The Screening Of Prognostic Factors For Distal Gastric Cancer Based On WGCNA And Functional Study

Background:Gastric cancer(GC)is a high-risk tumor in China and often diagnosed at an advanced stage.Although a variety of new drugs have improved the prognosis of advanced gastric cancer to a certain extent,the overall efficacy is still limited,and the median overall survival(mOS)is less than 1 year.Therefore,it is crucial to carry out a further exploration of the molecular mechanisms affecting the development of gastric cancer for the screening of new targets and the development of new drugs.Studies have confirmed that if the disease locations of malignant tumors are different,the prognoses and the molecular characteristics are also significantly different,even if they occur in the same organ.According to the location of the disease,gastric cancer can be divided into proximal gastric cancer(PGC),middle stomach cancer and distal gastric cancer(DGC).Analysis of large gastric cancer databases from China and the United States confirmed that proximal tumors were more common in Western populations,while DGC had a higher morbidity in Chinese populations.Analysis of clinical characteristics showed that DGC patients tended to have diffuse type tumors,poorly differentiated tumors,and DGC had a shorter survival time compared with PGC when the tumor was in an advanced stage.In view of the fact that drug therapy is dominated to advanced gastric cancer,the above studies suggested that DGC might be more resistant.Therefore,exploring the molecular mechanisms of the development of DGC can not only find the key factors that affect its prognosis,but also help to find new therapeutic targets.The aim of this study was to discover the key prognostic factors in DGC using bioinformatic methods,and to explore the function and molecular mechanisms.Methods: The Cancer Genome Atlas(TCGA)public database was employed to screen data relating to DGC with the disease location.We conducted a weighted gene co-expression network analysis(WGCNA)on DGC patient samples to establish co-expression modules and select the modules which were relevant to clinical characteristics.High-weight genes(hub genes)in a dominant module were identified using the cytohubba plugin based on cytoscape.The target gene related to the prognosis of patients with DGC was further selected by survival analysis in R.Next,a Protein-Protein Interaction(PPI)Network using the STRING web was performed to analyze the correlation of the related proteins.Besides,the differential expression of target molecules between the tumor tissue and normal gastric tissue was identified by using the on-line database GEPIA and TCGA database.The effect of the gene on gastric cancer cells was verified by cytological experiments,and the molecular mechanism was explored by gene set enrichment analysis(GSEA).P < 0.05 was considered to indicate a statistically significant difference.Results: In this study,139 DGC samples were enrolled to perform a co-expression analysis while 21 co-expression modules were constructed successfully,and each of them contained a cluster of genes with similar functions.According to the correlation between gene modules and clinical characteristics,the royal blue module related to stage M was screened.A total of 25 hub genes were screened out in the royal blue color module.The survival analysis and the Kaplan-Meier Plotter on-line analysis showed that high F5(Coagulation factor ?)expression was not only related to the poor prognosis of patients with DGC,but also significantly related to the poor prognosis of all gastric cancer.The further PPI network suggested that coagulation factor V interacted with Bone morphogenetic protein 4(BMP4)and amphiregulin(AREG).Gene differential expression analysis showed that F5 mRNA was significantly up-regulated in DGC tissues as well as gastric cancer tissues.In vitro experiments confirmed that F5 could promote the migration of gastric cancer cells.GSEA showed that F5 might affect prognosis of gastric cancer by modulating the activities of multiple pathways,such as the TGF-? signaling pathway.Conclusions: Our results indicated that F5 mRNA over-expressed in DGC and predicted poor prognosis of patients with DGC.In addition,high F5 expression predicted poor prognosis of patients with gastric cancer by promoting cell migration via TGF-? signaling pathways.