The genetic landscape of the childhood cancer medulloblastoma.
ABSTRACT Medulloblastoma (MB) is the most common malignant brain tumor of children. To identify the genetic alterations in this tumor type, we searched for copy number alterations using high-density microarrays and sequenced all known protein-coding genes and microRNA genes using Sanger sequencing in a set of 22 MBs. We found that, on average, each tumor had 11 gene alterations, fewer by a factor of 5 to 10 than in the adult solid tumors that have been sequenced to date. In addition to alterations in the Hedgehog and Wnt pathways, our analysis led to the discovery of genes not previously known to be altered in MBs. Most notably, inactivating mutations of the histone-lysine N-methyltransferase genes MLL2 or MLL3 were identified in 16% of MB patients. These results demonstrate key differences between the genetic landscapes of adult and childhood cancers, highlight dysregulation of developmental pathways as an important mechanism underlying MBs, and identify a role for a specific type of histone methylation in human tumorigenesis.
- [Show abstract] [Hide abstract]
ABSTRACT: Esophageal squamous cell carcinoma (ESCC) is one of the deadliest cancers. We performed exome sequencing on 113 tumor-normal pairs, yielding a mean of 82 non-silent mutations per tumor, and 8 cell lines. The mutational profile of ESCC closely resembles those of squamous cell carcinomas of other tissues but differs from that of esophageal adenocarcinoma. Genes involved in cell cycle and apoptosis regulation were mutated in 99% of cases by somatic alternations of TP53 (93%), CCND1 (33%), CDKN2A (20%), NFE2L2 (10%) and RB1 (9%). Histone modifier genes were frequently mutated, including KMT2D (also called MLL2; 19%), KMT2C (MLL3; 6%), KDM6A (7%), EP300 (10%) and CREBBP (6%). EP300 mutations were associated with poor survival. The Hippo and Notch pathways were dysregulated by mutations in FAT1, FAT2, FAT3 or FAT4 (27%) or AJUBA (JUB; 7%) and NOTCH1, NOTCH2 or NOTCH3 (22%) or FBXW7 (5%), respectively. These results define the mutational landscape of ESCC and highlight mutations in epigenetic modulators with prognostic and potentially therapeutic implications.Nature Genetics 08/2014; · 29.65 Impact Factor
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ABSTRACT: Gliomas, the most common primary brain tumors in adults, constitute clinically, histologically, and molecularly a most heterogeneous type of cancer. Owing to this, accurate clinical prognosis for short-term vs. long-term survival for patients with grade II or III glioma is currently nonexistent. A rigorous, multi-method bioinformatic approach was used to identify the top most differentially expressed genes as captured by mRNA sequencing of tumor tissue. Mathematical modeling was employed to develop the model, and three different and independent methods of validation were used to assess its performance. I present here a mathematical model that can identify with a high accuracy (sensitivity=92.9%, specificity=96.0%) those patients with glioma (grade II or III) who will experience short-term survival (≤ 1 year), as well as those with long-term survival (≥ 3 years), at the time of diagnosis and prior to surgery and adjuvant chemotherapy. The 5 gene input variables to the model are: FAM120AOS, PDLIM4, OCIAD2, PCDH15, and MXI1. MXI1, a transcriptional repressor, represents the top biomarker of survival and the most promising target for the development of a pharmacological treatment.American journal of cancer research. 01/2014; 4(6):862-73.
