Discovery and prioritization of somatic mutations
in diffuse large B-cell lymphoma (DLBCL) by
Jens G. Lohra,b, Petar Stojanova,b, Michael S. Lawrencea, Daniel Auclaira, Bjoern Chapuyb, Carrie Sougneza,
Peter Cruz-Gordilloa, Birgit Knoechela,b,c, Yan W. Asmannd, Susan L. Slagerd, Anne J. Novakd, Ahmet Dogand,
Stephen M. Anselld, Brian K. Linke, Lihua Zoua, Joshua Goulda, Gordon Saksenaa, Nicolas Stranskya,
Claudia Rangel-Escareñof, Juan Carlos Fernandez-Lopezf, Alfredo Hidalgo-Mirandaf, Jorge Melendez-Zajglaf,
Enrique Hernández-Lemusf, Angela Schwarz-Cruz y Celisf, Ivan Imaz-Rosshandlerf, Akinyemi I. Ojesinaa, Joonil Junga,
Chandra S. Pedamallua, Eric S. Landera,g,h,1, Thomas M. Habermannd, James R. Cerhand, Margaret A. Shippb,
Gad Getza, and Todd R. Goluba,b,g,i
aEli and Edythe Broad Institute, Cambridge, MA 02412;bDana–Farber Cancer Institute, Boston, MA 02115;dMayo Clinic College of Medicine, Rochester,
MN 55902;cChildren’s Hospital Boston, Boston, MA 02115;eUniversity of Iowa College of Medicine, Iowa City, IA 52245;fInstituto Nacional de Medicina
Genómica, 14610 Mexico DF, Mexico;gHarvard Medical School, Boston, MA 02115;hMassachusetts Institute of Technology, Cambridge, MA 02142;
andiHoward Hughes Medical Institute, Chevy Chase, MD 20815
Contributed by Eric S. Lander, December 29, 2011 (sent for review November 22, 2011)
To gain insight into the genomic basis of diffuse large B-cell
lymphoma (DLBCL), we performed massively parallel whole-exome
sequencing of 55 primary tumor samples from patients with DLBCL
and matched normal tissue. We identified recurrent mutations in
genes that are well known to be functionally relevant in DLBCL,
including MYD88, CARD11, EZH2, and CREBBP. We also identified
somaticmutationsin genesfor which a functional role in DLBCLhas
not been previously suspected. These genes include MEF2B, MLL2,
that BCL2 mutations commonly occur in patients with BCL2/IgH
rearrangements as a result of somatic hypermutation normally
occurring at the IgH locus. The BCL2 point mutations are primarily
synonymous, and likely caused by activation-induced cytidine de-
aminase–mediated somatic hypermutation, as shown by compre-
Those nonsynonymous mutations that are observed tend to be
found outside of the functionally important BH domains of the
protein, suggesting that strong negative selection against BCL2
loss-of-function mutations is at play. Last, by using an algorithm
designed to identify likely functionally relevant but infrequent
mutations, we identify KRAS, BRAF, and NOTCH1 as likely drivers
of DLBCL pathogenesis in some patients. Our data provide an un-
may point toward new therapeutic strategies for the disease.
next-generation sequencing|human genetics|activation-induced
Hodgkin lymphoma that affects 30,000 new patients in the
United States every year (1, 2). The standard of care for the
treatment of most cases of DLBCL is the R-CHOP regimen (rit-
uximab, cyclophosphamide, doxorubicin, vincristine, and predni-
sone) consisting of multiagent chemotherapy plus a therapeutic
antibody directed against CD20, a marker of B lymphocytes. The
3-year event-free survival rate is approximately 60%, with the
majority of the remaining 40% dying of their disease (3). To date,
treatment strategies to improve outcome have largely included
increased doses of standard agents in the context of autologous
stem cell transplantation (4). Therefore, there is a great medical
need to define the genetic abnormalities that are associated with
DLBCL to define novel targets for therapy.
Germinal centers (GCs) in lymphoid tissues are sites of clonal
expansion and editing of the Ig receptor in B lymphocytes, and
this GC reaction is a physiological component of the humoral im-
mune response. Somatic hypermutation (SHM) is part of the GC
reaction, and its dysregulation contributes to the accumulation of
iffuse large B-cell lymphoma (DLBCL) is an aggressive non-
somatic mutations in oncogenes and tumor-suppressor genes in
Traditionally, DLBCL has been classified by the morphology
and immunophenotype of the malignant B-cells but more re-
cently, molecular classifications have been reported. Specifically,
gene expression-based classification of DLBCL has been pro-
posed (5, 6), and the prognostic relevance for this has been
demonstrated (7). It has been suggested that distinct signal
transduction pathways are affected in the subtypes that are de-
fined in this way, and that certain genetic defects preferentially
occur in specific subtypes defined by the presumed cell of origin
of the tumors (8–12).
