Novel regions of acquired uniparental disomy discovered in acute myeloid leukemia

RESEARCH ARTICLES

Novel Regions of Acquired Uniparental DisomyDiscovered in Acute Myeloid Leukemia

Manu Gupta,1 Manoj Raghavan,1 Rosemary E. Gale,2 Claude Chelala,3 Christopher Allen,2 Gael Molloy,1

Tracy Chaplin,1 David C. Linch,2 Jean-Baptiste Cazier,1,4 and Bryan D. Young1*

1Cancer Genomics Unit,Medical Oncology Centre,Barts and the London Schoolof Medicine,Charterhouse Square,London EC1M 6BQ,UK2Departmentof Haematology,Royal Free and University College Medical School,LondonWC1E 6HX,UK3Centre for Molecular Oncology,Institute of Cancer & Cancer Research UKClinical Centre,Barts and The London School of Medicine,Charterhouse Square,London EC1M 6BQ,UK4Cancer Research UKBioinformatics & Biostatistics Service,LondonWC2A 3PX,UK

The acquisition of uniparental disomy (aUPD) in acute myeloid leukemia (AML) results in homozygosity for known gene muta-

tions. Uncovering novel regions of aUPD has the potential to identify previously unknown mutational targets. We therefore

aimed to develop a map of the regions of aUPD in AML. Here, we have analyzed a large set of diagnostic AML samples (n 5454) from young adults (age: 15–55 years) using genotype arrays. Acquired UPD was found in 17% of the samples with a non-

random distribution particularly affecting chromosome arms 13q, 11p, and 11q. Novel recurrent regions of aUPD were uncov-

ered at 2p, 17p, 2q, 17q, 1p, and Xq. Overall, aUPDs were observed across all cytogenetic risk groups, although samples with

aUPD13q (5.4% of samples) belonged exclusively to the intermediate-risk group as defined by cytogenetics. All cases with a

high FLT3-ITD level, measured previously, had aUPD13q covering the FLT3 gene. Significantly, none of the samples with FLT3-

ITD-/FLT3-TKD1 mutation exhibited aUPD13q. Of the 119 aUPDs observed, the majority (87%) were due to mitotic recombi-

nation while only 13% were due to nondisjunction. This study demonstrates aUPD is a frequent and significant finding in AML

and pinpoints regions that may contain novel mutational targets. VVC 2008 Wiley-Liss, Inc.

INTRODUCTION

Acute myeloid leukemia (AML) is characterized

by recurrent acquired cytogenetic and genetic

abnormalities. The biological importance of these

is underlined by the prognostic value conferred by

these abnormalities. From UK Medical Research

Council (MRC) trials, AML patients with translo-

cations involving t(8;21), t(15;17), and inv(16) have

been shown to have a favorable risk while those

with a complex karyotype with 5 or more ab-

normalities, 25/del(5q), 27 or abn(3q) have an

adverse risk (Grimwade et al., 1998). The remain-

ing large proportion of samples (about 60%) with

an intermediate risk includes cases with normal

karyotype (about 40% of AML patients). The

patients in this group have heterogeneity in

response to treatment. Mutation analysis has

helped to further stratify the patients and it has

been shown that mutations in genes such as the

fms-like tyrosine kinase 3 (FLT3) and nucleophos-

min 1 (NPM1) are linked to treatment outcome

(Kottaridis et al., 2001; Falini et al., 2005; Baldus et

al., 2007; Mead et al., 2007).

Studies have shown that patients with propor-

tionally high level of FLT3-internal tandem dupli-

cation (ITD) mutant compared with wild-type

FLT3 have a poor outcome (Kottaridis et al., 2001;

Thiede et al., 2002). Additionally, in 10% of

patients with normal karyotype AML, loss of the

wild-type FLT3 allele and ITD mutation in the

remaining FLT3 allele is associated with a worse

outcome (Whitman et al., 2001). Acquired unipar-

ental disomy (aUPD), a recently described somatic

aberration, has been shown to result in homozygos-

ity, and hence can be the basis of increased dosage,

for preexisting mutations in FLT3 and also in genes

such as WT1, RUNX1, and CEBPA (Fitzgibbon et

al., 2005; Raghavan et al., 2005). Acquired UPD

leads to the generation of two daughter cells each

with the reciprocal chromosomal products. The

*Correspondence to: Bryan D. Young, Cancer Genomics Unit,Medical Oncology Centre, Barts and the London School of Medi-cine, Charterhouse Square, London EC1M 6BQ, United Kingdom.E-mail: [email protected]

This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045-2257/suppmat.

