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2014;13:1270-1284. Published OnlineFirst March 21, 2014.Mol Cancer Ther
Mercedes Marín-Aguilera, Jordi Codony-Servat, Òscar Reig, et al.
Resistance and High Risk of Relapse in Prostate Cancer
Epithelial-to-Mesenchymal Transition Mediates Docetaxel
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Cancer Biology and Signal Transduction
Epithelial-to-Mesenchymal Transition Mediates Docetaxel
Resistance and High Risk of Relapse in Prostate Cancer
Mercedes Marín-Aguilera
1
, Jordi Codony-Servat
1
,
Oscar Reig
1
, Juan Jos
e Lozano
2
, Pedro Luis Fern
andez
3,5
,
María Ver
onica Pereira
1
, Natalia Jim
enez
1
, Michael Donovan
6
, Pere Puig
6
, Lourdes Mengual
4
,
Raquel Bermudo
3,7
, Albert Font
8
, Enrique Gallardo
9
, María Jos
e Ribal
4
, Antonio Alcaraz
3,4
, Pere Gasc
on
1,3
, and
Bego~
na Mellado
1,3
Abstract
Molecular characterization of radical prostatectomy specimens after systemic therapy may identify a gene
expression profile for resistance to therapy. This study assessed tumor cells from patients with prostate cancer
participating in a phase II neoadjuvant docetaxel and androgen deprivation trial to identify mediators of
resistance. Transcriptional level of 93 genes from a docetaxel-resistant prostate cancer cell lines microarray
study was analyzed by TaqMan low-density arrays in tumors from patients with high-risk localized prostate
cancer (36 surgically treated, 28 with neoadjuvant docetaxel þandrogen deprivation). Gene expression was
compared between groups and correlated with clinical outcome. VIM, AR and RELA were validated by
immunohistochemistry. CD44 and ZEB1 expression was tested by immunofluorescence in cells and tumor
samples. Parental and docetaxel-resistant castration-resistant prostate cancer cell lines were tested for
epithelial-to-mesenchymal transition (EMT) markers before and after docetaxel exposure. Reversion of EMT
phenotype was investigated as a docetaxel resistance reversion strategy. Expression of 63 (67.7%) genes
differed between groups (P<0.05), including genes related to androgen receptor, NF-kB transcription factor,
and EMT. Increased expression of EMT markers correlated with radiologic relapse. Docetaxel-resistant cells
had increased EMT and stem-like cell markers expression. ZEB1 siRNA transfection reverted docetaxel
resistance and reduced CD44 expression in DU-145R and PC-3R. Before docetaxel exposure, a selected CD44
þ
subpopulation of PC-3 cells exhibited EMT phenotype and intrinsic docetaxel resistance; ZEB1/CD44
þ
subpopulations were found in tumor cell lines and primary tumors; this correlated with aggressive clinical
behavior. This study identifies genes potentially related to chemotherapy resistance and supports evi-
dence of the EMT role in docetaxel resistance and adverse clinical behavior in early prostate cancer. Mol
Cancer Ther; 13(5); 1270–84. 2014 AACR.
Introduction
Prostate cancer is the most common malignancy in the
Western world and the second most common cause of
cancer-related mortality in men (1). Although most pat-
ients with metastatic prostate cancer respond to androgen
deprivation therapy, virtually all of them eventually
develop castration-resistant prostate cancer (CRPC). In
2004, the combination of docetaxel and prednisone was
established as the new standard of care for patients with
CRPC (2). More recently, two hormonal agents, abirater-
one and enzalutamide, and a new taxane, cabazitaxel,
have been approved for the treatment of CRPC (3–5).
However, current therapies are not curative and research
is needed to identify predictors of benefit and mechanisms
of resistance for each agent.
To date, several factors have been associated with
docetaxel resistance, including expression of isoforms of
b-tubulin (6), activation of drug efflux pumps (7), PTEN
loss (8), and expression and/or activation of survival
factors (i.e., PI3K/AKT1 and MTOR; refs. 9, 10). Previous
work by our group and others correlated the activation
of NF-kB/interleukin (IL)-6 pathways with docetaxel
resistance in CRPC models and in patients (11–13).