However, comprehensive understanding of the genomic land-
scape of DLBCL is lacking. In particular, a key question is which
mutations and pathways drive DLBCL pathogenesis. We report
here the unbiased sequencing of all protein-coding exons in 55
DLBCL patients, comparing each to its patient-matched normal
control. We uncover mutations that provide insights into mech-
anisms of lymphomagenesis.
Whole-Exome Sequencing Reveals Recurrent Mutations in DLBCL. We
performed solution-phase hybrid capture and whole-exome se-
quencing on paired tumor and germline (i.e., normal) DNA
samples from 55 patients with primary DLBCL. We achieved
150-fold mean sequence coverage of targeted exonic regions,
with an average of 97% of bases covered per patient (range, 91–
98%). Such high coverage is important because tumor samples
are often contaminated with normal cells (e.g., fibroblasts, im-
mune cells), which can obscure the identification of somatically
mutated alleles unless very deep coverage is achieved.
We excluded six samples from further analysis because of
extremely low apparent mutation rates, most consistent with
extensive stromal contamination. Of the remaining 49 patients,
Author contributions: J.G.L., P.S., M.S.L., E.S.L., T.M.H., J.R.C., M.A.S., G.G., and T.R.G.
designed research; J.G.L., D.A., C.S., and P.C.-G. performed research; P.S., M.S.L., Y.W.A.,
S.L.S., A.J.N., A.D., S.M.A., B.K.L., L.Z., J.G., G.S., N.S., A.I.O., J.J., and C.S.P. contributed new
reagents/analytic tools; J.G.L., P.S., M.S.L., B.C., C.S., B.K., C.R.-E., J.C.F.-L., A.H.-M., J.M.-Z.,
E.H.-L., A.S.-C.y.C., and I.I.-R. analyzed data; and J.G.L., P.S., M.S.L., B.K., M.A.S., G.G., and
T.R.G. wrote the paper.
The authors declare no conflict of interest.
Freely available online through the PNAS open access option.
Data deposition: The sequence reported in this paper has been deposited in the dbGAP
database, www.ncbi.nlm.nih.gov/gap (accession no. phs000450.v1.p1).
1To whom correspondence should be addressed. E-mail: firstname.lastname@example.org.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.
| March 6, 2012
| vol. 109
| no. 10
the mean nonsynonymous mutation rate was 3.2 mutations per
megabase, with mutation rates varying widely (0.6–8.7 mutations
per megabase), which is higher than the estimated mutation rate
in other hematopoietic malignancies, such as chronic lympho-
cytic leukemia and other leukemias (<1 per megabase) (13, 14),
and multiple myeloma (1.3 per megabase) (15) (Fig. 1A). There
was no correlation between patient-specific mutation rate and
frequency of particular types of mutation (e.g., *CpG→T, Cp(A/
C/T)→T, A→G, transversions, or indels; Fig. 1C). Similarly,
there was no correlation between observed mutation rate and
average allelic fraction of those mutations observed in each pa-
tient, suggesting that the variation in mutation rate was not
simply a function of variability in extent of stromal contamina-
tion (Fig. S1).
To define significantly mutated genes in DLBCL, we applied
the MutSig algorithm to identify genes harboring mutations at
a higher frequency than expected by chance (15, 16). To better
estimate the significance of observed mutations, MutSig takes into
account (i) the sample-specific mutation rate, (ii) the ratio of
nonsynonymous to synonymous mutations in a given gene, and
(iii) the median expression level of each gene in DLBCL [based
on gene expression profiling datasets (7)]. This approach revealed
58 statistically significant genes with a false discovery rate cutoff
of 0.1 (q1≤ 0.1; Fig. 1B, Table 1, and Tables S1 and S2). We
independently validated selected mutations by targeted rese-
quencing in a subset of patients and obtained 97.9% validation
rate (Table S5).
Among the significantly mutated genes were those for which a
functional role in the pathogenesis of DLBCL has accumulated
over many years. These include CD79B, TP53, CARD11, MYD88,
and EZH2 (8–11). In addition, we discovered mutations in genes
for which a pathogenic role in DLBCL has been suggested re-
cently (17, 18). These include MLL2, TNFRSF14, BTG1,MEF2B,
and GNA13, which are discussed in greater detail later.
