Literature DB >> 14684422

Gene expression profile of adult T-cell acute lymphocytic leukemia identifies distinct subsets of patients with different response to therapy and survival.

Sabina Chiaretti1, Xiaochun Li, Robert Gentleman, Antonella Vitale, Marco Vignetti, Franco Mandelli, Jerome Ritz, Robin Foa.   

Abstract

Gene expression profiles were examined in 33 adult patients with T-cell acute lymphocytic leukemia (T-ALL). Nonspecific filtering criteria identified 313 genes differentially expressed in the leukemic cells. Hierarchical clustering of samples identified 2 groups that reflected the degree of T-cell differentiation but was not associated with clinical outcome. Comparison between refractory patients and those who responded to induction chemotherapy identified a single gene, interleukin 8 (IL-8), that was highly expressed in refractory T-ALL cells and a set of 30 genes that was highly expressed in leukemic cells from patients who achieved complete remission. We next identified 19 genes that were differentially expressed in T-ALL cells from patients who either had a relapse or remained in continuous complete remission. A model based on the expression of 3 of these genes was predictive of duration of remission. The 3-gene model was validated on a further set of T-ALL samples from 18 additional patients treated on the same clinical protocol. This study demonstrates that gene expression profiling can identify a limited number of genes that are predictive of response to induction therapy and remission duration in adult patients with T-ALL.

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Year:  2003        PMID: 14684422     DOI: 10.1182/blood-2003-09-3243

Source DB:  PubMed          Journal:  Blood        ISSN: 0006-4971            Impact factor:   22.113


  71 in total

1.  Independent filtering increases detection power for high-throughput experiments.

Authors:  Richard Bourgon; Robert Gentleman; Wolfgang Huber
Journal:  Proc Natl Acad Sci U S A       Date:  2010-05-11       Impact factor: 11.205

Review 2.  Advances in the molecular genetics of acute leukemia.

Authors:  Joseph M Scandura
Journal:  Curr Oncol Rep       Date:  2005-09       Impact factor: 5.075

Review 3.  DNA microarrays in the diagnosis and management of acute lymphoblastic leukemia.

Authors:  Adolfo A Ferrando; A Thomas Look
Journal:  Int J Hematol       Date:  2004-12       Impact factor: 2.490

4.  Metagene projection for cross-platform, cross-species characterization of global transcriptional states.

Authors:  Pablo Tamayo; Daniel Scanfeld; Benjamin L Ebert; Michael A Gillette; Charles W M Roberts; Jill P Mesirov
Journal:  Proc Natl Acad Sci U S A       Date:  2007-03-27       Impact factor: 11.205

5.  Genes contributing to minimal residual disease in childhood acute lymphoblastic leukemia: prognostic significance of CASP8AP2.

Authors:  Christian Flotho; Elaine Coustan-Smith; Deqing Pei; Shotaro Iwamoto; Guangchun Song; Cheng Cheng; Ching-Hon Pui; James R Downing; Dario Campana
Journal:  Blood       Date:  2006-04-20       Impact factor: 22.113

Review 6.  T-cell acute lymphoblastic leukemia.

Authors:  Sabina Chiaretti; Robin Foà
Journal:  Haematologica       Date:  2009-02       Impact factor: 9.941

7.  Empirical evaluation of consistency and accuracy of methods to detect differentially expressed genes based on microarray data.

Authors:  Dake Yang; Rudolph S Parrish; Guy N Brock
Journal:  Comput Biol Med       Date:  2013-12-13       Impact factor: 4.589

Review 8.  Systems analysis of high-throughput data.

Authors:  Rosemary Braun
Journal:  Adv Exp Med Biol       Date:  2014       Impact factor: 2.622

9.  Proteomic classification of acute leukemias by alignment-based quantitation of LC-MS/MS data sets.

Authors:  Eric J Foss; Dragan Radulovic; Derek L Stirewalt; Jerald Radich; Olga Sala-Torra; Era L Pogosova-Agadjanyan; Shawna M Hengel; Keith R Loeb; H Joachim Deeg; Soheil Meshinchi; David R Goodlett; Antonio Bedalov
Journal:  J Proteome Res       Date:  2012-09-11       Impact factor: 4.466

10.  A gene expression signature of CD34+ cells to predict major cytogenetic response in chronic-phase chronic myeloid leukemia patients treated with imatinib.

Authors:  Shannon K McWeeney; Lucy C Pemberton; Marc M Loriaux; Kristina Vartanian; Stephanie G Willis; Gregory Yochum; Beth Wilmot; Yaron Turpaz; Raji Pillai; Brian J Druker; Jennifer L Snead; Mary MacPartlin; Stephen G O'Brien; Junia V Melo; Thoralf Lange; Christina A Harrington; Michael W N Deininger
Journal:  Blood       Date:  2009-10-16       Impact factor: 22.113

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