Targeting Melanoma-Initiating Cells by Caffeine: In Silico and In Vitro Approaches.
Claudio TabolacciMartina CordellaStefania RossiMarialaura BonaccioAdriana EramoCarlo MischiatiSimone BeninatiLicia IacovielloAntonio FacchianoFrancesco FacchianoPublished in: Molecules (Basel, Switzerland) (2021)
The beneficial effects of coffee on human diseases are well documented, but the molecular mechanisms of its bioactive compounds on cancer are not completely elucidated. This is likely due to the large heterogeneity of coffee preparations and different coffee-based beverages, but also to the choice of experimental models where proliferation, differentiation and immune responses are differently affected. The aim of the present study was to investigate the effects of one of the most interesting bioactive compounds in coffee, i.e., caffeine, using a cellular model of melanoma at a defined differentiation level. A preliminary in silico analysis carried out on public gene-expression databases identified genes potentially involved in caffeine's effects and suggested some specific molecular targets, including tyrosinase. Proliferation was investigated in vitro on human melanoma initiating cells (MICs) and cytokine expression was measured in conditioned media. Tyrosinase was revealed as a key player in caffeine's mechanisms of action, suggesting a crucial role in immunomodulation through the reduction in IL-1β, IP-10, MIP-1α, MIP-1β and RANTES secretion onto MICs conditioned media. The potent antiproliferative effects of caffeine on MICs are likely to occur by promoting melanin production and reducing inflammatory signals' secretion. These data suggest tyrosinase as a key player mediating the effects of caffeine on melanoma.
Keyphrases
- induced apoptosis
- gene expression
- endothelial cells
- immune response
- signaling pathway
- cell cycle arrest
- skin cancer
- molecular docking
- single cell
- healthcare
- squamous cell carcinoma
- papillary thyroid
- endoplasmic reticulum stress
- mental health
- poor prognosis
- pluripotent stem cells
- young adults
- cell death
- cell proliferation
- electronic health record
- inflammatory response
- big data
- dendritic cells
- cancer therapy
- mass spectrometry
- toll like receptor
- artificial intelligence