Supported by: Leukaemia Research Fund and Cancer Research,UK.

Received 20 February 2008; Accepted 14 April 2008

DOI 10.1002/gcc.20573

Published online 27 May 2008 inWiley InterScience (www.interscience.wiley.com).

VVC 2008 Wiley-Liss, Inc.

GENES, CHROMOSOMES & CANCER 47:729–739 (2008)

homozygosity observed in AML is due to the out-

growth of cells carrying the mutation thus eliminat-

ing or outnumbering the cells with wild-type allele.

The study of aUPD can thus identify regions con-

taining potential mutational targets. Because the

current list of genes known to be mutated in AML

is probably incomplete, it is important to develop a

map of aUPD in AML.

Previous studies in 64 AML samples with

diverse karyotype (Raghavan et al., 2005) and in 32

normal karyotype AML samples (Gorletta et al.,

2005) have shown aUPDs to be present in about

20% of the AML samples. However, since this fre-

quency estimate is based on small cohorts, less fre-

quent aUPDs may have been missed altogether.

To provide a more comprehensive map of the prev-

alence and locations of aUPD in AML, we have

genotyped samples from a large cohort of 454

young adult AML patients with diverse range of

karyotypes typical of the disease.

In common with other reports (Walker et al.,

2006; Fitzgibbon et al., 2007; Gondek et al.,

2007a,b,c; Kloth et al., 2007; Mohamedali et al.,

2007; Pfeifer et al., 2007), LOH and copy number

patterns were analyzed using pooled unrelated

controls. This study has identified novel recurrent

regions of aUPD at 2p, 17p, 2q, 17q, 1p, and Xq. In

addition, expected copy number alterations e.g.,25q, 27/27q, and 18 were reliably detected.

PATIENTS ANDMETHODS

Samples

We genotyped DNA from 463 young adult AML

patients at diagnosis aged between 15 and 55 years

entered into the UK MRC AML10 trial. These

constituted 24% of all of the AML patients entered

into the trial (Hann et al., 1997; Grimwade et al.,

1998). Ethical approval for the trial was obtained

from the Multi-Centre Research Ethics Commit-

tee of Wales and informed consent was provided

according to the Declaration of Helsinki. Four

samples were excluded from the study as the

patients were subsequently rediagnozed as not

AML. Another 4 samples that were either triploid

(n 5 1), tetraploid (n 5 2), or hypodiploid (n 5 1)

were excluded from the analysis (see supplemen-

tary information and supplementary Table 1). Fur-

ther, one sample with low call rate (<75%) was not

considered during analysis. Of the remaining 454

samples, the karyotype was known for 363 of which

55 were favorable risk, 276 intermediate risk

including 190 with a normal karyotype, and 32

adverse risk. The samples set consisted of 224

males and 230 females. Mutation status for FLT3(both ITDs and tyrosine kinase domain [TKD]

mutations) and NPM1 exon 12 mutations was avail-

able for all 454 samples. We also studied paired

remission DNA available from eight patients to

compare with the results from diagnostic samples.

Experiments on 23 samples (5% of the sample set)

were repeated to determine the reproducibility of

our data. Genomic DNA from blood samples of

10 nonleukemic individuals processed at the same

facility was used as control (control set I) to esti-

mate the copy number values.

Mapping 10K 2.0 GeneChip Assay

We used Mapping 10K 2.0 arrays (Affymetrix,

Santa Clara, CA) (Matsuzaki et al., 2004). These

arrays encode 10,204 single nucleotide polymor-

phisms (SNPs) and have a median intermarker dis-

tance of 113 kilobases (Kb). The markers cover all

22 autosomes and the X chromosome. Experi-

ments were performed according to the manufac-

turer’s instructions except that polymerase chain

reaction (PCR) products were purified using an

Ultrafree-MC filtration column (Millipore, Biller-

ica, MA). Signal intensity data were analyzed by

the GeneChip DNA Analysis Software and

GTYPE was used for calling the genotypes. The

signal intensity data were used to calculate DNA

copy number. The primary SNP microarray data

have been deposited in the NCBIs Gene Expres-

sion Omnibus (GEO, http://www.ncbi.nlm.nih.gov/

projects/geo/) and are accessible through GEO

series accession number GSE8721.

