Download Complexity of Lung Cancer Modifiers: Mapping of

Complexity of Lung Cancer
Modifiers: Mapping of
Thirty Genes and
Twenty-five Interactions in
Half of the Mouse Genome
Nikos Tripodis, Augustinus A. M.
Hart, Remond J. A. Fijneman,
Peter Demant
Background: Numerous low-penetrance
genes control susceptibility to cancer in
experimental animals, but the overall
genetic information on this group of
genes (i.e., number of loci and their mutual interactions) is missing. We performed a systematic search, scanning
roughly half of the mouse genome for
lung cancer susceptibility (Sluc) genes
affecting tumor size or number by using mouse recombinant congenic (RC)
strains. In each RC strain (OcB), approximately 12.5% of the genome is derived from the lung cancer-resistant
strain B10.O20, whereas the rest is derived from the lung cancer-susceptible
strain O20. Methods: A total of 730 F2
hybrids from five (OcB × O20) crosses
were tested. Pregnant mice were treated
on day 18 of gestation with a single dose
of N-ethyl-N-nitrosourea. When offspring were 16 weeks old, whole lungs
were removed and sectioned semiserially, and the size of all lung tumors
(n = 2658) was determined. Analysis of
variance was used for detection of linkage, and models (including main effect
and two-way interactions) were tested
with a statistical program. Results: We
detected a total of 30 Sluc loci (16 new
plus 14 previously reported) and 25
two-way interactions. Some of these interactions are counteracting (e.g.,
Sluc17 and Sluc20), resulting in the
partial or total masking of the individual independent effect (main effect)
of each involved locus. Seven loci
(Sluc1, Sluc5, Sluc12, Sluc16, Sluc18,
Sluc20, and Sluc26) and two interactions (Sluc5 × Sluc12 and Sluc5 ×
Sluc26) were detected in more than
one RC strain. Conclusions: The extrapolation of our results to the whole
genome suggests approximately 60 Sluc
loci (90% confidence intervals = 42 to
78). Despite the genetic complexity of
lung cancer, use of appropriate map1484 REPORTS
ping strategies can identify a large
number of responsible loci and can reveal their interactions. This study provides an insight into the genetic control
of lung tumorigenesis and may serve as
a paradigm for investigating the genetics of other cancer types. [J Natl Cancer Inst 2001;93:1484–91]
Understanding genetic predisposition
to nonfamilial (sporadic, common) cancer
requires identification of the majority of
involved genes. A recent extensive study
on twins (1) indicated that genetic predisposition is responsible for an unexpectedly large proportion of apparently nonhereditary cancers, supporting the indications
from numerous observations of familial
clustering of specific cancers. This study,
however, also indicated that the relevant
genes do not have a strong effect and
hence are difficult to identify. Lung cancer, the leading cause of cancer deaths
worldwide (2), also exhibits familial clustering both in smokers and in nonsmokers
(3), indicating the involvement of presently unknown genes. The comparison of
a number of inbred mouse strains revealed large differences in susceptibility
to both spontaneous and chemically induced lung tumors and resulted in the
mapping of several susceptibility loci (4–
6) and their mutual interactions. Most of
these susceptibility or modifier loci seem
to influence the “intrinsic” cellular properties, such as growth, invasion, differentiation or vascularization potential or
stimulation to appropriate immune responses, control of genomic stability, and
DNA repair damage rather than carcinogen activation or inactivation (4). Little is
known, however, about the total number
of genes predisposing to lung cancer in
humans or in animals. To estimate this
number, we used the mapping efficiency
of the mouse recombinant congenic (RC)
strains to screen systematically for genes
affecting number and size of lung tumors
in the mouse genome (7–10).
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) (5,8–10). 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, OcB9, 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
(8–10) in strains OcB-4, OcB-6, and
OcB-9 by using the MQM (i.e., multipleQTL [quantitative trait loci] model)mapping program (11–13). 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.
MATERIALS
AND
METHODS
Mice and Carcinogen Treatment
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 light–dark 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.
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@
nki.nl).
See “Notes” following “References.”
© Oxford University Press
Journal of the National Cancer Institute, Vol. 93, No. 19, October 3, 2001
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-␮m sections at 100-␮m intervals)
and stained with hematoxylin–eosin. 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 ␮m 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 × 106 ␮m3 to
1380 × 106 ␮m3, although, more frequently, the
within-mouse tumor size ranged between 6 and 60 ×
106 ␮m3. 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 × 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 (marker–marker and marker–sex) on tumor
size was tested by the PROC GLM (general linear
models) statement of the SAS® 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 backwardelimination 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 (183–109), OcB-4 (323–146), OcB-9
(291–168), and OcB-16 (302–158). 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.
