854
Views
26
CrossRef citations to date
0
Altmetric
Review Article

Prediction of therapy response in ovarian cancer: Where are we now?

ORCID Icon, , &
Pages 233-266 | Received 14 Jan 2017, Accepted 27 Mar 2017, Published online: 26 Apr 2017
 

Abstract

Therapy resistance is a major challenge in the management of ovarian cancer (OC). Advances in detection and new technology validation have led to the emergence of biomarkers that can predict responses to available therapies. It is important to identify predictive biomarkers to select resistant and sensitive patients in order to reduce important toxicities, to reduce costs and to increase survival. The discovery of predictive and prognostic biomarkers for monitoring therapy is a developing field and provides promising perspectives in the era of personalized medicine. This review article will discuss the biology of OC with a focus on targetable pathways; current therapies; mechanisms of resistance; predictive biomarkers for chemotherapy, antiangiogenic and DNA-targeted therapies, and optimal cytoreductive surgery; and the emergence of liquid biopsy using recent studies from the Medline database and ClinicalTrials.gov.

Acknowledgements

The authors wish to thank: Dr. Anisha Gokarna (Nanophotonics group, Laboratoire de Nanotechnologie et d'Instrumentation Optique, Université de Technologie de Troyes, France) who assisted in the proof-reading of the article and Hind Kadiri (PhD student, Cifre UTT – SILSEF, Laboratoire de Nanotechnologie et d'Instrumentation Optique, Institut Charles Delaunay - UMR CNRS 6279, Université de technologie de Troyes, France) for her constant encouragement.

Disclosure statement

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of this article.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 65.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 654.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.