Molecular characterization of a complex chromosomal translocation breakpoint t(10;14) including the HOX11 oncogene locus

Salvati, PD; Pm, Watt; Thomas, WR; Kees, UR

doi:10.1038/sj.leu.2401421

Cited by 11 publications

(7 citation statements)

References 26 publications

(52 reference statements)

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“…The diminution in the incidence of SIL-TAL1 and HOX11L2 with age is in keeping with progressive diminution in the thymic ␣␤ lineage, but it does not explain the late onset of HOX11 T-ALL (Table 2). HOX11 is, at least partly, deregulated by the TCR␣/␦ or TCR␤ locus, 11,12,32,62 whose activity are also likely to diminish with age. An increasing number of "idiopathic" HOX11-expressing T-ALLs are recognized.…”

Section: Discussionmentioning

confidence: 99%

Age-related phenotypic and oncogenic differences in T-cell acute lymphoblastic leukemias may reflect thymic atrophy

Asnafi

Beldjord

Libura

et al. 2004

Blood

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Postnatal thymic involution occurs progressively throughout the first 3 decades of life. It predominantly affects T-cell receptor (TCR) ␣␤-lineage precursors, with a consequent proportional increase in multipotent thymic precursors. We show that T-acute lymphoblastic leukemias (TALLs) demonstrate a similar shift with age from predominantly TCR expressing to an immature (IM0/␦/␥) stage of maturation arrest. Half demonstrate HOX11, HOX11L2, SIL-TAL1, or CALM-AF10 deregulation, with each being associated with a specific, age-independent stage of maturation arrest. HOX11 and SIL-TAL represent ␣␤-lineage oncogenes, whereas HOX11L2 expression identifies an intermediate ␣␤/␥␦-lineage stage of maturation arrest. In keeping with preferential ␣␤-lineage involution, the incidence of SIL-TAL1 and HOX11L2 deregulation decreased with age. In contrast, HOX11 deregulation became more frequent, suggesting longer latency. TAL1/LMO1 deregulation is more frequent in ␣␤-lineage T-ALL, when it is predominantly due to SIL-TAL1 rearrangements in children but to currently unknown mechanisms in adolescents and adults. LMO2 was more frequently coexpressed with LYL1, predominantly in IM0/␦/␥ adult cases, than with TAL1. These age-related changes in phenotype and oncogenic pathways probably reflect progressive changes in the thymic population at risk of malignant transformation. ( IntroductionHuman T lymphocytes are derived from pluripotent hemopoietic progenitors that migrate throughout life from the bone marrow to the thymus, where the majority of T-cell development occurs. Progressive thymic atrophy during the first 2 to 3 decades of life leads to a reduction of thymic mass and, to a lesser extent, function. 1,2 The earliest thymic progenitor corresponds to a minor (Ͻ 1% of thymocytes) sCD3 Ϫ , CD4/CD8 double-negative (DN) population that does not alter with age. [3][4][5][6] In the neonatal murine thymus, the majority of lymphocytes belong to the ␣␤ lineage; successful T-cell receptor ␤ (TCR␤) rearrangement in a DN precursor in the presence of pT␣ allows expression of the pre-TCR in association with CD3, progression to the CD4/8 double-positive (DP) stage, and massive thymocyte expansion, a process known as ␤ selection 7 ; this population diminishes markedly with age, with a consequent increase in the proportion of DN cells.T-acute lymphoblastic leukemias (T-ALLs) correspond to a heterogeneous group of acute leukemias arrested at various stages of lymphoid development. They account for 10% to 15% of pediatric and 25% of adult ALLs, with a relatively constant incidence up to the third decade. [8][9][10] Recognized T-ALL oncogenic pathways include transcriptional deregulation by juxtapositioning to one of the TCR loci, resulting in transcriptional deregulation of genes such as HOX11/TLX1, LMO2, LMO1, LYL1, and TAL1/SCL, each of which is present in less than 10% of cases. [11][12][13][14][15][16][17][18][19][20][21][22] More common genetic defects in T-ALL are submicroscopic deletions of p16/INK4 in 40% to 80% 23,24 or SIL-TAL1 in 10% to ...

