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Article Publish Status: FREE
Abstract Title:

Metabolic Profiling-based Data-mining for an Effective Chemical Combination to Induce Apoptosis of Cancer Cells.

Abstract Source:

Sci Rep. 2015 ;5:9474. Epub 2015 Mar 31. PMID: 25824377

Abstract Author(s):

Motofumi Kumazoe, Yoshinori Fujimura, Shiori Hidaka, Yoonhee Kim, Kanako Murayama, Mika Takai, Yuhui Huang, Shuya Yamashita, Motoki Murata, Daisuke Miura, Hiroyuki Wariishi, Mari Maeda-Yamamoto, Hirofumi Tachibana

Article Affiliation:

Motofumi Kumazoe

Abstract:

Green tea extract (GTE) induces apoptosis of cancer cells without adversely affecting normal cells. Several clinical trials reported that GTE was well tolerated and had potential anti-cancer efficacy. Epigallocatechin-3-O-gallate (EGCG) is the primary compound responsible for the anti-cancer effect of GTE; however, the effect of EGCG alone is limited. To identify GTE compounds capable of potentiating EGCG bioactivity, we performed metabolic profiling of 43 green tea cultivar panels by liquid chromatography-mass spectrometry (LC-MS). Here, we revealed the polyphenol eriodictyol significantly potentiated apoptosis induction by EGCG in vitro and in a mouse tumour model by amplifying EGCG-induced activation of the 67-kDa laminin receptor (67LR)/protein kinase B/endothelial nitric oxide synthase/protein kinase C delta/acid sphingomyelinase signalling pathway. Our results show that metabolic profiling is an effective chemical-mining approach for identifying botanical drugs with therapeutic potential against multiple myeloma. Metabolic profiling-based data mining could be an efficient strategy for screening additional bioactive compounds and identifying effective chemical combinations.

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Sayer Ji
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Easy Turmeric recipes + The Dark Side of Wheat

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