title: Proteomic-based prediction of clinical behavior in adult acute lymphoblastic leukemia.
abstract: BACKGROUND
  Response in adult acute lymphoblastic leukemia (ALL) can be achieved in a majority of patients. However, unlike pediatric ALL, recurrence is common in adult ALL, and the ability to predict at an early stage which patients are most likely to experience recurrence may help in devising new therapeutic approaches to prevent recurrence.
  
  
  METHODS
  Peripheral blood plasma from 57 patients with confirmed ALL was obtained before induction therapy for proteomic analysis. Follow-up continued for a median period of 71 weeks. For each plasma sample, 4 fractions eluted from a strong anion column were applied to 3 different ProteinChip array surfaces, and 12 surface-enhanced laser desorption/ionization (SELDI) spectra were generated. Peaks that correlated with recurrence were identified and decision trees were constructed and evaluated, using only 2 peaks per predictive tree.
  
  
  RESULTS
  The best decision trees provided strong positive prediction of recurrence, with correct predictions 84% to 92% of the time, whereas negative prediction of patients who did not experience recurrence was less robust, with 62% to 74% accuracy. Prediction of recurrence was independent of cytogenetics, bone marrow blast count, lactate dehydrogenase, beta-2-microglobulin, or surface markers. Positive prediction of L3 morphological classification was achieved in 80% of test cases.
  
  
  CONCLUSIONS
  Peripheral blood plasma is adequate to predict clinical behavior in ALL patients irrespective of the percentage of bone marrow blasts. Proteomic analysis of plasma offers a useful approach for profiling patients with ALL.
authors.affiliation: Quest Diagnostics Nichols Institute, San Juan Capistrano, CA 92690, USA. x.albitar@questdiagnostics.com
authors.forename: Maher
authors.initials: M
authors.lastname: Albitar
authors.forename: Steven J
authors.initials: SJ
authors.lastname: Potts
authors.forename: Francis J
authors.initials: FJ
authors.lastname: Giles
authors.forename: Susan
authors.initials: S
authors.lastname: O'Brien
authors.forename: Michael
authors.initials: M
authors.lastname: Keating
authors.forename: Deborah
authors.initials: D
authors.lastname: Thomas
authors.forename: Charlotte
authors.initials: C
authors.lastname: Clarke
authors.forename: Iman
authors.initials: I
authors.lastname: Jilani
authors.forename: Christine
authors.initials: C
authors.lastname: Aguilar
authors.forename: Elihu
authors.initials: E
authors.lastname: Estey
authors.forename: Hagop
authors.initials: H
authors.lastname: Kantarjian
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D002675:Child, Preschool; D003663:Decision Trees; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D054198:Precursor Cell Lymphoblastic Leukemia-Lymphoma / Q000097:blood / Q000235:genetics* / Q000473:pathology*; D011237:Predictive Value of Tests; D011379:Prognosis; D040081:Protein Array Analysis; D040901:Proteomics; D012008:Recurrence