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Published OnlineFirst November 8, 2012; DOI: 10.1158/0008-5472.CAN-12-1098
Cancer
Research
Molecular and Cellular Pathobiology
An Integrated Genomic Screen Identifies LDHB as an
Essential Gene for Triple-Negative Breast Cancer
Mark L. McCleland1, Adam S. Adler1, Yonglei Shang1, Thomas Hunsaker2, Tom Truong2, David Peterson3,
Eric Torres4, Li Li5, Benjamin Haley6, Jean-Philippe Stephan6, Marcia Belvin2, Georgia Hatzivassiliou2,
Elizabeth M. Blackwood2, Laura Corson2, Marie Evangelista3, Jiping Zha1, and Ron Firestein1
Abstract
Breast cancer has been redefined into three clinically relevant subclasses: (i) estrogen/progesterone receptor
positive (ERþ/PRþ), (ii) HER2/ERRB2 positive, and (iii) those lacking expression of all three markers (triple
negative or basal-like). While targeted therapies for ERþ/PRþ and HER2þ tumors have revolutionized patient
treatment and increased lifespan, an urgent need exists for identifying novel targets for triple-negative breast
cancers. Here, we used integrative genomic analysis to identify candidate oncogenes in triple-negative breast
tumors and assess their function through loss of function screening. Using this approach, we identify lactate
dehydrogenase B (LDHB), a component of glycolytic metabolism, as an essential gene in triple-negative breast
cancer. Loss of LDHB abrogated cell proliferation in vitro and arrested tumor growth in fully formed tumors in
vivo. We find that LDHB and other related glycolysis genes are specifically upregulated in basal-like/triplenegative breast cancers as compared with other subtypes, suggesting that these tumors are distinctly glycolytic.
Consistent with this, triple-negative breast cancer cell lines were more dependent on glycolysis for growth than
luminal cell lines. Finally, we find that patients with breast cancer and high LDHB expression in their tumors had a
poor clinical outcome. While previous studies have focused on the ubiquitous role of LDHA in tumor metabolism
and growth, our data reveal that LDHB is upregulated and required only in certain cancer genotypes. These
findings suggest that targeting LDHB or other components of lactate metabolism would be of clinical benefit in
triple-negative breast cancer. Cancer Res; 72(22); 5812–23. 2012 AACR.
Introduction
In the past decade, molecular profiling has redefined breast
cancer as a heterogeneous group of diseases. Gene expression
microarray analyses have identified at least 5 different breast
cancer subtypes: luminal A, luminal B, HER2þ (or ERBB2þ),
basal-like (or triple negative), and claudin-low (1–4). The
molecular distinction between these subtypes is defined by
a tissue-specific gene signature and by the status of estrogen
receptor (ER), progesterone receptor (PR), and ERBB2 (or
HER2). In the clinic, these molecular subgroups translate into
3 major categories of breast cancer: (i) those that express ER or
PR and are termed hormone receptor positive–dependent
(HRþ), (ii) those with ERBB2/HER2 amplification (HER2þ),
and (iii) those that lack expression of all 3 markers and are
referred to as triple negative. Each of these breast cancer
Authors' Affiliations: Departments of 1Pathology, 2Translational Oncology, 3Molecular Diagnostics & Cancer Cell Biology, 4Biochemical and
Cellular Pharmacology, 5Bioinformatics & Computational Biology, and
6
Protein Chemistry, Genentech, Inc., South San Francisco, California
Note: Supplementary data for this article are available at Cancer Research
Online (http://cancerres.aacrjournals.org/).
Corresponding Author: Ron Firestein, Genentech, Inc., 1 DNA Way, South
San Francisco, CA 94080. Phone: 650-225-8441; Fax: 650-467-2625; Email: [email protected]
doi: 10.1158/0008-5472.CAN-12-1098
2012 American Association for Cancer Research.
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subgroups has distinct clinicopathologic features and prognostic implications (5).
The molecular classification of these breast tumors is of
profound predictive value in determining patient response to
targeted therapies. For example, patients with HER2þ breast
tumors are frequently treated with Herceptin (trastuzumab), a
monoclonal antibody that blocks the growth promoting effects
of the amplified HER2 kinase (6). Likewise, HRþ tumors
respond to antiestrogen therapy (7). As neither hormone
receptors nor the HER2 oncogene is expressed in triple-negative breast cancer, a rational therapy for these tumors remains
elusive. This is underscored by the poor patient outcomes seen
in the triple-negative breast cancer population (8).
The goal of this study was to identify new therapeutic targets
for triple-negative breast cancers. Starting with an RNA interference (RNAi) screen conducted on both triple-negative and
luminal breast cancer cell lines, we identified the lactate
dehydrogenase B isoform (LDHB) as an essential gene of
triple-negative breast cancer. LDHB is overexpressed in triple-negative breast tumors as compared with normal and
luminal breast tumors, and importantly, this overexpression
correlates with a poor clinical outcome. Knockdown of LDHB
selectively reduced proliferation of triple-negative breast cancers both in vitro and in established tumors in vivo. Interestingly, we find that triple-negative breast cancers have a strong
predilection for the glycolytic pathway as an energy source. Our
work identifies LDHB as an important mediator of triple-
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LDHB Is a Regulator of Triple-Negative Breast Cancer
negative tumor growth and more broadly reveals that triplenegative breast cancers have unique metabolic profiles that
may be exploited for therapeutic intervention.
