The prognostic factors and nomogram for patients with high-grade gliomas

Utilizing the amide proton transfer technique to characterize diffuse gliomas based on the WHO 2021 classification of CNS tumors

PURPOSE

Diffuse gliomas present a significant challenge for healthcare systems globally. While brain MRI plays a vital role in diagnosis, prognosis, and treatment monitoring, accurately characterizing gliomas using conventional MRI techniques alone is challenging. In this study, we explored the potential of utilizing the amide proton transfer (APT) technique to predict tumor grade and type based on the WHO 2021 Classification of CNS Tumors.

METHODS

Forty-two adult patients with histopathologically confirmed brain gliomas were included in the study. They underwent 3T MRI imaging, which involved APT sequence. Multinomial and binary logistic regression models were employed to classify patients into clinically relevant groups based on MRI findings and demographic variables.

RESULTS

We found that the best model for tumor grade classification included patient age along with APT values. The highest sensitivity (88%) was observed for Grade 4 tumors, while Grade 3 tumors showed the highest specificity (79%). For tumor type classification, our model incorporated four predictors: APT values, patient's age, necrosis, and the presence of hemorrhage. The glioblastoma group had the highest sensitivity and specificity (87%), whereas balanced accuracy was the lowest for astrocytomas (0.73).

CONCLUSION

The APT technique shows great potential for noninvasive evaluation of diffuse gliomas. The changes in the classification of gliomas as per the WHO 2021 version of the CNS Tumor Classification did not affect its usefulness in predicting tumor grade or type.

Fluorescein-guided surgery in high-grade gliomas: focusing on the eloquent and deep-seated areas

PURPOSE

The vital function of eloquent and deep brain areas necessitates precise treatment for tumors located in these regions. Fluorescein-guided surgery (FGS) has been widely used for high-grade gliomas (HGGs) resection. Nevertheless, the safety and efficacy of utilizing this technique for resecting brain tumors located in eloquent and deep-seated areas remain uncertain. This study aims to assess the safety and extent of resection of HGGs in these challenging tumors with fluorescein and explore its impact on patient survival.

METHODS

A retrospective analysis was conducted on the clinical and radiological data of 67 consecutive patients with eloquent or deep-seated HGGs who underwent surgery between January 2020 and June 2023. Lacroix functional location grade was used to determine the eloquence of the tumors. The comparison between the fluorescence-guided surgery group (FGS, n = 32) and the conventional white-light microscopic surgery group (non-FGS, n = 35) included assessments of extent of resection (EOR), rates of gross total resection (GTR, 100%) and near-total resection (NTR, 99 to 98%), postoperative Neurologic Assessment in Neuro-Oncology (NANO) scores, overall survival (OS), and progression-free survival (PFS), to evaluate the safety and efficacy of fluorescein-guided technology in tumor resection at these specific locations.

RESULTS

Baseline of demographics, lesion location, and pathology showed no significant difference between the two groups. GTR of the FGS group was higher than the non-FGS group (84.4% vs. 60.0%, OR 3.60, 95% CI 1.18-10.28, p < 0.05). The FGS group also showed higher GTR + NTR (EOR ≥ 98%) than the non-FGS group (93.8% vs. 65.7%, OR 7.83, 95% CI 1.86-36.85, p < 0.01). 87.0% of eloquent tumors (Lacroix grade III) in the FGS group achieved GTR + NTR, compared to 52.2% of control group (OR 6.11, 95% CI 1.50-22.78, p < 0.05). For deep-seated tumors, the rate of GTR + NTR in the two groups were 91.7% and 53.3%, respectively (OR 9.62, 95% CI 1.05-116.50, p < 0.05). No significant difference of the preoperative NANO score of the two groups was found. The postoperative NANO score of the FGS group was significantly lower than the non-FGS group (2.56 ± 1.29 vs. 3.43 ± 1.63, p < 0.05). Median OS of the FGS group was 4.2 months longer than the non-FGS group despite no statistical difference (18.2 months vs. 14.0 months, HR 0.63, 95% CI 0.36-1.11, p = 0.112), while PSF was found significantly longer in FGS patients than those of the non-FGS group (11.2 months vs. 7.7 months, HR 0.59, 95% CI 0.35-0.99, p < 0.05).

