Screening Potential Biomarkers Of Ovarian Cancer Based On Weighted Network Co-expression Analysis

OBJECTIVE: Ovarian cancer mortality ranks first among gynecologic cancers due to the absence of obvious early symptoms and the lack of effective diagnostic methods.Pathological diagnosis and gene chip inspection have become routine in the early diagnosis of ovarian cancer.However,the low specificity and sensitivity tumor marker is not sufficient to accurate diagnosis the ovarian cancer with diversity of pathology and mechanisms.Up to now,there are no ideal tumor marker can be used for early clinical diagnosis of ovarian cancer.Therefore,there is a need for the high sensitivity and specificity of new tumor markers that can be applied on the early diagnosis of ovarian cancer.We used bioinformatics analysis to screen specificity and sensitivity tumor marker which could efficiently guide the early diagnosis and early treatment of ovarian cancer and further improve the quality of life of patients.METHODS: Using ovarian cancer gene chip data,bioinformatics software analysis and processing,and differentially expressed genes related to ovarian cancer were selected from the existing gene chip data.The WGCNA network was constructed,the disease-related gene modules were selected,the GO and KEGG enrichment analysis was performed on the gene modules,the Cytoscape software was used to visualize the module gene interaction relationship,the core node genes were selected,and the core node genes were analyzed for survival to filtrate out Core node genes associated with poor prognosis in ovarian cancer.RESULTS: Through the WGCNA network analysis of ovarian cancer gene chip data,the blue gene module related to ovarian cancer was found.The GO and KEGG enrichment analysis of the blue gene module revealed that the blue module contained genes mainly involved in the kidney,digestive tract,cartilage,bone and genitourinary development,regulating cell response to growth factor stimulation,ossification,etc.Signaling mechanism mainly involved in Rap1 signaling pathway,proteoglycans in cancer,MAPK signaling pathway,phospholipase D signaling pathway,PI3K-Akt signaling pathway,Ras signaling pathway and so on.Then,six hub genes related to the development and prognosis of ovarian cancer,ITLN1,CD24,LHX2,WNT2 B,LHX9,and LINC01105,were screened by survival analysis.Finally,the genomics and methylation analysis of the six hub genes were carried out.The genomics results showed that the six genes had lower mutation frequencies,and the highest LHX9 mutation frequency was only 4%.ITLN1 was 3%,WNT2 B was 2.1%,LHX2 was 1.5%,LINC01105(SILC1)was 1.4%,and most of the mutations were duplicates;methylation analysis showed that the degree of methylation of ITLN1,CD24,and CLDN15 varied greatly,we presumed it is possibly due to abnormal expression of genes.CONCLUSION:(1)Genes we screened out mainly involved in the kidney,digestive tract,cartilage,bone and genitourinary development,regulating cell response to growth factor stimulation,ossification,etc;signaling mechanism mainly involved in MAPK,phospholipase D,PI3K-Akt,Rap1 or Ras signaling pathway;(2)ITLN1,CD24,LHX2,WNT2 B,LHX9,and LINC01105,were screened by survival analysis;(3)these six hub genes related to the development and prognosis of ovarian cancer,these six genes had lower mutation frequencies.