Diagnostics and Treatment of Ovarian Cancer in the Era of Precision Medicine - Opportunities and Challenges

Overview

Journal Front Oncol

Specialty Oncology

Date 2023 Sep 25

PMID 37746296

Authors

Patrycja Aleksandra Buklaho

Joanna Kisluk

Jacek Niklinski

Affiliations

Soon will be listed here.

Abstract

Due to predictions of increasing incidences and deaths from ovarian cancer, this neoplasm is a challenge for modern health care. The advent of NGS technology has made it possible to understand the molecular characteristics of many cancers, including ovarian cancer. The data obtained in research became the basis for the development of molecularly targeted therapies thus leading to the entry of NGS analysis into the diagnostic process of oncological patients. This review presents targeted therapies currently in preclinical or clinical trials, whose promising results offer hope for their use in clinical practice in the future. As more therapeutic options emerge, it will be necessary to modify molecular diagnostic regimens to select the best treatment for a given patient. New biomarkers are needed to predict the success of planned therapy. An important aspect of public health is molecular testing in women with a familial predisposition to ovarian cancer enabling patients to be included in prevention programs. NGS technology, despite its high throughput, poses many challenges, from the quality of the diagnostic material used for testing to the interpretation of results and classification of sequence variants. The article highlights the role of molecular testing in ongoing research and also its role in the diagnostic and therapeutic process in the era of personalized medicine. The spread of genetic testing in high-risk groups, the introduction of more targeted therapies and also the possibility of agnostic therapies could significantly improve the health situation for many women worldwide.

Citing Articles

A disulfidptosis-related lncRNAs cluster to forecast the prognosis and immune landscapes of ovarian cancer.

Wei J, Wang M, Wu Y Front Genet. 2024; 15:1397011.

PMID: 39045330 PMC: 11263023. DOI: 10.3389/fgene.2024.1397011.

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