Data Analysis

For copy number estimation, the log2 ratio of

the signal intensity from the test sample versus the

pooled signal intensity from 10 unrelated nonleu-

kemic male control samples (control set I) was

used. In addition, for eight cases where paired

remission samples were studied, copy number in

the diagnostic samples was also analyzed as a ratio

of the diagnostic DNA/remission DNA signal in-

tensity. To identify regions with losses, gains or

aUPD, we used software developed in-house

known as Genome Oriented Laboratory File

(GOLF) (Fitzgibbon et al., 2007) (Cazier J-B and

Young BD, manuscript in preparation). A ratio of

signal intensity below 0.75 and above 1.25 on at

least three consecutive SNPs was defined as a loss

and a gain, respectively. The aberrations identified

by the software were confirmed by visual inspec-

tion of the log2 ratio plots of test sample against

control. The software package GOLF along with

Genes, Chromosomes & Cancer DOI 10.1002/gcc

730 GUPTA ETAL.

the guidelines for its use, and the data described in

this article are available for download from http://

bioinformatics.cancerresearchuk.org/cazier01. The

physical positions of markers and genes in this

report are based on the NCBI 35 assembly of the

human genome (May 2004).

Control Samples to Define Criteria for aUPD

In the absence of paired control samples, identi-

fication of aUPD is based on the presence of runs

of consecutive homozygous markers. However, the

human genome is known to harbor large inherited

regions of homozygosity (IRH) due to strong link-

age disequilibrium between the markers (2005). In

addition, areas of low SNP coverage and minor

alleles with a low frequency may appear as IRH.

IRHs may also exist due to consanguinity although

the later is less likely in the current sample set pri-

marily being from Caucasians. To distinguish IRHs

from acquired regions and to evaluate the false

positive rate in our data, we examined data from

the blood of another set of nonleukemic individu-

als (control set II). We defined the criteria for

aUPD in our AML cohort based on the 10K 2.0

data available from 90 independent germ-line sam-

ples (control set II) from the ColoRectal tumor

Gene Identification (CoRGI) Study Consortium

(Kemp et al., 2006).

Criterion for Detection of aUPD

To define a region of aUPD in our cohort of

AML samples, first we determined the number of

homozygous regions observed in CoRGI controls

(control set II) with a continuously increasing

threshold of consecutive homozygous SNPs while

allowing for 0, 1, or 2 heterozygous calls within the

regions to accomodate genotyping errors that may

result from the presence of some normal DNA in

the sample (Supplementary Fig. 1). Analysis was

done considering ‘‘no calls’’ as either homozygous

or heterozygous in separate comparisons. The

number of regions observed in controls reached a

lower plateau at the threshold of 50 consecutive

markers. The difference in the observed number

of regions between the CoRGI and AML sample

sets was greatest when two heterozygotes were

allowed. We further tested the number of homozy-

gous regions observed in controls in the above

fashion but without considering the ‘‘no calls.’’

Allowing two heterozygous calls among 50 SNPs

(abbreviated as 50/2) only three IRHs were

observed in just three samples (3.3%) among the

90 controls, suggesting this to be a stringent crite-

rion. We therefore used 50/2 as our definition of

aUPD with an expected false positive rate of 3.3%

i.e., homozygous regions not related to the disease.

This criterion has recently been used successfully

to define aUPD in a lymphoma study (Fitzgibbon

et al., 2007). Using this definition, the shortest

average length of aUPD regions in our study would

be 5.6 megabases (Mb) given that the median

inter-marker distance on the 10K 2.0 arrays is 113

Kb. The regions of aUPD on the X-chromosome

can only be identified in females. Thus, the num-

ber of aUPDs on the X-chromosome reported in

this article is from 230 females only.

Using the above-defined criteria of 50/2 for

aUPD, we did not observe any IRH in control set

I (n 5 10). Among 8 paired remission samples,

only one showed one IRH on chromosome 19 that

was centered on the centromere, i.e., regions

known to have strong linkage disequilibrium be-

tween markers.

RESULTS

Quality Control of the Data

A number of parameters were monitored during

sample processing to determine the sample quality

and the final quality of the SNP array data. All of

the sample DNAs were first run on 1% agarose gel

to check the DNA quality. Accuracy of the data

were estimated by calculating the frequency of

heterozygous calls on the X-chromosome in male

samples. One male sample with <75% call rate had

58 heterozygous calls on the X-chromosome and

was deleted from the analysis. In the remaining 224

male samples, we observed only eight heterozygous

calls giving an accuracy of >99.999% for genotype

calls. SNP call rate was considered the final arbiter

of data quality: median SNP call rate per array was

98.3%, mean 97.88% and range 88.24%–99.75%.