We discovered mutations in genes not previously recognized
as drivers of cancer. For example, we found β-actin (ACTB)
mutations in five patients (Fig. 2). Actins are highly conserved
proteins of the cytoskeleton and are involved in B lymphocyte
activation (19). By using the xvar algorithm (based on evolu-
tionary conservation and the nature of the observed amino acid
change), the predicted functional consequence of the ACTB
mutations observed in DLBCL is high. We also note a pre-
ponderance of ACTB mutations toward the amino terminus
of the protein, but the functional significance of this remains
Another unexpectedly recurrently mutated gene is P2RY8,
encoding a G protein-coupled purinergic receptor whose normal
function has not been extensively characterized (20). P2RY8 is
most notable for its involvement in a chromosomal translocation
with CRLF2 in 7% of patients with B-progenitor acute lympho-
blastic leukemia (ALL) and 53% of individuals with ALL and
Down syndrome (21). The presumed mechanism of action of such
P2RY8/CRLF2 fusions is activation of CRLF2 by its coming under
the control of the P2RY8 promoter, which is highly active in B
lymphoid cells (21). However, we note that P2RY8 has itself been
reported to function as an oncogene in experimental models (22).
In DLBCL, we identified six patients with coding mutations in
P2RY8, two of whom harbored two mutations (Fig. 2). In three
patients, the observed allelic fraction of these mutations is greater
than 0.5, suggestive of deletion of the WT allele or amplification
of the mutant allele. The functional consequence of P2RY8
mutation in DLBCL remains to be determined.
We also observed very common mutations in the gene PCLO
(Piccolo), encoding a protein that functions as part of the pre-
synaptic cytoskeletal matrix thought to be involved in regulating
neurotransmitter release (23). A role for PCLO in calcium
sensing has also been suggested (24), but a role in cancer has not
been reported. We found a total of 23 nonsynonymous mutations
in 17 patients (35%; Fig. S2), but the observed ratio of non-
synonymous to synonymous mutations (23:3) is consistent with
that expected by chance, given that most of the observed muta-
tions (12 of 23) are transversion mutations, which favor non-
synonymous outcomes by a ratio of nearly 5:1. It is thus possible
that, for unknown reasons, the local rate of mutation at the
megabase, with individual DLBCL samples ranked by total number of mutations. (B) The heat map represents individual mutations in 49 patient samples,
color-coded by type of mutation. Only one mutation per gene is shown if multiple mutations were found in a sample. Left: Histogram shows the number of
mutations in each gene. Percentages represent the fraction of tumors with at least one mutation in the specified gene. Right: The 15 genes with the lowest
q1-value, ranked by level of significance. (C) Base substitution distribution of individual samples, ranked in the same order as in A.
Significantly mutated genes in 49 patients with DLBCL. (A) The rate of synonymous and nonsynonymous mutations is displayed as mutations per
| www.pnas.org/cgi/doi/10.1073/pnas.1121343109Lohr et al.
PCLO locus is unusually high, giving rise to passenger mutations
of no functional consequence in DLBCL. Additional work is
clearly needed to resolve the role, if any, of PCLO mutations in
DLBCL and other cancers.
Histone 1 (H1) family proteins are linker histone proteins that
bind to the DNA entering and exiting the nucleosomal cores.
Different forms are expressed at different stages of the cell cycle
and possibly transcription (25). We observed a striking accumu-
lation ofmutations in H1family proteins, with 59 nonsynonymous
and 35 synonymous mutations among 31 histone H1 proteins in
34 patients (69%; Table S2). The functional significance of these
mutations remainstobeexplored, buthotspotanalysisasoutlined
later suggests that HIST1H3B and possibly other core histone
proteins are subject to activation-induced cytidine deaminase
We also identified mutations in genes that were recently
reported to be significantly mutated (17, 18). MLL2 is a histone
methyltransferase of the SET1 family that is responsible for his-
tone H3-lysine 4 trimethylation (H3K4me3) during oogenesis
and early development (26). Inactivating mutations have been
reported in medulloblastoma (27) and multiple myeloma (15),
and chromosomal translocations involving the MLL family
member MLL1 are well described in acute leukemias (28). The
MLL2 mutations we observed in DLBCL are highly biased to-
ward truncating events, the large majority being nonsense muta-
tions and frameshift-inducing insertions and deletions (Fig. 2). As
has been suggested previously, our data suggest that MLL2 may
function as an important tumor suppressor in DLBCL (17, 29).
TNFRSF14, also known as LIGHT Receptor, belongs to the
TNF-receptor superfamily most extensively studied in T cells.
