Molecular Markers to Predict Prognosis and Treatment Response in Uterine Cervical Cancer

Uterine cervical cancer is one of the leading causes of cancer-related mortality in women worldwide. Each year, over half a million new cases are estimated, resulting in more than 300,000 deaths. While less-invasive, fertility-preserving surgical procedures can be offered to women in early stages, t...

Description complète

Enregistré dans:
Détails bibliographiques
Auteurs principaux: Maximilian Fleischmann, Georgios Chatzikonstantinou, Emmanouil Fokas, Jörn Wichmann, Hans Christiansen, Klaus Strebhardt, Claus Rödel, Nikolaos Tselis, Franz Rödel
Format: article
Langue:EN
Publié: MDPI AG 2021
Sujets:
Accès en ligne:https://doaj.org/article/a1a25d87ef9f46f1a1e8ad9cd3d0d1ba
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
Description
Résumé:Uterine cervical cancer is one of the leading causes of cancer-related mortality in women worldwide. Each year, over half a million new cases are estimated, resulting in more than 300,000 deaths. While less-invasive, fertility-preserving surgical procedures can be offered to women in early stages, treatment for locally advanced disease may include radical hysterectomy, primary chemoradiotherapy (CRT) or a combination of these modalities. Concurrent platinum-based chemoradiotherapy regimens remain the first-line treatments for locally advanced cervical cancer. Despite achievements such as the introduction of angiogenesis inhibitors, and more recently immunotherapies, the overall survival of women with persistent, recurrent or metastatic disease has not been extended significantly in the last decades. Furthermore, a broad spectrum of molecular markers to predict therapy response and survival and to identify patients with high- and low-risk constellations is missing. Implementation of these markers, however, may help to further improve treatment and to develop new targeted therapies. This review aims to provide comprehensive insights into the complex mechanisms of cervical cancer pathogenesis within the context of molecular markers for predicting treatment response and prognosis.