Other studies support a role of JUN/AP-1, SNAI1, and
Authors' Affiliations:
1
Laboratory of Translational Oncology and Medical
Oncology Department;
2
Bioinformatics Platform Department, Centro de
Investigaci
on Biom
edica en Red—Enfermedades Hep
aticas y Digestivas
(CIBEREHD), Hospital Clínic;
3
Institut d'Investigacions Biom
ediques August
Pi i Sunyer(IDIBAPS);
4
Laboratoryand Departmentof Urology,Hospital Clínic,
Barcelona;
5
Department of Pathology, Hospital Clínic, Universitat de Barce-
lona;
6
Althia;
7
Tumor Bank, Hospital Clínic—IDIBAPS Biobank, Barcelona;
8
Medical Oncology Department, Hospital Germans Trias i Pujol, Catalan
Institute of Oncology, Badalona; and
9
Medical Oncology Department, Hos-
pital Parc Taulí, Sabadell, Spain
Note: Supplementary data for this article are available at Molecular Cancer
Therapeutics Online (http://mct.aacrjournals.org/).
M. Marín-Aguilera and J. Codony-Servat contributed equally to this work.
Corresponding Author: Bego~
na Mellado, Medical Oncology Department,
Hospital Clínic de Barcelona, Villarroel 170, Barcelona, 08036, Spain.
Phone: 34-93-227-5400, ext. 2262; Fax: 34-93-454-6520; E-mail:
bmellado@clinic.ub.es
doi: 10.1158/1535-7163.MCT-13-0775
2014 American Association for Cancer Research.
Molecular
Cancer
Therapeutics
Mol Cancer Ther; 13(5) May 2014
1270
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Published OnlineFirst March 21, 2014; DOI: 10.1158/1535-7163.MCT-13-0775
NOTCH2/Hedgehog signaling pathways in the devel-
opment of resistance to docetaxel or paclitaxel (14, 15).
Moreover, it has been shown that the inhibition of andro-
gen receptor (AR) nuclear translocation and AR activity
may be an important mechanism of taxane action in
prostate cancer (9).
In previous work, we identified 243 genes with dif-
ferential expression in CRPC docetaxel-sensitive versus
docetaxel-resistant cell lines (16). In the present study,
73 genes from that study together with 20 genes from
the literature were tested in tumor specimens of patients
with high-risk localized prostate cancer included in a
clinical trial of neoadjuvant hormone chemotherapy
(17), and compared with nontreated specimens with
similar clinical characteristics. This approach was based
on the notion that residual tumor cells in prostatectomy
specimens after neoadjuvant systemic therapy are likely
enriched for resistant tumor cells and their molecular
characterization may provide important information on
mechanisms of resistance (18). Our key findings were
then tested in two models of docetaxel-resistant prostate
cancer cell lines.
Patients and Methods
Patients and samples
The study included 28 patients with high-risk localized
prostate cancer from a previously published, multicenter,
phase II trial of neoadjuvant docetaxel plus androgen
deprivation followed by radical prostatectomy (17) and
36 control patients with high-risk prostate cancer treated
with radical prostatectomy without neoadjuvant treat-
ment. Of the 57 participants in the clinical trial (17), 29
were not included in this study: 23 patients did not
consent to participation in the molecular substudy and
insufficient material for molecular analysis was available
for 6 patients, 3 of whom had a pathologic complete
response (pCR) and 3 had microscopic residual tumor
(near pCR) in the prostate specimen.
Inclusion criteria were histologically confirmed adeno-
carcinoma of the prostate with any of the following three
risk criteria: (i) clinical stage T3; (ii) clinical stage T1c or T2
with serum prostate-specific antigen (PSA) >20 ng/mL
and/or Gleason score sum of 8, 9, or 10; or (iii) a Gleason
sum of 7 with a predominant form of 4 (i.e., Gleason score
4þ3). Clinical characteristics are shown in Table 1.
Treatment consisted of three cycles every 28 days of
docetaxel 36 mg /m
2
on days 1, 8, and 15 concomitant with
complete androgen blockade, followed by radical pros-
tatectomy. Patients were followed from the time of study
inclusion until death or last visit. Median follow-up time
was 82 months (range, 10–135). PSA relapse was defined
as two consecutive values of 0.2 ng/mL or greater (19).
Radiologic progression was defined as the progression in
soft tissue lesions measured by computed tomography or
MRI, or by progression to bone (20).
The study was approved by the Institutional Ethics
Committee of each participating hospital and written
informed consent was obtained from all participants.
Formalin-fixed paraffin-embedded (FFPE) specimens
were collected after radical prostatectomy. A representa-
tive tumor area was selected for each block and, according
to its size, between 2 and 12 sections were cut, 10-mm-
thick, and used for RNA isolation. Hematoxylin and eosin
(H&E)–stained sections from tumors and adjacent tissues
were prepared to confirm the histologic diagnosis.
RNA extraction
Total RNA was isolated from tumor specimens using
the RecoverAll Total Nucleic Acid Isolation Kit (Life
Technologies) according to the manufacturer’s protocol.
