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

2021 ◽  
Vol 12 ◽  
Author(s):  
Shanqiang Qu ◽  
Jin Liu ◽  
Huafu Wang
Keyword(s):  
T Cells ◽  
B Cells ◽  
Immune Cells ◽  
Cox Regression ◽  
Prognostic Biomarker ◽  
Area Under The Curve ◽  
Biological Databases ◽  
Clinical Prognosis ◽  
Immune Infiltration ◽  
Potential Biomarker

BackgroundPrevious research indicated that the tumor cells and microenvironment interactions are critical for the immunotherapeutic response. However, predicting the clinical response to immunotherapy remains a dilemma for clinicians. Hence, this study aimed to investigate the associations between EVA1B expression and prognosis and tumor-infiltrating immune cells in glioma.MethodsFirstly, we detected the EVA1B expression in glioma tissues through biological databases. The chi-squared test, Kaplan-Meier, and univariate and multivariate Cox regression analyses were used to analyze the clinical significance of EVA1B expression. The correlation between EVA1B expression and levels of tumor-infiltrating immune cells in glioma tissues was investigated. Receiver operating characteristic (ROC) analysis was performed to compare the predictive power between EVA1B and other commonly immune-related markers.ResultsIn the CGGA cohort of 325 glioma patients, we found that EVA1B was upregulated in glioma, and increased with tumor grade. High EVA1B expression was prominently associated with unfavorable clinicopathological features, and poorer survival of patients, which were further confirmed by TCGA (n=609) and GEO (n=74) cohorts. Furthermore, multivariate analysis indicated that EVA1B is an independent prognostic biomarker for glioma. Importantly, EVA1B overexpression was associated with a higher infiltration level of CD4+ T cells, CD8+ T cells, B cells, macrophages, and neutrophils in glioma. ROC curves showed that, compared with PD-L1, CTLA-4, and Siglec15, EVA1B presented a higher area under the curve (AUC) value (AUC=0.824) for predicting high immune infiltration levels in glioma.ConclusionsWe found that EVA1B was upregulated and could act as a poor prognostic biomarker in glioma. Importantly, EVA1B overexpression was associated with the immune infiltration levels of immune cells including B cells, CD4+ T cells, CD8+ T cells, macrophages, and neutrophils, and strongly with the overall immune infiltration levels of glioma. These findings suggested that EVA1B might be a potential biomarker for evaluating prognosis and immune infiltration in glioma.

scholarly journals Analysis of the Expression and Prognostic Value of MSH2 in Pan-Cancer Based on Bioinformatics

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Wenli Qiu ◽  
Ke Ding ◽  
Lusheng Liao ◽  
Yongchang Ling ◽  
Xiaoqiong Luo ◽  
...  
Keyword(s):  
T Cells ◽  
Prognostic Value ◽  
Cox Regression ◽  
Cancer Susceptibility ◽  
Prognostic Significance ◽  
Housekeeping Gene ◽  
Significant Negative Correlation ◽  
Immune Infiltration ◽  
Potential Biomarker ◽  
Pan Cancer

Background. MutS homolog 2 (MSH2), with the function of identifying mismatches and participating in DNA repair, is the “housekeeping gene” in the mismatch repair (MMR) system. MSH2 deficiency has been reported to enhance cancer susceptibility for the association of hereditary nonpolyposis colorectal cancer. However, the expression and prognostic significance of MSH2 have not been studied from the perspective of pan-cancer. Methods. The GTEx database was used to analyze the expression of MSH2 in normal tissues. The TCGA database was used to analyze the differential expression of MSH2 in pan-cancers. The prognostic value of MSH2 in pan-cancer was assessed using Cox regression and Kaplan-Meier analysis. Spearman correlations were used to measure the relationship between the expression level of MSH2 in pan-cancer and the level of immune infiltration, tumor mutational burden (TMB), and microsatellite instability (MSI). Results. MSH2 is highly expressed in most type of cancers and significantly correlated with prognosis. In COAD, KIRC, LIHC, and SKCM, the expression of MSH2 was significantly positively correlated with the abundance of B cells, CD4+ T cells, CD8+ T cells, dendritic cells, macrophages, and neutrophils. In THCA, MSH2 expression correlated with CD8+T Cell showed a significant negative correlation. MSH2 had significantly negative correlations with stromal score and immune score in a variety of cancers and significantly correlated with TMB and MSI of a variety of tumors. Conclusions. MSH2 may play an important role in the occurrence, development, and immune infiltration of cancer. MSH2 can emerge as a potential biomarker for cancer diagnosis and prognosis.

