The Journal of Clinical Investigation http://www.jci.org Volume 122 Number 8 August 2012
A remarkably simple genome underlies highly
malignant pediatric rhabdoid cancers
Ryan S. Lee,1,2 Chip Stewart,3 Scott L. Carter,3 Lauren Ambrogio,3 Kristian Cibulskis,3
Carrie Sougnez,3 Michael S. Lawrence,3 Daniel Auclair,3 Jaume Mora,4 Todd R. Golub,1,2,3,5
Jaclyn A. Biegel,6,7 Gad Getz,3 and Charles W.M. Roberts1,2,8
1Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA. 2Harvard Medical School, Boston, Massachusetts, USA.
3Broad Institute, Cambridge, Massachusetts, USA. 4Department of Pediatric Oncology, Hospital Sant Joan de Déu, Barcelona, Spain.
5Howard Hughes Medical Institute, Chevy Chase, Maryland, USA. 6Department of Pediatrics, University of Pennsylvania School of Medicine,
Philadelphia, Pennsylvania, USA. 7Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
8Division of Hematology/Oncology, Children’s Hospital Boston, Boston, Massachusetts, USA.
Cancer is principally considered a genetic disease, and numerous mutations are thought essential to drive its
growth. However, the existence of genomically stable cancers and the emergence of mutations in genes that
encode chromatin remodelers raise the possibility that perturbation of chromatin structure and epigenetic
regulation are capable of driving cancer formation. Here we sequenced the exomes of 35 rhabdoid tumors,
highly aggressive cancers of early childhood characterized by biallelic loss of SMARCB1, a subunit of the SWI/
SNF chromatin remodeling complex. We identified an extremely low rate of mutation, with loss of SMARCB1
being essentially the sole recurrent event. Indeed, in 2 of the cancers there were no other identified mutations.
Our results demonstrate that high mutation rates are dispensable for the genesis of cancers driven by muta-
tion of a chromatin remodeling complex. Consequently, cancer can be a remarkably genetically simple disease.
Cancer is generally considered to arise due to DNA mutations
that alter the function of numerous genes (1). Indeed, most cancer
genomes are aneuploid, contain amplifications and deletions, and
typically have hundreds to thousands of DNA point mutations.
However, not all cancers are necessarily so complex as some highly
aggressive tumors are diploid. Large-scale sequencing projects have
revealed that mutation rates display 10- to 100-fold differences
among cancer types and even among different cancers of the same
type (2, 3). Even in cancer types possessing the highest mutation
rates, there are often individual cases that contain many fewer muta-
tions. This raises a fundamental question about the nature of can-
cer: How simple can the genomes of highly aggressive cancers be?
Rhabdoid tumors (RTs) are a useful type of cancer with which
to address these questions. These extremely aggressive pediatric
cancers of the brain, kidney, and soft tissues are highly malignant,
locally invasive, frequently metastatic, and particularly lethal (4),
and yet, they are typically diploid and lack genomic aberrations
detectable by SNP arrays (5). Early-onset cancers also offer the
opportunity to examine cancer genomes prior to the acquisition
of substantial numbers of age-related mutations, the vast majority
of which are likely passenger mutations.
Near-uniform biallelic inactivating mutations in SMARCB1 (also
known as SNF5, INI1, and BAF47), a gene that encodes a core sub-
unit of the SWI/SNF chromatin remodeling complex (6, 7), are
a hallmark of RTs. Alterations in genes involved in chromatin
remodeling, and particularly in genes encoding SWI/SNF subunits
(8), are increasingly being identified in a wide variety of cancers,
raising the possibility that epigenetic dysregulation may be a cen-
tral mechanism of oncogenesis.
Results and Discussion
We obtained DNA from 32 diagnostic pretreatment SMARCB1
mutant RT samples, of which 20 were from brain, 3 were from kid-
ney, and 9 were from other soft tissues (Supplemental Table 1; sup-
plemental material available online with this article; doi:10.1172/
JCI64400DS1). The median age of the patients was 12 months.
