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Carcinogenesis Advance Access originally published online on August 10, 2005
Carcinogenesis 2006 27(2):311-318; doi:10.1093/carcin/bgi207
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Carcinogenesis vol.27 no.2 © Oxford University Press 2005; all rights reserved.

Evidence for complex multigenic inheritance of radiation AML susceptibility in mice revealed using a surrogate phenotypic assay

F. Darakhshan 1, C. Badie, J. Moody, M. Coster, R. Finnon, P. Finnon, A.A. Edwards, M. Szluinska, C.J. Skidmore 1, K. Yoshida 2, R. Ullrich 3, R. Cox and S.D. Bouffler *

Radiation Effects Department, Health Protection Agency, Radiation Protection Division, Chilton, Didcot, Oxfordshire, OX11 0RQ, UK, 1 School of Animal and Microbial Sciences, University of Reading, Whiteknights, PO Box 228, Reading, Berkshire, RG6 6AJ, UK, 2 NIRS, Inage-Ku, Chiba-shi 263, Japan and 3 Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO 80523, USA

* To whom correspondence should be addressed. Tel: +44 1235 822648; Fax: +44 1235 833891; Email: simon.bouffler{at}hpa-rp.org.uk


   Abstract
Top
 Abstract
Introduction
 Materials and methods
 Results
 Discussion
 References
 
The mapping of genes which affect individual cancer risk is an important but complex challenge. A surrogate assay of susceptibility to radiation-induced acute myeloid leukaemia (AML) in the mouse based on chromosomal radiosensitivity has been developed and validated. This assay was applied to the mapping of radiation-induced AML risk modifier loci by association with microsatellite markers. A region on chromosome (chr) 18 with strong association is identified and confirmed by backcross analysis. Additional loci on chrs 8 and 13 show significant association. A key candidate gene Rbbp8 on chr18 is identified. Rbbp8 is shown to be upregulated in response to X-irradiation in the AML sensitive CBA strain but not AML resistant C57BL/6 strain. This study demonstrates the strength of utilizing surrogate endpoints of cancer susceptibility in the mapping of mouse loci and identifies additional loci that may affect radiation cancer risk.

Abbreviations: AML, acute myeloid leukaemia; chr, chromosome; LOH, loss of heterozygosity; Tm, melting temperatures; RT–qPCR, real-time–quantitative PCR; SNP, single nucleotide polymorphism


   Introduction
Top
 Abstract
 Introduction
Materials and methods
 Results
 Discussion
 References
 
Cancer is a disease in which both environmental and inherited factors affect the incidence in individuals and populations. Twin studies have estimated that heritable factors can contribute up to 42% of the risk of spontaneous prostate cancer and perhaps ~20% of leukaemia risk (1). While it is evident that highly penetrant genes contribute significantly to cancer risk in some individuals, e.g. BRCA1 and BRCA2 carriers (2), it is clear that the major proportion of risk in populations is attributable to multiple genes of low penetrance (3,4). The identification of these common but low penetrance susceptibility alleles presents a major challenge in cancer genetics. Modelling studies have indicated that genes of low penetrance may significantly affect the distribution of breast cancer risk in human populations (5) and evidently the individual risk will be influenced. The difficulties in the unambiguous identification of a specific gene as a cancer susceptibility modifier are demonstrated in the recent publication implicating the Aurora 2 encoding Stk6/STK15 as a skin cancer modifier (6). In contrast, identifying genomic regions harbouring cancer risk modifiers is becoming simpler in the mouse (7). Most studies of human cancer susceptibility have focused on spontaneous cancers; however, cancers induced by factors such as ionizing radiation will almost certainly be similarly affected by multiple genetic factors. Studies using experimental animals, mice in particular, are of great importance for identifying modifiers of induced cancer risk.

