Integrated Analysis Of Gene Expression Profiles In Pancreatic Cancer

Background:Pancreatic ductal adenocarcinoma(PD AC),which is a type of refractory malignancies,accounts for approximately 90%of all pancreatic tumors.The incidence and mortality rates of pancreatic cancer are increasing worldwide.PD AC is difficult to be diagnosed at early stage due to lacking specific symptoms and signs.Since its complex anatomical features and characteristics of nerve invasion,surgical resection is difficult and results in a low removal rate.Because of a poor treatment response to radiotherapy and chemotherapy,the prognosis is still unsatisfactory.So,it is urgent to develop the molecular markers for early diagnosis and target therapy.Data mining of gene expressions using high-throughput methodologies has become more and more popular in recent years.The emerging technologies of DNA microarray and next generation sequencing provide powerful tools to investigate the differentially expressed genes between pancreatic cancer tissues and normal tissues.Objective:In order to explore the molecular mechanisms in PD AC development and progression,microarray data from the Gene Expression Omnibus(GEO)were used to explore differentially expressed genes between pancreatic cancer tissues and normal tissues.We hope that this study could make a contribution to detect the biomarkers for diagnosis.Methods:First,we downloaded 6 gene expression profiles of pancreatic cancer from GEO database,and performed analysis to screen differentially expressed genes between pancreatic cancer tissues and normal tissues.DEGs with a fold change more than 2 and the p-value less than 0.05 between cancer and normal tissues were selected.Then,we enriched the significant pathways and analyzed the pathway network to explore the key pathways in pancreatic cancer development and progression.Further more,we analyzed the correlation between the expression of genes in the core pathway and survival time of pancreatic cancer patients.Results:We obtained 32 common significant pathways and 13 common core pathways from 6 profiles.Because the "pathway in cancer" ranked first in the core pathway list,we analyzed the 137 differentially expressed genes in it,and found that the expression of BIRC5,CKS2,ITGA3,ITGA6 and RALA were associated with survival of PD AC individuals.The expression of CKS2 was positively correlated with copy number and negatively correlated with the degree of methylation in pancreatic cancer and other tumors in TCGA database.Knockdown of CKS2 decreased the proliferation significantly in both BxPC3 and CFPAC1 cell lines.Conclusion:We found that the "pathway in cancer" played an important role in pancreatic cancer development and progression via the analysis of signaling pathway network.CKS2,a component of the pathway in cancer,increased the proliferation of pancreatic cancer cell lines.It was important to study the molecular mechanism of CKS2.