CONCLUSION

Sodium fluorescein-guided surgery for high-grade gliomas in eloquent and deep-seated brain regions enables more extensive resection while preserving neurologic function and improve patient survival.

TGIF2 is a potential biomarker for diagnosis and prognosis of glioma

Background

TGFB-induced factor homeobox 2 (TGIF2), a member of the Three-Amino-acid-Loop-Extension (TALE) superfamily, has been implicated in various malignant tumors. However, its prognostic significance in glioma, impact on tumor immune infiltration, and underlying mechanisms in glioma development remain elusive.

Methods

The expression of TGIF2 in various human normal tissues, normal brain tissues, and gliomas was investigated using HPA, TCGA, GTEx, and GEO databases. The study employed several approaches, including Kaplan-Meier analysis, ROC analysis, logistic regression, Cox regression, GO analysis, KEGG analysis, and GSEA, to explore the relationship between TGIF2 expression and clinicopathologic features, prognostic value, and potential biological functions in glioma patients. The impact of TGIF2 on tumor immune infiltration was assessed through Estimate, ssGSEA, and Spearman analysis. Genes coexpressed with TGIF2 were identified, and the protein-protein interaction (PPI) network of these coexpressed genes were constructed using the STRING database and Cytoscape software. Hub genes were identified using CytoHubba plugin, and their clinical predictive value was explored. Furthermore, in vitro experiments were performed by knocking down and knocking out TGIF2 using siRNA and CRISPR/Cas9 gene editing, and the role of TGIF2 in glioma cell invasion and migration was analyzed using transwell assay, scratch wound-healing assay, RT-qPCR, and Western blot.

Results

TGIF2 mRNA was found to be upregulated in 21 cancers, including glioma. High expression of TGIF2 was associated with malignant phenotypes and poor prognosis in glioma patients, indicating its potential as an independent prognostic factor. Furthermore, elevated TGIF2 expression positively correlated with cell cycle regulation, DNA synthesis and repair, extracellular matrix (ECM) components, immune response, and several signaling pathways that promote tumor progression. TGIF2 showed correlations with Th2 cells, macrophages, and various immunoregulatory genes. The hub genes coexpressed with TGIF2 demonstrated significant predictive value. Additionally, in vitro experiments revealed that knockdown and knockout of TGIF2 inhibited glioma cell invasion, migration and suppressed the epithelial-mesenchymal transition (EMT) phenotype.

Conclusion

TGIF2 emerges as a potential biomarker for glioma, possibly linked to tumor immune infiltration and EMT.

Single-cell disulfidptosis regulator patterns guide intercellular communication of tumor microenvironment that contribute to kidney renal clear cell carcinoma progression and immunotherapy

Background

Disulfidptosis, an emerging type of programmed cell death, plays a pivotal role in various cancer types, notably impacting the progression of kidney renal clear cell carcinoma (KIRC) through the tumor microenvironment (TME). However, the specific involvement of disulfidptosis within the TME remains elusive.

Methods

Analyzing 41,784 single cells obtained from seven samples of KIRC through single-cell RNA sequencing (scRNA-seq), this study employed nonnegative matrix factorization (NMF) to assess 24 disulfidptosis regulators. Pseudotime analysis, intercellular communication mapping, determination of transcription factor activities (TFs), and metabolic profiling of the TME subgroup in KIRC were conducted using Monocle, CellChat, SCENIC, and scMetabolism. Additionally, public cohorts were utilized to predict prognosis and immune responses within the TME subgroup of KIRC.

Results

Through NMF clustering and differential expression marker genes, fibroblasts, macrophages, monocytes, T cells, and B cells were categorized into four to six distinct subgroups. Furthermore, this investigation revealed the correlation between disulfidptosis regulatory factors and the biological traits, as well as the pseudotime trajectories of TME subgroups. Notably, disulfidptosis-mediated TME subgroups (DSTN+CD4T-C1 and FLNA+CD4T-C2) demonstrated significant prognostic value and immune responses in patients with KIRC. Multiple immunohistochemistry (mIHC) assays identified marker expression within both cell clusters. Moreover, CellChat analysis unveiled diverse and extensive interactions between disulfidptosis-mediated TME subgroups and tumor epithelial cells, highlighting the TNFSF12-TNFRSF12A ligand-receptor pair as mediators between DSTN+CD4T-C1, FLNA+CD4T-C2, and epithelial cells.

