Download Sleeping beauty: a novel cancer gene discovery tool

Human Molecular Genetics, 2006, Vol. 15, Review Issue 1
doi:10.1093/hmg/ddl061
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Sleeping beauty: a novel cancer gene
discovery tool
Adam J. Dupuy, Nancy A. Jenkins and Neal G. Copeland*
Mouse Cancer Genetics Program, Center for Cancer Research, National Cancer Institute, Frederick, MD 21702, USA
Received February 1, 2006; Revised March 2, 2006; Accepted March 10, 2006
The National Cancer Institute and the National Human Genome Research Institute recently announced a
3-year 100-million-dollar pilot study to use large-scale resequencing of genes in human tumors to identify
new cancer genes. The hope is that some of these genes can be used as drug targets for developing
better therapeutics for treating cancer. Although this effort will identify new cancer genes, it could be
made more efficient by preferentially resequencing genes identified as novel candidate cancer genes in
animal models of cancer. Although retroviral insertional mutagenesis has proven to be an effective tool
for identifying novel cancer genes in the mouse, these studies are limited by the fact that retroviral mutagenesis primarily induces hematopoietic and mammary cancer, but little else, while the majority of cancers
affecting humans are solid tumors. Recently, two groups have shown that sleeping beauty (SB) transposonbased insertional mutagenesis can also identify novel candidate cancer genes in the mouse. Unlike retroviral
infection, SB transposition can be controlled to mutagenize any target tissue and thus potentially induce
many different kinds of cancer, including solid tumors. SB transposition in animal models of cancer could
therefore greatly facilitate the identification of novel human cancer genes and the development of better
cancer therapies.
INTRODUCTION
It has been over 20 years since the discovery of cellular
oncogenes confirmed the genetic basis for cancer (1). Since
this time the study of cancer genes has grown significantly
in complexity. We now know that the majority of human
cancer develops after a cell acquires loss-of-function
mutations in tumor suppressor genes and gain-of-function
mutations in oncogenes (2). Current estimates suggest that
it may require as many as five or six such mutations acting
together to transform the cell (3,4). In addition, so-called
‘epigenetic’ changes, alterations of gene expression because
of chromatin modifications instead of mutation, are common
in most human cancers. Overlapping but distinct sets of
genes seem to be targeted by genetic and epigenetic alterations
in cancer (5). Taken together these findings demonstrate the
genetic complexity found in human cancer.
Recent advances in cancer therapeutics have shown that our
knowledge of cancer genetics can be directly translated into
improved cancer treatments. Herceptin (trastuzumab) is an
antibody that binds to and inhibits the Her2 receptor
encoded by the ERBB2 gene frequently amplified in breast
cancer (6). Gleevec (imatinib) is a tyrosine kinase inhibitor
that has shown to be effective in treating chronic myelogenous
leukemia (CML) as well as gastrointestinal stromal tumors
(GISTs), both of which are known to frequently harbor activating mutations in ABL and PDGFR tyrosine kinases (7,8).
Finally, Iressa (gefitinib) is another tyrosine kinase inhibitor
that blocks the activity of the EGF receptor often amplified
in non-small-cell lung cancer (NSCLC) (9). These new targeted therapeutics have a range of activity from increased
patient survival to clinical remission. Although these results
are very encouraging, some patients do not respond to these
drugs, and other responsive patients relapse after the tumor
develops resistance to the drug (10 –13). Nonetheless, these
studies demonstrate the effectiveness of using targeted therapeutics in cancer treatment. These treatment strategies could
be improved and new drugs developed through a better understanding of cancer genetics to identify better drug targets.
Despite advances in technology, the identification of cancer
genes is still a slow and laborious process. Gene expression
arrays allow for rapid assessment of transcript levels of thousands of genes simultaneously. Although gene expression profiling has made many correlative studies possible, it cannot be
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used efficiently to identify mutations found within the genome
of a tumor cell (14). Comparative genome hybridization
(CGH) can be used to rapidly identify large-scale chromatin
rearrangements (i.e. deletions, amplifications, etc.) in tumor
cells but cannot be used to determine which gene or genes
in these regions contribute to transformation (15). Recently,
the Human Cancer Genome Project has been initiated to
utilize large-scale genome sequencing to sequence the
genomes of tumors in an effort to identify new cancer genes
(http://www.genome.gov/Pages/About/NACHGR/May2005
NACHGRAgenda/ReportoftheWorkingGrouponBiomedical
Technology.pdf ). Although this effort will identify new
cancer genes, it could be made more efficient by sequencing
genes identified as candidate cancer genes in animal models
of cancer. In addition, the Human Cancer Genome Project
will likely identify many genetic alterations of undetermined
significance. These will need to be complemented by reverse
or forward genetic approaches.