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ABSTRACT: SMARCA4 (BRG1) and SMARCB1 (INI1) are tumor suppressor genes that are crucially involved in the formation of malignant rhabdoid tumors, such as atypical teratoid/rhabdoid tumor (AT/RT). AT/RTs typically affect infants and occur at various sites of the CNS with a particular frequency in the cerebellum. Here, granule neurons and their progenitors represent the most abundant cell type and are known to give rise to a subset of medulloblastoma, a histologically similar embryonal brain tumor. To test how Smarc proteins influence the development of granule neurons and whether this population may serve as cellular origin for AT/RTs, we specifically deleted Smarca4 and Smarcb1 in cerebellar granule cell precursors. Respective mutant mice displayed severe ataxia and motor coordination deficits, but did not develop any tumors. In fact, they suffered from a severely hypoplastic cerebellum due to a significant inhibition of granule neuron precursor proliferation. Molecularly, this was accompanied by an enhanced activity of Wnt/β-catenin signaling that, by itself, is known to cause a nearly identical phenotype. We further used an hGFAP-cre allele, which deleted Smarcb1 much earlier and in a wider neural precursor population, but we still did not detect any tumor formation in the CNS. In summary, our results emphasize cell-type-dependent roles of Smarc proteins and argue against cerebellar granule cells and other progeny of hGFAP-positive neural precursors as the cellular origin for AT/RTs.Journal of Neuroscience 10/2014; · 6.75 Impact Factor
, 435 (2011);
, et al.D. Williams Parsons
The Genetic Landscape of the Childhood Cancer Medulloblastoma
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The Genetic Landscape of the
Childhood Cancer Medulloblastoma
D. Williams Parsons,1,2* Meng Li,1* Xiaosong Zhang,1* Siân Jones,1* Rebecca J. Leary,1*
Jimmy Cheng-Ho Lin,1Simina M. Boca,3Hannah Carter,4Josue Samayoa,4Chetan Bettegowda,1,5
Gary L. Gallia,5George I. Jallo,5Zev A. Binder,5Yuri Nikolsky,6James Hartigan,7Doug R. Smith,7
Daniela S. Gerhard,8Daniel W. Fults,9Scott VandenBerg,10Mitchel S. Berger,11
Suely Kazue Nagahashi Marie,12Sueli Mieko Oba Shinjo,12Carlos Clara,13Peter C. Phillips,14
Tom Curran,16Yiping He,17B. Ahmed Rasheed,17Henry S. Friedman,17Stephen T. Keir,17
Rachel Karchin,4Giovanni Parmigiani,20Darell D. Bigner,17Hai Yan,17Nick Papadopoulos,1
Bert Vogelstein,1‡ Kenneth W. Kinzler,1‡ Victor E. Velculescu1‡
Medulloblastoma (MB) is the most common malignant brain tumor of children. To identify the
genetic alterations in this tumor type, we searched for copy number alterations using high-density
microarrays and sequenced all known protein-coding genes and microRNA genes using Sanger
sequencing in a set of 22 MBs. We found that, on average, each tumor had 11 gene alterations,
fewer by a factor of 5 to 10 than in the adult solid tumors that have been sequenced to date. In
addition to alterations in the Hedgehog and Wnt pathways, our analysis led to the discovery of genes
not previously known to be altered in MBs. Most notably, inactivating mutations of the histone-lysine
N-methyltransferase genes MLL2 or MLL3 were identified in 16% of MB patients. These results
demonstrate key differences between the genetic landscapes of adult and childhood cancers, highlight
dysregulation of developmental pathways as an important mechanism underlying MBs, and identify
a role for a specific type of histone methylation in human tumorigenesis.
vous system, and are diagnosed in approximately
1 in 200,000 children less than 15 years old each
a substantial proportion of patients are currently
siderable treatment-related morbidities, including
neurocognitive deficits related to radiation ther-
apy. New insights into the pathogenesis of these
tumors are therefore sorely needed. Gene-based
research has identified two subgroups of MBs,
one associated with mutated genes within the
Hedgehog pathway and the other associated
with altered Wnt pathway genes (3, 4). Amplifi-
cations of MYC and the transcription factor
OTX2 (5–7), mutations in TP53 (8), and a num-
ber of chromosomal alterations have also been
define the pathogenesis of MB and have im-
proved our ability to identify patients who might
benefit from therapies targeting these pathways.
However, most MB patients do not have altera-
tions in these genes, and the compendium of
genetic alterations causing MB is unknown.
The determination of the human genome se-
informatic technologies have recently permitted
the sequences of all protein-encoding genes have
been reported in more than 80 human cancers
(9–20), representing a variety of adult tumors. In
analysis of a solid tumor of childhood. Our data
point to a major genetic difference between adult
cerebellum, have a propensity to dis-
seminate throughout the central ner-
and childhood solid tumors and provide new in-
Sequencing strategy. In the first stage of our
analysis, which we have called the “discovery
screen,” 457,814 primers (table S1) were used to
amplify and sequence 225,752 protein-coding ex-
ons, adjacent intronic splice donor and acceptor
sites, and microRNA (miRNA) genes in 22 pe-
diatric MB samples (17 samples extracted directly
from primary tumors, 4 samples passaged in nude
mice as xenografts, and 1 cell line) (tables S2 and
S3). Seven metastatic MBs were selected for in-
clusion in the discovery screen to ensure that high-
stage tumors were well represented in the study.