Journal of the National Cancer Institute, Vol. 93, No. 19, October 3, 2001
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.
RESULTS
Using one or more statistical models
per OcB cross to analyze the genetics of
tumor size, we confirmed the previously
detected lung tumor size Sluc loci (8–10)
(data not shown), and we report 16 new
lung cancer susceptibility loci, Sluc15
through Sluc30. All of the loci were detected in pairwise interactions, in which
the effect of each locus depends on the
genotype of the interacting locus (Table
1; Fig. 1, A and B). For example, the
Sluc12b/b (homozygote for the B10.O20
allele) genotype is associated with susceptibility if the genotype at the interacting locus is Sluc22b/b and with resistance
in Sluc22°/° (homozygote for the O20
allele) mice. Thus, the prediction of the
phenotypic effect of a particular locus requires knowledge of any possible interactions that this locus may be involved in
and determination of the allelic status of
the interacting loci. A statistically significant main effect was observed only for
Sluc20 (Table 1).
The magnitude of the effects observed
here is within the range of effects detected
in other studies of mouse lung tumor susceptibility (17–19). Some genotypic combinations are associated with extremely
susceptible phenotypes, such as Sluc5b/b
Sluc25° / °, Sluc9° / °Sluc25° / °, Sluc9 b/ °
Sluc25°/°, Sluc10b/bSluc25°/°, Sluc10°/°
Sluc25°/°, and Sluc18b/bSluc26b/b, which
all result in a greater than fivefold increase in tumor size, compared with the
mean size of the cross, whereas genotypes
Sluc5 b/b Sluc16 b/ °, Sluc5 b/b Sluc25 b/b ,
Sluc5 b/b Sluc25 b/ °, Sluc5 b/ °Sluc25 b/b ,
Sluc5 b/b Sluc26° / °, Sluc9° / °Sluc25 b/b ,
REPORTS 1485
Table 1. Linkage data and estimated effects of the lung cancer susceptibility (Sluc) loci on lung tumor size**
**The data are presented as percent deviations from the mean tumor size of each cross, adjusted for the effect of the remaining markers in the model (least-squares
mean from the SAS output). The loge (i.e., natural logarithm)-transformed means of tumor size for the crosses (± standard deviation) are as follows: OcB-3, 3.15
(±0.69); OcB-4, 2.91 (±0.74); OcB-9, 2.86 (±0.52); and OcB-16, 3.24 (±0.70). Only statistically significant new linkage data are presented. Confirmatory results
are in the text. The genotypes of loci A and B are b/b for homozygotes for the B10.O20 allele, b/o for heterozygotes, and o/o for homozygotes for the O20 allele.
The Sluc2 locus was detected as a main effect dependent on the sex of mice. A statistically significant main effect for Sluc20 was also detected (shown in the last
line). The (OcB × O20)F2 cross, in which loci A and B were detected, is shown in the second to the last column. The final corrected P value given in the last column
was determined according to reference (16) after taking into consideration the number of models used per cross.
*Loci A and B are interacting.
†Effects on female mice.
§Effects on male mice.
Sluc10b/bSluc25b/b, Sluc10b/bSluc25b/°,
and Sluc10°/°Sluc25b/b result in a greater
than fivefold decrease in tumor size
(Table 1). It is interesting that Sluc25 is
1486 REPORTS
frequently involved in the most resistant
(when at least one B10.O20-derived allele
is present) and most susceptible (when
homozygote for the O20 allele) pheno-
types. Importantly, statistically significant
linkage was also found for loci with weak
effects (e.g., Sluc20 main effect), where
the difference between the most extreme
Journal of the National Cancer Institute, Vol. 93, No. 19, October 3, 2001
Fig. 1. Lung cancer susceptibility
(Sluc) loci in the mouse. A) Schematic idiogram of the mouse genome
and the location of the 30 Sluc loci
detected by using the recombinant
congenic strain system. The Kras2
and the H-2 loci are also included.