IDENTIFICATION OF NOVEL CANCER GENES
The most common animal model used to study cancer is the
mouse. Two general strategies have typically been used for
identifying cancer genes in the mouse. The first involves generating engineered alleles (i.e. transgenic/knockout alleles) in
the mouse germline to either inactivate a candidate tumor
suppressor gene or introducing a transgene to overexpress a
candidate oncogene to determine if specific mutations cause
cancer. The second approach utilizes retroviral insertional
mutagenesis to induce tumors in mice. Both strategies have
been used successfully to identify new cancer genes, but
each presents a unique set of obstacles.
Generating transgenic or knockout alleles is perhaps the
most direct approach to determine the oncogenic potential of
candidate genes. The validity of these models is a continuing
source of concern, especially early models in which a candidate tumor suppressor was deleted in every cell of the
mouse or a candidate oncogene was ubiquitously overexpressed (16). These situations are atypical in human
cancer where tumor cells harboring mutations are surrounded
by wild-type cells. This problem is beginning to be addressed
through the use of the Cre/loxP system to generate spatially
and temporally induced mutations (17). Even with these
improvements, engineered alleles present several challenges.
First, generating tumors in mice often requires two or more
engineered mutations. This requires complex breeding
schemes that make these experiments time-consuming and
expensive. For this reason, engineered alleles are more often
used to validate candidate cancer genes whose role in cancer
is already implicated but rarely to identify novel cancer genes.
The second approach to inducing tumors in mice is more
often used to identify novel cancer genes. Retroviruses such
as the mouse mammary tumor virus (MMTV) and the
murine leukemia virus (MuLV) do not encode genes that are
acutely transforming. Instead these viruses introduce insertional mutations when they integrate into a host cell chromosome as a provirus. Integrated proviruses can introduce both
gain-of-function and loss-of-function mutations thus activating oncogenes or inactivating tumor suppressor genes. These
mouse models of cancer are very useful in the identification
of novel cancer genes because the proviruses not only
induce mutations efficiently but also provide a sequence tagmarking the site of mutation within the tumor. In the postgenome sequence era these mutations can now be easily
cloned using PCR-based approaches and mapped on the
mouse genome. Hundreds of novel candidate cancer genes
have been identified using insertional mutagenesis in mice
(18,19). The major limitation with these models is that retroviral infection can produce mammary and hematopoietic
cancer in mice but little else. Unfortunately, most cancer
deaths are caused by solid cancers for which there are no
insertional mutagen available to perform analogous screens
in mice for novel cancer genes.
SLEEPING BEAUTY AWAKES WITH
SOME EFFORT
Transposable elements are one type of insertional mutagen
that has been exploited for decades by geneticists studying a
variety of organisms (20,21). Sleeping Beauty (SB) became
the first cut-and-paste transposon shown to have activity in
mice (22). SB is a member of the Tc1/mariner family of transposable elements reconstructed from ancient elements found
in the genomes of salmon fish. The system consists of two
parts: the transposase enzyme and the DNA transposon
vector. Initial work on the SB system in mice further demonstrated its activity, but transposition rates were below that
needed for most genetic applications (23 – 26). Following
these experiments several publications demonstrated improvements to the SB system in an effort to improve the efficiency
of the system. The most significant factor affecting transposition rates appear to be the overall size of the transposon vector
(27). Not surprisingly, transposons that are approximately the
size of a wild-type Tc1/mariner element (2 kb) hop at much
higher rates than those of larger size. Additional experiments
produced improved versions of both the transposon (28)
and transposase (29,30) that improved transposition rates as
well. However, despite these improvements, only modest
increases in SB transposition rates in cell culture experiments
were observed.
Two recent publications demonstrated for the first time that
SB transposition can be used as a cancer gene discovery tool
by making a few improvements to the SB system (31,32).
