research paper
Microarray transcript profiling distinguishes the transient from the acute type of megakaryoblastic leukaemia (M7) in Down’s syndrome, revealing PRAME as a specific discriminating marker
Suzanne McElwaine,1 Claire Mulligan,1 Ju¨rgen Groet,1 Monica Spinelli,2 Andrea Rinaldi,2 Gareth Denyer,3 Afua Mensah,1 Simona Cavani,4 Chiara Baldo,4 Franca Dagna-Bricarelli,4 Ian Hann,5 Giuseppe Basso,2 Finbarr E. Cotter1 and Dean Nizetic1 1
Centre for Haematology, Institute of Cell and
Molecular Science, Barts and The London, Queen Mary’s School of Medicine, University of London, Medical College Building, Turner Street, London, UK, 2Italian National Association for Paediatric Haemato-Oncology (AIEOP), Department of Paediatrics, Faculty of Medicine, University of Padua, Italy, 3Department of Biochemistry, University of Sydney, Sydney, Australia, 4
Laboratory of Human Genetics, Galliera Hospital, Genoa, Italy, and 5Hospital for Sick
Children, Great Ormond Street, London, UK 2004 Blackwell Publishing Ltd, British Journal of Haematology, 125, 729–742 Received 27 February 2004; accepted for publication 19 March 2004 Correspondence: Prof. Dean Nizetic, Centre for Haematology, Institute of Cell and Molecular Science, Barts and The London, Queen Mary’s School of Medicine, University of London, Medical College Building, Turner Street, London E1 2AD, UK.
Summary Transient myeloproliferative disorder (TMD) is a unique, spontaneously regressing neoplasia specific to Down’s syndrome (DS), affecting up to 10% of DS neonates. In 20–30% of cases, it reoccurs as progressive acute megakaryoblastic leukaemia (AMKL) at 2–4 years of age. The TMD and AMKL blasts are morphologically and immuno-phenotypically identical, and have the same acquired mutations in GATA1. We performed transcript profiling of nine TMD patients comparing them with seven AMKL patients using Affymetrix HG-U133A microarrays. Similar overall transcript profiles were observed between the two conditions, which were only separable by supervised clustering. Taqman analysis on 10 TMD and 10 AMKL RNA samples verified the expression of selected differing genes, with statistical significance (P < 0Æ05) by Student’s t-test. The Taqman differences were also reproduced on TMD and AMKL blasts sorted by a fluorescence-activated cell sorter. Among the significant differences, CDKN2C, the effector of GATA1mediated cell cycle arrest, was increased in AMKL but not TMD, despite the similar level of GATA1. In contrast, MYCN (neuroblastoma-derived oncogene) was expressed in TMD at a significantly greater level than in AMKL. MYCN has not previously been described in leukaemogenesis. Finally, the tumour antigen PRAME was identified as a specific marker for AMKL blasts, with no expression in TMD. This study provides markers discriminating TMD from AMKL-M7 in DS. These markers have the potential as predictive, diagnostic and therapeutic targets. In addition, the study provides further clues into the pathomechanisms discerning selfregressive from the progressive phenotype. Keywords: Down’s syndrome, microarray, transient myeloproliferative disorder, acute megakaryoblastic leukaemia (M7).