One matched normal blood sample was sequenced
transcripts representing at least 21,039 protein-
encoding genes present in the Ensembl, Consensus
Coding Sequences (CCDS), and RefSeq databases
A total of 404,438 primers were described in our
previous publications, and an additional 53,376
assembled for each amplified region and evaluated
using stringent quality-control criteria, resulting in
of targeted amplicons and 95% of targeted bases in
the 22 tumors. A total of 735 megabases (Mb) of
After automated and manual curation of the se-
alterations (single base mutations and small inser-
tions and deletions) not present in the reference
genome or single-nucleotide polymorphism (SNP)
databases were reamplified in both the tumor and
matched normal tissue DNA and analyzed either
through sequencing by synthesis on an Illumina
ing (21). This process allowed us to confirm the
presence of the mutation in the tumor sample and
determine whether the alterationwassomatic (i.e.,
tumor-specific). Additionally, mutations identified
in the four xenograft samples were confirmed to
be present in the corresponding primary tumors.
Analysis of sequence and copy number alter-
ations. A total of 225 somatic mutations were
these, 199 (88%) were point mutations and the
remainder were small insertions, duplications, or
Of the point mutations, 148 (74%) were predicted
to result in nonsynonymous changes, 42 (21%)
located at canonical splice site residues that were
likely to alter normal splicing. Of the 225 somatic
truncate the encoded protein, either through newly
generated nonsense mutations or through inser-
in readingframe.Themutation spectrum observed
for MB was similar to those seen in pancreatic,
1Ludwig Center for Cancer Genetics and Therapeutics and
Howard Hughes Medical Institute, Johns Hopkins Kimmel
Cancer Center, Baltimore, MD 21231, USA.2Texas Children’s
Cancer Center and Departments of Pediatrics and Molecular
and Human Genetics, Baylor College of Medicine, Houston TX
Bloomberg School of Public Health, Baltimore, MD 21205,
USA.4Department of Biomedical Engineering, Institute for
Computational Medicine, Johns Hopkins Medical Institutions,
Baltimore, MD 21218, USA.5Department of Neurosurgery,
Johns Hopkins University School of Medicine, Baltimore, MD
21231, USA.6GeneGo, Inc., St. Joseph, St. Joseph, MI 49085,
USA.7Beckman Coulter Genomics, Inc., Danvers, MA 01923,
USA.8Office of Cancer Genomics, National Cancer Institute,
National Institutes of Health, Department of Health and
Human Services, Bethesda, MD 20892, USA.9Department of
Neurosurgery,UniversityofUtah School ofMedicine,SaltLake
City, UT 84132, USA.10Department of Pathology, Division of
CA, USA.11Department of Neurological Surgery, University of
Sao Paulo, Brazil.14Department of Pediatrics, The Children’s
of Neurosurgery, The Children’s Hospital of Philadelphia,
Philadelphia, PA 19104, USA.16Department of Pathology and
Laboratory Medicine, The Children’s Hospital of Philadelphia,
Philadelphia, PA 19104, USA.17The Preston Robert Tisch Brain
Tumor Center, Pediatric Brain Tumor Foundation Institute,
Department of Pathology, and Department of Surgery, Duke
of Neurosurgery and Program in Developmental and Stem Cell
Ontario M5G1L7, Canada.19Department of Pathology, Johns
Hopkins University School of Medicine, Baltimore, MD 21231,
USA.20Department of Biostatistics and Computational Biology,
Dana-Farber Cancer Institute, and Department of Biostatistics,
Harvard School of Public Health, Boston, MA, USA.
*These authors contributed equally to this work.
†Present address: Department of Pathology and Laboratory
Medicine, Children’s Hospital of Los Angeles, Los Angeles,
CA 90027, USA.
‡To whom correspondence should be addressed: velculescu@
jhmi.edu (V.E.V.); email@example.com (K.W.K.); vogelbe@gmail.
3Department of Biostatistics, Johns Hopkins
VOL 33128 JANUARY 2011
on March 9, 2011
colorectal, glial,and other malignancies (22), with
5′-CG to 5′-TA transitions observed more com-
sitions are generally associated with endogenous
residues, rather than exposure to exogenous carci-
22 MBs is illustrated in Fig. 1. Two key differences
were observed in this cancer as compared to the
typical adult solid tumor. First, the average number
of nonsilent somatic mutations (nonsynonymous
per MB patient was only 8.3, which is fewer by a
factor of 5 to 10 than the average number of al-
terations detected in the previously studied solid
tumor types (Table 1). Second, the proportion of
nonsensemutationswasmore than twiceashighas
tumor type (P < 1 × 10−4, chi-squared test), and the
relative fraction of nonsense, insertion, and du-
plication alterations was higher in MBs than in any
of the adult solid tumors analyzed (Table 1) (21).