Total RNA was quantified with a spectrophotometer
(NanoDrop Technologies).
Gene selection
In total, 93 targe t genes that could potentially be related
to docetaxel resistance and two endogenous control
genes (ACTB and GUSB) were selected for further anal-
ysis in tumors. A set of 73 target genes was selected for
their relative expression in docetaxel-resistant cells
(DU-145R and PC-3R) versus parental cells (DU-145 and
PC-3; ref. 16) using DAVID (21) and Ingenuity Pathway
Analysis software (http://www.ingenuity.com). Twen-
ty genes highlighted in the literature as potential targets
of docetaxel resistance were also selected.
Reverse transcription and preamplification
A High-Capacity cDNA Reverse Transcription Kit (Life
Technologies) was used to reverse transcribe 1 mg of total
RNA in a 50 mL reaction volume. cDNA preamplification
was performed by multiplex PCR with the 93 selected
genes (Supplementary Table S1) and the stem-like cell
markers CD24 and CD44, following the manufacturer’s
instructions for the TaqMan PreAmp Master Mix Kit (Life
Technologies), except that final volume of the reaction was
25 mL.
Gene expression analysis in FFPE samples
Preamplified cDNA was used for gene expression anal-
ysis using 384-Well Microfluidic Cards (Life Technolo-
gies). Preamplified samples were diluted 1:20 in TE 1X
buffer before use. Each card was configured into four
identical 96-gene sets (95 selected genes plus an endog-
enous control gene, RNA18S, by default). The reaction was
carried out following the manufacturer’s instructions on
an ABI 7900HT instrument (Life Technologies). Array
cards were analyzed with RQ Manager Software for
manual data analysis.
Gene expression of CD24 and CD44 markers was studied
by amplifying with TaqMan Gene Expression Master Mix
in a StepOnePlus Real-Time PCR system (Life Technolo-
gies), according to the manufacturer’s recommendations.
Relative gene expression values were calculated on the
basis of the quantification cycle values obtained with SDS
2.4 software (Life Technologies). Expression values were
relative to the GUSB endogenous gene. Samples from
EMT Role in Docetaxel Resistance
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patients who did not receive neoadjuvant treatment were
used for calibration.
Cell culture conditions
The CRPC cell lines DU-145 and PC-3 were purchased
from the American Type Culture Collection in October
2009. The docetaxel-resistant cell lines DU-145R and
PC-3R were developed and maintained as previously
described (12). No further authentication of the cell lines
was done by the authors.
Cell proliferation assays
Cell viability in response to docetaxel was assessed by
an MTT assay with the CellTiter 96 Aqueous Proliferation
Table 1. Clinical characteristics of patients
All
Neoadjuvant
treatment Control
Total number 64 28 36
Median age, y 64 (range, 46–74) 64 (range, 48–70) 64.5 (range, 46–74)
Clinical Stage
T1 19 (29.7%) 4 (14.3%) 15 (41.7%)
T2 33 (51.6%) 14 (50%) 18 (50%)
T3 12 (18.8%) 10 (35.7%) 3 (8.3%)
Pathologic stage
T0 1 (1.6%) 1 (3.6%) 0
T1 1 (1.6%) 1 (3.6%) 0
T2 26 (40.6%) 13 (46.4%) 13 (36.1%)
T3 36 (56.3%) 13 (46.4%) 23 (63.9%)
Gleason score (biopsy)
6 10 (15.6%) 2 (7.1%) 8 (22.2%)
7(3þ4) 22 (34.4%) 7 (25%) 15 (41.7%)
7(4þ3) 16 (25%) 8 (28.6%) 8 (22.2%)
7 (N/A
a
)——1 (2.8%)
8 11 (17.2%) 8 (28.6%) 3 (8.3%)
9 4 (6.3%) 3 (10.7%) 1 (2.8%)
Gleason score (prostatectomy)
N/A
b
18 (28.3%) 18 (64.3%) 0
6 7 (15.2%) 7 (25%) 0
7(3þ4) 13 (20.3%) 1 (3.6%) 12 (33.3%)
7(4þ3) 17 (26.6%) —17 (47.2%)
8 2 (4.3%) 0 2 (5.6%)
9 7 (15.2%) 2 (7.1%) 5 (13.9%)
Median PSA (ng/mL) 8.7 (range, 2.01–41) 12.2 (range, 4.7–41) 8.2 (range, 2.01–19.2)
PSA (ng/mL)
<20 56 (87.5) 20 (71.4%) 36 (100%)
>20 8 (12.5%) 8 (28.6%) 0 (0%)
Postoperative radiotherapy
No 35 (58.3%) 13 (54.2%) 22 (61.1%)
Yes 24 (40%) 10 (41.7%) 14 (38.9%)
N/A
a
1 (1.7%) 1 (4.2%) 0 (0%)
Biochemical relapse
No 30 (46.9%) 11 (39.3%) 19 (52.8%)
Yes 34 (53.1%) 17 (60.7%) 17 (47.2%)
Median biochemical relapse–free survival (mo) 31.7 (range, 4–81) 29.3 (range, 4–59) 34.1 (range, 8–81)
Clinical relapse
No 58 (90.6%) 22 (78.6%) 36 (100%)
Yes 6 (9.4%) 6 (21.4%) 0 (0%)
Median clinical relapse–free survival (mo) 51.2 (range, 31–84) 51.2 (range, 31–84) —
Follow-up (mo) 82 (range, 10–135) 91 (range, 81–96) 69 (range, 10–135)
Abbreviation: N/A, not available
a
Missing information.
