Subtype-specific accumulation of intracellular zinc pools is associated with the malignant phenotype in breast cancer
Chandler et al. Molecular Cancer
Subtype-specific accumulation of intracellular zinc pools is associated with the malignant phenotype in breast cancer
Paige Chandler 0 1
Bose S. Kochupurakkal 3 4
Samina Alam 0 5
Andrea L. Richardson 3
David I. Soybel 0 5
Shannon L. Kelleher 0 1 2 5
0 The Department of Cellular and Molecular Physiology, Penn State Hershey College of Medicine , Hershey, PA 17033 , USA
1 The Interdisciplinary Graduate Program in Physiology, Penn State Hershey College of Medicine , Hershey, PA 17033 , USA
2 The Department of Pharmacology, Penn State Hershey College of Medicine , Hershey, PA 17033 , USA
3 Department of Pathology, Brigham and Women's Hospital, Harvard Medical School , Boston, MA 02115 , USA
4 Dana Farber Cancer Institute , Boston, MA 02115 , USA
5 The Department of Surgery, Penn State Hershey College of Medicine , Hershey, PA 17033 , USA
Background: Zinc (Zn) hyper-accumulates in breast tumors and malignant cell lines compared to normal mammary epithelium. The mechanisms responsible for Zn accumulation and the consequence of Zn dysregulation are poorly understood. Methods: Microarrays were performed to assess differences in the expression of Zn transporters and metallothioneins (MTs) in human breast tumors and breast cancer cell lines. Real-time PCR and immunoblotting were employed to profile Zn transporter expression in representative luminal (T47D), basal (MDA-MB-231), and non-malignant (MCF10A) cell lines. Zn distribution in human tumors was assessed by X-ray fluorescence imaging. Zn distribution and content in cell lines was measured using FluoZin-3 imaging, and quantification and atomic absorption spectroscopy. Functional consequences of ZnT2 over-expression in MDA-MB-231 cells including invasion, proliferation, and cell cycle were measured using Boyden chambers, MTT assays, and flow cytometry, respectively. Results: Gene expression profiling of human breast tumors and breast cancer cell lines identified subtype-specific dysregulation in the Zn transporting network. X-ray fluorescence imaging of breast tumor tissues revealed Zn hyper-accumulation at the margins of Luminal breast tumors while Zn was more evenly distributed within Basal tumors. While both T47D and MDA-MB-231 cells hyper-accumulated Zn relative to MCF10A cells, T47D cells accumulated 2.5-fold more Zn compared to MDA-MB-231 cells. FluoZin-3 imaging indicated that Zn was sequestered into numerous large vesicles in T47D cells, but was retained in the cytoplasm and found in fewer and larger, amorphous sub-cellular compartments in MDA-MB-231 cells. The differences in Zn localization mirrored the relative abundance of the Zn transporter ZnT2; T47D cells over-expressed ZnT2, whereas MDA-MB-231 cells did not express ZnT2 protein due to proteasomal degradation. To determine the functional relevance of the lack of ZnT2 in MDA-MB-231cells, cells were transfected to express ZnT2. ZnT2 over-expression led to Zn vesicularization, shifts in cell cycle, enhanced apoptosis, and reduced proliferation and invasion. Conclusions: This comprehensive analysis of the Zn transporting network in malignant breast tumors and cell lines illustrates that distinct subtype-specific dysregulation of Zn management may underlie phenotypic characteristics of breast cancers such as grade, invasiveness, metastatic potential, and response to therapy.
Breast cancer; Basal/Luminal; Metallothionein; Zinc; Zinc importer; Zinc transporter
Breast cancer is a heterogeneous disease at the
molecular, histopathological, and clinical level. Through gene
expression profiling, four subtypes based on expression
of estrogen receptor (ER), progesterone receptor (PR),
and epidermal growth factor receptor 2 (HER2) are
recognized including: Luminal A (ER+/PR+/HER2−),
Luminal B (ER+/PR+/HER2+), Basal (ER−/PR−/HER2−) and
HER2- enriched (ER−/PR−/HER2+). These subtypes
differ in incidence [
], aggressiveness, and response to
]. Recently, it has been reported that breast
tumors accumulate zinc (Zn) to levels well above those
observed in normal tissue . The degree of Zn
accumulation is associated with cancer progression [
]. However, the mechanisms responsible for Zn
accumulation, and the relationship between Zn
accumulation and breast cancer subtype are not understood.
A multitude of cellular processes are regulated by Zn
including transcription, cell signaling, proliferation,
invasion, apoptosis, and autophagy [
]. Cellular Zn
metabolism is tightly regulated by a “Zn transporting network”
which consists of 24 Zn transporting proteins that
transport Zn into discrete sub-cellular compartments. The
ZnT family of Zn transporters (SLC30A1-10 gene family)
contains 10 members (ZnT1-10) [
] that export Zn from
the cytoplasm, either directly across the cell membrane
or into intracellular compartments. The ZIP family of
Zn transporters (SLC39A1-14 gene family) contains 14
members (ZIP1-14) [
] and facilitates Zn import into
the cytoplasm, either from across the cell membrane or
from within a sub-cellular compartment. Cellular Zn
management is also regulated by metallothioneins (MTs)
], which are Zn binding proteins that buffer
cytoplasmic Zn. ZnT2-mediated Zn accumulation into vesicles
and MT-binding are the two primary mechanisms
through which cells protect themselves from Zn toxicity,
and both are positively regulated by Zn exposure
through the activation of four metal responsive elements
(MREs) in their promoters [
Over-expression of several Zn transporters (ZIP6, ZIP7,
ZIP10, and ZnT2) [
] is associated with Zn
hyperaccumulation in breast tumors and several breast cancer
cell lines. ZIP6 over-expression has been noted in ER+
] and is associated with less aggressive tumors
]. Similarly, ZnT2 over-expression accumulates Zn in
vesicles which protects ER+ T47D cells from Zn toxicity
]. In contrast, ZIP10 is over-expressed in highly
invasive, basal-like cell lines (MDA-MB-231 and
MDA-MB435S cells) and potentiates invasion [
]. Similarly, ZIP7
over-expression in tamoxifen-resistant MCF7 cells is
associated with enhanced motility [
]. In addition to Zn
transporters, MT over-expression is documented in
~88 % of invasive ductal carcinoma tissue biopsies
], and is generally associated with poor prognosis
] and high histological grade [
]. However, reports of
Zn transporter dysregulation are sporadic and a
comprehensive analysis of Zn management in specific breast
cancer subtypes has not been reported.
We reasoned that the molecular portrait of the Zn
transporting network may be very different between
malignant subtypes, and perhaps even a driver of their
phenotypic behaviors. Herein, we used targeted genomic,
proteomic, and Zn profiling in breast tumors and
malignant cell lines that have characteristic features of
Luminal (low-invasive, ER+/PR+/HER2−; T47D cells) and
Basal (highly invasive, ER−/PR−/HER2−; MDA-MB-231
cells) subtypes. We observed subtype-specific differences
in Zn management between Luminal and Basal breast
tumors, and in cell culture models of luminal and basal-like
breast cancer cells. Importantly, we found that Zn
sequestration in vesicles through expression of ZnT2 profoundly
reduced the proliferative and invasive phenotype of
MDAMB-231 cells, indicating that Zn dysregulation is
subtypespecific, which may inform the development of novel
diagnostic or therapeutic strategies.
The distribution of Zn accumulation in breast tumors differs between Luminal and Basal tumors
We first utilized X-ray fluorescence microscopy to
determine the spatial distribution of Zn in Luminal and Basal
tumors and adjacent normal tissue (Fig. 1). Spatial
analysis revealed differences in Zn content and localization
within the malignant regions. In Luminal breast tumors,
Zn primarily accumulated around the tumor periphery.
In Basal breast tumors, Zn was more evenly distributed
throughout the malignant tissue. When compared with
the distribution of calcium (Ca), some differences were
noted such that Zn overlapped closely with Ca in Basal
tumors, but this was less consistent in Luminal tumors.
Zn transporter expression differs between Luminal and
Due to the differences in Zn distribution, we postulated
that Basal and Luminal breast tumors would have unique
patterns of Zn transporter expression. We analyzed
microarray gene expression data derived from human
breast tumors and noted a significant effect of subtype on
Zn transporter expression (Fig. 2a). Pair-wise comparison
of the subtypes show that Basal and ER+ tumors had
a distinct pattern of SLC30A, SLC39A, and MT gene
expression. Significant differences were detected in
the expression of MT1, MT2, SLC30A5-6, SLC30A8-9,
and SLC39A1-2, SLC39A4, SLC39A6-9, SLC39A11,
and SLC39A14 with a false discovery rate (FDR) of p <
0.05. In addition, we noted more similarity between the
Basal and HER2+ subtypes and less similarity between
the Basal and ER+ subtypes with respect to the
expression of the SLC30A, SLC39A, and MT genes
(Table 1). Of particular note, we found that MTs,
SLC39A4, and SLC39A14 were consistently
overexpressed while SLC39A6, SLC39A9, and SLC39A11 were
consistently under-expressed in the Basal subtypes
(foldchange >1.5). Finally, among ER+ tumors, increasing
tumor grade was associated with increased expression of
SLC39A8. Taken together our data indicated that gene
expression of members of the Zn transporting network
was substantially different between Basal and Luminal
breast tumor subtypes.
Zn transporter expression in luminal (T47D) and basal-like (MDA-MB-231) breast cancer cell lines mimics differences in expression in Luminal and Basal tumors
We next analyzed microarray gene expression data of
all breast cancer cell lines that were available (Fig. 2b).
