactory. The development of individualized scientific treatment strategy urgently requires the guidance of signature with clinical predictive value. In this study, five prognosis-related differentially expressed immune-related genes (PR-DE-IRGs) (CCNA2, HMGB2, CASP3, APOBEC3C, and BMP2) highly associated with glioma were identified for a prognostic model through weighted gene co-expression network analysis, univariate Cox and lasso regression. Kaplan-Meier survival curves, receiver operating characteristic curves and other methods have shown that the model has good performance in predicting the glioma patients’ prognosis. Further combined nomogram provided better predictive performance. The signature’s guiding value in clinical treatment has also been verified by multiple analysis results. We also constructed a comprehensive competing endogenous RNA (ceRNA) regulatory network based on the protective factor BMP2 to further explore its potential role in glioma progression. Numerous immune-related biological functions and pathways were enriched in a high-risk population. Further multi-omics integrative analysis revealed a strong correlation between tumor immunosuppressive environment/IDH1 mutation and signature, suggesting that their cooperation plays an important role in glioma progression.

The meningeal lymphatic vasculature in neuroinflammation

The lymphatic vasculature is a unidirectional network of lymphatic endothelial cells, whose main role is to maintain fluid homeostasis along with the absorption of dietary fat in the gastrointestinal organs and management and coordination of immune cell trafficking into lymph nodes during homeostasis and under inflammatory conditions. In homeostatic conditions, immune cells, such as dendritic cells, macrophages, or T cells can enter into the lymphatic vasculature and move easily through the lymph reaching secondary lymph nodes where immune cell activation or peripheral tolerance can be modulated. However, under inflammatory conditions such as pathogen infection, increased permeabilization of lymphatic vessels allows faster immune cell migration into inflamed tissues following a chemokine gradient, facilitating pathogen clearance and the resolution of inflammation. Interestingly, since the re-discovery of lymphatic vasculature in the central nervous system, known as the meningeal lymphatic vasculature, the role of these lymphatics as a key player in several neurological disorders has been described, with emphasis on the neurodegenerative process. Alternatively, less has been discussed about meningeal lymphatics and its role in neuroinflammation. In this review, we discuss current knowledge about the anatomy and function of the meningeal lymphatic vasculature and specifically analyze its contribution to different neuroinflammatory processes, highlighting the potential therapeutic target of meningeal lymphatic vasculature in these pathological conditions.

Construction of Molecular Subtypes and Related Prognostic and Immune Response Models Based on M2 Macrophages in Glioblastoma

OBJECTIVES

To identify the molecular subtypes of glioblastoma multiforme (GBM) related to M2 macrophage-based prognostic genes, then to preliminarily explore their biological functions and construct immunotherapy response gene models.

MATERIAL AND METHODS

We used R language to analyze GBM microarray data, and other tools, including xCell and CIBERSORTx, to identify subtypes of GBM that related to M2 macrophages. The process started with the exploration of biological functions of the two subtypes by pathway analyses and GSEA, and continued with a combined procedure of constructing an M2 macrophage-related prognostic gene model and exploring the immune treatment response for GBM.

RESULTS

A high abundance of M2 macrophages in GBM was associated with poor prognosis. According to M2 macrophage-related prognostic genes, GBM was divided into two subtypes (cluster A and cluster B). The differential gene enrichment analysis of the two clusters showed that cluster A was less enriched in M2 macrophages and had immunopotential. The M2score, which was constructed based on M2 macrophage-related prognostic genes, was not only related to the survival and prognosis of patients with GBM, but also predictive of the effectiveness of immunotherapy in these patients. This result has been effectively verified in an external data set.

CONCLUSION

GBM was successfully divided into two subtypes according to M2-macrophage-related prognostic genes. In GBM, a high M2score may indicate better clinical outcome and enhancement of the immunotherapy response.

Mediator Complex Subunit 19 Promotes the Development of Hepatocellular Carcinoma by Regulating the AKT/mTOR Signaling Pathway

Background

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors, the pathogenesis of which remains unclear. Mediator complex subunit 19 (MED19), a subunit of the Mediator complex, is a multi-protein co-activator necessary for DNA transcription factors to induce RNA polymerase II transcription. In the current study, we aimed to study the role of MED19 in HCC and elucidate its mechanism.

