Affiliations of authors: N. Tripodis, P. Demant (Division of Molecular Genetics, H5), A. A. M. Hart (Division of Radiotherapy), The Netherlands Cancer Institute, Amsterdam; R. J. A. Fijneman, Department of Cell Biology and Immunology, Faculty of Medicine, Vrije Universiteit, Amsterdam.
Correspondence to: Peter Demant, M.D., Ph.D., Division of Molecular Genetics (H5), The Netherlands Cancer Institute, Plesmanlaan 121, 1066CX Amsterdam, The Netherlands (e-mail: demant{at}nki.nl).
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ABSTRACT |
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INTRODUCTION |
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After N-ethyl-N-nitrosourea (ENU) treatment, the lung tumor-susceptible strain O20/A (denoted O20) develops statistically significantly larger tumors than the resistant strain B10.O20/Dem (denoted B10.O20) (5,810). RC strains (O20-congenic-B10.O20/Dem, abbreviated as OcB) have each only a random approximately 12.5% subset of genes derived from the lung tumor-resistant strain B10.O20, yet strains OcB-3, OcB-6, OcB-9, and OcB-16 do not develop statistically significantly larger lung tumors than strain B10.O20 (10). On the other hand, strain OcB-4 is more susceptible and, like strain O20, is statistically significantly different from strain B10.O20. With these five OcB strains, it is possible to screen approximately half of the mouse genome for susceptibility to lung cancer genes. F2 crosses between each of these OcB strains and strain O20 were generated, and linkage analysis of susceptibility to lung cancer was performed. Originally, we mapped 14 lung cancer susceptibility (Sluc) loci (810) in strains OcB-4, OcB-6, and OcB-9 by using the MQM (i.e., multiple-QTL [quantitative trait loci] model)-mapping program (1113). At the present time, higher computing power and advanced statistical packages allow for a more thorough analysis of these crosses. As a result, we now can simultaneously assay the possible main effects and pairwise interactions of markers from almost all segregating segments.
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MATERIALS AND METHODS |
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Strain O20, the H-2 congenic strain B10.O20 that carries the H-2pz haplotype of strain O20 on the C57BL/10 background, and the OcB series of RC strains that consists of 19 homozygous strains are maintained in The Netherlands Cancer Institute, Amsterdam. The mice used in this study (7) were subjected to a strict lightdark regimen and received acidified drinking water and a standard laboratory diet (Hope Farms, Woerden, The Netherlands) ad libitum. F2 crosses were generated between the common background strain O20 and each of the following OcB strains: OcB-3, OcB-4, OcB-6, OcB-9, and OcB-16. At day 18 of gestation, pregnant F1 mice were treated intraperitoneally with 40 mg/kg body weight of ENU, as described previously (8,9). The ENU-treated offspring were killed at 16 weeks of age, and their whole lungs were removed. The animal treatment and the setup of the experiments have been approved by the Animal Experimentation Ethics Committee of The Netherlands Cancer Institute.
Phenotyping and Genotyping
The whole lungs were fixed in AEF solution (i.e., 40% [vol/vol] ethanol, 5% [vol/vol] acetic acid, 4% [vol/vol] formaldehyde, and 0.41% NaCl) and embedded in histowax. The lungs were sectioned semiserially (5-µm sections at 100-µm intervals) and stained with hematoxylineosin. The size of the lung tumor was determined as described previously (8,9). Briefly, the tumor size is the sum of all measured surfaces (calculated with the aid of a grating in the ocular) in the semiserial sections where the tumor is present, and it corresponds to tumor volume. Tumors that did not exceed a diameter of 300 µm in any of the sections were not included in the data (total number of tumors used = 2658). Variation in tumor size within each mouse was quite high in each cross. For example, in the OcB-4 cross, in the same mouse, tumors ranged in size from 8 x 106 µm3 to 1380 x 106 µm3, although, more frequently, the within-mouse tumor size ranged between 6 and 60 x 106 µm3. Histologically, tumors were alveolar, papillary, or, most frequently, mixed alveolar and papillary, with relatively small mitotic figures and varying degrees of heterogeneity. The DNA of the F2 hybrid mice was isolated from their tails and genotyped with simple sequence-length polymorphic markers (Mouse MapPairs; Research Genetics, Huntsville, AL) (9,10). Marker positions are based on Version 3.2 of the mouse genome database (www.informatics.jax.org). The (O20 x OcB-6)F2 cross was used only for confirmation of loci mapped in the other crosses because of its small size (81 F2 mice were used in the analysis). The genomic segments that segregate in each F2 cross were identified previously (14,15).
