Intra-tumor genetic heterogeneity and alternative driver genetic alterations in breast cancers with heterogeneous HER2 gene amplification

Abstract

Background: HER2 is overexpressed and amplified in approximately 15% of invasive breast cancers, and is the molecular target and predictive marker of response to anti-HER2 agents. In a subset of these cases, heterogeneous distribution of HER2 gene amplification can be found, which creates clinically challenging scenarios. Currently, breast cancers with HER2 amplification/overexpression in just over 10% of cancer cells are considered HER2-positive for clinical purposes; however, it is unclear as to whether the HER2-negative components of such tumors would be driven by distinct genetic alterations. Here we sought to characterize the pathologic and genetic features of the HER2-positive and HER2-negative components of breast cancers with heterogeneous HER2 gene amplification and to define the repertoire of potential driver genetic alterations in the HER2-negative components of these cases.
Results: We separately analyzed the HER2-negative and HER2-positive components of 12 HER2 heterogeneous breast cancers using gene copy number profiling and massively parallel sequencing, and identified potential driver genetic alterations restricted to the HER2-negative cells in each case. In vitro experiments provided functional evidence to suggest that BRF2 and DSN1 overexpression/amplification, and the HER2 I767M mutation may be alterations that compensate for the lack of HER2 amplification in the HER2-negative components of HER2 heterogeneous breast cancers.
Conclusions: Our results indicate that even driver genetic alterations, such as HER2 gene amplification, can be heterogeneously distributed within a cancer, and that the HER2-negative components are likely driven by genetic alterations not present in the HER2-positive components, including BRF2 and DSN1 amplification and HER2 somatic mutations.

Full text

R E S E A R C H Open Access
Intra-tumor genetic heterogeneity and alternative
driver genetic alterations in breast cancers with
heterogeneous HER2 gene amplification
Charlotte KY Ng
1†
, Luciano G Martelotto
1†
,ArnaudGauthier
2†
,Huei-ChiWen
1†
, Salvatore Piscuoglio
1
, Raymond S Lim
1
,
Catherine F Cowell
1
, Paul M Wilkerson
3
, Patty Wai
3
, Daniel N Rodrigues
3
, Laurent Arnould
4
, Felipe C Geyer
5
,
Silvio E Bromberg
5
, Magali Lacroix-Triki
6
, Frederique Penault-Llorca
7
,SylviaGiard
8
, Xavier Sastre-Garau
2
,
Rachael Natrajan
3
, Larry Norton
9
, Paul H Cottu
10
, Britta Weigelt
1*†
, Anne Vincent-Salomon
2*†
and Jorge S Reis-Filho
1,11,12*†
Abstract
Background: HER2 is overexpressed and amplified in approximately 15% of invasive breast cancers, and is the
molecular target and predictive marker of response to anti-HER2 agents. In a subset of these cases, heterogeneous
distribution of HER2 gene amplification can be found, which creates clinically challenging scenarios. Currently, breast
cancers with HER2 amplification/overexpression in just over 10% of cancer cells are considered HER2-positive for
clinical purposes; however, it is unclear as to whether the HER2-negative components of such tumors would be
driven by distinct genetic alterations. Here we sought to characterize the pathologic and genetic features of the
HER2-positive and HER2-negative components of breast cancers with heterogeneous HER2 gene amplification and
to define the repertoire of potential driver genetic alterations in the HER2-negative components of these cases.
Results: We separately analyzed the HER2-negative and HER2-positive components of 12 HER2 heterogeneous breast
cancers using gene copy number profiling and massively parallel sequencing, and identified potential driver genetic
alterations restricted to the HER2-negative cells in each case. In vitro experiments provided functional evidence to suggest
that BRF2 and DSN1 overexpression/amplification, and the HER2 I767M mutation may be alterations that compensate for
the lack of HER2 amplification in the HER2-negative components of HER2 heterogeneous breast cancers.
Conclusions: Our results indicate that even driver genetic alterations, such as HER2 gene amplification, can be
heterogeneously distributed within a cancer, and that the HER2-negative components are likely driven by genetic
alterations not present in the HER2-positive components, including BRF2 and DSN1 amplification and HER2
somatic mutations.
Background
Amplification and overexpression of the proto-oncogene
HER2 (ERBB2) are found in approximately 15 to 20% of
all invasive breast cancers. HER2 positivity is defined ei-
ther by immunohistochemistry (IHC), when >10% of
cells show strong HER2 membrane staining (3+), or by
fluorescence or chromogenic in situ hybridization
(FISH/CISH), when the HER2:CEP17 ratio is ≥2 and/or
HER2 gene copy number is ≥6 [1]. HER2 is a bona fide
driver gene in breast cancer [2-5], and HER2 amplifica-
tion is the predictive marker and molecular target of
anti-HER2 agents such as trastuzumab, pertuzumab or
lapatinib [6]. Recently, HER2 somatic mutations have
been identified in approximately 1.5% of all invasive
breast cancers [7,8]. These mutations are preferentially
found in a subset of HER2-negative breast cancers and
have been shown to activate HER2 and its downstream
signaling pathways and to constitute a potential
* Correspondence: weigeltb@mskcc.org;anne.salomon@curie.fr;
reisfilj@mskcc.org
†
Equal contributors
1
Department of Pathology, Memorial Sloan Kettering Cancer Center, New
York, NY 10065, USA
2
Department of Tumor Biology, Institut Curie, 75248 Paris, France
Full list of author information is available at the end of the article
© 2015 Ng et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons
Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution , and
reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain
Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article,
unless otherwise stated.
Ng et al. Genome Biology (2015) 16:107
DOI 10.1186/s13059-015-0657-6

mechanism of resistance to trastuzumab and lapatinib
[7]. In fact, clinical trials testing irreversible HER2 inhib-
itors for the treatment of patients with breast cancers
harboring HER2 somatic mutations are currently on-
going (ClinicalTrials.gov: NCT01670877).
Massively parallel sequencing studies have revealed the
complexity and heterogeneity of breast cancer. In par-
ticular, it has been demonstrated that the number of
highly recurrently mutated genes, such as TP53 and
PIK3CA, is limited in breast cancer. On the other hand,
there is a large collection of genes mutated in <3% of
breast cancers [9,10], some of which are known driver
genes or are targeted by mutations that have been asso-
ciated with treatment resistance such as HER2 [7] and
ESR1 [11-13]. In addition to the variation between tu-
mors, intra-tumor genetic heterogeneity has also been
documented in breast cancer [14,15], as illustrated by
the identification of subclones, which harbor genetic al-
terations in addition to the founder genetic events
present in all cells [9,16-18]. To circumvent the potential
challenges posed by intra-tumor genetic heterogeneity,
in particular for biomarker assessment and therapeutic
decision-making, it has been suggested to focus on
founder driver genetic events present in all cells of a
given tumor (that is, the so-called ‘truncal drivers’) [19].
Whilst the majority of HER2-positive breast cancers
show homogeneous patterns of HER2 amplification and
HER2 protein overexpression, intra-tumor heterogeneity
in the form of two distinct or intermixed clones of
breast cancer cells exhibiting different patterns of HER2
gene amplification and overexpression can be observed
[15,20]. The incidence of this phenomenon ranges from
1 to 40% depending on the methodology and cutoffs
used [20-24]. We previously performed a re-review of a
consecutive series of >600 HER2-positive breast cancers
and 5% of these cases showed heterogeneous HER2
overexpression and gene amplification using clinical def-
initions of HER2-positivity [20]. It should be noted that
when a breast cancer displays >10% of tumor cells har-
boring HER2 overexpression and gene amplification, it is
diagnosed as HER2-positive and the patient is treated
accordingly without a precise understanding of the clin-
ical significance and the biological implications of this
heterogeneity and of having a large proportion of the
tumor composed of cells lacking HER2 overexpression/
gene amplification. Furthermore, it is assumed that
HER2 amplification is the driver genetic alteration in
these cancers; however, it is currently unknown whether
the HER2-negative components of HER2 heterogeneous
breast cancers harbor alternative genetic alterations. To
address this question, we sought i) to define the clinico-
pathologic characteristics of HER2 heterogeneous breast
cancers, ii) to determine the somatic gene copy number
alterations in the HER2-positive and HER2-negative
components of HER2 heterogeneous breast cancers, iii)
to define the repertoire of somatic mutations in the
HER2-positive and HER2-negative components of HER2
heterogeneous breast cancers, and iv) to identify poten-
tial driver genetic alterations of breast cancer based on
the analysis of the HER2-negative components of HER2
heterogeneous breast cancers. Here we show that HER2
heterogeneous breast cancers are estrogen receptor
(ER)-positive and predominantly TP53 mutant. In
addition, we identified and functionally validated alterna-
tive driver genetic alterations restricted to the HER2-
negative component of HER2 heterogeneous breast can-
cers, including BRF2 and DSN1 amplification, and a
HER2 somatic mutation.
Results
Clinico-pathologic characteristics of HER2 heterogeneous
breast cancers
We identified 41 HER2-positive breast carcinomas with
heterogeneous HER2 overexpression and HER2 gene
amplification, of which 13 cases were amenable to mi-
crodissection. For 12 HER2 heterogeneous breast cancers
the HER2-positive and HER2-negative components were
separated without cross-contamination as confirmed by
array-based comparative genomic hybridization (aCGH;
Figure 1; Additional files 1 and 2). Histologic and immu-
nohistochemical analysis revealed that all HER2 heteroge-
neous breast cancers subjected to microdissection were
ER-positive (as defined by the current cutoff of >1% of
ER-positive cells [25] in the whole tumor), and eight cases
were also progesterone receptor (PR)-positive (Figure 1A;
Additional file 1). The frequency of ER expression in these
HER2 heterogeneous cases was significantly higher than
that found in the HER2-positive breast cancers included
in The Cancer Genome Atlas (TCGA; 56/79, 71%) dataset
[10], the Molecular Taxonomy of Breast Cancer Inter-
national Consortium (METABRIC) discovery (40/72, 56%)
and validation (24/61, 39%) datasets [26], and the 1 year
adjuvant trastuzumab versus observation for HER2-
positive breast cancer (HERA) trial [27] cohort (1,536/
3,383, 45%) (Fisher’s exact test, two-tailed, P= 0.0326,
P= 0.0026, P< 0.0001, P< 0.0001, respectively). To de-
fine whether this observation related to the ER status
of HER2 heterogeneous breast cancers would be
generalizable, we investigated the ER status of the
HER2 heterogeneous breast cancers that were re-
trieved for this study but not amenable to microdissec-
tion. The diagnostic ER immunohistochemical slides of
26 of the remaining 29 cases were retrieved, and re-
analysis of their ER status revealed that 24 of 26 cases
(92%) were ER-positive. The majority of the HER2 het-
erogeneous breast cancers in this study were of high
histologic grade (9/12 grade 3, 75%, Additional file 1).
Sanger sequencing revealed that all but three cases
Ng et al. Genome Biology (2015) 16:107 Page 2 of 21

