Disclosure of Candidate Genes in Acute Myeloid Leukemia With Complex Karyotypes Using Microarray-Based Molecular Characterization
To identify novel genomic regions of interest in acute myeloid leukemia (AML) with complex karyotypes, we applied comparative genomic hybridization to microarrays (array-CGH), allowing high-resolution genome-wide screening of genomic imbalances.
Sixty AML cases with complex karyotypes were analyzed using array-CGH; parallel analysis of gene expression was performed in a subset of cases.
Genomic losses were found more frequently than gains. The most frequent losses affected 5q (77%), 17p (55%), and 7q (45%), and the most frequent genomic gains 11q (40%) and 8q (38%). Critical segments could be delineated to genomic fragments of only 0.8 to a few megabase-pairs of DNA. In lost/gained regions, gene expression profiling detected a gene dosage effect with significant lower/higher average gene expression levels across the genes located in the respective regions. Furthermore, high-level DNA amplifications were identified in several regions: 11q23.3-q24.1 (n = 7), 21q22 (n = 6), 11q23.3 (n = 5), 13q12 (n = 3), 8q24 (n = 3), 9p24 (n = 2), 12p13 (n = 2), and 20q11 (n = 2). Parallel analysis of gene expression in critical amplicons displayed overexpressed candidate genes (eg, C8FW and MYC in 8q24).
In conclusion, a large spectrum of genomic imbalances, including novel recurring changes in AML with complex karyotypes, was identified using array-CGH. In addition, the combined analysis of array-CGH data with gene expression profiles allowed the detection of candidate genes involved in the pathogenesis of AML.
Nonrandom, clonal chromosome aberrations are detected in approximately 50% of adult patients with acute myeloid leukemia (AML), and it is well established that karyotype provides important prognostic information that influences therapy and outcome of this disease.1-3 The cloning and molecular characterization of balanced translocations and inversions, such as t(8;21)(q22;q22), inv(16)(p13q22), and t(15;17)(q22;q11∼21), has resulted in the identification of cellular pathways that are causally implicated in the pathogenesis of distinct subtypes of AML.
In contrast, little is known about the molecular pathogenesis of AML with complex karyotypes, commonly defined as the presence of three or more chromosome abnormalities in the absence of t(8;21), inv(16)/t(16;16), t(15;17), and t(11q23). Complex karyotypes are found in approximately 10% to 15% of adult AML cases.4,5 They are often associated with prior myelodysplastic phase or prior exposure to toxic agents4,6 and almost invariably with a dismal outcome.1,2,4,5,7 Cytogenetic analysis has been hampered by the difficulty of dissecting the complex changes by conventional chromosome banding techniques alone. In particular, marker chromosomes, or the cytogenetic hallmarks of DNA amplifications, double minutes and homogeneously staining regions, cannot always be precisely localized to specific chromosomal bands. Previous cytogenetic and molecular cytogenetic studies have shown that genomic losses or gains are much more frequent than balanced rearrangements in this subset of AML.8-10 Among the imbalances most frequently found are losses affecting 5/5q (−5/5q–), −7/7q–, −17/17p–, −18/18q–, 12p–, and −16/16q–; and gains affecting 8/8q (+8/+8q), +21/+21q, +11q, and +22q.
Array-based comparative genomic hybridization (array-CGH) represents a novel technique that allows high-throughput, genome-wide screening of genomic imbalances with a 20- to 100-fold higher spatial resolution than conventional CGH.11-13 In hematologic research, array-CGH has so far mainly been applied to the analysis of lymphoproliferative disorders.14-16 The potential of this technology for the detection of genomic amplifications was also demonstrated in a recent study of AML cases with complex karyotypes that were analyzed using a chromosome 21q–specific microarray.17 In addition, parallel analysis of gene expression using microarray technology has also been shown to provide useful information regarding the delineation of candidate genes in genomic regions characterized by copy number alterations (CNAs).17-19
To identify novel candidate regions and disease-related genes, we studied 60 AML cases with complex karyotypes using genome-wide high resolution array-CGH in combination with global gene-expression profiling in a subset of cases.
Frozen cells (−70°C) from peripheral blood (PB; n = 20) or bone marrow (n = 40) from 60 adult patients with newly diagnosed AML and complex karyotypes (de novo AML, n = 35; secondary AML after myelodysplastic syndrome [MDS], n = 16; therapy-induced AML, n = 4; unknown, n = 5) were analyzed. Complex karyotypes were defined as the presence of at least three chromosome abnormalities in the absence of t(8;21), inv(16)/t(16;16), t(15;17), and t(11q23). The diagnosis of AML was made according to the French-American-British Cooperative Group criteria.20 The median age of the patients was 62 years (range, 22 to 81 years), the median blast count in PB 40% (range, 10% to 89%), and in bone marrow 69% (range, 30% to 91%). All patients had given informed consent for cryopreservation and molecular analyses.