Statistical Analysis
The chromosomal position of genes affecting tumor size in different chromosomal regions (with the use of individual microsatellite markers) was determined by analysis of variance. The size of the tumors was loge (natural logarithm) transformed (for the purpose of approximation to a normal distribution) and was nested per individual mouse. The effect of each marker, sex, and interactions between pairs (markermarker and markersex) on tumor size was tested by the PROC GLM (general linear models) statement of the SASTM 6.12 for Windows (SAS Institute, Inc., Cary, NC). All statistical tests were two-sided. We use the term "susceptibility" to denote larger tumors and "resistance" to denote smaller tumors. The number of markers as well as sex screened for each F2 cross and the size of each cross are as follows: The OcB-3 cross (130 F2 animals) had seven markers (D1Mit170, D7Mit57, D8Mit3, D10Mit51, D13Mit139, D14Mit120, and D19Mit3); the OcB-4 cross (157 F2 animals) had 15 markers (D1Mit36, D2Mit5, D2Mit56, D4Mit4, D4Mit27, D6Mit158, D8Mit35, D9Mit2, D9Mit12, D10Mit28, D13Mit78, D15Mit13, D15Mit96, D15Nds3, and D18Mit17); the OcB-6 cross (81 F2 animals) had 10 markers (D1Mit16, D2Mit5, D2Mit200, D4Mit23, D4Mit66, Kras2, D12Nds2, D14Mit120, D16Mit9, and D19Mit3); the OcB-9 cross (193 F2 animals) had 13 markers (D2Mit56, D4Mit158, D6Mit218, D7Mit32, D7Nds2, D8Mit3, D10Mit122, D11Mit15, D16Mit9, D18Mit17, D19Mit61, D19Mit9, and D19Mit33); and the OcB-16 cross (169 F2 animals) had 14 markers (D1Mit221, D2Mit200, D4Mit5, D4Mit70, D7Mit55, D7Mit105, D8Mit3, D8Mit15, D10Mit122, D12Nds2, D15Mit13, D15Mit96, D16Mit19, and D18Mit7). Each known segregating segment in each cross is represented by at least one marker (or more if the segment is longer than 20 cM) The OcB-6 cross was used only for confirmation purposes in this study because of its small size.
In each statistical model, we tried to include, in addition to all main effects (typically, approximately 14 markers and sex) from each segregating segment, as many two-way interactions as possible. Since it is not possible to include all two-way interactions in a single model (91 in the case of 14 markers) because of the limiting size of each cross, we first tested the effect of each marker and all of its two-way interactions with all other markers (13 interactions per marker in the case of a total of 14 markers). A backward-elimination procedure was followed to exclude statistically nonsignificant interactions (P>.05). In constructing the test model, typically, the five worst interactions from each marker are excluded, and all remaining interactions together with the main effects of all tested markers are combined. A backward-elimination procedure follows until all remaining pairs have statistical significance below 5%. In certain cases (the OcB-4 and the OcB-16 crosses), because of the large number of tested markers, one (in the OcB-4 cross) or two (in the OcB-16 cross) markers had to be left out when the test model was constructed. Therefore, two overlapping statistical models (in which a randomly selected marker and all of its interactions are substituted by the one left out in the other model) were used for the OcB-4 and three for the OcB-16 cross to have a more complete coverage of all segregating segments and a better representation of all possible interactions. The percentage of explained variance is approximately similar in all crosses (e.g., 39.3% for the OcB-3 cross), as is the goodness of fit (e.g., R2 for the OcB-3 cross is .315).
The calculated P values were then corrected according to a formula recommended by Lander and Kruglyak (16). One of the variables in this formula is the length of the segregating genome. Theoretically, in each cross, approximately 200 cM is segregating (12.5% of the total genome length), but that differs in each OcB strain. To use the appropriate value, we calculated the total length of the segregating segments per OcB strain. For each segregating segment, the extreme pair of markers (one proximal and the other distal) that have a donor allele determines the length of the minimal donor segment. Similarly, the length of the maximal segment is that of the minimal segment plus the distance between the next closest pair of markers (one proximal and the other distal) that has the allele of the background strain. The maximal and minimal segregating donor segment lengths (first and second values, respectively, in centimorgan) per OcB tested are as follows: OcB-3 (183109), OcB-4 (323146), OcB-9 (291168), and OcB-16 (302158). The more stringent maximal values were used in the correction formula (since the corrected P value is proportional to the tested genome length). The number of statistical models performed per cross was also taken into consideration in a final correction by multiplying the corrected P value by the number of models used per cross.
For confirmation, the statistical models included the tested locus and all of the other common loci between the original and the tested cross. One analysis per cross per tested locus was carried out. The pointwise P values from confirmatory analyses are reported as recommended previously (16).