Statistical analysis of Zn transporter expression
indicated that similar to what was observed in breast tumor
tissues, basal-like cancer cells also had significantly higher
expression of MTs and SLC39A14 and lower expression of
SLC39A6, SLC39A9, and SLC39A11 (fold-change >1.5;
FDR, p < 0.05) (Table 1). In sum, genes regulating Zn
Fig. 2 (See legend on next page.)
(See figure on previous page.)
Fig. 2 Microarray analysis reveals differential expression of SLC30A, SLC39A, and MT genes in breast cancer subtypes. Subtype dependent
differential expression of SLC30A, SLC39A, and MT genes in a breast tumors and b cell lines were identified using ANOVA and the heat map
representing differential expression of significant genes (FDR <0.05) is shown. Breast tumor classification is indicated by the color bar across the
top as Basal (red), ER+-High Grade (ER HG, blue), ER+-Low Grade (ER LG, green), HER (purple) and cell lines classified as Luminal (blue) and Basal
(red). The classifications were used as ANOVA factors and the mean log2 expression value was shifted to zero to generate the heatmap
transport have a subtype-specific pattern of expression in
cell lines under normal culture conditions that is similar
to that observed in breast tumors, suggesting that
malignant cell lines are reliable models for dissecting Zn
metabolism and the consequences of dysregulation in breast
Based upon these data, we chose T47D and
MDAMB-231 cells as common models representing Luminal
and Basal subtypes of breast cancer, respectively. First,
we measured the relative gene expression of all Zn
transporters and MTs using relative real-time PCR (Fig. 3
and Table 1). Similar to our microarray analysis, we
identified significant subtype-specific differences in the
expression of numerous Zn management proteins. MT
was only expressed in basal-like MDA-MB-231 cells.
Expression of four SLC30A (SLC30A2, SLC30A5, SLC30A6,
and SLC30A10) and two SLC39A (SLC39A4 and
SLC39A11) genes were significantly lower in basal-like
MDA-MB-231 cells compared to luminal T47D cells (p
< 0.05). Expression of SLC30A9, SLC39A2, and SLC39A8
were significantly higher in MDA-MB-231 cells relative
to expression in T47D cells (p < 0.05).
We next compared the expression of Zn transporters in
T47D and MDA-MB-231 cells to the non-transformed
ER HG estrogen receptor positive, high grade, ER LG estrogen receptor positive, low grade
*Numbers represent mean fold difference between subtypes analyzed by independent pairwise comparison, p < 0.05
**Numbers represent mean fold difference between MDA-MB-231 (basal-like) and T47D (luminal) cells analyzed by Student’s t-test, p < 0.05
aOnly genes that are significantly differentially expressed are indicated
mammary epithelial cell line MCF10A (Fig. 3). Luminal
cells: Consistent with reports that MT over-expression is
associated with invasiveness [
], we detected minimal
mRNA expression of MTs in non-invasive, T47D cells.
T47D cells had significantly lower expression of five
SLC39A (SLC39A1, SLC39A3, and SLC39A8-10) and three
SLC30A (SLC30A1, SLC30A7, and SLC30A9) genes
relative to expression in MCF10A cells (p < 0.05). Expression
of two SLC39A (SLC39A4 and SLC39A7) and two SLC30A
(SLC30A2 and SLC30A10) genes were higher relative to
expression in MCF10A cells (p < 0.05). Next, protein
expression profiles were generated for most of the ZIP
(SLC39A gene family) and ZnT (SLC30A gene family)
proteins except for ZIP2, ZIP9, and ZnT7, which we were
unable to identify suitable antibodies (Fig. 4). Changes in
gene expression did not always parallel changes in protein
abundance (Table 2). The protein abundance of ZnT9 and
several ZIP proteins (ZIP1, ZIP4, ZIP7, and ZIP12) was
significantly lower in T47D compared to MCF10A cells,
while numerous ZIP (ZIP5, ZIP6, ZIP8, ZIP10, and ZIP14)
and ZnT (ZnT1, ZnT2, ZnT3, ZnT4, ZnT5, ZnT8 and
ZnT10) proteins were significantly over-expressed in
T47D cells compared with MCF10A cells. In addition, the
presence of an additional protein much larger than the
predicted molecular mass was detected for ZIP3 (~130
kD), ZIP14 (~76 kD), and ZnT6 (~110 kD) in T47D cells.
(Only the larger molecular mass of the ZIP14 protein
has been reported previously [in U251 cells, Abcam],
thus it was included in the quantification).
Additionally, ZIP4 and ZIP11 proteins were only robustly detected
in MCF10A cells and ZIP13 protein was not detected in
human breast cells (data not shown). Basal-like cells:
Consistent with reports that MT over-expression is associated
with invasiveness [
], mRNA expression of MTs was
~200-fold higher in basal-like cells relative to expression
in MCF10A cells (Fig. 3). MDA-MB-231 cells had lower
(>4-fold) expression of six SLC30A (SLC30A1, SLC30A5,
SLC30A6, SLC30A7, SLC30A8, and SLC30A10) and five
Chandler et al. Molecular Cancer (2016) 15:2
Fig. 4 (See legend on next page.)
(See figure on previous page.)
Fig. 4 Zinc transporter proteins are differentially expressed in MCF10A, T47D, and MDA-MB-231 cells. a Representative immunoblots of ZnT proteins
detected in MCF10A, T47D, and MDA-MB-231 cells. Suitable antibodies for ZnT7 were not identified. B-actin was used as a normalization control.
Images from different immunoblots or images from different parts of the same immunoblot are separated by dividing lines (for visual consistency). The
major isoform was used for quantification. Data represent mean Zn transporter: β-actin ± SD, n = 2-3 for each cell line/experiment; each experiment
was conducted 2–5 times. Asterisk denotes a significant difference from MCF10A cells, *p < 0.05. ND, not detected. b Representative immunoblots of
ZIP proteins detected in MCF10A, T47D, and MDA-MB-231 cells. Suitable antibodies for ZIP2 and ZIP9 were not identified. ZIP13 was not
expressed in MCF10A, T47D or MDA-MB-231 cells, but was detected in HC11 cells (data not shown). Data represent mean Zn
transporter:βactin ± SD, n = 2-3 samples/cell line/experiment and each experiment was conducted 2–5 times. Asterisk denotes a significant difference from
MCF10A cells, p < 0.05. ND, not detected
SLC39A (SLC39A1, SLC39A2, SLC39A3, SLC39A6, and
SLC39A9) genes. Only the expression of SLC39A5 was
significantly higher (~5-fold) relative to its expression in
MCF10A cells (p < 0.05). Again, changes in gene
expression did not parallel changes in protein abundance
(Table 2). The protein abundance of four ZnT (ZnT2,
ZnT5, ZnT8, and ZnT9) and six ZIP (ZIP4, ZIP5, ZIP7,
ZIP8, ZIP11, and ZIP12) proteins was significantly lower,
aGreen indicates lower expression compared with MCF10A cells; yellow
indicates no change in expression compared with MCF10A cells; red indicates
higher expression compared with MCF10A cells
while only two Zn transporters (ZIP10 and ZnT1) were
significantly over-expressed at the protein level in
MDAMB-231 compared with MCF10A cells (Fig. 4). A larger
isoform (~2 kD larger than expected) of ZIP1 and ZIP10
was detected in MDA-MB-231 cells; however, these
isoforms were not detected in MCF10A cells and were not
included in the densitometric analysis. ZnT10 and ZIP14
were not detected in MCF10A or MDA-MB-231 cells.
ZnT2 protein is degraded in MDA-MB-231 cells
As described above, we noted that while mRNA
expression of numerous Zn transporters in MDA-MB-231 cells
was similar to/greater than expression in MCF10A cells
(ZIP4, ZIP5, ZIP7, ZIP8, ZIP11, ZIP12, ZnT2, and ZnT9),
the protein levels were greatly reduced. To provide some
mechanistic understanding behind this finding we chose
to focus on ZnT2. To determine why ZnT2 protein was
minimally detectable in MDA-MB-231 cells, we inhibited
proteasomal and lysosomal degradation and measured
ZnT2 abundance by immunoblotting. Treatment of
MDA-MB-231 cells with the proteasomal inhibitor
MG132, but not the lysosomal inhibitor chloroquine,
resulted in greater abundance of ZnT2 compared to
untreated MDA-MB-231 cells (Fig. 5), suggesting that ZnT2
is proteosomally degraded in MDA-MB-231 cells.
T47D and MDA-MB-231 cells accumulate more Zn but distribute Zn differently compared to MCF10A cells
We next assessed differences in Zn content and
distribution within these breast cancer and non-malignant cells.
We first quantified the total amount of Zn in cell lysates
using atomic absorption spectroscopy. Similar to
observations in breast tumors, T47D cells accumulated
~5fold greater Zn (0.276 ± 0.01 μg Zn/mg protein) while
MDA-MB-231 cells accumulated ~2.5-fold greater Zn
(0.107 ± 0.02 μg Zn/mg protein) relative to MCF10A cells
(0.057 ± 0.06 μg Zn/mg protein), p < 0.05. To visualize the
localization of Zn pools within these distinct subtypes, we
used the Zn-responsive fluorophore FluoZin-3 [
fluoresces upon Zn binding (kD = 4–15 nM) [
noted that the staining pattern of FluoZin-3 was distinctly
different in each cell line (Fig. 6a). Labile Zn pools in
MCF10A cells were confined to small peri-nuclear
vesicles, consistent with our previous observation that Zn
accumulates in the Golgi apparatus/endoplasmic
reticulum in normal mammary cells [
]. In contrast,
labile Zn pools in T47D cells were enriched in numerous
large punctate intracellular vesicles, while in
MDA-MB231 cells, hazy fluorescence was noted throughout the
cytoplasm and in a large, amorphous subcellular
compartment(s). Importantly, consistent with the
measurements of total Zn concentration noted above,
quantification of FluoZin-3 fluorescence suggested that
T47D cells accumulated significantly greater labile Zn
compared with MCF10A and MDA-MB-231 cells (Fig. 6b).