All samples were studied by chromosome banding analysis using standard techniques, and chromosomal abnormalities were described according to the International System for Human Cytogenetic Nomenclature.21
Validation of array-CGH was performed by fluorescence in situ hybridization (FISH). The corresponding bacterial artificial (BAC) or P1-derived artificial chromosome (PAC) clones were hybridized to metaphase and interphase cells of healthy volunteers to verify localization and hybridization specificity. Using the validated clones patients' metaphase and interphase cells were then hybridized as previously described.22
We designed a microarray consisting of 2,799 different BAC or PAC clones which were selected according to the NCBI database information (www.ncbi.nlm.nih.gov/mapview) released in March 2003. For detailed description of array design, hybridization conditions, image analysis, and identification of CNAs see the Appendix (online only). In brief, cutoff levels were determined for each individual experiment. After computing the ratios from dye-swap hybridization and subsequent normalization, an individual set of balanced clones for each experiment was used to calculate the mean and standard deviation. The cutoff levels were defined as mean ± 3× the standard deviation. Frequently affected regions recently detected as copy number polymorphisms (5q11, 7q22, 7q35, 14q32, and 15q11) were excluded from data analysis.23,24 For further refinement of genomic aberrations array-CGH using the previously described 6.0-k microarray was performed as recently published.25
On the basis of the availability of material (blast count > 50% before enrichment of malignant cells by Ficoll gradient density centrifugation and good RNA quality), for a subset of 24 cases, global gene expression profiling (GEP) analyses were performed as previously described.26 Seven of these cases have already been published,26 whereas 17 cases were newly analyzed. Following normalization of fluorescence ratios by mean-centering genes for each array and then for each gene across all arrays26 map positions for arrayed cDNA clones were assigned using the NCBI May 2005 genome assembly (accessed through the UCSC genome browser). In this way, approximately 35,000 arrayed clones representing 18,000 unique genes could be assigned map positions. The complete gene expression microarray data set is available at the Stanford Microarray Database (http://smd.stanford.edu).27
For hierarchical clustering, we applied average linkage hierarchical clustering and visualized results using TreeView.28 For two-class supervised analyses, we used the SAM (significance analysis of microarrays) method29 which utilizes a modified t-test statistic, with sample-label permutations to evaluate statistical significance.
Genomic imbalances were detected in all 60 cases. Losses were more frequent than gains (Fig 1). The most frequent losses affected 5q (77%), 17p (55%), 7q, (45%); followed by losses of 16q (32%), 18q (30%), 17q (22%), 3p and 12q (20% each), 20q and 12p (18% each), 18p (15%), and 13q and 11q (12% each). The most frequent genomic gains affected 11q (40%) and 8q (38%); followed by gains of 21q and 1p (25% each), 9p (18%), 22q (17%), 13q (15%), and 6p and 19p (12% each).
The significant genomic losses and gains are summarized in Table 1, and the 41 DNA amplifications are summarized in Table 2. Some important findings are described in detail according to their frequency:
Thirty-seven cases (62%) exhibited losses of chromosome 17. Two CDRs were identified: one in 17p13 between 7.3 Mb and 8.1 Mb containing the TP53 gene (33 cases); and a second in 17p11-17q11 between 23.1 Mb and 29.5 Mb containing the NF1 gene (18 cases). Seventeen of the latter cases had concomitant loss of the TP53 region; in nine of these 17 cases, the losses were noncontiguous; in one case, there was a small loss on 17q11 encompassing NF1 without loss of TP53.
Eleven cases (18%) had 20q losses encompassing the known approximately 2.6-Mb CDR in 20q12-q13.1.35
Genomic gains and amplifications of 11q were found in 24 cases (40%). Three commonly gained regions were identified: the first region was located between 59.1 Mb and 79.6 Mb in 11q12-q14 (15 cases). The second region mapped to 11q23.3 (21 cases), extended from 116.3 Mb to 119.6 Mb containing the MLL and DDX6 genes; five of these 21 cases showed high-level DNA amplifications within this region. The third region between 127.1 Mb and 129.3 Mb on 11q23.3.-q24.1 (20 cases), including the ETS1 and FLI1 genes, was highlighted by seven cases exhibiting high-level DNA amplifications. These findings were confirmed by FISH using corresponding clones.
Chromosome 8 gains were detected in 23 cases (38%). Three cases exhibited an approximately 10.2-Mb-sized amplified segment between 122.9 Mb and 133.1 Mb on 8q24.12-q24.13 encompassing the C8FW and MYC genes (Fig 2).
CNAs are characteristic for malignancies36 and might therefore lead to altered gene expression in terms of gene dosage effects. In consistency with this hypothesis, we, for example, discovered a gene dosage effect in cases with 5q–, 17p–, and 7q–detecting significant lower average gene expression levels across the genes located in the respective regions as compared to unaltered cases (Table 3). A similar effect was demonstrated in cases with trisomy 11q and 8q displaying significant higher average gene expression levels across the gained regions. These observations are in concordance with previous microarray findings in AML.37
In addition to the reported gene dosage effects, supervised analyses using the SAM method29 did not reveal significant gene expression signatures correlating with loss of 5q, 17p, and 7q, or gain of 11q and 8q, respectively (data not shown).
To delineate potential candidate genes of pathogenetic relevance, we correlated our high resolution array-CGH findings of amplified regions with our gene expression data. Thereby, we were able to disclose highly expressed genes in critical regions of amplicons, narrowing down the number of relevant candidates within these regions. For example, in cases displaying amplicons in 8q24, we found not only high expression levels of the well-known oncogene MYC, but also high expression of NSE2, FLJ32440, and C8FW, also known as TRIB1 (Fig 2). In 9p24 amplified cases, we identified highly expressed JAK2, in 13q14 FOXO1A, and in 13q12 FLT3, CDX2, and PAN3 (Fig 3).
