Abstract
Backgroud: The E545 mutation of PIK3CA in Cervical cancer is frequently happened. But the role of E545 mutation of PIK3CA in Cervical cancer is not clear.Methods: In this study, we analysised the molecular signatures of E545 mutation Cervical cancer by bioinformatics methods.Results: We collected transcriptome sequencing results of 227 no mutation cervical cancer tissue samples and 36 mutation cervical cancer tissue samples, then analyzed the data combining bioinformatics methods. A total of 5 differential expression miRNAs were obtained, including 3 up-regulated miRNAs, 1 down-rugulated miRNA. A total of 174 differential expression genes were obtained, including 132 up-regulated genes, 40 down-rugulated genes. GO analysis suggested that the up-regulated DEGs were mainly enriched in transcription factor activity, leukotriene signaling pathway and so on. Besides, we constructed a PPI network with DEGs to screen the top hub genes with a relatively high degree of connectivity. Among them CAV1, KRT20, FOS, had a degree of connectivity larger than 5 and functioned as hub module genes to promote the survival of E545 mutation cervical cancer. We also identified different miRNA-DEG axis, including hsa-mir-449a-AXL, hsa-mir-508-CGA, COL15A1, NNMT, hsa-mir-552-CHST6, NWD1. These axis regulated the survival of E545 mutation cervical cancer togetherly. Conclusions: In conclusion, this study identified DEGs and screened the key genes and pathways closely related to E545 mutation in Cervical cancer by bioinformatics analysis, These results might hold promise for finding potential therapeutic targets of cervical cancer harboring E545 mutation of PI3KCA.