Interestingly, it can convey opposing signals based on its speci-
ficity for diverse ligands. In our data, five of nine mutations
suggest loss of function (n = 4 nonsense mutations and n = 1
frameshift deletion), with an additional in-frame insertion and
three missense mutations. No synonymous mutations were seen
(Fig. 2). As has been suggested, these results strongly suggest
a tumor-suppressive role of TNFRSF14 in DLBCL (17). It has
been proposed that LIGHT-mediated triggering of TNFRSF14
renders B-cell lymphomas more immunogenic and sensitive to
in clusters and at conserved sites
Significantly mutated genes and genes with mutations
GenesMutations Patients Sites Silentq1
1.22 × 10-10
1.22 × 10-10
1.22 × 10-10
1.22 × 10-10
1.36 × 10-10
4.95 × 10-9
1.83 × 10-8
5.95 × 10-8
1.92 × 10-7
2.90 × 10-7
5.51 × 10-7
1.35 × 10-6
6.65 × 10-6
<1 × 10-6
<1 × 10-6
<1 × 10-6
GenesMutations Patients Sites Silentq1
Two algorithms were used to prioritize significantly mutated genes. The
top 58 genes, reflected by q-values (q1) of 0.1 or lower, are determined by
analyzing the frequency of somatic mutations across samples, corrected for
gene length, the sample-specific mutation rate, the nonsynonymous/synon-
ymous mutation ratio, and expression of these genes in independent DLBCL
datasets. The remainder of the list represents genes that have a q1-value
greater than 0.1, but are significant by an independent analysis that identi-
fies genes that may be functionally relevant based on clustering of mutations
and evolutionary sequence conservation (q2≤ 0.1). Genes for which q1- and
q2-value are listed are prioritized by both algorithms. Mutations, number of
nonsynonymous mutations in this gene across the individual set; patients,
number of patients with at least one nonsynonymous mutation; sites, num-
ber of unique sites with a nonsynonymous mutation; silent, number of silent
(i.e., synonymous) mutations in this gene across the individual set.
Lohr et al.PNAS
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FAS-induced apoptosis (30)—a potential mechanism by which
TNFRSF14 can act as a tumor suppressor.
Mutations in BTG1 were also observed to be relatively com-
mon (15 nonsynonymous and two synonymous mutations). BTG1
belongs to the BTG/Tob family of proteins that regulate cell cycle
progression in a variety of cells. BTG1 is thought to confer DNA
binding of sequence-specific transcription factors (31). Whether
mutations in BTG1 result in aberrations in chromatin structure
(as with MLL-family mutations) as opposed to nonhistone targets
remains to be determined. Interestingly, we observed several
patients with more than one mutation in BTG1, including two
patients with three mutations and one patient with four muta-
tions. In the latter patient, two sets of adjacent mutations (L37L
plus L31F and P3R plus M1I) were never found in the same se-
quencing read, suggesting that they occurred on different alleles,
i.e., in trans. We note that two patients had the identical silent
mutation at codon 31, suggesting that this mutation, although
it did not affect protein coding sequence, may alter codon use
or mRNA stability. Overall, the nature of BTG1 mutations does
not clearly point toward a gain-of-function or loss-of-function
mechanism, although the biallelic involvement seen in some
patients tends to favor loss of function (Fig. 2).
MEF2B mutations were observed in 18% of patients with
DLBCL,similar todata reported recently (17,18), predominantly
in the MADS box or MEF2 domains. MEF2B belongs to a family
of calcium-regulated transcription factors that recruit histone-
modifying enzymes. Further supporting an oncogenic role for
MEF2 proteins, MEF2C has been identified as a T-cell acute
lymphoblastic leukemia oncogene that is activated by chromo-
somal rearrangement (32).
Negative Selection Against Deleterious BCL2 Mutations. A hallmark
of cancer genes (i.e., genes that harbor “driver” mutations, which
contribute to the formation and progression of cancer) is the
preponderance of nonsynonymous mutations compared with
synonymous mutations (typicallywith anexpectedratio of ∼2.8:1).
Curiously, we observed a striking opposite effect in the BCL2
gene—a known driver in some DLBCLs. We observed a very high
mutation rate in BCL2, but with a depletion of nonsynonymous
mutations, with 18 nonsynonymous mutations and 28 synonymous
mutations, for a ratio of 0.64, far below that expected by chance
(P = 8.8 × 10−6; Fig. 3). We hypothesized that this phenomenon
at the BCL2 locus occurring via SHM, and second, negative se-
lection against functionally deleterious mutations.