Conclusion

Our study sheds light on the role of disulfidptosis-mediated intercellular communication in regulating the biological characteristics of the TME. These findings offer valuable insights for patients with KIRC, potentially guiding personalized immunotherapy approaches.

Ferroptosis-related gene MTF-1 as a novel prognostic biomarker in low-grade glioma and its correlation with immune infiltration

Background

Metal-responsive transcription factor-1 performs a necessary position in a range of cancers. It is unknown, though, how the prognosis of patients with low-grade gliomas is related to immune infiltration.

Method

The Cancer Genome Atlas database was used in this investigation to evaluate MTF-1 transcription in low-grade glioma and healthy brain tissues, and immunohistochemistry was used to confirm MTF-1 levels. By using functional enrichment analysis and R software, the putative biological roles and signaling pathways connected to MTF-1 in LGG as well as its prognostic significance were investigated. Further research was done on the connection involving MTF-1 and tumor mutational burden in LGG. Finally, the research evaluated how MTF-1 and immune cell infiltration are related.

Results

We noticed that the WHO grade, 1p/19q codeletion, and older age were all substantially linked with MTF-1 overexpression in low-grade gliomas. OS and disease-specific survival were significantly lowered as a result of MTF-1 transcription. MTF-1 was recognized as an independent OS prognostic predictor with a poor prognosis by multifactorial Cox analysis. Functional enrichment analysis revealed that the primary enrichment pathways were chemical carcinogenesis-receptor activation and the generation of miRNAs implicated in gene suppression by miRNA. Additionally, there was a negative correlation between MTF-1 overexpression and the degree of immune cell infiltration in neutrophils and DC.

Conclusion

MTF-1 may be a novel prognostic biomarker.

Multi-omics analysis reveals the involvement of origin recognition complex subunit 6 in tumor immune regulation and malignant progression

Background

Origin recognition complex 6 (ORC6) is one of the six highly conserved subunit proteins required for DNA replication and is essential for maintaining genome stability during cell division. Recent research shows that ORC6 regulates the advancement of multiple cancers; however, it remains unclear what regulatory impact it has on the tumor immune microenvironment.

Methods

Unpaired Wilcoxon rank sum and signed rank tests were used to analyze the differences in the expression of ORC6 in normal tissues and corresponding tumor tissues. Multiple online databases have evaluated the genetic alterations, protein expression and localization, and clinical relevance of ORC6. To evaluate the potential prognostic impact and diagnostic significance of ORC6 expression, we carried out log-rank, univariate Cox regression, and receiver operating characteristic curve analysis. The ICGC-LIRI-JP cohort, CGGA-301 cohort, CGGA-325 cohort, CGGA-693 cohort, and GSE13041 cohort were used for external validation of the study findings. The associations between ORC6 expression and immune cell infiltration, immune checkpoint expression, and immunotherapy cohorts was further analyzed. To explore the functional and signaling pathways related to ORC6 expression, gene set enrichment analysis was performed. To clarify the expression and function of ORC6 in hepatocellular carcinoma (LIHC) and glioma, we conducted in vitro experiments.

Results

Expression of ORC6 is upregulated in the majority of cancer types and is associated with poor patient prognosis, notably in cases of LIHC and gliomas. In addition, ORC6 may be involved in multiple signaling pathways related to cancer progression and immune regulation. High expression of ORC6 correlates with an immunosuppressive state in the tumor microenvironment. The results of further immunotherapy cohort analysis suggested that patients in the ORC6 high-expression group benefited from immunotherapy. Inhibiting ORC6 expression suppressed the proliferative and migratory abilities of LIHC and glioma cells.

Conclusion

High expression of ORC6 may be used as a biomarker to predict the poor prognosis of most tumor patients. The high expression of ORC6 may be involved in the regulation of the tumor immunosuppressive environment, and it is expected to become a molecular target for inhibiting tumor progression.

Independent prognostic biomarker FERMT3 associated with immune infiltration and immunotherapy response in glioma

BACKGROUND

Adult glioma progresses rapidly and has a poor clinical outcome. The focal adhesion protein Kindlin-3 (encoded by the FERMT3 gene) participates in tumor development, drug resistance, and progression. However, the relationship between Kindlin-3 and glioma prognosis or immune microenvironment is poorly understood.

