Abstract
OBJECTIVE: Searching for potential biomarkers and therapeutic targets for early diagnosis of gynecological tumors to improve patient survival. METHODS: Microarray datasets of cervical cancer (CC) and ovarian cancer (OC) were downloaded from the Gene Expression Omnibus (GEO) database, then, differential gene expression between cancerous and normal tissues in the datasets was analyzed. Weighted gene co-expression network analysis (WGCNA) was performed to screen for co-expression modules associated with CC and OC. The screened shared genes were then further analyzed for functional pathway enrichment. Next, the least absolute shrinkage and selection operator (LASSO) with tenfold cross validation is used to further screened for common diagnostic biomarkers for the two diseases, and further validation is performed using two independent GEO datasets. Finally, the CIBERSORT algorithm was used to estimate the immune infiltration levels of CC and OC, and the correlation between immune cell infiltration and common biomarkers was explored. RESULTS: After crossing the common DEGs detected by "Limma" R package with the common module genes identified by WGCNA, 44 shared genes were obtained. Functional enrichment indicates that these shared genes are mainly related to DNA synthesis pathways. Lasso regression analysis revealed that EFNA1, TYMS, and WISP2 were co-diagnostic markers for CC and OC, and then based on their expression levels and diagnostic efficacy, EFNA1 was selected as the best co-marker for CC and OC. Immune infiltration analysis shows that the immune environment has a significant impact on the occurrence and development of CC and OC, and the expression of EFNA1 is related to changes in immune cells. Gene-drug interaction analyses identified 27 common drug compounds that interact with candidate genes. CONCLUSION: This study adopted bioinformatics methods to investigate the common pathways and identify diagnostic markers between CC and OC, suggesting that DNA synthesis and immune environment are closely related to the occurrence and development of CC and OC. EFNA1 may be a potential diagnostic indicator and therapeutic target for patients with CC and OC.