Array-CGH allows comprehensive genome-wide screening of genomic imbalances at high resolution.11-13 There are only few limitations kept in mind interpreting the data: (i) array-CGH does not allow detecting balanced translocations, inversions, or insertions; identified in AMLs with complex karyotypes, albeit with much lower frequency than unbalanced rearrangements8-10; (ii) the assay used is unable to detect imbalances of sex chromosomes reported in this AML subgroup8-10; and (iii) imbalances present in small subclones will not be identified.
With the platforms used in this study, the resolutions were on average 2 Mb down to 0.1 Mb for the 2.8-k platform and 1 Mb down to 0.1 Mb for the 6.0-k platform, respectively. Using these platforms in 60 AMLs with complex karyotypes, we were able to identify novel recurring imbalances that likely pinpoint to regions harboring genes contributing to leukemogenesis.
Genomic losses were more frequent than gains. The most frequent aberrations were losses affecting 5q, 17p, and 7q, known recurring abnormalities in myeloid leukemias, with significant lower average gene expression levels across the genes located in the respective regions as compared to unaltered cases. Due to the heterogeneity of our sample set, known commonly deleted regions on 5q and 7q associated with MDS and AML could not be further refined.30-34
Genomic losses affecting 17p including the TP53 locus were found in 55% of the cases. Thus, the frequency was higher than reported in studies using conventional cytogenetic techniques, and comparable to studies using FISH with a locus-specific probe.8-10,38 Mutations and/or deletions of TP53 have been associated with genetic instability and complex genetic changes.39,40 Thus, the frequent loss of TP53 in our cases, likely leading to dysfunction of the TP53 protein, represents one possible pathway for genetic instability in AML with complex karyotypes.
Further recurring genomic losses were mapped to 18q, 16q, and 17q (35% each). Frequencies of losses of 18q and 16q resulting from deletions or unbalanced structural aberrations were higher than previously reported.8-10,41,42 More importantly, we were able to delineate CDRs. On the basis of two cases, an approximately 2.5-Mb-sized CDR located in 18q21 was delineated including the transcription factor 4 (TCF4) gene. TCF4, which has not yet been associated with leukemogenesis, encodes a transcription factor with homology to other transcription factors, such as TEL and TAL1, that are known to be involved in leukemogenesis. On 16q, an approximately 8.5-Mb-sized CDR encompassing, for example, CBFB and TRADD could be delineated. The smallest lost region in 17q11 was approximately 6.4 Mb in size and contained the NF1 gene. NF1 negatively regulates RAS signaling, and loss of NF1 can lead to a progressive myeloproliferative disorder, but for inducing AML, additional events are required.43,44 Therefore, loss of NF1 might be a cooperating genetic event in leukemogenesis in AML with complex karyotypes.
An enormous spectrum of other recurring losses was identified in a substantial proportion of cases (Fig 1). In part, these aberrations included known recurring losses (eg, 20q–, 12p–, 11q–), in part novel regions of interest. The most frequent genomic gains affected 11q, 8q, 21q, 1p, and 9p. Thereby, cases with trisomy 11q and 8q displayed significant higher average gene expression levels across the gained regions. On the basis of overlapping 11q gains and amplifications, three critical segments were delineated mapping to 11q12-q13, 11q23.3, and 11q23.3-q24.1. Furthermore, our data provided evidence for at least two distinct amplicon clusters in 11q23-q24: one containing MLL and DDX6 (approximately 3.3 Mb in 11q23.3), and another encompassing ETS1 and FLI1 (approximately 2.2 Mb in 11q23.3-q24.1). DDX6, ETS1, FLI1, and most commonly MLL have previously been recognized as targets of 11q23 amplifications.45,46 MLL amplifications have been associated with karyotype complexity, extremely poor survival, and mutations in TP53.45,46 Similarily, in our series, four of five cases with MLL amplifications exhibited TP53 deletion; however, given the high frequency of TP53 loss in our series, this is likely a more general association with karyotype complexity and not restricted to MLL amplifications. Recently, coamplified sequences on 11q13.5 and 11q23-q24 in MLL amplified AML/MDS cases have been described.47 Except for one single case, this was not observed in our study.
