High expression of TREM2 promotes EMT via the PI3K/AKT pathway in gastric cancer: bioinformatics analysis and experimental verification

Abstract Background: Gastric cancer (GC) is one of the most common cancers with one of the highest mortality rates. Unfortunately, underlying molecular mechanisms contributing to GC have not been fully illuminated. PABPC1 is involved in a series of processes, such as mRNA translation, and mRNA deadenylation and decay. We performed this study to clarify the role of PABPC1 in GC. Methods: To evaluate PABPC1 expressions in GC and normal tissues, we performed bioinformatics analysis of data from TCGA. PABPC1 expressions were evaluated by immunohistochemical (IHC) staining of 170 GC specimens. Associations between PABPC1 expression and clinicopathological variables were analyzed. Independent predictive factors for survival of GC patients were determined by Cox regression analysis. Results: It was revealed by bioinformatics analysis that compared with normal gastric tissues, PABPC1 expressions in GC tissues were significantly higher (P=0.002, paired) (P=3.605e^-9, unpaired). It was revealed that PABPC1 expression was significantly associated with tumor size (P=0.008), Borrmann classification (P=0.003), vessel invasion (P=0.017), depth of invasion (P=0.032), lymph node metastasis (P=0.001), and TNM stage (P=0.019). It was demonstrated through Cox regression analysis that PABPC1 expression was a predictive factor for both overall survival (OS) (P<0.001) and disease-free survival (DFS) (P<0.001) of GC patients. Conclusions: Compared with that of normal gastric tissue, expression level of PABPC1 in GC tissue was significantly higher and PABPC1,s high expression was significantly associated with poorer survival, suggesting its potential as a therapeutic biomarker for GC.

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MiR-203 Mimic Down-Regulates Baculoviral IAP Repeat Containing 5 Expression and Affects Proliferation and Apoptosis of Gastric Cancer Cells

Journal of Biomaterials and Tissue Engineering ◽

10.1166/jbt.2020.2215 ◽

2020 ◽

Vol 10 (1) ◽

pp. 81-86

Author(s):

Yanhua Xu ◽

Pailan Peng ◽

Qiuyuan Zhou

Keyword(s):

Gastric Cancer ◽

Cell Proliferation ◽

Cancer Cells ◽

Real Time Pcr ◽

Cell Apoptosis ◽

Bioinformatics Analysis ◽

Gastric Cancer Cells ◽

Tumor Tissues ◽

Proliferation And Apoptosis ◽

Cancer Bioinformatics

Human baculovirus IAP repeats containing protein 5 (BIRC5) is the most inhibitor of cell apoptosis. Abnormal miR-203 level is associated with the pathogenesis of gastric cancer. Bioinformatics analysis revealed a relationship between miR-203 and BIRC5. Our study assessed miR-203’s role in gastric cancer cells. Tumor tissues and adjacent tissues were collected. miR-203 and BIRC5 mRNA expression in SGC7901 and MKN45 cells was detected by real-time PCR. SGC7901 cells were divided into miR-NC group and miR-203 mimic group followed by analysis of cell proliferation by EdU staining. Compared to adjacent tissues, miR-203 level was decreased and BIRC5 was increased. There was a targeted relationship between miR-203 and BIRC5. Compared with RGM- 1 cells, miR-203 in SGC7901 and MKN45 cells was significantly downregulated and BIRC5 was upregulated. miR-203 mimic significantly downregulated BIRC5 in SGC7901 cells, promoted cell apoptosis, and attenuated cell proliferation. Decreased miR-203 expression and increased BIRC5 expression is associated with the pathogenesis of gastric cancer. MiR-203 can inhibit the expression of BIRC5, inhibit proliferation of gastric cancer cells and induce apoptosis.