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Transient Myeloproliferative Disorder (TMD), also previously referred to as transient leukaemia (TL) or transient abnormal myelopoiesis (TAM), is a self-regressing neoplasia, almost exclusively occurring in babies with Down’s syndrome (DS), during the first 4 weeks of life (Arceci, 2002; Gamis & Hilden, 2002; Taub & Ravindranath, 2002). It is estimated that as many as 10% of all DS cases suffer from a TMD episode (Zipursky et al, 1992, 1995; Al-Kasim et al, 2002). The self-regressive nature of the disorder means it could provide potential clues as to the mechanisms that could be exploited to control
myeloproliferation (Gamis & Hilden, 2002). Approximately 20–30% of cases with TMD develop acute megakaryoblastic leukaemia (AMKL, or AML-M7) with an onset at 2–4 years of age (Zipursky et al, 1992, 1994; Homans et al, 1993; Lu et al, 1993). Childhood AMKL has a relative risk of 500-fold in DS children (Zipursky et al, 1994; Gamis & Hilden, 2002), although all other types of acute leukaemias of childhood (ALL, AML-not M7) are also increased in DS children compared with non-DS children (Zipursky et al, 1992). Recently, Wechsler et al (2002) observed acquired mutations
ª 2004 Blackwell Publishing Ltd, British Journal of Haematology, 125, 729–742
doi:10.1111/j.1365-2141.2004.04982.x
S. McElwaine et al in the erythroid/megakaryocyte lineage-specific transcription factor GATA1 in the genomic DNA samples from six of six examined cases of DS with AMKL, and none in 92 control cases, which included DS with other kinds of myeloid leukaemia, AMKL cases in non-DS individuals, and healthy controls. All mutations were acquired (DNA from remission samples did not show them), and all resulted in a premature translation termination in the GATA1 activation domain (encoded by the second exon). The resulting cells only produced the shorter version of the GATA1 protein (GATA1s), lacking the activating domain. This domain is important for the proper transactivating potential of the protein (Shimizu et al, 2001). Following this first report, other groups found that a variety of similar mutations with identical protein consequences are acquired in utero in TMD patients (Groet et al, 2003; Hitzler et al, 2003; Mundschau et al, 2003; Rainis et al, 2003; Xu et al, 2003). The mutations do not predict whether a TMD will progress to a later AMKL (Groet et al, 2003; Rainis et al, 2003; Xu et al, 2003). When the individual TMD patients were followed after developing AMKL a few years later, the proliferating clone retained the same GATA1 mutation (Hitzler et al, 2003; Rainis et al, 2003). These findings clearly implicate mutation in GATA1 as an early event (Ahmed et al, 2003), having a very important role in the pathogenesis of AMKL in DS. What remains unanswered are the mechanisms that predispose the early, trisomy 21-bearing, myeloid precursor cells to acquire a GATA1 mutation in the first place, the exact pathomechanism by which GATA1 mutation leads to TMD, the mechanism responsible for the spontaneous regression of TMD, and the nature of the additional changes (‘second hits’) required for the development of the progressive AMKL. To investigate these questions, microarray hybridizations were used to obtain global transcriptional profiles of DS-TMD and DS-AMKL and identify genes with significantly differing levels between these two conditions.
Materials and methods Patients and samples The project was approved by the North East London Health Authority’s Ethical Committee. Samples were surplus clinical, or archived clinical material collected by the tissue bank of the Italian National Down’s Syndrome Association, (CEPIM), (samples kept by the team of Galliera Genetic Bank, http://www.ggb.galliera.it/), Italian National Association for Paediatric Haematology-Oncology (AIEOP), or the UK-Childhood Cancer Study Group. Written consent was obtained by the tissue banks for all subjects. All patients (detailed in Table I) were diagnosed with DS at birth, and confirmed by cytogenetics to contain a constitutional full trisomy 21. The diagnosis of AML-M7 was made by morphological criteria and confirmed by immunophenotyping. All samples consisted of mononucleated cells collected through Ficoll gradient from peripheral blood (PB) or bone marrow (BM), during the 730
course of routine clinical procedures. Non-leukaemic (normal) controls (n ¼ 11) included nine normal donor BM samples and two donated normal PB samples. DS non-leukaemic controls comprised three PB samples from DS children who never had TMD or leukaemia. After being frozen in 10% dimethylsulphoxide and stored in tissue banks, samples were washed in phosphate-buffered saline, and used for the isolation of RNA. In some patients, blast cells used in Taqman (Applied Biosystems, Warrington, UK) reverse transcription polymerase chain reaction (RT–PCR) experiments were sorted using FACSVantage for CD34+ (in patients with CD34+ blast cells) or CD45 and CD33 and/or CD7 in the remaining patients (for details see Table I and supplementary Fig 2 online, all supplementary figures and tables for online access can be found at http://www.smd.qmul.ac.uk/haematology/). As the sorted blast cells were positive for either CD34 or CD33 (or both) in all