The average minimal candidate Sluc
locus region (± standard deviation) is
10.5 (±8) cM, and the average maximal region (± standard deviation) is
19.9 (±9.9) cM, and eight of these
Sluc loci are mapped in regions of 12
cM or less. B) Schematic representation of all detected interactions between Sluc loci (numbers correspond
to Sluc locus numbers from Table 1
and from references (8–10). Sluc6,
Sluc8, and Sluc13 (9) (main effect
only) influence the number of lung
tumors, whereas all of the other loci
influence the size of the lung tumors.
The linking lines denote interactions.
phenotypes is as low as 20% of the mean
tumor size of the cross.
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
Journal of the National Cancer Institute, Vol. 93, No. 19, October 3, 2001
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 genoREPORTS 1487
types, 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 genotype–phenotype relationships in the two crosses (data not shown).
Since these loci are involved in interac-
tions, 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).
These confirmatory results not only increase the confidence of mapping but also
reduce the original candidate chromosomal regions by limiting them to the part of
the donor strain segments shared by both
RC strains. If one assumes a single Sluc
locus in the tested regions of chromosome
8, Sluc20 maps in the 25-cM B10.O20derived segregating segment shared by
strains OcB-9 and OcB-16 (Fig. 3, A).
Similarly, the shared segment of chromosome 19 in the OcB-3, OcB-6, and OcB-9
crosses is within the peak of Sluc1 of the
QTL-likelihood plot (8), reducing the
original candidate region (45.8–57.9 cM)
to the length of the common shared segment (8.8–14.3 cM; Fig. 3, B). The lung
Fig. 2. Independent detection and
confirmation of lung cancer susceptibility (Sluc) loci in different OcB F2
crosses. A) Sluc20 was independently detected in the OcB-9 (interacting with Sluc1) and OcB-16 (interacting with Sluc17) crosses. Each
panel shows the phenotypic effect (in
percent difference from the mean of
each cross for the mice that are homozygous for the O20 allele at the
interacting loci) of the Sluc20 genotypes indicated at the top right corner. The left panel shows the effect
of Sluc20 in the OcB-9 cross, in mice
homozygous for the O20 allele at the
interacting locus Sluc1. In this way, it
is possible to compare these effects
with the effects seen in the OcB-16
cross (in the right panel) in mice
homozygous for the O20 allele at the
interacting locus Sluc17. Sluc1, which
interacts with Sluc2 in the OcB-9
cross (8), was confirmed in the
OcB-3 and the OcB-6 crosses (B),
where Sluc2 does not segregate because it is in all of the mice homozygous for the O20 allele. Each panel
shows the phenotypic effect (expressed in percent difference from
the mean of each cross) of the Sluc1
genotypes indicated at the top right
corner. The left panel shows the effect of Sluc1 when the interacting locus Sluc2 is homozygous for the O20
allele (the percent difference from the
mean of the cross was recalculated
only for mice in which the interacting
locus Sluc2 is homozygous for the
O20 allele). The central panel shows
the main effects of Sluc1 in the
OcB-3 cross, and the right panel
shows the main effects of Sluc1 in
the OcB-6 cross.
1488 REPORTS
Journal of the National Cancer Institute, Vol. 93, No. 19, October 3, 2001
Fig. 3. Refinement of mapping of lung cancer susceptibility (Sluc) loci by independent detection or confirmation
in different OcB F2 crosses. In
each chromosome (chr.) idiogram, the maximal B10.O20derived donor (gray and
black), the minimal donor
(black only), and the O20derived background (white)
segments are shown. Representative polymorphic markers that define these regions
are shown over the chromosomes, and the distances between them are indicated at
the bottom in centimorgans
(each group of chromosomes
and segments is drawn to
scale). The abbreviations
“cen” and “tel” indicate the
orientation of the segment in
relation to the centromere and
telomere, respectively. For
the definition of maximal and
minimal segments, see the
“Materials and Methods” section. Chromosome 8 is shown
in the OcB-9 and OcB-16
strains (A). The maximal
common shared segment that
includes the Sluc20 (D8Mit3)
region between the two crosses
is 25 cM. Chromosome 19 is
shown in the OcB-3, OcB-6,
and OcB-9 strains (B). The
Sluc1 (D19Mit9) region is segregating in all three crosses.
