SEARCH:   Advanced

Blood, 1 December 2004, Vol. 104, No. 12, pp. 3423-3424. This Article Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Download to citation manager Rights and Permissions Citing Articles Citing Articles via CrossRef Citing Articles via Google Scholar Google Scholar Articles by Armstrong, S. A. Search for Related Content PubMed Articles by Armstrong, S. A. Related Collections Related Article in Blood Online Social Bookmarking                   What's this?  Previous Article  |  Table of Contents  |  Next Article  NEOPLASIA Comment on Ross et al, page 3679 Leukemia gene expression: MLL rearrangements in AML and ALL Scott A. Armstrong CHILDREN'S HOSPITAL, BOSTON, AND DANA FARBER CANCER INSTITUTE Gene expression profiling of pediatric acute myelogenous leukemias identifies signatures associated with recurrent chromosomal translocations including an MLL-associated signature found in both AML and ALL. Gene expression profiling of cancer cells holds the promise of providing better clinical stratification schemes and the ability to predict response to therapy. Also, a detailed understanding of gene expression may help identify critical pathways that could be therapeutic targets. This is particularly true for hematopoietic malignancies, where a detailed understanding of the importance of recurrent chromosomal translocations can be used to aid interpretation of complex gene expression data sets. Gene expression–based relationship between leukemias with MLL rearrangements and those without. See the complete figure in the article beginning on page 3679.   Studies by Ross and colleagues in this issue of Blood use microarray analysis to define gene expression signatures associated with recurrent chromosomal translocations found in pediatric acute myeloid leukemia (AML). They identify distinct gene expression signatures associated with the most common translocations including those that encode promyelocytic leukemia–retinoic acid receptor (PML-RAR), acute myeloid leukemia 1-821 (AML1-ETO), core-binding factor –smooth muscle myosin heavy chain (CBF-MYH11), and mixed-lineage leukemia (MLL) fusion proteins. When the class discriminating genes are used to predict the presence of specific translocations, the gene expression–based classifier performs with 93% accuracy. Importantly, when AML samples obtained from adults are classified based on gene expression defined in pediatric samples, the classifier performs equally well. The inability to correctly classify a few samples appears to be a result of molecular heterogeneity in AMLs with either CBF-MYH11 or MLL translocations. While the explanation for such heterogeneity remains unknown, it raises interesting questions for further study. A particularly intriguing aspect of the current study is the assessment of gene expression signatures associated with MLL rearrangements in leukemias characterized as T-lineage acute lymphoblastic leukemia (T-ALL), B-lineage ALL (B-ALL), or AML. When Ross et al performed unsupervised clustering of leukemia samples using principle component analysis, MLL-rearranged AMLs and T-ALLs were intermixed with the other AML and T-ALL samples, respectively. MLL-rearranged B-ALL samples, while "closest" to B-ALL, were clustered together and separate from other B-ALL samples (see figure). This provides support for the notion that MLL-rearranged B-ALLs are biologically distinct from other ALLs and provides new data showing that MLL-rearranged T-ALL and AML are biologically more similar to other leukemias of similar lineage. This is in concordance with clinical data where MLL rearrangements are associated with a particularly poor prognosis in B-ALL but not T-ALL or AML.1 Also, this analysis identified a "core" gene expression signature associated with MLL rearrangements despite the lineage classification. Presumably these genes represent important downstream mediators of MLL-induced leukemogenesis. While similar types of analysis have been performed previously,2-5 this is the largest study using well-annotated AML, T-ALL, and B-ALL samples and thus provides important new insight into the biology of these leukemias. Gene expression studies such as this continue to provide important information about the biology of leukemia and suggest that gene expression–based classification schemes might improve upon those currently used. But, gene expression studies performed on human tumors are largely hypothesis-generating experiments and thus much work lies ahead in the testing of these hypotheses. A similarly demanding and equally important task will be demonstration of the ability to prospectively predict outcome using gene expression–based technologies. Despite these caveats, genomic analysis is providing an unprecedented view of the molecular events in leukemia. References Pui CH, Relling MV, Downing JR. Acute lymphoblastic leukemia. N Engl J Med. 2004;350: 1535-1548.[Free Full Text] Armstrong SA, Staunton JE, Silverman LB, et al. MLL translocations specify a distinct gene expression profile that distinguishes a unique leukemia. Nat Genet. 2002;30: 41-47.[CrossRef][Medline] [Order article via Infotrieve] Ferrando AA, Armstrong SA, Neuberg DS, et al. Gene expression signatures in MLL-rearranged T-lineage and B-precursor acute leukemias: dominance of HOX dysregulation. Blood. 2003;102: 262-268.[Abstract/Free Full Text] Valk PJ, Verhaak RG, Beijen MA, et al. Prognostically useful gene-expression profiles in acute myeloid leukemia. N Engl J Med. 2004;350: 1617-1628.[Abstract/Free Full Text] Yeoh EJ, Ross ME, Shurtleff SA, et al. Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling. Cancer Cell. 2002;1: 133-143.[CrossRef][Medline] [Order article via Infotrieve] CiteULike    Connotea    Del.icio.us    Digg    Reddit    Technorati    What's this? Related Article in Blood Online: Gene expression profiling of pediatric acute myelogenous leukemia Mary E. Ross, Rami Mahfouz, Mihaela Onciu, Hsi-Che Liu, Xiaodong Zhou, Guangchun Song, Sheila A. Shurtleff, Stanley Pounds, Cheng Cheng, Jing Ma, Raul C. Ribeiro, Jeffrey E. Rubnitz, Kevin Girtman, W. Kent Williams, Susana C. Raimondi, Der-Cherng Liang, Lee-Yung Shih, Ching-Hon Pui, and James R. Downing Blood 2004 104: 3679-3687. [Abstract] [Full Text] [PDF] This Article Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Download to citation manager Rights and Permissions Citing Articles Citing Articles via CrossRef Citing Articles via Google Scholar Google Scholar Articles by Armstrong, S. A. Search for Related Content PubMed Articles by Armstrong, S. A. Related Collections Related Article in Blood Online Social Bookmarking                   What's this?

	Copyright © 2004 by American Society of Hematology         Online ISSN: 1528-0020