Abstract:BackgroundTaxol resistance of serous ovarian cancer is responsible for its poor prognosis, yet the underlying mechanism was still poorly understood. Thus, we probed the mechanism of taxol resistance in serous ovarian cancer with multiple bioinformatic methods to provide novel insights for potential therapy. MethodsThe differentially expressed genes (DEGs) and their relationship with overall survival (OS) and progress-free interval (PFI) of ovarian cancer patients were analyzed using gene expression datasets fr… Show more
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