First, two new mutagenic transposons were constructed
specifically for the purpose of mutagenesis (T2/Onc, T2/
Onc2). These transposons carry a retroviral LTR and splice
donor and can thus activate the expression of a protooncogene located nearby (Fig. 1A). In addition, these transposons carry splice acceptor sites on both DNA strands and a
bidirectional polyA sequence and can thus disrupt the
expression of a tumor suppressor gene when integrated in it
(Fig. 1C and D). Likewise, the transposon can induce the
expression of a truncated oncogene when integrated in it
(Fig. 1B). These transposons were initially introduced into
mice via a standard pronuclear injection in which a linear
plasmid containing a single copy of the transposon forms a
multicopy array at one site in the mouse genome (Fig. 2).
These transposon donor arrays can be grouped according to
Human Molecular Genetics, 2006, Vol. 15, Review Issue 1
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Figure 2. Impact of SB transposon and transposase alleles on tumor frequency
and latency.
Figure 1. Mechanisms of transposon induced mutations. Both the T2/Onc and
T2/Onc2 transposons can function to induce gain-of-function mutations
in oncogenes (A and B). These are typically caused by transposon integration
within the promoter region of the oncogene (A) or within the transcription unit
of the oncogene (B). In both cases, the promoter/splice donor within the transposon (blue arrow & box) drives overexpression of either a near full-length
transcript (A) or truncated transcript (B). In the case of tumor suppressor
genes, transposon integration within the transcription unit can introduce a
loss-of-function mutation. Splice acceptor and polyA signals within the transposon (red boxes) can trap the promoter of a tumor suppressor gene in either
orientation (C and D). The predicted splicing pattern of the gene transcript is
shown above each figure with exons shown as solid lines and predicted splicing events as dashed lines.
copy number with two transgenic lines having a moderate
transposon copy number (31) and three having high copy
number (32). As SB mobilizes transposons via a cut-and-paste
mechanism, increasing the number of transposons in the cell
should increase the number of transposition events. Two
sources were used to drive transposase expression in these
screens: a ubiquitously expressed transpose transgene
(CAGGS-SB10) and a knock-in allele in which the transposase gene was knocked-in to the mouse Rosa26 locus
(RosaSB) (23,32). Genes knocked-in to the Rosa26 locus are
generally ubiquitously expressed in both embryonic and
adult mouse tissues. Knock-in alleles are preferred to transgenes as they provide consistent, enforced gene expression.
Transgenes, by comparison, are often silenced by direct
methylation of the transgene thus producing unpredictable
variegated patterns of gene expression.
The low copy transposon donor arrays together with the
CAGGS-SB10 transposase transgene produced no spontaneous tumors in mice (31). In contrast, the high copy transposon donor array in combination with the RosaSB knock-in
allele produced spontaneous tumors in mice (32). The prediction would be that the combinations of the low copy transposon array with RosaSB or the high copy transposon array with
the CAGGS-SB10 transgene should produce an intermediate
phenotype. In fact, the RosaSB transposase allele does
produce spontaneous tumors in mice with low copy transposon
arrays but at longer latency than with high copy donor arrays
(David Largaespada, personal communication). In both cases,
the RosaSB transposase allele produces lymphomas most
frequently.
IDENTIFICATION OF TAGGED CANCER GENES
USING TRANSPOSONS
As the transposons act as insertional mutagens they provide
sequence tag-marking sites of mutation within the tumor.
With recent advances in PCR technology and the availability
of the mouse genome sequence, literally thousands of transposon integration sites can be cloned and mapped within a few
weeks. This provides a broad picture of the mutations found
within each tumor. This approach has been applied in two
ways: to initiate and accelerate the development of tumors
in wild-type mice or to accelerate the development of
tumors in mice already predisposed to cancer.
In the first approach, transposons will provide the initiating
mutations as well as the accelerating mutations. In this
context, transposon mutagenesis can be used as a genetic
tool to perform relatively unbiased forward genetic screens
to identify not only novel cancer genes but also combinations
of cancer genes that act together to transform a cell. For
example, over 60% of the SB transposon-induced T-cell lymphomas described by Dupuy et al. (32) harbor activating transposon integrations in the Notch1 gene. Roughly, half of these
T-cell lymphomas also harbor activating transposon integrations in the Rasgrp1 gene, a gene that functions upstream
of Ras and activates Ras-signaling, suggesting that Rassignaling cooperates with Notch1 signaling to produce these
T-cell lymphomas. Identification of such cooperating cancer
gene pathways will be extremely valuable for the development
of improved targeted cancer therapeutics.