Collectively, Zn transporter protein profiling (setting a
threshold of a >1.4-fold change in protein abundance)
combined with the visualization of sub-cellular Zn
pools using FluoZin-3, allowed us to generate a model
of the Zn ionome (the profile of subcellular Zn
transporters and Zn distribution) in luminal and basal-like
breast tumor cells (Fig. 6c). This modeling illustrates
that increased abundance of numerous ZIP and
vesicular ZnT proteins (ZnT2, ZnT3, ZnT4, ZnT5, ZnT8, and
ZnT10) is associated with enhanced vesicular Zn
accumulation in luminal cells, while increased expression of only
two ZIP proteins and MT is associated with more
moderate Zn accumulation in basal-like cells.
ZnT2 staining is greater in Luminal breast tumors compared with Basal tumors and adjacent non-malignant tissue
Because ZnT2 expression is positively associated with
vesicular Zn accumulation in malignant breast cancer
cells, we next used immunofluorescent imaging in
Luminal and Basal tumors to determine if the abundance
of ZnT2 was similar to our observations in luminal and
basal-like breast cancer cells. Indeed, we found that
ZnT2 was primarily detected in Luminal tumors and in
some cases was enhanced around the periphery (Fig. 6d),
similar to the pattern of Zn accumulation observed using
Xray fluorescence microscopy (Fig. 1). However, this
peripheral staining pattern in Luminal tumors was not
consistently observed. Moreover, minimal ZnT2 was detected
in Basal tumors, collectively reflecting the results obtained
in cultured breast cancer cells.
The loss of ZnT2 in MDA-MB-231 cells contributes to the invasive malignant phenotype
To test the hypothesis that the ability to sequester Zn in
vesicles via ZnT2 is an important driver of the molecular
phenotype, we expressed ZnT2 in MDA-MB-231 cells
and assessed the functional response (Fig. 7). We chose
this approach because ZnT2 is a vesicular transporter
important for Zn accumulation [
] and protection against
Zn cytotoxicity [
], this approach complemented our
previous report that ZnT2 attenuation in T47D cells reduces
], and ZnT2 was significantly
overexpressed in luminal cells and Luminal tumors and not
expressed in basal-like cells and Basal tumors. In the
current set of studies, we found that ZnT2 over-expression
in MDA-MB-231 cells (Fig. 7a) led to Zn vesicularization
and decreased cell viability. FluoZin-3 imaging revealed
that in MDA-MB-231 cells transfected to express ZnT2,
labile Zn accumulated in vesicles throughout the cell
(Fig. 7b). Moreover, there were significantly more vesicles
(Fig. 7c) and vesicles of a larger size (Fig. 7d) compared to
vesicles in the mock transfected cells. In addition, the
overall fluorescence intensity of vesicles per cell (Fig. 7e)
was significantly greater suggesting that ZnT2
overexpressing cells accumulated more vesicular Zn. This was
associated with a concurrent change in morphology
(Fig. 7f ) and a ~25 % reduction in cell viability (Fig. 7g).
To better understand the effects of ZnT2
overexpression on cell viability, we analyzed the effects of
ZnT2 over-expression on cell cycle and CDK2 activity.
CDK2 is a cell cycle protein that is critical for the G1/S
transition. We observed distinct shifts in cell cycle in ZnT2
over-expressing cells compared to mock-transfected cells
(Fig. 8a). Immunoblot analysis and kinase activity assays
for CDK2 revealed that Zn sequestration in ZnT2
overexpressing cells had no effect on CDK protein abundance
(Fig. 8b; top panel); however, CDK2 activity was
significantly reduced by ~80 % (Fig. 8b; bottom panel).
Shifts in cell cycle in ZnT2 over-expressing cells were also
associated with decreased cell proliferation (Fig. 8c) and
increased apoptotic cell death (Fig. 8d and e). However, most
importantly, the molecular phenotype was profoundly
affected, as invasion was significantly reduced (80 %) in
ZnT2 over-expressing MDA-MB-231 cells (Fig. 8f ).
Zn hyper-accumulates in breast tumors [
] and breast
cancer cells [
]; however, the relevance of Zn
accumulation and the relationship to the molecular
phenotype is not understood. Consistent with previous
reports, we found that not only does Zn accumulate, but
that Zn distribution and the entire Zn transporting
network was profoundly different. Importantly, our study
revealed functionally relevant subtype-specific
differences in Zn dysregulation between Luminal and Basal
breast tumors and luminal and basal-like breast cancer
cells, and provides direct evidence that the ability to
sequester Zn into a vesicular compartment underlies
the malignant phenotype.
Zn is a critical regulator of multiple cellular processes
including DNA transcription, cell signaling,
proliferation, invasion, apoptosis, and autophagy [
], thus Zn
mismanagement may underlie hallmarks such as
malignant transformation, tumorigenesis, invasion, and
metastasis. Zn accumulation within the Golgi/vesicular
compartment may be of particular functional relevance.
The Golgi/vesicular compartment contains many
apoptotic regulatory components such as Fas, Hippi protein,
tumor necrosis factor receptor-1, Bcl-2 family members,
and caspase-2 [
]. Fas is activated by Zn depletion in
hippocampal neurons [
] and conversely, Zn decreases
abundance of NFκB and Bcl-2 family members [
Zn accumulation or depletion in the Golgi/vesicular
compartment may profoundly affect cell function. In
Chandler et al. Molecular Cancer (2016) 15:2
Fig. 8 (See legend on next page.)
(See figure on previous page.)
Fig. 8 ZnT2 over-expression in MDA-MB-231 cells causes alterations in cell cycle, increased apoptosis and decreased invasion. a Cell cycle analysis
was measured using in Mock-transfected and ZnT2 over-expressing (ZnT2-OX) MDA-MB-231 cells by flow cytometry. Data represent mean % of
cells ± SEM, n = 3 samples/genotype from 3 independent experiments. Asterisk(s) indicates a significant difference from Mock transfected
controls, *p < 0.05; **p < 0.01. b Cyclin dependent kinase 2 (CDK2) kinase activity in MDA-MB-231 cells. (Top panel) Representative immunoblot of
immunoprecipitated CDK2, total CDK2 and β-actin in Mock-transfected and ZnT2-OX MDA-MB-231 cells. (Bottom panel) CDK2 kinase activity was
assessed using histone H1 as a substrate. Representative gel illustrating 32P labeling of histone H1 and corresponding relative densitometric analysis.
Data represent mean band intensity (normalized to CDK2 protein) ± SD, n = 3 samples/genotype, from 2 independent experiments. Asterisks
indicates a significant difference from Mock transfected controls, ***p < 0.001. c Cell proliferation in Mock-transfected and ZnT2-OX
MDA-MB231 cells. Data represent mean absorbance ± SEM, n = 3 samples/genotype, from 3 independent experiments. Asterisk(s) indicates a significant
difference from Mock-transfected controls, *p < 0.05; **p < 0.01. d Representative forward-by-side scatter plot depicts the population of early
apoptotic (I), apoptotic (IV), apoptotic/dead (III) and dead cells (II). e The percentage of apoptotic and dead cells was significantly higher in
ZnT2-OX cells compared to Mock-transfected cells. Data represent mean % cells ± SEM n = 3 samples/genotype from 2 independent experiments.
Asterisks indicates a significant difference from Mock-transfected controls, ***p < 0.001. f ZnT2-OX resulted in a significant reduction in invasion
(~80 %) compared with Mock-transfected controls. Data represent mean % control ± SEM n = 3 samples/genotype from 2 independent experiments.