b
In some cases Gleason score could not be assessed because of tissue changes related to neoadjuvant treatment.
Marín-Aguilera et al.
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Assay Kit (Promega) and by the trypan blue exclusion
method using a Neubauer hemocytometer chamber.
Western blot analysis
Whole-cell extracts were prepared and Western blot
analysis performed as described previously (22). Antibo-
dies used were anti-PARP. Antibody was purchased from
Roche (ref. 11835238001); b-catenin (6B3; CTNNB1) anti-
body (ref. 9582), CD44 (156-3C11) Mouse mAb (monoclo-
nal antibody; ref. 3570), E-cadherin (CDH1) antibody (ref.
4065), Snail (C15D3) Rabbit mAb (ref. 3879), TCF8/ZEB1
(D80D3) Rabbit mAb (ref. 3396), and Vimentin (R28; VIM)
antibody (ref. 3932) were purchased from Cell Signaling
Technology. Monoclonal anti–a-tubulin clone B-5-1-2 (ref.
T5168) was purchased from Sigma-Aldrich.
Real-time qRT-PCR in cell lines
Total RNA was isolated from cell lines using the
RNeasy Micro Kit (Qiagen), and quantified with a spec-
trophotometer (Nanodrop Technologies). cDNA was gen-
erated from 1 mg of total RNA using the High Capacity
cDNA Archive Kit (Life Technologies), following the
manufacturer’s instructions. Real-time quantitative rev-
erse transcription PCR (qRT-PCR) was carried out in a
StepOnePlus Real-Time PCR system (Life Technologies)
according to the manufacturer’s recommendations. Data
were acquired using SDS Software 1.4. Amplification
reactions were performed in duplicate. Expression values
were relative to the ACTB endogenous gene. Target genes
were amplified using commercial primers and probes
(Life Technologies; Supplementary Table S1).
Immunohistochemistry
Tissue sections were deparaffinized in xylene and rehy-
drated in graded alcohols. For AR and VIM staining, the
sections were placed in a 97C solution of 0.01 mol/L
EDTA (pH 9.0) for antigen retrieval. Primary mouse
mononuclear antibody for AR (DAKO; Agilent Technol-
ogies) was applied for 20 minutes at room temperature at
dilution 1:150. FLEX Monoclonal Mouse anti-VIM, Clon
V9 (DAKO) was used for VIM staining. Detection was
accomplished with the DAKO Envision System followed
by diaminobenzidine enhancement. For RELA, the sec-
tions were placed in a 97C solution of 0.01 mol/L sodium
citrate (pH 6.0) for antigen retrieval. Then, samples were
incubated with a rabbit polyclonal antibody (Santa Cruz
Biotechnology, Inc.) at dilution 1:400. Detection was per-
formed with Bond Polymer Refine Detection (DAKO;
Agilent Technologies) for the automated Bond system.
AR and RELA were evaluated throughout the semi-
quantitative method histologic score (H-score), which
measures both the intensity and proportion of staining.
The H-score for each sample was calculated by multiply-
ing the percentage of stained tumor cells by the intensity
(0, nonstained; 1, weak; 2, moderate; 3, strong). VIM was
evaluated in the same way but scoring the percentage of
staining on a scale of 0 to 4 (0, 0; 1, <1%; 2, 1%–9%; 3, 10%–
50%; 4, >50%). Nuclear and cytoplasmatic stains were
scored separately for AR and RELA proteins. The assess-
ment of all samples was done by a senior pathologist (P.L.
Fern
andez) who was blinded to all clinical information.
Immunofluorescence staining in cell lines and tumor
samples
Cell pellets were collected in a 1% agarose solution,
fixed in 4% PBS-buffered formaldehyde, and then FFPE.