Ionizing radiation is a human carcinogen (8) and acute myeloid leukaemia (AML) features prominently in the cancers seen in the primary radiation-exposed study population, the Japanese A-bomb survivors (9). For experimental studies, mouse models of radiation-induced AML have been developed (10–12) and one of the most extensively studied of these is the CBA inbred strain (13). In CBA mice AML presents following a mean latent period of ~18 months after a whole body acute X-ray exposure with a maximal incidence of 25–30% at 3 Gy (13). The spontaneous incidence of AML is very low, <1/1000 (14), giving confidence that radiation is the causal agent in the vast majority of tumours studied. Chromosome (chr) 2 deletions are a consistent feature of radiation-induced AMLs in CBA mice (15,16), and the transcription factor Pu.1/Sfpi1 has been identified as a key target gene, one copy of which is lost and the other frequently mutated in radiation AMLs (17). Furthermore, the early induction of elevated frequencies of chr2 aberrations in bone marrow is a feature of the CBA strain, but not the AML resistant strain, C57BL/6 (18). In this paper, the utility of chr2 radiation sensitivity, as a surrogate endpoint for AML sensitivity, has been investigated. All types of aberration were included in the analysis despite the more specific association of chr2 deletions with AML. This approach was selected as certain AMLs present with translocations and some of these evolve into deletions (15,19). Thus, many or all types of chr2 aberrations may be associated with AML. Having established the radiation sensitivity of chr2 in a range of inbred strains of mouse a novel strategy for the mapping of loci controlling this trait was developed. The method is essentially a microsatellite association mapping exercise which exploits the public database of microsatellite polymorphism information (http://www-genome.wi.mit.edu/cgi-bin/mouse/index). In principle this mapping method is analogous to that of Grupe et al. (20) with the exception that microsatellite polymorphisms are exploited rather than single nucleotide polymorphisms (SNPs). Mapping was refined by further microsatellite typing and confirmation sought through a limited backcross analysis.

The picture that emerged from these mapping exercises was that multiple candidate loci controlling chr2/AML sensitivity could be identified and that the allelic influence of individual loci may depend upon other factors in the genetic background of mice. In this respect chr2/AML sensitivity is similar to other mouse cancer susceptibilities (21,22). The most strongly associating locus is located to a ~1.5 Mb region on the proximal region of chr18. Among the candidate genes in this region is Rbbp8 encoding CtIP which appears to play a role in several key cellular functions with relevance to cancer, chief amongst these in the present context is a potential role in chromatin remodelling which might be the basis of the specific radiosensitivity of chr2. The expression of Rbbp8 is differentially regulated in bone marrow cells of the chr2/AML sensitive CBA and chr2/AML resistant strains following in vivo X irradiation.


   Materials and methods
Top
 Abstract
 Introduction
 Materials and methods
Results
 Discussion
 References
 
Mouse strains and irradiation
CBA/H and C3H mice were obtained from MRC, Harwell. Strains DBA/2, A, AKR, C57BL/6, BALB/c, SJL and CBA/Ca were obtained from Harlan SeraLab, Loughborough UK. NOD mice were a gift from Prof. J.Todd, Cambridge Institute for Medical Research, UK. NON and LP were supplied by the Jackson Labs, Bar Harbor, USA. RFM mice were obtained from the colony held at the National Institute for Radiological Sciences, Chiba Japan. The experiments on mice that were carried out in the USA and Japan were performed in the respective countries according to institutional and national guidelines. All other animal procedures conformed to the UK Animals (Scientific Procedures) Act, 1986 and were conducted under project licences PPL 30/1169 and PPL 30/1782. Mice were irradiated with a standard whole body 3 Gy dose of 250 KVp X-rays at a dose rate of 0.5–1 Gy/min.

Cytogenetic procedures
Direct bone marrow metaphase chromosome preparations were made from unirradiated controls and irradiated mice at 24 h post-irradiation as detailed in Bouffler et al. (18). For inbred strains and F1 hybrids 3–5 mice were sampled. Chromosome painting by fluorescence in situ hybridization (FISH) of chrs 1, 2 and 3 was performed by one of the three procedures. Originally a standard single colour FISH protocol (18) was employed. This was superseded by single colour FISH with tyramide detection. This latter method followed similar pre-hybridization and hybridization steps as the standard protocol with the exception that only 2 µl of the probe diluted in the hybridization buffer was used. Washing also followed the standard protocol. For detection the TSA system kit (NEN Life Sciences, Beaconsfield, UK) was used in accordance with the manufacturer's recommendations, following an initial incubation of slides for 30 min at 37°C with 1:200 diluted rabbit anti-FITC conjugated with horse radish peroxidase (DAKO, Ely, UK). Latterly a three colour FISH protocol was used (23).

