Background
Cervical cancer, as a common gynecological disease, endangers female health. Give the lack of effective biomarkers for the diagnosis and treatment of cervical cancer, this paper aims to analyze the Gene Expression Omnibus (GEO) data sets using comprehensive bioinformatics tools, and to identify biomarkers associated with the cancer in patient samples.
Conclusion
We identified a biomarker (TRIM8) that may be related to cervical cancer through a series of analyses on the GEO dataset. Experimental verification confirmed the inhibition of cervical cancer cells proliferation by lowering TRIM8 expression. Therefore, TRIM8 can be adopted as a new biomarker of cervical cancer to develop new therapeutic targets.
Methods
The bioinformatics methods were used to extract genes related to cervical cancer from GSE39001, while the GEO2R online tool to elaborate on differentially expressed genes (DEGs) in normal and cancer samples, and to clarify related genes and functions. The
Results
A total of 2,859 DEGs were identified in the GEO microarray dataset. We extracted genes associated with both ubiquitination and autophagy from the key modules of weighted gene co-expression network analysis (WGCNA), and the analysis showed that TRIM8 was of great significance for the diagnosis and prognosis of cervical cancer. Besides, experimental validation showed the high TRIM8 expression in cervical cancer, as well as its involvement in the proliferation of cervical cancer cells.