Asterisk indicates a significant difference from Mock-transfected controls, *p < 0.05
addition, the Golgi apparatus provides a platform for
], RANK/NFκB [
] and PI3K [
signaling. The role of Zn in cell signaling is multifactorial
and complex and involves (in)activation of
phosphorylation pathways, modulation of cAMP and cGMP activity
via degradation by Zn-dependent cyclic nucleotide
phosphodiesterases, and perhaps direct binding of Zn to
TRAF6, the upstream effector of MEK and NFkB
]. Intriguingly, ZIP7, ZIP11 and ZIP13 are
reported to localize to the Golgi apparatus or intracellular
]. Moreover, ZIP7 , ZIP13 [
] have been shown to specifically activate EGFR,
TGFβ, and G-protein coupled receptor-mediated
cAMPCREB signaling, respectively. Thus the loss of ZIP7,
ZIP11, and ZIP13 expression that we noted in both T47D
and MDA-MB-231 cells suggests that aberrant expression
and/or function of these Zn transporters in particular,
may underlie defective cell signaling in malignant breast
Previous studies have found that over-expression of
21, 23, 40
], ZIP6 [
14, 15, 41
], ZIP10 [
], and ZnT2
] is associated with breast cancer. Increased MT
expression has been associated with chemoresistance
] and is correlated with increased matrix
metalloproteinase expression, a Zn-dependent enzyme important
for the degradation of extracellular matrix and thus
invasion/metastasis. ZIP6 expression is regulated by estrogen,
is upregulated in ER+ breast tumors, and has been
associated with chemotherapy resistance [
14, 15, 41
expression is associated with increased motility and
invasiveness in triple-negative breast cell lines [
], and ZnT2
is over-expressed in luminal breast cancer cells [
data now dramatically expands this current list of Zn
transporters that are dysregulated in breast cancer, as we
found that increased abundance of ZIP10 and loss of
ZIP4, ZIP7, ZIP11, and ZnT9 were universal mechanisms
associated with Zn hyper-accumulation in malignant
breast cells. Moreover, a key finding from our study was
that dysregulation in the Zn transporting network was
extensive and subtype-specific. While numerous Zn
transporters were over-expressed in luminal cells (ZIP3, ZIP5,
ZIP6, ZIP8, ZIP10, ZIP14, ZnT1, ZnT2, ZnT3, ZnT4,
ZnT5, ZnT8, and ZnT10), only a few were over-expressed
in basal-like cells (MT, ZIP10 and ZnT1). Using FluoZin-3
as a Zn reporter, we found that changes in Zn
transporters corresponded to subtype-specific alterations in
sub-cellular Zn pools. While MDA-MB-231 cells
hyperaccumulate a modest amount of Zn, the excess Zn likely
exists primarily bound to MTs to protect cells from Zn
]. In contrast, T47D cells accumulate
much greater Zn than MDA-MB-231 cells and Zn is
sequestered in the vesicular compartment, consistent with
the over-expression of the Golgi/vesicular Zn transporters
ZnT2, ZnT3, ZnT4, ZnT5, ZnT8, and ZnT10 [
While further studies using novel genetically encoded
Zn reporters [
] are required to better understand
the identity and function of these intracellular Zn
pools, these data strongly implicate differences in Zn
distribution as a defining characteristic of the
molecular subtype of breast cancer.
We previously reported that the inability to
accumulate Zn in vesicles, by attenuating ZnT2 in T47D cells,
results in cytoplasmic Zn accumulation, oxidative stress
and autophagic cell death [
]. Here, we extend those
observations and report that Zn accumulation into the
vesicular compartment by expressing ZnT2 in
MDAMB-231 cells resulted in shifts in cell cycle as a result of
decreased CDK2 kinase activity. CDK2 is required for
the G1/S phase transition in the cell cycle. The
vesicularization of Zn concomitant with decreased CDK2
activity suggests that CDK2 activity is a Zn-dependent
process. To our knowledge, this is the first report of the
Zn-dependency of CDK2. Decreased CDK2 activity
ultimately led to reduced proliferation and increased apoptosis
consistent with recent studies that have shown that CDK2
inhibition is required for apoptosis [
]. However, the
most provocative finding was that ZnT2 over-expression
and Zn vesicularization caused an 80 % reduction in
invasion. This provides further evidence that modulation
of sub-cellular Zn pools in malignant breast cells plays an
important role in the regulation of cell phenotype and
suggests that the inability to vesicularize Zn pools may
reflect and/or promote the aggressiveness of breast
cancer; however, additional studies are needed to understand
the relevance of Zn accumulation into vesicles on these
critical phenotypic hallmarks in breast cancer.
Our study also highlights the need to move beyond
the analysis of mRNA expression when interpreting
functional relationships between Zn transporters and
disease. As previously reported [
], gene and protein
expression are not always positively correlated, which
reaffirms that post-transcriptional regulatory mechanisms
including miRNA binding [
], mRNA stability and
protein cleavage [
], and protein ubiquitination [
critical determinants of Zn transporter regulation (see
Additional file 1: Table S1). Here, our data suggest
that post-transcriptional regulatory mechanisms may be
subtype-specific for ZIP1, ZIP3, ZIP10 and ZIP14, as
numerous isoforms were differentially expressed in
specific breast cancer sub-types. Moreover, our observations
regarding ZnT2 in breast cancer cells directly illustrate
this post-transcriptional regulation. In contrast to
observations in T47D cells, we found that while ZnT2 mRNA
expression in MDA-MB-231 cells was similar to that in
MCF10A cells, there was significantly less ZnT2 protein
in MDA-MB-231 cells. Similar to estrogen receptor alpha
], we found that ZnT2 was robustly degraded in the
proteome, perhaps as a feature of enhanced proteasomal
degradation machinery [
]. However, another
postulate is that ZnT2 may also be post-transcriptionally
regulated by microRNAs. In fact, 16 miRNAs are
predicted to bind to ZnT2 mRNA
(http://www.microrna.org/microrna/getMrna.do?gene = 7780&utr =
22874&organism = 9606). Of these 16 miRNAs, 2 miRNAs (miR-24
and miR-96) are associated with breast cancer
(http://mircancer.ecu.edu) and importantly, 3 miRNAs (miR-24,
miR30a and miR-149) are upregulated in MDA-MB-231 cells
]. Further studies are required to understand the
differential post-transcriptional regulation of ZnT2 in breast
Targeted profiling of breast tumors and malignant cell
lines has identified the Zn transporting network as a key
centroid of subtype-specific dysregulation. Manipulation
of the Zn transporting network and sub-cellular Zn
pools decreased malignancy in aggressive, triple-negative
breast cancer cells. These data suggest that defects in
the subcellular Zn microenvironment may play a key
role in alterations in apoptosis, oxidative stress and/or
cell signaling, which influences the behavior of
malignant breast cancer cells. This may be critical in
understanding the molecular differences in phenotype
between Luminal and Basal subtypes and potentially
elucidate novel diagnostic or therapeutic avenues.
A breast cancer cell line dataset (GSE12777, [
a breast tumor dataset (GSE5460, [
]) was used in
the analysis. The analysis was performed using the
PARTEK software [
]. The cel files were normalized
using RMA and the batch effect was corrected using
scan date and subtype as ANOVA factors within PARTEK
batch-correction implementation. Finally, each array was
scaled to the grand median to ensure accuracy of
interarray comparisons. Breast tumors were classified into
Basal, ER-High Grade (ER HG), ER-Low Grade (ER LG)
and HER [
]. Breast cancer cell lines were classified into
basal and luminal based on previously published work and
the unassigned cell lines were classified based on cluster
membership after Hierarchical clustering of the top 10 %
highly variant genes [
]. The Jetset definitions
for “best-probeset” (jetset.scores.hgu133plus 2_0.99.3.csv)
available for download at  was used to restrict the
analysis to one probe-set per gene [
analysis was performed on the SLC30A1-A10 (ZnT
proteins), SLC39A1-A14 (ZIP proteins) and the
metallothionein genes MT1E, MT1F, MT1G, MT1H and
MT2A. The latest Affymetrix annotation (June 2011)
assigns probeset 219215_s_at to SLC39A4 and 202667_s_at
to SLC39A4 and SLC39A7. However both Jetset and
] assigned probeset 202667_s_at to SLC39A7
and 219215_s_at to SLC39A4, therefore we followed the
Jetset/GeneAnnot definitions and retained both probesets
in our analysis. ANOVA was used to identify differentially
expressed genes and the FDR (step-up) corrected p-value
<0.05 was used as the cut-off criteria for selecting
significant genes. Hierarchical clustering based on Spearman
rank dissimilarity of gene expression values and complete
linkage was used to generate the heatmaps.
Human malignant luminal ER+/PR+/HER2− (T47D),
basallike ER−/PR−/HER2− (MDA-MB-231) and non-malignant
(MCF10A) breast cells were chosen to represent three
different breast cell subtypes. Cells were obtained from
the American Type Culture Collection (ATCC, Manassas,
VA). T47D cells were maintained in growth medium
containing, RPMI 1640 (SIGMA, St. Louis, MA)
supplemented with fetal bovine serum (10 %), insulin (0.2 units/
mL), sodium pyruvate (1.0 mM) and
penicillin/streptomycin (1 %). MDA-MB-231 cells were maintained in
L15 medium containing penicillin/streptomycin (1 %)
and horse serum (10 %). MCF10A cells were
maintained in 171 Medium supplemented with Mammary
Epithelial Growth Supplement (Invitrogen, Carlsbad,
CA). All culture mediums contained ~5 μM Zn as assessed
by atomic absorption spectroscopy. Cells were routinely
cultured in plastic 75 cm2 flasks and sub-cultured
every 4–5 days. Cells were maintained in a humidified
chamber in 5 % CO2 at 37 °C.
Cellular zinc concentration
Cells were cultured on 15 cm2 polycarbonate dishes in
growth medium until 90–100 % confluent. Cells were
initially rinsed with PBS, and then rinsed with PBS
plus EDTA (1 mM) to remove any loosely bound Zn.
Cells were collected by gentle scraping and pelleted by
centrifugation at 2000 g for 10 min at 4 °C. Cellular
protein concentration was determined by the Bradford
assay. Cells were resuspended in Ultrex II Nitric Acid
(0.5 mL, VWR, West Chester, PA) in mineral-free
polypropylene vials and digested at room temperature
overnight. Zn concentration was analyzed by atomic
absorption spectroscopy using an Atomic Absorption
Analyst 400 (Perkin Elmer, Waltham, MA) with
WinLab32 software. Data was normalized to total protein
content measured by the Bradford assay.