Aberrations were scored in painted chromosomes using a system similar to that of Tucker et al. (24), i.e. each colour junction between painted and unpainted (or between differently painted) chromosomes scored 1. All types of aberration yielding colour junctions were scored (translocations, insertions, dicentrics, multi-coloured fragments and chromatid exchanges). In addition where there was a distinct length difference between homologous chromosomes (~25%) a score of 1 was recorded, these were assumed to be deletions. A few intra-homologue aberrations were observed, where this was unequivocal those ‘junctions’ were also scored. The number of colour junctions for each chromosome was enumerated separately. Care was taken to ensure that the scoring system was consistent between the single colour and multi-colour FISH protocols. For the statistical analysis of heterogeneity in aberration score between chromosomes {chi}2-tests were employed. The distribution of aberrations among cells was analysed using a dispersion index test (25) and any overdispersion of aberrations among cells was factored into the {chi}2-tests.

Computer comparison of microsatellite sizes
Initial mapping of candidate loci exploited the publicly available microsatellite polymorphism data (http://www-genome.wi.mit.edu/cgi-bin/mouse/index). Whole genome data from release 16 was downloaded into Excel files. The logical operators of Excel were used to identify microsatellite loci where strains of one phenotypic group had identical size and strains of the other phenotypic group had a divergent microsatellite size.

Genotyping
DNA was extracted from spleens by proteinase K/RNase digestion followed by phenol–chloroform extraction (inbred strains and F1 hybrids) and ear clips (backcross mice). Microsatellite sizes were analysed following PCR amplification using MapPairs primers (Research Genetics, Paisley, UK) as described previously (26). PCR products were separated on 3% w/v agarose or 8% acrylamide gels. DNA run on acrylamide gels was stained with SYBR Green I (Molecular Probes, Paisley, UK).

The strength of statistical association between genotype and phenotype was determined using Fisher's exact tests as previously described (27).

Quantitative PCR analysis
RNA was extracted from the bone marrow of mice exposed to 3 Gy X-rays in vivo at 1–24 h post-exposure. Duplicate CBA/H and C57BL/6 mice were used at each time point. Expression of Rbbp8 was investigated by real-time–quantitative PCR (RT–qPCR) using an iCycler iQ (Bio-Rad, Hemel Hempstead, UK) and iQ SYBR Green supermix with fluorescein (Bio-Rad). Hprt and Cables-1 were used as reference genes as their expression was expected to be comparable with Rbbp8 (28,29) (www.ncbi.nlm.nih.gov/UniGene). This was confirmed using experiments comparing the baseline expression levels of ß-actin, Gapdh and Hprt. Hprt expression was most similar to that of Rbbp8. As Cables-1 locates adjacent to Rbbp8 on chr18 (Figure 2) it was also a reference for possible common cis-acting promotor mechanisms. Primer pair design was aided by Primer3 (30) (http://frodo.wi.mit.edu) and primers were selected to span cDNA exon–exon junctions and have similar melting temperatures (Tm). These were demonstrated to amplify from cDNA only and an optimum Tm was established from gradient experiments (data not shown). Primer sequences are shown in Table I. A 25 µl reaction volume was used, and 40 cycles of a three step amplification reaction were employed (95°C 5 min; 40x (95°C 15 s, 57°C 30 s and 72°C 30 s); 95°C 1 min). This was followed by an 80 step melt curve analysis from 55 to 95°C to confirm amplification specificity. Samples were analysed in triplicate and a 10x dilution series using Rbbp8 primers and the Rbbp8 PCR product as target monitored reaction dynamics across the range from 6 x 102 to 6 x 108 copies. Efficiency of target amplification and reference amplification were equal over a 100-fold concentration range. Data analysis was performed using a Microsoft Excel Macro implementation (Bio-Rad) of algorithms outlined by Vandesompele et al. (31).