Matched non-tumor peripheral blood DNA was also obtained from
each patient. Whole-exome sequencing and SNP array analysis was
performed on all 32 sample pairs. Analysis of SNP arrays identified
a single region with significant focal somatic copy number altera-
tions (SCNAs): deletions at 22q11.23 that contained the SMARCB1
gene were identified in 25 out of the 32 samples (GISTIC2.0, ref. 9;
q < 10–50), which comprised focal deletions in 16 cases, monosomy
22 in 15 cases, and both in 6 cases (Figure 1). One sample (08-262A)
had a germ line focal deletion. Tumor purity ranged from 43% to
97%, so the lack of additional detected SCNAs was not likely due to
stromal contamination (Supplemental Table 2).
We next performed exome sequencing of DNA to a mean cover-
age of 83-fold across 32.6 Mb of targeted coding regions for each
sample (Supplemental Table 3). This level of coverage resulted in
a “call-able” exome of 28.6 Mb. Detection of SCNAs by sequenc-
ing data was consistent with SNP array findings (Supplemental
Figure 1). Analysis revealed a total of 172 somatic substitutions
and insertions/deletions (indels) in the 32 tumors (Table 1 and
Supplemental Table 12). Other than SMARCB1 loss, 2 tumors
(08-114 and 09-223) had no detectable mutations, and 4 tumors
(07-057, 07-221, 08-172, and 09-131) had only subclonal muta-
tions (Figure 2A). The mean mutation rate was 0.19 mutations
per Mb, with a minimum of 0 and a maximum of 0.45 mutations
per Mb. This rate is, to our knowledge, the lowest of all cancers
sequenced to date, particularly for such a high-grade and lethal
type of cancer (Figure 2B). Consistent with our tumor selection
process, all tumors had combinations of SMARCB1 mutations
and/or deletions predicted to cause homozygous loss of function
(Supplemental Table 4 and Supplemental Figures 3 and 6). Over-
Authorship note: Ryan S. Lee and Chip Stewart contributed equally to this work. Jac-
lyn A. Biegel, Gad Getz, and Charles W.M. Roberts are co–senior authors.
Conflict of interest: The authors have declared that no conflict of interest exists.
Citation for this article: J Clin Invest. 2012;122(8):2983–2988. doi:10.1172/JCI64400.
2984 The Journal of Clinical Investigation http://www.jci.org Volume 122 Number 8 August 2012
all, 71.5% of the mutations were classified as clonal. All 7 of the
point mutations in SMARCB1 were classified as clonal (Figure 2A
and Supplemental Table 5).
We looked for recurrent mutations that may cooperate with
SMARCB1 loss to drive RTs. The only other recurrently mutated
gene was GABRB2, a subunit of the GABA A receptor, which was
found to be clonally mutated in 2 out of the 32 samples (10-330
and SJDOS006; Supplemental Figure 4). However, the Catalog
of Somatic Mutations in Cancer (COSMIC v51) database con-
tains only 2 other instances of this gene being mutated, neither of
which matched the RT mutations (10, 11). Only 2 mutations found
among the 32 sequenced RTs, aside from SMARCB1 and GABRB2,
were present in the COSMIC database: 1 in NF2 (10-213) and the
other in TP53 (10-330). The NF2 nonsense mutation (Y144*) may
have been contributory; although subclonal (26% of cells), the muta-
tion was present on a background of hemizygous deletion, implying
SNP arrays of primary RT sam-
ples and matched normal DNA.
(A) Genome display of copy
number changes. (B) Enlarged
view of the SMARCB1 locus.
Mutations are overlaid on the
SCNAs and loss-of-heterozy-
gosity (LOH) tracks. Samples
with focal deletions covering
SMARCB1 are marked with “@.”
Samples with monosomy 22 or
loss of heterozygosity across 22
are marked with “x” or “+” next
to the sample label. The red box
represents the highlighted region
of the chromosome, including
the SMARCB1 locus shown
below. Red triangles represent
the centromeric regions of the
chromosome. Chr, chromosome.
