The Role of Natural and Semi-Synthetic Compounds in Ovarian Cancer: Updates on Mechanisms of Action, Current Trends and Perspectives.
Md Rezaul IslamMd Mominur RahmanPuja Sutro DharFeana Tasmim NowrinNasrin SultanaMuniya AkterAbdur RaufAnees Ahmed KhalilAlessandra GianoncelliGiovanni RibaudoPublished in: Molecules (Basel, Switzerland) (2023)
Ovarian cancer represents a major health concern for the female population: there is no obvious cause, it is frequently misdiagnosed, and it is characterized by a poor prognosis. Additionally, patients are inclined to recurrences because of metastasis and poor treatment tolerance. Combining innovative therapeutic techniques with established approaches can aid in improving treatment outcomes. Because of their multi-target actions, long application history, and widespread availability, natural compounds have particular advantages in this connection. Thus, effective therapeutic alternatives with improved patient tolerance hopefully can be identified within the world of natural and nature-derived products. Moreover, natural compounds are generally perceived to have more limited adverse effects on healthy cells or tissues, suggesting their potential role as valid treatment alternatives. In general, the anticancer mechanisms of such molecules are connected to the reduction of cell proliferation and metastasis, autophagy stimulation and improved response to chemotherapeutics. This review aims at discussing the mechanistic insights and possible targets of natural compounds against ovarian cancer, from the perspective of medicinal chemists. In addition, an overview of the pharmacology of natural products studied to date for their potential application towards ovarian cancer models is presented. The chemical aspects as well as available bioactivity data are discussed and commented on, with particular attention to the underlying molecular mechanism(s).
Keyphrases
- poor prognosis
- cell proliferation
- end stage renal disease
- long non coding rna
- public health
- mental health
- healthcare
- gene expression
- cell death
- chronic kidney disease
- depressive symptoms
- oxidative stress
- newly diagnosed
- prognostic factors
- signaling pathway
- physical activity
- peritoneal dialysis
- case report
- emergency department
- electronic health record
- social support
- cell cycle arrest
- machine learning
- social media
- combination therapy
- cell cycle
- artificial intelligence
- data analysis
- patient reported