The maximal common segregating region between the three
crosses is 14.3 cM, and the
minimal region is 8.8 cM. The
distal part of chromosome 1 is
shown in the OcB-4, OcB-6, and OcB-16 strains (C). The Sluc5 (D1Mit16) region is segregating in the OcB-4 and OcB-6 crosses. Linkage results with marker D1Mit221
in the OcB-16 cross also suggest a Sluc locus in this part of chromosome 1. It is possible that a small as-yet-unidentified segment is shared by all three crosses, carrying
the Sluc5 gene, most likely in the region common to the OcB-4 and OcB-6 strains. Alternatively, Sluc5 and an additional Sluc locus map in distal chromosome 1.
tumor susceptibility locus Pas3 (19) maps
outside the OcB-3 and OcB-6 segregating
segments of chromosome 19, suggesting
the presence of at least two lung cancer
susceptibility loci in this chromosome
(Pas3 proximal and Sluc1 distal).
The distal part of chromosome 1,
where Sluc5 has been mapped previously
(9), interacts with Sluc26 in the OcB-4
and OcB-16 crosses (Table 1) and with
Sluc12 in the OcB-16 and OcB-6 crosses
(9). Possibly, an as-yet-unidentified short
common segment of donor strain origin is
shared between all three strains (Fig. 3,
C), suggesting the involvement of a single
locus, Sluc5, in these interactions; alternatively, the OcB-16 results indicate an
additional Sluc locus. A susceptibility to
the colon cancer locus (Scc3) and a radia-
tion-induced leukemia sensitivity locus
(Ril3) also maps in this region (20,21).
DISCUSSION
We have shown here that susceptibility
to lung cancer is controlled by many
genes, acting either alone or through interactions with other genes. Similar results have been observed in other studies
on tumor susceptibility (17,18,22,23). In
our study and in two previous studies
(8,9), scanning of approximately one half
of the genome with a total of 887 (OcB ×
O20)F2 hybrid mice—730 for lung tumor
size here and 887 for lung tumor number
and size (9)—provided statistically significant evidence for 30 Sluc loci on 17
chromosomes (Fig. 1, A) and the Kras2
Journal of the National Cancer Institute, Vol. 93, No. 19, October 3, 2001
locus on chromosome 6 (9). Perhaps even
more important is the fact that 25 unique
pairwise interlocus interactions were detected (Fig. 1, B). This result is equivalent
to approximately one locus per approximately 29 F2 mice and one interaction per
35 F2 mice. These results are all the more
impressive, considering that all other
mouse lung cancer susceptibility loci
mapped to date (17–19,23–28) required
an excess of 1500 test mice (or about one
statistically significant locus per 133 mice)
and, in those studies, only two interactions were identified (17,18). These results demonstrate the high resolving power
of the RC system. A possible explanation
for the success of this system may be that,
given a complex multigenic trait with numerous interacting loci, it allows the sysREPORTS 1489
tematic testing not only of main effects
but also of a high percentage of all possible two-way interactions with a reasonable number of test animals (e.g., in this
study, there were, on average, 146 animals per F2 cross). In contrast, for crosses
in which the whole genome is segregating, it is practically impossible to systematically scan for interactions (an average
of 14 markers and 91 two-way interactions for an RC cross compared with 80
markers and 3160 two-way interactions
for a cross where the whole genome is
segregating), unless specific selection criteria are applied to study only small subsets of two-way interactions; e.g., Festing
et al. (24) tested for interactions only between markers for which they detected a
statistically significant main effect.
Several Sluc loci (Sluc1, Sluc5, Sluc12,
Sluc16, Sluc18, Sluc20, and Sluc26) and
interactions (Sluc5 × Sluc12 and Sluc5 ×
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 cM–9 cM), Sluc3 (12 cM–2.8 cM),
Sluc4 (12 cM–8 cM), Sluc12 (3 cM–3 cM),
Sluc17 (11.5 cM–3 cM), Sluc23 (5 cM–3
cM), Sluc26 (11.7 cM–1 cM), and Sluc28
(11 cM–8 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 finemapping 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 inter1490 REPORTS
actions (e.g., protein–protein 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
Supported by grant 925-01-01 from the Dutch
Foundation for Scientific Research (Nederlandse
Organisatie voor Wetenschappelijk Onderzoek) and
by contracts CHRXCT930181 and CTBIO-98-0445
from the Commission of European Communities.
We thank M. Treur-Mulder and E. DelzenneGoette (Division of Molecular Genetics, The Netherlands Cancer Institute, Amsterdam) for their excellent technical assistance.
Manuscript received January 29, 2001; revised
July 17, 2001; accepted August 10, 2001.
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