The 11q23.3-q24.1 amplicons identified in our study included ETS1 and FLI1, members of the ETS gene family. The ETS gene family includes numerous genes playing important roles in regulating hematopoiesis, proliferation, differentiation, and apoptosis.48-50 Interestingly, six cases in our study without 11q23.3-q24.1 gains exhibited high-level DNA amplifications of ERG and ETS2, two other members of the ETS gene family localized in 21q22. Thus, 13 of the 60 AML cases exhibited high-level DNA amplification of ETS gene family members suggesting a pathogenetic role in AML with complex karyotypes. In accordance with our findings, in a recent study, the ERG and ETS2 loci were also frequently amplified in complex karyotype AML with abnormal chromosome 21.17
In addition, three cases exhibited an amplified region in 8q24 containing among others the MYC gene, a known amplification target in AML.51,52 Surprisingly, further refinement of the 8q24 amplicon using the 6.0-k platform and correlation with GEP revealed overexpression of MYC, NSE2, and FLJ32440. However, the highest expression levels were identified for C8FW, also known as TRIB1, encoding a phosphoprotein regulated by mitogenic pathways. Little is known about C8FW, but it binds to 12-lipoxygenase, which has been shown to be overexpressed in human cancer tissues.53 Moreover, C8FW is homologous to SKIP3, a protein kinase overexpressed in several tumor types assuming a role in tumor progression.54 In accordance with a recently published study, these findings suggest that C8FW might be one candidate target gene of 8q24 amplifications.55
Furthermore, a large number of other high-level DNA amplifications were identified in our study, suggesting a more general role of proto-oncogene activation in AML pathogenesis (Table 2). These included a recurring amplicon mapping to 13q12 (Fig 3) encompassing, for example, FLT3, FLT1, PAN3, and the caudal-type homeobox transcription factor 2 gene (CDX2). ETV6/CDX2 fusion genes have been reported in three AML cases with t(12;13)(p13;q12).56 In a murine model of t(12;13)(p13;q12), it has been recently shown that the ectopic overexpression of Cdx2 was the key transforming event.57 Cdx genes have has a key role as upstream regulator of several Hox genes,58,59 and upregulation of HOX genes has been associated with AML pathogenesis.26,60 Interestingly, parallel analysis displayed the highest count ratios in array-CGH and GEP for FLT3 and PAN3. PAN3, encodes for a regulatory subunit of the polyadenylate-binding protein dependent poly(A) nuclease complex being involved in mRNA deadenylation, a mechanism greatly affecting mRNA stability. Furthermore, a recent study in yeast demonstrated a role in post-transcriptional regulation of DNA repair genes.61,62 Moreover, in seven cases, GEP disclosed overexpression of the forkhead box 01A gene (FOXO1A, also known as FKHR) as involved in cell cycle arrest and the regulation of apoptosis.63 As recently shown, a synthetic fusion of FOXO1A and MLL transform hematopoietic progenitor cells in vitro.64
By using high-resolution genome-wide screening tools such as array-CGH and GEP, we are beginning to unravel the enormous genetic diversity of AML cases with complex karyotypes. Further correlation of high-resolution genomic profiling with global gene expression studies may help to better characterize this disease, and should be followed by subsequent functional analyses to identify disease relevant genes in the critical regions.
Clone selection, preparation and spotting. For the DNA microarray, only clones with corresponding Mb localization and FISH mapping information were selected. The clones were ordered from the libraries RPCIB753 or RPCIP704 of the German Resource Center for Genome Research (RZPD, Berlin, Germany). A set of 1,500 of the 2,799 clones covers the whole human genome in a physical distance of approximately 2 Mb (part of the golden Path clone set). The remaining 1,299 clones either contiguously span genomic regions known to be frequently involved in hematologic malignancies (eg, 1p, 2p, 3q, 7q, 9p, 11q, 12q, 13q, 17p, 18q; n = 600) or contain oncogenes or tumor suppressor genes known to be of pathogenetic relevance in hematologic malignancies (n = 699). In consideration of continuous updating of database information (eg, physical mapping, sequencing, and marker information), critical regions discussed in this study were carefully reviewed. Positions are referred to the first base of each chromosome according to the NCBI database information. Nevertheless, particular genomic information may still vary as a result of the latest database releases.
Preparation of the DNA was performed as previously described (Fiegler H, Carr P, Douglas EJ, et al. Genes Chromosomes Cancer 36:361-374, 2003. Erratum in Genes Chromosomes Cancer 37:223, 2003). The DNA isolated from cultured BAC/PAC clones by alkaline lysis was amplified using three different DOP primers (DOP1, DOP2, DOP3). Because of the high specificity for amplification of human DNA and low specificity for E coli DNA, these primers allow the specific amplification of the human inserts. The obtained polymerase chain reaction (PCR) products representing more than 90% of the initial human DNA insert were pooled and thereafter reamplified using a consensus DOP 4 primer.
Three minor modifications were performed: (i) primer concentrations in all PCR reactions were 10 mM, (ii) the consensus DOP4 primers were not amine modified, and (iii) after adding of 2 μl of 20 × saline sodium citrate to 10 μl of the PCR product, the reamplified PCR products were directly used for spotting.
The PCR products were spotted in quadruplicate onto Corning CMT-Gaps II glass slides (Corning, Corning, NY) using the Omnigrid microarrayer (Gene Machines, San Carlos, CA). The slides were then baked at 80°C for 10 minutes and exposed to ultraviolet light for cross linking of DNA fragments (254 nm/2,400 μJ). The arrays were stored at room temperature.
Array-CGH. Genomic DNA of the tumor specimens was isolated using standard protocols. Pooled PB DNA from five female or five male healthy volunteers was used as common reference in each experiment. In total, 300 ng of tumor DNA and reference DNA were differentially labeled with Cy3- and Cy5-conjugated dCTP (2′-deoxycytidine 5′-triphosphate) by random primed labeling. Microcon membrane column centrifugation was used to remove unincorporated nucleotides. To account for different incorporation of fluorochrome-labeled nucleotides, each experiment was performed in duplicate labeling tumor DNA either with Cy3 or Cy5 and reference DNA with Cy5 or Cy3, respectively (dye-swap). Because labeled male tumor DNA was cohybridized with differentially labeled female DNA as an internal control, alterations affecting the sex chromosomes were not detectable. Labeled DNA, 75 μg of human Cot-1 DNA, and 75 μg of E coli DNA were precipitated and resolved in 130 μl of prewarmed Ultrahyb buffer (Ambion, Austin, TX) at 37°C for 30 minutes. After consecutive denaturation at 75°C for 10 minutes and preannealing at 37°C for 60 minutes, hybridization was performed for 36 hours at 37°C using a GeneTac hybridization chamber (Genomic Solutions, Cambridgeshire, United Kingdom). Slides were washed three times in 2x saline sodium citrate, 50% formamide and 0.1% Tween20, pH 7.0 at 45°C, followed by washing for 2 minutes in 1× phosphate buffered saline, 0.05% Tween20, pH 7.0 at 25°C. Afterwards, slides were dried by spinning for 5 minutes at 2,500 rpm (Kohlhammer H, Schwaenen C, Wessendorf S, et al. Blood 795-801, 2004. Schwaenen C, Nessling M, Wessendorf S, et al. Proc Natl Acad Sci U S A 101:1039-1044, 2004).