scholarly journals EMILIN2 Correlated With Its Methylation and Immune Infiltration Could Be an Independent Prognostic Biomarker in LGG

2021 ◽  
Author(s):  
Li-chong Wang ◽  
Zhe Zhang ◽  
Zi-long Tan ◽  
Qiao-li Lv ◽  
Shu-hui Chen ◽  
...  
Keyword(s):  
Immune Cells ◽  
Poor Prognosis ◽  
Bioinformatics Analysis ◽  
Cox Regression ◽  
Prognostic Biomarker ◽  
Low Grade ◽  
Central Nervous System Neoplasms ◽  
Immune Infiltration ◽  
Nervous System Neoplasms ◽  
Slow Growing

Abstract Low-grade gliomas (LGGs) are slow-growing brain cancer in central nervous system neoplasms. EMILIN2 is an extracellular matrix (ECM) protein which could influence the progress of some tumour which is unclear in LGG. In our study, the methylation, expression, prognosis and immune value of EMILIN2 were analysed in LGG through bioinformatics analysis. we first analysed the LGG data from TCGA and discovered that the EMILIN2 expression, negatively correlated to the EMILIN2 methylation could predict a poor prognosis and associated with different clinical parameters. Moreover, univariate and multivariate Cox regression were performed in CGGA showed that the EMILIN2 could be an independent prognostic biomarker in LGG. Finally, EMILIN2 expression showed a correlation with gene makers in some immune cells which identified the significance of EMILIN2 in immune infiltration. In conclusion, EMILIN2 could act as an independent prognostic biomarker which might be associated with the malignancy and development of gliomas and play a crucial role in glioma in immune infiltration.

scholarly journals PCOLCE Is Potent Prognostic Biomarker and Associates With Immune Infiltration in Gastric Cancer

2020 ◽  
Vol 7 ◽  
Author(s):  
Aizhai Xiang ◽  
Xia Lin ◽  
Lvping Xu ◽  
Honggang Chen ◽  
Jufeng Guo ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
T Cells ◽  
Cancer Patients ◽  
Prognostic Biomarker ◽  
M2 Macrophage ◽  
Th1 Cell ◽  
Clinical Prognosis ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
Gastric Cancer Patients

BackgroundThe exact biological role of PCOLCE was not yet clear and there were few reports study the correlation of PCOLCE gene expression level with the occurrence and development of gastric cancer.MethodsThe expression of PCOLCE was analyzed by performing the Oncomine and Ualcan database. We evaluated the function of PCOLCE on clinical prognosis with the use of Kaplan–Meier plotter database. The relationship between PCOLCE and cancer immune in filtrates was researched by Tumor Immune Estimation Resource (TIMER) site database.ResultsPCOLCE significantly upregulated in gastric cancer patients compared to normal gastric samples. And the increased expression of PCOLCE mRNA was closely linked to shorter overall survival (OS), progress-free survival (PFS) in all gastric cancers. Besides, PCOLCE expression displayed a tight correlation with infiltrating levels of macrophages and dendritic cells (DCs) in gastric cancer. Moreover, PCOLCE expression was positively correlated with diverse immune marker sets in gastric cancer.ConclusionAll the results above suggested that overexpression of PCOLCE indicated unfavorable prognosis in patients with gastric cancer. PCOLCE was correlated with immune infiltrating levels including those of B cells, CD8 + T cells, CD4 + T cells, macrophages, neutrophils, and DCs in gastric cancer patients. All the findings suggested that PCOLCE could be used as a prognostic biomarker for determining prognosis and immune infiltration in gastric cancer. Additionally, PCOLCE expression potentially contributed to the regulation of monocyte, M2 macrophage, Tfh, CD8 + T cell, TAM, Th1 cell Thus PCOLCE is a potential target for gastric cancer therapy and these preliminary findings require further study to determine whether PCOLCE-targeting reagents might be developed for clinical application in gastric cancer.