Materials and Methods
Cell lines
All breast cancer cells were grown in RPMI, 10% FBS, 2
mmol/L L-glutamine (Invitrogen), and 1% penicillin–streptomycin (Invitrogen). 293T human embryonic kidney packaging
cells were grown in Dulbecco's Modified Eagle's Medium (high
glucose), 10% FBS, 100 mmol/L nonessential amino acids
(Invitrogen), and 1% penicillin–streptomycin.
Antibodies
The following antibodies were used for immunoblot analysis: actin (MP Biomedicals; 69100), LDHA (Santa Cruz Biotechnology; sc-133123), LDHB (Epitomics; 2090-1), MCT1 (Sigma; HPA003324), MCT4 (Santa Cruz Biotechnology; sc-50329),
tubulin (Sigma; T6074), and horseradish peroxidase–conjugated anti-mouse and anti-rabbit secondary antibodies (Jackson
ImmunoResearch).
Compilation of genes for RNAi screen
To identify genes that are specifically required in triplenegative versus luminal breast cancers, a targeted siRNA
library was assembled on the basis of 3 main criteria (mRNA
overexpression, genes residing in genomic amplicons, and
literature supported). Public microarray datasets were
retrieved from Oncomine (9–11) and were used to identify
genes overexpressed in triple-negative breast tumors as compared with luminal tumors. Genes were filtered and selected if
the Q value was less than 0.1, and at least more than 2-fold
change was observed over luminal tumors. Genes located in
copy number gain regions (defined by GISTIC analysis with Q
value less than 0.1) were identified using in-house array
comparative genomic hybridization (CGH) datasets from triple-negative breast tumors and from 2 published array CGH
datasets (12, 13). In addition, correlation analysis between
expression and copy number gain was conducted in a panel
of 3 triple-negative and 4 luminal breast cancer cell lines. After
cross-referencing the tumor gene set with the cell line analysis,
a total of 39 genes were selected on the basis of overexpression,
and 30 genes were selected on the basis of gene copy number
gain in triple-negative versus luminal breast cancer. Finally, 10
genes were selected on the basis of published data, which
implicate Notch and Wnt-b–catenin signaling pathways in
triple-negative breast cancer (14).
siRNA screen and data analysis
Appropriate cell number and transfection conditions were
optimized for each cell line (Supplementary Table S1). Briefly,
cell number for plating was determined by quantifying cell
growth on an IncuCyte (Essen BioScience) so that the cell
density was approximately 80% 4 days after plating (duration of
screen). Transfection conditions were optimized using 5 different lipid transfection reagents (Dharmafect 1–4 and Lipofectamine RNAiMAX) and appropriate positive and negative
siRNAs (siNTC, Tox, siPLK1, and siCDK1). For the screen, cells
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were reverse transfected in 96-well plates in triplicate using the
Dharmacon siGENOME SMARTpool library (4 siRNAs/gene) at
a final concentration of 100 nmol/L and the appropriate lipid.
Cells were incubated for 4 days before 5-ethynyl-20 -deoxyuridine (EdU) labeling. As internal positive controls for the
screen, Tox (to ensure transfection efficiency) and siCDK1
were included. CDK1 is a key cell-cycle regulator and upon
knockdown significantly reduces the S-phase index (15).
EdU labeling was carried out according to the manufacturer's instructions with minor modification (Invitrogen).
Briefly, cells were incubated for 30 minutes with EdU before
fixation and permeabilization. Nuclei were labeled with
Hoechst 33342. Cell number and EdU-positive cells were
quantified using an ImageXpress system (Molecular Devices).
One image per well was collected for a total of 3 images per
gene per cell line. For each gene, an EdU-positive percentage
was calculated by dividing the EdU-positive nuclei by the total
number of nuclei.
Data were normalized on each plate by dividing the percentage EdU-positive nuclei by the average of 2 nontargeting
controls. Normalized values from each plate were then averaged and Z-scores were calculated using the following formula:
(gene value plate average)/plate SD (Supplementary Table
S2). Z-scores from the basal and luminal lines were independently averaged. To reduce the Z-score to a single, comparable
value, the luminal Z-score was subtracted from the basal Zscore. Conducting a t test between the 2 groups identified
statistically significant hits. Genes with a Z-score less than 0.9
and a P value more than 0.05 were considered hits.
Cell proliferation assays
Validation of LDHB knockdown with individual siRNA
oligos was conducted in 96-well format. Briefly, cells were
reverse transfected with a single siGENOME oligo at a final
concentration of 25 nmol/L using 0.11 mL of Dharmafect 4
(Dharmacon) per well. For LDHB, 2 independent siRNAs from
the siGenome pool were used for subsequent analysis (Dharmacon D-009779-01 and D-009779-02). Cells were plated at
2,750 cells per well and incubated for 6 days. Cell proliferation
was measured at the end of study using CellTiter-Glo (Promega) according to manufacturer instructions.