Image analysis and identification of CNAs. Microarrays were imaged using a dual laser scanner and the GenePix Pro 6.0 imaging software (GenePix 4000B, Axon Instruments, Union City, CA). Raw data were analyzed as previously described (Schwaenen C, Nessling M, Wessendorf S, et al. Proc Natl Acad Sci U S A 101:1039-1044, 2004). Fluorescence ratios were normalized using the median of the fluorescence ratios computed as log2 values from the 1,503 DNA control fragments spanning the whole genome. The cutoff level was determined for each individual experiment. After computing the ratios from the dye-swap hybridization and subsequent normalization, an individual set of balanced clones for each experiment was used to calculate the mean and standard deviations. The cutoff levels were defined as mean plus/minus three times the standard deviation. Frequently affected regions recently detected as copy number polymorphisms (5q11, 7q22, 7q35, 14q32, and 15q11) were excluded from data analysis (Sebat J, Lakshmi B, Troge J, et al. Science 305:525-528, 2004. Iafrate AJ, Feuk L, Rivera MN, et al. Nat Genet 36:949-951, 2004).
The authors indicated no potential conflicts of interest.
Conception and design: Frank G. Rücker, Lars Bullinger, Konstanze Döhner, Hartmut Döhner
Administrative support: Peter Lichter, Konstanze Döhner, Hartmut Döhner
Provision of study materials or patients: Carsten Schwaenen, Swen Wessendorf, Martin Bentz, Richard F. Schlenk, Bernhard Radlwimmer, Peter Lichter
Collection and assembly of data: Frank G. Rücker, Lars Bullinger, Daniel B. Lipka, Simone Miller
Data analysis and interpretation: Frank G. Rücker, Lars Bullinger, Swen Wessendorf, Stefan Fröhling, Claudia Scholl, Bernhard Radlwimmer, Hans A. Kestler, Jonathan R. Pollack, Hartmut Döhner
Manuscript writing: Frank G. Rücker, Lars Bullinger, Carsten Schwaenen, Stefan Fröhling, Jonathan R. Pollack, Peter Lichter, Konstanze Döhner, Hartmut Döhner
Final approval of manuscript: Frank G. Rücker, Hartmut Döhner
|Loss or Gain||Chromosome||No. of Cases||Region (approximate Mb)||Consensus Region||Candidate Genes|
|Approximate Mb||No. of Cases|
|Loss||12p13||11||0.1-32.7||12.6-15.6||11||CDKN1, CDKN1B, ETV6*|
|Gain||22q||10||20.2-48.8||20.2-38.3||3||BCR, CHEK2, NF2|
*Validated by fluorescence in situ hybridization analyses.
|Chromosomal Band||Amplification size (approximate Mb)||No. of Cases||Candidate Genes|
|8q24.12-q24.13||122.9-133.1||3||FLJ32440, C8FW, MYC*|
|9p21.3-9p21.1||17.4-24.0||1||IFN, MLLT3, CDKN2A, CDKN2B|
|11q13||72.2-81.3||1||PDE2A, SERPINH2, WNT11, GARP, RAB30|
|12p13||0.1-5.9||1||RBBP2, FGF6, CCND2|
|13q11-q12||19.9-31.7||3||FLT3, PAN3, CDX2*|
*Validated by fluorescence in situ hybridization analyses.
|Copy Number Alteration||Unaltered Cases (mean)||Altered Cases (mean)||P|
published online ahead of print at www.jco.org on July 24, 2006.
Supported by Bundesministerium für Bildung und Forschung (BMBF), Grant No. 01GS0439 NGFN2.
Presented in part at Gemeinsame Jahrestagung der Deutschen, Österreichischen und Schweizerischen Gesellschaft für Hämatologie und Onkologie, Innsbruck, Austria, October 2-6, 2002; Gemeinsame Jahrestagung der Deutschen, Österreichischen und Schweizerischen Gesellschaft für Hämatologie und Onkologie, Hannover, Germany, October 1-5, 2005; 10th Congress of the European Hematology Associate, Stockholm, Sweden, June 2-5, 2005; and the 26th Annual Meeting of the American Society of Hematology, San Diego, CA, December 4-7, 2004.
F.G.R. and L.B. contributed equally to this work.
Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.
We thank the members of the AML Study Group (AMLSG) for providing leukemia specimens. We gratefully acknowledge Stefan Hein, Zoraja Keresman, and Sandra Ruf for technical assistance.