Bioinformatics analysis of immune infiltration patterns in breast cancer for identification of prognostic markers

2019 ◽  
Author(s):  
Yan Yao ◽  
Tingting Zhang ◽  
Lingyu Qi ◽  
Ruijuan Liu ◽  
Gongxi Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
T Cells ◽  
Immune Cells ◽  
Prognostic Markers ◽  
T Cell Subsets ◽  
M2 Macrophage ◽  
M2 Macrophages ◽  
Clinical Prognosis ◽  
Immune Infiltration ◽  
Significant Difference

Abstract Background/purpose Cancer immunotherapy has revolutionized the clinical treatment of several tumors. Immune infiltration has been found to be closely related to clinical prognosis, but it shows limited activity in breast cancer (BC). Therefore, this study aimed to explore the infiltration pattern of immune cells in BC, and to find potential prognostic markers and new therapeutic targets.Patients and methods We downloaded the immune genome data of BC from the Cancer Genome Atlas (TCGA), and analyzed the tumor- infiltrating immune cells (TIICs) in BC for the first time using the CIBERSORT algorithm. The aim of this study was to assess the proportions of 22 immune cell subsets in BC and examine the correlation between each TIIC and overall survival (OS) as well as clinical characteristics.Results The results indicated that: (1) there was a significant difference between the immune infiltration spectrum of cancerous and adjacent tissues, with M2 macrophages, M0 macrophages, and CD4 + T cells being highly expressed in BC; (2) CD8 + T cells were positively correlated with activated CD4 + memory T cells and negatively correlated with M0 macrophages, and M2 macrophages was inversely correlated with M1 macrophages, T cells regulatory, T cells CD8; (3) T cells, macrophages and BC TNM stage, age, clinical stage were correlated (P < 0.05); and (4) high expression of M2 macrophage markers could be an independent biomarker of poor prognosis and a potential therapeutic target for BC.Conclusion This study provides a new research method for the systematic study of immune cells in the BC tumor microenvironment, and provides theoretical guidance for further experiments to verify M2 macrophages and T cell subsets as a potential target for immunotherapy and prognosis.

scholarly journals SNAP25 Is a Potential Prognostic Biomarker for Prostate Cancer

2021 ◽  
Author(s):  
Longjiang Di ◽  
Maoli Gu ◽  
Yan Wu ◽  
Guoqiang Liu ◽  
Lishuo Zhang ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
T Cells ◽  
Gene Ontology ◽  
Differentially Expressed Genes ◽  
Gleason Score ◽  
Immune Cells ◽  
Prognostic Biomarker ◽  
Differentially Expressed ◽  
Normal Prostate ◽  
Immune Infiltration

Abstract Background Prostate cancer is one of the most lethal cancers in male individuals. The Synaptosome associated protein 25 (SNAP25) gene is a key mediator of multiple biological functions in tumours. However, its significant impact on the prognosis in prostate cancer remains to be elucidated.Methods We performed a comprehensive analysis of the Cancer Genome Atlas dataset (TCGA) to identify the differentially expressed genes between prostate cancer and normal prostate tissue. We subjected the differentially expressed genes to gene ontology analysis and Kyoto Encyclopedia of Genes and Genomes functional analysis, and constructed a protein-protein interaction network. We then screened for pivotal genes to identify the hub genes of prognostic significance by performing Cox regression analysis. We identified SNAP25 as one such gene and analysed the relationship between its expression in prostate cancer to poor prognosis using Studio R. Results TCGA database demonstrated that SNAP25 was significantly downregulated in prostate cancer, and that its expression was significantly correlated with the Gleason score and pathological TNM stage of patients. The association between SNAP25 expression and tumour-infiltrating immune cells was evaluated using the Tumour Immune Estimation Resource site. Gene set enrichment and gene ontology analyses were used to analyse the function of SNAP25. We found that SNAP25 expression strongly correlated with overall survival in the Gleason score. In addition, SNAP25 was involved in the activation, differentiation, and migration of immune cells, and its expression was positively correlated with immune infiltration, including of B cells, CD8+ T cells, CD4+ T cells, neutrophils, dendritic cells, macrophages, and natural killer cells. SNAP25 expression was also positively correlated with chemokines/chemokine receptors, suggesting that SNAP25 might regulate the migration of immune cells. These molecular experiment results validate the low expression of SNAP25 seen in prostate cancer cells.Conclusion Our findings indicate a relationship between SNAP25 expression and prostate cancer, demonstrating that SNAP25 is a potential prognostic biomarker due to its vital role in immune infiltration.

scholarly journals Identification of Tumor Mutation Burden and Immune Infiltrates in Hepatocellular Carcinoma Based on Multi-Omics Analysis

2021 ◽  
Vol 7 ◽  
Author(s):  
Lu Yin ◽  
Liuzhi Zhou ◽  
Rujun Xu
Keyword(s):  
T Cells ◽  
Prediction Model ◽  
Risk Prediction ◽  
Immune Cell ◽  
Cox Regression ◽  
Area Under The Curve ◽  
Risk Prediction Model ◽  
Activated T Cells ◽  
Immune Infiltration ◽  
Differential Genes