METHODS

We comprehensively analyzed the expression, prognostic value, mutation landscape, functional enrichment, immune infiltration, and therapeutic role of FERMT3 in glioma using multiple datasets and validated Kindlin-3 expression in clinical tissue specimens by immunohistochemistry and multiple immunofluorescence staining.

RESULTS

FERMT3 is an independent predictor of glioma prognosis and is highly expressed in glioblastoma tissues. Functional enrichment analyses indicated that FERMT3 participates in multiple immune-related pathways such as immune response and cytokine production. Furthermore, FERMT3 expression was positively correlated with the infiltration of several immune cells, immune scores, and the expression of genes related to immune checkpoints. Further analyses revealed that overexpression of FERMT3 was linked to a better response to anti-PD1 therapy. Data from single-cell RNA-seq reveal that FERMT3 was largely expressed in microglial cells and tissue-resident macrophages. Multiple immunofluorescence staining confirmed the overexpression of Kindlin-3 in the glioma-associated microglia/macrophages (GAMs).

CONCLUSION

The findings of this study provide a new perspective on the role of Kindlin-3 in glioma and may have a significant impact on the discovery of novel biomarkers and targeting of GAMs in the future.

Increase in serum vimentin levels in patients with glioma and its correlation with prognosis of patients with glioblastoma

Early diagnosis of glioma is of great value to improve prognosis. We focused on serum vimentin levels as a useful biomarker for preoperative diagnosis. The aim of this study was to determine whether serum vimentin levels in patients with glioma are significantly higher than those of healthy adult volunteer and whether the serum vimentin level is associated with overall survival (OS) in patients with glioblastoma (GBM). This study included 52 consecutive patients with newly diagnosed glioma and a control group of 13 healthy adult volunteers. We measured serum vimentin levels in blood samples obtained from patients with glioma preoperatively and a control group. Furthermore, we investigated the correlation between serum vimentin levels and OS in patients with GBM. The serum vimentin levels of patients with glioma were significantly higher than those of the control group. The serum vimentin level of 2.9 ng/ml was the optimal value for differentiating patients with glioma from the control group with a sensitivity of 92.3% and specificity of 88.5%. The serum vimentin levels correlated significantly with immunoreactivity for survivin. In 27 patients with GBM, serum vimentin levels (cutoff value, median value 53.3 ng/ml) correlated with OS in univariate and multivariate analyses. Our study revealed that serum vimentin levels of patients with glioma are significantly higher than those of the control group. Therefore, we believe that serum vimentin level might be a useful and practical biomarker for preoperative diagnosis of glioma. Furthermore, high serum vimentin levels correlated significantly with shorter OS in patients with GBM.

Prognostic biomarker CCR6 and its correlation with immune infiltration in cutaneous melanoma

Background

Cutaneous melanoma (CM) is an aggressive type of skin cancer. Even after standard treatment, the recurrence and malignant progression of CM were almost inevitable. The overall survival (OS) of patients with CM varied widely, making it critical for prognostic prediction. Based on the correlation between CCR6 and melanoma incidence, we aimed to investigate the prognostic role of CCR6 and its relationship with immune infiltration in CM.

Methods

We obtained RNA sequencing data from The Cancer Genome Atlas (TCGA) to analyze the CM expression. Functional enrichment analyses, immune infiltration analyses, immune checkpoint analyses, and clinicopathology analyses were performed. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors. A nomogram model had been developed. Kaplan-Meier survival analysis and log-rank test were used to estimate the relationship between OS and CCR6 expression.

Results

CCR6 was significantly upregulated in CM. Functional enrichment analyses revealed that CCR6 was correlated with immune response. Most immune cells and immune checkpoints were positively correlated with CCR6 expression. Kaplan-Meier analyses showed that high CCR6 expression was associated with a good outcome in CM and its subtypes. Cox regression showed that CCR6 was an independent prognostic factor in patients with CM (HR = 0.550, 95% CI = 0.332-0.912, p<0.05).

Conclusions

CCR6 is considered to be a new prognostic biomarker for patients with CM, and our study provides a potential therapeutic target for CM treatment.