Sections of 5 mm were analyzed with a multiplex immu-
nofluorescent assay. They were stained with H&E for
histopathologic assessment and stained using immuno-
fluorescence with Alexa fluorochrome–labeled antibo-
dies. Briefly, both control and resistant prostate cancer
cell lines were evaluated with a series of simplex and
duplex immunofluorescence assays to quantify the level
of selected antibody–antigen complexes from specific
regions of interest (ROI).
The FFPE prostate tissue sections also were assessed by
immunofluorescence using a single multiplex assay with
two differentially labeled antibodies (ZEB1 and CD44).
For all specimens the H&E images were used to guide and
register immunofluorescence image capture with a max-
imum of four ROIs per cell pellet and six per tissue section.
Alexa fluorochrome dyes were Vimentin (ref. MO725;
Dako), CD44 (ref. 156-3C11; Cell Signaling Technology),
ZEB1 (ref. sc-25388; Santa Cruz Biotechnology). The ROIs
were acquired from the cells and tumor tissue sections,
blinded to outcome, with a CRI Nuance imaging system,
and then analyzed with fluorescent image analysis soft-
ware to derive quantitative features from cellular/tissue
compartments. Quantitative assessment was performed
using a pixel-area function, normalized to the ROI under
investigation.
siRNA transfection
Dharmacon SMART pool control and ZEB1 siRNA
were used with lipofectamine according to the manufac-
turer’s protocol (Thermo Scientific) to inhibit ZEB1 in DU-
145/R cells. Commercial Silencer Select siRNA of ZEB1
(s229971; Life Technologies) was transfected to PC-3/R
cell lines. Cells were incubated with the siRNA complex
for 24 hours, treated with docetaxel, then harvested to
study protein expression changes of ZEB1 and CDH1 by
Western blot analysis. Apoptosis was studied at 24 and 48
hours by PARP analysis (Western blot analysis), and cell
viability was measured by MTT at 72 hours as described
before.
Fluorescence-activated cell sorting
For flow cytometry, cells were dissociated with Accutase
(Invitrogen) and washed twice in a serum-free medium.
Cells were stained live in the staining solution containing
bovine serum albumin andfluorescein isothiocyanate-con-
jugated monoclonal anti-CD44 (15 minat 4C). A minimum
of 500,000 viable cells per sample were analyzed on a
cytometer. For fluorescence-activated cell sorting (FACS),
2to510
7
cells were similarly stained for CD44 and used
to sort out CD44
þ
and CD44
cells. For the positive
EMT Role in Docetaxel Resistance
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Table 2. Multivariate analysis of gene expression and patient outcomes
Gene FC Progression
Multivariate
a
HR (95% CI) Gene FC Progression
Multivariate
a
HR (95% CI) Gene FC Progression
Multivariate
a
HR (95% CI)
Differentially expressed genes
TGFBR3 4.48 rPFS ABCB1 2.46 —NFKB1 1.76 bPFS
SERPINB5 4.43 —CDH2 2.45 —AR 1.73 rPFS
CST6 4.19 —LTB 2.40 —PTPRM 1.71 —
CLDN11 3.69 rPFS, bPFS 3.056
(1.169–7.988)
rPFS
TIMP2 2.38 rPFS REL 1.68 bPFS
GPR87 3.65 bPFS ID2 2.38 —KLF9 1.50 rPFS
AREG 3.42 —EFEMP1 2.35 rPFS BRCA1 1.47 —
SCD5 3.32 rPFS FRMD3 2.32 —SMAD4 1.36 bPFS 0.163
(0.058–0.457)
TMEM45A 3.30 rPFS HTRA1 2.31 —FRMD4A 1.31 —
MAP7D3 3.23 —LAMC2 2.22 bPFS 0.131
(0.027–0.634)
GSPT2 1.29 —
VIM 3.23 rPFS SLC1A3 2.17 rPFS, bPFS 2.555
(1.088–5.999)
rPFS
FN1 1.20 —
BCL2A1 3.09 —ZEB1 2.16 rPFS GOSR2 1.16 —
PLSCR4 3.01 rPFS IFI16 2.15 —NDRG1 1.27 —
SCARA3 3.01 —EGFR 2.11 —BTBD11 1.41 bPFS 0.321
(0.143–0.720)
ITGB2 2.92 —SAMD9 2.09 —CCNB1 1.41 —
SAMD12 2.80 rPFS, bPFS FBN1 2.03 —ESRP1 1.46 —
S100A4 2.80 rPFS FAS 1.91 —FBP1 1.53 —
G0S2 2.79 —TACSTD2 1.83 —EPCAM 1.73 —
SLCO4A1 2.75 rPFS RELA 1.81 rPFS AIM1 1.98 —
SNAI1 2.71 —TXNIP 1.77 rPFS FLJ27352 2.09 rPFS, bPFS 0.257
(0.113–0.584)
rPFS
IL6 2.64 rPFS 0.112
(0.015–0.856)
rPFS
KLHL24 1.77 rPFS ST14 2.19 rPFS
LOC401093 2.49 —EML1 1.76 rPFS C1orf116 6.08 rPFS
(Continued on the following page)
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population, only the top 10% mostly brightly stained cells
were selected. The CD44
þ
cells selected were culturedas an
individual clone in 96-well plates and expanded.