Experiments were repeated on 23 (5%) samples to

check the reproducibility and validity of the data.

In total 71 calls (range: 0–11) were found to be dis-

cordant among 23 pairs, which means the reproduci-

bility of our genotype calls is 99.96%.

Global View of all of the Aberrations Observed

We detected a total of 351 aberrations (aUPDs,

losses and gains) in 163 (36%) of the 454 samples

(Tables 1 and 2). A global view of the aberrations

detected on each chromosome is depicted in Fig-

ure 1 and details are given in Table 3. Acquired

UPDs were observed in 17% of samples, losses in

15% and gains in 12% of samples (Tables 1 and 2).

In total, 5 samples had more than two aUPDs. No

homozygous losses were observed. At least one


731ACQUIRED UNIPARENTAL DISOMY IN AML

aberration was observed on each chromosome

across the 454 samples studied. The minimum

genomic size of each aberration was: aUPD 7.17

Mb, loss 1.8 Mb and gain 3.6 Mb. The results for

23 repeat samples were identical.

Acquired UPDs

The chromosomal distribution of aUPD was

nonrandom (Fig. 1). Chromosomes 11 and 13 had

the highest number of aUPDs (16% and 15% of all

aUPDs respectively) and are depicted in Figures

2A and 2B.

Results in diagnostic samples were also com-

pared with corresponding remission samples in

eight cases. Acquired aUPDs were observed in five

diagnostic samples and in each case these were

absent in the corresponding remission sample.

These included three samples with aUPD on chro-

Figure 1. Global view of aUPDs, losses and gains in 454 AML samples across the 22 autosomes and Xchromosome. Aberrations (gain in red, loss in green, and aUPD in blue) for individual samples are shown tothe right of each chromosome.


732 GUPTA ETAL.

mosome 13, one sample with aUPD on 11p and 1

sample with deletion on 11p in addition to aUPD

on 11q. Absence of these aberrations in remission

samples confirms their somatic origin and corrobo-

rates previous observations (Gorletta et al., 2005;

Raghavan et al., 2005). In general, we did not find

any correlation between aUPDs and the losses,

gains or aUPDs in other regions of the genome or

with chromosomal rearrangements identified

through karyotype analysis.

Chromosome 11

aUPDs were observed on both 11p (n 5 8) and

11q (n 5 9). In two samples aUPDs were observed

across the centromere. Four minimal regions of

aUPD could be delineated: 11pter-11p15.2 (17.4

Mb, n 5 8), 7 of which included the WT1 gene,

11p11.2 (2.8 Mb, n 5 6), 11q22.3 (4.51 Mb, n 5 7)

that includes the ATM gene and 11q24.1-q25 (11.8

Mb, n 5 7) (Fig. 2A; Supplementary Table 2). Six

of the nine samples with 11q aUPD included the

MLL gene.

Chromosome 13

Of the 18 samples with aUPD, 13 involved the

whole chromosome and another 2 had aUPD

resulting from a single breakpoint at 13q12.2 lead-

ing to homozygosity across most of the chromo-

some (Fig. 2B). The aUPDs in these 15 cases all

included the FLT3 gene and mutation analysis

revealed that all of the 15 had FLT3-ITD mutation

while only one had FLT3-TKD mutation. Eleven

of 15 samples had a single high-level ITD mutant

comprising 59–96% of total FLT3 alleles, indicative

of the loss of wild-type (WT) alleles in at least a

proportion of cells. One sample had a high total

FLT3-ITD level (68%) but this was made up of 2

mutants, 51% and 17%, respectively. Among the

remaining three samples, one had 2 ITD mutants

of total 48% (35% and 13%), and two samples each

had single ITD mutants of 39% and 36%, respec-

tively. Three further samples had interstitial

aUPDs between q13.1-q14.2 and q31.1-q33.2 that

did not include the FLT3 gene and all three lacked

TABLE 1. Aberrations Observed in Relation to Cytogenetic Risk Groups in the Total Cohort of 454 Samples

Adverserisk

Favorablerisk NKa

Intermediaterisk minus NKa

Unknownkaryotype Total (%)

Number of samples (% of total) 32 (7) 55 (12) 190 (42) 86 (19) 91 (20) 454Gains, no. (% of gains) 12 (22) 5 (9) 3 (5) 21 (38) 14 (25) 55 (12)Losses, no. (% of losses) 25 (36) 7 (10) 7 (10) 15 (21) 16 (23) 70 (15)aUPDs, no. (% of aUPDs) 8 (10) 6 (8) 37 (47) 9 (12) 18 (23) 78 (17)

aNK indicates normal karyotype.