We evaluated copy number alterations using
Illumina SNP arrays containing ~1 million probes
in a set of 23 MBs, including all discovery screen
samples. Using stringent criteria for focal amplifi-
cations and homozygous deletions, we identified
tumors (tables S5 and S6) (21). High-level ampli-
fications indicate an activated oncogene within the
signal inactivation of a tumor suppressor gene. The
total number of copy number changes affecting
ilar to the point mutation data, we found conside-
rably fewer amplifications (an average of 0.4 per
tumor) and homozygous deletions (an average of
in adult solid tumors (which average 1.6 amplifica-
tions and 1.9 homozygous deletions) (18, 19, 24).
We next evaluated a subset of the mutated
genes in an additional 66 primary MBs, including
bothpediatricandadulttumors (tablesS2and S3).
and had previously been reported to be mutated
in other tumor types. Nonsilent somatic mutations
the prevalence screen, the nonsilent mutation fre-
far higher than the rate found in the discovery
exact test). The ratio of nonsilent to silent muta-
more than 5 times as high as the 4.4 to 1 ratio de-
termined inthediscoveryscreen (P< 0.01,Fisher’s
exact test). In addition, 23 of the 50 prevalence
screen mutations (46%) were nonsense alterations
or insertions or deletions that were expected to
truncate the encoded protein. These data suggest
that the genes selected for the prevalence screen
were enriched for functionally important genes.
Frequent mutation of MLL2 and MLL3 in MB.
Somatic mutations in tumor DNA can either pro-
mutations) or have no net effect on tumorgrowth
(passenger mutations). A variety of methods are
or individual mutation is likely to be a driver. At
the gene level, the passenger probability score cor-
responds to a metric reflecting the frequency of
mutations, including point mutations, indels, am-
for sequence context as well nucleotide composi-
Table 1. Summary of somatic sequence mutations in five tumor types.
Number of samples analyzed
Number of mutated genes
Number of nonsilent mutations
Splice site or untranslated
Average number of nonsilent
mutations per sample
Observed/expected number of
1831163 748849 1112
9 (4.9)51 (4.4)27 (3.6)30 (3.5) 53 (4.8)
8 4836 77101
2.48 1.181.00 1.251.37
Total number of substitutions#
Substitutions at C:G base pairs
C:G to T:A**
C:G to G:C**
C:G to A:T**
Substitutions at T:A base pairs
T:A to C:G**
T:A to G:C**
T:A to A:T**
Substitutions at specific
*Based on 22 tumors analyzed in the current study.
in parentheses refer to percentage of total nonsilent mutations.
dependent on mutation spectra in each tumor type (21).
identified in the indicated study.
534 (59.8) 422 (36.5)
130 (14.6) 175 (15.1)
†Based on 24 tumors analyzed in (18).
¶Ratio of observed to expected nonsense alterations is
#Includes synonymous as well as nonsynonymous point mutations
**Numbers in parentheses refer to percentage of total substitutions.
427 (47.8) 195 (16.9)
99 (11.1) 395 (34.1)
‡Based on 21
Fig. 1. Number of genetic alterations detected through sequencing and copy number analyses in each of
the 22 cancers. NS, nonsilent mutations (including nonsynonymous alterations, insertions, duplications,
deletions,and splicesitechanges);S,silent mutations;deletions,gene-containing regionsabsent in tumor
samples; amplifications, gene-containing regions focally amplified at levels > 10 copies per nucleus (21).
28 JANUARY 2011VOL 331
on March 9, 2011
probability score, the less likely it is that mutations
probability scores of the candidate cancer genes
(CAN-genes)identifiedinMB are listedinTable2.
At the individual mutation level, the Cancer-
Specific High-Throughput Annotation of Somatic
function of the respective protein and provides a
selective advantage to the tumor cell (25). The
including conservation of the wild-type amino acid
and the mutation’s predicted effects on secondary
served in this study and the associated P value are
listed in table S4. Nonsense mutations, as well as
small insertions or deletions that disrupt the reading
a score of 0.001 in this table. About 36% of the
gene function using this approach, a proportion
higher than observed in the adult tumor types
analyzed to date (21).
Finally, we evaluated the discovery screen
number alterations) at a higher “gene set” level.