Methods

MED19 expression in HCC tissues was determined. The relationship between MED19 and the clinical prognosis was explored. The influence of MED19 on HCC cell viability, migration, invasion, and apoptosis was studied. The expression of AKT/mTOR pathway genes and proteins was detected by qRT-PCR and western blot. The correlation between MED19 and immune infiltration was investigated.

Results

MED19 was upregulated in HCC tissues compared with tumor-adjacent tissues, and was associated with a poor prognosis. Furthermore, high MED19 expression was correlated with race, gender, etc. Knockdown of MED19 inhibited cell proliferation, migration, invasion, and promoted apoptosis. Knockdown of MED19 decreased p-AKT and p-mTOR protein expression. Additionally, the downstream effectors of the AKT/mTOR pathway, p70S6K1 and 4EBP1, were affected by MED19. Notably, MED19 expression was positively correlated with the infiltration levels of B cells, CD4⁺ T cells, CD8⁺ T cells, macrophages, etc.

Conclusion

MED19 is significantly upregulated in HCC tissues and cells. MED19 may promote the progression of HCC in vitro and may be related to immune infiltration. Together, our data show that MED19 could be considered as a new possible biomarker as well as a novel therapeutic target for HCC.

Epigenetic Drugs and Their Immune Modulating Potential in Cancers

Epigenetic drugs are used for the clinical treatment of hematologic malignancies; however, their therapeutic potential in solid tumors is still under investigation. Current evidence suggests that epigenetic drugs may lead to antitumor immunity by increasing antigen presentation and may enhance the therapeutic effect of immune checkpoint inhibitors. Here, we highlight their impact on the tumor epigenome and discuss the recent evidence that epigenetic agents may optimize the immune microenvironment and promote antiviral response.

HNRNPC, a predictor of prognosis and immunotherapy response based on bioinformatics analysis, is related to proliferation and invasion of NSCLC cells

BACKGROUND

Little is known about the relationship between N6-methyladenosine (m6A)-related genes and tumor immune microenvironment (TIME) in non-small cell lung cancer (NSCLC). It is unclear which m6A regulators are essential for NSCLC progression. The aim of this work was to excavate the role of m6A-related genes in the TIME and progression of NSCLC.

METHODS

Based on bioinformatics analysis, heterogeneous nuclear ribonucleoprotein C (HNRNPC) was considered as the most influential m6A regulator. Further study was investigated using patient samples, stable cell lines, and xenograft mice models.

RESULTS

The differentially expressed profiles of m6A-related genes were established in NSCLC, and the NSCLC samples were clustered into two subtypes with different immune infiltration and survival time. Next, we found that the risk score (RS) based on m6A-related genes was a predictor of prognosis and immunotherapy response for NSCLC, in which HNRNPC was considered as the most influential m6A regulator. In NSCLC patients, we confirmed that HNRNPC predicted poor prognosis and correlated with tumor invasion and lymph node metastasis. RNA-seq data revealed that HNRNPC was involved in cell growth, cell migration, extracellular matrix organization and angiogenesis. In vitro, we verified that HNRNPC knockdown attenuated the cell proliferation, clonogenicity, invasion and migration. In vivo, HNRNPC knockdown inhibited the tumor growth and lung metastasis. Additionally, HNRNPC knockdown was associated with high CD8 + T cell infiltration, along with elevated CD4 + T cell infiltration, collagen production and angiogenesis.

CONCLUSIONS

M6A regulator HNRNPC, a predictor of prognosis and immunotherapy response based on bioinformatics analysis, is related to proliferation and invasion of NSCLC cells.

Comprehensive analysis identifies IFI16 as a novel signature associated with overall survival and immune infiltration of skin cutaneous melanoma

Background

Skin cutaneous melanoma (SKCM) is the most common skin tumor with high mortality. The unfavorable outcome of SKCM urges the discovery of prognostic biomarkers for accurate therapy. The present study aimed to explore novel prognosis-related signatures of SKCM and determine the significance of immune cell infiltration in this pathology.

