Background: Cervical cancer (CC) is the primary cause of death in women. This study sought to investigate the therapeutic targets of CC. Methods: We downloaded four gene expression profiles from GEO. The RRA method was used to integrate and screen DEGs between CC and normal samples. Functional analysis was performed by clusterprofiler. We built PPI network by STRING and selected hub modules via MCODE. CMap was used to find molecules with therapeutic potential for CC. We also validated hub genes

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... in GEO datasets, GEPIA, immunohistochemistry. Cox regression analysis, TCGA methylation analysis and ONCOMINE were carried out. ROC curve analysis and GSEA were also done to dig out the significance of hub genes. Results: Functional analysis revealed that DEGs were significantly enriched in binding, cell proliferation, transcriptional activity and cell cycle regulation. PPI network screened 30 prominent proteins, with CDK1 having the strongest association with CC. Cmap showed that apigenin, thioguanine and trichostatin A might be used to treat CC. Eight genes were screened out through GEPIA. Of them, only PTGDS and SNX10 have not been reported in CC related articles. The validation in GEO showed that PTGDS showed low expression in tumor tissues while SNX10 showed high expression in tumor tissues. Their expression profiles were consistent with the results in immunohistochemistry. They can distinguish CC and normal tissue and have good diagnostic efficiency. GSEA showed that the two genes were associated with the chemokine signaling pathway. TCGA methylation analysis showed that patients with low-expressed and hyper-methylated PTGDS had a bad prognosis than the patients with high-expressed and hypo-methylated PTGDS. Cox regression analysis showed that SNX10 and PTGDS were independent prognostic indicators for OS among CC patients. Conclusions: In conclusion, PTGDS and SNX10 showed abnormal expression and methylation in CC. Both genes could be used to develop new target treatments for CC.