Literature DB >> 28443762

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

Khalid El Bairi1, Mariam Amrani2, Abdul Hafeez Kandhro3, Said Afqir4.   

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.

Entities:  

Keywords:  Ovarian cancer; predictive biomarkers; resistance; therapy

Mesh:

Substances:

Year:  2017        PMID: 28443762     DOI: 10.1080/10408363.2017.1313190

Source DB:  PubMed          Journal:  Crit Rev Clin Lab Sci        ISSN: 1040-8363            Impact factor:   6.250


  7 in total

Review 1.  Starvation tactics using natural compounds for advanced cancers: pharmacodynamics, clinical efficacy, and predictive biomarkers.

Authors:  Khalid El Bairi; Mariam Amrani; Said Afqir
Journal:  Cancer Med       Date:  2018-05-06       Impact factor: 4.452

2.  CCNG1 (Cyclin G1) regulation by mutant-P53 via induction of Notch3 expression promotes high-grade serous ovarian cancer (HGSOC) tumorigenesis and progression.

Authors:  Ying Xu; Qing Zhang; Chunying Miao; Samina Dongol; Yinuo Li; Chenjuan Jin; Ruifeng Dong; Yingwei Li; Xingsheng Yang; Beihua Kong
Journal:  Cancer Med       Date:  2018-12-18       Impact factor: 4.452

3.  Dynamic analysis of N-glycomic and transcriptomic changes in the development of ovarian cancer cell line A2780 to its three cisplatin-resistant variants.

Authors:  Guiling Lin; Ran Zhao; Yisheng Wang; Jing Han; Yong Gu; Yiqing Pan; Changhao Ren; Shifang Ren; Congjian Xu
Journal:  Ann Transl Med       Date:  2020-03

4.  EIF5A2 enhances stemness of epithelial ovarian cancer cells via a E2F1/KLF4 axis.

Authors:  Kun Wang; Yiyang Wang; Yuanjian Wang; Shujie Liu; Chunyan Wang; Shuo Zhang; Tianli Zhang; Xingsheng Yang
Journal:  Stem Cell Res Ther       Date:  2021-03-16       Impact factor: 6.832

5.  Circulating Tumor Cell-Free DNA Genes as Prognostic Gene Signature for Platinum Resistant Ovarian Cancer Diagnosis.

Authors:  Camille C Gunderson; Rangasudhagar Radhakrishnan; Rohini Gomathinayagam; Sanam Husain; Sheeja Aravindan; Kathleen M Moore; Danny N Dhanasekaran; Muralidharan Jayaraman
Journal:  Biomark Insights       Date:  2022-03-28

6.  Tracing ovarian cancer research in Morocco: A bibliometric analysis.

Authors:  Khalid El Bairi; Ouissam Al Jarroudi; Said Afqir
Journal:  Gynecol Oncol Rep       Date:  2021-05-07

Review 7.  Repurposing anticancer drugs for the management of COVID-19.

Authors:  Khalid El Bairi; Dario Trapani; Angelica Petrillo; Cécile Le Page; Hanaa Zbakh; Bruno Daniele; Rhizlane Belbaraka; Giuseppe Curigliano; Said Afqir
Journal:  Eur J Cancer       Date:  2020-09-22       Impact factor: 9.162

  7 in total

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