EVA1B to Evaluate the Tumor Immune Microenvironment and Clinical Prognosis in Glioma

Multi-cohort comprehensive analysis unveiling the clinical value and therapeutic effect of GNAL in glioma

Clinical data indicates that glioma patients have poor treatment outcomes and clinical prognosis. The role of olfactory signaling pathway-related genes (OSPRGs) in glioma has not been fully elucidated. In this study, we aimed to investigate the role and relationship between OSPRGs and glioma. Univariate and multivariate Cox regression analyses were performed to assess the relationship between OSPRGs and the overall survival of glioma based on public cohorts, and the target gene (G Protein Subunit Alpha L, GNAL) was screened. The association of GNAL expression with clinicopathological characteristics, gene mutation landscape, tumor immune microenvironment (TIME), deoxyribonucleic acid (DNA) methylation, and naris-occlusion controlled genes (NOCGs) was performed. Immunohistochemistry was used to evaluate GNAL level in glioma. Further analysis was conducted to evaluate the drug sensitivity, immunotherapy response, and functional enrichment of GNAL. GNAL was an independent prognostic factor, and patients with low GNAL expression have a poor prognosis. Expression of GNAL was closely associated with clinicopathological characteristics, DNA methylation, and several immune-related pathways. Immune infiltration analysis indicated that GNAL levels were negatively correlated with immune scores. GNAL low-expression group showed efficacy with anti-PD-1 therapy. Ten compounds with significantly different half-maximal inhibitory concentration (IC50) values between the GNAL high and low-expression groups were identified. Furthermore, its expression was associated with several immune cells, immune-related genes, and NOCGs. The expression of GNAL is closely associated with clinicopathological characteristics, TIME, and the response to therapeutic interventions, highlighting its potential as a prognostic biomarker for glioma.

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

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

Classification of Glioblastoma Associated with Immune Checkpoints and Tumor Microenvironment based on Immunogenomic Profiling

BACKGROUND

Immune microenvironment is involved in tumor initiation and progression, and its effect on glioblastoma (GBM) is still unknown.

OBJECT

We sought to investigate the association between immune status and GBM.

METHODS

Transcriptome data and the relevant clinical data were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus (GEO) databases, and we identified two immune subtypes based on 29 immune-associated gene sets.

RESULTS

Through single-sample gene set enrichment analysis (ssGSEA), we found that the high-immunity subtype had the most tumor-infiltrating immune cells and immune checkpoint molecules in GBM patients. Furthermore, we could more effectively identify immune signature pathways in GBM.

CONCLUSION

After validation with the GEO dataset, we conclude that the identified GBM high-immune subtypes may be amenable to the application of novel immune therapy for GBM.

Novel Immune-Related LncRNA Pairs are Associated with Immunol Infiltration and Survival Status in Glioblastoma

Background

Immune-related lncRNA is involved in tumor initiation and progression, while its effect in glioblastoma (GBM) is still unknown.

Objective

We sought to investigate the association between immune-related lncRNA (ir-lncRNA) and GBM.

Methods

Transcriptomic and clinical data were obtained from the TCGA dataset, and we found 2008 ir-lncRNA differentially expressed between GBM and adjacent brain tissues.

Results

Appling the univariate Cox and Lasso regression model, we found 30 prognosis-related ir-lncRNA pairs to construct a Cox regression risk model to associate the outcome of GBM patients. Furthermore, with this risk model, we can identify the tumor immune infiltration status, the expression of immunosuppressive biomarkers, and chemical sensitivity in GBM patients.

Conclusions

We constructed an immunologic risk model with lncRNA to associate the survival outcome of GBM patients, which can provide useful biomarkers.