We aimed to explore the tumor mutational burden (TMB) and immune infiltration in HCC and investigate new biomarkers for immunotherapy. Transcriptome and gene mutation data were downloaded from the GDC portal, including 374 HCC samples and 50 matched normal samples. Furthermore, we divided the samples into high and low TMB groups, and analyzed the differential genes between them with GO, KEGG, and GSEA. Cibersort was used to assess the immune cell infiltration in the samples. Finally, univariate and multivariate Cox regression analyses were performed to identify differential genes related to TMB and immune infiltration, and a risk prediction model was constructed. We found 10 frequently mutated genes, including TP53, TTN, CTNNB1, MUC16, ALB, PCLO, MUC, APOB, RYR2, and ABCA. Pathway analysis indicated that these TMB-related differential genes were mainly enriched in PI3K-AKT. Cibersort analysis showed that memory B cells (p = 0.02), CD8+ T cells (p = 0.09), CD4+ memory activated T cells (p = 0.07), and neutrophils (p = 0.06) demonstrated a difference in immune infiltration between high and low TMB groups. On multivariate analysis, GABRA3 (p = 0.05), CECR7 (p &lt; 0.001), TRIM16 (p = 0.003), and IL7R (p = 0.04) were associated with TMB and immune infiltration. The risk prediction model had an area under the curve (AUC) of 0.69, suggesting that patients with low risk had better survival outcomes. Our study demonstrated for the first time that CECR7, GABRA3, IL7R, and TRIM16L were associated with TMB and promoted antitumor immunity in HCC.

scholarly journals GRAP2 is a Prognostic Biomarker and Correlated with Immune Infiltration in Lung Adenocarcinoma

2022 ◽  
Author(s):  
Shimao Song ◽  
Xinzhou Deng ◽  
Jincheng Wang ◽  
Jiahui Han ◽  
Zhen Peng ◽  
...  
Keyword(s):  
Dendritic Cells ◽  
B Cells ◽  
Lung Adenocarcinoma ◽  
Prognostic Biomarker ◽  
Adaptor Protein ◽  
Primary Therapy ◽  
Clinical Prognosis ◽  
Immune Infiltration ◽  
Normal Tissues ◽  
Immunohistochemistry Staining

Abstract Background: GRAP2 is an adaptor protein involved in leukocyte-specific protein-tyrosine kinase signaling; however, the prognostic value of GRAP2 and its correlation with immune cell infiltration in lung adenocarcinoma (LUAD) remain unclear.Methods: All original data were downloaded from the TCGA database and integrated via R 3.2.2. GRAP2 expression was explored with the TCGA and TIMER databases. We evaluated the influence of GRAP2 on clinical prognosis using the Kaplan-Meier plotter, Gene Expression Omnibus (GEO) database and GEPIA database. Correlations between GRAP2 and cancer immune characteristics were analyzed via TIMER and TISIDB databases. Finally, we confirmed the expression of GRAP2 in LUAD by immunohistochemistry staining.Results: Transcription levels of GRAP2 were significantly lower in several human cancers, including LUAD, than in adjacent normal tissues. We also found that tumor tissues have lower protein expression levels of GRAP2 compared with adjacent normal tissues in LUAD by immunohistochemistry staining. The down-regulated GRAP2 was associated with poorer overall survival, pathologic stage, T stage, N stage and primary therapy outcome in LUAD. Mechanically, we identified a hub gene that included a total of 91 GRAP2 co-expressed genes, which were tightly associated with immune response in LUAD. GRAP2 expression was positively correlated with infiltrating levels of B cells, CD8+ T cells, dendritic cells, eosinophils, macrophages, mast cells, Th2 cells, Th1 cells, Th17 cells, NK cells and neutrophils. GRAP2 expression level also affected the cumulative survival time of B cells and dendritic cells. GRAP2 expression is positively correlated with multiple immune markers, chemokines, chemokine receptors and MHC molecules of LUAD.Conclusions: These findings suggest that GRAP2 is a tumor suppressor gene and can be used as a prognostic biomarker for determining prognosis and immune infiltration in LUAD.

scholarly journals Identification of Tumor Mutation Burden and Immune Infiltrates in Hepatocellular Carcinoma Based on Multi-Omics Analysis

2020 ◽  
Author(s):  
Lu Yin ◽  
Liuzhi Zhou ◽  
Rujun Xu
Keyword(s):  
T Cells ◽  
Prediction Model ◽  
Risk Prediction ◽  
Immune Cell ◽  
Cox Regression ◽  
Area Under The Curve ◽  
Risk Prediction Model ◽  
Activated T Cells ◽  
Immune Infiltration ◽  
Differential Genes

