RT Journal Article
SR Electronic
T1 Predicting Response to Standard First-line Treatment in High-grade Serous Ovarian Carcinoma by Angiogenesis-related Genes
JF Anticancer Research
JO Anticancer Res
FD International Institute of Anticancer Research
SP 5393
OP 5400
DO 10.21873/anticanres.12869
VO 38
IS 9
A1 MARTA MENDIOLA
A1 ANDRÉS REDONDO
A1 VICTORIA HEREDIA-SOTO
A1 JESÚS HERRANZ
A1 ALBERTO BERJÓN
A1 ALICIA HERNÁNDEZ
A1 MARÍA MIGUEL-MARTÍN
A1 ROBERTO CRESPO
A1 JORGE BARRIUSO
A1 PATRICIA CRUZ
A1 LAURA YÉBENES
A1 ALBERTO PELÁEZ-GARCÍA
A1 BEATRIZ CASTELO
A1 ANA RAMÍREZ DE MOLINA
A1 JAIME FELIU
A1 DAVID HARDISSON
YR 2018
UL http://ar.iiarjournals.org/content/38/9/5393.abstract
AB 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.