The Journal of Clinical Investigation http://www.jci.org Volume 122 Number 8 August 2012
homozygous loss in the mutant subclone. The relevance of the TP53
mutation (D49N) was unclear; although clonal, the variant did not
occur in one of the canonical mutation domains and was predicted
not to be detrimental.
In addition to the 32 primary samples, we analyzed 3 indepen-
dent recurrent tumor/normal pairs after chemotherapy (Supple-
mental Table 6). Sample 09-044 was found to be aneuploid (Figure
3A). The range of purity and coverage was comparable to that in
the primary samples (Supplemental Tables 7 and 8). While the
largest number of mutations per sample found in the 32 primary
tumors was 13, the recurrent cancers contained 38, 47, and 47
mutations, resulting in a rate of 1.53 mutations per Mb (Supple-
mental Table 9), 8 times higher than that in the primary tumors
(Figure 3B; P < 0.005). Other than SMARCB1, which was homo-
zygously lost in all 3 recurrent samples (Supplemental Table 10),
none of the mutations matched any in the COSMIC database and
no gene contained recurrent, clonal mutations (Supplemental
Figure 5). Notably, the treated samples had significantly more
subclonal mutations than the primary tumors (P = 7 × 10–4; Fig-
ure 2A and Supplemental Table 11). Despite their absence from
the COSMIC database, we could not exclude the possibility that
these mutations could be conferring a growth advantage for sub-
clones that could ultimately contribute to recurrent or refractory
disease. Regardless, these mutations are unlikely to constitute
effective therapeutic targets up front, given their absence from the
predominant cancer population.
The mutational profile was also distinct in the recurrent sam-
ples, as they contained a significantly reduced proportion of C→T
transitions (P < 10–5, 2-proportion z test) and increased propor-
tions of A→T (P < 0.05) and C→A (P < 0.005) transversions (Fig-
ure 3C). Overall, the recurrent tumors had a greater percentage of
transversions (P < 10–4; Figure 3D and Supplemental Figure 2).
In part based upon the large number of mutations commonly
present in tumors, genetic alterations that affect numerous pro-
tein coding genes have typically been considered a fundamental
requirement for cancer development. The finding that SMARCB1
is the sole gene recurrently mutated at high frequency in extreme-
ly aggressive and lethal RTs, and in some cases may be the only
mutated gene, prompts essential questions: What accounts for the
extreme paucity of mutations, and how can these data be recon-
ciled with current models of cancer that estimate that 5 to 15 driv-
ing mutations are required for oncogenesis (12)?
We considered 4 possible explanations. First, as we have only
sequenced exome DNA, we cannot exclude the existence of muta-
tions in noncoding portions of the genome, such as in noncoding
RNAs or regulatory elements or in mutations in low coverage areas.
Further, we cannot exclude balanced translocations or inversions,
although these are not characteristic of RTs by karyotype (13). None-
theless, occult events could cooperate with SMARCB1 loss. Second,
as mutations were largely identified based upon differences between
tumor and normal DNA, contributions from germ line events are
difficult to exclude. However, since genetically engineered models
have demonstrated that inactivation of Smarcb1 drives extremely
rapid formation of cancer in all mice and since this occurs on sev-
eral genetic backgrounds (14, 15), it seems unlikely that germ line
alterations are essential for cancer formation driven by SMARCB1
loss. Third, the developmental stage/epigenetic state may serve a
contributory role. During development, there is relative enrichment
of minimally differentiated cell populations that have a high prolif-
erative capacity. Consequently, it is possible that developmentally
restricted or lineage-specific populations of cells characterized by a
certain epigenetic state are particularly susceptible, such that muta-
tion of a single chromatin remodeler can drive transformation. This
is consistent with our mouse model in which Smarcb1 deletion in the
T cell lineage leads to transformation of a highly specific cell type,
CD8+CD44hiCD122lo memory T cells, a population that has a high
intrinsic capacity for proliferation. Notably, this transformation
arises due to aberrant responses to lineage-specific T cell receptor
Somatic mutations in RTs. (A) Mutation multiplic-
ity for each sample. Multiplicity is a measure of
the average number of alternate alleles per tumor
cell for each mutation. Heterozygous clonal muta-
tions have a multiplicity near 1, while events below
1 are subclonal. Multiplicities close to 2 tend to be
the result of mutations in loss-of-heterozygosity
regions. Circles indicate the 9 SMARCB1 muta-
tions. (B) Logarithmic plot of mutation rates in 5
other types of cancer compared with those in RTs.
