Original Article
Leukemia (2006) 20, 1751–1758. doi:10.1038/sj.leu.2404358; published online 17 August 2006
Identification of a molecular signature predictive of sensitivity to differentiation induction in acute myeloid leukemia
E Tagliafico1, E Tenedini1, R Manfredini1, A Grande1, F Ferrari1, E Roncaglia1, S Bicciato2, R Zini1, S Salati1, E Bianchi1, C Gemelli1, M Montanari1, T Vignudelli1, T Zanocco-Marani1, S Parenti1, P Paolucci3, G Martinelli4, P P Piccaluga4, M Baccarani4, G Specchia5, U Torelli1 and S Ferrari1
- 1Dipartimento di Scienze Biomediche, Sezione di Chimica Biologica, Università di Modena e Reggio Emilia, Modena, Italy
- 2Dipartimento di Processi Chimici dell'Ingegneria, Università di Padova, Padova, Italy
- 3Dipartimento Materno Infantile, Sezione di Oncoematologia Pediatrica, Università di Modena e Reggio Emilia, Modena, Italy
- 4Istituto di Ematologia ed Oncologia Medica 'L. e A. Seragnoli', Università di Bologna, Bologna, Italy
- 5Dipartimento di Scienze Mediche e del Lavoro, Università di Foggia, Ematologia, Foggia, Italy
Correspondence: Professor S Ferrari, Dipartimento di Scienze Biomediche, Universita' di Modena e Reggio Emilia, Via Campi 287, Modena 41100, Italy. E-mail: ferrari.sergio@unimore.it
Received 5 December 2005; Revised 25 May 2006; Accepted 5 June 2006; Published online 17 August 2006.
Abstract
Acute myeloid leukemia (AML) blasts are immature committed myeloid cells unable to spontaneously undergo terminal maturation, and characterized by heterogeneous sensitivity to natural differentiation inducers. Here, we show a molecular signature predicting the resistance or sensitivity of six myeloid cell lines to differentiation induced in vitro with retinoic acid or vitamin D. The identified signature was further validated by TaqMan assay for the prediction of response to an in vitro differentiation assay performed on 28 freshly isolated AML blast populations. The TaqMan assay successfully predicts the in vitro resistance or responsiveness of AML blasts to differentiation inducers. Furthermore, performing a meta-analysis of publicly available microarray data sets, we also show the accuracy of our prediction on known phenotypes and suggest that our signature could become useful for the identification of patients eligible for new therapeutic strategies.
Keywords:
gene expression profiling, microarrays, acute myeloid leukemia, differentating therapy
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