TABLE 2. Aberrations Stratified by the Number of Breakpoints Involved

No breakpointSingle

breakpointDouble

breakpointTotal aberrations

(% of total)

Gains, no. (% of gains) 50 (66) 20 (26) 6 (8) 76 (21)Losses, no. (% of losses) 34 (22) 67 (43) 55 (35) 156 (44)aUPDs, no. (% of aUPDs) 15 (13) 56 (47) 48 (40) 119 (34)Total, no. (% of total) 99 (28) 143 (41) 109 (31) 351

TABLE 3. Distribution of the Total Number of Gains, Lossesand aUPDs Observed on 22 Autosomes and X Chromosome

Chromosome Gains Losses aUPDs All

1 2 2 9 132 0 3 13 163 3 9 4 164 3 3 1 75 2 17 3 226 2 12 8 227 0 31 6 378 31 5 5 419 2 9 5 16

10 1 2 0 311 13 11 19 4312 0 7 0 713 4 2 18 2414 1 0 2 315 1 1 0 216 1 5 3 917 0 9 7 1618 0 9 2 1119 1 3 5 920 0 8 2 1021 7 1 4 1222 1 1 1 3X 1 6 2 9

Total 76 156 119 351



a FLT3-ITD although one was positive for FLT3-

TKD mutation. Interestingly, all of the samples in

the cohort with a high FLT3-ITD mutant level,

i.e., greater than 50% of total alleles, had

aUPD13q. Recurrent whole chromosome aUPD

was observed only on chromosome 13 (Supplemen-

tary Table 3). Acquired UPDs on chromosome 13

were observed exclusively in intermediate risk

Figure 2. Aberrations observed on chromosomes 11 and 13. (A) Chromosome 11 and (B) chromosome13 are shown with their bands, a subset of potential target genes in AML and regions of gain (red), loss(green) and aUPD (blue) annotated. The scale at the bottom shows the length of each chromosome in meg-abases (Mb). The color gradient above each kind of aberration summarizes the data for that aberration.


734 GUPTA ETAL.

patients (n 5 15, 5% of this group), 13 of whom

had a normal karyotype (Supplementary Table 4).

Novel regions of aUPD

Novel recurrent aUPDs in 3 or more samples

were detected at 2p (n 5 5), 17p (n 5 5), 2q (n 54), 17q (n 5 4), 1p (n 5 4), and Xq (n5 2) (Supple-

mentary Figs. 2A–2U; Supplementary Table 2).

Region of aUPD at 17p included the TP53 gene,

but for the other regions there are no obvious

candidates previously described in AML.

Other regions

Other chromosomes with areas of recurrent

aUPD were 6p, 9p, 19q, and 21q (Supplementary

Figs. 2A–2U). Acquired UPD in these regions has

been reported in earlier studies (Gorletta et al.,

2005; Raghavan et al., 2005). Regions of aUPD on

19q and 21q included CEBPA and RUNX1 genes,

respectively, mutations of which have been associ-

ated with aUPD in earlier studies (Fitzgibbon et

al., 2005; Raghavan et al., 2005).

aUPDs across cytogenetically defined risk groups

Table 1 shows the abnormalities observed in the

samples stratified by cytogenetic risk group. Sam-

ples with adverse risk cytogenetics had highest fre-

quency of all three types of aberration with aUPDs

in 25% of the samples, copy number loss in 78%

and gain in 38%. In samples from patients with

favorable risk cytogenetics, all three types of aber-

ration were present at a relatively lower frequency,

11% had aUPD, 13% had copy number loss, and

9% had copy number gain. In the samples from

patients with intermediate risk cytogenetics,

aUPDs were present at a higher frequency (17% of

samples) than copy number losses (8%) or gains

(9%). Stratifying the samples with intermediate

risk into those with a normal karyotype and the

rest showed that aUPDs were more common in the

normal karyotype group (19% and 10% of samples,

respectively) but the difference did not reach sta-

tistical significance (P 5 0.09, Table 1).