Blue circles represent recurrent the RT samples.
For box-and-whisker plots, red horizontal bars
indicate medians, boxes indicate 25th and 75th
percentiles, lower whiskers indicate lowest datum
within 1.5 times the interquartile range (1.5xIQR) of
the lower quartile, upper whiskers indicate highest
datum within 1.5xIQR of the upper quartile, and red
dots represent outliers. CLL, chronic lymphocytic
2986 The Journal of Clinical Investigation http://www.jci.org Volume 122 Number 8 August 2012
signaling caused by SMARCB1 loss (16). Such specificity in lineage
effects could explain why mutation of SMARCB1 is largely restricted
to RTs and a few other cancers. It should be noted that the SWI/SNF
complex contributes to differentiation control in many tissues and
that several other members of the SWI/SNF complex are mutated
across a variety of adult cancers, including subsets of ovarian and
renal cancer, among other cancers, with each mutated subunit hav-
ing a distinct profile of associated cancers (8, 17–19). We speculate
that this specificity may be related to epigenetic state and distinct
roles for the subunits in modulating interactions with particular
transcription factors. Fourth, it is conceivable that 5 to 15 is an
overestimation of the number of mutations required for oncogenic
transformation. While adult cancers that arise in tissues exposed
to mutagens, such as those of skin, lung, and the gastrointestinal
tract, generally contain an extremely high number of mutations,
other adult cancers, such as acute myeloid leukemia (AML) and
breast cancer, are typically much simpler. Similarly, pediatric can-
cers, such as osteosarcomas, have extremely complex genomes, while
retinoblastomas, poorly differentiated but generally good prognosis
cancers, have extremely low mutation rates (20, 21). Regardless of
the explanation, our data from RTs demonstrate that collaboration
between multiple coding mutations is not essential for the genesis
of extremely aggressive and highly lethal cancers.
It is interesting that a type of cancer that has extremely few
gene mutations at the time of initial diagnosis is characterized by
a much higher number of mutations in recurrent samples. The
reason for this is unclear. While we do not have specific treatment
data, these patients were treated with chemotherapy and poten-
tially radiation therapy. It is possible that genotoxic chemotherapy
directly causes such damage. This possibility is supported by the
presence in recurrent samples of a high percentage of transver-
sions, a mutation type known to be associated with chemotherapy
and similarly seen in recurrent AML (22). This raises the possibil-
ity that chemotherapy can cause the conversion of a remarkably
simple cancer genome into one with 8-fold more mutations, a
possibility with substantial clinical implications, as such muta-
tions could potentially contribute to resistance. Alternatively, the
selective pressure of chemotherapy may result in the outgrowth of
subclones with high rates of mutation, or, conceivably, the funda-
mental nature of the recurrent disease has changed such that these
cancers have acquired genetic instability and a high mutation rate.
Finally, while there is increasing evidence that epigenetic regula-
tors are mutated in a large variety of cancers, it has been unclear
whether these alterations are selected for because they act to facili-
tate genomic instability, because they potentiate the effects of
other mutations, or because they directly drive oncogenic trans-
formation. Particularly in cancers in which mutations in chroma-
tin regulators exist in a genetically complex background, it has
been extremely difficult to determine the relative contribution of
epigenetic alterations. Our findings from RTs demonstrate that
mutations in the SWI/SNF chromatin remodeling complex can
act as potent drivers of cancer. Understanding the contributions
of mutations in these remodelers to oncogenesis has the potential
to facilitate development of targeted therapies for the wide variety
of SWI/SNF mutant cancers.
Samples. Tumor tissue and matched blood from 32 newly diagnosed patients
with cancer and from 3 recurrent tumors were collected. Mutation and dele-
tion analysis of the SMARCB1 gene was performed as previously described
(6). Tumors were reviewed to confirm the diagnosis and to estimate tumor
content (The Children’s Hospital of Philadelphia, Hospital Sant Joan de
Déu). DNA was extracted using standard techniques.