System analysis based on the migration- and invasion-related gene sets identifies the infiltration-related genes of glioma

The current database has no information on the infiltration of glioma samples. Here, we assessed the glioma samples' infiltration in The Cancer Gene Atlas (TCGA) through the single-sample Gene Set Enrichment Analysis (ssGSEA) with migration and invasion gene sets. The Weighted Gene Co-expression Network Analysis (WGCNA) and the differentially expressed genes (DEGs) were used to identify the genes most associated with infiltration. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the major biological processes and pathways. Protein-protein interaction (PPI) network analysis and the least absolute shrinkage and selection operator (LASSO) were used to screen the key genes. Furthermore, the nomograms and receiver operating characteristic (ROC) curve were used to evaluate the prognostic and predictive accuracy of this clinical model in patients in TCGA and the Chinese Glioma Genome Atlas (CGGA). The results showed that turquoise was selected as the hub module, and with the intersection of DEGs, we screened 104 common genes. Through LASSO regression, TIMP1, EMP3, IGFBP2, and the other nine genes were screened mostly in correlation with infiltration and prognosis. EMP3 was selected to be verified in vitro. These findings could help researchers better understand the infiltration of gliomas and provide novel therapeutic targets for the treatment of gliomas.

URB2 as an important marker for glioma prognosis and immunotherapy

Introduction: Glioma is the most common primary brain tumor and primary malignant tumor of the brain in clinical practice. Conventional treatment has not significantly altered the prognosis of patients with glioma. As research into immunotherapy continues, glioma immunotherapy has shown great potential. Methods: The clinical data were acquired from the Chinese Glioma Genome Atlas (CGGA) database and validated by the Gene Expression Omnibus (GEO) database, The Cancer Genome Atlas (TCGA) dataset, Clinical Proteomic Tumor Analysis Consortium (CPTAP) database, and Western blot (WB) analysis. By Cox regression analyses, we examined the association between different variables and overall survival (OS) and its potential as an independent prognostic factor. By constructing a nomogram that incorporates both clinicopathological variables and the expression of URB2, we provide a model for the prediction of prognosis. Moreover, we explored the relationship between immunity and URB2 and elucidated its underlying mechanism of action. Results: Our study shows that URB2 likely plays an oncogenic role in glioma and confirms that URB2 is a prognostic independent risk factor for glioma. Furthermore, we revealed a close relationship between immunity and URB2, which suggests a new approach for the immunotherapy of glioma. Conclusion: URB2 can be used for prognosis prediction and immunotherapy of glioma.

Integration of clinical and spatial data to explore lipid metabolism-related genes for predicting prognosis and immune microenvironment in gliomas

Lipid metabolism is crucial to tumor growth and immune microenvironment as well as drug sensitivity in glioma. Identifying prognostic indicators of glioma and elucidating the mechanisms of glioma progression are critical for improving the prognosis of glioma patients. In this study, we investigated the role and prognostic value of metabolism-related genes in glioma by integrative analysis of datasets from GEO, CGGA, and TCGA. Based on clinical data and transcriptome data, we found that the expression pattern of three major pathways related to lipid metabolism is fatty acidhigh-phospholipidhigh-triglyceridelow, which is associated with better prognosis and immune infiltration. The genes involved in these three pathways were used to generate a prognostic model, which showed high stability and efficiency in the test set and validation set. The spatial transcriptome of glioma patients revealed that the microenvironment of the regions with high expression of risk genes CAV1 and SCD is in a state of hypoxia, EMT, and cell cycle arrest, and thus can be used as markers of metabolic reprogramming in the tumor microenvironment. In the high-risk group, M0 macrophages and M1 macrophages were significantly enriched, and the risk score was significantly correlated with gene mutation and methylation of risk genes. We further performed drug sensitivity screening corresponding to different risk genes. This study provided novel insights into the differential immune microenvironment with different expression patterns of metablism-related genes and highlighted the spatial and temporal synergy of tumor progression and metabolic reprogramming.