BCL2A1 is associated with tumor-associated macrophages and unfavorable prognosis in human gliomas

B-cell lymphoma 2-related protein A1 (BCL2A1) is a member of the BCL-2 family. Previous studies have shown that BCL2A1 is closely related to the tumorigenesis and resistance to chemotherapy of multiple solid tumors, such as breast cancer. However, the expression pattern and potential biological function of BCL2A1 in glioma remain unknown. For the first time, we found that the expression of BCL2A1 was higher in human glioma tissues than in normal brain tissues (NBTs) in both public datasets and an in-house cohort. High BCL2A1 expression was associated with advanced WHO grade, IDH 1/2 wild type and the mesenchymal (ME) subtype, and its overexpression in glioma predicted resistance to temozolomide (TMZ) chemotherapy and unfavorable prognosis. In addition, Gene set enrichment analysis (GSEA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated that BCL2A1 was significantly correlated with the immune response and immune-related pathways, and BCL2A1 expression was positively correlated with microenvironmental parameters (immune, stromal, and ESTIMATE scores) and macrophage infiltration. Interestingly, bioinformatic prediction and immunohistochemical/immunofluorescence staining analysis revealed that BCL2A1 expression was obviously associated with the tumor-associated macrophages (TAMs) markers CD68 and CCL2. Notably, knockdown of BCL2A1 significantly inhibited cell proliferation of U87 and U251 in vitro, induced smaller tumor size and prolonged survival time of mice in vivo. Co-culture experiments of macrophages and GBM cells showed that BCL2A1 knockdown inhibited macrophage migration. Meanwhile, knockdown of BCL2A1 was associated with low expression of CD68 and CCL2 in intracranial xenograft model. This may suggest that BCL2A1 promotes the progression of glioma and influences the prognosis of patients by participating in TAMs infiltration. In conclusion, these findings suggest that BCL2A1 could serve as a promising prognostic indicator and immunotherapy target in gliomas.

TCAF2 is associated with the immune microenvironment, promotes pathogenesis, and impairs prognosis in glioma

PURPOSE

Glioma is the most common primary intracranial tumor and exhibits rapid growth and aggressiveness. TRPM8 channel-associated factor 2 (TCAF2), located in cell junctions and the plasma membrane, plays a key role in the pathogeneses of several cancers in humans. However, the role of TCAF2 in glioma has been elusive.

METHODS

A combination of bioinformatic analysis using The Cancer Genome Atlas database and biological experiments, including 5-ethynyl-2'-deoxyuridine, transwell, and immunohistochemistry assays and xenotransplantation, was performed to analyze the expression level of TCAF2 and to mechanistically explore the relationship of TCAF2 with malignancy, prognosis, and the immune microenvironment in glioma.

RESULTS

TCAF2 was upregulated in glioma, and its expression level correlated with tumor grade and clinical outcome. The role of TCAF2 in promoting glioma malignancy was characterized through in vitro and in vivo experiments. Additionally, we observed that TCAF2 can modulate the metabolic pathways and immune microenvironment.

CONCLUSION

TCAF2 acts as an oncogene and may serve as a therapeutic target and prognostic marker in glioma.

A novel oncolytic virus-based biomarker participates in prognosis and tumor immune infiltration of glioma

Background

Glioma is the most common central nervous malignancy. Due to its poor survival outcomes, it is essential to identify novel individualized therapy. Oncolytic virus (OV) treatment is a key therapy regulating tumor microenvironment in malignant glioma. Herein, we aim to identify the key genes after OV infection and its role in glioma.

Methods

Performing an RNA-seq analysis, the differentially expressed genes (DEGs) between EV-A71-infection and mock group were screened with GFold values. DAVID online analysis was performed to identify the functional classification. Overall survival (OS) or disease-free survival (DFS) was evaluated to analyze the relation between PTBP1 expression levels and prognosis of glioma patients. Additionally, the ssGSEA and TIMER algorithms were applied for evaluating immune cell infiltration in glioma.

Results

Following EV-A71 infection in glioma cells, PTBP1, one of the downregulated DEGs, was found to be associated with multiple categories of GO and KEGG enrichment analysis. We observed elevated expression levels of PTBP1 across various tumor grades of glioma in comparison to normal brain samples. High PTBP1 expression had a notable impact on the OS of patients with low-grade glioma (LGG). Furthermore, we observed an obvious association between PTBP1 levels and immune cell infiltration in LGG. Notably, PTBP1 was regarded as an essential prognostic biomarker in immune cells of LGG.