aUPDs detected as sole aberration

Based on SNP array results, aUPD(s) were

detected as the sole aberration in 59 (13%) of the

454 samples, 49 of which had a single aUPD, 6 had

two aUPDs, and 4 had four or more aUPDs (4, 6, 8,

and 14 aUPDs each). Cytogenetic profiles were

available for 48 of these samples; 36 (75%) had a

normal karyotype including the 4 samples with

four or more aUPDs, 6 additional samples had

intermediate risk karyotype, 5 had favorable and 1

had adverse risk karyotype. Fifteen (8%) samples

with a normal karyotype had no evidence of FLT3-ITDs and FLT3-TKDs while 10 (5%) samples

with a normal karyotype had no mutations in FLT3and NPM1.

aUPDs and number of breakpoints

Acquired UPDs resulting from a single break-

point, i.e., continuing from a certain point on the

chromosome to the telomere were the most fre-

quent (47% of all aUPDs). Interstitial aUPDs

resulting from double breakpoint events, i.e., not

reaching to either telomere occurred in 40% and

whole chromosome aUPDs with no evidence of a

breakpoint in 13% of the cases. Overall, 87% of the

aUPDs involved at least one breakpoint (Table 2).

Losses and Gains

The overall pattern of losses and gains is

depicted in Figure 1. As expected, the most fre-

quent losses (monosomies included) detected were

27/del(7q) (n 5 28, 18% of all losses), del(5q) (n 515, 10%), and 17p (n 5 9, 6%). Recurrent gains

(trisomies included) were observed at 8q (n 5 31,

41% of all gains), 11q (n 5 10, 13%), 21q (n 5 7,

9%), and 13q (n 5 4, 5%) in the region of the FLT3gene. None of the four samples with 113q had a

FLT3-ITD or FLT3-TKD. Other regions of gain

and loss are listed in Supplementary Table 5 and 6

(see also Supplementary Figs. 2A–2U). All recur-

rent losses or gains identified were in the regions

that have been reported for AML in the Mitelman

Database (http://cgap.nci.nih.gov/Chromosomes/

Mitelman). Besides del(5q) and del(7q), losses at

20q (13% of adverse risk samples), 18q (13%), 8p

(9%), 16q (9%) and gains on 5p (6%) were

observed exclusively while losses at 12p (9%), 17p

(9%), 3p (6%), and 3q (6%) were observed at

increased frequencies in adverse risk samples

(Supplementary Table 4).

Cytogenetic analysis compared with SNP array analysis

A comparison of the most frequent copy number

changes detected using karyotype analysis and

SNP arrays is listed in Supplementary Table 7. Of

the listed 119 events detected by either method,

56% were concordant, 23% were detected by

karyotype only, and 21% by SNP arrays only (dis-

cussed further in supplementary information). Of

the 190 samples classified as normal by karyotype

analysis, abnormalities associated with an adverse

prognosis were detected by SNP arrays in 3 (1 had

del(5q) and 2 had monosomy 7). Furthermore,

using SNP arrays we were able to evaluate copy



number changes in 91 cases where the karyotype

was not available [NDS (sample not available) 569, failed 5 15, incomplete information 5 7]; 56

were normal and 35 showed aberrations with a total

of 15 gains, 39 losses, and 20 aUPDs. Six samples

had abnormalities associated with adverse progno-

sis, 4 had del(5q) (2 failed and 2 NDS on karyotype

analysis), and 2 had monosomy 7 (both NDS).

DISCUSSION

In AML, high levels of mutants in genes like

FLT3 have been shown to be related to worse clini-

cal outcome (Kottaridis et al., 2001; Whitman et

al., 2001; Thiede et al., 2002). Acquired UPD is

one of the mechanisms that can lead to increased

levels of mutant by rendering the cells homozy-

gous for preexisting mutations (Fitzgibbon et al.,

2005; Raghavan et al., 2005) and hence could be

related to clinical outcome. Thus, it is important to

know the regions of aUPD to determine novel

underlying molecular aberrations affecting disease

pathogenesis and treatment outcome. Here, we

have developed a comprehensive map of aUPD in

a large cohort of AML samples. We detected

aUPDs in 17% of the 454 samples and have deter-

mined its frequency on different chromosomes,

the most frequent being on 13q, 11p, and 11q,

confirming previous studies (Gorletta et al., 2005;

Raghavan et al., 2005). In addition, we also identi-

fied novel regions of aUPD at 2p, 17p, 2q, 17q, 1p,

and Xq indicating the existence of unknown muta-

tional targets yet to be discovered. Our previous

analysis using both fluorescent in situ hybridization

and direct sequencing has validated the interpreta-

tion of these array data (Fitzgibbon et al., 2005;

Raghavan et al., 2005). Reproducibility of our data

were confirmed by the identical results in 23

samples for which the experiments were repeated.