There is now abundant evidence that alterations
of driver genes can be productively organized
according to the biochemical pathways and bio-
ber of gene sets that define these pathways and
processes is much less than the number of genes
and can provide clarity to lists of genes identified
each gene set at the patient rather than the gene
significant pathways and biologic processes high-
lighted by this gene-set analysis are depicted in
table S7. Of these, two—the Hedgehog and Wnt
signaling pathways—have been previously shown
to play a critical role in MB development. In the
Hedgehog pathway, PTCH1 was mutated in 15 of
Notably, however, the pathways most highly
enriched for genetic alterations had not previously
been implicated in MB. These involved genes re-
sponsible for chromatin remodeling and transcrip-
tional regulation, particularly the histone-lysine
N-methyltransferase MLL2. Eighteen of the 88
these pathways or in a related gene member: the
of chromatin members SMARCA4 (3 tumors) and
ARID1A (1 tumor); and the histone lysine deme-
thylase KDM6B (1 tumor). The mutations in these
alterations. In MLL2, for example, 8 of the 12 mu-
proteins as a result of nonsense mutations, out-of-
frame indels, or splice site mutations. In contrast,
only 32 of the 222 mutations (14%) not affecting
pathways (PTCH1, CTNNB1, MLL2, MLL3,
SMARCA4, ARID1A, and KDM6B) resulted in
predicted protein truncations (P < 0.001, Fisher’s
of the 15 mutations in the two histone methyl-
transferase genes would cause truncations is very
small (P < 0.001, binomial test). All truncating mu-
tations in MLL2 and MLL3 were predicted to result
in protein products lacking the key methyltrans-
ferase domain (Fig. 2). These data not only provide
on the basis of genetic criteria, tumor suppressor
genes that are inactivated by mutation.
Discussion. These data provide a comprehen-
sive view of a solid tumor arising in children. The
most impressive difference between this tumor type
and those affecting adults is the number of genetic
predicted on the basis of previous evidence (27). In
fact, at the karyotypic level, the incidence of chro-
as that in adult solid tumors [reviewed in (27)].
What does the smaller number of mutations
reveal about the tumorigenesis of MBs? Most
mutations observed in adult tumors are predicted
to be passenger alterations (19). Passenger muta-
records the number of divisions that a cell has
undergone during both normal development and
ber is linearly related to the number of passenger
mutations detected in a tumor (28). This concept is
between increasing patient age and the number of
observed for both the mutations detected in the
P < 0.01) and the number of alterations observed
(tables S8 and S9). Even if we assume that all but
one of the mutations in each MB is a passenger,
the number of passenger mutations in MBs is still
mutations in adult solid tumors (16–19), implying
that a smaller number of cell divisions is required
to reach clinically detectable tumor size in MBs.
These data therefore suggest that fewer driver mu-
tations are required for MB tumorigenesis and that
driver mutations in MB confer a greater selective
advantage than those of adult solid tumors.
Previously, most insights into the molecular
basis of MB emerged from the study of hereditary
tumor syndromes (27), including Gorlin syndrome,
caused by germline mutations of PTCH1; Turcot
syndrome, caused by germline mutations of APC;
and Li-Fraumeni syndrome, caused by germline
mutations of TP53. In our study, we found both
PTCH1 and TP53 to be somatically mutated in
Table 2. Medulloblastoma CAN-genes.*
*CAN-genes were defined as those having at least two nonsilent alterations in the samples analyzed. Passenger
probabilities were calculated as described in (21). The denominators refer to the number of tumors evaluated: 88 tumors
were sequenced for mutations, and 23 tumors were analyzed for copy number alterations.
22 / 88
12 / 88
11 / 88
6 / 88
0 / 88
3 / 88
0 / 88
3 / 88
3 / 88
0 / 23
0 / 23
0 / 23
0 / 23
3 / 23
0 / 23
2 / 23
0 / 23
0 / 23
0 / 23
0 / 23
0 / 23
0 / 23
0 / 23
0 / 23
0 / 23
0 / 23
0 / 23
Fig. 2. Somatic mutations in MLL2 and MLL3 genes. Nonsense mutations and out-of-frame insertions and
deletions are indicated as red arrows; missense mutations are indicated as black arrows. PHD, plant
homeodomain finger; HMG, high mobility group box; FYRN, FY-rich N-terminal domain; FYRC, FY-rich C-
terminal domain; SET, Su(var)3-9 Enhancer-of-zeste Trithorax methyltransferase domain.
VOL 33128 JANUARY 2011
on March 9, 2011
to those observed in earlier studies. We also
previously implicated in MB (5–7).
