Dataset Information

Association Between EphA1 and Tumor Microenvironment in Gastric Carcinoma and its Clinical Significance.

ABSTRACT: BACKGROUND With the growing global burden of gastric carcinoma (GC) and the urgent need for biomolecular targeted therapies, this study aimed to elucidate the relationship between EphA1 and the tumor microenvironment (focusing primarily on the key inflammatory cytokines IL-6 and tumor angiogenic cytokine VEGF) to identify a new potential therapeutic target. MATERIAL AND METHODS IHC and qRT-PCR were performed to quantify the protein and gene expression levels of EphA1, IL-6, and VEGF in normal mucosal tissues, carcinoma tissues, and paracarcinomatous tissues from 57 GC patients. Spearman's rank correlation test was performed to determine the relationship between EphA1, IL-6, and VEGF expression levels. The relationships of EphA1 with clinicopathologic parameter and survival in GC patients were also evaluated. RESULTS The protein and gene expression levels of EphA1 were all attenuated gradually from carcinoma tissues to paracarcinomatous tissues and then to normal mucosal tissues in GC patients. Additionally, significant correlations between the overexpression of EphA1 with aggressive clinicopathological features and shorter survival time of GC patients were verified. In particular, we found a significant positive correlation between the expression of EphA1 and tumor microenvironment hallmark proteins IL-6 and VEGF in carcinoma tissues and paracarcinomatous tissues. CONCLUSIONS EphA1 can promote the occurrence and development of GC by its selective high expression in cancer tissues and its relationship with malignant clinical features and prognosis of GC patients. The underlying potential mechanism appears to involve enhancement of the tumor microenvironment, which via drives the expression of tumor microenvironment hallmark proteins IL-6 and VEGF.

SUBMITTER: Wang YC

PROVIDER: S-EPMC7133419 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Association Between EphA1 and Tumor Microenvironment in Gastric Carcinoma and its Clinical Significance.

Wang Yong-Cang YC Dai Yin Y Xu Ge-Liang GL Yu Wei W Quan Rui-Liang RL Zhao Ya-Jun YJ

Medical science monitor : international medical journal of experimental and clinical research 20200327

BACKGROUND With the growing global burden of gastric carcinoma (GC) and the urgent need for biomolecular targeted therapies, this study aimed to elucidate the relationship between EphA1 and the tumor microenvironment (focusing primarily on the key inflammatory cytokines IL-6 and tumor angiogenic cytokine VEGF) to identify a new potential therapeutic target. MATERIAL AND METHODS IHC and qRT-PCR were performed to quantify the protein and gene expression levels of EphA1, IL-6, and VEGF in normal mu ...[more]

PMID: 32218416

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Project description:Background: Gastric carcinoma (GC) is a carcinoma with a high incidence rate, and it is a deadly carcinoma globally. An effective tool, that is, able to predict different survival outcomes for GC patients receiving individualized treatments is deeply needed. Methods: In total, data from 975 GC patients were collected from TCGA-STAD, GSE15459, and GSE84437. Then, we performed a comprehensive unsupervised clustering analysis based on 54 TGFβ-pathway-related genes and correlated these patterns with tumor microenvironment (TME) cell-infiltrating characteristics. WGCNA was then applied to find the module that had the closest relation with these patterns. The least absolute shrinkage and selection operator (LASSO) algorithm was combined with cross validation to narrow down variables and random survival forest (RSF) was used to create a risk score. Results: We identified two different TGFβ regulation patterns and named them as TGFβ Cluster 1 and Cluster 2. TGFβ Cluster 1 was linked to significantly poorer survival outcomes and represented an inflamed TME subtype of GC. Using WGCNA, a module (magenta) with the closest association with the TGFβ clusters was identified. After narrowing down the gene list by univariate Cox regression analysis, the LASSO algorithm and cross validation, four of the 243 genes in the magenta module were applied to build a risk score. The group with a higher risk score exhibited a considerably poorer survival outcome with high predictive accuracy. The risk score remained an independent risk factor in multivariate Cox analysis. Moreover, we validated this risk score using GSE15459 and GSE84437. Furthermore, we found that the group with a higher risk score represented an inflamed TME according to the evidence that the risk score was remarkably correlated with several steps of cancer immunity cycles and a majority of the infiltrating immune cells. Consistently, the risk score was significantly related to immune checkpoint genes and T cell-inflamed gene expression profiles (GEPs), indicating the value of predicting immunotherapy. Conclusions: We have developed and validated a TGFβ-associated signature, that is, capable of predicting the survival outcome as well as depicting the TME immune characteristics of GC. In summary, this signature may contribute to precision medicine for GC.

Project description:BackgroundIt was reported that tumor heterogeneity and the surrounding tumor microenvironment (TME) in ovarian cancer affects immunotherapy efficacy and patient outcomes. And the TME of ovarian cancer is intrinsically heterogeneous. CD47 plays vital roles in cell functional behavior and immune homeostasis relating to cancer prognosis. But how it affects TME and its contribution to heterogeneity in ovarian cancer has not been fully illustrated. Therefore, we aimed to identify a prognostic biomarker which may help explain tumor immune microenvironment heterogeneity of ovarian cancer.MethodsCancer single-cell state atlas (CancerSEA) was used to evaluate functional role of CD47. Several bioinformatics database including Oncomine, Gene Expression Profiling Interaction Analysis (GEPIA), Tumor Immune Estimation Resource (TIMER), The Human Protein Atlas (HPA), Ualcan and Kaplan-Meier plotter (KM plotter) were applied to illustrate correlation of CD47 with ovarian cancer prognosis and immune infiltration. Tumor Immune Single-cell Hub (TISCH) single cell database was employed to evaluate correlation of CD47 with tumor microenvironment. GeneMANIA was implemented to identify regulation networks of CD47. Differentially expressed genes (DEGs) between CD47 high and low expression groups were analyzed with R package DESeq2. Kyoto encyclopedia of genes and genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) were utilized to explore how CD47 affect the immune related cell signaling pathway.ResultsCD47 expression was upregulated and connected to worse OS and PFS in ovarian cancer. Close relation was found between CD47 expression level and immune infiltration in ovarian cancer, especially with Treg cells, Monocytes, Macrophages and T cell exhaustion (P<0.05). The CD47 expression level was relatively low in plasma cells, dendritic cells and Mono/Macro cells of OV_GSE115007, in myofibroblasts, fibroblasts and endothelial cells of OV_GSE118828, compared to malignant cells of OV_GSE118828 dataset. The cell components and distribution in primary and metastatic ovarian cancer are quite distinct, which may lead to TME heterogeneity of ovarian cancer.ConclusionOur results indicated that CD47 is closely correlated to ovarian cancer immune microenvironment and might induce ovarian cancer heterogeneity. Therefore, CD47 may be used as a candidate prognostic biomarker and provide us with new insights into potential immunotherapy in ovarian cancer patients.

Dataset Information

Association Between EphA1 and Tumor Microenvironment in Gastric Carcinoma and its Clinical Significance.

Publications

Association Between EphA1 and Tumor Microenvironment in Gastric Carcinoma and its Clinical Significance.

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