title: Molecular classification of human cancers using a 92-gene real-time quantitative polymerase chain reaction assay.
abstract: BACKGROUND
  Correct diagnosis of the tissue origin of a metastatic cancer is the first step in disease management, but it is frequently difficult using standard pathologic methods. Microarray-based gene expression profiling has shown great promise as a new tool to address this challenge.
  
  
  OBJECTIVE
  Adoption of microarray technologies in the clinic remains limited. We aimed to bridge this technological gap by developing a real-time quantitative polymerase chain reaction (RT-PCR) assay.
  
  
  METHODS
  We constructed a microarray database of 466 frozen and 112 formalin-fixed, paraffin-embedded (FFPE) samples of both primary and metastatic tumors, measuring expression of 22,000 genes. From the microarray database, we used a genetic algorithm to search for gene combinations optimal for multitumor classification. A 92-gene RT-PCR assay was then designed and used to generate a database for 481 frozen and 119 FFPE tumor samples.
  
  
  RESULTS
  The microarray-based K-nearest neighbor classifier demonstrated 84% accuracy in classifying 39 tumor types via cross-validation and 82% accuracy in predicting 112 independent FFPE samples. We successfully translated the microarray database to the RT-PCR platform, which allowed an overall success rate of 87% in classifying 32 different tumor classes in the validation set of 119 FFPE tumor samples.
  
  
  CONCLUSIONS
  The RT-PCR-based expression assay involving 92 genes represents a powerful tool for accurately and objectively identifying the site of origin for metastatic tumors, especially in the cases of cancer of unknown primary. The assay uses RT-PCR and routine FFPE samples, making it suitable for rapid clinical adoption.
authors.affiliation: Research and Development, Arcturus Bioscience, Inc, Carlsbad, CA 92008, USA.
authors.forename: Xiao-Jun
authors.initials: XJ
authors.lastname: Ma
authors.forename: Rajesh
authors.initials: R
authors.lastname: Patel
authors.forename: Xianqun
authors.initials: X
authors.lastname: Wang
authors.forename: Ranelle
authors.initials: R
authors.lastname: Salunga
authors.forename: Jaji
authors.initials: J
authors.lastname: Murage
authors.forename: Rupal
authors.initials: R
authors.lastname: Desai
authors.forename: J Todd
authors.initials: JT
authors.lastname: Tuggle
authors.forename: Wei
authors.initials: W
authors.lastname: Wang
authors.forename: Shirley
authors.initials: S
authors.lastname: Chu
authors.forename: Kimberly
authors.initials: K
authors.lastname: Stecker
authors.forename: Rajiv
authors.initials: R
authors.lastname: Raja
authors.forename: Howard
authors.initials: H
authors.lastname: Robin
authors.forename: Mat
authors.initials: M
authors.lastname: Moore
authors.forename: David
authors.initials: D
authors.lastname: Baunoch
authors.forename: Dennis
authors.initials: D
authors.lastname: Sgroi
authors.forename: Mark
authors.initials: M
authors.lastname: Erlander
mesh_terms: D000465:Algorithms; D016208:Databases, Factual; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D008297:Male; D009362:Neoplasm Metastasis / Q000175:diagnosis* / Q000235:genetics*; D009369:Neoplasms / Q000145:classification / Q000175:diagnosis / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D020133:Reverse Transcriptase Polymerase Chain Reaction / Q000379:methods*