|1.||Byrd JC, Mrozek K, Dodge RK, et al: Cancer and Leukemia Group B (CALGB 8461). Pretreatment cytogenetic abnormalities are predictive of induction success, cumulative incidence of relapse, and overall survival in adult patients with de novo acute myeloid leukemia: Results from Cancer and Leukemia Group B (CALGB 8461). Blood 100:: 4325,2002-4336, Crossref, Medline, Google Scholar|
|2.||Grimwade D, Walker H, Oliver F, et al: The importance of diagnostic cytogenetics on outcome in AML: Analysis of 1,612 patients entered into the MRC AML 10 trial—The Medical Research Council Adult and Children's Leukaemia Working Parties. Blood 92:: 2322,1998-2333, Crossref, Medline, Google Scholar|
|3.||Mrozek K, Heinonen K, Bloomfield CD: Clinical importance of cytogenetics in acute myeloid leukaemia. Best Pract Res Clin Haematol 14:: 19,2001-47, Crossref, Medline, Google Scholar|
|4.||Grimwade D, Walker H, Harrison G, et al: Medical Research Council Adult Leukemia Working Party: The predictive value of hierarchical cytogenetic classification in older adults with acute myeloid leukemia (AML)—Analysis of 1065 patients entered into the United Kingdom Medical Research Council AML11 trial. Blood 98:: 1312,2001-1320, Crossref, Medline, Google Scholar|
|5.||Schoch C, Haferlach T, Haase D, et al: Patients with de novo acute myeloid leukaemia and complex karyotype aberrations show a poor prognosis despite intensive treatment: A study of 90 patients. Br J Haematol 112:: 118,2001-126, Crossref, Medline, Google Scholar|
|6.||Mauritzson N, Albin M, Rylander L, et al: Pooled analysis of clinical and cytogenetic features in treatment-related and de novo adult acute myeloid leukemia and myelodysplastic syndromes based on a consecutive series of 761 patients analyzed 1976-1993 and on 5098 unselected cases reported in the literature 1974-2001. Leukemia 16:: 2366,2002-2378, Crossref, Medline, Google Scholar|
|7.||Arthur DC, Berger R, Golomb HM, et al: The clinical significance of karyotype in acute myelogenous leukemia. Cancer Genet Cytogenet 40:: 203,1989-216, Crossref, Medline, Google Scholar|
|8.||Schoch C, Haferlach T, Bursch S, et al: Loss of genetic material is more common than gain in acute myeloid leukemia with complex aberrant karyotype: A detailed analysis of 125 cases using conventional chromosome analysis and fluorescence in situ hybridization including 24-color FISH. Genes Chromosomes Cancer 35:: 20,2002-29, Crossref, Medline, Google Scholar|
|9.||Mrozek K, Heinonen K, Theil KS, et al: Spectral karyotyping in patients with acute myeloid leukemia and a complex karyotype shows hidden aberrations, including recurrent overrepresentation of 21q, 11q, and 22q. Genes Chromosomes Cancer 34:: 137,2002-153, Crossref, Medline, Google Scholar|
|10.||Van Limbergen H, Poppe B, Michaux L, et al: Identification of cytogenetic subclasses and recurring chromosomal aberrations in AML and MDS with complex karyotypes using M-FISH. Genes Chromosomes Cancer 33:: 60,2002-72, Crossref, Medline, Google Scholar|
|11.||Solinas-Toldo S, Lampel S, Stilgenbauer S, et al: Matrix-based comparative genomic hybridization: Biochips to screen for genomic imbalances. Genes Chromosomes Cancer 20:: 399,1997-407, Crossref, Medline, Google Scholar|
|12.||Pinkel D, Segraves R, Sudar D, et al: High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays. Nat Genet 20:: 207,1998-211, Crossref, Medline, Google Scholar|
|13.||Pollack JR, Perou CM, Alizadeh AA, et al: Genome-wide analysis of DNA copy-number changes using cDNA microarrays. Nat Genet 23:: 41,1999-46, Medline, Google Scholar|
|14.||Martinez-Climent JA, Alizadeh AA, Segraves R, et al: Transformation of follicular lymphoma to diffuse large cell lymphoma is associated with a heterogeneous set of DNA copy number and gene expression alterations. Blood 101:: 3109,2003-3117, Crossref, Medline, Google Scholar|
|15.||Kohlhammer H, Schwaenen C, Wessendorf S, et al: Genomic DNA-chip hybridization in t(11;14)-positive mantle cell lymphomas shows a high frequency of aberrations and allows a refined characterization of consensus regions. Blood 104:: 795,2004-801, Crossref, Medline, Google Scholar|
|16.||Schwaenen C, Nessling M, Wessendorf S, et al: Automated array-based genomic profiling in chronic lymphocytic leukemia: Development of a clinical tool and discovery of recurrent genomic alterations. Proc Natl Acad Sci U S A 101:: 1039,2004-1044, Crossref, Medline, Google Scholar|
|17.||Baldus CD, Liyanarachchi S, Mrozek K, et al: Acute myeloid leukemia with complex karyotypes and abnormal chromosome 21: Amplification discloses overexpression of APP, ETS2, and ERG genes. Proc Natl Acad Sci U S A 101:: 3915,2004-3920, Crossref, Medline, Google Scholar|
|18.||Pollack JR, Sorlie T, Perou CM, et al: Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors. Proc Natl Acad Sci U S A 99:: 12963,2002-12968, Crossref, Medline, Google Scholar|
|19.||Pollack JR: Parallel analysis of gene copy number and expression using cDNA microarrays. Methods Mol Biol 224:: 89,2003-97, Medline, Google Scholar|