Conclusion

Our research uncovered a critical role of PTBP1 in outcomes and immune cell infiltration of glioma patients, particularly in those with LGG.

A novel classifier combining G protein-coupled receptors and the tumor microenvironment is associated with survival status in glioblastoma

Background: Numerous studies have highlighted the crucial role of G protein-coupled receptors (GPCRs) in tumor microenvironment (TME) remodeling and their correlation with tumor progression. However, the association between GPCRs and the TME in glioblastoma (GBM) remains largely unexplored. Methods: In this study, we investigated the expression profile of GPCRs in GBM using integrated data from single-cell RNA sequencing and bulk sequencing. Surgical samples obtained from meningioma and GBM patients underwent single-cell RNA sequencing to examine GPCR levels and cell-cell interactions. Tumor microenvironment (TME) score is calculated by the infiltrated immune cells with CIBERSORT. Results: Our findings revealed a predominantly increased expression of GPCRs in GBM, and demonstrated that the classification of GPCRs and TME is an independent risk factor in GBM. Patients with high GPCR expression in the tumor tissue and low TME score exhibited the worst outcomes, suggesting a potentially aggressive tumor phenotype. On the other hand, patients with low GPCR expression in the tumor tissue and high TME score showed significantly better outcomes, indicating a potentially more favorable tumor microenvironment. Furthermore, the study found that T cells with high GPCR levels displayed extensive cell-cell connections with other tumor and immune cells in the single cell RNA analysis, indicating their potential involvement in immune escape. Conclusion: In conclusion, GPCRs in combination with TME classification can serve as prognostic markers for GBM. GPCRs play an essential role in tumor progression and the TME in 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.

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.

Transcription factor CASZ1 increases an oncogenic transcriptional process in tumorigenesis and progression of glioma cells

As a transcription factor, the role of CASZ1 in different entities is inconsistent. Glioma is one of the leading causes of cancer death worldwide. Its prognostic relevance and biological functions in glioma remain obscure. We focused on the role, mechanism, and prognostic value of CASZ1 in glioma cells. Herein, CASZ1 was identified as a novel potential oncogene in glioma tissues from GEO and TCGA datasets. CASZ1 was highly expressed in glioma tissues, predicting poor prognosis in glioma patients. Knockdown of CASZ1 inhibited proliferation and invasion in vitro, whereas upregulation of CASZ1 presented opposite results. Overexpression of CASZ1 increased transcriptional process of target gene p75NTR. CASZ1 was the potential transcriptional regulators for p75NTR. In addition, the p75NTR expression is essential for CASZ1 to exert its function as an oncogene. Our findings indicate that highly expressed CASZ1 in glioma cells acts as a pro‐oncogene factor in gliomas via regulating transcriptional process of target gene p75NTR, which was identified as an unfavorable prognostic marker in patients with gliomas. CASZ1 is expected to become a novel target for the treatment of gliomas.

Construction and Validation of a Prognostic Model Based on mRNAsi-Related Genes in Breast Cancer

Background

Breast cancer is a big threat to the women across the world with substantial morbidity and mortality. The pressing matter of our study is to establish a prognostic gene model for breast cancer based on mRNAsi for predicting patient's prognostic survival.

Methods

From The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we downloaded the expression profiles of genes in breast cancer. On the basis of one-class logistic regression (OCLR) machine learning algorithm, mRNAsi of samples was calculated. Kaplan-Meier (K-M) and Kruskal-Wallis (K-W) tests were utilized for the assessment of the connection between mRNAsi and clinicopathological variables of the samples. As for the analysis on the correlation between mRNAsi and immune infiltration, ESTIMATE combined with Spearman test was employed. The weighted gene coexpression network analysis (WGCNA) network was established by utilizing the differentially expressed genes in breast cancer, and the target module with the most significant correlation with mRNAsi was screened. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to figure out the biological functions of the target module. As for the construction of the prognostic model, univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses were performed on genes in the module. The single sample gene set enrichment analysis (ssGSEA) and tumor mutational burden were employed for the analysis on immune infiltration and gene mutations in the high- and low-risk groups. As for the analysis on whether this model had the prognostic value, the nomogram and calibration curves of risk scores and clinical characteristics were drawn.