(75%) were TP53 mutant (Figure 1A; Additional file 1),
a frequency similar to that found in HER2-positive
breast cancers from the TCGA dataset. When assessing
the HER2-positive and HER2-negative components
separately, we noted that in 10 out of 12 of the HER2
heterogeneous breast cancers the ER status and histo-
logic grade were identical between the two compo-
nents of a given case, as was the TP53 status in all
cases (Figure 1A; Additional file 1). Taken together, the
HER2 heterogeneous breast cancers amenable to
Figure 1 HER2 heterogeneous breast cancers are ER-positive and preferentially TP53 mutant. (A) Clinico-pathologic characteristics of HER2
heterogeneous breast cancers included in this study. ER, estrogen receptor; PR progesterone receptor; WT, wild-type. (B) Micrographs of
representative hematoxylin and eosin (H&E) stained sections, HER2 immunohistochemistry (IHC) and HER2 chromogenic in situ hybridization
(CISH) of selected HER2 heterogeneous breast cancers included in this study (scale bar IHC, 200 μm; scale bar CISH, 50 μm). Chromosome 17
plots of microdissected HER2-positive and HER2-negative components of each case confirming the presence and absence of HER2 gene
amplification (17q12), respectively. In the chromosome plots, the circular binary segmentation (cbs)-smoothed Log
2
ratios for each bacterial
artificial chromosome mapping to chromosome 17 were plotted on the y-axis and their genomic positions were plotted on the x-axis. Gains,
amplifications and losses are highlighted in dark green, bright green and red, respectively. Please see Additional file 2 for the remaining cases.
Ng et al. Genome Biology (2015) 16:107 Page 3 of 21

microdissection and included in this study were ER-
positive and preferentially TP53 mutant.
Copy number alterations in HER2-positive and HER2-
negative components of HER2 heterogeneous breast
cancers
To determine if there would be a common alternative
gene copy number alteration (CNA) present in the
HER2-negative components, which would account for
the lack of HER2 gene amplification, the microdissected
HER2-positive and HER2-negative components of each
case were subjected to DNA extraction and aCGH ana-
lysis (Figure 1B). When the copy number gains, losses
and amplifications of the HER2-positive components
were compared with those of the HER2-negative compo-
nents from all 12 HER2 heterogeneous breast cancers,
we observed that the patterns of CNAs were highly simi-
lar (Figure 2A). In fact, Fisher’s exact test revealed that
the only recurrent CNA present at significantly different
frequencies between the HER2-positive and HER2-
negative components of the HER2 heterogeneous breast
cancers studied here was the HER2 amplicon itself (that
is, 17q12). Furthermore, hierarchical cluster analysis of
the categorical gene copy number states revealed that
the HER2-positive and HER2-negative components of a
given HER2 heterogeneous breast cancer clustered to-
gether, rather than all HER2-positive and all HER2-
negative components clustering together (Figure 2B).
Figure 2 Gene copy number alterations in HER2-positive and HER2-negative components of HER2 heterogeneous breast cancers. (A) Frequency
plots of copy number gains and losses (top) and of amplifications (bottom) in HER2 non-amplified and HER2-amplified components of 12 HER2
heterogeneous breast cancers. The proportion of cases in which each bacterial artificial chromosome (BAC) clone is gained/amplified (green) or
lost (red) is plotted (y-axis) for each BAC clone according to its genomic position (x-axis). Inverse Log
10
values of the Fisher’s exact test P-values
are plotted according to genomic location (x-axis) at the bottom of each graph. The only statistically significant difference identified between the
genomic profiles of HER2 non-amplified and HER2-amplified components of 12 HER2 heterogeneous breast cancers was HER2 itself. (B) Hierarchical
clustering of the genomic profiles of HER2-positive and HER2-negative components of 12 HER2 heterogeneous breast cancers. Hierarchical cluster
analysis was performed with categorical states (that is, gains, losses, and amplifications) using Euclidean distance metric and the Wards algorithm.
Amp, amplification; Del, deletion; NC, normal copy number.
Ng et al. Genome Biology (2015) 16:107 Page 4 of 21

These data suggest that the HER2-positive and HER2-
negative components of each case are clonally related
and that there is no highly recurrent alternative CNA in
the HER2-negative components of HER2 heterogeneous
breast cancers that compensates for the lack of HER2
gene amplification.
We next assessed the patterns of gene CNAs in a pair-
wise manner by comparing the HER2-negative and
HER2-positive components of each case. Although the
components of each HER2 heterogenous breast cancer
were more similar to each other than to the components
of any of the other cases (Figure 2B), we observed differ-
ences in their pattern of CNAs in addition to the HER2
amplification. These differences were restricted to a
few genomic regions in some tumors (for example,
case T1), whereas in others, the two components were
substantially different (for example, case T12) (Figure 2B;
Additional file 3). This analysis further revealed specific
amplifications, comprising 1,535 individual genes, re-
stricted to the HER2-negative components of HER2 het-
erogeneous breast cancers (Figures 2B and 3A; Additional
file 4). Some of these map to regions recurrently amplified
in breast cancer, including the 1q24, 8p11-p12, 8q24,
11q13 and 20q13 amplicons, which have been shown to
contain known driver genes [26,28-30]. To identify pos-
sible driver events in the HER2-negative components of
HER2 heterogeneous breast cancers, of which >90% were
ER-positive and of luminal A-like or luminal B-like sub-
type according to the St Gallen International Expert Con-
sensus 2013 [31] (Additional file 1), the copy number
status and gene expression of the 1,535 genes found to be
amplified only in the HER2-negative components of the
cases analyzed here were assessed in the luminal A and lu-
minal B breast cancers of the TCGA dataset [10]. This list
of genes contains numerous likely breast cancer drivers,
including MDM4 [32], ZNF703 [33], RAB11FIP1 [28,29],
MYC,FAM83A [34], PIK3CA,PROSC [28], PPAPDC1B
[35], LSM1 [28,36], BAG4 [36], EEF1A2 [37], CAMK1D
[38], PHGDH [39], FGFR1 [40], DDHD2 [28] and
WHSC1L1 [28,41] (Additional file 5). To prioritize the
validation of novel potential driver genes based on the
analysis of the HER2-negative components of HER2
heterogeneous breast cancers, we searched for genes i)
whose expression is copy number regulated and are
overexpressed when amplified, in a way akin to HER2
itself [2,3], and ii) that are recurrently amplified in the
dataset of HER2 heterogeneous cases and/or preferen-
tially amplified in HER2-negative tumors in the TCGA
luminal breast cancer dataset.
This analysis revealed that of the 1,535 amplified genes
restricted to the HER2-negative components of our 12
HER2 heterogeneous breast cancers, 59 genes were sta-
tistically significantly copy number regulated in the lu-
minal breast cancers of the TCGA dataset (Additional
files 5 and 6), some of which were either recurrently
amplified in the HER2-negative components of HER2
heterogeneous cases (for example, BRF2 in cases T2 and
T4) or mutually exclusively amplified with HER2 in the
TCGA luminal breast cancer dataset (for example, DSN1
in case T12) (Figure 3A,B; Additional file 6).
From this list of genes, we focused on BRF2 and
DSN1, given the lack of direct functional evidence to
support a potential oncogenic role of the amplification
of these genes in breast cancer. Hence, we sought to de-
fine whether BRF2 and DSN1 would have oncogenic
properties in in vitro models of breast cancer. BRF2
(8p11.23) maps to the 8p11-p12 amplicon and is re-
ported to be recurrently amplified in 10 to 15% of breast
cancers [28]. This gene encodes a subunit of the RNA
polymerase III transcription initiation factor and has
been identified as a potential oncogene in lung squa-
mous cell carcinomas [42]. DSN1 maps to 20q11.23, and
encodes a kinetochore protein of the minichromosome
instability-12 centromere complex [43]. This gene is
amplified only in 1.7% of all breast cancers, and its amp-
lification is mutually exclusive with HER2 amplification
in the TCGA luminal breast cancer dataset (Figure 3B)
[10]. The DSN1 amplicon is distinct from the 20q13
amplicon, and is not encompassed by its smallest region
of amplification [30]. Forced expression of BRF2 and
DSN1 in NIH3T3 and non-malignant MCF10A breast
epithelial cells resulted in their nuclear localization as
expected (Figure 4A; Additional file 7), and in significant
transformation of NIH3T3 and MCF10A cells as
measured by a foci formation assay (Figure 4B) and
anchorage-independent growth in soft agar (Figure 4C),
respectively. In addition, forced expression of BRF2 and
DSN1 in non-malignant breast epithelial cells MCF10A
and MCF12A affected the growth and glandular archi-
tecture of these cells when grown in three-dimensional
culture systems. Whilst empty vector-transfected MCF10A
and MCF12A cells formed spheroid acinar-like structures,
BRF2 and DSN1 overexpression led to larger, multiacinar
structures with filled lumens (Figure 4D), in line with
phenotypes previously observed when oncoproteins are
expressed in this model system [44,45].
Taken together, the HER2-negative components of
HER2 heterogeneous breast cancers are not underpinned
by a single highly recurrent amplification. Our findings
demonstrate, however, that some of the genes amplified
only in the HER2-negative components of HER2 hetero-
geneous breast cancers, such as genes previously de-
scribed as oncogenic, including MDM4 [32], FGFR1
[40,46], ZNF703 [33], MYC,FAM83A [34], RAB11FIP1
[28,29], and PIK3CA (Table 1), as well as BRF2 and
DSN1, which were shown to have oncogenic properties
here, may constitute potential drivers and compensate
for the lack of HER2 amplification.
Ng et al. Genome Biology (2015) 16:107 Page 5 of 21