|20.||Bennett JM, Catovsky D, Daniel MT, et al: Proposed revised criteria for the classification of acute myeloid leukemia: A report of the French-American-British Cooperative Group. Ann Intern Med 103:: 620,1985-625, Crossref, Medline, Google Scholar|
|21.||Mitelman F: ISCN (1995): An International System for Human Cytogenetic Nomenclature . Basel, Switzerland, S. Karger, 1995 Google Scholar|
|22.||Frohling S, Skelin S, Liebisch C, et al: Comparison of cytogenetic and molecular cytogenetic detection of chromosome abnormalities in 240 consecutive adult patients with acute myeloid leukemia. J Clin Oncol 20:: 2480,2002-2485, Link, Google Scholar|
|23.||Sebat J, Lakshmi B, Troge J, et al: Large-scale copy number polymorphism in the human genome. Science 305:: 525,2004-528, Crossref, Medline, Google Scholar|
|24.||Iafrate AJ, Feuk L, Rivera MN, et al: Detection of large-scale variation in the human genome. Nat Genet 36:: 949,2004-951, Crossref, Medline, Google Scholar|
|25.||Zielinski B, Gratias S, Toedt G, et al: Detection of chromosomal imbalances in retinoblastoma by matrix-based comparative genomic hybridization. Genes Chromosomes Cancer 43:: 294,2005-301, Crossref, Medline, Google Scholar|
|26.||Bullinger L, Dohner K, Bair E, et al: Use of gene-expression profiling to identify prognostic subclasses in adult acute myeloid leukemia. N Engl J Med 350:: 1605,2004-1616, Crossref, Medline, Google Scholar|
|27.||Ball CA, Awad IA, Demeter J, et al: The Stanford Microarray Database accommodates additional microarray platforms and data formats. Nucleic Acids Res 33: (Database issue): D580,2005-582, Medline, Google Scholar|
|28.||Eisen MB, Spellman PT, Brown PO, et al: Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci U S A 95:: 14863,1998-14868, Crossref, Medline, Google Scholar|
|29.||Tusher VG, Tibshirani R, Chu G: Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci U S A 98:: 5116,2001-5121, Crossref, Medline, Google Scholar|
|30.||Zhao N, Stoffel A, Wang PW, et al: Molecular delineation of the smallest commonly deleted region of chromosome 5 in malignant myeloid diseases to 1-1.5 Mb and preparation of a PAC-based physical map. Proc Natl Acad Sci U S A 94:: 6948,1997-6953, Crossref, Medline, Google Scholar|
|31.||Boultwood J, Fidler C, Strickson AJ, et al: Narrowing and genomic annotation of the commonly deleted region of the 5q- syndrome. Blood 99:: 4638,2002-4641, Crossref, Medline, Google Scholar|
|32.||Le Beau MM, Espinosa R III, Davis EM, et al: Cytogenetic and molecular delineation of a region of chromosome 7 commonly deleted in malignant myeloid diseases. Blood 88:: 1930,1996-1935, Medline, Google Scholar|
|33.||Fischer K, Frohling S, Scherer SW, et al: Molecular cytogenetic delineation of deletions and translocations involving chromosome band 7q22 in myeloid leukemias. Blood 89:: 2036,1997-2041, Crossref, Medline, Google Scholar|
|34.||Dohner K, Brown J, Hehmann U, et al: Molecular cytogenetic characterization of a critical region in bands 7q35-q36 commonly deleted in malignant myeloid disorders. Blood 92:: 4031,1998-4035, Crossref, Medline, Google Scholar|
|35.||Bench AJ, Nacheva EP, Hood TL, et al: Chromosome 20 deletions in myeloid malignancies: Reduction of the common deleted region, generation of a PAC/BAC contig and identification of candidate genes. UK Cancer Cytogenetics Group (UKCCG). Oncogene 19:: 3902,2000-3913, Crossref, Medline, Google Scholar|
|36.||Lengauer C, Kinzler KW, Vogelstein B: Genetic instabilities in human cancers. Nature 396:: 643,1998-649, Crossref, Medline, Google Scholar|
|37.||Schoch C, Kohlmann A, Dugas M, et al: Genomic gains and losses influence expression levels of genes located within the affected regions: A study on acute myeloid leukemias with trisomy 8, 11, or 13, monosomy 7, or deletion 5q. Leukemia 19:: 1224,2005-1228, Crossref, Medline, Google Scholar|
|38.||Barouk-Simonet E, Soenen-Cornu V, Roumier C, et al: Role of multiplex FISH in identifying chromosome involvement in myelodysplastic syndromes and acute myeloid leukemias with complex karyotypes: A report on 28 cases. Cancer Genet Cytogenet 157:: 118,2005-126, Crossref, Medline, Google Scholar|
|39.||Kirsch DG, Kastan MB: Tumor-suppressor p53: Implications for tumor development and prognosis. J Clin Oncol 16:: 3158,1998-3168, Link, Google Scholar|
|40.||Bouffler SD, Kemp CJ, Balmain A, et al: Spontaneous and ionizing radiation-induced chromosomal abnormalities in p53-deficient mice. Cancer Res 55:: 3883,1995-3889, Medline, Google Scholar|
|41.||Betts DR, Rohatiner AZ, Evans ML, et al: Abnormalities of chromosome 16q in myeloid malignancy: 14 new cases and a review of the literature. Leukemia 6:: 1250,1992-1256, Medline, Google Scholar|
|42.||Yamamoto K, Nagata K, Kida A, et al: Deletion of 16q11 is a recurrent cytogenetic aberration in acute myeloblastic leukemia during disease progression. Cancer Genet Cytogenet 131:: 65,2001-68, Crossref, Medline, Google Scholar|
