Dataset Information

Characterization of Hypoxia Signature to Evaluate the Tumor Immune Microenvironment and Predict Prognosis in Glioma Groups.

ABSTRACT: Glioma groups, including lower-grade glioma (LGG) and glioblastoma multiforme (GBM), are the most common primary brain tumor. Malignant gliomas, especially glioblastomas, are associated with a dismal prognosis. Hypoxia is a driver of the malignant phenotype in glioma groups; it triggers a cascade of immunosuppressive processes and malignant cellular responses (tumor progression, anti-apoptosis, and resistance to chemoradiotherapy), which result in disease progression and poor prognosis. However, approaches to determine the extent of hypoxia in the tumor microenvironment are still unclear. Here, we downloaded 575 LGG patients and 354 GBM patients from Chinese Glioma Genome Atlas (GGGA), and 530 LGG patients and 167 GBM patients from The Cancer Genome Atlas (TCGA) with RNA sequence and clinicopathological data. We developed a hypoxia risk model to reflect the immune microenvironment in glioma and predict prognosis. High hypoxia risk score was associated with poor prognosis and indicated an immunosuppressive microenvironment. Hypoxia signature significantly correlated with clinical and molecular features and could serve as an independent prognostic factor for glioma patients. Moreover, Gene Set Enrichment Analysis showed that gene sets associated with the high-risk group were involved in carcinogenesis and immunosuppression signaling. In conclusion, we developed and validated a hypoxia risk model, which served as an independent prognostic indicator and reflected overall immune response intensity in the glioma microenvironment.

SUBMITTER: Lin W

PROVIDER: S-EPMC7243125 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Characterization of Hypoxia Signature to Evaluate the Tumor Immune Microenvironment and Predict Prognosis in Glioma Groups.

Lin Wanzun W Wu Shihong S Chen Xiaochuan X Ye Yuling Y Weng Youliang Y Pan Yuhui Y Chen Zhangjie Z Chen Long L Qiu Xianxin X Qiu Sufang S

Frontiers in oncology 20200515

Glioma groups, including lower-grade glioma (LGG) and glioblastoma multiforme (GBM), are the most common primary brain tumor. Malignant gliomas, especially glioblastomas, are associated with a dismal prognosis. Hypoxia is a driver of the malignant phenotype in glioma groups; it triggers a cascade of immunosuppressive processes and malignant cellular responses (tumor progression, anti-apoptosis, and resistance to chemoradiotherapy), which result in disease progression and poor prognosis. However, ...[more]

PMID: 32500034

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Project description: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.

Project description:Hypoxia, a typical hallmark of numerous tumors, indicates poor infiltration of antitumor lymphocytes, as well as facilitates the development, progression, and drug resistance of malignant cells. Here, the present research was performed to identify novel hypoxia-related molecular markers and their correlation to the tumor immune microenvironment (TIME) in colon cancer. The expression of hypoxia-related gene signature was extracted from The Cancer Genome Atlas (TCGA) COAD cohort. Based on this signature, a risk score model was constructed using the Lasso regression model. Its discrimination ability and stability were validated in another independent cohort (GSE17536) from Gene Expression Omnibus (GEO) database. Moreover, molecular biology experiments (quantitative real-time PCR and multiple immunohistochemistry) were performed to validate the results of bioinformatics analyses. Three hub genes, including PPFIA4, SERPINE1, and STC2, were chosen to build the risk score model. All of these genes were increasingly expressed in the hypoxia subgroup (HS). Compared with the normoxia subgroup (NS), HS had worse pathological features (T, N, M, and stage) and overall survival (OS), more expression of immune checkpoint molecules, poorer infiltration of some pro-inflammation immune cells (CD4+ T cells and CD8+ T cells), and enriched infiltration of M0/M2 macrophages. After the risk model was proven to be valuable and stable, a nomogram was built based on this model and some clinicopathological factors. Moreover, it had been identified that three hub genes were all increasingly expressed in hypoxic conditions by quantitative real-time PCR (qPCR). The results of multiple immunohistochemistry (mIHC) also showed that higher expression of hub genes was associated with poorer infiltration of pro-inflammation immune cells (CD8+ T cells and M1 macrophages) and richer infiltration of anti-inflammation immune cells (Treg cells and M2 macrophages). In conclusion, the present study uncovered the relations among hypoxia, TIME, and clinicopathological features of colon cancer. It might provide new insight and a potential therapeutic target for immunotherapy.

Dataset Information

Characterization of Hypoxia Signature to Evaluate the Tumor Immune Microenvironment and Predict Prognosis in Glioma Groups.

Publications

Characterization of Hypoxia Signature to Evaluate the Tumor Immune Microenvironment and Predict Prognosis in Glioma Groups.

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