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Patient-derived tumor models in cancer research: Evaluation of the oncostatic effects of melatonin
- Source :
- Biomedicine & Pharmacotherapy, Vol 167, Iss , Pp 115581- (2023)
- Publication Year :
- 2023
- Publisher :
- Elsevier, 2023.
-
Abstract
- The development of new anticancer therapies tends to be very slow. Although their impact on potential candidates is confirmed in preclinical studies, ∼95 % of these new therapies are not approved when tested in clinical trials. One of the main reasons for this is the lack of accurate preclinical models. In this context, there are different patient-derived models, which have emerged as a powerful oncological tool: patient-derived xenografts (PDXs), patient-derived organoids (PDOs), and patient-derived cells (PDCs). Although all these models are widely applied, PDXs, which are created by engraftment of patient tumor tissues into mice, is considered more reliable. In fundamental research, the PDX model is used to evaluate drug-sensitive markers and, in clinical practice, to select a personalized therapeutic strategy. Melatonin is of particular importance in the development of innovative cancer treatments due to its oncostatic impact and lack of adverse effects. However, the literature regarding the oncostatic effect of melatonin in patient-derived tumor models is scant. This review aims to describe the important role of patient-derived models in the development of anticancer treatments, focusing, in particular, on PDX models, as well as their use in cancer research. This review also summarizes the existing literature on the anti-tumoral effect of melatonin in patient-derived models in order to propose future anti-neoplastic clinical applications.
Details
- Language :
- English
- ISSN :
- 07533322
- Volume :
- 167
- Issue :
- 115581-
- Database :
- Directory of Open Access Journals
- Journal :
- Biomedicine & Pharmacotherapy
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.0b3f5a33da46fda33933131f598776
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.biopha.2023.115581