Abstract 392: Predictive value of angiogenesis related genes in advanced ovarian carcinoma
Authors: Mendiola Marta , Barriuso Jorge , Redondo Andrés , Madero Rosario , Sánchez-Navarro Iker , Pérez-Fernández Elia , Hernández-Cortés Ginés , Gómez-Raposo César , de Santiago Javier , Vara Juan Ángel Fresno , Espinosa Enrique , Hernández Alicia , Zamora Pilar , Mariño-Enríquez Adrián , Feliu Jaime , Gonzalez-Barón Manuel , Hardisson David 
Published: February 2011

Management of advanced ovarian cancer (AOC) involves surgery in order to achieve surgical cytoreduction followed by chemotherapy. Combination platinum (C) - paclitaxel (P) chemotherapy has become a standard first line treatment for the advanced-stage disease. Outcome is significantly improved with this regimen and 40 to 50% achieve complete clinical remission. Classical parameters such as age at diagnosis, extent of disease residual disease after surgery, and the histopathological features of the tumor are imperfect predictors of response. Angiogenesis plays a major rol in ovarian carcinogenesis and antiangiogenic compounds such as bevacizumab proved efficacy in AOC in early phase trials. The aim of this study is to build a profile able to predict clinical response to multimodal first line therapy.

Materials and Methods:

61 patients with III/IV FIGO stage ovarian cancer who underwent surgical cytoreduction and received a C plus P regimen were included. RNAs were collected from formalin-fixed paraffin-embedded AOC samples. Expression levels of 82 angiogenesis related genes were measured using quantitative real time polymerase chain reaction. Clinical response was evaluated using CT after the completion of multimodal therapy. Statistical analysis was performed using a regression method to generate multiple models based on the significant genes. The accuracy of the models was evaluated using Receiver Operating Characteristic (ROC) curves. The Akaike Information Criterion based selection was used to find the most accurate one.

Results:

The median age at diagnosis was 53 years (range, 21 to 82 years). All patients had advanced disease (FIGO stages III/IV). Most of them had FIGO stage III (51, 83.6%), grade 3 tumors (35, 57.4%), and serous histology (42, 68.9%). 52 patients (85.2%) achieved an initial response (complete response or partial response by RECIST criteria) to this therapy. It was found an independent model able to predict any degree of response to therapy comprising 8 genes with an Area Under the Curve (AUC) of 0.955 (p&lt;0.001). Leave-one-out cross validation was applied to avoid overfitting of the model, obtaining a corrected AUC of 0.880, 95%IC: 0,776-0,985.

Conclusions: It is possible to generate a predictive model of clinical response for ovarian cancer based on angiogenesis related genes using formalin-fixed paraffin-embedded samples. The present results are consistent with the increasing weight of several angiogenesis genes in prognosis of ovarian cancer. Although these results should be validated prospectively in larger series of ovarian cancer patients, this model could identify those patients that would achieve any degree of response to standard treatment. So it could be used to tailor therapy in those patients with no response at all to treatment.

Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 392.