In the second approach, transposon mutagenesis can be used
to identify cancer genes that cooperate with a specific initiating event such as loss of a tumor suppressor or activation of an
oncogene. The complexity of integrations identified with this
strategy will likely be decreased as each tumor cell carries a
tumor initiating non-SB-induced mutation. However, it
offers the ability to perform forward genetic screens for
mutations that accelerate a defined mutation associated with
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cancer. The first paper to use the SB system for this purpose
mobilized transposons in mice deficient for the tumor suppressor p19Arf (31). Loss of p19 expression is associated with a
number of human cancers, and mice lacking a functional
p19 gene develop a wide variety of tumor types (33). In this
context, the SB system could accelerate every tumor type
that developed in p19 deficient mice. Analysis of 30 independent soft tissue sarcomas in these animals identified activating
transposon integrations in the Braf locus as the most common
mutation cooperating with p19 loss. In fact, the mutations
caused by transposon integration in these tumors produce a
truncated Braf protein with constitutive kinase activity. Point
mutation of the BRAF gene is thought to produce a similar
constitutive kinase activity in human sarcoma, melanoma
and other tumor types (34) validating the usefulness of SB
for identifying cancer genes in solid tumors.
CREATING CUSTOM CANCER MODELS IN MICE
The available technologies for the identification of cancer
genes involved in leukemia and lymphoma have been used
successfully to identify hundreds of genes involved in these
forms of cancer. Unfortunately, our current technical limitations make it much more challenging to identify cancer
genes involved in most solid tumor types. The SB transposon
system is one example of a new technology that could be used
to identify candidate cancer genes in many forms of cancer.
Regulated and/or inducible transposase alleles can be utilized
to direct transposon-induced mutagenesis to specific sites in
the mouse to model many forms of cancer. This could be
done using a number of approaches. First, SB transposase
could be expressed from a tissue-specific promoter instead
of the ubiquitous Rosa26 locus (Fig. 3A). Investigators
could take advantage of a number of cloned promoters or
utilize BAC transgenes to target SB transposase expression
to the site of interest.
A second approach would be to generate a Cre-inducible
transposase allele. With this strategy, a ubiquitous SB transposase allele, such as the RosaSB allele, could be silenced by
introducing a ‘lox-stop-lox’ cassette just upstream of the
transposase cDNA (Fig. 3B). This approach has been used
successfully to generate alleles that can be activated through
the targeted expression of Cre recombinase (35,36). Investigators could then take advantage of a number of Cre alleles
already available in mice to induce transposition at specific
sites in the animal. In addition, Cre fusion proteins such as
CreER could be used to initiate transposition at specific
time points during embryonic development or in adult
animals.
The transposon vector itself could also be modified, in
addition to creating inducible and/or tissue-specific transposase alleles. Mutagenic transposons that lack an internal promoter could be used to exclusively disrupt gene expression
in screens for novel tumor suppressor genes. Transposons containing insulator/silencing elements could be utilized to make
broad alterations to chromatin structure often seen in human
tumors. These are just a few possibilities, and many other
modifications could be utilized as the transposon structure is
quite flexible.
Figure 3. Two different strategies for regulating the sites of SB transposition.
(A) Tissue-specific transposon mutagenesis can be achieved by expressing the
SB transposase from a tissue-specific promoter. (B) This can also be achieved
by expressing the SB transposase from a ubiquitous promoter (i.e. Rosa26) but
disrupt its expression with a ‘floxed stop cassette’. This cassette consists of a
sequence that efficiently terminates transcription to prevent expression of
downstream genes. The cassette is flanked by loxP sites and can be
removed by Cre recombinase. This approach can then take advantage of
many Cre strains to induce mutagenesis in specific sites in mice.
TRANSLATING MOUSE CANCER INTO BETTER
CANCER THERAPIES
While cancer drugs designed against specific targets have
shown much promise, clearly there is much work yet to be
done. Recent advances in screening tools now make it possible
to rapidly identify compounds with specific cellular targets
(37). Unfortunately, our ability to identify the appropriate
targets within tumor cells has limited the application of
these tools. Mouse models of cancer generated using the SB
transposon system could provide much needed insight into
the complex genetic events that drive the initiation and progression of cancer. Initially, these models will be useful for
the identification of candidate cancer genes in many forms
of human cancer. Eventually, the SB system could be used
to drive mutagenesis high enough in mice to link such clinically relevant processes as metastasis and drug resistance to
specific gene mutations. It is also possible that transposon
mutagenesis in mice will produce tumor models with sufficient
genetic heterogeneity such that it could be used in preclinical
testing of new cancer drugs. In this way, the SB system could
contribute to many aspects of cancer research.