Figure 3 (See legend on next page.)
Ng et al. Genome Biology (2015) 16:107 Page 6 of 21

Somatic mutations in HER2-negative components of HER2
heterogeneous breast cancers
To determine if the constellations of mutations would
be distinct between the HER2-positive and HER2-
negative components of HER2 heterogeneous breast
cancers, and to identify potential driver mutations re-
stricted to the HER2-negative components, we subjected
the HER2-positive and HER2-negative components of
three cases (that is, T6, T11 and T12), for which suffi-
cient DNA from frozen tumor and matched normal tis-
sues was available, to whole exome sequencing. Selected
somatic mutations identified were validated by high-depth
amplicon sequencing (Ion Torrent, 4000×) or targeted
massively parallel sequencing (Figure 5A; Additional files
8, 9 and 10). Analysis of the clonal frequencies using AB-
SOLUTE [47] revealed that known founder genetic events
such as somatic mutations in TP53 and/or PIK3CA were
shared and inferred to be present in all cells of both the
HER2-positive and HER2-negative components of these
cases (Table 1; Figure 5A). This analysis also revealed the
presence of subclonal mutations in the HER2-negative
components of all cases, and in the HER2-positive compo-
nent of cases T6 and T12 (Figure 5A,B). We next per-
formed targeted massively parallel sequencing, using a
panel of 273 genes frequently mutated in breast cancer
and DNA repair-related genes [48], of the HER2-negative
and HER2-positive components of 5 HER2 heterogeneous
breast cancers (that is, T1, T3, T4, T8, and T9; Figure 5C).
Consistent with the observations made by whole exome
sequencing analysis, in all cases, the HER2-negative and
HER2-positive components harbored somatic mutations
in common, including TP53 somatic mutations in three
cases (Figure 5C). Interestingly, in the two TP53 wild-type
cases subjected to targeted sequencing, we identified an
ARID1A mutation (that is, T4) and PIK3CA and CBFB
mutations (that is, T8), which were common to the two
components (Figure 5C). Taken together, in all cases ana-
lyzed, the HER2-negative and HER2-positive components
shared identical somatic mutations, indicating their clonal
relatedness.
When focusing on the mutations restricted to the
HER2-negative components, we identified a HER2 I767M
somatic mutation in one of the three cases subjected
to whole exome sequencing (T6; Figure 5A; Additional
file 11). HER2 somatic mutations have been shown not
to result in HER2 overexpression using the current im-
munohistochemical assays [7]. The HER2 I767M kin-
ase domain mutation has previously been reported to
increase the levels of HER2 phosphorylation modestly
in MCF10A cells [7], but it has not been further evalu-
ated for its potential as an activating driver event. Here
we demonstrate using two independent cell-free kinase
assays that the HER2 I767M mutation displayed sig-
nificantly increased transphosphorylation of the tyro-
sine kinase substrate Poly(Glu4-Tyr) compared with
wild-type HER2 (Figure 6A,B). We next investigated
whether the HER2 I767M mutation would result in
transformation of NIH3T3 cells. Stable forced expres-
sion of the HER2 I767M mutation resulted in signifi-
cantly increased foci formation compared with empty
vector and wild-type HER2 (Figure 6C). To define the
impact of the HER2 I767M mutation on anchorage-
independent growth, we generated MCF10A cells sta-
blyexpressingtheemptyvector,wild-typeHER2and
the HER2 I767M mutation. Soft agar assays revealed
that both wild-type and I767M mutant HER2 led to an
increase in the number of colonies compared with
empty vector; however, the HER2 I767M mutation re-
sulted in significantly larger colonies than those caused
by wild-type HER2 (Figure 6D). Similar results were
obtained with NIH3T3 cells stably expressing the
empty vector, wild-type HER2 and the HER2 I767M
mutation (Additional file 12). To define whether the
HER2 I767M mutation would have an impact similar
to that of HER2 tyrosine kinase mutations previously
shown to be strongly activating (V777L) or not activat-
ing (Y835F) by Bose et al. [7], we transiently forced
the expression of empty vector, wild-type HER2, HER2
I767M, HER2 V777L and HER2 Y835F in NIH3T3,
MCF10A and MCF12A cells. These transiently trans-
fected cells were subsequently subjected to a soft agar
assay which demonstrated that the HER2 I767M mu-
tation resulted in anchorage-independent growth in
soft agar that was higher than that caused by wild-
type HER2 and the non-activating HER2 mutation
(Y835F), but not statistically different from that
caused by the strongly activating mutation (V777L)
(Additional file 13).
(See figure on previous page.)
Figure 3 Identification of BRF2 and DSN1 amplification in HER2-negative components of HER2 heterogeneous breast cancers. (A) Gene copy
number analysis of HER2-positive and HER2-negative components of HER2 heterogeneous breast cancers confirmed the presence and absence of
HER2 amplification (genome plots, middle), respectively, and identified the presence of an 8p11-p12 amplification, including BRF2 and other breast
cancer genes, in cases T2 and T4, and of a 20q11 amplification, encompassing DSN1, in case T12 restricted to the HER2-negative component of
each case (chromosome plots, right). In the genome plots and chromosome plots, the genomic position is plotted along the x-axis and circular
binary segmentation (cbs)-smoothed Log
2
ratio on the y-axis; amplifications are shown in bright green, gains in dark green, losses in dark red and
normal copy number in black. (B) Selected amplified genes identified to be restricted to the HER2-negative components of HER2 heterogeneous
breast cancers were assessed in luminal breast cancers from the TCGA dataset (for complete list of genes and data source, see Additional file 6).
Ng et al. Genome Biology (2015) 16:107 Page 7 of 21

Figure 4 (See legend on next page.)
Ng et al. Genome Biology (2015) 16:107 Page 8 of 21