The frequency of aUPD in our AML samples

(17%) is far more than that seen in control popula-

tion (3%), which strongly suggests that these are

somatically acquired events as shown earlier (Gor-

letta et al., 2005; Raghavan et al., 2005). The pat-

tern of aUPD reported in this article is distinct

from that identified in other hematological and

solid tumor malignancies (White et al., 1998; Hag-

strom and Dryja, 1999; Shearer et al., 1999; Kra-

lovics et al., 2002; Murthy et al., 2002; Baxter et al.,

2005; James et al., 2005; Kralovics et al., 2005; Lev-

ine et al., 2005; Teh et al., 2005; Gaasenbeek et al.,

2006; Fitzgibbon et al., 2007; Karow et al., 2007;

Kratz et al., 2007; Pfeifer et al., 2007; Purdie et al.,

2007; Stark and Hayward, 2007).

The introduction of an area of aUPD may have a

number of possible consequences. Firstly, as stated

above, it may give rise to homozygosity for a

mutated gene that provides a selection advantage

to the cell such as a proliferative drive or increased

chemoresistance. This is very well exemplified by

our data for FLT3 gene where ITD but not TKD

mutations were observed on all of the samples with

UPD13q in the region of FLT3 gene. FLT3-ITDs

are associated with a poor prognosis, and in some

studies this is limited to patients with a high mu-

tant level indicative of the loss of wild-type alleles

(Kottaridis et al., 2001; Whitman et al., 2001;

Thiede et al., 2002). All samples with a high

(>50%) mutant ITD level in our cohort had chro-

mosome 13 aUPD suggesting that in these cases

UPD arose after the acquisition of FLT3-ITD

mutation. aUPD was also observed in 3 samples

with lower (<50%) level of FLT3-ITDs raising the

possibility that the aUPD was acquired prior to the

FLT3-ITD and therefore there may be other

mutated genes on chromosome 13 that are driving

the selection process. The WT1 gene on 11p is also

in an area of recurrent aUPD and homozygous

mutations of functional significance in this gene

have been reported in AML (Fitzgibbon et al.,

2005; Summers et al., 2007). In one of our studies

(Fitzgibbon et al., 2005) it was shown that of the

three samples with aUPD11p in the region of WT1,a homozygous WT1 mutation was detected in 1 of

the 3 samples (Fitzgibbon et al., 2005), again sug-

gesting that mutations might exist in other genes

within the aUPD region. Although two samples

were observed with aUPD5q in the region of the

NPM1 gene, neither had a mutation in this gene.

The reported NPM1 mutations in AML have been

heterozygous, and its putative function being

involved in the nuclear-cytoplasmic shuttling of

proteins and nucleic acids is thought to require

wild-type NPM1 (Grisendi et al., 2006). It would

therefore be an unlikely target for a homozygous

mutation.

A second possible consequence of aUPD may be

its impact on epigenetic changes. Transcriptional

silencing through methylation is a frequent mecha-

nism by which tumor suppressor genes are inacti-

vated in human cancers (Stebbing et al., 2006) and

it is interesting that a report on global assessment

of methylation targets in de novo AML found

methylation to be overrepresented on both the

arms of chromosome 11 (Rush et al., 2001). It is

possible that epigenetic changes are the events

underlying aUPD11p and aUPD11q in at least few

of our samples. Similarly, aUPD could introduce


736 GUPTA ETAL.

homozygosity for coding polymorphisms (rather

than mutations) with variable functional activity,

such as those in the drug metabolizing enzymes

(Schwahn and Rozen, 2001), or noncoding regula-

tory polymorphisms that result in differential

expression of alleles (Milani et al., 2007) where

acquired homozygosity could lead to haploinsuffi-

ciency or over-expression of critical proteins.

This study also suggests mitotic recombination

to be the major mechanism behind aUPD in AML.

The number of breakpoints through which aUPDs

arise indicates the mechanism that leads to aUPD.

Whole chromosome aUPDs with no breakpoints

may be the result of nondisjunction followed by

duplication or loss during cell division, whereas

those arising from single or double breakpoints

result from mitotic recombination events. Of all of

the 119 aUPDs observed, 87% were due to mitotic

recombination events. The remaining 13% could

be attributed to nondisjunction, 87% of these

being only on chromosome 13.