Abstract Background: We aimed to explore the tumor mutational burden (TMB) and immune infiltration in HCC and investigate new biomarkers for immunotherapy.Methods: Transcriptome and gene mutation data were downloaded from the GDC portal, including 374 HCC samples and 50 matched samples. Furthermore, we divided the samples into high and low TMB groups, and analyzed the differential genes between them with GO, KEGG, and GSEA. Cibersort was used to assess the immune cell infiltration in the samples. Finally, univariate and multivariate Cox regression analyses were performed to identify differential genes related to TMB and immune infiltration, and a risk prediction model was constructed.Results: We found 10 frequently mutated genes, including TP53, TTN, CTNNB1, MUC16, ALB, PCLO, MUC, APOB, RYR2, and ABCA. Pathway analysis indicated that these TMB-related differential genes were mainly enriched in PI3K-AKT. Cibersort analysis showed that memory B cells (P=0.02), CD8+ T cells (P=0.09), CD4+ memory activated T cells (P=0.07), and neutrophils (P=0.06) demonstrated a difference in immune infiltration between high and low TMB groups. On multivariate analysis, GABRA3 (P=0.05), CECR7 (P<0.001), TRIM16 (P=0.003), and IL7R (P=0.04) were associated with TMB and immune infiltration. The risk prediction model had an area under the curve (AUC) of 0.69, suggesting that patients with low risk had better survival outcomes.Conclusions: Our study demonstrated for the first time that CECR7, GABRA3, IL7R, and TRIM16L mutations were associated with TMB and promoted antitumor immunity in HCC.

scholarly journals CLEC10A is a Potential Prognostic Biomarker and Immune Regulator of Tumor Microenvironment in Breast Cancer

2021 ◽  
Author(s):  
Jincheng He ◽  
Lei Jiang ◽  
Jun Wang ◽  
Guangtao Min ◽  
Xiangwen Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
T Cells ◽  
B Cells ◽  
Tumor Microenvironment ◽  
Immune Cells ◽  
Cox Regression ◽  
Clinical Stage ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cox Regression Analysis

Abstract The communication between tumor cells and immune cells influences the ecology of the tumor microenvironment in breast cancer, as well as the disease progression and clinical outcome. The aim of this study was to investigate the prognostic value of the immunomodulatory factor CLEC10A in breast cancer. We applied the CIBERSORT and ESTIMATE calculation methods to calculate the proportion of tumor-infiltrating immune cells (TICs) and the amount of immune and stromal components in 1053 BRCA cases from The Cancer Genome Atlas (TCGA) database. The differentially expressed genes (DEGs) were analyzed by COX regression analysis and protein-protein interaction (PPI) network construction. Then, CLEC10A was identified as a prognostic factor by the intersection analysis of univariate COX and PPI. Further analysis revealed that CLEC10A expression was negatively correlated with the clinical pathologic characteristics (age, clinical stage) and positively correlated with survival of BRCA patients. Gene set enrichment analysis (GSEA) showed that genes in the high CLEC10A expression group were mainly enriched in immune-related activities. Genes in the low CLEC10A expression group were enriched in biochemical functions. CIBERSORT analysis of the proportion of TICs revealed that Macrophages M1, B cells memory, B cells naive, T cells CD4+ memory activated, T cells CD8+, and T cells gamma delta were positively correlated with CLEC10A expression, and Macrophages M0, Macrophages M2, Neutrophils, and NK cells resting were positively correlated with CLEC10A expression was negatively correlated, suggesting that CLEC10A may be an important factor in the immune regulation of the tumor microenvironment, especially in mediating the anti-tumor immune response of tumor-infiltrating immune cells at the tumor initiation stage. Therefore, CLEC10A expression may contribute to the prognosis of BRCA patients and provide a new idea for the immunotherapy of BRCA.

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

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhicheng Hu ◽  
Shanqiang Qu
Keyword(s):  
Immune Cells ◽  
Human Cancer ◽  
World Health ◽  
Poor Overall Survival ◽  
Who Grade ◽  
Clinical Prognosis ◽  
Immune Infiltration ◽  
Potential Biomarker ◽  
Grade Ii ◽  
Health Organization

BackgroundImmunotherapy 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.MethodsThe 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.ResultsIn 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.ConclusionsFor 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.

Sign in / Sign up

Export Citation Format

Share Document