SNP arrays. All of these samples were processed and hybridized to
Affymetrix SNP 6.0 arrays for genotyping and copy number analysis (2).
SNP array data were further analyzed using the ABSOLUTE tool (23) to
infer the tumor purity and ploidy (11, 24, 25).
Whole-exome sequence data. Library construction followed the procedure of
previous publications (11, 24, 25). Descriptions of sequencing and analysis
methods are in the Supplemental Methods. Data were deposited in dbGaP
(accession no. phs000508). The complete list of all detected mutations can
be found in Supplemental Table 12.
Statistics. Comparison of mutation rates was performed using a 2-tailed
Welch’s t test for samples with unequal variance. Two-proportion z test
and Pearson’s χ2 test with a Yates’s correction for continuity were used
to analyze the different proportions of mutation type. Subclonal muta-
tion frequency was analyzed using Fisher’s exact test. Data in figures are
shown as mean ± SEM.
Somatic mutation types in 32 primary RT samples
Numbers in the “total” column represent the total number of somatic
substitutions and indels.
The Journal of Clinical Investigation http://www.jci.org Volume 122 Number 8 August 2012
cer Innovative Research Grant from the American Association
of Cancer Research. J.A. Biegel is partly supported by NIH grant
Received for publication April 19, 2012, and accepted in revised
form June 7, 2012.
Address correspondence to: Jaclyn Biegel, The Children’s Hos-
pital of Philadelphia, ARC Room 1002, 3615 Civic Center
Boulevard, Philadelphia, Pennsylvania 19104, USA. Phone:
215.590.3856; Fax: 215.590.3764; E-mail: email@example.com.
upenn.edu. Or to: Gad Getz, Broad Institute, 301 Binney St.,
Cambridge, Massachusetts 02142, USA. Phone: 617.714.7471;
Fax: 617.714.8102; E-mail: firstname.lastname@example.org. Or to:
Charles Roberts, Dana-Farber Cancer Institute, 450 Brook-
line Avenue, Boston, Massachusetts 02215, USA. Phone:
617.632.6497; Fax: 617.582.8096; E-mail: Charles_Roberts@
Study approval. Patients’ guardians provided informed consent prior to
their participation. Local IRBs (The Children’s Hospital of Philadelphia,
Hospital Sant Joan de Déu) approved collection and testing of each sam-
ple. Subsequently, the Broad Institute’s IRB approved consents.
We are grateful to K. Eaton and L. Tooke for technical assistance,
A. Sivachenko for indel detection, A. McKenna for germ line
mutation calling, C. Zhang for SegSeq, G. Saksema for SNP array
processing, P. Stojanov for MutSig advice, and M. Meyerson and
T. Pugh for fruitful discussions. We also thank all the members
of the Broad Institute’s Biological Samples, Genetic Analysis,
and Genomic Sequencing Platforms. This project is part of the
Slim Initiative for Genomic Medicine, a joint US-Mexico project
funded by the Carlos Slim Health Institute. R.S. Lee is partly sup-
ported by a NSF Graduate Research Fellowship. C.W.M. Roberts
is partly supported by the Garrett B. Smith Foundation, PHS
awards R01CA113794 and U01-1156106, and a Stand Up to Can-
Recurrent RTs have more mutations than primary tumors. (A) SNP array of 2 matched tumor/normal pairs from recurrent tumors reveals an
aneuploid tumor sample (09-044). Blue represents deletion; red represents amplification; and green represents copy neutral LOH. (B) The muta-
tion rate in recurrent RTs is significantly higher (*P < 0.005) than that in primary RT samples. (C) While primary samples had a greater proportion
of C→T transitions, recurrent samples had a greater proportion of C→A and A→T transversions. Significant differences between primary and
recurrent samples are indicated. *P < 0.05, **P < 0.005, ***P < 10–5. (D) Recurrent samples have significantly more transversions than primary
samples (P < 0.0005).
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