Statistical analysis
TaqMan low-density arrays (TLDA) gene expression
data were evaluated by the Wilcoxon rank-sum test and
receiver operating characteristic (ROC) analysis. Time to
PSA progression and radiologic progression were calcu-
lated from the time of prostate cancer diagnosis until PSA
or radiologic progression, respectively. The log-rank test
was used in univariate survival analyses. Multivariate
analysis of gene expression was evaluated by Cox pro-
portional hazards regression, including stage, Gleason,
PSA, and neoadjuvant treatment as clinical covariates;
backward stepwise likelihood was used for selection.
Real-time qRT-PCR experimental data were expressed as
mean SEM and were analyzed by the Student ttest. All
the statistical tests were conducted at the two-sided 0.05
level of significance.
Results
Differential gene expression between treated and
nontreated tumors
Among the 93 genes analyzed (Supplementary Table
S1), we observed differential expression (P<0.05) in 63
(67.7%) genes (Table 2); 53 genes were overexpressed and
10 underexpressed in tumor specimens from patients
treated with neoadjuvant docetaxel plus androgen depri-
vation. Genes of the NF-kB pathway (such as NFKB1,REL,
and RELA), AR, and epithelial-to-mesenchymal transition
(EMT)–related genes (such as ZEB1,VIM,CDH2, and
TGFBR3) were overexpressed in treated tumors. Among
the downregulated genes in treated tumors, were the
metastasis-suppressor gene NDRG1 (23) and the adhesion
molecule EPCAM, a regulator of the alternative splicing of
CD44 (ESRP1; ref. 24) and ST14 (a negative regulator of the
EMT mediator ZEB1; Table 2; Fig. 1A; ref. 25).
Gene expression and clinical outcome
We tested the possible prognostic impact of the 93 genes
studied by TLDAs (Supplementary Table S1). Individu-
ally, the expression of several genes was related to time-to-
PSA and/or clinical relapse (Table 2). Time to radiologic
progression and PSA progression curves are shown
in Fig. 1B and C and Supplementary Figs. S1 and S2. Of
note, the overexpression of AR, and the EMT-related
genes TGFBR3,ZEB1, and VIM was correlated with a
shorter time of radiologic progression (Fig. 1B).
We then performed a multivariate analysis, including
the genes with individual prognostic value, clinical prog-
nostic factors (PSA, Gleason, and clinical stage), and
neoadjuvant treatment. Results are shown in Table 2A
and B. In the multivariate analysis, the reduced expression
of CLDN7 was an adverse-independent prognostic factor
for clinical relapse. Loss of CLDN7 has been correlated
with adverse prognostic variables in prostate cancer and
Table 2. Multivariate analysis of gene expression and patient outcomes (Cont'd )
Gene FC Progression
Multivariate
a
HR (95% CI) Gene FC Progression
Multivariate
a
HR (95% CI) Gene FC Progression
Multivariate
a
HR (95% CI)
Nondifferentially expressed genes
CBLB ns bPFS 0.315
(0.143–0.695)
CSCR7 ns bPFS 0.241
(0.077–0.755)
RAB40B ns bPFS 0.314
(0.134–0.739)
CCPG1 ns bPFS 0.263
(0.118–0.585)
EPS8L1 ns bPFS SCEL ns rPFS
CDH1 ns bPFS 0.446
(0.217–0.917)
IGF1R ns bPFS SERPINA1 ns rPFS 0.032
(0.002–0.632)
CDK19 ns rPFS LOC401093 ns rPFS TP53INPL ns rPFS
CLDN7 ns rPFS 0.054
(0.004–0.699)
MALAT1 ns rPFS, bPFS 0.361
(0.141–0.921)
rPFS
NOTE: False discovery rate for differentially expressed genes was <0.074 in all cases.
Abbreviations: bPFS, biochemical progression-free survival; FC, fold change; rPFS, radiologic progression-free survival.
a
Significant Cox regression analysis; HR (95% confidence interval, CI); P<0.05.