For 2-deoxyglucose (2DG) studies, cells were seeded in 45 mL
at 3.4 104 cells per mL (in a 384-well plate) in RPMI containing 5% FBS, 6 mmol/L glucose, 2 mmol/L glutamine, and 1
antibiotic. 2DG was added 12 hours after plating at a final
concentration of either 5 mmol/L or 20 mmol/L (2DG was
prepared as a 10 stock). Cell growth was quantified 5 days
later with Cyquant Direct (Invitrogen). Relative cell growth was
calculated by averaging normalized values from the 2 drug
concentrations.
Construction of stable cell lines with inducible
knockdown
For the inducible knockdown experiments, the lentivirus
pHush–shRNA system was used (16). Two independent short
hairpin RNA (shRNA) sequences were constructed for LDHB
(shLDHB-1 target sequence: GGATATACCAACTGGGCTA and
shLDHB-2 target sequence: GTACAGTCCTGATTGCATC).
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McCleland et al.
MCT1 shRNA target sequence was GCAGTATCCTGGTGAATAA and the MCT4 shRNA target sequence was CCGCAAGGTTACAAGGCAT. Sequences were first cloned into the pSHUTTLE-H1 vector and then the pSHUTTLE-H1–shRNA was Gateway (Invitrogen) recombined into a puromycin-selectable
pHush vector (16). The pHush–shNTC control was obtained
from David Davis (Genentech).
To make lentiviral particles, the pHUSH–shRNA construct
was transfected into 293T cells along with pCMV–VSVG and
pCMV-dR8.9 plasmids. Viral particles were added to cells with
8 mg/mL polybrene and spin infected at room temperature
(1,800 rpm, 30–45 minutes). Stable integration of shRNAs was
selected with 2 mg/mL puromycin 48 hours after infection.
Xenograft tumor models
For each cell line, 5 106 cells were injected subcutaneously
into the flank of 26 female NCr nude mice (Taconic) to initiate
tumor growth. Tumor size was monitored using a calliper.
Once tumors reached 200 mm3 in size, the animals from each
cell line were split into 2 groups. One group was given 5%
sucrose in their water (control group) and the other group was
given 5% sucrose þ 1 mg/mL doxycycline (Clontech) in their
water to induce hairpin expression. Eleven days after mice were
started on doxycycline, 3 mice from each group were euthanized and the tumors were harvested to examine LDHB
knockdown. The remaining 10 mice in each group were
monitored for tumor growth for the remainder of the study
(39 days). Mouse weight was measured at each time point to
monitor weight changes throughout the study.
Microarray data analysis
The mRNA expression dataset to examine LDHB and related
lactate pathway genes in different breast tumor subtypes was
downloaded from Gene Expression Omnibus, accession
GSE18229 (3). Mean-centered log2 expression values of LDHB
were sorted from high to low for each tumor subtype. Pearson
correlation was calculated between LDHB and MCT1, MCT2,
MCT3, and MCT4. This is essentially a score for the expression
level of lactate-pathway genes in each tumor as compared with
LDHB expression, in which a high correlation value indicates
that a gene is coupregulated when LDHB is overexpressed.
Pearson values were calculated specifically in basal-like
tumors, in which LDHB is significantly upregulated, and across
all tumor subtypes. Survival curves were calculated by the
Kaplan–Meier method. High and low LDHB and LDHA expression was defined by values above or below the mean expression
of all tumors, respectively (the log2 mean was set to 0).
Immunohistochemistry
Immunohistochemistry (IHC) was conducted on 4 mm thick
formalin-fixed paraffin embedded tissue sections mounted on
glass slides. All IHC steps were carried out on the Ventana
Discovery XT autostainer (Ventana Medical Systems).
Pretreatment was done with Cell Conditioner 1 with the
standard time. Primary antibodies were used at the following
concentrations: MCT1 (Santa Cruz Biotechnology; sc-365501)
at 1 mg/mL, MCT4 (Santa Cruz Biotechnology; sc-50329) at
0.1 mg/mL, LDHA (Cell Signaling Technologies; 3582) at
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0.081 mg/mL, and LDHB (Epitomics; 2090-1) at 0.04 mg/mL.
Slides were incubated with primary antibody for 60 minutes at
37 C. Ventana Mouse or Rabbit OmniMap was used as the
detection system. Ventana 3,30 -diaminobenzidine (DAB) and
Hematoxylin II were used for chromogenic detection and
counterstain.
Results
LDHB is overexpressed in triple-negative breast cancer
and essential for tumor growth
We conducted a loss of function RNAi screen to identify
genes that are selectively required for cell proliferation in
triple-negative breast cancer. Target genes for the screen were
selected on the basis of their genomic amplification status or
noncopy number dependent overexpression in triple-negative
as compared with luminal tumors. An additional set of genes,
representing key cancer-signaling pathways implicated in
triple-negative breast cancer growth, were also included (Fig.
1A). On the basis of this analysis, 79 genes in total were
screened across 8 triple-negative and 3 luminal cell lines and
cell proliferation was quantified using an EdU incorporation
assay 4 days posttransfection. By comparing the average Zscore of triple-negative and luminal cell lines, genes with a
differential cell proliferation effect between triple-negative and
luminal breast cancer cell lines were identified (Fig. 1B and
Supplementary Table S2). Of the 4 genes that met our significance criteria of scoring at a DZ-score (Z-score triple negative–Z-score luminal) of 0.9 or below, we found that only 1,
LDHB, was specifically required for proliferation of triplenegative breast cancers (Fig. 1C–E and Supplementary Fig.