|43.||Bollag G, Clapp DW, Shih S, et al: Loss of NF1 results in activation of the Ras signaling pathway and leads to aberrant growth in haematopoietic cells. Nat Genet 12:: 144,1996-148, Crossref, Medline, Google Scholar|
|44.||Le DT, Kong N, Zhu Y, et al: Somatic inactivation of Nf1 in hematopoietic cells results in a progressive myeloproliferative disorder. Blood 103:: 4243,2004-4250, Crossref, Medline, Google Scholar|
|45.||Poppe B, Vandesompele J, Schoch C, et al: Expression analyses identify MLL as a prominent target of 11q23 amplification and support an etiologic role for MLL gain of function in myeloid malignancies. Blood 103:: 229,2004-235, Crossref, Medline, Google Scholar|
|46.||Andersen MK, Christiansen DH, Kirchhoff M, et al: Duplication or amplification of chromosome band 11q23, including the unrearranged MLL gene, is a recurrent abnormality in therapy-related MDS and AML, and is closely related to mutation of the TP53 gene and to previous therapy with alkylating agents. Genes Chromosomes Cancer 31:: 33,2001-41, Crossref, Medline, Google Scholar|
|47.||Zatkova A, Ullmann R, Rouillard JM, et al: Distinct sequences on 11q13.5 and 11q23-24 are frequently coamplified with MLL in complexly organized 11q amplicons in AML/MDS patients. Genes Chromosomes Cancer 39:: 263,2004-276, Crossref, Medline, Google Scholar|
|48.||Bartel FO, Higuchi T, Spyropoulos DD: Mouse models in the study of the Ets family of transcription factors. Oncogene 19:: 6443,2000-6454, Crossref, Medline, Google Scholar|
|49.||Blair DG, Athanasiou M: Ets and retroviruses: Transduction and activation of members of the Ets oncogene family in viral oncogenesis. Oncogene 19:: 6472,2000-6481, Crossref, Medline, Google Scholar|
|50.||Truong AH, Ben-David Y: The role of Fli-1 in normal cell function and malignant transformation. Oncogene 19:: 6482,2000-6489, Crossref, Medline, Google Scholar|
|51.||Alitalo K, Saksela K, Winqvist R, et al: Acute myelogenous leukaemia with c-myc amplification and double minute chromosomes. Lancet 2:: 1035,1985-1039, Medline, Google Scholar|
|52.||Slovak ML, Ho JP, Pettenati MJ, et al: Localization of amplified MYC gene sequences to double minute chromosomes in acute myelogenous leukemia. Genes Chromosomes Cancer 9:: 62,1994-67, Crossref, Medline, Google Scholar|
|53.||Tang K, Finley RL Jr, Nie D, et al: Identification of 12-lipoxygenase interaction with cellular proteins by yeast two-hybrid screening. Biochemistry 39:: 3185,2000-3191, Crossref, Medline, Google Scholar|
|54.||Bowers AJ, Scully S, Boylan JF: SKIP3, a novel Drosophila tribbles ortholog, is overexpressed in human tumors and is regulated by hypoxia. Oncogene 22:: 2823,2003-2835, Crossref, Medline, Google Scholar|
|55.||Storlazzi CT, Fioretos T, Paulsson K, et al: Identification of a commonly amplified 4.3 Mb region with overexpression of C8FW, but not MYC in MYC-containing double minutes in myeloid malignancies. Hum Mol Genet 13:: 1479,2004-1485, Crossref, Medline, Google Scholar|
|56.||Peeters P, Raynaud SD, Cools J, et al: Fusion of TEL, the ETS-variant gene 6 (ETV6), to the receptor-associated kinase JAK2 as a result of t(9;12) in a lymphoid and t(9;15:12) in a myeloid leukemia. Blood 90:: 2535,1997-2540, Crossref, Medline, Google Scholar|
|57.||Rawat VP, Cusan M, Deshpande A, et al: Ectopic expression of the homeobox gene Cdx2 is the transforming event in a mouse model of t(12;13)(p13;q12) acute myeloid leukemia. Proc Natl Acad Sci U S A 101:: 817,2004-822, Crossref, Medline, Google Scholar|
|58.||van den Akker E, Forlani S, Chawengsaksophak K, et al: Cdx1 and Cdx2 have overlapping functions in anteroposterior patterning and posterior axis elongation. Development 129:: 2181,2002-2193, Medline, Google Scholar|
|59.||Isaacs HV, Pownall ME, Slack JM: Regulation of Hox gene expression and posterior development by the Xenopus caudal homologue Xcad3. EMBO J 17:: 3413,1998-3427, Crossref, Medline, Google Scholar|
|60.||Roche J, Zeng C, Baron A, et al: Hox expression in AML identifies a distinct subset of patients with intermediate cytogenetics. Leukemia 18:: 1059,2004-1063, Crossref, Medline, Google Scholar|
|61.||Uchida N, Hoshino S, Katada T: Identification of a human cytoplasmic poly(A) nuclease complex stimulated by poly(A)-binding protein. J Biol Chem 279:: 1383,2004-1391, Crossref, Medline, Google Scholar|
|62.||Hammet A, Pike BL, Heierhorst J: Posttranscriptional regulation of the RAD5 DNA repair gene by the Dun1 kinase and the Pan2-Pan3 poly(A)-nuclease complex contributes to survival of replication blocks. J Biol Chem 277:: 22469,2002-22474, Crossref, Medline, Google Scholar|
|63.||Burgering BM, Kops GJ: Cell cycle and death control: Long live Forkheads. Trends Biochem Sci 27:: 352,2002-360, Crossref, Medline, Google Scholar|
|64.||So CW, Cleary ML: Common mechanism for oncogenic activation of MLL by forkhead family proteins. Blood 101:: 633,2003-639, Crossref, Medline, Google Scholar|