Literature DB >> 30194194

Predicting Response to Standard First-line Treatment in High-grade Serous Ovarian Carcinoma by Angiogenesis-related Genes.

Marta Mendiola1,2, Andrés Redondo3,4,5, Victoria Heredia-Soto1,2, Jesús Herranz6, Alberto Berjón1,7, Alicia Hernández5,8, María Miguel-Martín1, Roberto Crespo4, Jorge Barriuso9, Patricia Cruz3, Laura Yébenes1,7, Alberto Peláez-García1, Beatriz Castelo3,4, Ana Ramírez DE Molina10, Jaime Feliu2,3,4,5,11, David Hardisson12,5,7.   

Abstract

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. Copyright
© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Entities:  

Keywords:  Ovarian cancer; angiogenesis; chemotherapy; gene-expression profile; high-grade serous carcinoma; response prediction

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Year:  2018        PMID: 30194194     DOI: 10.21873/anticanres.12869

Source DB:  PubMed          Journal:  Anticancer Res        ISSN: 0250-7005            Impact factor:   2.480


  2 in total

Review 1.  The Ovarian Cancer Tumor Immune Microenvironment (TIME) as Target for Therapy: A Focus on Innate Immunity Cells as Therapeutic Effectors.

Authors:  Denisa Baci; Annalisa Bosi; Matteo Gallazzi; Manuela Rizzi; Douglas M Noonan; Alessandro Poggi; Antonino Bruno; Lorenzo Mortara
Journal:  Int J Mol Sci       Date:  2020-04-28       Impact factor: 5.923

2.  Antitumoral Effect of Plocabulin in High Grade Serous Ovarian Carcinoma Cell Line Models.

Authors:  Victoria Heredia-Soto; Javier Escudero; María Miguel; Patricia Ruiz; Alejandro Gallego; Alberto Berjón; Alicia Hernández; Marta Martínez-Díez; Shuyu Zheng; Jing Tang; David Hardisson; Jaime Feliu; Andrés Redondo; Marta Mendiola
Journal:  Front Oncol       Date:  2022-03-17       Impact factor: 6.244

  2 in total

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