S1). LDHB is a member of the LDH family of enzymes and
functions as a metabolic regulator (Fig. 1F) to interconvert
pyruvate and lactate (17, 18).
To validate LDHB as a regulator of triple-negative breast
cancer, a panel of triple-negative breast cell lines were transfected with 2 independent LDHB siRNAs. Both LDHB siRNAs
exhibited robust knockdown of LDHB protein and significantly
reduced cell proliferation on average 3- to 4-fold in a 6-day
assay (Fig. 2A). To determine the genotype–phenotype relationship between LDHB and its knockdown effect, LDHB
expression was analyzed in basal-like/triple-negative and luminal cell lines and tumors. Gene expression and immunoblot
analysis of both LDH isoforms showed that while LDHA
expression is ubiquitous, LDHB is specifically upregulated in
basal-like/triple-negative breast cancer cell lines and tumors as
compared with luminal cancers (Fig. 2B–D). Even within the
triple-negative breast cancer subset, the variability of LDHB
expression correlated well with its knockdown phenotype, as 5
of the highest expressing triple-negative cell lines (BT549,
CAL51, CAL120, MDA-MB-231, and MDA-MB-436) showed the
strongest LDHB knockdown effect on proliferation (Fig. 1E).
These effects are specific to LDHB isoform inhibition, as LDHA
levels did not change upon LDHB knockdown (Supplementary
Fig. S3). These results show that triple-negative breast cancer
cell lines express elevated LDHB levels and are highly dependent on its expression for proliferation.
To extend our in vitro observations, the effect of acute loss of
LDHB on xenograft tumor growth and maintenance was
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Published OnlineFirst November 8, 2012; DOI: 10.1158/0008-5472.CAN-12-1098
LDHB Is a Regulator of Triple-Negative Breast Cancer
Figure 1. RNAi screening strategy to identify regulators of basal-like breast cancer. A, schematic highlighting the criteria for gene selection and experimental
setup of the RNAi screen. B, distribution curve showing the average Z-score of triple negative minus the average Z-score of luminal cell lines (DZ-score) for all
the genes included in the RNAi screen. A negative value indicates that the siRNA decreased EdU incorporation more so in the triple-negative cell lines.
The dashed line indicates the Z-score cutoff for genes that preferentially affected triple-negative cell lines (<0.9). As an additional threshold, a gene also had
to pass a t test (P < 0.05) comparing triple negative and luminal Z-scores. C, representative images from the primary RNAi screen of a triple-negative
(CAL120) and luminal (MCF-7) cell line. Nuclear staining with Hoechst 33342 and EdU incorporation after knockdown with siNTC (nontargeting control),
siCDK1 (positive control), and siLDHB are shown. D, average triple-negative and luminal Z-scores for all cell lines for LDHB. P value indicates a statistically
significant difference in EdU incorporation between triple-negative and luminal lines. Error bars represent SD. E, normalized Z-scores for LDHB siRNA
across cell lines in the RNAi screen. Corresponding immunoblot of LDHB levels are shown for each cell line: BT549 (1), CAL51 (2), CAL120 (3), HCC1395 (4),
HCC38 (5), MDA-MB-231.x1 (6), MDA-MB-436 (7), SW982 (8), KPL1 (9), MCF7 (10), and T47D (11). F, schematic of LDH function in glycolysis.
investigated. A doxycycline-inducible shRNA lentiviral system
was used to introduce 2 independent shRNAs to LDHB
(shLDHB) or a nontargeting control (shNTC) into a human
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triple-negative breast cancer cell line (MDA-MB-231). Resulting
cell lines were injected into the flanks of mice. Once tumors were
established (measuring 200 mm3), a subset of mice in each
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Figure 2. LDHB is upregulated in
triple-negative breast cancer and
critical for cell proliferation. A,
effect of LDHB knockdown on the
proliferation of triple-negative
breast cancer cells. Bar graph
depicts cell proliferation (measured
by CellTiter-Glo) after 6 days of
growth in 4 triple-negative cell lines
following LDHB knockdown using
2 independent LDHB siRNAs. Data
represent the average of 3
independent experiments (each
experiment was carried out in
triplicate) and was normalized to
the siNTC before averaging. A
paired t test identified statistically
significant differences in cell
growth ( , P < 0.05 and
, P < 0.005). Error bars represent
SD. Immunoblot analysis showing
LDHB knockdown after siRNA
treatment and 4 days of growth is
displayed for each cell line. b-Actin
was used as a loading control. B
and C, microarray analysis of LDHB
gene expression in breast cancer
cell lines (from in-house data) and
primary breast tumors (3). P values
indicate significant expression of
LDHB in basal-like/triple-negative
6
cell lines (P ¼ 10 ) and tumors
(P ¼ 1026) compared with luminal
ones. D, immunoblot showing
LDHB and LDHA protein
expression in triple-negative and
luminal breast cell lines. b-Actin
was used as a loading control.
cohort was administered doxycycline to initiate LDHB knockdown. LDHB knockdown in fully formed tumors led to profound
tumor growth inhibition (tumor growth inhibition for shLDHB-1
¼ 75% and shLDHB-2 ¼ 66%), when compared with the shNTC
control (P < 1010 for both hairpins) or the nondoxycyclineinduced shLDHB tumors (P < 108 for both hairpins; Fig. 3A and
Supplementary Fig. S2). Acute and sustained LDHB knockdown
in the tumors was confirmed by immunoblot at day 11 and day
39 after doxycycline treatment, respectively (Fig. 3B). No significant weight changes were observed in the mice throughout the
study for any of the treatment groups (Supplementary Fig. S2).