Imaging and quantification of cellular zinc pools
Labile Zn pools were characterized and visualized as
previously described [
]. Cells were seeded onto glass
coverslips and cultured overnight until 60–90 %
confluent. Cells were rinsed twice with PBS then loaded with
FluoZin-™3 AM (1 μM in DMSO containing pluronic
acid 127 to a final concentration of 0.02 %; Invitrogen,
USA) following manufacturer’s instructions in
OptiMEM for 1 h at 37 °C. Cells were briefly rinsed twice
with PBS and washed with PBS for 30 min at 25 °C with
constant shaking. Images were collected from live cells
using a FV-1000 confocal microscope (Penn State
Microscopy and Cytometry Facility). Number, size and the
fluorescence intensity of vesicles were analyzed using
Imaris® software (Connecticut, USA).
X-ray fluorescence microscopy
Discarded human tissue samples were collected under
Dana-Farber Harvard Cancer Center institutional review
board protocol #93-085. Tissue samples were
plungefrozen in ice-cold isopentane bath and processed for
microscopy as previously described [
]. Frozen, unfixed
tumors were sectioned (5 μm), mounted on
positivelycharged glass slides, dried at room temperature,
postfixed in phosphate-buffered 4 % paraformaldehyde,
washed three times with 1× PBS at 4 °C for 5 min
and stained with hematoxylin and eosin (H & E).
Briefly, sections were air dried for 4 min, stained with
0.1 % hematoxylin for 2 min and rinsed in ddH2O for
5 min. Sections were then stained with 0.5 % Eosin
times and then rinsed in distilled H2O 3 times.
Sections were then dehydrated in ethanol and rinsed in
xylenes. Regions of malignant tissue were identified.
Serial sections (20 μm) were used for X-ray
fluorescence microscopy and imaged with the scanning x-ray
microprobe at beamline 2-ID-E at the Advanced
Photon Source (Argonne, IL), quantified and processed as
previously described [
Frozen, unfixed tumors were sectioned (5 μm) with a
Microm HM 505 E cryostat (GMI, Ramsey, MN) at
−25 °C and briefly dried at room temperature onto
positively-charged slides. Sections were then post-fixed
in phosphate-buffered 4 % paraformaldehyde at room
temperature for 15 min. Following fixation, sections
were washed with 1× PBS at 4 °C for 5 min; this was
repeated 3 times. Sections were treated with 3 % H2O2
for 10 min and washed twice in 1× PBS for 5 min.
Sections were then permeabilized with 0.2 % triton
X100 in 1× PBS for 45 min at room temperature. Sections
were blocked (0.1 % heat inactivated goat serum, 1 %
BSA, 0.3 % Triton X-100 in 1× PBS) for 1 h at room
temperature in a humidified chamber. ZnT2 antibody
] was diluted in blocking buffer (4 μg/mL) and
sections were incubated overnight at 4 °C in a humidified
chamber. Sections were washed 3 times with 1× PBS for
5 min and then incubated with DAPI (175 μg/mL) for
10 min at RT, then washed three times with 1× PBS for
5 min. Tissue was mounted in ProLong® Diamond
Antifade (ThermoFisher Scientific, USA) and the coverslips
were sealed with nail polish.
Total RNA was isolated from cells using Trizol
(Invitrogen, Carlsbad, CA) according to manufacturer’s
instructions. RNA was quantified by spectrophotometry and
the integrity was assessed by examination of 28S and
18S bands in 2 % agarose gel electrophoresis. cDNA was
synthesized from 1.0 μg of total RNA using TaqMan®
reverse transcription kit (Applied Biosystems, Foster City,
CA) in 25 μl reaction mixture following manufacturer’s
instructions. The reaction mixture was incubated at
25 °C for 10 min, then at 48 °C for 30 min and heated to
95 °C for 5 min. cDNA products were stored at −20 °C
until used for semi-quantitative PCR. Semi-quantitative
PCR was performed using the DNA Engine Opticon 2
System real-time thermocycler (BioRad, Hercules, CA)
coupled with SYBR Green technology (BioRad) and
genespecific primers to human Zn transporters (SLC39A1-14
and SLC30A1-10), MT (predicted to detect MT1A,
MT1C, MT1D, MT1E, MT1F, MT1H, MT1L, MT1S,
MT1X and MT2A) and human β-actin (Primer 3 Input
v4.0). The PCR cycling parameters were as follows: 95 °C
for 10 min, and 40 cycles of 95 °C for 15 s, 60 °C for 30 s
and 72 °C for 30 s. The linearity of the dissociation curve
was analyzed by Opticon 2 System software and the mean
cycle time of the linear part of the curve was designated
Ct. Each sample was analyzed in duplicate and normalized
to β-actin using the following equation: ΔCtgene = Ctgene −
Ctβ-actin. The difference in expression between
MDA-MB231 and T47D cells was calculated using the following
equation: 2(ΔΔCt), (ΔΔCt = mean ΔCtgene in MDA-MB-231
cells − mean ΔCtgene in T47D cells. Values represent mean
fold change ± SD, relative to MDA-MB-231 cells (set to
100 %). The difference in expression between
MDA-MB231 or T47D cells and non-malignant MCF10A cells was
calculated using the following equation: 2(ΔΔCt), (ΔΔCt =
mean ΔCtgene in MCF10A cells − mean ΔCtgene in
MDAMB-231 or T47D cells. Values represent mean fold
change ± SD, relative to MCF10A cells (set to 100 %).
Total membrane proteins were isolated from cultured
cells, electrophoresed (20–100 μg/sample) and
transferred to nitrocellulose as previously described [
Additional file 1: Table S1 identifies the antibodies used
and the molecular mass of Zn transporters in various
cell lines and tissues that have been reported in the
literature. Antibodies used in this study are noted.
Membranes were blocked for 1 h in 5 % non-fat milk in
PBS/0.1 % Tween-20 (PBS-T) and washed 3 times in
PBS-T, followed by incubation with antibodies directed
against Zn transporters for 45 min then washed 3 times
in PBS-T. We were unable to identify suitable antibodies
for ZnT7, ZIP2 and ZIP9. Proteins were detected
following incubation with donkey, anti-rabbit IgG (1:30,000)
conjugated to horseradish peroxidase (Amersham
Pharmacia Biotech), visualized with Super Signal Femto
Chemiluminescent Detection System (Pierce, Rockford,
IL) and exposed to autoradiography film. Membranes
were stripped and reprobed for β-actin to control for
equal protein loading. Relative band density was
quantified using the Carestream Gel Logic 212 Pro and the ratio
of Zn transporter: β-actin was used for analysis. Samples
were run in duplicate or triplicate and immunoblots were
repeated 3–5 times. ZnT2 over-expression in transfected
cells was confirmed by incubating membranes with
antiHA antibody (0.8 μg/mL) for 1 h, detected with secondary
antibody labeled with IRDye (1:20,000) for 1 h protected
from light. ZnT2-HA was detected using the LI-COR®
Odyssey CLx System (LI-COR; Lincoln, NE).
Proteasomal and lysosomal inhibition
MDA-MB-231 cells were plated in 6-well plates at a cell
density of 5 ×105. Twenty-four h later, MDA-MB-231
cells were treated with either 30 μM of MG132
(SigmaAldrich) for 6 h or 10 μM of Chloroquine Diphosphate
salt (MP Biomedicals, LLC; Solon, OH) for 24 h. Total
membrane preps and immunoblot analysis were
executed as described above. Briefly, ZnT2 was detected
following incubation with anti-rabbit IgG (1 μg/mL)
conjugated to horseradish peroxidase and visualized with
Super Signal Femto Chemiluminescent Detection
System (Pierce, Rockford, IL) on a FluorChem System
(ProteinSimple, San Jose, CA). Nitrocellulose membranes
were stripped once and reprobed for β-actin. Relative
densitometry was quantified using the AlphaView®
Software (ProteinSimple, San Jose, California). ZnT2
densitometry was normalized to β-actin and used for analysis.
Samples were run in triplicate and immunoblots were
repeated 2–3 times.
ZnT2 over-expression in MDA-MB-231 cells utilized the
Lipofectamine® 2000 Transfection Reagent delivery system
(Thermo Scientific, Grand Island, NY). MDA-MB-231
cells were plated at a cell density of ~5 × 105 in 6-well
plates (Corning®, USA) and cultured until ~80–90 %
confluence. Cells were transfected with Lipofectamine® 2000
and plasmid containing ZnT2-HA [
] (2.5 μg) at a ratio
of 2.8:1 (transfection reagent: DNA ratio) in Opti-MEM®
(Life Technologies, USA) per manufacturer’s instructions.
Cells were transfected for 5 h, after which the transfection
medium was removed and replaced with antibiotic-free,
normal growth medium. All experiments were done
24 h post transfection. Transfection was confirmed by
immunoblotting as described above.
Proliferation was determined with the MTT Cell Growth
Determination Kit (Sigma-Aldrich, USA). MDA-MB-231
cells were transfected as described previously in a 6-well
plate. Cells were trypsinized and plated in four 96-well
plates at a cell density of 5 × 103. Cells were allowed to
grow for up to 48 h. Time 0 represents cells plated and
analyzed on the same day (~6 h after cells attach). Cells
were treated with 3-[4, 5-dimethylthiazol-2-yl]-2,
5diphenyl tetrazolium bromide (MTT) as instructed by
the manufacturer. Briefly, 10 μL of MTT was added
aseptically per well and incubated for 3 h. Medium was
removed and 100 μL of MTT solvent added. Absorbance
was read at 570 nm. Data represent mean ± SD, n = 3
samples/genotype from 3 independent experiments.