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  		Table I. Primer sequences used for quantitative PCR analysis

 

   Results
Top
 Abstract
 Introduction
 Materials and methods
 Results
Discussion
 References
 
Radiation-induced chromosome aberration analysis
Aberration scores for chrs 1, 2 and 3 observed in bone marrow cells from 12 inbred strains of mouse 24 h following in vivo 3 Gy X-irradiation are given in Table II. Chromosome aberrations were very rare in unirradiated control bone marrow samples. Control aberration scores for all strains were 0 apart from AKR and DBA/2, where scores of 1 in 900 and 300 cells, respectively, were recorded. The results presented in Table II confirm and extend previous findings (18). Aberration scores in chrs 1, 2 and 3 were statistically indistinguishable in strains C57BL, NON, NOD, A, AKR and DBA/2. However in strains BALB/c, CBA/H, CBA/Ca, SJL, LP, C3H and RFM significantly higher scores were observed in chr2 by comparison with chrs 1 and 3. This is reflected in the chr2 sensitivity ratio, where ratios of ~1 imply equi-sensitive chromosomes while ratios of ≥1.45 indicate chr2 sensitivity. The majority of the strains in the chr2 sensitive group are known to be sensitive to the induction of AML by radiation. Radiation-induced AML has been documented in CBA/H and CBA/Ca (32,33), C3H (11), RFM (34), SJL (35) and BALB/c (36). In contrast radiation-induced AML has not been reported for any of the strains in the non-chr2 sensitive group. Thus the relative frequency of chromosomal aberrations scored in bone marrow cells 24 h following 3 Gy in vivo X-irradiation appears to be a valid surrogate for AML sensitivity. These data additionally predict that LP should be sensitive to the induction of AML.


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  		Table II. Variation in 3 Gy X-ray induced chromosome aberration scores for inbred strains and F1 hybrids between C57BL and CBA/H

 
Aberration scores averaged over the three chromosomes also showed substantial variation, compare for example C57BL/6 and A with NOD and CBA/H. This characteristic is not another reflection of chr2 sensitivity as high scoring non-chr2 sensitivities were identified (NOD for example), as were low scoring chr2 sensitivities (RFM for example). This characteristic of overall chromosomal radiation sensitivity is the subject of further investigation.

In the F1 reciprocal crosses between C57BL/6 and CBA/H (CBB6F1, B6CBF1) chr2 sensitivity appears to act as an at least partially dominant genetic trait with no clear evidence of differential inheritance from male or female (Table II). AMLs can be induced in C57BL x CBA hybrids, albeit at a somewhat lower frequency than in the inbred CBA parent (37). Thus the behaviour of F1 hybrids in terms of radiation AML sensitivity and chr2 sensitivity are consistent.

Mapping by association with microsatellites
The initial mapping strategy adopted to identify candidate regions associated with chr2/AML sensitivity exploited the publicly available microsatellite data for inbred mouse strains. Given the origins of laboratory mouse strains (38) it was predicted that genome regions harbouring chr2/AML sensitivity candidate genes would share common microsatellite alleles in the chr2/AML sensitive strains and the microsatellite alleles at these locations would be divergent in strains of dissimilar phenotype. Microsatellite allele comparisons were carried out by the computer-based analysis of mouse microsatellite data provided at http://www-genome.wi.mit.edu/cgi-bin/mouse/index. In principle this approach is analagous to that adopted by Grupe et al. (20) but using microsatellite variation rather than SNP variation. Initial tests of the validity of the method were carried out, which involved attempting to predict the locations of the mouse coat colour genes agouti, brown and albino. Taking the observable coat colours of strains A, AKR, BALB/c, C3H, C57BL/6, DBA/2 and LP and what may be readily inferred of hidden coat colour genes through standard crosses with tester strains, the strains were grouped according to status at the agouti (a), brown (b) and albino (c) loci. Computer comparison of microsatellite alleles was then carried out for each locus searching for microsatellite loci where strains within one group carried an identical allele that was different in all members of the other group. For each of the coat colour loci 3–6 clusters of microsatellite loci fitting the criteria were identified along with several more dispersed individual microsatellite loci. In each case a region spanning ~2–3 cM, including the locus under investigation plus 2–5 false positives, was identified. Thus, even with a limited number of strains, this approach appeared to be successful in reducing significantly the portion of the genome in which it would be necessary to search for the genes of interest. The false positives require that an independent confirmation will be required in situations where new loci are being identified and mapped. With this caveat in mind, this approach was applied to the chr2/AML sensitivity dataset. Of the 12 strains for which phenotype information had been obtained, the whole genome microsatellite data were available for 9 (A, AKR, BALB/c, C3H, C57BL/6, DBA/2, LP, NOD and NON). These nine strains were grouped in terms of chr2 sensitivity (Table II). Thus the chr2 sensitive group consisted of C3H, BALB/c and LP, while A, AKR, C57BL/6, DBA, NOD and NON comprised the non-sensitive chr2 resistant group. Computer comparisons of microsatellite alleles between and within these groups were carried out requiring loci identical within but divergent between each group to be identified. The microsatellite loci highlighted in this way are given in Table III.