These observations indicate that LDHB is required for triplenegative breast tumor growth in vivo.
Basal-like/triple-negative tumors and cell lines show
glycolytic dependence
It has been known for over half a century that tumor cells
display an altered cellular metabolism (19, 20). Instead of using
pyruvate oxidation in the mitochondria as their primary means
of generating energy, many tumor cells rely exclusively on a
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high rate of glycolysis for ATP production (18). We hypothesized that upregulation of LDHB in triple-negative breast
cancer may reflect a more global shift in cellular metabolism.
To examine whether the breast cancer subtypes differ in their
glycolytic dependence, we analyzed and compared the expression of defined metabolic gene signatures across breast cancer
subtypes using a breast cancer microarray dataset [gene
signatures adapted from the Broad Institute Molecular Signatures Database (MSigDB) gene sets for Glucose_Metabolic_Process, (21), and shown in Supplementary Table S3]. Strikingly, basal-like, claudin-low, which are representative of triple-negative breast cancer (3, 22), and HER2þ breast tumors
exhibit an elevated glycolytic gene signature and concomitant
lower oxidative phosphorylation signature compared with
luminal tumors (Fig. 4A and B). These results imply that
triple-negative breast cancers have altered their transcriptional profiles to accommodate a dependence on glycolysis.
To functionally test these changes in gene expression, we
profiled the glycolytic dependence of a panel of 23 triple
negative and 6 luminal cell lines by examining their sensitivity
Cancer Research
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LDHB Is a Regulator of Triple-Negative Breast Cancer
Figure 3. LDHB is required for tumor growth in vivo. A, tumor volumes from
indicated xenografted MDA-MB-231 cell lines were measured over time.
Mice were administered doxycycline once tumors were established
3
(measuring 200 mm ). Graph represents data from 1 experiment in which
each treatment group contained 10 mice. Tumor growth inhibition values
were determined by area under the curve calculation (shLDHB-1
TGI ¼ 75%; shLDHB-2 TGI ¼ 66%). Error bars represent SEM. B,
immunoblot analysis of LDHB protein levels in shLDHB xenograft tumors
at day 11 and day 39 postdoxycycline administration.
to 2DG. 2DG is a glucose molecule in which the 2-hydroxyl
group is replaced by hydrogen and functions inside the cell to
inhibit hexokinase activity and block glycolysis. Cells were
grown in the presence of increasing concentrations of 2DG
and cell proliferation was quantified after 5 days of growth.
2DG retarded cell growth on an average 2-fold more in triple
negative as compared with luminal cell lines (P ¼ 0.004; Fig.
4C). Together, these data reveal that triple-negative breast
cancers have an altered metabolic gene profile and are distinctly reliant on glycolysis for their metabolic demand.
To gain insight into the genetic interplay between LDHB and
other glycolysis genes in triple-negative breast cancer, we
examined whether specific genes from the glycolytic signature
correlated with LDHB expression. Eighteen genes were found
to positively correlate with LDHB expression, the most significant being the lactate transporter MCT1 (Supplementary Fig.
S4). The monocarboxylate transporter (MCT) family includes
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14 genes, 4 of which (MCT1-4) are involved in lactate transport
(23–25). Therefore, we examined the expression profile of
LDHB, MCT1, and other lactate pathway genes (LDHA, MCT2,
MCT3, and MCT4) across the different breast tumor subtypes
to determine if specific pathway components might cofunction
(Fig. 4D and Supplementary Fig. S5). MCT1 expression significantly correlated to LDHB expression in both basal-like and
claudin-low tumors. In contrast, the other MCT proteins
showed either no correlation (MCT2 and MCT3) or a negative
correlation (MCT4) to LDHB in basal-like tumors. Interestingly, while MCT4 and LDHA are upregulated in response to
hypoxia (18, 25), both MCT1 and LDHB are expressed in
normoxic regions of breast cancer (data not shown), suggesting that different isoforms of LDH and MCTs function together
in distinct tumor microenvironments.
To extend these coexpression findings at the protein level,
we conducted immunohistochemical analysis of LDHA, LDHB,
MCT1, and MCT4 in ER/PR, and HER2-annotated breast
tumors. The specificity of immunohistochemical staining for
each antibody was validated by the use of cell line controls
(Supplementary Fig. S6). Consistent with our data in breast
cancer cell lines, LDHB was expressed at moderate or high
levels (having an IHC score of 2 or 3; P ¼ 105) in 64% of triplenegative breast cancers (n ¼ 31 tumors), with weak or no
expression detected in normal breast, HER2þ tumors, or HRþ
tumors (Fig. 5 and Table 1). Furthermore, MCT1, but not
MCT4, was significantly upregulated in triple-negative breast
tumors, as 26% of triple-negative breast cancers (P ¼ 0.02; n ¼
31 tumors) exhibited an IHC score of 2 or 3. Moreover, MCT1
correlated to LDHB expression (P ¼ 0.001) within the triplenegative tumor subset (Fig. 5C–E). These data indicate that
LDHB and MCT1 are coupregulated in triple-negative breast
tumors and suggest a codependent function for these 2 genes
in triple-negative breast cancer.