Cell cycle analysis
Cells were plated (3 × 105) in a 6-well plate and
transfected as described previously. Cells were collected 24 h
post-transfection and suspended in cold 70 % ethanol
and stored at −20 °C for 24 h. Cells were stained with
propidium iodide (BD Biosciences; San Jose, CA) and
analyzed by flow cytometry using a FACSCALIBUR (BD
Biosciences; Penn State Hershey Flow Cytometry Core
Facility). Data represent mean ± SD, n = 3
sample/genotype from 2 independent experiments.
Trypan blue exclusion
Cells that were non-adherent 24 h post-transfection
were collected, along with adherent cells and stained
with 0.4 % trypan blue solution at a 1:2 dilution. Cell
viability was determined by counting the number of blue
cells with a hemocytometer and dividing that number by
the total number of cells. Data represent mean ± SD, n =
3 samples/genotype from 3 independent experiments.
Measurement of CDK2-associated kinase activity
Immunoprecipitation of CDK2 protein containing
complexes and determination of associated kinase activity
were both determined as previously described [
protein extracts were prepared from 2 × 106
MDA-MB231 mock-transfected cells and cells over-expressing
ZnT2 using the glass-bead breakage method, followed by
immunoprecipitation of CDK2-containing protein
complexes from 200 μg of protein, with the exception of the
pre-clearing step which was performed using a 1:1000
dilution of normal rabbit IgG (Upstate).
Immunoprecipitated CDK2 complexes and CDK2 protein expression
levels in total cell lysates were determined using
immunoblot analysis. Immunoprecipitated CDK2-containing
protein complexes were subjected to a Histone H1 kinase
assay. Briefly, immunoprecipitated CDK2 complexes were
washed once in immunoprecipitation buffer and then
twice with kinase reaction buffer. Kinase reactions were
performed in a final volume of 20 μL consisting of kinase
buffer supplemented with 20 μM ATP, 10 μCi of [γ-32P]
ATP, and 1 μg of histone H1 (Roche) as substrate. Kinase
assay mixtures were incubated at 30 °C for 30 min.
Reactions were stopped with the addition of loading buffer,
and samples were boiled for 10 min. Reactions were
resolved by electrophoresis on a 10 % SDS-polyacrylamide
gel and dried, followed by autoradiograpy.
Apoptosis was determined via the Annexin V-FITC kit
(Trevigen, Gaithersburg, MD). Briefly, 3 × 105 cells were
transfected in a 6-well plate; 24 h later, cells were
trypsinized (2 min), washed and centrifuged at 300 × g for
5 min at room temperature. Cells were stained with both
Annexin V-FITC and propidium iodide for 15 min in
the dark at room temperature. Cells were washed and
processed by flow cytometry. Data represent mean ± SD,
n = 3 samples/genotype from 3 independent experiments.
Cells were transfected as previously described and 4 × 104
cells were added to 200 μL of serum- and antibiotic-free
growth medium per Boyden insert while 600 μL of
antibiotic-free growth medium, with 10 % FBS, was added
to the bottom of the well (in a 24-well plate). Cells were
incubated in a humidified chamber for 24 h at 37 °C.
Inserts were removed and submerged in PBS several times
to remove unattached cells. Non-invading cells were
removed by gently scraping with a wet cotton applicator.
Cells were fixed by submerging the inserts into 4 %
paraformaldehyde for 10 min. The insert was washed with
1× PBS and stained with hematoxylin and 3 % glacial
acetic acid for 30 min. The insert was washed gently,
several times with distilled water. Migrated cells were
visualized under light microscopy at 40× by cutting out
the porous membrane of the insert and mounting on a
slide (migrated side down). Data represent mean ± SD,
n = 3 samples/genotype from 2 independent experiments.
Gene names (SLC30A and SLC39A) and concomitant
proteins (ZnT and ZIP, respectively) are used to
differentiate between gene and protein expression. Results of
studies in cultured cells are presented as mean ± SD or
SEM where indicated. Statistical comparisons were
performed using Student’s t-test or one-way ANOVA as
indicated (Prism Graph Pad, Berkeley, CA). A significant
difference was demonstrated at p < 0.05.
Additional file 1: Table S1. Summary of the molecular mass of Zn
transporters and antibodies used for detection [
]. (DOCX 35 kb)
Ca: calcium; ER HG: estrogen receptor, high-grade; ER LG: estrogen receptor,
low grade; ER+: estrogen receptor positive; ER+/PR+/HER2+: estrogen,
progesterone, HER2 positive; ER−/PR−/HER2−: estrogen, progesterone,
HER2 negative; FDR: false discovery rate; MREs: metal responsive elements;
MT: metallothionein; PBS-T: phosphate buffered saline/tween-20;
SCL39A1-14: solute carrier family 1–14; SLC30A1-10: solute carrier family 1–10;
ZIP1-14: ZRT/IRT-like protein 1–14; Zn: zinc; ZnT1-10: zinc transporter 1–10.
The authors have no competing interests to disclose.
DIS and SLK conceived of the study, designed the experiments, and
interpreted the data; ALR provided the breast tumor samples; BK analyzed
and interpreted the microarray data; PC and SA executed the cell
experiments and analyzed the data; PC, BK and SLK wrote the manuscript
and all authors edited and approved of the manuscript.
The authors would like thank Drs. Lydia Finney and Stefan Vogt (Argonne
National Lab) for assistance with X-ray fluorescence imaging and
acknowledge the technical expertise of Drs. Veronica Lopez and Nickolas H.
McCormick as well as Thomas P Croxford, and Brian Perfilio. Financial support:
Intramural funds to SLK; Hale and Terri Brodeur Breast Cancer Foundation
fellowships to BSK; Breast Cancer Research Foundation to ALR; and Department
of Surgery Intramural Funds to DIS and SLK.
1. Millikan R , Newman B , Tse C , Moorman P , Conway K , Dressler L , et al. Epidemiology of basal-like breast cancer . Breast Cancer Res Treat . 2008 ; 109 : 123 - 39 .
2. Prat A , Perou CM . Deconstructing the molecular portraits of breast cancer . Mol Oncol . 2011 ; 5 ( 1 ): 5 - 23 .
3. Parke J , Mullins M , Cheang M , Leung S , Voduc D , Vickery T , et al. Supervised risk predictor of breast cancer based on intrinsic subtypes . J Clin Oncol . 2009 ; 27 : 1160 - 7 .
4. Ionescu J , Novotny J , Stejskal V , Lätsch A , Blaurock-Busch E , Eisenmann-Klein M . Increased levels of transition metals in breast cancer tissue . Neuro Endocrinol Lett . 2006 ; 1 : 36 - 9 .
5. Cui Y , Vogt S , Olson N , Glass AG , Rohan TE . Levels of zinc, selenium, calcium, and iron in benign breast tissue and risk of subsequent breast cancer . Cancer Epidemiol Biomarkers Prev . 2007 ; 16 ( 8 ): 1682 - 5 .
6. Santoliquido PM , Southwick HW , Olwin JH . Trace metal levels in cancer of the breast . Surg Gynecol Obstet . 1976 ; 142 ( 1 ): 65 - 70 .
7. Lee SJ , Koh JY . Roles of zinc and metallothionein-3 in oxidative stressinduced lysosomal dysfunction, cell death, and autophagy in neurons and astrocytes . Mol Brain . 2010 ; 3 ( 1 ): 30 .
8. Palmiter RD , Huang L . Efflux and compartmentalization of zinc by members of the SLC30 family of solute carriers . Pflugers Arch . 2004 ; 447 ( 5 ): 744 - 51 .
9. Eide D. The SLC39 family of metal ion transporters . Eur J Physiol . 2004 ; 447 ( 5 ): 796 - 800 .
10. Babula P , Masarik M , Adam V , Eckschlager T , Stiborova M , Trnkova L , et al. Mammalian metallothioneins: properties and functions . Metallomics . 2012 ; 4 ( 8 ): 739 - 50 .
11. Andrews G . Regulation of metallothionein gene expression by oxidative stress and metal ions . Biochem Pharmacol . 2000 ; 59 ( 1 ): 95 - 104 .
12. Lu YJ , Liu YC , Lin MC , Chen YT , Lin LY . Coordinative modulation of human zinc transporter 2 gene expression through active and suppressive regulators . J Nutri Biochem . 2014 ; 26 : 351 - 9 .
13. Kagara N , Tanaka N , Noguchi S , Hirano T. Zinc and its transporter ZIP10 are involved in invasive behavior of breast cancer cells . Cancer Sci . 2007 ; 98 ( 5 ): 692 - 7 .
14. Kasper G , Weiser AA , Rump A , Sparbier K , Dahl E , Hartmann A , et al. Expression levels of the putative zinc transporter LIV-1 are associated with a better outcome of breast cancer patients . Int J Cancer . 2005 ; 117 ( 6 ): 961 - 73 .
15. Taylor KM . A distinct role in breast cancer for two LIV-1 family zinc transporters . Biochem Soc Trans . 2008 ; 036 ( 6 ): 1247 - 51 .
16. Kelleher SL , Seo YA , Lopez V . Mammary gland zinc metabolism: regulation and dysregulation . Genes Nutr . 2009 ; 4 ( 2 ): 83 - 94 .
17. Lopez V , Kelleher SL . Zip6-attenuation promotes epithelial-to-mesenchymal transition in ductal breast tumor (T47D) cells . Exp Cell Res . 2010 ; 316 ( 3 ): 366 - 75 .
