Abstract
BACKGROUND: To search for genes with high sensitivity and to explore its application value related to clinical prognostic prediction, so as to provide important foundation for the preventive intervention, early diagnosis, treatment and prognosis evaluation for breast cancer. METHODS: Tissue samples from ten clinical breast cancer patients were collected to search for the common mutant genes among various samples, and to explore the enrichment degree of mutant genes at both disease and signaling pathway levels using the whole exome sequencing (WES). Subsequently, targets genes with changes in expression levels that showed high correlations with mutation were screened from the above common genes using The Cancer Genome Atlas (TCGA) database. On this basis, differences in the mutation and expression levels of the screened target genes between breast cancer tissues and para-carcinoma tissues, as well as their correlations with patient survival were analyzed using the gene expression and mutation data in TCGA database, together with the clinical information. Finally, the potential regulatory pathways and potential downstream targets of the target genes were predicted through gene set enrichment analysis (GSEA) using Multi-Experiment Matrix (MEM) software. RESULTS: A total of 23 common mutant genes were discovered from the tissue samples from ten breast cancer patients, which were mostly enriched in the cancer, PI3K/Akt and cAMP signaling pathways. Among these 23 genes, only the changes in the expression levels of ZNF384 and PDE4DIP had displayed over 15% consistency with mutation. Besides, it was discovered through TCGA database analysis that, the expression level of ZNF384 gene in breast cancer tissues with ZNF384 mutation was far higher than that in those with no ZNF384 mutation. Moreover, such gene mutation and high expression had shown significantly positive correlation with the patient survival (P<0.05). In addition, GSEA indicated that, tissues with high ZNF384 expression were associated with enrichments related to cell cycle signaling pathway and mitosis metaphase pathway, while this series of effects might be correlated with its regulation on the level and activity of its downstream gene CXCL14. CONCLUSIONS: ZNF384 mutation and up-regulated ZNF384 expression level in breast cancer tissues is significantly positively correlated with patient survival. Therefore, ZNF384 can serve as a molecular marker for the diagnosis and prognostic prediction of breast cancer as well as a potential therapeutic target.