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  		Table III. Microsatellite loci identified by initial comparisons based on chr2 sensitivity phenotype grouping

 
Following these initial ‘in silico’ comparisons, microsatellite typing of the strains not represented in the MIT/WIGR database (CBA, SJL, RFM) was carried out for the loci given in Table II. At this time all inbred strains were genotyped at these loci to eliminate any confounding due to variation in allele size between that quoted in the database and that in the strains actually used in this study. Results are given in Table IV. Manenti et al. (27) recommend that a Fisher's Exact Test –log P-value of >2 be taken as an indication of a significant association between a marker and the phenotype. Under this criterion, the most significantly associating region was found to be on chr18, apparently centring on D18Mit146. A more detailed screen of markers in this region of chr18 confirmed that the association was strongest around D18Mit146 and D18Mit67 (Figure 1). Fisher's test –logP-values suggestive of the association were also obtained for D3Mit319, D4Mit248 and D8Mit178 (Table IV). Several discrepancies in allele size between the MIT/WIGR database and the strains type tested here were noted, most dramatically for D1Mit304, which did not appear to be polymorphic in the animals tested here. For those markers most strongly associating (D18MIT146 and D18MIT67) either a unique allele associating with AML resistance that is larger than alleles in the AML sensitive group or the allele sizes associating with resistance are all smaller than the alleles found in the sensitive group. Thus there is a size relationship between alleles within phenotypic groups. This is expected from the probable evolutionary relationships between large and small alleles.


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  		Table IV. Experimentally determined microsatellite allele sizes at candidate loci and strength of association with the phenotype

 

Figure 1
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  		Fig. 1. Partial map of chr 18 showing markers checked for association with chr2/AML sensitivity, strength of association (Fisher's exact test –log P-value) and associating alleles. Map information was taken from www.ncbi.nlm.nih.gov.

 
Backcross analysis
In an attempt to seek confirmation of the above mapping exercise, a limited (CBA/Ca x C57BL/6) x C57BL/6 backcross analysis was carried out. A total of 36 first and second generation backcross mice were phenotyped and then genotyped for the chr18 region. The range of chr2 sensitivity ratios in these mice was 0.43–2.4. Using the criterion of a chr2 sensitivity ratio of ≥1.45, indicating the sensitive phenotype, 8 mice were classified as chr2 sensitive and the remaining 28 as chr2 resistant. Of the 8 sensitive mice 7 were homozygous for C57BL/6 alleles in the chr18 region, while 11 of the 28 chr2 resistant mice were C57BL/6 homozygotes for the D18Mit markers. A Fisher's exact test of association between the D18Mit markers and the sensitive phenotype gives a –log P-value of 1.7, which is a significant association on the basis of the definitions proposed by the Complex Traits Consortium (39). Unlike the previous analysis using inter-strain comparison, in this case the C57BL/6 alleles appear to associate with chr2 sensitivity. Genotyping for the other markers identified in the previous analysis (Table IV) in 22 first generation backcross mice did not identify any regions with a stronger association. However, –log P-values suggestive of significant association were found for D8Mit178 (–log P-value of 1.44) and for D13Mit23 (–log P-value of 1.21).