18. Lopez V , Foolad F , Kelleher SL . ZnT2-overexpression represses the cytotoxic effects of zinc hyper-accumulation in malignant metallothionein-null T47D breast tumor cells . Cancer Lett . 2011 ; 304 ( 1 ): 41 - 51 .
19. Bostanci Z , Alam S , Soybel DI , Kelleher SL . Prolactin receptor attenuation induces zinc pool redistribution through ZnT2 and decreases invasion in MDA-MB-453 breast cancer cells . Exp Cell Res . 2014 ; 321 ( 2 ): 190 - 200 .
20. Taylor KM , Vichova P , Jordan N , Hiscox S , Hendley R , Nicholson RI . ZIP7- mediated intracellular zinc transport contributes to aberrant growth factor signaling in antihormone-resistant breast cancer cells . Endocrinology . 2008 ; 149 ( 10 ): 4912 - 20 .
21. Yap X , Tan HY , Huang J , Lai Y , Yip GWC , Tan PH , et al. Over-expression of metallothionein predicts chemoresistance in breast cancer . J Pathol . 2009 ; 217 ( 4 ): 563 - 70 .
22. Surowiak P , Materna V , Maciejczyk A , Pudełko M , Markwitz E , Spaczyński M , et al. Nuclear metallothionein expression correlates with cisplatin resistance of ovarian cancer cells and poor clinical outcome . Eur J Pathol . 2007 ; 450 ( 3 ): 279 - 85 .
23. Kim HG , Kim JY , Han EH , Hwang YP , Choi JH , Park BH , et al. Metallothionein2A overexpression increases the expression of matrix metalloproteinase-9 and invasion of breast cancer cells . FEBS Lett . 2011 ; 585 ( 2 ): 421 - 8 .
24. Cima RR , Dubach JM , Wieland AM , Walsh BM , Soybel DI . Intracellular Ca2+ and Zn2+ signals during monochloramine-induced oxidative stress in isolated rat colon crypts . Am J Physiol Gastrointest Liver Physiol . 2006 ; 290 ( 2 ): G250 - 61 .
25. McCormick N , Velasquez V , Finney L , Vogt S , Kelleher SL . X-ray fluorescence microscopy reveals accumulation and secretion of discrete intracellular zinc pools in the lactating mouse mammary gland . PLoS One . 2010 ; 5 ( 6 ): e11078 .
26. Chowanadisai W , Lönnerdal B , Kelleher SL . Identification of a mutation in SLC30A2 (ZnT-2) in women with Low milk zinc concentration that results in transient neonatal zinc deficiency . J Biol Chem . 2006 ; 281 ( 51 ): 39699 - 707 .
27. Palmiter RD , Cole TB , Findley SD . ZnT-2, a mammalian protein that confers resistance to zinc by facilitating vesicular sequestration . EMBO J . 1996 ; 15 ( 8 ): 1784 .
28. Jiang Z , Hu Z , Zeng L , Lu W , Zhang H , Li T , et al. The role of the Golgi apparatus in oxidative stress: is this organelle less significant than mitochondria? Free Radic Biol Med . 2011 ; 50 ( 8 ): 907 - 17 .
29. Gao HL , Zheng W , Xin N , Chi ZH , Wang ZY , Chen J , et al. Zinc deficiency reduces neurogenesis accompanied by neuronal apoptosis through caspase-dependent and -independent signaling pathways . Neurotox Res . 2009 ; 16 ( 4 ): 416 - 25 .
30. Chang KL , Hung TC , Hsieh BS , Chen YH , Chen TF , Cheng HL . Zinc at pharmacologic concentrations affects cytokine expression and induces apoptosis of human peripheral blood mononuclear cells . Nutrition . 2006 ; 22 ( 5 ): 465 - 74 .
31. Yi P , Nguyên DT , Higa-Nishiyama A , Auguste P , Bouchecareilh M , Dominguez M , et al. MAPK scaffolding by BIT1 in the Golgi complex modulates stress resistance . J Cell Sci . 2010 ; 123 ( 7 ): 1060 - 72 .
32. Crockett JC , Mellis DJ , Shennan KIJ , Duthie A , Greenhorn J , Wilkinson DI , et al. Signal peptide mutations in RANK prevent downstream activation of NF-κB . J Bone Miner Res . 2011 ; 26 ( 8 ): 1926 - 38 .
33. Domin J , Gaidarov I , Smith M , Keen J , Waterfield M. The class II phosphoinositide 3-kinase PI3K-C2alpha is concentrated in the transGolgi network and present in clathrin-coated vesicles . J Biol Chem . 2000 ; 275 : 11943 - 50 .
34. Haase H , Rink L . Functional significance of zinc-related signaling pathways in immune cells . Annu Rev Nutr . 2009 ; 29 ( 1 ): 133 - 52 .
35. Huang L , Kirschke CP , Zhang Y , Yu YY . The ZIP7 gene (Slc39a7) encodes a zinc transporter involved in zinc homeostasis of the Golgi apparatus . J Biol Chem . 2005 ; 280 ( 15 ): 15456 - 63 .
36. Bin BH , Fukada T , Hosaka T , Yamasaki S , Ohashi W , Hojyo S , et al. Biochemical characterization of human ZIP13 protein a homo-dimerized zinc transporter involved in the spondylocheiro dysplastic ehlers-danlos syndrome . J Biol Chem . 2011 ; 286 ( 46 ): 40255 - 65 .
37. Taylor KM , Hiscox S , Nicholson RI , Hogstrand C , Kille P. Protein Kinase CK2 Triggers Cytosolic Zinc Signaling Pathways by Phosphorylation of Zinc Channel ZIP7 . Sci Signal . 2012 ; 5 ( 210 ): ra11 .
38. Fukada T , Civic N , Furuichi T , Shimoda S , Mishima K , Higashiyama H , et al. The zinc transporter SLC39A13/ZIP13 is required for connective tissue development; its involvement in BMP/TGF-beta signaling pathways . PLoS One . 2008 ; 3 : e3642 .
39. Lichten LA , Ryu MS , Guo L , Embury J , Cousins RJ . MTF-1-mediated repression of the zinc transporter Zip10 is alleviated by zinc restriction . PLoS One . 2011 ; 6 ( 6 ): e21526 .
40. Goulding H , Jasani B , Pereira H , Reid A , Galea M , Bell J , et al. Metallothionein expression in human breast cancer . Br J Cancer . 1995 ; 72 : 968 - 72 .
41. Taylor KM , Morgan HE , Smart K , Zahari NM , Pumford S , Ellis IO , et al. The emerging role of the LIV-1 subfamily of zinc transporters in breast cancer . Mol Med . 2007 ; 13 : 396 - 406 .
42. Bosomworth HJ , Thornton JK , Coneyworth LJ , Ford D , Valentine RA . Efflux function, tissue-specific expression and intracellular trafficking of the Zn transporter ZnT10 indicate roles in adult Zn homeostasis . Metallomics . 2012 ; 4 ( 8 ): 771 - 9 .
43. Fukunaka A , Suzuki T , Kurokawa Y , Yamazaki T , Fujiwara N , Ishihara K , et al. Demonstration and characterization of the heterodimerization of ZnT5 and ZnT6 in the early secretory pathway . J Biol Chem . 2009 ; 284 ( 45 ): 30798 - 806 .
44. McCormick NH , Kelleher SL . ZnT4 provides zinc to zinc-dependent proteins in the trans-Golgi network critical for cell function and Zn export in mammary epithelial cells . Am J Physiol Cell Physiol . 2012 ; 303 ( 3 ): C291 - 7 .
45. Lopez V , Kelleher SL . Zinc transporter-2 (ZnT2) variants are localized to distinct subcellular compartments and functionally transport zinc . J Biochem . 2009 ; 422 ( 1 ): 43 - 52 .
46. Park JG , Palmer AE . Quantitative measurement of Ca2+ and Zn2+ in mammalian cells using genetically encoded fluorescent biosensors . Fluorescent Protein-Based Biosensors . New York, NY: Humana Press; 2014 . p. 29 - 47 .
47. McClue SJ , Blake D , Clarke R , Cowan A , Cummings L , Fischer PM , et al. In vitro and in vivo antitumor properties of the cyclin dependent kinase inhibitor CYC202 (R‐roscovitine) . Int J Cancer . 2002 ; 102 ( 5 ): 463 - 8 .
48. Golsteyn RM . Cdk1 and Cdk2 complexes (cyclin dependent kinases) in apoptosis: a role beyond the cell cycle . Cancer Lett . 2005 ; 217 ( 2 ): 129 - 38 .
49. Galimberti F , Thompson SL , Liu X , Li H , Memoli V , Green SR , et al. Targeting the cyclin E-Cdk-2 complex represses lung cancer growth by triggering anaphase catastrophe . Clin Cancer Res . 2010 ; 16 ( 1 ): 109 - 20 .
50. Kelleher SL , Velasquez V , Croxford TP , McCormick NH , Lopez V , MacDavid J. Mapping the zinc‐transporting system in mammary cells: molecular analysis reveals a phenotype‐dependent zinc‐transporting network during lactation . J Cell Physiol . 2012 ; 227 ( 4 ): 1761 - 70 .
51. Weaver B , Andrews G . Regulation of zinc-responsive Slc39a5 (Zip5) translation is mediated by conserved elements in the 3′-untranslated region . Biometals . 2012 ; 25 ( 2 ): 319 - 35 .
