Title |
Investigation of Phenolic Composition and Anticancer Properties of Ethanolic Extracts of Japanese Quince Leaves / |
Authors |
Zvikas, Vaidotas ; Urbanaviciute, Ieva ; Bernotiene, Rasa ; Kulakauskiene, Deimante ; Morkūnaitė, Urtė ; Balion, Zbigniev ; Majiene, Daiva ; Liaudanskas, Mindaugas ; Viškelis, Pranas ; Jekabsone, Aiste ; Jakštas, Valdas |
DOI |
10.3390/foods10010018 |
Full Text |
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Is Part of |
Foods.. Basel : MDPI. 2020, vol. 10, no. 1, 18, p. 1-13.. ISSN 2304-8158 |
Keywords [eng] |
Chaenomeles japonica leaves ; phenolic compounds ; glioblastoma ; anticancer activity |
Abstract [eng] |
Glioblastoma multiforme is an aggressive and invasive disease with no efficient therapy available, and there is a great need for finding alternative treatment strategies. This study aimed to investigate anticancer activity of the extracts of the Japanese quince (JQ) cultivars ‘Darius’, ‘Rondo’, and ‘Rasa’ leaf extracts on glioblastoma C6 and HROG36 cells. As identified by ultra high performance liquid chromatography electrospray ionization tandem mass spectrometry, the extracts contained three prevailing groups of phenols: hydroxycinnamic acid derivatives; flavan-3-ols; and flavonols. Sixteen phenols were detected; the predominant compound was chlorogenic acid. The sum of detected phenols varied significantly between the cultivars ranging from 9322 g/g (‘Rondo’) to 17,048 g/g DW (‘Darius’). Incubation with the extracts decreased the viability of glioblastoma HROG36 cells with an efficiency similar to temozolomide, a drug used for glioblastoma treatment. In the case of C6 glioblastoma cells, the extracts were even more efficient than temozolomide. Interestingly, primary cerebellar neuronal-glial cells were significantly less sensitive to the extracts compared to the cancer cell lines. The results showed that JQ leaf ethanol extracts are rich in phenolic compounds, can efficiently reduce glioblastoma cell viability while preserving non-cancerous cells, and are worth further investigations as potential anticancer drugs. |
Published |
Basel : MDPI |
Type |
Journal article |
Language |
English |
Publication date |
2020 |
CC license |
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