EMT Role in Docetaxel Resistance
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ANontreated Treated
C
0 20 40 60 80 100 120
Low expression
CD24
High expression
P= 0.01
1.0
0.8
0.6
0.4
0.2
0.0
Time (mo)
Proportion of biochemical relapse-free survival
B
Proportion of radiologic progression-free survival
P = 0.009
VIM Low expression
High expression
1.0
0.8
0.6
0.4
0.2
0.0
P = 0.015
AR Low expression
High expression
0 25 50 75 100 125 0 25 50 75 100 125
0 25 50 75 100 125 0 25 50 75 100 125
Time (mo) Time (mo)
Time (mo) Time (mo)
1.0
0.8
0.6
0.4
0.2
0.0
P = 0.044
ZEB1 Low expression
High expression
1.0
0.8
0.6
0.4
0.2
0.0
P = 0.024
TGFB3R Low expression
High expression
1.0
0.8
0.6
0.4
0.2
0.0
Proportion of radiologic progression-free survival
E Low expression
Cytoplasmatic AR
High expression
P = 0.005
1.0
0.8
0.6
0.4
0.2
0.0
P = 0.035
Low expression
High expression
Nuclear RELA
0 25 50 75 100 125
Time (mo)
0 25 50 75 100 125
Time (mo)
1.0
0.8
0.6
0.4
0.2
0.0
Proportion of radiologic progression-free survival
High cytoplasmatic AR
60×
20×
20×
60×
High nuclear RELA
60×
20×
Low nuclear RELA
60×
20×
Low cytoplasmatic AR
F
D
Nuclear AR Cytoplasmic AR VIM Nuclear RELA Cytoplasmic RELA
IHC score (arbitrary units)
**
Controls (nontreated) Treated patients
300
250
200
50
0
100
150
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with EMT (26). Of note, the low expression of CDH1 was
an independent prognostic factor for time to PSA relapse.
We also analyzed the prognostic impact of the stem-like
cell markers CD24 and CD44, which were underexpressed
and overexpressed, respectively, in treated tumors (FC
CD24: 0.59, P¼0.07; FC CD44: 1.63, P<0.000; Supple-
mentary Table S1 and Supplementary Figs. S1 and S2). Of
note, low expression of CD24 was correlated with shorter
time of biochemical progression (Fig. 1C).
Immunohistochemistry in treated versus nontreated
tumors
We explored the expression of VIM and both cytoplas-
matic and nuclear RELA and AR in tumor samples from
neoadjuvant-treated and -nontreated patients. Staining of
cytoplasmatic RELA was significatively higher in the trea-
ted versus nontreated patients [immunohistochemistry
(IHC) score 181.9 vs. 148.3, respectively; Fig. 1D and F].
Moreover, nuclear RELA was significantly related to worse
clinical relapse (Fig. 1E). Vimentin expression was nonsig-
nificantly higher in treated tumors (IHC score 2 vs. 1,
respectively; Fig. 1D). No differences were found in the
expression of nuclear AR; however, cytoplasmatic AR
expression was significantly higher in the treated tumors
(IHC score 102.5 vs. 14.5) and correlated with radiologic
progression survival (Fig. 1D–F).
Docetaxel-resistant prostate cancer cells express
EMT and stem-like cell markers
On the basis of the results described above, we studied
the link between EMT and docetaxel resistance in four
prostate cancer cell lines models (parental DU-145 and
PC-3R cells, and their docetaxel-resistant partners DU-
145R and PC-3R, respectively). As shown in Fig. 2A and B,
the docetaxel-resistant cells phenotype was consistent
with EMT, i.e., decreased expression of epithelial markers
(CDH1 and CTNNB1) and increased expression of mes-
enchymal markers (VIM and ZEB1) at the protein level.
Consistent results were found at mRNA level, except for
CTNNB1 (data not shown).
Recent studies have shown that cells with EMT pheno-
type share characteristics of stem-like cancer cells (14, 27).
For that reason, we tested the expression of stem-like cell
markers and showed that docetaxel-resistant cells, both
DU-145R and PC-3R, exhibit transcriptional features of
cancer-stem cells, such as increased expression of CD44
and the loss of CD24 (Fig. 2C).
Moreover, in cell lines, we detected by immunofluores-
cence analysis a subset of cells coexpressing CD44 and
ZEB1. Scattered cells with these features were detectable
in the parental cell lines; however, this population was
highly enriched in the resistant cells (Fig. 2D). By FACS,
we then isolated from the parental PC-3 cells a subpop-
ulation of cells with high expression of CD44. We selected
a derived CD44
þ
/PC-3 clone that showed an increased
expression of VIM and ZEB1 and decreased CDH1 expres-
sion (Fig. 2E). This clone from the parental cells was
significantly more resistant to docetaxel than the parental
cell line, PC-3 (Fig. 2F).
