TY - JOUR T1 - Predicting Response to Standard First-line Treatment in High-grade Serous Ovarian Carcinoma by Angiogenesis-related Genes JF - Anticancer Research JO - Anticancer Res SP - 5393 LP - 5400 DO - 10.21873/anticanres.12869 VL - 38 IS - 9 AU - MARTA MENDIOLA AU - ANDRÉS REDONDO AU - VICTORIA HEREDIA-SOTO AU - JESÚS HERRANZ AU - ALBERTO BERJÓN AU - ALICIA HERNÁNDEZ AU - MARÍA MIGUEL-MARTÍN AU - ROBERTO CRESPO AU - JORGE BARRIUSO AU - PATRICIA CRUZ AU - LAURA YÉBENES AU - ALBERTO PELÁEZ-GARCÍA AU - BEATRIZ CASTELO AU - ANA RAMÍREZ DE MOLINA AU - JAIME FELIU AU - DAVID HARDISSON Y1 - 2018/09/01 UR - http://ar.iiarjournals.org/content/38/9/5393.abstract N2 - Background/Aim: Predicting response to treatment in high-grade serous ovarian carcinoma (HGSOC) still remains a clinical challenge. The standard-of-care for first-line chemotherapy, based on a combination of carboplatin and paclitaxel, achieves a high response rate. However, the development of drug resistance is one of the major limitations to efficacy. Therefore, identification of biomarkers able to predict response to chemotherapy in patients with HGSOC is a critical step for prognosis and treatment of the disease. Several studies suggest that angiogenesis is an important process in the development of ovarian carcinoma and chemoresistance. The aim of this study was to identify a profile of angiogenesis-related genes as a biomarker for response to first-line chemotherapy in HGSOC. Materials and Methods: Formalin-fixed paraffin-embedded samples from 39 patients with HGSOC who underwent surgical cytoreduction and received a first-line chemotherapy with carboplatin and paclitaxel were included in this study. Expression levels of 82 angiogenesis-related genes were measured by quantitative real-time polymerase chain reaction using TaqMan low-density arrays. Results: Univariate analysis identified five genes [angiopoietin 1 (ANGPT1), aryl hydrocarbon receptor nuclear translocator (ARNT), CD34, epidermal growth factor (EGF) and matrix metallopeptidase 3 (MMP3)] as being statistically associated with response to treatment. Multivariable analysis by Lasso-penalized Cox regression generated a model with the combined expression of seven genes [angiotensinogen (AGT), CD34, EGF, erythropoietin receptor (EPOR), interleukin 8 (IL8), MMP3 and MMP7)]. The area under the receiver operating characteristics curve (0.679) and cross-validated Kaplan–Meier survival curves were used to estimate the accuracy of these predictors. Conclusion: An angiogenesis-related gene expression profile useful for response prediction in HGSOC was identified, supporting the important role of angiogenesis in HGSOC. ER -