Classification related to immunogenic cell death predicts prognosis, immune microenvironment characteristics, and response to immunotherapy in lower-grade gliomas

Background

Immunogenic cell death (ICD) is a form of cell death that elicits immune responses against the antigens found in dead or dying tumor cells. Growing evidence implies that ICD plays a significant role in triggering antitumor immunity. The prognosis for glioma remains poor despite many biomarkers being reported, and identifying ICD-related biomarkers is imminent for better-personalized management in patients with lower-grade glioma (LGG).

Materials and methods

We identified ICD-related differentially expressed genes (DEGs) by comparing gene expression profiles obtained across Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) cohorts. On the foundation of ICD-related DEGs, two ICD-related clusters were identified through consensus clustering. Then, survival analysis, functional enrichment analysis, somatic mutation analysis, and immune characteristics analysis were performed in the two ICD-related subtypes. Additionally, we developed and validated a risk assessment signature for LGG patients. Finally, we selected one gene (EIF2AK3) from the above risk model for experimental validation.

Results

32 ICD-related DEGs were screened, dividing the LGG samples from the TCGA database into two distinct subtypes. The ICD-high subgroup showed worse overall survival (OS), greater immune infiltration, more active immune response process, and higher expression levels of HLA genes than the ICD-low subgroup. Additionally, nine ICD-related DEGs were identified to build the prognostic signature, which was highly correlated with the tumor-immune microenvironment and could unambiguously be taken as an independent prognostic factor and further verified in an external dataset. The experimental results indicated that EIF2AK3 expression was higher in tumors than paracancerous tissues, and high-expression EIF2AK3 was enriched in WHO III and IV gliomas by qPCR and IHC, and Knockdown of EIF2AK3 suppressed cell viability and mobility in glioma cells.

Conclusion

We established novel ICD-related subtypes and risk signature for LGG, which may be beneficial to improving clinical outcome prediction and guiding individualized immunotherapy.

H2B gene family: A prognostic biomarker and correlates with immune infiltration in glioma

The current prognosis of glioma is unfavorable and effective treatments remain limited. However, bioinformatics has created new opportunities for improving glioma treatment. Research indicates that H2B is involved in the pathological process of cancer. Thus, this study conducted bioinformatic analyses of the H2B gene family to evaluate whether these genes can play a role in predicting prognosis and are associated with immune infiltration. High expression of H2B genes was observed in cholangiocarcinoma, esophageal carcinoma, glioblastoma multiforme (GBM), head and neck squamous cell carcinoma, and other cancers. In addition, a rise in H2B gene expression was correlated with an increase in glioma grade. In the Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA) database and multiple datasets from the Gene Expression Omnibus (GEO), high expression of H2B gene family members predicted poor prognosis of a variety of tumors including glioma. In particular, high H2BC5, H2BC9, H2BC11, and H2BC21 expression was associated with poor glioma prognosis. H2BC9, H2BC11, and H2BC12 expression were also positively correlated with both immune and stromal scores. Enrichment analysis indicated that H2B family genes may be involved in the pathological process of glioma using various pathways including the cell cycle and immune response. H2B-specific siRNAs were used to verify the role of H2BC5, H2BC9, H2BC11, and H2BC21 expression on cell cycle distribution. In summary, H2BC5, H2BC9, H2BC11, and H2BC21 were independent prognostic indicators of glioma, and H2BC9 and H2BC11 may correlate with tumor immunity.

Microfibrillar-associated protein 2 is a prognostic marker that correlates with the immune microenvironment in glioma

Aims: microfibrillar-associated protein 2 (MFAP2), a component of the extracellular matrix, plays key roles in regulating growth factor signal transduction and various malignant tumors. However, the clinicopathological features of microfibrillar-associated protein 2 in gliomas have not been elucidated to date.

Methods: TCGA and CGGA databases were used to study the expression of microfibrillar-associated protein 2 in glioma and its relationship with clinicopathological features of patients with glioma. Western blotting was performed to detect the expression of microfibrillar-associated protein 2 protein in tissue samples from glioma patients. Gene set enrichment analysis (GSEA) was applied to detect biological processes and signal pathways related to microfibrillar-associated protein 2. Single-sample gene set enrichment analysis, TIMER 2.0, and TISIDB databases were used to evaluate the role of microfibrillar-associated protein 2 in tumor immune characteristics. The prognostic role of microfibrillar-associated protein 2 in glioma was analyzed using the Kaplan-Meier method and Cox regression. Survival data were used to establish a nomogram prediction model.

