title: New data on robustness of gene expression signatures in leukemia: comparison of three distinct total RNA preparation procedures.
abstract: BACKGROUND
  Microarray gene expression (MAGE) signatures allow insights into the transcriptional processes of leukemias and may evolve as a molecular diagnostic test. Introduction of MAGE into clinical practice of leukemia diagnosis will require comprehensive assessment of variation due to the methodologies. Here we systematically assessed the impact of three different total RNA isolation procedures on variation in expression data: method A: lysis of mononuclear cells, followed by lysate homogenization and RNA extraction; method B: organic solvent based RNA isolation, and method C: organic solvent based RNA isolation followed by purification.
  
  
  RESULTS
  We analyzed 27 pediatric acute leukemias representing nine distinct subtypes and show that method A yields better RNA quality, was associated with more differentially expressed genes between leukemia subtypes, demonstrated the lowest degree of variation between experiments, was more reproducible, and was characterized with a higher precision in technical replicates. Unsupervised and supervised analyses grouped leukemias according to lineage and clinical features in all three methods, thus underlining the robustness of MAGE to identify leukemia specific signatures.
  
  
  CONCLUSIONS
  The signatures in the different subtypes of leukemias, regardless of the different extraction methods used, account for the biggest source of variation in the data. Lysis of mononuclear cells, followed by lysate homogenization and RNA extraction represents the optimum method for robust gene expression data and is thus recommended for obtaining robust classification results in microarray studies in acute leukemias.
authors.affiliation: University of Padua, Laboratory of Molecular Diagnostic, Department of Pediatric Oncology, Padua, Italy. marta.campodellorto@unipd.it
authors.forename: Marta
authors.initials: M
authors.lastname: Campo Dell'Orto
authors.forename: Andrea
authors.initials: A
authors.lastname: Zangrando
authors.forename: Luca
authors.initials: L
authors.lastname: Trentin
authors.forename: Rui
authors.initials: R
authors.lastname: Li
authors.forename: Wei-min
authors.initials: WM
authors.lastname: Liu
authors.forename: Geertruy
authors.initials: G
authors.lastname: te Kronnie
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Basso
authors.forename: Alexander
authors.initials: A
authors.lastname: Kohlmann
mesh_terms: D000704:Analysis of Variance; D014408:Biomarkers, Tumor / Q000235:genetics; D020869:Gene Expression Profiling; D015973:Gene Expression Regulation, Leukemic; D005821:Genetic Techniques; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007938:Leukemia / Q000235:genetics* / Q000378:metabolism*; D007963:Leukocytes, Mononuclear / Q000378:metabolism; D008954:Models, Biological; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis; D012313:RNA / Q000378:metabolism; D012334:RNA, Neoplasm; D012997:Solvents / Q000737:chemistry
chemical_list: D014408:Biomarkers, Tumor; D012334:RNA, Neoplasm; D012997:Solvents; D012313:RNA