LDHB expression in breast cancer correlates to a poor
clinical outcome
Cancers with a high glycolytic rate have been noted to have
worse clinical outcome (26, 27). To determine whether LDHB
expression correlates with prognosis in patients with breast
cancer, we analyzed a cohort of 227 patients with outcome data
(3). We segregated patients into 2 categories: those with LDHB
expression above the mean were considered high expressors
and those below the mean were considered low expressors. We
find that high expression of LDHB is associated with both poor
overall survival (P ¼ 0.0001) and progression-free survival (P ¼
0.0004; Fig. 6A and B). Because LDHB is primarily upregulated
in basal-like/triple-negative breast cancer and these cancers
are typically more aggressive than other subtypes, we also
examined if LDHB expression correlated to clinical outcome
independent of the basal-like breast cancer subtype. High
expression of LDHB was associated with a poor overall survival
(P ¼ 0.00003) and progression-free survival (P ¼ 0.00006), even
in the luminal tumor category (Fig. 6C and D). In contrast,
LDHA expression did not correlate with clinical outcome in
patients with breast cancer (Fig. 6E–H). Taken together, these
data indicate that LDHB expression correlates to poor patient
outcome in breast cancer.
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Figure 4. Basal-like breast cancers are dependent on glycolysis. A and B, bar graph depicts glycolysis (A) and oxidative phosphorylation (B) gene signatures in 5
breast cancer subtypes. Average log2 expression of the signature genes is shown for basal-like (n ¼ 68), claudin-low (n ¼ 27), HER2þ (n ¼ 39), luminal A
(n ¼ 95), and luminal B (n ¼ 57) breast tumors (3). Error bars represent SEM. C, sensitivity of 21 triple-negative cell lines and 5 luminal cell lines to 2DG. Graph
represents the average cell proliferation of all cell lines in each cancer subtype after 5 days of growth in 2DG. Data are the average of 3 independent
experiments (each experiment carried out in triplicate) and was normalized to cells treated with dimethyl sulfoxide. Each dot or square denotes an individual
cell line and error bars represent SEM. P value indicates a statistically significant difference. D, distribution plot showing LDHB mRNA expression in 5 breast
cancer subtypes. LDHB expression was normalized to its average expression across all breast tumors and sorted from high to low for each breast cancer
subtype (n ¼ 286 tumors). Below, MCT1-4 expression is shown for each corresponding tumor. Pearson correlation between LDHB and MCT expression in the
basal-like cohort is indicated. P values for each correlation are as follows: MCT1: Pearson ¼ 0.48, P ¼ 0.00002; MCT2: Pearson ¼ 0.22, P ¼ 0.04; MCT3:
Pearson ¼ 0.15, P ¼ 0.1; or MCT4: Pearson ¼ 0.42, P ¼ 0.0002.
Discussion
Patients with triple-negative breast cancers experience poor
clinical outcome and an aggressive tumor pathology, highlighting the need for an effective treatment (5). In this study, we
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Cancer Res; 72(22) November 15, 2012
have identified LDHB as an essential gene in triple-negative
breast cancer. LDHB was selectively required for the growth of
triple-negative breast cancers both in vitro and in vivo and
specifically was overexpressed in triple-negative breast
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LDHB Is a Regulator of Triple-Negative Breast Cancer
Figure 5. LDHB and MCT1 are coexpressed in basal-like breast cancer. A, representative photomicrographs show LDHB expression in normal breast and
triple-negative breast tumors. IHC score is indicated in parenthesis. B, average IHC scores for LDHB, LDHA, MCT1, and MCT4 are shown for each
breast tumor subtype. The number of samples scored for each marker per tumor subytpe is shown in Table 1. Tumor subtypes were defined as HRþ, HER2
positive (HER2þ), and triple negative (TN; lacking ER, PR, and HER2). P values indicate a statistically significant difference and error bars represent SEM.
C and D, correlation analysis of LDHB coexpression with MCT1 (C) or MCT4 (D) in triple-negative breast tumors (n ¼ 31 tumors). Orange box highlights a
statistically significant association between LDHB and MCT1 overexpression using Fisher exact test (P ¼ 0.001). Levels of LDHB, MCT1, and MCT4
proteins are indicated on the top as low (IHC score 0 or 1) or high (IHC score 2 or 3). E, representative images showing LDHB and MCT1 expression from serial
sections of the same tumors. Level of LDHB and MCT1 protein expression are indicated on the top as low or high.
tumors. Gene expression analysis indicates that triple-negative
breast tumors upregulate a number of genes important for
glycolysis. In support of this expression profile, we show that
triple-negative breast cell lines are more sensitive to the
glycolysis inhibitor 2-deoxyglucose than luminal cell lines,
suggesting that triple-negative tumors exploit glycolysis for
their energy demands. Finally, we show that LDHB overexpression affords patients with breast cancer an overall poor clinical
outcome, regardless of tumor subtype.