While the finding of apparently differing allelic influences of the chr18 region on chr2/AML sensitivity using the two approaches is surprising, it is not without precedent. Tripodis et al. (21) identified 30 modifier loci of chemically-induced lung carcinogenesis and the allelic influence of many of these was found to be dependent on the genotype of another locus. Thus, the same genotype was found to be associated with resistance in one case and susceptibility in another, depending upon the genotype at another locus.

Chr18 loss of heterozygosity in AMLs
Loss of heterozygosity (LOH) for the chr18 region was investigated in AMLs. In some circumstances cancer risk modifiers are frequently lost in the tumours to which they predispose (7). DNAs from 22 AMLs induced by X-irradiation of F1 hybrid mice (28,37) were examined for LOH at the chr18 markers shown in Figure 1. No evidence of LOH was obtained (data not shown).

Identification of candidate genes in the chr18 region and the homologous human region
Given the evidence from two independent approaches that the region on chr18 around markers D18Mit146 and D18Mit67 influences chr2/AML sensitivity, known or predicted candidate genes mapping to the region were identified from the NCBI, Ensembl and UCSC mouse map viewers (Figure 2). This region of the mouse chr18 is syntenic with human 18q11. This region has been identified as being involved in structural aberrations in 322 cases of cancer (http://cgap.nci.nih.gov/Chromosomes/RecurrentAberrations), and amongst these are 24 cases of AML and 12 cases of refractory anaemia.


Figure 2
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  		Fig. 2. Simplified scheme showing some of the known and predicted genes locating to the chr18 region harbouring a chr2/AML sensitivity gene.

 
While several of the known or predicted genes within this region might be associated with cancer susceptibility, Rbbp8 (retinoblastoma binding protein 8, also known as CtIP, CTBP interacting protein) is a particularly strong candidate. It has been proposed that the chr2 sensitivity phenotype is driven by chromatin structural features specific to the chr2/AML sensitive strains (40). Rbbp8 is implicated in chromatin remodelling through its interaction with Brca1 (41). Furthermore Rbbp8 is phosphorylated by ATM following an ionizing radiation exposure of human cells (42) and this phosphorylation depends upon BRCA1 (43). Indirectly Rbbp8 may influence chromatin due to both Rbbp8 and polycomb proteins Pc1 and Pc2 interacting with C-terminal binding protein 1, CTBP1 (44,45).

Quantitative PCR analysis demonstrates that Rbbp8 expression in bone marrow is upregulated in response to in vivo X-irradiation in CBA mice. This upregulation persists for a period of 2 h. It is over time-scales of this order that chromosomal aberrations form. In contrast no upregulation of Rbbp8 is observed in C57BL/6 over the same time course. Thus differential Rbbp8 expression in response to radiation may underlie the phenotype described and lends further support to the potential involvement of Rbbp8: it should be noted that the expression of Cables-1 is not affected by irradiation of either of the mouse strains. Therefore it is unlikely that there are common cis-acting promotor mechanisms acting in this region of chr18.

Candidate genes in other chromosomal regions
The inbred strain and backcross analyses identified associations between chr2 sensitivity and markers on chrs 3, 4, 8 and 13 in addition to chr18. Genomic and DNA sequence databases were screened for candidate genes and human orthologous regions were identified. These are given in Table V. It is notable that all human orthologous cytogenetic regions are recorded as having involvement in AML. This is most notable for the chr8 region. Additionally most of the identified regions carry reasonable candidate genes for involvement in susceptibility and oncogenesis. Perhaps the most striking gene in the current context is Nsd1 (Nuclear receptor binding Su-var, Enhancer of zeste and trithorax domain protein 1), which was identified by virtue of involvement in a t(5;11) in childhood AML (46,47). The protein is involved in transcriptional regulation through interaction with the ligand binding domain of the androgen receptor (48), possibly through chromatin structural modification. Further analysis will be required to identify definitively the genes involved in chr2/AML sensitivity in the identified chromosomal regions.