sorted patient samples, the normal controls for sorted cells were prepared by sorting separately for either CD33+ or CD34+ cells from normal or remission tissues. The choice of control material was made to match the patient population as closely as possible, limited by the availability of consented samples of sufficient quality and quantity within our tissue bank sources. Normal sorted samples hybridized to microarrays were further limited to only those from which >5 lg of starting RNA could be obtained. The non-leukaemic (normal) sorted samples used for Taqman RT–PCR included magnetic bead-separated CD34+ cells (n ¼ 6) from four normal cord blood samples, one non-leukaemic DS cord blood sample, and one pool of 10 BM-complete remission samples from DS children after various types of leukaemia. The CD34) effluents from those same separations were separated, by a fluorescence-activated cell sorter (FACS), for CD33+ cells in all except two normal cord blood samples. An additional sample of FACS-separated CD33+ cells from one adult male BM brought the total number of CD33+ normal samples to n ¼ 5. This BM sample (NBM33+), along with CD33+ cells from one normal male cord blood (NCB33+) and one nonleukaemic DS male cord blood sample (DSCB33+) were also analysed on microarrays as non-leukaemic myelocyte controls. Although the normal sorted samples comprise a slightly heterogeneous group, they were included mainly for illustration purposes and conclusions in the study were not based on these samples, but strictly on comparisons between the two groups of patient samples. For details of cell purification and examples of purity assessment by FACS, see supplementary Fig 2 online. For all non-leukaemic normal and DS control samples the GATA1 exon 2 was amplified by RT–PCR from the RNA and confirmed by agarose gel electrophoresis, and sequencing using ABI3100 automated sequencer, to have the full-length wild type GATA1 sequence.
Preparation and utilization of RNA from clinical samples We isolated total RNA from mononuclear cells from PB or BM samples taken during the presenting phase of the disease
ª 2004 Blackwell Publishing Ltd, British Journal of Haematology, 125, 729–742
M F
M M
5d
20 d
Newborn
94 32
94 78
50 >94 33
20
ND
ND
85 >94 50 >94 60 >94 55
Blasts (%)
Table I. Description of individual RNA samples used in the study.
Remission Dg CD7+33+ Dg CD7+33+ Dg
Remission Dg
Remission Dg
Dg
CD33+34+45+
Dg CD33+34+ Dg
Dg CD33+45+ Dg
Dg
Dg
Dg
Dg CD7+33+34+ Dg CD34+ Dg CD34+ Dg
Material
Taqman U133A(Stand), Taqman Taqman U133A(Stand), Taqman Taqman U133A(Stand), Taqman
Taqman Taqman
Taqman U133A(Amp), Taqman
U133A(Stand), Taqman
Taqman
U133A(Stand), Taqman Taqman U133A(Stand), Taqman
U133A(Stand), Taqman Taqman U133A(Stand), Taqman
Insufficient RNA
U133A(Amp), Taqman
U133A(Amp), Taqman
U133A(Stand), Taqman Taqman U133A(Stand), Taqman Taqman U133A(Stand), Taqman Taqman Taqman
RNA utilization
None None
Splice D-exon 2 Splice D-exon 2
160–161del2bp
251delT
wt Splice D-exon 2
wt Splice D-exon 2
wt 344–345ins2bp
270–271ins7bp
303dup10bp
263 del G
245–266del22bp
263delG
Treated
Treated
Treated
Treated
Treated
Treated
None
None
None
None
None
None
Splice D-exon 2
344–345ins2bp
None
None
None
None
Therapy
160–161del2bp
161C>T, STOP
259dup34bp
270–271ins7bp
GATA1 exon 2
Died during therapy
Died during therapy
Died during therapy
Complete remission (>9 years)
Complete remission (>9 years)
Complete remission (>1 years) Complete remission (>3 months) Complete remission (>3 years)
Complete remission (>9 years) Died during TMD
Died later (non-haem. cause) Complete remission (>8 years) Complete remission (>7 years) Complete remission (2Æ5 years) ND
Complete remission (>7 years)
Complete remission (>7 years)
Complete remission (2 years)
Outcome
Microarray Profiling of TMD vs AMKL in Down’s Syndrome
731
732
M M M F
M M
months months months months 24 36 28 24
34 months 10 months
All patients were diagnosed with Down’s syndrome at birth, and confirmed by cytogenetics of stimulated lymphocytes to contain a constitutional full trisomy 21. Some of these data and more details about the majority of patients are shown in Groet et al (2003). Dg, diagnosis; TMD, transient myeloproliferative disorder; AMKL, acute megakaryoblastic leukaemia; wt, wild-type; blasts, RNA isolated from cells separated by fluorescence-activated cell sorter (FACS) from the diagnostic samples of individual patients stained with antibodies against the indicated CD markers; details of the cell sorting procedure and examples of sorted cell purity assessment are shown in supplementary Fig 2 online; U133A or Taqman indicate whether a particular RNA sample was hybridized to HG-U133A GeneChips and/or used in realtime reverese transcription polymerase chain reaction (RT–PCR; Taqman) verification experiments; Stand, standard Affymetrix labelling protocol (>5 lg of starting RNA) was used to prepare the RNA for array hybridization; Amp, Affymetrix small sample (‘amplified’) protocol was used to prepare the RNA for array hybridization; ND, no data; ‘splice D-exon 2’ indicates that only a shorter product was detected by RT–PCR, resulting from a splicing event skipping the entire exon 2; *an acquired mutation in RUNX1 runt domain was found (unpublished); **see Sato et al (1989).