The ability to investigate the sequence of all
coding genes in MBs has also revealed mutated
genes not previously implicated in MBs (table S4).
Among these, MLL2 and MLL3 were of greatest
interest, because the frequency of inactivating mu-
with functional studies showing that knock-out of
murine MLL3 results in ureteral epithelial cancers
(29). These genes are large and have been reported
in the Catalogue of Somatic Mutations in Cancer
cers, but not at a sufficiently high frequency to dis-
tinguish them from passenger alterations (and with
no evidence of a high fraction of inactivating muta-
tions of MLL2 have recently been identified as a
disorder without known cancer predisposition (31).
The general role of genes controlling histone
inactivating mutations of the histone H3K27 de-
myelomas, esophageal cancers, and renal cell can-
cancers contain mutations in the histone methyl-
transferase gene SETD2 and the histone demethy-
lase gene JARID1C (33), and the histone
methyltransferase gene EZH2 has been found to
be mutated in non-Hodgkin’s lymphomas (34).
Most recently, frequent mutations of the chromatin
remodeling gene ARID1A have been discovered in
ovarian clear cell carcinomas (20, 35); of note, one
ARID1A mutation was discovered in our MB pa-
genes (although not MLL2 or MLL3) and MB has
also previously been hypothesized based on the
observation that copy number alterations affecting
chromosomal regions containing histone methyl-
transferases or demethylases occur in a subset of
The mechanism(s) through which MLL genes
clues can be gleaned from the literature. The MLL
and SET1B) (37). MLL family genes have been
and an attractive possibility is that they normally
down-regulate OTX2,an MB oncogene (6, 7,40).
Another possibility is suggested by the observation
that b-catenin brings MLL complexes to the en-
hancers of genes regulating the Wnt pathway, there-
differentiation (42) and that their disruption may
lead to aberrant proliferation of precursor cells.
The identification of MLL2 and MLL3 as fre-
that MB is fundamentally characterized by dys-
regulation of core developmental pathways (43).
TP53, MYC, and PTEN) were also identified in
these childhood tumors, our sequence analysis
normal developmental processes, such as MLL
family genes and Hedgehog and Wnt pathway
genes, were much more frequent. The fact that a
relatively small number of somatic mutations is
sufficient for MB pathogenesis as compared to
adult solid tumors provides further evidence that
the temporally restricted subversion of normal
cerebellar development is critical in the develop-
ment of these tumors. This is consistent with the
observation that the incidence of MB decreases
markedly after childhood, with the tumors be-
coming quite rare after the age of 40 years (1). It
will be interesting to determine whether genetic
alterations in developmental pathways are a key
feature of all childhood malignancies.
risk-adapted therapy to patients is a primary goal of
current MB research. The designation of specific
prognostic value. For example, large-cell/anaplastic
MBs, which are aggressive tumors often associ-
ated with MYC amplification, carry a relatively
poor prognosis (44),whereas desmoplastic MBs,
which frequently have alterations of PTCH1 or
other Hedgehog pathway genes (4), are more
revealed that these histologic subtypes are bio-
logically heterogeneous (3); in addition, most MBs
are of the classic subtype and do not have defining
molecular alterations. Our results add an addi-
Although activation of the Wnt and Hedgehog
pathways are generally considered to define two
MB subtypes (3), our data revealed that these
groups overlap, because two adult MBs were
found to contain mutations of both PTCH1 and
mutations do not appear exclusive to any known
subset of MBs: Mutations were identified in both
pediatric and adult MBs and were found in all
histologic subtypes(althoughthey weremostcom-
mon in large-cell/anaplastic MBs) (Table 3 and
tables S9 and S10). In addition, the frequency of
genes in larger number of MBs that have been
clarify the molecular classification of this tumor.
number of driver mutations, and in our cohort, the
Table 3. Characteristics of medulloblastomas with mutations in MLL2-related genes.*
*All genes reported in the table were determined to be wild type unless otherwise indicated.
