Biomarkers in Ovarian Cancer: Towards Personalized Medicine.
Carlos López-PortuguésMaría Montes-BayónPaula DíezPublished in: Proteomes (2024)
Ovarian cancer is one of the deadliest cancers in women. The lack of specific symptoms, especially at the initial stages of disease development, together with the malignancy heterogeneity, lower the life expectancy of patients. Aiming to improve survival rates, diagnostic and prognostic biomarkers are increasingly employed in clinics, providing gynecologists and oncologists with new tools to guide their treatment decisions. Despite the vast number of investigations, there is still an urgent need to discover more ovarian cancer subtype-specific markers which could further improve patient classification. To this end, high-throughput screening technologies, like mass spectrometry, are applied to deepen the tumoral cellular landscape and describe the malignant phenotypes. As for disease treatment, new targeted therapies, such as those based on PARP inhibitors, have shown great efficacy in destroying the tumoral cells. Likewise, drug-nanocarrier systems targeting the tumoral cells have exhibited promising results. In this narrative review, we summarize the latest achievements in the pursuit of biomarkers for ovarian cancer and recent anti-tumoral therapies.
Keyphrases
- induced apoptosis
- mass spectrometry
- cell cycle arrest
- primary care
- machine learning
- newly diagnosed
- single cell
- oxidative stress
- deep learning
- ejection fraction
- dna damage
- high resolution
- cell death
- liquid chromatography
- drug delivery
- endoplasmic reticulum stress
- pregnant women
- dna repair
- combination therapy
- case report
- replacement therapy
- depressive symptoms
- chronic kidney disease
- simultaneous determination
- sleep quality
- childhood cancer
- cervical cancer screening