Over the last decade, there has been a tremendous transformation in the way we research and treat breast cancer. We
now recognize that it is not a homogenous disease, but rather a
diverse set of diseases that arise from the same tissue. Most
clinical advancements have benefited patients that present
with intact ER/PR or overexpress HER2. However, patients that
lack these growth factor receptors currently have few therapeutic options. Notably, many triple-negative breast cancers
display aberrant p53, BRCA1 mutations, and express intact
EGFR/HER1 (28). Recent reports have found that basal-like
cancers contain activated KRAS and MYC gene signatures and
www.aacrjournals.org
are sensitive to mitogen-activated protein/extracellular signal–regulated kinase (MEK) inhibition, despite the lack of
KRAS mutation (29–31). While targeting these signaling pathways is an active area of investigation, we took an unbiased
approach to discovering novel therapeutic targets by identifying genes that exhibit differential expression or genomic
amplification between luminal and triple-negative/basal-like
cancers. Our hypothesis was that as tumor cells become
dependent on cellular activities for cell growth or survival,
they find ways to upregulate components in that pathway.
Using this integrated genomic approach, we identified LDHB
and other metabolic pathway genes that are upregulated and
essential for triple-negative cell proliferation.
In adult somatic tissue, LDHA and LDHB are the predominant LDH isoforms that are expressed. While many tissues
express both isoforms, LDHB is exclusively expressed in heart
and LDHA is exclusively found in skeletal muscle (32). Interestingly, patients have presented in the clinic that lack functional LDHA or LDHB, suggesting that both are individually
dispensable for normal adult physiology (33, 34). Importantly,
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McCleland et al.
Table 1. Expression of lactate metabolism genes in breast cancer subtypes
LDHA
LDHB
MCT1
MCT4
Mutational status
Expression level
% (n)
% (n)
% (n)
% (n)
HRþ
0
1þ
2þ
3þ
0
1þ
2þ
3þ
0
1þ
2þ
3þ
10 (39)
38 (39)
33 (39)
18 (39)
0 (14)
64 (14)
36 (14)
0 (14)
13 (16)
25 (16)
37 (16)
25 (16)
76 (55)
18 (55)
6 (55)
0 (55)
62 (26)
27 (26)
12 (26)
0 (26)
19 (31)
16 (31)
45 (31)
19 (31)
80 (54)
17 (54)
4 (54)
0 (54)
81 (27)
7 (27)
7 (27)
4 (27)
42 (31)
32 (31)
23 (31)
3 (31)
61 (54)
28 (54)
4 (54)
4 (54)
67 (27)
15 (27)
15 (27)
4 (27)
55 (31)
32 (31)
13 (31)
0 (31)
HER2þ
Triple negative
NOTE: LDHB, LDHA, MCT1, and MCT4 protein expression scores are shown for the different breast cancer subtypes. Expression was
ranked from 0 (no expression) to 3 (highest expression). Tumor subtypes were defined by HRþ (expressing ER or PR), HER2 positive
(HER2þ), or triple negative (TN; lacking ER, PR, and HER2). For each gene, the percentage of tumors with the indicated expression is
shown. Percentages were calculated within each subtype and n designates the number of tumors for each subtype.
this also suggests that small molecules that target LDH activity
should afford patients few off-target effects. While our data
using RNAi to deplete LDHB are compelling, the development
of such molecules will be an important tool to validate the
phenotype associated with RNAi mediated loss of LDHB.
LDHA has garnered the most attention in tumor biology, as it
is broadly upregulated in many tumors, is a downstream target
of hypoxia-inducible factor-1 (HIF-1), and plays an essential
role in tumor initiation and growth (18, 35). The significance of
LDHB in tumor biology is not well defined. Our IHC data show
that LDHB is expressed at low levels in normal breast tissue.
This would argue that luminal tumors are more like normal
tissue and that triple-negative/basal-like tumors actively upregulated LDHB expression. Recent reports indicate that LDHB
expression and function in tumors may be context or tissue
specific. In mouse immortalized cell lines, it was found that
LDHB expression was controlled by the mTOR pathway and
that mTOR-mediated tumor formation depended on LDHB
(36). Our in vitro and in vivo LDHB knockdown data extend on
these initial observations and implicate LDHB as a metabolic
regulator in triple-negative breast cancer. It is worth noting
that LDHB downregulation has been reported in the context of
other tumor types. For example, LDHB is expressed in normal
prostate tissue, but silenced by promoter methylation in
prostate carcinomas (37). In the future, it will be of interest
to determine the upstream pathways that regulate LDHB
expression in both luminal and triple-negative breast cancer.
A key question remains how LDHB inhibition causes
reduced tumor growth. Because LDHA is present in all breast
cancers and cell lines we have examined, we speculate that
LDHB has a nonredundant function. LDHA and LDHB can
form homo or heterotetramers with each other to generate a
functional enzymatic complex. One possible mechanism to
account for the essential effects of LDHB in triple-negative
5820
Cancer Res; 72(22) November 15, 2012
breast cancer is that in these tumors, LDHB homotetramers
or LDHB–LDHA heterotetramers are preferred or have
increased catalytic activity in comparison with LDHA only
homotetramers.
