Based On The ME Algorithm To Search For A Class Of Lung Cancer Driven Genes

The incidence and death rate of malignant tumors is increasingin the world,which has a very serious effect on the patients and the society.Mutations in cancer-driven genes play an extremely important role in the formation and development of tumors.The prediction of the driving genes is of great significance in the theoretical study of the disease and the clinical diagnosis and treatment of the patients.However,due to the complexity of the disease itself,there are still limitations on the experimental and computational methods of the disease,so it is still difficult to predict the driving genes accurately.This paper is based on the MEmutual exclusion algorithm,which combines the gene expression data of lung cancer with the Gene Ontology(GO)annotation,to predict the mutation-driven gene in lung cancer samples.First,we established a model,selecting the differentially expressed genes from the gene expression profile dataof tumor samples on account of a three times differential.Based on the differentially expressed genes selected,then,we found a set of functional genes and tumors annotated with a common GO term,constructed a subset of differentially expressed genes for lung cancer.Then we used the super geometry distribution to calculatethe correlation coefficient of the mutation gene,the copy number mutation gene and the selected tumor.At last,we used the ME algorithm to select the genes with the least correlation coefficient as a result,which also are the genes differentiate most significantly between tumor and the normal sample and coverage the largest number of tumor.Finally,our model draws a forecast set of the driving genes that are closely related to the occurrence and development of lung cancer.Comparing the results with the published biological experiments,we found that some genes are known as cancer-driven genes,and we found that the forecast set we got has a large number of genes that have been proven to be closely related to the corresponding type of cancer and play an important role in promoting theoccurrence and development of cancer.Therefore,our research is of great significance for the establishment of disease models and the treatment of diseasesin the future,and can provide a scientific and effective method for future study of lung cancer disease mechanism and follow-up treatment.