Dataset Information

GRN is a prognostic biomarker and correlated with immune infiltration in glioma: A study based on TCGA data.

ABSTRACT:

Background

Among primary brain tumors, gliomas are associated with a poor prognosis and a median survival that varies depending on the tumor grade and subtype. As the most malignant form of glioma, glioblastoma (GBM) constitutes a significant health concern. Alteration in granulin(GRN) has been proved to be accountable for several diseases. However, the relationship between GRN and GBM remains unclear. We evaluated the role of GRN in GBM through The Cancer Genome Atlas (TCGA) database.

Methods

First, we assessed the relationship between GRN and GBM through the GEPIA database. Next, the relationship between GRN and GBM prognosis was analyzed by logistic regression and multivariate cox methods. Using CIBERSORT and the GEPIA correlation module, we also investigated the link between GRN and immune infiltrates in cancer. Using the TCGA data, a gene set enrichment analysis (GSEA) was performed. We also employed Tumor Immune Estimation Resource (TIMER) to examine the data set of GRN expression and immune infiltration level in GBM and investigate the cumulative survival in GBM. We also validated tissues from GBM patients by Western blotting, RT-qPCR, and immunohistochemistry.

Results

Increased GRN expression was shown to have a significant relationship to tumor grade in a univariate study utilizing logistic regression. Furthermore, multivariate analysis disclosed that GRN expression down-regulation is an independent predictive factor for a favorable outcome. GRN expression level positively correlates with the number of CD4+ T cells, neutrophils, macrophages, and dendritic cells (DCs) that infiltrate a GBM. The GSEA also found that the high GRN expression phenotype pathway was enriched for genes involved in immune response molecular mediator production, lymphocyte-mediated immunity, cytokine-mediated signaling pathway, leukocyte proliferation, cell chemotaxis, and CD4+ alpha beta T cell activation. Differentially enriched pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) include lysosome, apoptosis, primary immunodeficiency, chemokine signaling pathway, natural killer cell-mediated cytotoxicity, and B cell receptor signaling pathway. Validated result showed that GRN was upregulated in GBM tissues. These results suggested that GRN was a potential indicator for the status of GBM.

Conclusion

GRN is a prognostic biomarker and correlated with immune infiltrates in GBM.

SUBMITTER: Xu SM

PROVIDER: S-EPMC10117795 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

GRN is a prognostic biomarker and correlated with immune infiltration in glioma: A study based on TCGA data.

Xu Su-Mei SM Xiao Hai-Yan HY Hu Zhong-Xu ZX Zhong Xue-Feng XF Zeng You-Jie YJ Wu You-Xuan YX Li Dai D Song Tao T

Frontiers in oncology 20230406

<h4>Background</h4>Among primary brain tumors, gliomas are associated with a poor prognosis and a median survival that varies depending on the tumor grade and subtype. As the most malignant form of glioma, glioblastoma (GBM) constitutes a significant health concern. Alteration in granulin(GRN) has been proved to be accountable for several diseases. However, the relationship between GRN and GBM remains unclear. We evaluated the role of GRN in GBM through The Cancer Genome Atlas (TCGA) database.<h ...[more]

