Gene Expression Profiles Of Gastric Cancer Research Articles

Therapeutic effect of microRNA-21 on differentially expressed hub genes in gastric cancer based on systems biology

Gastric cancer (GC) is a leading cause of mortality for many people. Cancer’s initiating factors are poorly understood. miR-21 has a crucial function in several malignancies, particularly GC. Furthermore, it has been shown that miR-21 is critical for the emergence and advancement of GC. This work intends to identify new genes which expression is associated with the activity of mir-21 in GC and to investigate the effect of downregulation of mir-21 on these genes and gastric tumorigenesis. We utilized the gene expression profiles of GCs from an Array database (GSE13911) from the Gene Expression Omnibus (GEO) dataset to find differentially expressed genes (DEGs) between control and gastric cancer groups. Using weighted gene correlation network analysis (WGCNA) in R, the Gene co-expression network was reconstructed. The microRNA–mRNA network was then reconstructed using the miRWalk database, and by investigating the microRNA–mRNA network, the genes that have an association with mir-21 were found. To implement the functional investigation, MKN and AGS cell lines were transfected with anti-miR-21 next. Subsequently, MTT proliferation was utilized to assess the cell's vitality. qRT-PCR was then used to evaluate the anticipated levels of gene expression in both GC cell lines. This study discovered and predicted CCL28, NR3C2, and SNYPO2 as the targets of miR-21 (GC), which are downregulated through gastric tumorigenesis, showing great potential as therapeutic and diagnostic targets. The suppression of miR-21 in gastric GC cells led to the inhibition of cell proliferation and decreased expression of CCL28, NR3C2, and SNYPO2 genes. This study established that miR-21, via downregulating these genes, contributes significantly to the development of GC. In addition, systems biology techniques identified CCL28, NR3C2, and SNYPO2 genes as possible GC surveillance and therapy components.

Investigation of target genes and potential mechanisms related to compound Xiao-ai-fei honey ointment based on network pharmacology and bioinformatics analysis.

Compound Xiao-ai-fei honey ointment (CXHO) is an anticancer preparation with a long history in Uyghur folk medicine in China and has been used for the treatment of gastric cancer (GC) in Xinjiang, China. Nevertheless, the mechanism of its anticancer effect remains to be investigated. Bioactive ingredients of CXHO were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database. Target genes of ingredients were acquired via the PubChem and Swiss target prediction database. Gene expression profiling of GC was obtained from GSE54129 in the GEO database and analyzed using the limma package in R. The hub genes associated with CXHO in GC were validated using the TIMER2.0 database, GEPIA2 database and Auto Dock tools. The effect of CXHO on migration of GC cells was detected by Transwell chamber assay and Wound healing assay. The effect of CXHO on expression levels of MMP2/MMP9 and NF-κb, PI3K/AKT signaling pathway was detected by Western blot assay. Forty-five bioactive ingredients and their 819 related genes were found. A total of 462 differentially expressed genes were identified between GC patients and healthy controls. Seventeen common target genes were identified as hub genes CXHO against GC. Among them, MMP2 and MMP9 were significantly associated with tumor immune infiltrates and had good binding affinity with effective ingredients. Moreover, we validated the mRNA and protein expression levels and prognostic value of MMP2 and MMP9 by different databases. In addition, Kyoto encyclopedia of genes and genomes and gene ontology analyses showed that the 17 common target genes were mainly involved in steroid hormone biosynthesis and cancer-related pathways. Experimental results showed that CXHO inhibited migration of GC cells and down regulated the expression levels of MMP2/MMP9, NF-κb. In addition, CXHO can inhibited PI3K/AKT signaling pathway. We identified and experimental validated 2 pivotal target genes of CXHO against GC and preliminarily analyzed the potential mechanisms by which CXHO inhibits the development of GC. All these findings support CXHO as a promising drug for the treatment of GC.

TRPV2 Promotes Cell Migration and Invasion in Gastric Cancer via the Transforming Growth Factor-β Signaling Pathway.

Transient receptor potential vanilloid 2 (TRPV2) is a highly Ca2+-permeable ion channel that is involved in a number of cellular processes. It is expressed in various human cancers; however, the role of TRPV2 in gastric cancer (GC) remains poorly understood. TRPV2 gene expression was knocked down in GC cell lines by small-interfering RNA (siRNA), and the biological roles of TRPV2 in the proliferation, migration, and invasion of GC cells were then investigated. The gene expression profile of GC was elucidated using a microarray analysis. TRPV2 expression in tumor tissue sections was analyzed by immunohistochemistry. The migration and invasion abilities of GC cells were inhibited by the knockdown of TRPV2. Moreover, the microarray assay revealed that TRPV2 was associated with the transforming growth factor (TGF)-β signaling pathway. Immunohistochemical staining showed that the strong expression of TRPV2 correlated with lymphatic invasion, venous invasion, pathological T (pT), pathological N (pN), and a poor prognosis in GC patients. TRPV2 appeared to promote tumor migration and invasion via the TGF-β signaling pathway, and the strong expression of TRPV2 was associated with a worse prognosis in GC patients.

