Literature DB >> 14603332

Pediatric acute lymphoblastic leukemia (ALL) gene expression signatures classify an independent cohort of adult ALL patients.

A Kohlmann1, C Schoch, S Schnittger, M Dugas, W Hiddemann, W Kern, T Haferlach.   

Abstract

Recent reports support a possible future application of gene expression profiling for the diagnosis of leukemias. However, the robustness of subtype-specific gene expression signatures has to be proven on independent patient samples. Here, we present gene expression data of 34 adult acute lymphoblastic leukemia (ALL) patients (Affymetrix U133A microarrays). Support Vector Machines (SVMs) were applied to stratify our samples based on given gene lists reported to predict MLL, BCR-ABL, and T-ALL, as well as MLL and non-MLL gene rearrangement positive pediatric ALL. In addition, seven other B-precursor ALL cases not bearing t(9;22) or t(11q23)/MLL chromosomal aberrations were analyzed. Using top differentially expressed genes, hierarchical cluster and principal component analyses demonstrate that the genetically more heterogeneous B-precursor ALL samples intercalate with BCR-ABL-positive cases, but were clearly distinct from T-ALL and MLL profiles. Similar expression signatures were observed for both heterogeneous B-precursor ALL and for BCR-ABL-positive cases. As an unrelated laboratory, we demonstrate that gene signatures defined for childhood ALL were also capable of stratifying distinct subtypes in our cohort of adult ALL patients. As such, previously reported gene expression patterns identified by microarray technology are validated and confirmed on truly independent leukemia patient samples.

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Year:  2004        PMID: 14603332     DOI: 10.1038/sj.leu.2403167

Source DB:  PubMed          Journal:  Leukemia        ISSN: 0887-6924            Impact factor:   11.528


  18 in total

Review 1.  Emerging technologies in paediatric leukaemia.

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Journal:  Am J Respir Crit Care Med       Date:  2005-03-04       Impact factor: 21.405

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.  Loss of Pax5 Exploits Sca1-BCR-ABLp190 Susceptibility to Confer the Metabolic Shift Essential for pB-ALL.

Authors:  Alberto Martín-Lorenzo; Franziska Auer; Lai N Chan; Idoia García-Ramírez; Inés González-Herrero; Guillermo Rodríguez-Hernández; Christoph Bartenhagen; Martin Dugas; Michael Gombert; Sebastian Ginzel; Oscar Blanco; Alberto Orfao; Diego Alonso-López; Javier De Las Rivas; Maria B García-Cenador; Francisco J García-Criado; Markus Müschen; Isidro Sánchez-García; Arndt Borkhardt; Carolina Vicente-Dueñas; Julia Hauer
Journal:  Cancer Res       Date:  2018-02-28       Impact factor: 12.701

5.  Clinical utility of microarray-based gene expression profiling in the diagnosis and subclassification of leukemia: report from the International Microarray Innovations in Leukemia Study Group.

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Journal:  J Clin Oncol       Date:  2010-04-20       Impact factor: 44.544

6.  Identification of genomic classifiers that distinguish induction failure in T-lineage acute lymphoblastic leukemia: a report from the Children's Oncology Group.

Authors:  Stuart S Winter; Zeyu Jiang; Hadya M Khawaja; Timothy Griffin; Meenakshi Devidas; Barbara L Asselin; Richard S Larson
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7.  An intact gut microbiome protects genetically predisposed mice against leukemia.

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Journal:  Blood       Date:  2020-10-29       Impact factor: 22.113

8.  Comprehensive genomic analysis reveals FLT3 activation and a therapeutic strategy for a patient with relapsed adult B-lymphoblastic leukemia.

Authors:  Malachi Griffith; Obi L Griffith; Kilannin Krysiak; Zachary L Skidmore; Matthew J Christopher; Jeffery M Klco; Avinash Ramu; Tamara L Lamprecht; Alex H Wagner; Katie M Campbell; Robert Lesurf; Jasreet Hundal; Jin Zhang; Nicholas C Spies; Benjamin J Ainscough; David E Larson; Sharon E Heath; Catrina Fronick; Shelly O'Laughlin; Robert S Fulton; Vincent Magrini; Sean McGrath; Scott M Smith; Christopher A Miller; Christopher A Maher; Jacqueline E Payton; Jason R Walker; James M Eldred; Matthew J Walter; Daniel C Link; Timothy A Graubert; Peter Westervelt; Shashikant Kulkarni; John F DiPersio; Elaine R Mardis; Richard K Wilson; Timothy J Ley
Journal:  Exp Hematol       Date:  2016-05-13       Impact factor: 3.084

Review 9.  Potential of gene expression profiling in the management of childhood acute lymphoblastic leukemia.

Authors:  Deepa Bhojwani; Naomi Moskowitz; Elizabeth A Raetz; William L Carroll
Journal:  Paediatr Drugs       Date:  2007       Impact factor: 3.022

10.  Quantitative comparison of microarray experiments with published leukemia related gene expression signatures.

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Journal:  BMC Bioinformatics       Date:  2009-12-15       Impact factor: 3.169

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