PMID: 37091137

Similar Datasets

Project description:ObjectiveGlioma accounts for the vast majority of primary brain tumors with inevitable recurrence and poor prognosis. Maternal embryonic leucine zipper kinase (MELK) is overexpressed in multiple human tumors and could activate a variety of oncogenic-associated signal pathways. However, its role in the glioma microenvironment is still largely unknown.MethodsWe collected the RNA sequence data and clinical information of gliomas from the Chinese Glioma Genome Atlas (CGGA), The Cancer Genome Atlas (TCGA), and the Gene Expression Omnibus (GEO) databases, and investigated MELK expression and its correlation with clinicopathologic features and prognosis in glioma. Moreover, the relationship between MELK expression and immune cell infiltration in the tumor microenvironment of gliomas was explored through single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT. In addition, gene set enrichment analysis (GSEA) and Metascape online analysis were performed to find out signaling pathways enriched by differentially expressed genes (DEGs) between high- and low-MELK expression groups. Finally, immunohistochemistry was performed to validate our findings.ResultsData analysis of CGGA and GEO datasets showed that MELK was significantly upregulated in gliomas than in normal brain tissues, and MELK expression was obviously correlated with clinicopathologic features, including age, WHO grade, histological subtype, IDH mutant status, 1p19q codeletion status, and PRS type. Stratified analysis, Cox regression analysis, and nomogram model revealed that high expression of MELK predicted poor survival; hence, MELK could serve as an independent prognostic biomarker for glioma. Moreover, results from enrichment pathway analysis indicated that the immune system process, angiogenesis, apoptosis, cell cycle, and other oncogenic-related signal pathways were significantly enriched between high- and low-MELK expression groups. Immune infiltration analysis demonstrated that increased MELK expression was significantly correlated with higher immune scores, higher fractions of immunocytes (T cells, NK cells resting, macrophages, resting mast cells, and neutrophils), and higher expression levels of immune checkpoints (B7-H3, CTLA4, LAG3, PD-1, PD-L1, and TIM3). Finally, immunohistochemistry analysis validated our findings that high expression of MELK relates to increased malignancy and poor prognosis of glioma.ConclusionOur findings identified that MELK could act as an independent prognostic indicator and potential immunotherapy target for glioma. In conclusion, these findings suggested that DDOST mediated the immunosuppressive microenvironment of gliomas and could be an important biomarker in diagnosing and treating gliomas.

Project description:Background: Centromeric protein A (CENP-A), an essential protein involved in chromosomal segregation during cell division, is associated with several cancer types. However, its role in gliomas remains unclear. This study examined the clinical and prognostic significance of CENP-A in gliomas. Methods: Data of patients with glioma were collected from the Cancer Genome Atlas. Logistic regression, the Kruskal-Wallis test, and the Wilcoxon signed-rank test were performed to assess the relationship between CENP-A expression and clinicopathological parameters. The Cox regression model and Kaplan-Meier curve were used to analyze the association between CENP-A and survival outcomes. A prognostic nomogram was constructed based on Cox multivariate analysis. Gene set enrichment analysis (GSEA) was conducted to identify key CENP-A-related pathways and biological processes. Results: CENP-A was upregulated in glioma samples. Increased CENP-A levels were significantly associated with the world health organization (WHO) grade [Odds ratio (OR) = 49.88 (23.52-129.06) for grade 4 vs. grades 2 and 3], primary therapy outcome [OR = 2.44 (1.64-3.68) for progressive disease (PD) and stable disease (SD) vs. partial response (PR) and complete response (CR)], isocitrate dehydrogenase (IDH) status [OR = 13.76 (9.25-20.96) for wild-type vs. mutant], 1p/19q co-deletion [OR = 5.91 (3.95-9.06) for no codeletion vs. co-deletion], and age [OR = 4.02 (2.68-6.18) for > 60 vs. ≤ 60]. Elevated CENP-A expression was correlated with shorter overall survival in both univariate [hazard ratio (HR): 5.422; 95% confidence interval (CI): 4.044-7.271; p < 0.001] and multivariate analyses (HR: 1.967; 95% CI: 1.280-3.025; p < 0.002). GSEA showed enrichment of numerous cell cycle-and tumor-related pathways in the CENP-A high expression phenotype. The calibration plot and C-index indicated the favorable performance of our nomogram for prognostic prediction in patients with glioma. Conclusion: We propose a role for CENP-A in glioma progression and its potential as a biomarker for glioma diagnosis and prognosis.

