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

Bentley J. Hanish, Jennifer Hackney Price, Ichiro Kaneko, Ning Ma, Arjan van der Vaart, Carl Wagner, Peter Jurutka, Pamela Marshall

Research output: Contribution to journalArticle

2 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)36-49
Number of pages14
JournalSteroids
Volume135
DOIs
StatePublished - Jul 2018

Keywords

  • Analytics
  • Cancer
  • Gene expression
  • Microarrays
  • RXR
  • Rexinoids

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Endocrinology
  • Pharmacology
  • Clinical Biochemistry
  • Organic Chemistry

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