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Steroids. 2018 Jul;135:36-49. doi: 10.1016/j.steroids.2018.04.009. Epub 2018 Apr 26.

A novel gene expression analytics-based approach to structure aided design of rexinoids for development as next-generation cancer therapeutics.

Author information

1
New College of Interdisciplinary Arts and Sciences, Arizona State University, Glendale, AZ, United States.
2
New College of Interdisciplinary Arts and Sciences, Arizona State University, Glendale, AZ, United States; University of Arizona College of Medicine-Phoenix, Department of Basic Medical Sciences, Phoenix, AZ, United States; Department of Molecular Nutrition, Institution of Health Bioscience, University of Tokushima Graduate School, Kuramoto-cho, Japan.
3
Department of Chemistry, University of South Florida, Tampa, FL 33620, United States.
4
New College of Interdisciplinary Arts and Sciences, Arizona State University, Glendale, AZ, United States; University of Arizona College of Medicine-Phoenix, Department of Basic Medical Sciences, Phoenix, AZ, United States; University of Arizona Cancer Center, Tucson, AZ, United States.
5
New College of Interdisciplinary Arts and Sciences, Arizona State University, Glendale, AZ, United States. Electronic address: pamela.marshall@asu.edu.

Abstract

Rexinoids are powerful ligands that bind to retinoid-X-receptors (RXRs) and show great promise as therapeutics for a wide range of diseases, including cancer. However, only one rexinoid, bexarotene (Targretin TM) has been successfully transitioned from the bench to the clinic and used to treat cutaneous T-cell lymphoma (CTCL). Our goal is to develop novel potent rexinoids with a less untoward side effect profile than bexarotene. To this end, we have synthesized a wide array of rexinoids with EC50 values and biological activity similar to bexarotene. In order to determine their suitability for additional downstream analysis, and to identify potential candidate analogs for clinical translation, we treated human CTCL cells in culture and employed microarray technology to assess gene expression profiles. We analyzed twelve rexinoids and found they could be stratified into three distinct categories based on their gene expression: similar to bexarotene, moderately different from bexarotene, and substantially different from bexarotene. Surprisingly, small changes in the structure of the bexarotene parent compound led to marked differences in gene expression profiles. Furthermore, specific analogs diverged markedly from our hypothesis in expression of genes expected to be important for therapeutic promise. However, promoter analysis of genes whose expression was analyzed indicates general regulatory trends along structural frameworks. Our results suggest that certain structural motifs, particularly the basic frameworks found in analog 4 and analog 9, represent important starting points to exploit in generating additional rexinoids for future study and therapeutic applications.

KEYWORDS:

Analytics; Cancer; Gene expression; Microarrays; RXR; Rexinoids

PMID:
29704526
PMCID:
PMC5977990
DOI:
10.1016/j.steroids.2018.04.009
[Indexed for MEDLINE]
Free PMC Article

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