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  		Table V. Human orthologous regions, AML involvement and candidate genes for regions of interest

 

   Discussion
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
References
 
The identification of loci which modify individual susceptibility is a key challenge in cancer research. Genetic factors have been estimated to account for up to ~40% of individual risk for a variety of sporadic cancer types (1,49). Modelling studies suggest that cancers develop predominantly in genetically predisposed individuals. Pharoah et al. (5) estimate that ~50% of sporadic breast cancers develop in the most susceptible 12.5% of women and 80% of these tumours will occur in the most susceptible 50% of the female population. These and several other lines of evidence point to a major role of multiple cancer risk modifying genes of relatively low penetrance acting together to determine individual risk. Experimental animal studies have a major role to play in identifying these many cancer risk modifiers and increasingly sophisticated tools are available for this purpose (7). Recently the first successful application of the haplotype analysis in identifying a cancer risk modifier in human and mouse skin has been published (6).

Mouse models of the radiation-associated haematological malignancy, AML, are available and inter-strain variation in susceptibility to radiation-induced AML is apparent. In this study, this inter-strain variation in AML susceptibility has been exploited to map candidate modifier loci by genetic association analysis. Previous work suggested that AML sensitive CBA/H mouse bone marrow cells carried higher than expected burdens of chr2 aberrations in comparison with aberrations on chrs 1 and 3 shortly after whole body X-ray exposure (18). In contrast, this phenotype is not observed in the AML-resistant C57BL/6 inbred strain. A more complete survey of the correlation between AML susceptibility and bone marrow cell chr2 sensitivity is reported here. All known AML sensitive strains also expressed the chr2 sensitivity phenotype, while known AML resistant strains did not. Thus, the chr2 sensitivity assay is a valid surrogate for AML susceptibility.

Genome-wide comparison of polymorphic microsatellite loci was exploited as a method for genetic association. The easy availability of datasets make this an attractive and accessible method. The principle of this method is essentially the same as that described by Grupe et al. (20) for SNP/phenotype association. The ancestory of laboratory mouse inbred strains does not favour the use of SNPs for such association studies due to the presence of a mosaic high/low SNP structure (50). Testing of the microsatellite association method with known mapped colour coat phenotypes/genes suggested that the method is capable of reducing the proportion of the genome that requires a detailed analysis for identifying the genes of interest.

Using the microsatellite association method, a primary computer-based screen, including the strains for which allele size information is available (C57BL/6, A, AKR, DBA, NOD, NON, C3H, BALB/c and LP), identified potential regions of interest identified on chrs 1, 2, 3, 4, 5, 8, 11, 13 and 18 (Table III). The addition of new data on microsatellite allele sizes from strains CBA, SJL and RFM indicated strongest association in the D18Mit146-D18Mit229 region. The –log P-value from Fisher's exact tests approached 3 for D18Mit146, a highly significant association (P < 0.001) as defined by the Complex Trait Consortium (39). Regions identified on chrs 3, 4 and 8 reached the level of significant association (i.e. P < 0.05 or –log P-value >1.3). Using a backcross mapping strategy and AML incidence as a phenotype Boulton et al. (51) identified significant associations between AML susceptibility and regions in chrs 1, 2, 4, 6 and 13. Thus there is partial overlap between the chromosomes identified as harbouring AML modifiers in the present study and those identified in the previous investigation of radiation-induced AML modifiers. In the Boulton et al. (51) study the chrs 1 and 6 regions were the most strongly associated. Despite some concordance of the chromosomes implicated in harbouring modifiers in the two studies, the distances between peak associated markers is large, except in the case of chr13, where markers are separated by ~5 Mb.

Notwithstanding the differences in associated regions identified in the present study and that of Boulton et al. (51) both come to the similar conclusion that multiple loci influence radiation AML susceptibility. The difficulties of interpretation of studies with similar aims identifying different regions are widely recognized (39). The finding that multiple loci affect radiation AML/chr2 sensitivity is not surprising in the light of the extensive Tripodis et al. (21) study of modifiers of chemically-induced mouse lung carcinogenesis, which estimated 60 genes influencing susceptibility. Tripodis et al. (21) also found that modifiers could exert opposing phenotypic effect depending on genetic background. A similar phenomenon was observed in the present study for the chr18 region. Furthermore, similar phenomena were reported for the AML susceptibility loci previously reported (51). In the limited backcross experiments, C57BL/6 alleles associated with chr2 sensitivity. Fisher's tests indicated significant association (–log P = 1.7) for the chr18 region. Confirmation of significant association at the chrs 8 and 13 loci was also obtained (–log P = 1.44 and 1.21, respectively).

