In silico analyses identify gene-sets, associated with clinical outcome in ovarian cancer: role of mitotic kinases.

ABSTRACT:

Introduction

Accurate assessment of prognosis in early stage ovarian cancer is challenging resulting in suboptimal selection of patients for adjuvant therapy. The identification of predictive markers for cytotoxic chemotherapy is therefore highly desirable. Protein kinases are important components in oncogenic transformation and those relating to cell cycle and mitosis control may allow for identification of high-risk early stage ovarian tumors.

Methods

Genes with differential expression in ovarian surface epithelia (OSE) and ovarian cancer epithelial cells (CEPIs) were identified from public datasets and analyzed with dChip software. Progression-free (PFS) and overall survival (OS) associated with these genes in stage I/II and late stage ovarian cancer was explored using th

SUBMITTER: Ocana A 

PROVIDER: S-EPMC5008407 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature