title: Routine use of microarray-based gene expression profiling to identify patients with low cytogenetic risk acute myeloid leukemia: accurate results can be obtained even with suboptimal samples.
abstract: BACKGROUND
  Gene expression profiling has shown its ability to identify with high accuracy low cytogenetic risk acute myeloid leukemia such as acute promyelocytic leukemia and leukemias with t(8;21) or inv(16). The aim of this gene expression profiling study was to evaluate to what extent suboptimal samples with low leukemic blast load (range, 2-59%) and/or poor quality control criteria could also be correctly identified.
  
  
  METHODS
  Specific signatures were first defined so that all 71 acute promyelocytic leukemia, leukemia with t(8;21) or inv(16)-AML as well as cytogenetically normal acute myeloid leukemia samples with at least 60% blasts and good quality control criteria were correctly classified (training set). The classifiers were then evaluated for their ability to assign to the expected class 111 samples considered as suboptimal because of a low leukemic blast load (n = 101) and/or poor quality control criteria (n = 10) (test set).
  
  
  RESULTS
  With 10-marker classifiers, all training set samples as well as 97 of the 101 test samples with a low blast load, and all 10 samples with poor quality control criteria were correctly classified. Regarding test set samples, the overall error rate of the class prediction was below 4 percent, even though the leukemic blast load was as low as 2%. Sensitivity, specificity, negative and positive predictive values of the class assignments ranged from 91% to 100%. Of note, for acute promyelocytic leukemia and leukemias with t(8;21) or inv(16), the confidence level of the class assignment was influenced by the leukemic blast load.
  
  
  CONCLUSIONS
  Gene expression profiling and a supervised method requiring 10-marker classifiers enable the identification of favorable cytogenetic risk acute myeloid leukemia even when samples contain low leukemic blast loads or display poor quality control criterion.
authors.affiliation: Plateforme SNP, Transcriptome & Epigénomique, Centre Hospitalier Universitaire, Angers, France.
authors.forename: Diane Raingeard
authors.initials: DR
authors.lastname: de la Blétière
authors.forename: Odile
authors.initials: O
authors.lastname: Blanchet
authors.forename: Pascale
authors.initials: P
authors.lastname: Cornillet-Lefèbvre
authors.forename: Anne
authors.initials: A
authors.lastname: Coutolleau
authors.forename: Laurence
authors.initials: L
authors.lastname: Baranger
authors.forename: Franck
authors.initials: F
authors.lastname: Geneviève
authors.forename: Isabelle
authors.initials: I
authors.lastname: Luquet
authors.forename: Mathilde
authors.initials: M
authors.lastname: Hunault-Berger
authors.forename: Annaelle
authors.initials: A
authors.lastname: Beucher
authors.forename: Aline
authors.initials: A
authors.lastname: Schmidt-Tanguy
authors.forename: Marc
authors.initials: M
authors.lastname: Zandecki
authors.forename: Yves
authors.initials: Y
authors.lastname: Delneste
authors.forename: Norbert
authors.initials: N
authors.lastname: Ifrah
authors.forename: Philippe
authors.initials: P
authors.lastname: Guardiola
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D045744:Cell Line, Tumor; D020732:Cytogenetic Analysis / Q000379:methods* / Q000592:standards; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods* / Q000592:standards; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D006801:Humans; D015470:Leukemia, Myeloid, Acute / Q000235:genetics*; D008297:Male; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods* / Q000592:standards; D011786:Quality Control; D055815:Young Adult