28 JANUARY 2011VOL 331
on March 9, 2011
gene set most highly enriched for alterations in-
cluded MLL2. However, there are several limi-
tations to our study. Although in a few cases we
have identified two or three bona fide cancergenes
that are mutated in individual MBs, other cases
show no mutations of any known cancer gene and
only one alteration of any gene (Fig. 1 and table
S4). Several explanations for the relative absence
of genetic alterations in occasional MBs can be
offered. First, despite the use of classic Sanger se-
quencing, a small fraction of the exome cannot be
or of homology to highly related genes. Second, it
of the genome could occur, and these would not
be detected. Third, copy-neutral genetic transloca-
fications, or homozygous deletions. Fourth, it is
possible that low copy number gains or loss-of-
heterozygosity (LOH) of specific regions contain-
ing histone-modifying genes could mimic the
it is possible that heritable epigenetic alterations
are responsible for initiating some MBs. The last
explanation, involving covalent changes in chro-
matin proteins and DNA, is intriguing given the
new data on MLL2 in this tumor type. It should
thus be informative to characterize the methyla-
tion status of histones and DNA in MBs with and
without MLL2/MLL3 gene alterations, as well as
todeterminetheexpression changes resulting from
these gene mutations. These data highlight the im-
portant connection between genetic alterations in
the cancer genome and epigenetic pathways and
provide potentially new avenues for research and
disease management in MB patients.
References and Notes
1. F. Giangaspero et al., in WHO Classification of the
Central Nervous System, H. O. D. N. Louis, O. D. Wiestler,
W. K. Cavenee, Eds. (WHO Press, Lyon, France, 2007).
2. W. R. Polkinghorn, N. J. Tarbell, Nat. Clin. Pract. Oncol.
4, 295 (2007).
3. P. A. Northcott et al., J. Clin. Oncol., published online
7 September 2010; 10.1200/JCO.2009.27.4324
4. M. C. Thompson et al., J. Clin. Oncol. 24, 1924 (2006).
5. S. H. Bigner et al., Cancer Res. 50, 2347 (1990).
6. K. Boon, C. G. Eberhart, G. J. Riggins, Cancer Res. 65,
7. C. Di et al., Cancer Res. 65, 919 (2005).
8. R. L. Saylors 3rd et al., Cancer Res. 51, 4721 (1991).
9. L. Ding et al., Nature 464, 999 (2010).
10. W. Lee et al., Nature 465, 473 (2010).
11. E. R. Mardis et al., J. Med. 361, 1058 (2009).
12. E. D. Pleasance et al., Nature 463, 191 (2009).
13. E. D. Pleasance et al., Nature 463, 184 (2010).
14. S. P. Shah et al., Nature 461, 809 (2009).
15. T. J. Ley et al., Nature 456, 66 (2008).
16. T. Sjoblom et al., Science 314, 268 (2006).
17. L. D. Wood et al., Science 318, 1108 (2007).
18. S. Jones et al., Science 321, 1801 (2008).
19. D. W. Parsons et al., Science 321, 1807 (2008).
20. S. Jones et al., Science 330, 228 (2010).
21. Materials and methods are available as supporting
material on Science Online.
22. C. Greenman et al., Nature 446, 153 (2007).
23. T. Soussi, C. Béroud, Hum. Mutat. 21, 192 (2003).
24. R. J. Leary et al., Proc. Natl. Acad. Sci. U.S.A. 105, 16224
25. H. Carter et al., Cancer Res. 69, 6660 (2009).
26. S. M. Boca et al., Genome Biol. 11, R112 (2010).
27. P. A. Northcott, J. T. Rutka, M. D. Taylor, Neurosurg. Focus
28, E6 (2010).
28. N. Beerenwinkel et al., PLOS Comput. Biol. 3, e225
29. J. Lee et al., Proc. Natl. Acad. Sci. U.S.A. 106, 8513
30. S. A. Forbes et al., Nucleic Acids Res. 38, D652 (2010).
31. S. B. Ng et al., Nat. Genet. 42, 790 (2010).
32. G. van Haaften et al., Nat. Genet. 41, 521 (2009).
33. G. L. Dalgliesh et al., Nature 463, 360 (2010).
34. R. D. Morin et al., Nat. Genet. 42, 181 (2010).
35. K. C. Wiegand et al., N. Engl. J. Med. 363, 1532
36. P. A. Northcott et al., Nat. Genet. 41, 465 (2009).
37. M. Vermeulen, H. T. M. Timmers, Epigenomics 2, 395
38. K. I. Ansari, S. S. Mandal, FEBS J. 277, 1790 (2010).
39. K. Agger et al., Nature 449, 731 (2007).
40. D. C. Adamson et al., Cancer Res. 70, 181 (2010).
41. J. Sierra, T. Yoshida, C. A. Joazeiro, K. A. Jones, Genes Dev.
20, 586 (2006).