Given that all HER2 heterogeneous breast cancers sub-
jected to sequencing here were ER-positive, and all but
one case was TP53 and/or PIK3CA-mutant, we assessed
the effect of forced expression of the HER2 I767M mu-
tation on the growth and HER2 downstream signaling in
ER-positive breast cancer cell lines harboring TP53 and/
or PIK3CA mutations (that is, MCF7, PIK3CA-mutant;
T47D, TP53 and PIK3CA-mutant). Upon forced expres-
sion, both wild-type and mutant HER2 protein were
found to be expressed in the membranous subcellular
fraction of stably transfected breast cancer cell lines
(Additional file 14). In MCF7 cells, expression of HER2
I767M led to a significant advantage in cell growth com-
pared with empty vector when cultured in standard
growth media (Figure 6E). By contrast, forced expression
of HER2 I767M in T47D cells resulted in a significant
growth advantage in comparison to T47D cells express-
ing wild-type HER2 or empty vector control only in the
presence of neuregulin-1, an activator of HER receptors
[49] (Figure 6E). To determine whether these differences
would stem from distinct levels of endogenous
neuregulin-1 in MCF7 and T47D cells, we assessed
neuregulin-1 protein and mRNA expression levels in
these cells by western blotting and quantitative RT-PCR,
respectively; no differences in the levels of neuregulin-1
protein expression in these cells and their conditioned
media and of NRG1 mRNA in samples extracted from
MCF7 and T47D cells were detected (Additional file 15).
To determine the effect of forced wild-type HER2 and
HER2 I767M expression on downstream effector path-
ways in MCF7 and T47D cells, we performed a time-
course experiment where the activation of HER2, AKT,
ERK1/2 and ribosomal protein S6 (rpS6) was determined
at baseline, after 20 minutes of neuregulin-1 treatment,
and 30 minutes, 3 hours, 5 hours and 24 hours post-
neuregulin-1 withdrawal using quantitative infrared
fluorescent western blotting (LI-COR; Figure 7). At
baseline, cells expressing wild-type HER2 and HER2
I767M were found to display similar levels of activation
of the AKT and MAPK pathways (Figure 7). Although
neuregulin-1 stimulation resulted in similarly increased
levels of activation of AKT and ERK1/2 in cells express-
ing wild-type HER2 and the HER2 I767M mutation, we
observed that the activation of AKT was sustained for
(See figure on previous page.)
Figure 4 BRF2 and DSN1 amplifications are potential driver genetic alterations in HER2-negative breast cancer cells. (A) Nuclear subcellular
localization of BRF2 and DSN1 in NIH3T3 (top) and MCF10A (bottom) cells expressing BRF2-ZsGreen and DSN1-ZsGreen (scale bar, 25 μm). (B) Foci
formation assay of NIH3T3 cells expressing vector control, BRF2 or DSN1 protein. Cells were fixed and stained with crystal violet 21 days after
plating, and the foci were quantified (see Materials and methods). *P< 0.05, unpaired t-test. Error bars represent standard deviation of mean. (C)
Anchorage-independent growth of MCF10A cells expressing vector control, BRF2 or DSN1 protein. Quantification was performed using an MTT
assay (left) or by defining the number and size of colonies (right). *P< 0.05, **P< 0.01, ***P< 0.001, ****P< 0.0001, unpaired t-test. Error bars
represent standard deviation of mean. (D) Impact of empty vector, BRF2 and DSN1 expression on growth and glandular architecture of MCF10A
(top) and MCF12A (bottom) cells grown in three-dimensional basement membrane cultures (scale bar, 500 μm).
Table 1 Potential driver genetic alterations in both HER2-negative and HER2-positive components of HER2 heterogeneous
breast cancers, and in the HER2-negative components only
Sample
ID
Potential driver mutations present
in both HER2-negative and
HER2-positive components
Potential driver mutations restricted
to the HER2-negative component
Potential drivers within regions whose
amplification was restricted to the
HER2-negative component
T1 TP53 (P152L) FAM83A,MDM4
T2 NP NP BRF2,FGFR1,ZNF703,RAB11FIP1,LSM1,DDHD2,
WHSC1L1,PPAPDC1B,EEF1A2,ERLIN2,BAG4
T3 TP53 (E258D) ATRX (splice site dinucleotide substitution) YWHAZ,MYC,FAM83A
T4 ARID1A (R1446*) BRF2,ZNF703,RAB11FIP1,ERLIN2
T5 TP53 (E286D) NP IKBKB,CAMK1D
T6 TP53 (R273H), PIK3CA (H1047R) HER2 (I767M), ETV5 (E60K) PHGDH
T8 PIK3CA (H1047R), CBFB (splice site) BRAF (P403S), XRCC1 (S236F)
T9 TP53 (R282G), PIK3CA (H1047R),
MAP2K4 (R110G), MED12 (R2015M)
LMX1B
T10 TP53 (S94fs) NP CBX3,RAD21
T11 TP53 (G187_E192delLAPPQ) NRP1 (R767H) MYC,RAD21
T12 TP53 (T195N), KIT (A755T) FANCD2 (L1394F) DSN1
T13 TP53 (S240I) NP PIK3CA
NP, massively parallel sequencing not performed due to lack of DNA of sufficient quantity and/or quality.
Ng et al. Genome Biology (2015) 16:107 Page 9 of 21

Figure 5 (See legend on next page.)
Ng et al. Genome Biology (2015) 16:107 Page 10 of 21

longer in cells expressing the HER2 I767M mutation
than in cells expressing wild-type HER2 (Figure 7).
To assess the effect of the HER2 I767M mutation on
acinar structures, non-malignant breast epithelial cells
expressing wild-type HER2 and HER2 I767M were
grown in basement membrane cultures. In line with
previous reports [44], wild-type HER2 expression in
MCF10A cells elicited a multiacinar phenotype com-
pared with the spherical structures of MCF10A empty
vector cells (Figure 8A). Expression of HER2 I767M in
MCF10A cells led to a significantly higher number of
large multiacinar structures with increased branching
and filled lumens than the expression of wild-type HER2
(Figure 8A). Furthermore, while forced expression of
wild-type HER2 in MCF12A cells led to irregular
structures compared with empty vector MCF12A
spheroids, HER2 I767M MCF12A structures were sig-
nificantly more frequently larger (Figure 8A). In
MCF12A cells, these structures displayed luminal fill-
ing and irregular contours, and some showed infiltrat-
ing edges (Additional file 16). The phenotype induced
by forced expression of HER2 I767M is consistent with
that observed when other oncoproteins are expressed
in this model system [44,45]. To validate these obser-
vations, MCF10A cells stably expressing empty vector,
wild-type HER2 and the HER2 I767M mutation were
grown in the same three-dimensional culture system.
This analysis confirmed that stable forced expression
of the HER2 I767M mutation resulted in significantly
larger acini, whose lumina were significantly more fre-
quently filled than those observed in cells expressing
the empty vector or wild-type HER2 (Figure 8B). These
observations suggest that case T6 is an example of a
convergent phenotype, where HER2 is activated by two
different mechanisms in a breast cancer; whilst the
HER2-positive component is driven by HER2 amplifi-
cation, the HER2-negative component is likely driven
by a HER2 tyrosine kinase mutation.
Taken together, the analysis of all somatic CNAs and
mutations in HER2 heterogeneous breast cancers not
only revealed the founder genetic events (that is, somatic
genetic alterations likely present in all cells) of these tu-
mors, including TP53 and PIK3CA mutations, but also
led to the identification of at least one potential alterna-
tive driver genetic alteration restricted to the HER2-
negative component in the breast cancers analyzed
(Table 1). In addition to the genetic alterations discussed
above, that is, BRF2 amplification, DSN1 amplification
and HER2 I767M somatic mutation, we identified an
ATRX splice site dinucleotide substitution (case T3), a
BRAF P403S potentially pathogenic mutation (case T8),
and a FANCD2 L1394F potentially pathogenic mutation
(case T12), and amplification of the candidate oncogene
FAM83A [34] (cases T1 and T3), of MYC (cases T3 and
T11), and of PIK3CA (case T13) amongst others (Table 1),
which were present exclusively in the HER2-negative
components of these HER2 heterogeneous breast cancers.
Discussion
Our study demonstrates that intra-tumor genetic hetero-
geneity is not restricted to passenger genes but that in
breast cancer also bona fide driver genetic alterations
such as HER2 gene amplification can be heterogeneously
distributed within a given tumor. Here, we have identi-
fied potential alternative driver genetic alterations that
are present only in the HER2-negative and are absent in
the HER2-positive components of HER2 heterogeneous
breast cancers. These potential alternative driver alter-
ations were found to affect known cancer genes (Table 1),
including amplification of PIK3CA or MYC, and likely
driver genes mapping to the 8p11-p12 amplicon, includ-
ing ZNF703 [33], RAB11FIP1 [28,29], LSM1 [28],
PPAPDC1B [35], WHSC1L1 [28,41] and FGFR1 [40,46].
Here we also provide functional evidence to suggest that
the copy number regulated genes BRF2, a TFIIB-like fac-
tor mapping to the 8p11-p12 amplicon [28,42], and
DSN1, a kinetochore protein mapping to 20q11 [43], as
well as the HER2 I767M mutation may confer a neoplas-
tic advantage to HER2-negative breast epithelial cells.
The HER2-positive breast cancers with heterogeneous
patterns of HER2 overexpression and gene amplification
studied here were all ER-positive, and most were of high
histologic grade (75%) and harbored somatic TP53 mu-
tations (75%). We noted that this phenotype resembles
that of breast cancers arising in TP53 germline mutation
carriers (that is, Li-Fraumeni syndrome), which have
(See figure on previous page.)
Figure 5 Sequencing analysis of HER2-positive and HER2-negative components of HER2 heterogeneous breast cancers identified founder genetic
events and intra-tumor mutational heterogeneity. (A) Clonal frequencies of mutations identified in HER2-positive and HER2-negative components
of HER2 heterogeneous breast cancers T6, T11 and T12, which were subjected to whole exome sequencing and orthogonal validation by amplicon
sequencing (Ion Torrent) or targeted capture massively parallel sequencing (Illumina). Clonal mutation frequencies were estimated from the mutant
allelic fractions adjusted according to tumor cellularity, tumor ploidy and local copy number states using ABSOLUTE [47]. Indel, insertion and deletion;
SNV, single nucleotide variant. (B) Diagram illustrating the cancer cell fraction, as defined by ABSOLUTE, of mutations identified in cases T6, T11 and
T12. Note the presence of subclonal mutations in the HER2-negative components of all cases, and in the HER2-positive components of cases T6 and
T12. (C) Allelic fractions of mutations identified in HER2-positive and HER2-negative components of HER2 heterogeneous breast cancers obtained
through targeted massively parallel sequencing analysis using a panel of 273 genes comprising genes frequently mutated in breast cancer and DNA
repair-related genes. Indel, insertion and deletion; SNV, single nucleotide variant.
Ng et al. Genome Biology (2015) 16:107 Page 11 of 21

Figure 6 (See legend on next page.)
Ng et al. Genome Biology (2015) 16:107 Page 12 of 21

(See figure on previous page.)
Figure 6 Identification of a HER2 mutation as a potential driver genetic alteration in the HER2-negative component of a HER2 heterogeneous
breast cancer. (A) Cell-free in vitro kinase assay determining the tyrosine kinase activity of the Poly(Glu4-Tyr) substrate and the autophosphorylation
activity of wild-type (WT) HER2 (dark gray) and I767M mutant HER2 (light gray) in the presence and absence of neuregulin-1 (NRG1). Tyrosine kinase
activity was assessed using the ADP Hunter HS Assay (DiscoveRx, left). Western blot analysis of representative elutes post-kinase assay of HER2-tagRFP,
HER2(I767M)-tagRFP and tagRFP control proteins. The amounts of HER2 wild-type and I767M mutant HER2 enzymes used in the DiscoveRx kinase assay
were similar as confirmed using antibodies against total HER2 (top panel) and tagRFP (bottom panel). ****P< 0.0001, Holm-Šídák-correction, multiple
t-test. Error bars represent standard deviation of mean. (B) The Tyrosine Kinase Assay Kit (Millipore) confirmed the significantly higher
transphosphorylation of the tyrosine kinase substrate Poly(Glu4-Tyr) by I767M mutant HER2 (light gray) compared with wild-type HER2 (dark
gray). ***P< 0.001, Holm-Šídák-correction, multiple t-test. Error bars represent standard deviation of mean. (C) Foci formation assay of NIH3T3
cells stably expressing empty vector, wild-type HER2 or I767M mutant HER2 protein. Cells were fixed and stained with crystal violet 5 and
12 days after plating. Quantification was performed at day 5. Note that at day 12, the wild-type HER2 resulted in increased foci formation.
***P< 0.001, unpaired t-test. Error bars represent standard deviation of mean. (D) Anchorage-independent growth of MCF10A cells stably
expressing empty vector, wild-type HER2 or I767M mutant HER2 protein. Quantification was performed using an MTT assay (left) or by defining
the number and size of colonies (right). *P< 0.05, **P< 0.01, ****P< 0.0001, unpaired t-test. N.s., not significant. Error bars represent standard
deviation of mean. (E) Effect of stable expression of wild-type HER2 (blue) and I767M mutant HER2 (red) on survival and growth of ER-positive
MCF7 (PIK3CA mutant) and T47D (PIK3CA and TP53 mutant) cells in growth media with or without neuregulin-1 (NRG1, 10 ng/ml). **P< 0.01,
***P< 0.001, Holm-Šídák-correction, multiple t-test. Error bars represent standard deviation of mean.
Figure 7 Signaling pathway activation of ER-positive MCF7 and T47D cell lines expressing wild-type (WT) or I767M mutant HER2. Whole-cell
lysates of MCF7 and T47D, stably expressing empty vector control, wild-type HER2 or I767M mutant HER2 were analyzed by western blotting for
total and phosphorylated levels of HER2, AKT, ERK1/2 and rpS6 on the same membrane, detected by near infrared two-color detection and
quantified (LI-COR; Odyssey). Phospho-/total protein ratios are shown below. NRG1, neuregulin-1.
Ng et al. Genome Biology (2015) 16:107 Page 13 of 21

been shown to be preferentially ER-positive, HER2-
positive and of high histologic grade [50]. The implica-
tions of this similarity in the histopathologic profile be-
tween breast tumors arising in TP53 germline mutation
carriers and the HER2 heterogeneous breast cancers
studied warrants further investigation. Interestingly, in
the cases harboring TP53 somatic mutations analyzed
here, these mutations were found to be likely founder
genetic events, potentially preceding the amplification of
HER2, in a way akin to the TP53 germline mutations
preceding HER2 amplification in breast cancers from Li-
Fraumeni patients.
HER2 amplification and overexpression have been sug-
gested to be an early event in breast tumorigenesis [51].
It is not clear whether in the HER2 heterogeneous breast
cancers studied here, HER2 amplification was an early
event and subsequently lost in the HER2-negative com-
ponents, or whether HER2 amplification was acquired in
the HER2-positive components at a relatively late stage
of tumorigenesis. It could be posited that the presence
of bona fide driver genetic alterations shared by the
HER2-positive and HER2-negative components in all
cases subjected to sequencing (Table 1) would be sug-
gestive of the HER2 amplification being a relatively late
Figure 8 Impact of the HER2 I767M mutation on glandular architecture of non-malignant breast epithelial cells. (A) Impact of transient expression
of empty vector, wild-type HER2 (WT) and I767M mutant HER2 on growth and glandular architecture of MCF10A (top) and MCF12A (bottom) cells
grown in three-dimensional basement membrane cultures (scale bar, 500 μm). The percentage of acinar structures ≥250 μm (MCF10A) and ≥200 μm
(MCF12A) were quantified. **P< 0.01, ***P< 0.001, unpaired t-test. Error bars represent standard deviation of mean. (B) Impact of stable expression
of empty vector, wild-type HER2 and I767M mutant HER2 on acinar size and lumina filling of MCF10A cells. Representative micrographs are shown
(original magnification 40×). MCF10A cells expressing I767M mutant HER2 formed significantly larger acinar structures (left), which significantly more
frequently displayed filled lumina (right) compared with MCF10A cells stably expressing empty vector or wild-type HER2. **P<0.01, ****P<0.0001,
unpaired t-test. N.s., not significant. Error bars represent standard deviation of mean.
Ng et al. Genome Biology (2015) 16:107 Page 14 of 21

event in the development of these tumors. For example,
a possible explanation for the findings observed in case
T6 is that the TP53 and PIK3CA mutations were the
truncal drivers, whereas the HER2 gene amplification
and the HER2 I767M mutation would constitute two
distinct branch drivers. Alternatively, loss of HER2 amp-
lification in one of the components could be the result
of the acquisition of another driver genetic alteration
that is in epistatic interaction [52] with HER2 amplifica-
tion. This scenario, albeit possible, would likely require
the HER2 amplicon to be syntenic in tumors with het-
erogeneous HER2 amplification. Whole genome sequen-
cing analysis and fiber fluorescence in situ hybridization,
which can be performed in fresh/frozen samples, could
be employed to define whether the HER2 amplicon is
syntenic or distributed in multiple chromosomal loca-
tions in HER2 heterogeneous cancers.
It has been reported previously that patients whose tu-
mors display intra-tumor genetic heterogeneity of HER2
gene amplification have a shorter progression-free sur-
vival than patients with homogeneous HER2 gene ampli-
fication [22]. Furthermore, we have described previously
that lymph node or distant metastases from patients
with primary HER2 heterogeneous breast cancers treated
with anti-HER2 agents and chemotherapy may be
HER2-positive or HER2-negative, suggestive of clonal se-
lection [20]. Together with the findings in this study that
alternative driver genetic alterations may be present in
the HER2-negative components of HER2 heterogeneous
breast cancers, our data may provide an explanation for
the presence of discordant HER2 status between primary
tumors and metastases when assessed on biopsy mater-
ial, which has been found in up to 14% of cases [53]. Im-
portantly, analysis of the distant relapses of cases T4 and
T8 after trastuzumab and chemotherapy treatment re-
vealed that whilst in the former the contralateral axillary
relapse was HER2 amplified and displayed a pattern of
gene CNAs similar to that of the HER2-positive compo-
nent of the primary tumor, the cutaneous chest wall me-
tastasis of T8 following trastuzumab and chemotherapy
treatment was HER2 non-amplified (Additional files 17
and 18). In the era of precision medicine, it may be of
importance to acknowledge the existence of HER2 het-
erogeneity in tumors and to take this information into
account when biopsies of HER2-positive breast cancers
are subjected to genomic analyses, as the repertoire of
somatic genetic alterations may differ between the
HER2-positive and HER2-negative components.
Recent studies have suggested that mutations affecting
driver genes and driver genetic alterations are homoge-
neously distributed within some cancer types (for ex-
ample, EGFR,KRAS, and TP53 mutations in non-small
cell lung cancers) [54,55]. On the other hand, in triple-
negative (that is, ER-negative, PR-negative and HER2-
negative) breast cancers, even mutations affecting bona
fide driver genes, such as TP53, have been shown to be
heterogeneously distributed in a subset of cases [9].
Here, we provide direct evidence to demonstrate that,
like triple-negative breast cancers [9], a subset of HER2-
positive cancers are mosaics at diagnosis, and the sub-
populations of cancer cells in these tumors may differ
on the basis of the presence of HER2 gene amplification,
their perceived main driver, in addition to the presence
of subclonal mutations affecting other genes.
Our study has several limitations. Nine of the patients
with HER2 heterogeneous breast cancer included in this
study received adjuvant trastuzumab, of whom two had
relapses to date (Additional files 1, 17 and 18). Given the
limited follow-up and number of relapses, the impact of
the intra-tumor HER2 heterogeneity on response to
anti-HER2 therapy and outcome could not be assessed.
Furthermore, the number of HER2 heterogeneous breast
cancers included in this study is small, due to the rela-
tive rarity of HER2 heterogeneous cases where each
component could be adequately microdissected for
downstream genomics analyses. The statistical power to
identify recurrent driver genetic alterations in the HER2-
negative components that were present in <30% of cases
was therefore limited. However, in all cases potential al-
ternative driver events were identified, suggesting that in
the absence of HER2 amplification, there are several dis-
tinct genetic alterations that may drive the HER2-
negative components of HER2 heterogeneous cases.
Although we have validated functionally three somatic
genetic alterations found in the HER2-negative compo-
nents of the HER2 heterogeneous cases analyzed, several
additional genes identified as amplified or somatically
mutated in the HER2-negative components were docu-
mented (Table 1). Further studies investigating their po-
tential role as drivers of HER2-negative cancers are
warranted. Finally, the mechanistic basis of the HER2
genetic heterogeneity documented in this study remains
to be defined; it should be noted, however, that this
study provides direct evidence to demonstrate that a
known driver and clinically actionable somatic genetic
alteration (that is, HER2 gene amplification) can be het-
erogeneously distributed within breast cancers classified
as HER2-positive by clinical definitions.
Conclusions
A subset of HER2-positive breast cancers show hetero-
geneous HER2 amplification and harbor distinct driver
genetic alterations in the different components. Detailed
genomic analyses of these components coupled with
in vitro experiments resulted in the identification of
BRF2 and DSN1 amplification and HER2 I767M somatic
mutation as potential novel breast cancer driver genetic
events. Given that in HER2 heterogeneous breast
Ng et al. Genome Biology (2015) 16:107 Page 15 of 21

cancers, HER2 gene amplification and protein overex-
pression, their perceived driver and therapeutic target,
may be present only in a subset of cancer cells, our find-
ings have important implications for the delivery of tar-
geted therapies. Harnessing the information stemming
from the genetic heterogeneity affecting genes that are
bona fide drivers of breast cancer and the chronology of
genetic alterations in cancer is germane to the realization
of the potentials of precision medicine.
Materials and methods
Sample selection
Breast cancers diagnosed as HER2-positive but showing
HER2 heterogeneous overexpression were selected and
retrieved from the authors’institutions and re-reviewed
by three pathologists (AG, AV-S and JSR-F). In brief,
over 250 HER2-positive breast cancers diagnosed at
Institut Curie, Paris, France between 2005 and 2008 and
treated with conservative surgery as a first step of treat-
ment were reviewed at Institut Curie and cases showing
a heterogeneous overexpression pattern for HER2 de-
fined as >10% but <100% of cells displaying HER2 over-
expression in the form of strong, complete membrane
staining were identified. Furthermore, cases with similar
staining patterns were obtained from four French Com-
prehensive Cancer Centers (Centre Georges François
Leclerc, Dijon; Institut Claudius Regaud, Toulouse;
Centre Jean Perrin, Clermont-Ferrand; Centre Oscar
Lambret, Lille), and from Hospital Israelita Albert
Einstein, São Paulo, Brazil, and submitted for further re-
view at Institut Curie, Paris, France. Analysis of human
samples was performed in accordance with the French
Bioethics Law 2011-814, the French National Institute of
Cancer (INCa) Ethics Charter and after approval by the
Institut Curie Review Board and Ethics committee
(Comité de Pilotage du Groupe Sein; project 'Repertoire
des alterations genetiques somatiques dans les adenocar-
cinomes mammaires avec heterogeneite du statut HER2',
final version approved on 18 June 2013). Written con-
sent was obtained from patients whose samples were
subjected to massively parallel sequencing. Cases were
anonymized prior to genomic profiling and massively
parallel sequencing analyses. This study is compliant
with the Declaration of Helsinki.
Immunohistochemistry and chromogenic in situ
hybridization
Formalin-fixed, paraffin-embedded sections of the se-
lected HER2 heterogeneous breast cancers were cut at
3μm, and immunohistochemistry performed for ER, PR
and Ki67 using the antibodies and antigen retrieval
methods described in Duprez et al. [56]. For confirm-
ation, tumor sections were stained for HER2 using the
HercepTest (Dako, Glostrup, Denmark) [57]. Scoring
was performed by two pathologists (AV-S and JSR-F) ac-
cording to the American Society of Clinical Oncology
(ASCO)/College of American Pathologists (CAP) guide-
lines [1,25]. Only cases with distinct areas of HER2 3+
positivity with adjacent areas of HER2 1+ positivity or
absent HER2 overexpression were included (n = 41).
Cases with admixed levels of HER2 overexpression, in-
cluding HER2 2+ (that is, equivocal), were excluded. In
addition to the local FISH analyses performed, HER2
gene amplification was confirmed by CISH, which
allowed for the assessment of HER2 gene copy number
status and its distribution in the neoplastic tissues.
CISH was performed using the ZytoDot 2C SPEC
HER2/CEN 17 Probe Kit (Zytovision GmbH, Bremerhaven,
Germany) or the HER2 CISHpharmaDXkit(Dako)
according to the manufacturers’instructions. HER2
gene amplification was defined according to ASCO/
CAP guidelines [1] and assessed by three pathologists
(AG, AV-S and JSR-F). Tumors were graded according
to the Nottingham grading system [58] by three
pathologists (AG, AV-S and JSR-F).
Microdissection and DNA extraction
Of the cases reviewed and selected, 13 breast cancers with
heterogeneous HER2 protein overexpression and HER2
gene amplification by central IHC and CISH were amen-
able to microdissection, as HER2-positive and HER2-
negative areas were sufficiently discrete. The HER2-positive
and HER2-negative components were microdissected either
on a PixCell II laser capture microdissector (Arcturus, Life
Technologies, Paisley, UK) into separate tubes from 8 μm-
thick representative tissue sections stained with HercepTest
for guidance, or using a sterile needle under a stereomicro-
scope in selected cases as previously described [59]. DNA
was extracted from the microdissected HER2-positive
and HER2-negative components using DNeasy Blood
and Tissue kit (Qiagen, Crawley, UK), and quantity was
assessed using a PicoGreen assay (Life Technologies,
Paisley, UK).
Microarray-based comparative genomic hybridization
DNA obtained from the microdissected HER2-positive
and HER2-negative components of 13 HER2 heteroge-
neous breast cancers was subjected separately to aCGH,
using a 32K bacterial artificial chromosome (BAC) array
platform with 50 kb resolution [56,57]. This platform
has been shown to be as robust as, and to have compar-
able resolution with, high-density oligonucleotide arrays
[60-62] and to perform well with DNA extracted from
formalin-fixed paraffin-embedded tissue samples. DNA
labeling and hybridization, image acquisition and data
analysis were performed as previously described [56,57]
(Additional file 19). The aCGH analysis script and code
are available in Additional file 20.
Ng et al. Genome Biology (2015) 16:107 Page 16 of 21

Whole exome sequencing and targeted sequencing
Microdissected frozen samples of the HER2-positive
component, the HER2-negative component and the
matched normal tissue from three cases (T6, T11 and
T12) were subjected to whole exome sequencing (Agilent
SureSelect, Santa Clara, CA, USA) on an Illumina Gen-
ome Analyzer IIx or Illumina HiSeq2000 platform to a
median coverage of 81× (Additional files 8 and 19). Candi-
date somatic variants with mutant allele frequencies >15%
identified by whole exome sequencing in at least one com-
ponent were subjected either to deep re-sequencing on an
Ion Torrent platform (Life Technologies), or to targeted
capture massively parallel sequencing on an Illumina
HiSeq2000 (Additional file 19). Clonal mutation frequen-
cies were inferred using ABSOLUTE [47]. In addition, five
of the twelve cases subjected to aCGH profiling had suffi-
cient DNA from tumor and normal tissues to be subjected
to custom 273 gene paired-end massively parallel targeted
sequencing on an Illumina HiSeq2000 essentially as previ-
ously described [48]. Details of the coverage and depth ob-
tained in each component of these cases are described in
Additional file 8. The strategy for the classification of mu-
tations according to their pathogenicity is outlined in
Additional file 19.
Sanger sequencing
Sanger sequencing of exons 1 to 11 of TP53 was per-
formed in the HER2-positive and HER2-negative com-
ponents of all HER2 heterogeneous breast cancers as
previously described [48] (for primer sequences, see
Additional file 21). A perfect agreement between the re-
sults of TP53 Sanger sequencing and TP53 mutation sta-
tus as defined by massively parallel sequencing was
observed for the cases analyzed.
Cell lines
MCF10A, MCF12A, MCF7, T47D, BT474, HEK293T
and NIH3T3 cells were purchased from the American
Type Culture Collection (ATCC), authenticated by short
tandem repeat profiling as previously described [63], and
tested for mycoplasma infection using a PCR-based test
(ATCC). Culture conditions are described in Additional
file 19.
Vector construction, mutagenesis, transformation and
plasmid preparation
The human ERBB2 (NM_004448) cDNA ORF clone
pCMV6-ERBB2::Myc-DDK was purchased from Origene
(RC212583, Rockville, MD, USA), and the I767M mutation
introduced using the GeneArt Site Directed Mutagenesis
Kit (Life Technologies) following the manufacturer’s recom-
mendations (pCMV6-ERBB2(I767M)::Myc-DDK). ERBB2
(HER2) wild-type and mutant (I767M) open reading frames
were cloned into the pCMV6-TagRFP vector to generate
pCMV6-ERBB2::TagRFP and pCMV6-ERBB2(I767M)::
TagRFP plasmids, respectively, and into the pLenti-
EF1a-GFP-2A-Puro vector (LV067, ABM, Richmond, BC,
Canada), to generate the pLenti-ERBB2 and pLenti-
ERBB2(I767M) lentiviral plasmids, as previously described
[45] (Additional file 19). BRF2 and DSN1 open reading
frames were amplified from total RNA derived from a
healthy donor using SuperScript III First Strand Synthesis
System and Platinum Taq polymerase High Fidelity (Life
Technologies), and cloned into the pCMV6-ZsGreen
vector to generate pCMV6-BRF2::ZsGreen and pCMV6-
DSN1::ZsGreen plasmids, respectively, and into the
pLenti-EF1a-GFP-2A-Puro vector (LV067, ABM), generat-
ing the pLenti-BRF2 and pLenti-DSN1 lentiviral plasmids,
respectively. Sanger sequencing was used to confirm the
reading frames of the wild-type ERBB2, the I767M mutant
ERBB2, and wild-type BRF2 and DSN1.Primersequences
are available in Additional file 21.
Transfections of mammalian cells and analysis of
transgene expression
Transfections of empty vector, wild-type ERBB2,BRF2
and DSN1, and I767M mutant ERBB2 were performed
essentially as previously described [45] (Additional file 19).
The expression of transgenes in stable clones for DSN1
and BRF2 was evaluated at the mRNA level by qualitative
and quantitative RT-PCR (Additional files 7 and 19), given
that antibodies producing satisfactory western blot results
were not available. The expression of wild-type and
I767M mutant HER2 proteins was confirmed by western
blot (see below). The expression of transgenes from
pCMV-ZsGreen/TagRFP-derived plasmids was visually
evaluated 48 hours after transfection using a Nikon
Eclipse Ti fluorescence microscope.
Confocal microscopy for BRF2 and DSN1 subcellular
localization
Cells expressing BRF2-ZsGreen and DSN1-ZsGreen,
TagRFP and ZsGreen (control) proteins grown on cover-
slips were fixed for 15 minutes in 10% buffered formalin,
washed with 1× phosphate buffered saline (PBS), coun-
terstained with 300 nM 4',6-diamidino-2-phenylindole
(DAPI; Life Technologies) for 2 minutes, and mounted
using ProLong Gold Antifade Reagent (LifeTechnologies).
After 24 hours, fluorescence images were acquired using a
Leica TCS SP5-II Upright microscope.
Growth curves
T47D and MCF7 cells stably expressing HER2 wild-type,
HER2(I767M) and vector control (T47D, 1,000 cells/well
and MCF7, 500 cells/well) were seeded in the corre-
sponding normal growth medium in 96-well plates in trip-
licate as previously described [45] (Additional file 19).
Growth curves were plotted and analyzed (multiple t-tests,
Ng et al. Genome Biology (2015) 16:107 Page 17 of 21

corrected for multiple comparisons using the Holm-
Šídák method, alpha: 0.05) using GraphPad Prism
v_6.0c (GraphPad Software, Inc., La Jolla, CA, USA).
Protein fractionation
Cytoplasmic and membrane/organellular enriched pro-
tein fractions from MCF7 and T47D cells expressing
HER2 wild-type and HER2(I767M) proteins and vector
control were prepared using a Cell Fractionation Kit
(Cell Signaling Technologies, Danvers, MA, USA) follow-
ing the manufacturer’s protocol. To determine the effi-
ciency and purity of the cell fractionation, the separated
subcellular fractions were assayed by western blotting
using antibodies against MEK1/2 (cytoplasm) and AIF
(membrane/organellular) (Cell Fractionation Antibody
Sampler Kit, Cell Signaling Technologies), and against
HER2 as previously described [45].
Western blotting
Standard western blotting was conducted as previously
described [63]. Antibodies and dilutions are described in
Additional file 19. Quantification of conjugated second-
ary antibodies and analysis were performed using the
Image Studio Software from LI-COR (LI-COR Biosci-
ences, Lincoln, NE, USA).
Foci formation
NIH3T3 cells expressing HER2 wild-type, HER2(I767M),
BRF2 and DSN1 protein, and empty vector control cells
were seeded at 5 × 10
5
cells density in six-well culture
dishes in full media without penicillin/ streptomycin for
up to 21 days, then fixed with methanol and stained with
0.5% (w/v) crystal violet. Photomicrographs were taken
using a Nikon DS5000 digital camera at day 21 for
empty vector, BRF2 and DSN1, and using the EVOS XL
Imaging System (Life Technologies) at days 5 and 12 for
HER2 wild-type, HER2(I767M) and empty vector. All
experiments were performed in triplicate. Foci were
counted at the end of the assays using Image J and ana-
lyzed using GraphPad Prism v_6.0c (unpaired Student’s
t-test, two-tailed).
Anchorage-independent growth
Anchorage-independent transformation assays were per-
formed using the Cell Biolabs CytoSelect 96-well Cell
Transformation Assay (colorimetric, Cell Biolabs, San
Diego, CA, USA) following the manufacturer’s instruc-
tions. Briefly, MCF10A cells stably expressing HER2
wild-type, HER2(I767M), BRF2 and DSN1 proteins, as
well as vector control cells, were incubated in a propri-
etary semisolid agar media for 8 days before being solu-
bilized, transferred and detected by the provided MTT
Solution (570 nm) using the Victor X4 Multimode Plate
Reader (PerkinElmer, Waltham, MA, USA). Assays were
performed in quadruplicate reactions. For colony count-
ing, soft-agar cultures were set up in triplicate as de-
scribed above for i) MCF10A cells (stable for HER2
wild-type, HER2(I767M), BRF2, DSN1 and empty vector;
transient for HER2 wild-type, HER2(I767M), HER2(Y835F),
HER2(V777L) and empty vector), ii) NIH3T3 cells (stable
for HER2 wild-type, HER2(I767M) and empty vector; tran-
sient for HER2 wild-type, HER2(I767M), HER2(Y835F),
HER2(V777L) and empty vector), and iii) MCF12A
cells (transient for HER2 wild-type, HER2(I767M),
HER2(Y835F), HER2(V777L) and empty vector). Colony
number and size were documented at day 9 using the phase
contrast EVOS XL Imaging System (Life Technologies).
Colonies were counted in Image J and colony size was
determined in MetaMorph Image Analysis software
(MolecularDevices,Sunnyvale,CA,USA).Analyses
were carried out using GraphPad Prism v_6.0c.
ERBB2-TagRFP and ERBB2(I767M)-TagRFP
immunoprecipitation and tyrosine kinase assay
Forty-eight hours post-transfection with pCMV6-
ERBB2::TagRFP, pCMV6-ERBB2(I767M)::TagRFP and
the vector control, HEK293T cells were treated with
10 ng/ml of human neuregulin-1 (hNRG-1, Cell Signal-
ing Technologies) for HER2 pre-activation or vehicle
(20 mM citrate, pH 3.0) for 15 minutes. TagRFP anti-
body (Evrogen, Farmingdale, NY, USA) was crosslinked to
magnetic beads using the PierceTM Crosslink Magnetic
IP/Co-IP Kit (Thermo Scientific, Somerset, NJ, USA) fol-
lowing the manufacturers’recommendations. On the day
of preparation, 600 μl of protein lysates at 1 mg/ml were
pre-cleared using 75 μl of washed protein A/G magnetic
bead slurry and incubated for 1 hour at 4°C. Triplicates of
200 μl (1 mg/ml) of the pre-cleared lysates were then in-
cubated with the equivalent of 5 μg of TagRFP antibody
conjugated to magnetic beads under gentle rocking over-
night at 4°C. The magnetic beads were then pelleted by
placing the tubes in a magnetic separation rack. The mag-
netic bead pellets were washed five times with 1 ml of ice-
cold M-PER Mammalian Protein Extraction Reagent sup-
plemented with Halt Protease and Phosphatase inhibitors
cocktail (Thermo Scientific). All steps were carried out at
4°C. Tyrosine kinase activity was evaluated using the ADP
Hunter HS Assay (DiscoveRx, Fremont, CA, USA) and
the Tyrosine Kinase Assay Kit (colorimetric detection,
Millipore, Billerica, MA, USA) essentially as previously de-
scribed [45] (Additional file 19).
Three-dimensional matrigel cultures
MCF10A and MCF12A cells expressing HER2 wild-type,
HER2(I767M), BRF2 and DSN1 proteins, as well as vec-
tor control cells, were seeded on top of growth factor-
reduced reconstituted basement membrane (Matrigel,
Ng et al. Genome Biology (2015) 16:107 Page 18 of 21

BD Biosciences, San Jose, CA, USA) and analyzed essen-
tially as previously described [45] (Additional file 19).
Data availability
aCGH data have been deposited into the NCBI Gene
Expression Omnibus under the accession GSE67908.
The R code for analysis of the aCGH data is deposited
on GitHub [64]. Whole exome data have been deposited
into the NCBI Sequence Read Archive under the acces-
sion SRP049005.
Additional files
Additional file 1: Clinico-pathologic characteristics of HER2
heterogeneous breast cancers included in this study, and genomic
analyses performed.
Additional file 2: Representative micrographs of HER2
heterogeneous breast cancers included in this study. Micrographs of
representative hematoxylin and eosin (H&E) stained sections and HER2
immunohistochemistry (IHC) of 12 HER2 heterogeneous breast cancers
included in this study (T1-T13). Microdissected HER2-positive and HER2-
negative components of each case were subjected to gene copy number
profiling, and chromosome 17 plots are shown to confirm the presence
(arrow) and absence of HER2 gene amplification (17q12), respectively. In
the chromosome plots, the circular binary segmentation (cbs)-smoothed
Log
2
ratios for each bacterial artificial chromosome mapping to chromosome
17 were plotted on the y-axis and their genomic positions were plotted on
the x-axis. Gains, amplifications and losses are highlighted in dark green,
bright green and red, respectively.
Additional file 3: Differences in the patterns of gene copy number
alterations between the HER2-positive and HER2-negative components
of HER2 heterogeneous breast cancers. Subtraction of gene copy number
alterations identified in the HER2 non-amplified component from those in the
HER2 amplified component of a given HER2 heterogeneous breast cancer.
Differences between the genomic profiles were found to be negligible (for
example, T1, top), moderate (for example, T10, middle) or substantial
(for example, T12, bottom). In these genome plots, the scaled and
median centered circular binary segmentation (cbs)-smoothed Log
2
ratios for each bacterial artificial chromosome (BAC) obtained in the
analysis of the HER2-negative component was subtracted from the
respective BAC from the HER2-positive component and plotted on
the y-axis according to its genomic position on the x-axis. Gains are
highlighted in green, and losses are depicted in red.
Additional file 4: List of amplifications present in HER2-negative
but absent in matched HER2-positive components of HER2
heterogeneous breast cancers.
Additional file 5: Amplified genes restricted to HER2-negative
components of HER2 heterogeneous breast cancers, whose
expression is copy number-regulated in luminal breast cancers
of the TCGA dataset.
Additional file 6: Amplified genes restricted to HER2-negative
components of HER2 heterogeneous breast cancers, and their copy
number profiles in luminal breast cancers from The Cancer Genome
Atlas (TCGA) dataset. (A) Re-analysis of gene copy number profiles of
luminal breast cancers from the TCGA dataset using amplified genes
identified to be restricted to HER2-negative components of HER2
heterogeneous breast cancers. Gene copy number information was
retrieved from the cBioPortal website [65]. (B) HER2,BRF2 and DSN1 are
copy number regulated genes. Correlation between mRNA expression
(y-axis) and copy number states (x-axis) as determined by GISTIC, retrieved
from the cBioPortal website [65].
Additional file 7: HER2, BRF2 and DSN1 mRNA expression levels.
(A,B) Given the lack of commercial anti-BRF2 and anti-DSN1 antibodies
that produced reliable western blot results, the mRNA expression levels
of forced expression of BRF2 and DSN1 in MCF10A and NIH3T3 cells were
assessed by semiquantitative RT-PCR (A) and by quantitative real-time
RT-PCR (B). Wild-type HER2 (WT) and I767M mutant HER2 (MUT), as well
as GAPDH were included as controls.
Additional file 8: Sequencing statistics of the HER2 heterogeneous
breast cancer subjected to whole exome sequencing and to
targeted capture massively parallel sequencing using a platform
containing baits targeting all exons of 273 genes.
Additional file 9: Mutations identified by whole exome sequencing
analysis and validated by amplicon sequencing on an Ion Torrent
Personal Genome Machine or by targeted capture massively parallel
sequencing on an Illumina HiSeq2000.
Additional file 10: Mutations validated in the HER2-positive and
HER2-negative components of case T12 using targeted capture
massively parallel sequencing. Allelic fractions of mutations identified
in HER2-positive and HER2-negative components of the HER2 heterogeneous
breast cancer T12 subjected to targeted capture massively parallel
sequencing using a panel of 273 genes comprising genes frequently
mutated in breast cancer and DNA repair-related genes. Indel, insertion
and deletion; SNV, single nucleotide variant.
Additional file 11: Somatic mutations restricted to HER2-negative
components of HER2 heterogeneous breast cancers identified by
massively parallel sequencing.
Additional file 12: Anchorage-independent growth of NIH3T3 cells
stably expressing empty vector, wild-type and I767M mutant HER2.
Anchorage-independent growth of NIH3T3 cells stably expressing empty
vector, wild-type HER2 or I767M mutant HER2 protein. The number and
size of colonies was quantified (right). *P< 0.05, **P< 0.01, unpaired t-test.
Error bars represent standard deviation of mean. N.s., not significant.
Additional file 13: Anchorage-independent growth of NIH3T3,
MCF10A and MCF12A cells transiently expressing empty vector,
HER2 wild-type, I767M mutant HER2, and other previously validated
HER2 mutations. (A-C) Anchorage-independent growth of NIH3T3 (A),
MCF10A (B) and MCF12A (C) cells transiently expressing empty vector,
wild-type HER2, HER2 I767M, HER2 V777L and HER2 Y835F in NIH3T3. The
V777L and the Y835F HER2 mutations have been previously shown [7]
to be strongly activating or not activating, respectively. The number and
size of colonies was quantified (right). *P< 0.05, **P< 0.01, ***P< 0.001,
****P< 0.0001, unpaired t-test. Error bars represent standard deviation of
mean. N.s., not significant.
Additional file 14: Cellular fractionation of MCF7 and T47D cells
expressing wild-type and I767M mutant HER2. Cellular fractionation
and western blot analysis illustrating the subcellular distribution of forced
expression of wild-type HER2 and I767M mutant HER2 in MCF7 and
T47D, and the HER2 amplified BT474 control cells (untransfected). HER2
expression was assessed by western blotting. The efficiency and purity of
cellular fractionation was evaluated using expression of AIF (membrane/
organellular localization) and MEK1/2 (cytoplasmic localization). Cyto,
cytoplasm; Mem, membrane; WCL, whole cell lysate; WT, wild-type.
Additional file 15: Assessment of neuregulin-1 expression in T47D
and MCF7 cells. (A) Neuregulin-1 expression was assessed in protein
lysates and in conditioned media from MCF7 and T47D cells stably
expressing empty vector, HER2 wild-type and I767M mutant HER2 using
quantitative infrared fluorescent western blotting (LI-COR). (B)
Quantitative RT-PCR analysis of NRG1 mRNA expression in MCF7 and
T47D cells.
Additional file 16: Representative micrographs obtained from
MCF12A cells transiently expressing I767M mutant HER2. Note that some
acinar structures display infiltrating borders. Original magnification, 40×.
Additional file 17: Contralateral axillary relapse of case T4 after
adjuvant trastuzumab and chemotherapy treatment. (A,B) Representative
micrographs of the hematoxylin and eosin stained sections of the
distant relapse of case T4. Note the areas of necrosis and hemorrhage
in the bottom left corner of (B). (C,D) Representative micrographs of
HER2 immunohistochemical assessment of the distant relapse of case
T4 demonstrate complete, weak-to-moderate membranous staining
in >10% of the cells. (E) Chromogenic in situ hybridization confirmed
Ng et al. Genome Biology (2015) 16:107 Page 19 of 21

thepresenceofHER2 amplification (HER2 probe, green; chromosome
17 centromere probe, red). (F) Chromosome 17 plot demonstrating
amplification of the HER2 locus. In the chromosome plot, the circular
binary segmentation (cbs)-smoothed Log
2
ratios for each bacterial artificial
chromosome mapping to chromosome 17 are plotted on the y-axis and
their genomic positions are plotted on the x-axis. Gains, amplifications and
losses are highlighted in dark green, bright green and red, respectively. (G)
Genome plot of the distant contra-lateral axillary relapse of case T4. In the
genome plot, the cbs-smoothed Log
2
ratios for each bacterial artificial
chromosome are plotted on the y-axis and their genomic positions are
plotted on the x-axis. Gains, amplifications and losses are highlighted in dark
green, bright green and red, respectively. Note the similarities between the
genome plot of the relapse and the HER2-positive component of the T4
primary tumor illustrated in Figure 3A. Original magnification: 40× (A,C);
100× (B,D); 200× (E); 400× (E, inset).
Additional file 18: Cutaneous chest wall distant relapse of case T8
after adjuvant trastuzumab and chemotherapy treatment. (A,B)
Representative micrographs of the hematoxylin and eosin stained
sections of the distant relapse of case T8. (C,D) Representative micrographs
of HER2 immunohistochemical assessment of the distant relapse of case T8
demonstrate incomplete, weak-to-moderate membranous staining in >10%
of the cells. (E) Chromogenic in situ hybridization confirmed the absence
or presence of HER2 amplification (HER2 probe, black; chromosome 17
centromere probe, red). Original magnification: 40× (A,C); 100× (B,D);
200× (E).
Additional file 19: Supplementary methods.
Additional file 20: R script and code.
Additional file 21: Sanger sequencing primers used in this study.
Abbreviations
aCGH: array-based comparative genomic hybridization; BAC: bacterial artificial
chromosome; CISH: chromogenic in situ hybridization; CNA: copy number
alteration; ER: estrogen receptor; FISH: fluorescence in situ hybridization;
IHC: immunohistochemistry; PR: progesterone receptor; SNV: single
nucleotide variant; TCGA: The Cancer Genome Atlas.
Competing interests
The authors have no conflicts of interest to declare.
Authors’contributions
AV-S and JSR-F conceived the study. LA, FCG, SEB, ML-T, FP-L, SG, XS-G, PHC,
and AV-S provided materials. AG, AV-S and JRF-S performed the histopathologic
review. LGM, AG, H-CW, BW, SP, CFC, PMW, PW, DNR and RN carried out the
experiments. CKYN and RSL performed the bioinformatics analysis which was
coordinated by BW and JSR-F. CKYN, BW, LGM, H-CW, SP, PMW, DNR, FCG, and
JSR-F discussed and interpreted the results. CKYN, BW and LGM wrote the first
draft. All authors read and approved the final manuscript.
Acknowledgements
A Gauthier is supported by the Fondation Curie; A Vincent-Salomon is
supported by an Interface INSERM grant. S Piscuoglio is funded by a Susan G
Komen Postdoctoral Fellowship Grant (PDF14298348), and R Natrajan by a
Breast Cancer Campaign Career Development Fellowship (2011MaySF01). We
thank Ke Xu at the MSKCC Molecular Cytology Core Facility for the image
analysis assistance provided. Research reported in this publication was
supported in part by the Cancer Center Support Grant of the National
Institutes of Health/National Cancer Institute under award number P30CA008748.
The content of this study is solely the responsibility of the authors and does not
necessarily represent the official views of the National Institutes of Health.
Author details
1
Department of Pathology, Memorial Sloan Kettering Cancer Center, New
York, NY 10065, USA.
2
Department of Tumor Biology, Institut Curie, 75248
Paris, France.
3
The Breakthrough Breast Cancer Research Centre, Institute of
Cancer Research, London SW3 6JB, UK.
4
Department of Pathology and CRB
Ferdinand Cabanne, Centre Georges Francois Leclerc, 21000 Dijon, France.
5
Departments of Anatomic Pathology and Oncology, Hospital Israelita Albert
Einstein, São Paulo, 05652-900, Brazil.
6
Department of Pathology, Institut
Claudius Regaud, IUCT-Oncopole, 31059 Toulouse, France.
7
Department of
Pathology, Centre Jean Perrin, and University of Auvergne, 63000 Clermont
Ferrand, France.
8
Department of Pathology, Centre Oscar Lambret, 59000
Lille, France.
9
Department of Medicine, Memorial Sloan Kettering Cancer
Center, New York, NY 10065, USA.
10
Department of Medical Oncology,
Institut Curie, 75248 Paris, France.
11
Affiliate Member, Human Oncology &
Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York,
NY 10065, USA.
12
Affiliate Member, Computational Biology Center, Memorial
Sloan Kettering Cancer Center, New York, NY 10065, USA.
Received: 5 November 2014 Accepted: 20 April 2015
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