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Identification of Novel Prognostic Biomarkers to Predict Pembrolizumab Response in Gastric Cancer by Bioinformatics Analysis

10.21203/rs.3.rs-784591/v1 ◽

2021 ◽

Author(s):

Si-Yu Liu ◽

Ling-yan He ◽

Mei-ling Lv ◽

Wei-liang Sun

Keyword(s):

Gastric Cancer ◽

Bioinformatics Analysis ◽

Immune Cell ◽

Checkpoint Inhibitors ◽

Predictive Ability ◽

Metastatic Gastric Cancer ◽

Gene Expression Omnibus ◽

High Expression ◽

Hub Gene ◽

Low Sensitivity

Abstract Immune checkpoint inhibitors (ICIs), especially pembrolizumab, have improved outcomes in patients with advanced or metastatic gastric cancer (GC). However, there are no reliable markers for the evaluation of its efficacy. GC samples from the UCSC Xena Browser and Gene Expression Omnibus (GEO) databases were performed by bioinformatics analysis. The single sample gene set enrichment (ssGSEA) algorithm was used to calculate the prognostic genes expression differences score (ssGSEA score) for each sample. Weighted gene co-expression network analysis (WGCNA) was applied to identify the score-related key model. The hub gene was identified based on the intersection between tumor-related transcription factors (TFs) and the key module. The predictive ability for pembrolizumab response of the hub gene was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC). The correlations between the hub gene and immune infiltration in GC were investigated by the CIBERSORT algorithm. According to the ssGSEA score, patients with GC were divided into the high- and low-score group. RUNX1T1 was the hub gene of the ICIs treatment in GC. Its high expression was related to the low-score group, which indicated low sensitivity to pembrolizumab and poor prognosis. RUNX1T1 showed good predictive power for pembrolizumab response (AUC = 0.742). The CIBERSORT analysis showed that a high expression for RUNX1T1 weakened the anti-tumor immune response by affecting the immune cell infiltration.Runx1T1 may be a potential predictor of pembrolizumab efficacy in GC and be a prognostic marker for GC.

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Bioinformatics Analysis Identifies CPZ as a Tumor Immunology Biomarker For Gastric Cancer

Current Bioinformatics ◽

10.2174/1574893615999200707145643 ◽

2020 ◽

Vol 15 ◽

Author(s):

Yuan Gu ◽

Ying Gao ◽

Xiaodan Tang ◽

Huizhong Xia ◽

Kunhe Shi

Keyword(s):

Gastric Cancer ◽

T Cells ◽

Signaling Pathway ◽

Tumor Immunology ◽

Bioinformatics Analysis ◽

Human Cancer ◽

Disease Free Survival ◽

Kaplan Meier ◽

Potential Biomarker ◽

Pathway Regulation

Background: Gastric cancer (GC) is one of the most common malignancies worldwide. However, the biomarkers for the prognosis and diagnosis of Gastric cancer were still need. Objective: The present study aimed to evaluate whether CPZ could be a potential biomarker for GC. Method: Kaplan-Meier plotter (http://kmplot.com/analysis/) was used to determine the correlation between CPZ expression and overall survival (OS) and disease-free survival (DFS) time in GC [9]. We analyzed CPZ expression in different types of cancer and the correlation of CPZ expression with the abundance of immune infiltrates, including B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells, via gene modules using TIMER Database. Results: The present study identified that CPZ was overexpressed in multiple types of human cancer, including Gastric cancer. We found that overexpression of CPZ correlates to the poor prognosis of patients with STAD. Furthermore, our analyses show that immune infiltration levels and diverse immune marker sets are correlated with levels of CPZ expression in STAD. Bioinformatics analysis revealed that CPZ was involved in regulating multiple pathways, including PI3K-Akt signaling pathway, cGMP-PKG signaling pathway, Rap1 signaling pathway, TGF-beta signaling pathway, regulation of cell adhesion, extracellular matrix organization, collagen fibril organization, collagen catabolic process. Conclusion: This study for the first time provides useful information to understand the potential roles of CPZ in tumor immunology and validate it to be a potential biomarker for GC.

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