ND Died during therapy** Treated Treated** wt* 117–119del3bpinsC
ND ND ND ND Treated Treated Treated Treated 197 G>T, STOP 301 C>G, STOP wt 262–263 ins7bp
Died during therapy Treated Splice D-exon2
U133A(Stand), Taqman Taqman U133A(Amp) Taqman Taqman Taqman Taqman Taqman U133A(Stand), Taqman M 24 months
AMKL7 AMKL7blasts AMKL8 AMKL9blasts AMKL10 AMKL11 AMKL11blasts AMKL12 CMK
60 >94 >50 >94 ND 50 >94 20 100
Dg CD7+33+ Dg CD34+ Dg Dg CD7+33+ Dg Cell line
Therapy RNA utilization Age at Dg Sample
Table I. continued
Sex
Blasts (%)
Material
GATA1 exon 2
Outcome
S. McElwaine et al (diagnosis, pretreatment), from 12 DS-AMKL patients and 12 DS-TMD patients. The details of the age, sex, percentage blasts, sorted blast samples, and follow-up information are listed in Table I. More details (such as blast karyotype) can be found in Groet et al (2003), for the majority of the samples. None of the TMD cases were treated, and in all of them the blast proliferation regressed spontaneously. One died from the severe form of TMD (while his blasts were in spontaneous regression), and one died later from non-haematological causes, whereas all others (data availability permitting) are still alive. All AMKL cases underwent therapy using a variety of therapeutic regimes, and the outcomes, where available, are given in Table I. All analysed cases were sequenced for GATA1 in their RNA [majority published (Groet et al, 2003), with six new GATA1 mutations identified since that publication], and all of these data are also shown in Table I. Seven AMKL and nine TMD samples yielded RNA of sufficient quantity and quality for hybridizations to Affymetrix Human GenomeU133A microarrays. All microarray data and related information are Minimum Information about a Microarray Experiment (MIAME) compliant and have been deposited in the Europrean Bioinformatics Institute (EBI) MIAMExpress microarray data repository (http://www.ebi.ac.uk/arrayexpress). Sample TMD7 had insufficient RNA for any experiments besides GATA1 sequencing. The entire sample AMKL8 was used up for the array hybridization, and there was none left for the Taqman experiments. All other samples from Table I were used in Taqman verification experiments (a total of 10 TMD and 10 AMKL unsorted diagnosis samples). Note that additional samples TMD12 and AMKL9 were available as sorted cells only, and were used in Taqman comparisons alongside sorted cells from other patients.
Microarray analysis The RNA was extracted from the samples indicated in Table I using Qiagen RNeasy mini-columns (Qiagen, Crawley, UK) and processed according to the protocol recommended by Affymetrix (http://www.affymetrix.com), with samples TMD5, TMD6, AMKL2 and AMKL8 undergoing an additional amplification cycle as described in the Affymetrix small sample protocol, due to the low amount of starting material available in those cases. Labelled cRNA samples were first hybridized to Affymetrix Test3 arrays and scaled to a target intensity of 500 to check sample quality. For the standard labelling protocol, only those samples in which >15% of probe sets were called present, and the 3¢/5¢ GAPDH ratio was