Project description:Background: BTBD10 serves as an activator of Akt family members through decreasing the protein phosphatase 2A-mediated dephosphorylation. The present study attempted to investigate the prognostic value of BTBD10 in hepatocellular carcinoma (HCC), specially, its relationship with tumor-infiltrating lymphocytes (TILs). Methods: BTBD10 expression was evaluated in HCC using The Cancer Genome Atlas (TCGA) and Xijing Hospital database, and verified in HCC cell lines. Cox analyses were performed to analyze independent prognostic risk factors for HCC. The optimal cut-off value of BTBD10 was calculated, by which all patients were divided into two groups to compare the overall survival (OS). The signaling pathways were predicted, by which BTBD10 may affect the progression of HCC. To investigate the impact of BTBD10 on HCC immunotherapy, correlations between BTBD10 and TILs, immune checkpoints, m6A methylation-related genes and ferroptosis-related genes were assessed. The distribution of half-maximal inhibitory concentration (IC50) of diverse targeted drugs was observed based on the differential expression of BTBD10. Results: BTBD10 expression was higher in HCC tissues and cell lines than that of normal liver tissues and cells. The patients with high expression of BTBD10 showed a worse OS, as compared to that of BTBD10 low-expressing group. Cox analyses indicated that BTBD10 was an independent prognostic risk factor for HCC. Several molecular pathways of immune responses were activated in HCC patients with high-expressing of BTBD10. Furthermore, BTBD10 expression was demonstrated to be positively correlated with tumor-infiltrating B cells, T cells, macrophages, neutrophils and dendritic cells. Meanwhile, the expression of BTBD10 was synchronized with that of several m6A methylation-related genes, ferroptosis-related genes and immune checkpoints. The IC50 scores of Sorafenib, Navitoclax, Veliparib, Luminespib, and Imatinib were found to be lower in BTBD10 high-expressing HCC group. Conclusion: BTBD10 negatively regulates tumor immunity in HCC and exhibits adverse effect on the prognosis of HCC, which could be a potential target for immunotherapy.

Project description:The poliovirus receptor (PVR) is a member of the immunoglobulin superfamily (Ig SF) and is essential for the promotion of cancer cell proliferation and invasion. However, the correlation between PVR expression and prognosis as well as immune infiltration in hepatocellular carcinoma (HCC) remains unclear. The expression level of PVR was quantified using the Tumor and Tumor Immunity Evaluation Resource (TIMER) and Sangerbox. The Gene Expression Omnibus (GEO) database was used to validate the PVR expression. The receiver operating characteristic (ROC) curve was used to evaluate the feasibility of using PVR as a differentiating factor according to the area under curve (AUC) score. A PVR binding protein network was built using the STRING tool. An enrichment analysis using the R package clusterProfiler was used to explore the potential function of PVR. Immune infiltration analysis was calculated with ESTIMATE algorithms. We also assessed the correlation between PVR expression and immune infiltration by the single-sample Gene Set Enrichment Analysis (ssGSEA) method from the R package GSVA and TIMER database. The results showed that PVR was commonly overexpressed in multiple types of tumors including HCC. The data of GSE64041 confirmed the same result. The ROC curve suggested that PVR could be a potential diagnostic biomarker. Additionally, high mRNA expression of PVR in HCC was significantly correlated with poor overall survival (OS) and relapse free survival (RFS). Results also indicated correlations between PVR mRNA expression with the level of infiltration immune cells including B cells, CD8+ T cells, cytotoxic cells, DCs, CD56dim NK cells, pDCs, and Th2 cells. Furthermore, the PVR level was significantly correlated with immune markers for immunosuppressive cells in HCC. In conclusion, PVR might be an important regulator of tumor immune cell infiltration and a valuable prognostic biomarker in HCC. However, additional work is needed to fully elucidate the underlying mechanisms.

Dataset Information

GRN is a prognostic biomarker and correlated with immune infiltration in glioma: A study based on TCGA data.

Background

Methods

Results

Conclusion

Publications

GRN is a prognostic biomarker and correlated with immune infiltration in glioma: A study based on TCGA data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets