Clinically potential subclasses of retinoid synergists revealed by gene expression profiling

Seiichi Ishida, Yukari Shigemoto-Mogami, Hiroyuki Kagechika, Koichi Shudo, Shogo Ozawa, Jun Ichi Sawada, Yasuo Ohno, Kazuhide Inoue

Research output: Contribution to journalArticlepeer-review

29 Citations (Scopus)


Retinoids have chemopreventive and therapeutic potency in oncology and dermatology, although their application is restricted by many undesirable side effects. For the development of more effective and less toxic retinoids, gene expression analyses using DNA microarrays have the potential to supplement conventional screening methods, which are based on the changes in cell morphology and/or function. In this study, we applied the class prediction algorithm, which was used in the molecular phenotyping of tumors, for the classification of synthetic retinoids (Am80 and Tp80) and retinoid synergists (HX630, TZ335, and PA024) as all-trans retinoic acid-like, 9-cis retinoic acid-like, and control-like classes. By analyzing the effects of all-trans retinoic acid and 9-cis retinoic acid on the gene expressions in a human promyelocytic leukemia cell line, HL60, we successfully selected 50 marker genes whose expression pattern could distinguish these classes. Moreover, the classification revealed the existence of two subclasses among the retinoid synergists used with Am80. Close inspection of the DNA microarray analyses indicated that these two subclasses had different effects on the apoptosis of HL60 cells, and this was confirmed by in vivo experiments. These results indicate that the retinoidal activity of Am80, which has already been used in clinical trials, could be modulated differently by the two classes of retinoid synergists. Thus, these two subclasses of retinoid synergists have the potency to widen the usage of Am80. Our analyses demonstrated that the gene expression profiling could provide important information for developing useful retinoid synergists by compensating conventional screening methods.

Original languageEnglish
Pages (from-to)49-58
Number of pages10
JournalMolecular cancer therapeutics
Issue number1
Publication statusPublished - Jan 2003
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research


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