A novel algorithm for simplification of complex gene classifiers in cancer

Raphael A. Wilson, Ling Teng, Karen M. Bachmeyer, Mei Lin Z Bissonnette, Aliya N. Husain, David M. Parham, Timothy J. Triche, Michele R. Wing, Julie M. Gastier-Foster, Frederic G. Barr, Douglas S. Hawkins, James R. Anderson, Stephen X. Skapek, Samuel L. Volchenboum

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


The clinical application of complex molecular classifiers as diagnostic or prognostic tools has been limited by the time and cost needed to apply them to patients. Using an existing 50-gene expression signature known to separate two molecular subtypes of the pediatric cancer rhabdomyosarcoma, we show that an exhaustive iterative search algorithm can distill this complex classifier down to two or three features with equal discrimination. We validated the two-gene signatures using three separate and distinct datasets, including one that uses degraded RNA extracted from formalin-fixed, paraffin-embedded material. Finally, to show the generalizability of our algorithm, we applied it to a lung cancer dataset to find minimal gene signatures that can distinguish survival. Our approach can easily be generalized and coupled to existing technical platforms to facilitate the discovery of simplified signatures that are ready for routine clinical use.

Original languageEnglish (US)
Pages (from-to)5625-5632
Number of pages8
JournalCancer research
Issue number18
StatePublished - Sep 15 2013

ASJC Scopus subject areas

  • Oncology
  • Cancer Research


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