Results

Nine mRNAsi-related genes (CFB, MAL2, PSME2, MRPL13, HMGB3, DCTPP1, SHCBP1, SLC35A2, and EVA1B) comprised the prognostic model. According to the results of ssGSEA and gene mutation analysis, differences were shown in immune cell infiltration and gene mutation frequency between the high- and low-risk groups.

Conclusion

Nine mRNAsi-related genes screened in our research can be considered as the biomarkers to predict breast cancer patients' prognoses, and this model has a potential relationship with individual somatic gene mutations and immune regulation. This study can offer new insight into the development of diagnostic and clinical treatment strategies for breast cancer.

Neutrophils: New Critical Regulators of Glioma

In cancer, neutrophils are an important part of the tumour microenvironment (TME). Previous studies have shown that circulating and infiltrating neutrophils are associated with malignant progression and immunosuppression in gliomas. However, recent studies have shown that neutrophils have an antitumour effect. In this review, we focus on the functional roles of neutrophils in the circulation and tumour sites in patients with glioma. The mechanisms of neutrophil recruitment, immunosuppression and the differentiation of neutrophils are discussed. Finally, the potential of neutrophils as clinical biomarkers and therapeutic targets is highlighted. This review can help us gain a deeper and systematic understanding of the role of neutrophils, and provide new insights for treatment in gliomas.

Molecular Characteristics, Oncogenic Roles, and Relevant Immune and Pharmacogenomic Features of EVA1B in Colorectal Cancer

OBJECTIVE

EVA1B, a protein coding gene, is a critical paralog of EVA1A gene. Herein, our study was conducted to investigate the role of EVA1B in colorectal cancer (CRC) progression and prognosis.

METHODS

Pan-cancer analysis was conducted to analyze expression, genetic and epigenetic alterations, and immunological characteristics of EVA1B. Especially, immunological characteristics and mutational landscape were compared between high and low EVA1B expression groups in the combined TCGA-COAD and TCGA-READ datasets. Through random survival forest analysis, an EVA1B-derived genomic model was developed, and its prognostic value was verified in the external datasets (GSE14333, GSE39582, and GSE87211). Drug sensitivity was compared between high- and low-risk subpopulations. A nomogram was conducted through integrating independent factors.

RESULTS

EVA1B expression presented a remarkable upregulation in most cancer types, especially CRC. EVA1B expression was significantly correlated to DNA methyltransferases, DNA mismatch repair genes, m⁶A regulators, TMB, and MSI across pan-cancer. High EVA1B expression indicated an undesirable CRC patients' prognosis. Additionally, its upregulation was correlated to enhanced immune cell infiltration, increased stromal and immune activation, and elevated activities of cancer immunity cycle. Higher frequencies of amplification and deletion were investigated in high EVA1B expression subpopulation. Following verification, the EVA1B-derived genomic model reliably predicted patients' prognosis and drug responses. The nomogram (age, stage, EVA1B-derived risk score) was conducted to quantify an individual's survival probability. Furthermore, our experimental validation based on immunohistochemistry indicated that EVA1B overexpression is correlated with CRC tumorigenesis and poor outcomes in our CRC patients' cohort.

CONCLUSION

Collectively, our findings provided valuable resource for guiding the mechanisms and therapeutic analysis of EVA1B in CRC.

FOXM1/lncRNA TYMSOS/miR-214-3p–Mediated High Expression of NCAPG Correlates With Poor Prognosis and Cell Proliferation in Non–Small Cell Lung Carcinoma