The absence of LOH in the chr18 region in radiation-induced AMLs suggests that susceptibility is conferred by a mechanism distinct from that operating in familial retinoblastoma, for example. In such a situation, high frequency LOH of one allele would be predicted. As this is not observed the locus must be acting on other target genes or regions.

Within the chr18 region of interest, Rbbp8 stands out as a key candidate gene. This gene encodes CtIP, the CtBP interacting protein. CtIP interacts with multiple protein partners, such as CtBP (52), Brca 1 (42), Ikaros (53) and Rb (54). CtIP has been suggested to act as a tumour suppressor in pancreatic cells (41), and the human Rbbp8 encoding chromosomal segment is lost or altered in cancers including AML and refractory anaemia (http://cgap.nci.nih.gov/Chromosomes/RecurrrentAberrations). The mouse Rbbp8 gene reacts differentially to radiation in bone marrow cells from the AML sensitive CBA strain and the AML resistant C57BL/6 strain (Figure 3). Rbbp8 is upregulated uniquely in CBA mouse bone marrow at 1–2 h post-3 Gy whole body X-irradiation. It is over time-scales of this order that chromosomal aberrations form. This provides evidence of a difference in response of Rbbp8 in AML sensitive and resistant strains thus supporting the involvement of Rbbp8 in post-irradiation chr2 sensitivity and possibly AML sensitivity. Evidently further work is required to confirm this suggestion.


Figure 3
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  		Fig. 3. Quantitative PCR analysis of Rbbp8 (shaded bars) and Cables-1 (clear bars) expression in CBA (upper panel) and C57BL/6 (lower panel) mouse bone marrow cells. Two mice of each strain were irradiated with 3 Gy X-rays in vivo and samples taken at 1–24 h. Expression levels in each sample were assessed in triplicate. Bars represent the means obtained from the two independent animals ± standard errors.

 
Each of the other chromosomal regions identified in the present mapping study gain support for an involvement in AML susceptibility by virtue of the human orthologous regions involvement in somatic rearrangements in AML (Table V). Genomic database analysis allows the identification of potential candidate genes within the regions of association. Credible candidates can be identified but significant effort will be required to provide direct evidence for involvement.

Boulton et al. (51) suggest that the haemopoietic stem cell regulator Scfr1 located on chr1 may represent a key radiation AML modifier. Evidently, alterations in stem cell number will influence susceptibility. The present study suggests that early acting factors which determine the nature of genetic rearrangements following DNA damage might also play a role. Previous work on AML chr2 breakpoints revealed strong breakpoint clustering (40) and the genomic architecture of the region suggested a role of chromatin remodelling in determining the breakpoint clustering. Formal testing of the direct radiation sensitivity of this site is required. However, a model may be suggested in which strain-specific variation in chr2 chromatin structure driven by CtIP or interacting factors modifies radiation AML risk in mouse. The identification of the human orthologous region, 18q11, as being involved in human AML raises the possibility of similar mechanisms acting in humans.

The data presented here serve to highlight the complexity of the genetics of AML susceptibility. The use of a surrogate endpoint for AML susceptibility, chr2 sensitivity, allowed a more rapid phenotype analysis. An additional advantage is the reduction in the experimental animal numbers required. Microsatellite association is also shown to be a valid and simple method to map to a crude scale at least cancer risk modifier loci and indeed any other quantitative trait loci.


   Acknowledgments
 
The authors thank Graham Bailey for assisting with statistical analyses. The authors are grateful to Prof. John Todd for providing NOD mice and MRC, Harwell for use of radiation facilities. This work was funded by EU contracts MAGELLANS (FIGH-CT-1999-00035) and RISC-RAD (FI6R-CT-2003-508842). F.D. was supported by an extra-mural research grant to the University of Reading from the National Radiological Protection Board.

Conflict of Interest Statement: None declared.


   References
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 

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Received December 24, 2004; revised August 1, 2005; accepted August 2, 2005.


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