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Section: Discussionmentioning

confidence: 99%

Age-related phenotypic and oncogenic differences in T-cell acute lymphoblastic leukemias may reflect thymic atrophy

Asnafi

Beldjord

Libura

et al. 2004

Blood

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“…Beta 1 integrin D U33880 ‫21.5מ‬ 0.0021 1.0000 1.0000 TPO up-regulates adhesion of hematopoetic progenitors to fibronectin through activation of integrin alpha4beta1 and alpha5beta1 (Gotoh et al 1997). Sp4 transcription factor X68561 ‫60.5מ‬ 0.0030 1.0000 1.0000 Sp4 not well characterized but closely related to Sp1 (Suske 1999), TPO activates several Sp1-dependent genes during megakaryopoiesis (Wang et al 1999 (Streit et al 1999), close relative thrombospondin 1 is negative regulator of megakaryopoiesis (Chen et al 1997;Touhami et al 1997 (Marlton et al 1995;Mancini et al 2000), CML/ALL translocations identified in 10q (Kagan et al 1989;Aguiar et al 1997;Salvati et al 1999 (Melnick et al 1999), isochromosomes on 17q common (Fioretos et al 1999) Biglycan J04599 ‫71.4מ‬ 0.2119 1.0000 1.0000 Xq28 Translocation found in AML (Weis et al 1985), common in ALL (Stern 1996 Dataset from Golub et al (1999).…”

Section: Discussionmentioning

confidence: 99%

An Efficient and Robust Statistical Modeling Approach to Discover Differentially Expressed Genes Using Genomic Expression Profiles

Thomas¹,

Olson²,

Tapscott³

et al. 2001

Genome Res.

286

192

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We have developed a statistical regression modeling approach to discover genes that are differentially expressed between two predefined sample groups in DNA microarray experiments. Our model is based on well-defined assumptions, uses rigorous and well-characterized statistical measures, and accounts for the heterogeneity and genomic complexity of the data. In contrast to cluster analysis, which attempts to define groups of genes and/or samples that share common overall expression profiles, our modeling approach uses known sample group membership to focus on expression profiles of individual genes in a sensitive and robust manner. Further, this approach can be used to test statistical hypotheses about gene expression. To demonstrate this methodology, we compared the expression profiles of 11 acute myeloid leukemia (AML) and 27 acute lymphoblastic leukemia (ALL) samples from a previous study ) and found 141 genes differentially expressed between AML and ALL with a 1% significance at the genomic level. Using this modeling approach to compare different sample groups within the AML samples, we identified a group of genes whose expression profiles correlated with that of thrombopoietin and found that genes whose expression associated with AML treatment outcome lie in recurrent chromosomal locations. Our results are compared with those obtained using t-tests or Wilcoxon rank sum statistics.

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“…HOX11 was first identified from the nonrandom chromosomal translocation t(10;14)(q24;q11) or variant t(7;10)(q35;q24), which occurs in up to 7% of T-cell acute lymphoblastic leukemia (T-ALL) cases (Kees et al, 1989;Dube et al, 1991;Hatano et al, 1991;Kennedy et al, 1991;Lu et al, 1991;Schneider et al, 2000). As a result of this translocation, HOX11 is placed under the transcriptional control of the TCR6 or TCRB regulatory elements (Lu et al, 1990;Kagan et al, 1994;Salvati et al, 1999). In the majority of cases, the protein product remains unaltered after translocation; hence, dysregulation of HOX11 is believed to be the key leukemogenic event (Kagan et al, 1989;Lu et al, 1990).…”

Section: Introductionmentioning

confidence: 99%

A microarray model system identifies potential new target genes of the proto‐oncogene HOX11

Hoffmann

Dixon

Greene

et al. 2004

Genes Chromosomes & Cancer

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HOX11 is a homeobox gene originally identified at a chromosomal breakpoint in T-cell acute lymphoblastic leukemia (T-ALL). It is one of the most frequently deregulated genes in T-ALL, although the precise role of HOX11 in leukemogenesis as well as in normal development remains obscure. To gain more insight into the functional role of HOX11, we utilized a microarray model system to characterize the gene expression network that it directs. Using one of our T-ALL cell lines that had been stably transfected to express HOX11 and high-density oligonucleotide HG-U95A arrays, we identified a large number of differentially expressed genes in response to the enforced expression of HOX11. We focused on examining genes found to be up-regulated according to the microarray analysis and selected three putative target genes, NFKB2, SMARCD3, and NR4A3, for further investigation. We could not only confirm the up-regulation of NR4A3 by an independent method in all clones expressing HOX11, but luciferase reporter assays demonstrated that the effect that HOX11 exerted on the proximal promoter of NR4A3 was dependent on the presence of an intact homeodomain, providing support for the idea that HOX11 manifests its regulatory function via its action as a transcription factor.

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Molecular characterization of a complex chromosomal translocation breakpoint t(10;14) including the HOX11 oncogene locus

Cited by 11 publications

References 26 publications

Age-related phenotypic and oncogenic differences in T-cell acute lymphoblastic leukemias may reflect thymic atrophy

Age-related phenotypic and oncogenic differences in T-cell acute lymphoblastic leukemias may reflect thymic atrophy

An Efficient and Robust Statistical Modeling Approach to Discover Differentially Expressed Genes Using Genomic Expression Profiles

A microarray model system identifies potential new target genes of the proto‐oncogene HOX11

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