ObjectiveTo study the mechanism of the effect on invasion and metastasis of colorectal cancer by down-regulating c-Met gene.Methodsc-Met genes were knocked down in SW480 cells, differential genes were screened by gene chip, functional cluster analysis of differential genes was carried out, and IPA was used to analyze the interaction network of cell signal pathway and related differential genes, as well as the ralationship between related genes and upstream regulatory molecules. The related genes in the suppressed signal pathway were selected for qPCR verification.ResultsAfter knockdown of c-Met, the number of up-regulated genes and down-regulated genes in SW480 cells was 399 and 286, respectively. Cluster analysis showed that c-Met knockdown had a great effect on the gene expression level of SW480 cells, IPA pathway analysis showed that HGF signaling pathway was suppressed, and after c-Met knockdown, IPA interaction network suggested that AKT2, PIK3CA, and MAP2K4 in HGF pathway were down-regulated, and qPCR verified that the above genes were also down-regulated, which was consistent with the results of microarray.Conclusionc-Met may affect the invasion and metastasis of colorectal cancer through the regulation of AKT2, PIK3CA, and MAP2K4 in HGF pathway.
ObjectiveTo explore the mechanism of DDX46 regulation of esophageal squamous cell carcinoma.MethodsPicture signals of fluorescence in gene array were scanned and differential expression of gene in two groups (a DDX46-shRNA-LV group and a control-LV group) were compared by GCOSvL.4 software. These differential expressed genes were analyzed by bioinformatics methods finally, and validated by quantitative real time polymerase chain reaction (qRT-PCR) analysis.ResultsAccording to the screening criteria of fold change ≥2 and P<0.05, 1 006 genes were differentially expressed after DDX46 knockdown, including 362 up-regulated and 644 down-regulated genes. Bioinformatics analysis and gene co-expression network building identified that these differentially expressed genes were mainly involved in cell cycle, proliferation, apoptosis, adhesion, energy metabolism, immune response, etc. Phosphatidylinositol 3-kinase (PI3K) was the key molecule in the network. The results of RT-qPCR were completely consistent with the results of gene microarra.ConclusionBioinformatics can effectively exploit the microarray data of esophageal squamous cell carcinoma after DDX46 knockdown, which provides a valuable clue for further exploration of DDX46 tumorigenesis mechanism and helps to find potential drug therapy.
ObjectiveThrough the analysis of gene enrichment in gastric cancer samples, the changes of RNA alternative splicing and related molecular mechanisms were explored.MethodsThe pathological samples of three cases of gastric cancer patients and adjacent tissues were obtained clinically, and the data were obtained by cell culture, protein quantitative labeling, gene chip detection, high-throughput sequencing, etc. GO enrichment was performed on samples by DAVID and other network software, KEGG pathway analysis yielded relevant information for screening for variable splicing of differential genes.ResultsA total of 605 genes with individual ENSG IDs consistent with the gene identification of the ENSEMBL database were screened, and the gene levels of cancer tissues and adjacent tissues were compared. There were 411 non-differentiated genes, 119 differentially up-regulated genes, and 75 differentially down-regulated genes. A total of 69 differentially spliced genes were screened out. Functional annotation and pathway analysis revealed that the detection genes were mainly concentrated in molecular metabolic processes, cell migration, extracellular matrix tissue, blood coagulation, cell matrix adhesion, signal transduction, negative apoptosis regulation, angiogenesis, platelet activation, complement system, adipokines signaling pathway, peroxisome, cancer pathway, transforming growth factor (TGF) signaling pathway, axon guidance, cell cycle, etc.ConclusionThere are a large number of differentially spliced genes in gastric cancer tissue samples, and the difference in expression due to changes in splice sites may play an important role in the development of gastric cancer.
ObjectiveTo analyze the expression and prognostic value of PHD Finger Protein 19 (PHF19) in non-small cell lung cancer (NSCLC) based on gene chip data. MethodsThe data about The Cancer Genome Atlas (TCGA) lung cancer patients were downloaded to analyze the expression of PHF19 in lung cancer. The data sets GSE30219 and GSE50081 were downloaded from the Gene Expression Omnibus (GEO), and the patients were screened into the training set and the validation set respectively, thus analyzing the relationship between PHF19 expression, gender, age, tumor clinical stage, pathological type and disease-free survival (DFS), as well as their relationship with overall survival (OS). Gene Ontology (GO)-Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and immune infiltration analysis were performed on PHF19 and co-expression related genes in lung cancer patients through the online database. ResultsThe data from TCGA and GEO showed PHF19 was highly expressed in lung cancer (P<0.001), and PHF19 expression was related to tumor stage. The NSCLC patients in the PHF19 low expression group had longer DFS and OS than those in the high expression group (P<0.05). Multivariate COX regression analysis showed PHF19 was an independent prognostic factor in NSCLC patients (P<0.05). A nomogram drawing to predict the survival rate of lung cancer patients and verifying the C index showed the model has good accuracy. Gene enrichment analysis showed PHF19 high expression is mainly related to the cell cycle, cell nucleus, chromatin, etc. Immune infiltration analysis showed PHF19 is closely related to immune cell infiltration. ConclusionsPHF19 can be used as an indicator to predict the prognosis of NSCLC. PHF19 high expression is an independent predictor of poor prognosis of NSCLC and may be a new target for its treatment.