Methods

Four gene expression profiles (GSE130244, GSE3189, GSE7553 and GSE46517) of SKCM and normal skin samples were retrieved from the GEO database. Differentially expressed genes (DEGs) were then screened, and the feature genes were identified by the LASSO regression and Boruta algorithm. Survival analysis was performed to filter the potential prognostic signature, and GEPIA was used for preliminary validation. The area under the receiver operating characteristic curve (AUC) was obtained to evaluate discriminatory ability. The Gene Set Variation Analysis (GSVA) was performed, and the composition of the immune cell infiltration in SKCM was estimated using CIBERSORT. At last, paraffin-embedded specimens of primary SKCM and normal skin tissues were collected, and the signature was validated by fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC).

Results

Totally 823 DEGs and 16 feature genes were screened. IFI16 was identified as the signature associated with overall survival of SKCM with a great discriminatory ability (AUC > 0.9 for all datasets). GSVA noticed that IFI16 might be involved in apoptosis and ultraviolet response in SKCM, and immune cell infiltration of IFI16 was evaluated. At last, FISH and IHC both validated the differential expression of IFI16 in SKCM.

Conclusions

In conclusion, our comprehensive analysis identified IFI16 as a signature associated with overall survival and immune infiltration of SKCM, which may play a critical role in the occurrence and development of SKCM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02409-6.

Glioma: molecular signature and crossroads with tumor microenvironment

In patients with glioblastoma, the average survival time with current treatments is short, mainly due to recurrences and resistance to therapy. This insufficient treatment success is, in large parts, due to the tremendous molecular heterogeneity of gliomas, which affects the overall prognosis and response to therapies and plays a vital role in gliomas’ grading. In addition, the tumor microenvironment is a major player for glioma development and resistance to therapy. Active communication between glioma cells and local or neighboring healthy cells and the immune environment promotes the cancerogenic processes and contributes to establishing glioma stem cells, which drives therapy resistance. Besides genetic alterations in the primary tumor, tumor-released factors, cytokines, proteins, extracellular vesicles, and environmental influences like hypoxia provide tumor cells the ability to evade host tumor surveillance machinery and promote disease progression. Moreover, there is increasing evidence that these players affect the molecular biological properties of gliomas and enable inter-cell communication that supports pro-cancerogenic cell properties. Identifying and characterizing these complex mechanisms are inevitably necessary to adapt therapeutic strategies and to develop novel measures. Here we provide an update about these junctions where constant traffic of biomolecules adds complexity in the management of glioblastoma.

A Systematic Review of the Tumor-Infiltrating CD8+ T-Cells/PD-L1 Axis in High-Grade Glial Tumors: Toward Personalized Immuno-Oncology

Based on preclinical findings, programmed death-ligand 1 (PD-L1) can substantially attenuate CD8⁺ T-cell-mediated anti-tumoral immune responses. However, clinical studies have reported controversial results regarding the significance of the tumor-infiltrating CD8⁺ T-cells/PD-L1 axis on the clinical picture and the response rate of patients with high-grade glial tumors to anti-cancer therapies. Herein, we conducted a systematic review according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statements to clarify the clinical significance of the tumor-infiltrating CD8⁺ T-cells/PD-L1 axis and elucidate the impact of this axis on the response rate of affected patients to anti-cancer therapies. Indeed, a better understanding of the impact of this axis on the response rate of affected patients to anti-cancer therapies can provide valuable insights to address the futile response rate of immune checkpoint inhibitors in patients with high-grade glial tumors. For this purpose, we systematically searched Scopus, Web of Science, Embase, and PubMed to obtain peer-reviewed studies published before 1 January 2021. We have observed that PD-L1 overexpression can be associated with the inferior prognosis of glioblastoma patients who have not been exposed to chemo-radiotherapy. Besides, exposure to anti-cancer therapies, e.g., chemo-radiotherapy, can up-regulate inhibitory immune checkpoint molecules in tumor-infiltrating CD8⁺ T-cells. Therefore, unlike unexposed patients, increased tumor-infiltrating CD8⁺ T-cells in anti-cancer therapy-exposed tumoral tissues can be associated with the inferior prognosis of affected patients. Because various inhibitory immune checkpoints can regulate anti-tumoral immune responses, the single-cell sequencing of the cells residing in the tumor microenvironment can provide valuable insights into the expression patterns of inhibitory immune checkpoints in the tumor micromovement. Thus, administrating immune checkpoint inhibitors based on the data from the single-cell sequencing of these cells can increase patients’ response rates, decrease the risk of immune-related adverse events development, prevent immune-resistance development, and reduce the risk of tumor recurrence.

