Ovarian cancer is the eighth most common cancer and the seventh highest cause of cancer-associated mortality in women worldwide. It is the second highest cause of mortality among female reproductive malignancies. The current standard first-line treatment for advanced ovarian cancer includes a combination of surgical debulking and standard systemic platinum-based chemotherapy with carboplatin and paclitaxel. Although a deeper understanding of this disease has been attained, relapse occurs in 70% of patients 18 months subsequent to the first-line treatment. Therefore, it is crucial to develop a novel drug that effectively affects ovarian cancer, particularly tumors that are resistant to current chemotherapy. The aim of the present study was to identify genes whose expression may be used to predict survival time or prognosis in ovarian cancer patients treated with chemotherapy. Gene or protein expression is an important issue in chemoresistance and survival prediction in ovarian cancer. In the present study, the research group consisted of patients treated at the Surgical Clinic of the Gynecology and Obstetrics Gynecological Clinical Hospital, Poznan University of Medical Sciences (Poznan, Poland) between May 2006 and November 2014. Additional eligibility criteria were a similar severity (International Federation of Gynecolgy and Obstetrics stage III) at the time of diagnosis, treatment undertaken in accordance with the same schedule, and an extremely good response to treatment or a lack of response to treatment. The performance of the OncoScan® assay was evaluated by running the assay on samples obtained from the four patients and by following the recommended protocol outlined in the OncoScan assay manual. The genomic screening using Affymetrix OncoScan Arrays resulted in the identification of large genomic rearrangements across all cancer tissues. In general, chromosome number changes were detected in all examined tissues. The OncoScan arrays enabled the identification of ~100 common somatic mutations. Chemotherapy response in ovarian cancer is extremely complex and challenging to study. The present study identified specific genetic alterations associated with ovarian cancer, but not with response for treatment.
Keywords: efficacy of the treatment; microarrays; ovarian adenocarcinoma; point gene mutations.