Results: microfibrillar-associated protein 2 expression was significantly elevated in gliomas. receiver operating characteristic analysis revealed good discrimination of microfibrillar-associated protein 2 between glioma and normal tissues. High expression of microfibrillar-associated protein 2 was associated with malignant phenotypes, such as histological type. Based on gene set enrichment analysis, we identified pathways associated with high microfibrillar-associated protein 2 expression. High microfibrillar-associated protein 2 expression was related to the infiltration of tumor immune cells, including Th2 cells and macrophages, and correlated with key markers of T-cell exhaustion. Based on the TISIDB database, microfibrillar-associated protein 2 was observed to be associated with chemokines, chemokine receptors, and multiple immunoinhibitors in glioma. Kaplan–Meier survival analyses revealed that high microfibrillar-associated protein 2 expression predicted poor overall survival, DSS, and PFS in patients with glioma. By combining microfibrillar-associated protein 2 and other prognostic factors, a nomogram prognostic prediction model was constructed, which demonstrated an ideal prediction effect.

Conclusion: microfibrillar-associated protein 2 is a potential prognostic marker that plays a key role in glioma development given its association with malignant phenotypes, cancer-related pathways and tumor immunity.

Comprehensive Analysis of the Prognostic Value and Immune Infiltration of Butyrophilin Subfamily 2/3 (BTN2/3) Members in Pan-Glioma

The BTN2/3 subfamilies are overexpressed in many cancers, including pan-glioma (low- and high-grade gliomas). However, the expression and prognosis of BTN2/3 subfamilies and tumor-infiltrating lymphocytes in pan-glioma remain unknown. In the present study, we systematically explored and validated the expression and prognostic value of BTN2/3 subfamily members in pan-glioma [The Cancer Genome Atlas–glioblastoma and low-grade glioma (TCGA-GBMLGG) merge cohort] using multiple public databases. We used clinical specimens for high-throughput verification and cell lines for qRT-PCR verification, which confirmed the expression profiles of BTN2/3 subfamilies. In addition, the function of the BTN2/3 subfamily members and the correlations between BTN2/3 subfamily expression and pan-glioma immune infiltration levels were investigated. We found that BTN2/3 subfamily members were rarely mutated. BTN2/3 subfamilies were overexpressed in pan-glioma; high expression of BTN2/3 subfamily members was correlated with poor prognosis. In addition, BTN2/3 subfamilies might positively regulate proliferation, and the overexpression of BTN2/3 subfamilies influenced cell cycle, differentiation, and glioma stemness. In terms of immune infiltrating levels, BTN2/3 subfamily expression was positively associated with CD4+ T-cell, B-cell, neutrophil, macrophage, and dendritic cell infiltrating levels. These findings suggest that BTN2/3 subfamily expression is correlated with prognosis and immune infiltration levels in glioma. Therefore, the BTN2/3 subfamilies can be used as biomarkers for pan-glioma and prognostic biomarkers for determining the prognosis and immune infiltration levels in pan-glioma.

A Novel CRISPR/Cas9 Screening Potential Index for Prognostic and Immunological Prediction in Low-Grade Glioma

Glioma is a malignancy with the highest mortality in central nervous system disorders. Here, we implemented the computational tools based on CRISPR/Cas9 to predict the clinical outcomes and biological characteristics of low-grade glioma (LGG). The transcriptional expression profiles and clinical phenotypes of LGG patients were retrieved from The Cancer Genome Atlas and Chinese Glioma Genome Atlas. The CERES algorithm was used to screen for LGG-lethal genes. Cox regression and random survival forest were adopted for survival-related gene selection. Nonnegative matrix factorization distinguished patients into different clusters. Single-sample gene set enrichment analysis was employed to create a novel CRISPR/Cas9 screening potential index (CCSPI), and patients were stratified into low- and high-CCSPI groups. Survival analysis, area under the curve values (AUCs), nomogram, and tumor microenvironment exploration were included for the model validation. A total of 20 essential genes in LGG were used to classify patients into two clusters and construct the CCSPI system. High-CCSPI patients were associated with a worse prognosis of both training and validation set (p < 0.0001) and higher immune fractions than low-CCSPI individuals. The CCSPI system had a promising performance with 1-, 3-, and 5-year AUCs of 0.816, 0.779, 0.724, respectively, and the C-index of the nomogram model reached 0.743 (95% CI = 0.725–0.760). Immune-infiltrating cells and immune checkpoints such as PD-1/PD-L1 and POLD3 were positively associated with CCSPI. In conclusion, the CCSPI had prognostic value in LGG, and the model will deepen our cognition of the interaction between the CNS and immune system in different LGG subtypes.