Prognostic Gene Expression Signature in Patients With Distinct Glioma Grades

Background

Glioma is the most common type of primary brain tumor in adults. Patients with the most malignant form have an overall survival time of <16 months. Although considerable progress has been made in defining the adapted therapeutic strategies, measures to counteract tumor escape have not kept pace, due to the developed resistance of malignant glioma. In fact, identifying the nature and role of distinct tumor-infiltrating immune cells in glioma patients would decipher potential mechanisms behind therapy failure.

Methods

We integrated into our study glioma transcriptomic datasets from the Cancer Genome Atlas (TCGA) cohort (154 GBM and 516 LGG patients). LM22 immune signature was built using CIBERSORT. Hierarchical clustering and UMAP dimensional reduction algorithms were applied to identify clusters among glioma patients either in an unsupervised or supervised way. Furthermore, differential gene expression (DGE) has been performed to unravel the top expressed genes among the identified clusters. Besides, we used the least absolute shrinkage and selection operator (LASSO) and Cox regression algorithm to set up the most valuable prognostic factor.

Results

Our study revealed, following gene enrichment analysis, the presence of two distinct groups of patients. The first group, defined as cluster 1, was characterized by the presence of immune cells known to exert efficient antitumoral immune response and was associated with better patient survival, whereas the second group, cluster 2, which exhibited a poor survival, was enriched with cells and molecules, known to set an immunosuppressive pro-tumoral microenvironment. Interestingly, we revealed that gene expression signatures were also consistent with each immune cluster function. A strong presence of activated NK cells was revealed in cluster 1. In contrast, potent immunosuppressive components such as regulatory T cells, neutrophils, and M0/M1/M2 macrophages were detected in cluster 2, where, in addition, inhibitory immune checkpoints, such as PD-1, CTLA-4, and TIM-3, were also significantly upregulated. Finally, Cox regression analysis further corroborated that tumor-infiltrating cells from cluster 2 exerted a significant impact on patient prognosis.

Conclusion

Our work brings to light the tight implication of immune components on glioma patient prognosis. This would contribute to potentially developing better immune-based therapeutic approaches.

High expression of PYCARD is an independent predictor of unfavorable prognosis and chemotherapy resistance in glioma

Background

PYD and CARD domain-containing (PYCARD) was upregulated in TMZ-resistant cell lines and glioma tissue and was correlated with poor prognosis, its role in glioma is unclear known. The aim of this study was to elucidate the relationship between PYCARD and glioma based on Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), and Chinese Glioma Genome Atlas (CGGA) databases.

Methods

Glioma-resistant cells were compared with parental cells based on the GSE53014 and GSE113510 data sets. The relationship between PYCARD, tumor microenvironment, and long noncoding RNAs (lncRNAs) was assessed using logistic regression. Moreover, Kaplan-Meier and Cox regression were used to analyze the relationship between PYCARD expression and survival rate. Gene set enrichment analysis (GSEA) was also used to determine the biological function of PYCARD and lncRNAs. Cell viability and cell migration assays were used to evaluate the ability of cells to migrate and proliferate. Finally, we analyzed the expression patterns of PYCARD genes in a wide range of cancers.

Results

Elevated expression of PYCARD promoted glioma cell proliferation and migration. PYCARD expression was significantly positively associated with gamma delta T cells but negatively correlated with M2 macrophages in glioblastoma multiforme (GBM). Likewise, PYCARD expression was significantly positively associated with monocytes but negatively associated with activated mast cells in low grade glioma (LGG). We also found that 3 PYCARD-related lncRNAs in GBM and 4 PYCARD-related lncRNAs in LGG had a predictive value for glioma patients. The pan-cancer analysis showed that PYCARD expression was higher in most cancer groups.

Conclusions

High expression of PYCARD is an independent predictor of unfavorable prognosis and chemotherapy resistance in glioma.