Lung cancer is the most common cancer with high mortality. Increasing evidence has demonstrated that nonstructural maintenance of chromosomes condensin I complex subunit G (NCAPG) plays a crucial role in the progression of human cancers. However, the biological function and underlying mechanism of NCAPG in non–small cell lung cancer (NSCLC) are still unclear. Here, we utilized diverse public databases to analyze the expression of NCAPG in pan-cancer. We found that NCAPG was highly expressed in various human cancers, especially in NSCLC. NCAPG expression was significantly positively correlated with poor clinical-pathological features, poor prognosis, tumor mutational burden, DNA microsatellite instability, and immune cell infiltration in NSCLC. In addition, our results showed that depletion of NCAPG significantly inhibited NSCLC cell proliferation, migration, and self-renewal abilities, yet these could be reversed by adding microRNA (miRNA)-214-3p. Knockdown of long noncoding RNA (lncRNA) thymidylate synthetase opposite strand (TYMSOS) also inhibits the NSCLC cell proliferation, migration, and self-renewal abilities. In summary, our findings demonstrated that the crucial roles of the FOXM1/lncRNA-TYMSOS/miRNA-214-3p/NCAPG axis in NSCLC may shed light on how NCAPG may act as a therapeutic target for NSCLC.

Identification of a basement membrane-related gene signature for predicting prognosis and estimating the tumor immune microenvironment in breast cancer

INTRODUCTION

Breast cancer (BC) is the most common malignancy in the world and has a high cancer-related mortality rate. Basement membranes (BMs) guide cell polarity, differentiation, migration and survival, and their functions are closely related to tumor diseases. However, few studies have focused on the association of basement membrane-related genes (BMRGs) with BC. This study aimed to explore the prognostic features of BMRGs in BC and provide new directions for the prevention and treatment of BC.

METHODS

We collected transcriptomic and clinical data of BC patients from TCGA and GEO datasets and constructed a predictive signature for BMRGs by using univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis. The reliability of the model was further evaluated and validated by Kaplan-Meier survival curves and receiver operating characteristic curves (ROC). Column line plots and corresponding calibration curves were constructed. Possible biological pathways were investigated by enrichment analysis. Afterward, we assessed the mutation status by tumor mutational burden (TMB) analysis and compared different subtypes using cluster analysis. Finally, we examined drug treatment sensitivity and immunological correlation to lay the groundwork for more in-depth studies in this area.

RESULTS

The prognostic risk model consisted of 7 genes (FBLN5, ITGB2, LAMC3, MMP1, EVA1B, SDC1, UNC5A). After validation, we found that the model was highly reliable and could accurately predict the prognosis of BC patients. Cluster analysis showed that patients with cluster 1 had more sensitive drugs and had better chances of better clinical outcomes. In addition, TMB, immune checkpoint, immune status, and semi-inhibitory concentrations were significantly different between high and low-risk groups, with lower-risk patients having the better anti-cancer ability.

DISCUSSION

The basement membrane-related gene signature that we established can be applied as an independent prognostic factor for BC and can provide a reference for individualized treatment of BC patients.

EVA1C Is a Potential Prognostic Biomarker and Correlated With Immune Infiltration Levels in WHO Grade II/III Glioma

Background

Immunotherapy is an effective therapeutic approach for multiple human cancer types. However, the correlations between EVA1C and patients’ prognosis as well as immune infiltration remain obscure. Herein, we employed transcriptomic and clinical data extracted from two independent databases to systematically investigate the role of EVA1C in the oncological context.

Methods

The differential expression of EVA1C was analyzed via TCGA and Oncomine databases. We evaluated the influence of EVA1C on clinical prognosis using Kaplan-Meier plotter. We then used the expression profiler to calculate stromal score, immune score, and ESTIMATE score based on the ESTIMATE algorithm. The abundance of infiltrating immune cells was calculated via TIMER. The correlations between EVA1C expression and immune infiltration levels were analyzed in two independent cohorts.

Results

In patients with World Health Organization (WHO) grade II/III glioma, high EVA1C expression was associated with malignant clinicopathological features and poor overall survival in both cohorts. EVA1C expression was positively associated with immune infiltration levels of B cell, CD4+ T cell, neutrophil, macrophage, and dendritic cells (DCs). Besides, EVA1C expression strongly correlated with diverse immune marker sets. And the predictive power of EVA1C was better than that of other indicators in predicting high immune infiltration levels in glioma.

Conclusions

For the first time, we identified the overexpression of EVA1C in glioma, which was tightly correlated with the high infiltration levels of multiple immune cells as well as poor prognosis. Meanwhile, EVA1C might be a potential biomarker for predicting high immune infiltration in WHO grade II/III gliomas.