A recent set of publications has provided new perspectives on
tumor metabolism, which offers an alternative hypothesis for
how loss of LDHB may impact tumor metabolism in triplenegative breast cancer (18, 38, 39). In what has been termed the
"reverse Warburg effect," tumor cells that are hypoxic and
glucose-deprived can use lactate that was derived from aerobic
glycolysis from surrounding stromal or tumor cells. This mechanism requires the concerted effort of the monocarboxylate
transporters MCT4, which favors lactate export, and MCT1,
which favors lactate import (24, 25, 40, 41). Of particular interest,
in triple-negative tumors it was observed that MCT1 is
expressed on tumor cells and MCT4 is expressed on the
surrounding stromal cells (39). Our findings that MCT1 is
coexpressed in LDHB-high tumors are consistent with the
hypothesis that these tumors use pyruvate or lactate as an
energy source (18, 42). It has been postulated that LDHB in
tumor cells functions to convert lactate to pyruvate (18) and is
supported by biochemical studies (43). LDHB exhibits a lower
affinity for pyruvate and is more sensitive to substrate inhibition
by pyruvate, compared with LDHA. Thus, an alternative hypothesis is that LDHB might be overexpressed in glycolytic tumors to
counteract the activity of LDHA and provide cells' metabolic
flexibility. Further work is required to test these hypotheses and
is beyond the scope of this present work. Taken together, we
postulate that the concerted upregulation of LDHB and MCT1
may provide tumors with alternative means of energy generation and the ability to adapt to the tumor microenvironment.
Our data show that on a molecular level, LDHB expression
represents a more global shift in tumor metabolism in triplenegative tumors. We find that triple-negative breast tumors and
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LDHB Is a Regulator of Triple-Negative Breast Cancer
Figure 6. LDHB expression
correlates to a poor clinical outcome
in patients with breast cancer. A–H,
Kaplan–Meier curves depicting the
correlation between LDHB (A–D) or
LDHA (E–H) expression and overall
patient survival (A, C, E, and G) or
progression-free survival (B, D, F,
and H) in primary breast tumors.
LDHB and LDHA expression were
normalized to their average
expression across all breast tumors.
For A, B, E and F, all tumors with
survival data were analyzed
(n ¼ 227). For C, D, G and H, only
luminal (A) and tumors (B)
with survival data were analyzed
(n ¼ 125). P values indicate
differences between the 2 patient
populations.
cell lines upregulate glycolytic genes and become more dependent on glycolysis for growth. In addition to our findings, 2
recent studies reported that a subset of triple-negative breast
cancers is marked by amplification and overexpression of
phosphoglycerate dehydrogenase (PHGDH; refs. 44–46).
PHGDH is a key enzyme in serine biosynthesis and shunts
glucose toward glycine production. Similar to our findings with
LDHB, triple-negative tumors with high PHGDH levels were
dependent on PHGDH expression and showed metabolic addiction to serine. These converging data indicate that triple-negative breast cancers are distinctly wired for dependence on key
metabolic components of glucose metabolism, and interference
with these pathways presents a plausible therapeutic approach.
In conclusion, our work identifies LDHB as an important
mediator of triple-negative tumor growth and supports the
idea that triple-negative breast cancers have unique metabolic
profiles that may be exploited for therapeutic intervention.
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Disclosure of Potential Conflicts of Interest
All authors are employed by Genentech, Inc.
Authors' Contributions
Conception and design: M.L. McCleland, Y. Shang, B. Haley, J.-P. Stephan, E.M.
Blackwood, L. Corson, J. Zha, R. Firestein
Development of methodology: M.L. McCleland, Y. Shang, D. Peterson, B. Haley,
J.-P. Stephan, L. Corson, R. Firestein
Acquisition of data (provided animals, acquired and managed patients,
provided facilities, etc.): M.L. McCleland, A.S. Adler, T. Hunsaker, T. Truong, D.
Peterson, E. Torres, B. Haley, J.-P. Stephan, E.M. Blackwood, L. Corson, M.
Evangelista
Analysis and interpretation of data (e.g., statistical analysis, biostatistics,
computational analysis): M.L. McCleland, A.S. Adler, Y. Shang, T. Hunsaker, D.
Peterson, E. Torres, L. Li, J.-P. Stephan, M. Belvin, G. Hatzivassiliou, E.M.
Blackwood, M. Evangelista, J. Zha, R. Firestein
Writing, review, and/or revision of the manuscript: M.L. McCleland, A.S.
Adler, J.-P. Stephan, G. Hatzivassiliou, E.M. Blackwood, L. Corson, M. Evangelista,
J. Zha, R. Firestein
Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): D. Peterson, B. Haley
Study supervision: E.M. Blackwood, L. Corson, J. Zha, R. Firestein
Cancer Res; 72(22) November 15, 2012
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5821
Published OnlineFirst November 8, 2012; DOI: 10.1158/0008-5472.CAN-12-1098
McCleland et al.
Acknowledgments
The authors thank James Lee for help and advice with the RNAi screen, David
Davis for reagents, William Forrest for biostatistical advice, and Pete Haverty for
his assistance in creating metabolic gene signatures.
The costs of publication of this article were defrayed in part by the
payment of page charges. This article must therefore be hereby marked
advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this
fact.
Received March 22, 2012; revised July 16, 2012; accepted September 1, 2012;
published OnlineFirst November 8, 2012.
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An Integrated Genomic Screen Identifies LDHB as an Essential
Gene for Triple-Negative Breast Cancer
Mark L. McCleland, Adam S. Adler, Yonglei Shang, et al.
Cancer Res 2012;72:5812-5823. Published OnlineFirst November 8, 2012.
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