Copy number loss and aUPD both independ-

ently lead to loss of heterozygosity (LOH) but

result in a difference in gene dosage that may have

different pathological consequences; haploinsuffi-

ciency in the case of copy number loss potentially

coupled with mutation in the remaining allele, and

two copies of a mutant allele in aUPD. In our data,

we observed losses and aUPDs in common regions

at many locations covering genes such as CTNNA1and NPM1 (on chromosome 5), WT1, ATM and

MLL (on chromosome 11), TP53 (on chromosome

17), CEBPA (on chromosome 19), and RUNX1 (on

chromosome 21) (see Supplementary Figs. 2A–

2U). Further work will be required to determine if

LOH per se, at least in few loci, resulting either

from loss or aUPD have same pathological conse-

quences. Studies in chronic lymphocytic leukemia

have shown that homozygous deletions of

MIRN15A/MIRN16-1 at 13q14 are associated with

aUPD13q (Pfeifer et al., 2007; Lehmann et al.,

2008). We did not find any homozygous deletions

at this locus.

For identification of aUPD in a tumor sample,

ideally it should be compared with a germline

DNA obtained from the same individual (matched

reference sample). Matched references allow

unequivocal differentiation of IRH from the

acquired aberrations. A copy-neutral region of

homozygosity observed in the matched reference

indicates an IRH, while such a region when pres-

ent in a tumor sample but missing in matched ref-

erence indicates its acquired nature. In the absence

of matched reference, it is possible that IRHs may

be called as aUPD. In the current study the false

discovery rate for the number of aUPD regions

identified is 3.3%.

The frequency of constitutional UPDs in

healthy individuals is currently not known, apart

from reports of rare sporadic cases (Karanjawala et

al., 2000; O’Keefe et al., 2006; Ting et al., 2006).

The 3.3% of control samples with copy number

neutral IRHs observed could be due to consan-

guinity or linkage disequilibrium of extended hap-

lotypes in these individuals, or may be real aUPD

events. We observed only 5 AML samples, i.e., 1%

of the total cohort, with more than 2 aUPDs.

These multiple aUPDs could be germ-line events

due consanguinity or other reasons defined above,

although, without remission material for compari-

son their acquired nature cannot be excluded.

The incidence of aUPD in this report may be an

underestimate, since we used lower-resolution 10K

arrays. Recently available arrays have 50–200 fold

higher resolution and are capable of identifying

even smaller aberrations. Also, a stringent criterion

of 50/2 (see methods) to define regions of aUPD

could have missed a few smaller regions of aUPD.

In one sample, aUPD on 11q could not be identi-

fied using our criteria of 50/2 but could only be

identified when compared with paired remission

sample. Furthermore, the density of the SNPs on

the arrays used is not uniform across all of the chro-

mosomes and smaller aUPDs in the regions with

low SNP density, for example chromosome 19,

chromosome X or close to centromeres, might not

have been detected. The use of a large set of con-

trols (n 5 90), however, gave us a good estimate of

IRHs in the control population with a similar eth-

nic composition which further gives us confidence

in the regions identified as interstitial aUPDs.

These regions might otherwise have been difficult

to infer in the absence of paired control samples.

In conclusion, our study provides a map of large

aUPDs on a genome-wide basis in a large cohort of

diagnostic AML samples. It confirms and extends

previous studies and shows that aUPDs in AML

are common and nonrandom, the most frequent

being on chromosomes 13, 11p, 11q. Novel regions

of aUPD have been identified at 2p, 17p, 2q, 17q,

1p, and Xq. The aUPDs on 13q and 11p are clearly

associated with underlying mutations as demon-

strated by those in the FLT3 and WT1 (Fitzgibbon

et al., 2005) genes and may, therefore, identify

genes with functional consequences in the hetero-

zygous as well as homozygous state. However, they

do not appear to represent widespread genomic

damage as most were restricted to just one or two



sites in an individual sample. The future challenge

will be to identify the relevant genes and muta-

tions within these areas of aUPD. Furthermore,

the relatively low frequency of aUPDs on a given

chromosomal region suggests that samples from

even larger cohort of patients may be necessary to

determine their prognostic significance.

ACKNOWLEDGMENTS

The authors thank Ian Tomlinson and Richard

S. Houlston for providing the data on 90 controls

from CORGI study, Christine Harrison and Keith

Wheatley for providing the karyotype data, and

Jude Fitzgibbon and Andrew Lister for reading the

manuscript. The authors also thank the staff of the

Medical Oncology laboratory.

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Novel regions of acquired uniparental disomy discovered in acute myeloid leukemia