We first explored the possibility that the high rate of BCL2
mutations observed in our patients might be related to SHM. This
physiologic process in B lymphocytes has been best studied at Ig
gene loci, where it facilitates the development of antibody di-
versity (33), but other genes have been shown to be subject to
aberrant SHM (including the PIM1 gene, in which we also ob-
served hypermutation with 30 mutations in 16 patients; Fig. S2)
(34). Chromosomal translocations of the BCL2 gene into the Ig
heavy chain (IgH) locus occur in approximately 20% of DLBCL
tumors, and the resulting BCL2 overexpression provides an
antiapoptotic signal to the lymphoma cells (35). We hypothesized
that BCL2 hypermutation in our patients might be explained by
the BCL2 gene adopting the IgH locus’s normal process of SHM
as a result of the translocation (36). If this hypothesis were cor-
rect, those tumors with elevated BCL2 mutation rates would be
expected to also harbor BCL2/IgH translocations. We tested for
BCL2/IgH translocation in 26 patients with DLBCL (13 with
BCL2 mutation and 13 others selected randomly). As predicted,
the vast majority of patients with BCL2 hypermutation (10 of 13,
77%) had BCL2/IgH translocation, whereas only one of 13
patients (8%) lacking BCL2 mutation had the translocation (P =
0.0005, one-sided Fisher exact test; Fig. S3). To determine
whether BCL2 or other genes may be targets of SHM, which is
mediated by AID, we asked whether mutations occur preferen-
tially in the context of WRCY motifs, which are known target
sequences of AID. This analysis indeed revealed that BCL2, as
well as other genes, including PIM1, have significant enrichment
of mutations in WRCY motifs (Table S3).
Although these results likely explain the hypermutation at the
BCL2 locus, they do not explain the preponderance of synony-
mous mutations observed in these patients. We hypothesized
that they represent a vestige of negative selection against dele-
terious mutations in BCL2, on which the tumor cells are de-
pendent for survival. If this hypothesis were correct, we would
expect that any nonsynonymous mutations would be confined to
functionally nonessential domains of the protein, whereas the
synonymous mutations would not. To address this, we focused on
the BCL2 BH domains that mediate interactions with proa-
poptotic proteins (37). We observed 18 nonsynonymous muta-
tions, but only three of these fell within BH domains, whereas
15 of 28 synonymous mutations fell within BH domains (Fig. 3).
We used permutations to determine the probability of non-
synonymous mutations being located within versus outside BH
domains, corrected for domain size. To increase the power of
this analysis, we included the BCL2 mutations observed in the
present study and those recently reported (17). This analysis
indicated a significant enrichment of nonsynonymous mutations
falling outside of BH domains (P = 0.041). These results argue
that the nonsynonymous mutations preserve BCL2 function by
avoiding critical BH domains. On the contrary, we found the
synonymous mutations to be preferentially located within BH
domains (P = 0.02). This can be explained by nonuniform dis-
tribution of these mutations along the gene (P = 0.045) with
preferential clustering at the 5′ end. This is consistent with
previous demonstrations of aberrant SHM preferentially occur-
ring closer to the 5′ end (34).
Our results are most consistent with purifying selection (i.e.,
negative selection) against mutations that inhibit or decrease
BCL2 function. Such mutations likely result in loss of or
somatic mutations in significantly mutated genes called by analysis pipeline
and passing manual review. A diagram of the relative positions of somatic
mutations is shown for MLL2, TNFRSF14, BTG1, MEF2B, ACTB, and P2RY8.
The type of the mutation is indicated in the key (Bottom). The overall vali-
dation rate of mutation calls was 97.9% [of 47 selected mutations tested,
only one (ACTB G20A) failed to validate; see Table S5].
Somatic mutations in DLBCL affect genes of various classes. Sites of
| www.pnas.org/cgi/doi/10.1073/pnas.1121343109Lohr et al.
impaired tumor cell viability, leaving behind only those muta-
tions that are synonymous or that affect nonrelevant domains.
Interestingly, we note the presence of recurrent synonymous
mutations at codons N11 and K22 (Fig. 3), suggesting a prefer-
ence for certain sites to acquire mutations. Whether there is
a functional consequence of these synonymous mutations, for
example by affecting mRNA stability, remains to be determined.
Identifying Functionally Relevant but Rare Mutations. The preceding
sections focused on the identification of cancer genes based on
their mutation frequency across the whole genome. However,
additional genes may harbor functionally important mutations
that fall short of statistical significance (in the standard mutation
frequency test) given the modest size of our dataset. Some of
these genes are recognizable based on their known importance
in the pathogenesis of other malignancies. For example, we ob-
served two mutations in KRAS (G13D), four mutations in
NOTCH1, and two mutations in BRAF, often involving specific
amino acids documented to be sites of recurrent mutation in the
Catalogue of Somatic Mutations in Cancer (COSMIC) database.
It therefore seems likely that these mutations similarly play
a causal role in DLBCL, albeit at a low frequency. To perform
this search in a rigorous manner, we also tested each gene
whether it has an increased mutation rate only in sites previously
reported in the COSMIC database. Table S4 shows a list of the
most significant genes identified by this test.