42. D. A. Lim et al., Nature 458, 529 (2009).
43. R. J. Gilbertson, D. W. Ellison, Annu. Rev. Pathol. 3,
44. C. G. Eberhart et al., Cancer 94, 552 (2002).
45. We thank J. Ptak, N. Silliman, L. Dobbyn, and M. Whalen
for technical assistance with sequencing analyses, and
M. Ehinger, D. Satterfield, E. Lipp, D. Lister, and
M. J. Dougherty for help with sample preparation and
data collection. This project has been funded in part by the
National Cancer Institute, National Institutes of Health,
under contract HHSN261200800001E. The content of this
publication does not necessarily reflect the views or policies
of the Department of Health and Human Services, nor
does mention of trade names, commercial products, or
organizations imply endorsement by the U.S. government.
This work was supported by the Virginia and D. K. Ludwig
Fund for Cancer Research, Alex’s Lemonade Stand
Foundation, the American Brain Tumor Association, the
Brain Tumor Research Fund at Johns Hopkins, the Hoglund
Foundation, the Ready or Not Foundation, the Children’s
Brain Tumor Foundation, the Pediatric Brain Tumor
Foundation Institute, the David and Barbara B. Hirschhorn
Foundation, American Association for Cancer Research
Stand Up To Cancer Dream Team Translational Cancer
Research Grant, Johns Hopkins Sommer Scholar Program,
NIH grants CA121113, CA096832, CA057345, CA118822,
CA135877, and GM074906-01A1/B7BSCW, NSF grant
DBI 0845275, and DOD NDSEG Fellowship 32 CFR 168a.
D.W.P. is a Graham Cancer Research Scholar at Texas
Children’s Cancer Center. Under licensing agreements
between the Johns Hopkins University and Beckman
Coulter, B.V., K.W.K., and V.E.V. are entitled to a share of
royalties received by the university on sales of products
related to research described in this paper. N.P., B.V.,
K.W.K., and V.E.V are cofounders of Inostics and Personal
Genome Diagnostics and are members of their Scientific
Advisory Boards. N.P., B.V., K.W.K., and V.E.V. own Inostics
and Personal Genome Diagnostics stock, which is subject
to certain restrictions under university policy. The terms of
these arrangements are managed by Johns Hopkins
University in accordance with its conflict-of-interest policies.
Supporting Online Material
Materials and Methods
Tables S1 to S10
21 September 2010; accepted 8 December 2010
Published online 16 December 2010;
Rotational Symmetry Breaking
in the Hidden-Order Phase of URu2Si2
R. Okazaki,1* T. Shibauchi,1† H. J. Shi,1Y. Haga,2T. D. Matsuda,2E. Yamamoto,2
Y. Onuki,2,3H. Ikeda,1Y. Matsuda1
A second-order phase transition is characterized by spontaneous symmetry breaking. The nature
of the broken symmetry in the so-called “hidden-order” phase transition in the heavy-fermion
compound URu2Si2, at transition temperature Th= 17.5 K, has posed a long-standing mystery.
We report the emergence of an in-plane anisotropy of the magnetic susceptibility below Th, which
breaks the four-fold rotational symmetry of the tetragonal URu2Si2. Two-fold oscillations in the
magnetic torque under in-plane field rotation were sensitively detected in small pure crystals.
Our findings suggest that the hidden-order phase is an electronic “nematic” phase, a
translationally invariant metallic phase with spontaneous breaking of rotational symmetry.
second-order phase transition generally
causes a change in symmetry, such as ro-
tational, gauge, or time-reversal symmetry.
An order parameter can then be introduced to
describe the low-temperature ordered phase with
a reduced symmetry. The heavy-fermion com-
pound URu2Si2undergoes a second-order phase
transition at Th= 17.5 K, which is accompanied
by large anomalies in thermodynamic and trans-
port properties (1–3). Because the nature of the
associated order parameter has not been eluci-
dated, the low-temperature phase is referred to
as the hidden-order phase. It is characterized by
several remarkable features. No structural phase
transition is observed at Th. A tiny magnetic
moment appears (M0≈ 0.03mB, where mBis the
Bohr magneton) below Th(4), but it is far too
1Department of Physics, Kyoto University, Kyoto 606-8502,
Japan.2Advanced Science Research Center, Japan Atomic
Energy Agency, Tokai 319-1195, Japan.3Graduate School
of Science, Osaka University, Toyonaka, Osaka 560-0043,
*Present address: Department of Physics, Nagoya Univer-
sity, Nagoya 464-8602, Japan.
†To whom correspondence should be addressed. E-mail:
VOL 33128 JANUARY 2011
on March 9, 2011