A 21‑gene Support Vector Machine classifier and a 10‑gene risk score system constructed for patients with gastric cancer.

Gastric cancer (GC) ranks fifth in terms of incidence and third in terms of tumor mortality worldwide. The present study was designed to construct a Support Vector Machine (SVM) classifier and risk score system for GC. The GSE62254 (training set) and GSE26253 (validation set 2) datasets were downloaded from the Gene Expression Omnibus database. Furthermore, the gene expression profile of GC (validation set 1) was obtained from The Cancer Genome Atlas database. Differentially expressed genes (DEGs) between recurrent and non-recurrent samples were determined using the limma package. The feature genes were selected using the Caret package, and an SVM classifier was built using the e1071 package. Using the penalized package, the optimal predictive genes for constructing a risk score system were screened. Finally, stratification analysis of clinical factors and pathway enrichment analysis were performed using Gene Set Enrichment Analysis. A total of 239 DEGs were identified in GSE62254, among which 114 DEGs were significantly associated with both recurrence-free survival and overall survival. Subsequently, 21 feature genes were screened from the 114 DEGs, and an SVM classifier was built. A risk score system for survival prediction was constructed, following the selection of 10 optimal genes, including A-kinase anchoring protein 12, angiopoietin-like protein 1, cysteine-rich sequence 1, myeloid/lymphoid or mixed-lineage leukemia, translocated to chromosome 11, neuron navigator 3, neurobeachin, nephroblastoma overexpressed, pleiotrophin, tumor suppressor candidate 3 and zinc finger and SCAN domain containing 18. The stratification analysis revealed that pathological stage was an independent prognostic clinical factor in the high-risk group. Additionally, eight significant pathways were associated with the 10-gene signature. The SVM classifier and risk score system may be applied for classifying and predicting the prognosis of patients with GC, respectively.

Abundant PD-L1 expression in Epstein-Barr Virus-infected gastric cancers.

Gastric cancer (GC) is a deadly disease with limited treatment options. Recent studies with PD-1 inhibition have shown promising results in GC, but key questions remain regarding which GC subclass may respond best. In other cancers, expression of the PD-1 ligand PD-L1 has been shown to identify cancers with greater likelihood of response to PD-1 blockade. We here show with immunohistochemistry that Epstein-Barr Virus (EBV)+ GCs (n = 32) have robust PD-L1 expression not seen in other GCs. In EBV+ GC, we observed PD-L1 staining in tumor cells in 50% (16/32) and immune cells in 94% (30/32) of cases. Among EBV-negative GCs, PD-L1 expression within tumors cells was observed only in cases with microsatellite instability (MSI), although 35% of EBV-/MSS GCs possessed PD-L1 expression of inflammatory cells. Moreover, distinct classes of GC showed different patterns of PD-L1+ immune cell infiltrations. In both EBV+ and MSI tumors, PD-L1+ inflammatory cells were observed to infiltrate the tumor. By contrast, such cells remained at the tumor border of EBV-/MSS GCs. Consistent with these findings, we utilized gene expression profiling of GCs from The Cancer Genome Atlas study to demonstrate that an interferon-γ driven gene signature, an additional proposed marker of sensitivity to PD-1 therapy, were enriched in EBV+ and MSI GC. These data suggest that patients with EBV+ and MSI GC may have greater likelihood of response to PD-1 blockade and that EBV and MSI status should be evaluated as variables in clinical trials of these emerging inhibitors.

Identification of Differentially-expressed Genes in Intestinal Gastric Cancer by Microarray Analysis

Gastric cancer (GC) is one of the most frequent malignant tumors. In order to systematically characterize the cellular and molecular mechanisms of intestinal GC development, in this study, we used 22K oligonucleotide microarrays and bioinformatics analysis to evaluate the gene expression profiles of GC in 45 tissue samples, including 20 intestinal GC tissue samples, 20 normal appearing tissues (NATs) adjacent to tumors and 5 noncancerous gastric mucosa tissue samples. These profiles allowed us to explore the transcriptional characteristics of GC and determine the change patterns in gene expression that may be of clinical significance. 1519 and 1255 differentially-expressed genes (DEGs) were identified in intestinal GC tissues and NATs, respectively, as determined by Bayesian analysis (P<0.001). These genes were associated with diverse functions such as mucosa secretion, metabolism, proliferation, signaling and development, which occur at different stages of GC development.