We also sought to prioritize rare mutations based on the
clustering of mutations within particular regions of the coding
sequence. Mutations occurring by chance (i.e., passenger muta-
tions) would be expected to be scattered randomly across the
protein, whereas functionally consequential mutations may clus-
ter within critical domains. First, we assumed that mutations have
a higher likelihood of functional impact if they are found at the
same site or in close proximity to each other. For example, highly
clustered mutations are observed in MYD88, CARD11, CD79B,
and EZH2 (Fig. S4). Second, we assumed that mutated genes are
more likely to be functionally relevant if the affected amino acid
residue is more conserved across species. Our algorithm thus
score reflecting sequence conservation and clustering of mutation
sites (Table 1). This analysis prioritized genes known to be mu-
tated in DLBCL and to play a role in its pathogenesis and also
novel genes that would not otherwise be considered as likely
drivers. For example, the tyrosine kinase SYK was identified as
a likely driver based on these criteria, and it has recently been
demonstrated that SYK inhibitors have significant clinical activity
in non-Hodgkin lymphoma, including DLBCL (38, 39). Similarly,
the serine/threonine kinase SGK1 was identified by this analysis
despite its not reaching statistical significance based on frequency
alone (q1> 0.1), but a recent study confirms the recurrent nature
of SGK1 mutation in DLBCL (17).
We performed whole-exome sequencing on tumor samples and
matched normal samples from 55 patients with DLBCL to
identify the spectrum of mutations associated with the disease.
This analysis provides a rich description of the DLBCL genome
and forms the basis for future discovery and therapeutic target
identification. In this single study, we rediscovered the genes
previously discovered to be important drivers of DLBCL, and
identified candidates deserving of functional follow-up.
Near the completion of our study, two groups reported their
analysis of the DLBCL genome (17, 18). Remarkably, the re-
currently mutated genes identified in these studies are highly
overlapping [of our 58 significantly mutated genes, 20 were also
reported as frequently mutated by Morin et al. (17), and 14 were
reported by Pasqualucci et al. (18)]. Such overlap provides strong
evidence that the mutations identified by our significance
thresholds are indeed recurrent in DLBCL. The fact that these
studies identified largely the same genes at similar frequency
suggests that these are the most common targets of somatic
mutation in DLBCL. Although our results and interpretation are
largely concordant with those recently published, we differ in our
interpretation of the frequent mutations seen in the BCL2 gene.
Whereas Morin et al. (17) suggest that these are likely indicative
of positive selection for nonsynonymous variants, we suggest the
mutations are in fact passenger mutations and observe a de-
pletion of damaging mutations in BCL2. Thus, whereas BCL2/
IgH translocation is likely indeed a driver of DLBCL, it also
increases the overall mutation rate in BCL2 (via AID), and we
believe that the resulting point mutations are likely non-
contributory to the pathogenesis of the disease. However, it is
interesting to speculate that the striking recurrence of silent
mutations at two distinct residues may indicate a selective ad-
vantage that is conferred by silent mutations.
More generally, a unique feature of B-cell malignancies is the
role of SHM in increasing mutation frequency. Under normal
conditions, suchSHM promotes affinity maturation ofantibodies,
but the enzymes that mediate this effect, such as AID, may also
in oncogenes and tumor-suppressor genes. High mutation rates
observed at particular loci in the genome may therefore indicate
the presence of dysfunctional SHM, rather than indicating posi-
tive selective growth advantage conferred by such mutations. Our
analyses suggest that BCL2, as well as PIM1 and other genes, are
subject to enrichment of mutations in WRCY hotspots, and
therefore likely to represent AID targets. Although, in the case of
BCL2, SHM can be explained as a result of translocation to the
IgH locus (40), this is less clear for other genes. Whole-genome
sequencing approaches may reveal whether hypermutation and
chromosome translocation events are related more generally. A
complete elucidation of those frequently mutated genes that are
contributory to the malignant phenotype, versus those that are
simply frequent passenger mutations caused by local SHM will
require future studies.
Ourlistofsignificantly mutatedgenes isbasedon thefrequency
of the occurrence of mutations, corrected for the size of the gene
and its expression level, the sample-specific mutation rate, and
the ratio of nonsynonymous to synonymous mutations. However,
some mutations may be functionally important despite not
meeting statistical significance based on these criteria alone. As
an additional tool to discover these mutations, we analyzed the
clustering of mutations in hotspots of individual genes, evolu-
tionary conservation, and overlap with mutated genes reported in
tions in BCL2 and sites of somatic mutations in BCL2.
Nonsynonymous mutations in BCL2 are preferentially lo-
cated outside of BH-domains.
Selection for functionally inconsequential muta-
Lohr et al. PNAS
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| vol. 109
| no. 10
the COSMIC database. These analyses reveal several genes that Download full-text
are rarely mutated, but that may nevertheless play an important
role in the pathophysiology of DLBCL. Future studies may ben-
efit from an even more thorough computational assessment ofthe
likely functional consequence of observed mutations.