ACKNOWLEDGEMENTS
We thank David Largaespada for helpful comments on this
manuscript. Adam J. Dupuy, Nancy A. Jenkins and Neal
G. Copeland are supported by the Intramural Research
Program of the NIH, National Cancer Institute, Center for
Cancer Research.
Conflict of Interest statement. None declared.
Human Molecular Genetics, 2006, Vol. 15, Review Issue 1
REFERENCES
1. Stehelin, D., Varmus, H.E., Bishop, J.M. and Vogt, P.K. (1976) DNA
related to the transforming gene(s) of avian sarcoma viruses is present in
normal avian DNA. Nature, 260, 170–173.
2. Hahn, W.C. and Weinberg, R.A. (2002) Rules for making human tumor
cells. N. Engl. J. Med., 347, 1593–1603.
3. Hahn, W.C., Counter, C.M., Lundberg, A.S., Beijersbergen, R.L.,
Brooks, M.W. and Weinberg, R.A. (1999) Creation of human tumour cells
with defined genetic elements. Nature, 400, 464–468.
4. Hanahan, D. and Weinberg, R.A. (2000) The hallmarks of cancer.
Cell, 100, 57 –70.
5. Ushijima, T. (2005) Detection and interpretation of altered methylation
patterns in cancer cells. Nat. Rev. Cancer, 5, 223–231.
6. Emens, L.A. (2005) Trastuzumab: targeted therapy for the management of
HER-2/neu-overexpressing metastatic breast cancer. Am. J. Ther.,
12, 243 –253.
7. Deininger, M., Buchdunger, E. and Druker, B.J. (2005) The development
of imatinib as a therapeutic agent for chronic myeloid leukemia. Blood,
105, 2640–2653.
8. De Giorgi, U. and Verweij, J. (2005) Imatinib and gastrointestinal stromal
tumors: where do we go from here? Mol. Cancer Ther., 4, 495 –501.
9. Herbst, R.S., Fukuoka, M. and Baselga, J. (2004) Gefitinib—a novel
targeted approach to treating cancer. Nat. Rev. Cancer, 4, 956– 965.
10. Lan, K.H., Lu, C.H. and Yu, D. (2005) Mechanisms of trastuzumab
resistance and their clinical implications. Ann. NY Acad. Sci., 1059,
70– 75.
11. Chen, L.L., Sabripour, M., Andtbacka, R.H., Patel, S.R., Feig, B.W.,
Macapinlac, H.A., Choi, H., Wu, E.F., Frazier, M.L. and Benjamin, R.S.
(2005) Imatinib resistance in gastrointestinal stromal tumors. Curr. Oncol.
Rep., 7, 293 –299.
12. Deininger, M. (2005) Resistance to imatinib: mechanisms and
management. J. Natl Compr. Canc. Netw., 3, 757–768.
13. Kobayashi, S., Boggon, T.J., Dayaram, T., Janne, P.A., Kocher, O.,
Meyerson, M., Johnson, B.E., Eck, M.J., Tenen, D.G. and Halmos, B.
(2005) EGFR mutation and resistance of non-small-cell lung cancer to
gefitinib. N. Engl. J. Med., 352, 786 –792.
14. Wang, Y. (2005) Gene expression-driven diagnostics and
pharmacogenomics in cancer. Curr. Opin. Mol. Ther., 7, 246 –250.
15. Davies, J.J., Wilson, I.M. and Lam, W.L. (2005) Array CGH technologies
and their applications to cancer genomes. Chrom. Res., 13, 237–248.
16. Hann, B. and Balmain, A. (2001) Building ‘validated’ mouse models of
human cancer. Curr. Opin. Cell. Biol., 13, 778 –784.
17. Maddison, K. and Clarke, A.R. (2005) New approaches for modelling
cancer mechanisms in the mouse. J. Pathol., 205, 181–193.
18. Callahan, R. (1996) MMTV-induced mutations in mouse mammary
tumors: their potential relevance to human breast cancer. Breast Cancer
Res. Treat., 39, 33–44.
19. Mikkers, H. and Berns, A. (2003) Retroviral insertional mutagenesis:
tagging cancer pathways. Adv. Cancer Res., 88, 53–99.
20. Osborne, B.I. and Baker, B. (1995) Movers and shakers: maize
transposons as tools for analyzing other plant genomes. Curr. Opin. Cell.
