Transcriptomic response of breast cancer cells to anacardic acid

David J. Schultz, Abirami Krishna, Stephany L. Vittitow, Negin Alizadeh-Rad, Penn Muluhngwi, Eric C. Rouchka, Carolyn M. Klinge

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

Anacardic acid (AnAc), a potential dietary agent for preventing and treating breast cancer, inhibited the proliferation of estrogen receptor α (ERα) positive MCF-7 and MDA-MB-231 triple negative breast cancer cells. To characterize potential regulators of AnAc action, MCF-7 and MDA-MB-231 cells were treated for 6 h with purified AnAc 24:1n5 congener followed by next generation transcriptomic sequencing (RNA-seq) and network analysis. We reported that AnAc-differentially regulated miRNA transcriptomes in each cell line and now identify AnAc-regulated changes in mRNA and lncRNA transcript expression. In MCF-7 cells, 80 AnAc-responsive genes were identified, including lncRNA MIR22HG. More AnAc-responsive genes (886) were identified in MDA-MB-231 cells. Only six genes were commonly altered by AnAc in both cell lines: SCD, INSIG1, and TGM2 were decreased and PDK4, GPR176, and ZBT20 were increased. Modeling of AnAc-induced gene changes suggests that AnAc inhibits monounsaturated fatty acid biosynthesis in both cell lines and increases endoplasmic reticulum stress in MDA-MB-231 cells. Since modeling of downregulated genes implicated NFκB in MCF-7, we confirmed that AnAc inhibited TNFα-induced NFκB reporter activity in MCF-7 cells. These data identify new targets and pathways that may account for AnAc's anti-proliferative and pro-apoptotic activity.

Original languageEnglish (US)
Article number8063
JournalScientific reports
Volume8
Issue number1
DOIs
StatePublished - Dec 1 2018
Externally publishedYes

Bibliographical note

Funding Information:
We thank Brandie N. Radde for performing the initial cell treatments and RNA isolation for RNA-seq. The research was supported in part by a pilot grant from the University of Louisville Center for Genetics and Molecular Medicine to C.M.K. and D.J.S.; and by an Internal Research Grant from the Office of the Executive Vice President for Research and Innovation of the University of Louisville to C.M.K.; E.C.R. and the KBRIN Bioinformatics core are supported by NIH/NIGMS grant P20 GM103436 (Nigel Cooper, PI); A.K. was supported by a NIH 5 T35 DK072923 (Carolyn M. Klinge, PI), S.L.V. was supported by the University of Louisville Summer Research Opportunity Program (SROP).

Publisher Copyright:
© 2018 The Author(s).

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