52. Weaver B , Dufner-Beattie J , Kambe T , Andrews G . Novel zinc-responsive post-transcriptional mechanisms reciprocally regulate expression of the mouse Slc39a4 and Slc39a5 zinc transporters (Zip4 and Zip5) . Biol Chem . 2007 ; 388 : 1301 - 12 .
53. Mao X , Kim BE , Wang F , Eide DJ , Petris MJ . A histidine-rich cluster mediates the ubiquitination and degradation of the human zinc transporter, hZIP4, and protects against zinc cytotoxicity . J Biol Chem . 2007 ; 282 ( 10 ): 6992 - 7000 .
54. Chai F , Liang Y , Bi J , Chen L , Zhang F , Cui Y , et al. REGγ regulates ERα degradation via ubiquitin-proteasome pathway in breast cancer . Biochem Biophys Res Commun . 2015 ; 456 ( 1 ): 534 - 40 .
55. Tian M , Xiaoyi W , Xiaotao L , Guosheng R . Proteasomes reactivator REG gamma enchances oncogenicity of MDA-MB-231 cell line via promoting cell proliferation and inhibiting apoptosis . Cell Mol Biol . 2008 ; 55 : 1121 - 31 .
56. Riaz M , Jaarsveld M , Hollestelle A , Prager-Van Der Smissen W , Heine A , Boersma A , et al. miRNA expression profiling of 51 human breast cancer cell lines reveals subtype and driver mutation-specific miRNAs . Breast Cancer Res . 2013 ; 15 ( 2 ): R33 .
57. Kruger S , Elmageed ZY , Hawke DH , Wörner PM , Jansen DA , Abdel-Mageed AB . Molecular characterization of exosome-like vesicles from breast cancer cells . BMC Cancer . 2014 ; 14 ( 1 ): 44 .
58. Hoeflich KP , O'Brien C , Boyd Z , Cavet G , Guerrero S , Jung K. In vivo antitumor activity of MEK and phosphatidylinositol 3-kinase inhibitors in basal-like breast cancer models . Clin Cancer Res . 2009 ; 15 ( 14 ): 4649 - 64 .
59. Lu X , Wang Z , Iglehart J , Zhang X , Richardson A . Predicting features of breast cancer with gene expression patterns . Breast Cancer Res Treat . 2008 ; 108 ( 2 ): 191 - 201 .
60. Partek . www. partek.com. Accessed 18 Feb 2010 .
61. Liou GY , Storz P . Reactive oxygen species in cancer . Free Radic Res . 2010 ; 44 ( 5 ): 479 - 96 .
62. Kao J , Salari K , Bocanegra M , Choi YL , Girard L , Gandhi J , et al. Molecular profiling of breast cancer cell lines defines relevant tumor models and provides a resource for cancer gene discovery . PLoS One . 2009 ; 4 ( 7 ): e6146 .
63. Neve RM , Chin K , Fridlyand J , Yeh J , Baehner FL , Fevr T , et al. A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes . Cancer Cell . 2006 ; 10 ( 6 ): 515 - 27 .
64. Qiyuan Li , Balazs G , Zoltan S , Eklund AC . Jetset: selecting an optimal microarray probe set to represent a gene . Available from: http://www.cbs. dtu.dk/biotools/jetset/. Accessed 18 Feb 2010 .
65. Ferrari F , Bortoluzzi S , Coppe A , Sirota A , Safran M , Shmoish M , et al. Novel definition files for human GeneChips based on GeneAnnot . BMC Bioinformatics . 2007 ; 8 : 446 .
66. Kelleher SL , Lönnerdal B . Zn transporter levels and localization change throughout lactation in rat mammary gland and are regulated by Zn in mammary cells . J Nutr . 2003 ; 133 ( 11 ): 3378 - 85 .
67. Alam S , Sen E , Brashear H , Meyers C . Adeno-associated virus type 2 increases proteosome-dependent degradation of p21WAF1 in a human papillomavirus type 31b-positive cervical carcinoma line . J Virol . 2006 ; 80 ( 10 ): 4927 - 39 .
68. Costello L , Franklin R , Zou J , Feng P , Bok R , Swanson M , et al. Human prostate cancer ZIP1/zinc/citrate genetic/metabolic relationship in the TRAMP prostate cancer animal model . Cancer Biol Ther . 2011 ; 12 : 1078 - 84 .
69. My MJ , Philipps A , Kelleher S , Lönnerdal B. Effects of zinc exposure on zinc transporter expression in human intestinal cells of varying maturity . J Pediatr Gastroenterol Nutr . 2010 ; 50 : 587 - 95 .
70. Dufner-Beattie J , Kuo YM , Gitschier J , Andrews GK . The adaptive response to dietary zinc in mice involves the differential cellular localization and zinc regulation of the zinc transporters ZIP4 and ZIP5 . J Biol Chem . 2004 ; 279 ( 47 ): 49082 - 90 .
71. Weaver B , Zhang Y , Hiscox S , Guo G , Apte U , Taylor K , et al. Zip4 (Slc39a4) expression is activated in hepatocellular carcinomas and functions to repress apoptosis, enhance cell cycle and increase migration . PLoS One . 2010 ; 5 : e13158 .
72. Shen H , Qin H , Guo J . Concordant correlation of LIV-1 and E-cadherin expression in human breast cancer cell MCF-7 . Mol Biol Rep . 2009 ; 36 ( 4 ): 653 - 9 .
73. Croxford TP , McCormick NH , Kelleher SL . Moderate zinc deficiency reduces testicular Zip6 and Zip10 abundance and impairs spermatogenesis in mice . J Nutr . 2011 ; 141 ( 3 ): 359 - 65 .
74. Besecker , Bao S , Bohacova B , Papp A , Sadee W , Knoell DL . The human zinc transporter SLC39A8 (Zip8) is critical in zinc-mediated cytoprotection in lung epithelia . Am J Physiol Lung Cell Mol Physiol . 2008 ; 294 ( 6 ): L1127 - 36 .
75. Ryu MS , Lichten LA , Liuzzi JP , Cousins RJ . Zinc transporters ZnT1 (Slc30a1), Zip8 (Slc39a8), and Zip10 (Slc39a10) in mouse red blood cells Are differentially regulated during erythroid development and by dietary zinc deficiency . J Nutr . 2008 ; 138 ( 11 ): 2076 - 83 .
76. Aydemir TB , Liuzzi JP , McClellan S , Cousins RJ . Zinc transporter ZIP8 (SLC39A8) and zinc influence IFN-γ expression in activated human T cells . J Leukoc Biol . 2009 ; 86 ( 2 ): 337 - 48 .
77. Liuzzi JP , Lichten LA , Rivera S , Blanchard RK , Aydemir TB , Knutson MD , et al. Interleukin-6 regulates the zinc transporter Zip14 in liver and contributes to the hypozincemia of the acute-phase response . Proc Natl Acad Sci U S A . 2005 ; 102 ( 19 ): 6843 - 8 .
78. Gao J , Zhao N , Knutson MD , Enns CA . The hereditary hemochromatosis protein, HFE, inhibits iron uptake via down-regulation of Zip14 in HepG2 cells . J Biol Chem . 2008 ; 283 ( 31 ): 21462 - 8 .
79. Yu YY , Kirschke CP , Huang L . Immunohistochemical analysis of ZnT1, 4, 5, 6, and 7 in the mouse gastrointestinal tract . J Histochem Cytochem . 2007 ; 55 ( 3 ): 223 - 34 .
80. Guo L , Lichten LA , Ryu MS , Liuzzi JP , Wang F , Cousins RJ . STAT5- glucocorticoid receptor interaction and MTF-1 regulate the expression of ZnT2 (Slc30a2) in pancreatic acinar cells . Proc Natl Acad Sci . 2010 ; 107 ( 7 ): 2818 - 23 .
81. Palmiter RD , Cole TB , Quaife CJ , Findley SD . ZnT-3, a putative transporter of zinc into synaptic vesicles . Proc Natl Acad Sci . 1996 ; 93 ( 25 ): 14934 - 9 .
82. Murgia C , Vespignani I , Cerase J , Nobili F , Perozzi G . Cloning, expression, and vesicular localization of zinc transporter Dri 27/ZnT4 in intestinal tissue and cells . Am J Physiol . 1999 ; 277 ( 6 ): G1231 - 9 .
83. Michalczyk AA , Allen J , Blomeley RC , Ackland ML . Constitutive expression of hZnT4 zinc transporter in human breast epithelial cells . J Biochem . 2002 ; 364 ( 1 ): 105 - 13 .
84. Kambe T , Narita H , Yamaguchi-Iwai Y , Hirose J , Amano T , Sugiura N. Cloning and characterization of a novel mammalian zinc transporter, zinc transporter 5, abundantly expressed in pancreatic β cells . J Biol Chem . 2002 ; 277 ( 21 ): 19049 - 55 .
85. Kumar L , Michalczyk A , McKay J , Ford D , Kambe T , Hudek L , et al. Altered expression of two zinc transporters, SLC30A5 and SLC30A6, underlies a mammary gland disorder of reduced zinc secretion into milk . Genes Nutr . 2015 ; 10 ( 5 ): 1 - 16 .
86. Huang L , Kirschke CP , Gitschier J . Functional characterization of a novel mammalian zinc transporter, ZnT6 . J Biol Chem . 2002 ; 277 ( 29 ): 26389 - 95 .
87. Chimienti F , Devergnas S , Favier A , Seve M . Identification and cloning of a β-cell-specific zinc transporter, ZnT-8, localized into insulin secretory granules . Diabetes . 2004 ; 53 ( 9 ): 2330 - 7 .