title: A novel algorithm for simplification of complex gene classifiers in cancer.
abstract: 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.
authors.affiliation: Authors' Affiliations: Division of Hematology/Oncology, Department of Pediatrics, University of Texas Southwestern Medical Center and Children's Medical Center, Dallas, Texas; Department of Pathology, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma; Department of Pathology, University of Southern California and Children's Hospital of Los Angeles, Los Angeles, California; Department of Pathology and Laboratory Medicine, Nationwide Children's Hospital and Department of Pathology and Pediatrics, The Ohio State University, Columbus, Ohio; National Cancer Institute, Bethesda, Maryland; Division of Hematology/Oncology, Department of Pediatrics, University of Washington and Seattle Children's Hospital, Seattle, Washington; Department of Biostatistics, College of Public Health, University of Nebraska Medical Center, Omaha, Nebraska; The Section of Pediatric Hematology/Oncology, Department of Pediatrics, Department of Pathology, Center for Research Informatics, and The Computation Institute, University of Chicago, Chicago, Illinois.
authors.forename: Raphael A
authors.initials: RA
authors.lastname: Wilson
authors.forename: Ling
authors.initials: L
authors.lastname: Teng
authors.forename: Karen M
authors.initials: KM
authors.lastname: Bachmeyer
authors.forename: Mei Lin Z
authors.initials: ML
authors.lastname: Bissonnette
authors.forename: Aliya N
authors.initials: AN
authors.lastname: Husain
authors.forename: David M
authors.initials: DM
authors.lastname: Parham
authors.forename: Timothy J
authors.initials: TJ
authors.lastname: Triche
authors.forename: Michele R
authors.initials: MR
authors.lastname: Wing
authors.forename: Julie M
authors.initials: JM
authors.lastname: Gastier-Foster
authors.forename: Frederic G
authors.initials: FG
authors.lastname: Barr
authors.forename: Douglas S
authors.initials: DS
authors.lastname: Hawkins
authors.forename: James R
authors.initials: JR
authors.lastname: Anderson
authors.forename: Stephen X
authors.initials: SX
authors.lastname: Skapek
authors.forename: Samuel L
authors.initials: SL
authors.lastname: Volchenboum
mesh_terms: D000465:Algorithms; D014408:Biomarkers, Tumor / Q000235:genetics*; D000071161:Forkhead Box Protein O1; D051858:Forkhead Transcription Factors / Q000235:genetics*; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D009369:Neoplasms / Q000145:classification* / Q000235:genetics* / Q000473:pathology; D020411:Oligonucleotide Array Sequence Analysis; D051761:Paired Box Transcription Factors / Q000235:genetics*
chemical_list: D014408:Biomarkers, Tumor; C085126:FOXO1 protein, human; D000071161:Forkhead Box Protein O1; D051858:Forkhead Transcription Factors; D051761:Paired Box Transcription Factors; C070835:PAX1 transcription factor
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