Bioinformatics Analysis on Molecular Mechanism of Green Tea Compound Epigallocatechin‐3‐Gallate Against Ovarian Cancer. Issue 4 (23rd May 2017)

• Record Type: Journal Article
• Authors: Xinqiang, S; Mu, Z; Lei, C; Mun, LY
• Is Part Of: Clinical and translational science. Volume 10:Issue 4(2017)
• Page Start: 302
• Page End: 307
• Publication Date: 2017-05-23
• Subjects: Medicine, Experimental -- Periodicals; Medical innovations -- Periodicals; 616.027
• DOI: 10.1111/cts.12470
• Languages: English
• ISSNs: 1752-8054

Abstract

Abstract : Epigallocatechin‐3‐gallate (EGCG) is the most abundant and biologically active catechin in green tea, and it exerts multiple effects in humans through mechanisms that remain to be clarified. The present study used bioinformatics to identify possible mechanisms by which EGCG reduces the risk of ovarian cancer. Possible human protein targets of EGCG were identified in the PubChem database, possible human gene targets were identified in the National Center for Biotechnology Information database, and then both sets of targets were analyzed using Ingenuity Pathway Analysis (IPA). The results suggest that signaling proteins affected by EGCG in ovarian cancer, which include JUN, FADD, NFKB1, Bcl‐2, HIF1α, and MMP, are involved primarily in cell cycle, cellular assembly and organization, DNA replication, etc. These results identify several specific proteins and pathways that may be affected by EGCG in ovarian cancer, and they illustrate the power of integrative informatics and chemical fragment analysis for focusing mechanistic studies.