Biol., 7, 406 –413.
21. Spradling, A.C., Stern, D.M., Kiss, I., Roote, J., Laverty, T. and Rubin,
G.M. (1995) Gene disruptions using P transposable elements: an integral
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
R79
component of the Drosophila genome project. Proc. Natl Acad. Sci. USA,
92, 10824–10830.
Ivics, Z., Hackett, P.B., Plasterk, R.H. and Izsvak, Z. (1997) Molecular
reconstruction of sleeping beauty, a Tc1-like transposon from fish, and its
transposition in human cells. Cell, 91, 501 –510.
Dupuy, A.J., Fritz, S. and Largaespada, D.A. (2001) Transposition and
gene disruption in the male germline of the mouse. Genesis, 30, 82– 88.
Fischer, S.E., Wienholds, E. and Plasterk, R.H. (2001) Regulated
transposition of a fish transposon in the mouse germ line. Proc. Natl Acad.
Sci. USA, 98, 6759–6764.
Horie, K., Kuroiwa, A., Ikawa, M., Okabe, M., Kondoh, G., Matsuda, Y.
and Takeda, J. (2001) Efficient chromosomal transposition of a Tc1/
mariner-like transposon Sleeping Beauty in mice. Proc. Natl Acad. Sci.
USA, 98, 9191–9196.
Luo, G., Ivics, Z., Izsvak, Z. and Bradley, A. (1998) Chromosomal
transposition of a Tc1/mariner-like element in mouse embryonic stem
cells. Proc. Natl Acad. Sci. USA, 95, 10769–10773.
Karsi, A., Moav, B., Hackett, P. and Liu, Z. (2001) Effects of insert size
on transposition efficiency of the sleeping beauty transposon in mouse
cells. Mar. Biotechnol. (NY ), 3, 241 –245.
Cui, Z., Geurts, A.M., Liu, G., Kaufman, C.D. and Hackett, P.B. (2002)
Structure-function analysis of the inverted terminal repeats of the sleeping
beauty transposon. J. Mol. Biol., 318, 1221–1235.
Geurts, A.M., Yang, Y., Clark, K.J., Liu, G., Cui, Z., Dupuy, A.J.,
Bell, J.B., Largaespada, D.A. and Hackett, P.B. (2003) Gene transfer
into genomes of human cells by the sleeping beauty transposon system.
Mol. Ther., 8, 108–117.
Zayed, H., Izsvak, Z., Walisko, O. and Ivics, Z. (2004) Development of
hyperactive sleeping beauty transposon vectors by mutational analysis.
Mol. Ther., 9, 292–304.
Collier, L.S., Carlson, C.M., Ravimohan, S., Dupuy, A.J. and
Largaespada, D.A. (2005) Cancer gene discovery in solid tumours using
transposon-based somatic mutagenesis in the mouse. Nature, 436,
272–276.
Dupuy, A.J., Akagi, K., Largaespada, D.A., Copeland, N.G. and Jenkins,
N.A. (2005) Mammalian mutagenesis using a highly mobile somatic
sleeping beauty transposon system. Nature, 436, 221 –226.
Kamijo, T., Zindy, F., Roussel, M.F., Quelle, D.E., Downing, J.R.,
Ashmun, R.A., Grosveld, G. and Sherr, C.J. (1997) Tumor suppression at
the mouse INK4a locus mediated by the alternative reading frame product
p19ARF. Cell, 91, 649 –659.
Davies, H., Bignell, G.R., Cox, C., Stephens, P., Edkins, S., Clegg, S.,
Teague, J., Woffendin, H., Garnett, M.J., Bottomley, W. et al. (2002)
Mutations of the BRAF gene in human cancer. Nature, 417, 949 –954.
Soriano, P. (1999) Generalized lacZ expression with the ROSA26 Cre
reporter strain. Nat. Genet., 21, 70–71.
Tuveson, D.A., Shaw, A.T., Willis, N.A., Silver, D.P., Jackson, E.L.,
Chang, S., Mercer, K.L., Grochow, R., Hock, H., Crowley, D. et al. (2004)
Endogenous oncogenic K-ras(G12D) stimulates proliferation and
widespread neoplastic and developmental defects. Cancer Cell, 5,
375–387.
Onyango, P. (2004) The role of emerging genomics and proteomics
technologies in cancer drug target discovery. Curr. Cancer Drug Targets,
4, 111–124.