Association Analysis Of Gastric Cancer And Parkinson's Disease Based On Gene Expression Profile

In the past 20 years,the analysis of gene expression profile data has been one of the important research directions that statistics,computer science and bioinformatics cross each other.Analysis of gene expression profile data sets can reveal the relationship between genomic information and phenotype.With the further development of high-throughput technology,the cost of measuring the expression level of all mRNA in samples is getting lower and lower,which makes the application of gene expression profile technology more and more extensive.Therefore,microarray experiments have obtained a large number of data sets,and the selection of appropriate statistical methods for gene expression profile data has become a very important topic.Parkinson's disease is a kind of death of dopaminergic neurons in the substantia nigra neurodegenerative disease,and gastric cancer is a common form of cancer that is caused by abnormal cell growth,that is to say,has the characteristics of cell death in Parkinson's disease,and gastric cancer has the characteristics of cell proliferation,and therefore Parkinson's disease and gastric cancer are two completely different diseases.An epidemiological study has shown that people with Parkinson's disease have a relatively low risk of developing gastric cancer.The purpose of this paper is to analyze the gene expression profile data sets from two different analytical perspectives to explore the relationship between gastric cancer and Parkinson's disease.This paper is based on two different analytical perspectives.Firstly,the gene expression profiles of gastric cancer and Parkinson's disease were analyzed for gene differential expression(using the moderated t test provided by limma package),and secondly,the gene expression profiles of gastric cancer and Parkinson's disease were analyzed for weighted gene co-expression network(WGCNA).The former is a singlegene analysis that tests each gene individually in the dataset,while the latter is a systems biology approach that takes into account all the genes in the dataset and analyzes them together.In this paper,using the gastric cancer tumor gene expression profile data set and Parkinson's disease gene expression profile data set from GEO database,a total of 53 samples from gastric cancer tumors,53 samples from adjacent healthy tissues of gastric cancer,66 blood samples from patients with Parkinson's disease and 60 blood samples from healthy controls were collected.Using gene differential expression analysis(moderated t test provided by limma package)for gastric cancer gene expression profile and Parkinson's disease gene expression profile respectively,the threshold for screening differentially expressed genes was set to a adjusted P value of less than 0.05,5,696 differentially expressed genes(3,087 up-regulated genes and 2,609 down-regulated genes)between gastric cancer tumor tissues and healthy tissues adjacent to gastric cancer,and 16,405 differentially expressed genes(8,594 up-regulated genes and 7,811 down-regulated genes)between Parkinson's disease group and healthy control group were identified.In addition,there are 4,459 overlapping differentially expressed genes between gastric cancer and Parkinson's disease.The common differentially expressed genes in gastric cancer and Parkinson's disease were enriched and analyzed.The results of KEGG enrichment analysis showed that the intersection genes mainly participated in TRL signal pathway and MAPK signal pathway,both of which were related to neurodegenerative diseases and cancer.The weighted gene co-expression network analysis(WGCNA)was used to construct the weighted gene co-expression network for gastric cancer tumor group and Parkinson's disease group,respectively.The genes in the gastric cancer tumor group network were hierarchically clustered and 20 gene modules were identified.Taking the gastric cancer tumor group network as the reference network and the Parkinson's disease group network as the test network,using the differential network analysis method,the results show that a total of 8 modules of gastric cancer tumor network are retained in the Parkinson's disease network,and the hub genes of these 8 modules are functionally enriched,and the KEGG enrichment analysis results show that hub genes are mainly enriched in the cell cycle pathway.Our research shows that there are important common differential expression genes and pathways between gastric cancer and Parkinson's disease.