With a first draft of the genomic landscape of DLBCL now
defined, the next step for the field should be to establish the
functionalconsequence oftheobserved mutations.Inmanycases,
the consequence is already known (e.g., activating the B-cell re-
ceptor pathway or activating the NF-κB pathway). In others,
however (particularly in the case of rare mutations), there is no
current insight into the role of those gene products in cancer
pathogenesis. Although the traditional approach to this problem
has been to attack such candidate genes one by one, we propose
that new, systematic approaches to the functional characteriza-
tion of candidate oncogenes and tumor suppressors are needed.
Systematic studies to connect such genes to known pathways and/
or processes will help to extend the utility of cancer genome
studies and accelerate the pace at which genetic findings are
translated into therapeutic impact.
Materials and Methods
Sample Selection and Massively Parallel Sequencing. A total of 55 patients with
DLBCL provided DNA for this study. This study was reviewed and approved by
the human subjects review board of the Mayo Clinic, the University of Iowa,
and the Broad Institute, and written informed consent was obtained from all
participants. DNA was extracted from lymph node samples (tumor) and blood
(normal) as previously described and processed as detailed in SI Materials
Calculation of Sequence Coverage, Mutation Calling, and Significance Analysis.
Massively parallel sequencing data were processed by using two consecutive
pipelines developed at the Broad Institute: “Picard” generates a single BAM
file representing the sample; “Firehose” starts with the BAM files for each
DLBCL sample and matched normal sample from peripheral blood (hg19)
and performs various analyses (15, 16). We evaluated the fraction of all
bases suitable for mutation calling whereby a base is defined as covered if
at least 14 and eight reads overlapped the base in the tumor and in the
germline sequencing, respectively. Subsequent analysis is described in more
detail in SI Materials and Methods.
PCR. A PCR assay was used for detection of the t(14;18) translocation, which
targets the joining region of the IgH gene and distinct regions of the BCL2 locus
(InVivoScribe Technologies). Details are provided in SI Materials and Methods.
Cortez, Jadwiga Grabarek, Ami S. Bhatt, Niall J. Lennon, and all members of
the Broad Institute’s Biological Samples Platform; Genetic Analysis Platform;
and Genome Sequencing Platform, without whom this work would not have
been possible. This work was conducted as part of the Slim Initiative for Ge-
nomic Medicine (SIGMA), a joint US–Mexico project funded by the Carlos Slim
Health Institute, and was also supported by National Cancer Institute Grants
5P01 CA092625-07 and P50 CA97274.
1. Abramson JS, Shipp MA (2005) Advances in the biology and therapy of diffuse large B-
cell lymphoma: moving toward a molecularly targeted approach. Blood 106:1164–1174.
2. Lenz G, Staudt LM (2010) Aggressive lymphomas. N Engl J Med 362:1417–1429.
3. Pfreundschuh M, et al.; German High-Grade Non-Hodgkin Lymphoma Study Group
(DSHNHL) (2008) Six versus eight cycles of bi-weekly CHOP-14 with or without ritux-
imab in elderly patients with aggressive CD20+ B-cell lymphomas: A randomised
controlled trial (RICOVER-60). Lancet Oncol 9:105–116.
4. Glass B, et al.; German High-Grade Non-Hodgkin Lymphoma Study Group (DSHNHL)
(2010) High-dose therapy followed by autologous stem-cell transplantation with and
without rituximab for primary treatment of high-risk diffuse large B-cell lymphoma.
Ann Oncol 21:2255–2261.
5. Alizadeh AA, et al. (2000) Distinct types of diffuse large B-cell lymphoma identified by
gene expression profiling. Nature 403:503–511.
6. Monti S, et al. (2005) Molecular profiling of diffuse large B-cell lymphoma identifies
robust subtypes including one characterized by host inflammatory response. Blood
7. Lenz G, et al.; Lymphoma/Leukemia Molecular Profiling Project (2008) Stromal gene
signatures in large-B-cell lymphomas. N Engl J Med 359:2313–2323.
8. Davis RE, et al. (2010) Chronic active B-cell-receptor signalling in diffuse large B-cell
lymphoma. Nature 463:88–92.
9. Ngo VN, et al. (2011) Oncogenically active MYD88 mutations in human lymphoma.
10. Lenz G, et al. (2008) Oncogenic CARD11 mutations in human diffuse large B cell
lymphoma. Science 319:1676–1679.
11. Morin RD, et al. (2010) Somatic mutations altering EZH2 (Tyr641) in follicular and
diffuse large B-cell lymphomas of germinal-center origin. Nat Genet 42:181–185.
12. Pasqualucci L, et al. (2011) Inactivating mutations of acetyltransferase genes in B-cell
lymphoma. Nature 471:189–195.
13. Puente XS, et al. (2011) Whole-genome sequencing identifies recurrent mutations in
chronic lymphocytic leukaemia. Nature 475:101–105.