MD2 Is a Potential Biomarker Associated with Immune Cell Infiltration in Gliomas

BACKGROUND

Glioma is the most common primary malignant tumor in the central nervous system. Myeloid differentiation protein 2 (MD2) acts as a coreceptor of toll-like receptor 4 (TLR4) to mediate innate immune response. However, the actual roles of MD2 in the regulation of progression and immune cell infiltration in gliomas remain largely unclear. This study aims to explore whether MD2 could be an independent prognostic factor through the mediation of immune cell infiltration in gliomas.

METHODS

The mRNA expression and DNA methylation differential analyses of MD2 were performed using CGGA, TCGA and Rembrandt databases and survival analyses were performed using Kaplan-Meier plotter. Univariate and multivariate Cox regression was applied to analyze the prognostic value of MD2 and nomograms were constructed to evaluate the clinical value of MD2. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were utilized to analyze MD2-related signal pathways. Furthermore, correlations between MD2 and immune cell infiltration were calculated by TIMER and CIBERSOPT. The correlation between MD2 expression and the infiltrations of macrophages and neutrophils was experimentally verified by the knockdown of MD2 expression using small interfering RNA (siRNA) in glioma cells.

RESULTS

We found that MD2 was overexpressed and associated with a poor prognosis in gliomas. Meanwhile, higher expression of MD2 could be a result of lower DNA methylation of MD2 gene in gliomas. In addition, univariate and multivariate Cox regression analysis indicated that MD2 could be an independent prognostic factor for gliomas. Further functional enrichment analysis revealed that the functions of MD2 were closely related to immune responses. Moreover, the expression level of MD2 was strongly correlated with the infiltration and polarization of pro-tumor phenotype of tumor-associated macrophages and tumor-associated neutrophils in gliomas.

CONCLUSIONS

These findings have provided strong evidence that MD2 could be served as a valuable immune-related biomarker to diagnose and predict the progression of gliomas.

MD2 Is a Potential Biomarker Associated with Immune Cell Infiltration in Gliomas

Background

Glioma is the most common primary malignant tumor in the central nervous system. Myeloid differentiation protein 2 (MD2) acts as a coreceptor of toll-like receptor 4 (TLR4) to mediate innate immune response. However, the actual roles of MD2 in the regulation of progression and immune cell infiltration in gliomas remain largely unclear. This study aims to explore whether MD2 could be an independent prognostic factor through the mediation of immune cell infiltration in gliomas.

Methods

The mRNA expression and DNA methylation differential analyses of MD2 were performed using CGGA, TCGA and Rembrandt databases and survival analyses were performed using Kaplan-Meier plotter. Univariate and multivariate Cox regression was applied to analyze the prognostic value of MD2 and nomograms were constructed to evaluate the clinical value of MD2. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were utilized to analyze MD2-related signal pathways. Furthermore, correlations between MD2 and immune cell infiltration were calculated by TIMER and CIBERSOPT. The correlation between MD2 expression and the infiltrations of macrophages and neutrophils was experimentally verified by the knockdown of MD2 expression using small interfering RNA (siRNA) in glioma cells.

Results

We found that MD2 was overexpressed and associated with a poor prognosis in gliomas. Meanwhile, higher expression of MD2 could be a result of lower DNA methylation of MD2 gene in gliomas. In addition, univariate and multivariate Cox regression analysis indicated that MD2 could be an independent prognostic factor for gliomas. Further functional enrichment analysis revealed that the functions of MD2 were closely related to immune responses. Moreover, the expression level of MD2 was strongly correlated with the infiltration and polarization of pro-tumor phenotype of tumor-associated macrophages and tumor-associated neutrophils in gliomas.

Conclusions

These findings have provided strong evidence that MD2 could be served as a valuable immune-related biomarker to diagnose and predict the progression of gliomas.