To compare the effect of a to-be-confirmed locus (A) between the cross in which it was originally mapped (the original cross) and the confirmatory cross, we used the following procedure: If locus A is involved in an interaction with locus B, but the interacting locus is not segregating in the confirmatory cross, then all of the mice in this cross are B°/°, i.e., homozygous for the O20 allele. In that case, the weighted mean of the original cross is recalculated only for all mice that have the B°/° genotype, with the use of mendelian frequencies (1 : 2 : 1), and the effect of locus A is then given as a percent difference from this weighted mean (therefore, these values are different from the ones in Table 1, which are derived from the cross mean). This weighted mean is then compared with the effect of locus A in the confirmation cross.
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RESULTS |
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The reliability of the RC strain mapping is shown by our ability to map the same Sluc loci in two or three different RC strains. The Sluc20 locus, found independently in the OcB-9 and OcB-16 crosses, has similar phenotypic effects (in the sense that the same genotypes in the two crosses have effects in the same direction, i.e., that susceptibility and resistance are associated with the same genotypes, although the magnitude of the effect is different) in the two crosses (Table 1; Fig. 2
, A). The Sluc1 locus, originally mapped in the OcB-9 strain (8), was also detected in the OcB-3 (P = .0016) cross, with a consistent association between the genotype and the phenotype (Fig. 2
, B), and in the OcB-6 (P = .0262) cross. Similarly, we confirmed Sluc16 (P = .0025) and Sluc18 (P = .036), both originally detected in the OcB-4 cross, as main effects in the OcB-6 cross but with different genotypephenotype relationships in the two crosses (data not shown). Since these loci are involved in interactions, differences in their effects between crosses may be due to the presence of additional interactions in the confirmatory crosses. The interaction between Sluc5 and Sluc12 that was originally detected in an OcB-6 cross, where the animals were killed after 35 weeks (9), was independently found in the OcB-16 cross (Table 1
). The same genotypes have effects in the same direction in both crosses; e.g., Sluc5b/bSluc12b/b is more resistant than Sluc5b/bSluc12°/° or Sluc5°/°Sluc12b/b, in both crosses (Table 1
) (9).
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DISCUSSION |
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Several Sluc loci (Sluc1, Sluc5, Sluc12, Sluc16, Sluc18, Sluc20, and Sluc26) and interactions (Sluc5 x Sluc12 and Sluc5 x Sluc26) were confirmed in more than one RC strain. Because of the random segmentation of the donor genome in the RC strains, the average estimated length of the Sluc loci candidate regions (± standard deviation) is 15.2 cM (±8.2), and eight of the Sluc loci are mapped in regions of 12 cM or less. These Sluc loci are (maximal region indicated by first number and minimal region indicated by second number): Sluc1 (12 cM9 cM), Sluc3 (12 cM2.8 cM), Sluc4 (12 cM8 cM), Sluc12 (3 cM3 cM), Sluc17 (11.5 cM3 cM), Sluc23 (5 cM3 cM), Sluc26 (11.7 cM1 cM), and Sluc28 (11 cM8 cM). We are currently refining the mapping of the boundaries of the segregating segments of all candidate regions of Sluc loci. In addition, new recombinants are currently being generated and tested, with the aim of further reducing and fine-mapping the candidate regions, thus facilitating loss of heterozygosity studies and direct cloning of these genes. Furthermore, the homologous regions of human chromosomes are also better defined, providing an excellent tool for focused genetic studies in the human population and the cloning of their human counterparts.
Extrapolating the number of Sluc loci to the total mouse genome, we predict approximately 60 (90% confidence interval = 42 to 78) loci and multiple interactions. This number is probably an underestimation of the true number of Sluc loci, since it is derived from a limited number of F2 hybrid mice and a single pair of inbred strains. The high frequency of these interactions suggests the existence of synergic pathways and molecular interactions (e.g., proteinprotein interactions), as well as the existence of higher order interactions. These interactions may play a role in buffering of genetic variation (29) and may be subsets of more complicated functional modules (30).
We show that, despite the apparent complexity of a multigenic trait, with the right choice of genetic and statistical tools, it is possible to detect the relevant loci and their interactions. To our knowledge, this is the first time that a direct calculation of loci involved in a polygenic trait has been performed by systematically screening half of the murine genome. Although the number of these loci is large, new technologies (e.g., single nucleotide polymorphism analysis, complementary DNA arrays) and the sequence of the human and mouse genome and syntenic comparisons between the two will greatly facilitate the identification of these genes. Elucidation of the action of these genes will provide an insight into the molecular mechanisms of tumorigenesis and may serve as a paradigm for other multigenic traits.
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NOTES |
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We thank M. Treur-Mulder and E. Delzenne-Goette (Division of Molecular Genetics, The Netherlands Cancer Institute, Amsterdam) for their excellent technical assistance.
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