14. Greenman C, et al. (2007) Patterns of somatic mutation in human cancer genomes.
15. Chapman MA, et al. (2011) Initial genome sequencing and analysis of multiple my-
eloma. Nature 471:467–472.
16. Stransky N, et al. (2011) The mutational landscape of head and neck squamous cell
carcinoma. Science 333:1157–1160.
17. Morin RD, et al. (2011) Frequent mutation of histone-modifying genes in non-
Hodgkin lymphoma. Nature 476:298–303.
18. Pasqualucci L, et al. (2011) Analysis of the coding genome of diffuse large B-cell
lymphoma. Nat Genet 43:830–837.
19. Harwood NE, Batista FD (2011) The cytoskeleton coordinates the early events of B-cell
activation. Cold Spring Harb Perspect Biol 3.
20. Cantagrel V, et al. (2004) Disruption of a new X linked gene highly expressed in brain
in a family with two mentally retarded males. J Med Genet 41:736–742.
21. Mullighan CG, et al. (2009) Rearrangement of CRLF2 in B-progenitor- and Down
syndrome-associated acute lymphoblastic leukemia. Nat Genet 41:1243–1246.
22. Fujiwara S, et al. (2007) Transforming activity of purinergic receptor P2Y, G protein
coupled, 8 revealed by retroviral expression screening. Leuk Lymphoma 48:978–986.
23. Leal-Ortiz S, et al. (2008) Piccolo modulation of Synapsin1a dynamics regulates syn-
aptic vesicle exocytosis. J Cell Biol 181:831–846.
24. Fujimoto K, et al. (2002) Piccolo, a Ca2+ sensor in pancreatic beta-cells. Involvement
of cAMP-GEFII.Rim2. Piccolo complex in cAMP-dependent exocytosis. J Biol Chem 277:
25. Izzo A, Kamieniarz K, Schneider R (2008) The histone H1 family: Specific members,
specific functions? Biol Chem 389:333–343.
26. Andreu-Vieyra CV, et al. (2010) MLL2 is required in oocytes for bulk histone 3 lysine 4
trimethylation and transcriptional silencing. PLoS Biol 8.
27. Parsons DW, et al. (2011) The genetic landscape of the childhood cancer medullo-
blastoma. Science 331:435–439.
28. Coenen EA, et al. (2011) Prognostic significance of additional cytogenetic aberrations
in 733 de novo pediatric 11q23/MLL-rearranged AML patients: Results of an in-
ternational study. Blood 117:7102–7111.
29. Ng SB, et al. (2010) Exome sequencing identifies MLL2 mutations as a cause of Kabuki
syndrome. Nat Genet 42(9):790–793.
30. Costello RT, et al. (2003) Stimulation of non-Hodgkin’s lymphoma via HVEM: an al-
ternate and safe way to increase Fas-induced apoptosis and improve tumor immu-
nogenicity. Leukemia 17:2500–2507.
31. Winkler GS (2010) The mammalian anti-proliferative BTG/Tob protein family. J Cell
32. Homminga I, et al. (2011) Integrated transcript and genome analyses reveal NKX2-1
and MEF2C as potential oncogenes in T cell acute lymphoblastic leukemia. Cancer Cell
33. Klein U, Dalla-Favera R (2008) Germinal centres: Role in B-cell physiology and ma-
lignancy. Nat Rev Immunol 8:22–33.
34. Pasqualucci L, et al. (2001) Hypermutation of multiple proto-oncogenes in B-cell
diffuse large-cell lymphomas. Nature 412:341–346.
35. Iqbal J, et al. (2011) BCL2 predicts survival in germinal center B-cell-like diffuse large
B-cell lymphoma treated with CHOP-like therapy and rituximab. Clin Cancer Res
36. Saito M, et al. (2009) BCL6 suppression of BCL2 via Miz1 and its disruption in diffuse
large B cell lymphoma. Proc Natl Acad Sci USA 106:11294–11299.
37. Letai AG (2008) Diagnosing and exploiting cancer’s addiction to blocks in apoptosis.
Nat Rev Cancer 8:121–132.
38. Friedberg JW, et al. (2010) Inhibition of Syk with fostamatinib disodium has signifi-
cant clinical activity in non-Hodgkin lymphoma and chronic lymphocytic leukemia.
39. Chen L, et al. (2008) SYK-dependent tonic B-cell receptor signaling is a rational
treatment target in diffuse large B-cell lymphoma. Blood 111:2230–2237.
40. Tanaka S, Louie DC, Kant JA, Reed JC (1992) Frequent incidence of somatic mutations
in translocated BCL2 oncogenes of non-Hodgkin’s lymphomas. Blood 79:229–237.
| www.pnas.org/cgi/doi/10.1073/pnas.1121343109 Lohr et al.