Dose–response experiments in both parental and resis-
tant cells showed that docetaxel exposure significantly
increased the expression of VIM in PC-3 and PC-3R cells,
of ZEB1 in PC-3 cells, and of SNAI1 in DU-145, PC-3 and
PC-3R cells. TWIST1 expression increased in all cell lines
after docetaxel treatment. In contrast, no significant dif-
ferences were observed in the expression of SNAI2 and
CDH1 with docetaxel exposure (Fig. 3A). About stem-like
cell markers, inconsistent results were obtained for CD24
expression after docetaxel exposure because CD24 exp-
ression increased in PC-3 cells but decrease in DU-145
cells. In contrast, CD44 significantly increased in PC-3
cells with docetaxel treatment (Fig. 3B).
EMT mediates docetaxel resistance in prostate
cancer cells
To test whether inhibition of EMT could revert doce-
taxel resistance, we downmodulated the expression of
ZEB1, a key inducer of EMT. siRNA ZEB1 transfected DU-
145R and PC-3R cells had an increased expression of
CDH1 (Fig. 4A) and decreased CD44 (Fig. 4B), confirm-
ing the link between EMT and stem-like cell phenotype.
Moreover, siRNA ZEB1 transfected cells showed signif-
icantly increased sensitivity to docetaxel compared with
control cells (P<0.05; Fig. 4B and C). The magnitude of
the reversion of chemoresistance was more pronounced
in DU-145R and PC-3R cells than in the parental cells.
Docetaxel-induced apoptosis was more pronounced in
the ZEB1–siRNA transfected cells (Fig. 4B).
ZEB1/CD44 expression in tumor samples
On the basis of preclinical findings, we decided to
investigate whether CD44
þ
/ZEB1
þ
cells were present in
primary prostate cancer specimens. Twenty-two FFPE
tumors from patients with high-risk prostate cancer
Figure 1. The gene expression profile and related outcome of patients treated with neoadjuvancy versus nontreated patients. A, heatmap of differentially
expressed genes in tumor samples from neoadjuvant-treated patients, compared with those without treatment (P<0.05). Rows, genes; columns,
samples. Red pixels, upregulated genes; green pixels, downregulated genes. B, radiologic progression-free survival analysis of patients according to gene
expression of AR and the EMT-related markers TGFBR3,ZEB1, and VIM. High and low expression was established according to receiver operating
characteristic (ROC) curve analysis. The log-rank test was used to assess the statistical difference between the two groups (P<0.05). C, Kaplan–Meier curve
representing biochemical progression-free survival analysis of patients according to gene expression of the stem-like cell marker CD24. High and low
expression was established according to ROC curve analysis. The log-rank test was used to assess the statistical difference between the two groups
(P<0.05). D, IHC of VIM and nuclear and cytoplasmatic RELA and AR. Box plot, IHC scores for each protein. ,P<0.05. E, Kaplan –Meier graphs representing
radiologic progression-free survival analysis of patients according to cytoplasmatic AR and RELA nuclear staining by IHC. The log-rank test was used
to assess the statistical difference between the two groups (P<0.05). F, images show representative immunohistoche mical staining for nuclear RELA and
cytoplasmatic AR protein in prostate cancer tumors. Magnifications illustrate high and low staining of cells.
EMT Role in Docetaxel Resistance
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treated with docetaxel and androgen suppression and 15
control patients with sufficient remaining material were
available for immunofluorescence studies. All samples
were positive for CD44 staining but only 7 of 15 controls
(46.7%) and 7 of 22 treated patients (31.8%) had a ZEB1
signal. Overall, there were no differences between the
control and treated groups in the expression of ZEB1
(0.0059 vs. 0.013 mean intensity, respectively) or CD44
(1.27 vs. 1.01 mean intensity, respectively). Tumor cells
that coexpressed ZEB1 and CD44
þ
were observed in 3
(13.6%) of the 22 patients in the neoadjuvant group.
However, none of the control patients presented with
coexpression of both markers (Fig. 4D). Notably, ZEB1/
CD44 coexpression was associated with aggressive clin-
ical behavior: At the time of outcome analysis, all patients
had relapsed, 2 had developed liver metastasis, and 1 had
died due to disease progression (Fig. 4E).
Discussion
In this study, we confirm that some of the molecular
alterations associated with docetaxel resistance in a pre-
viously described in vitro model of CRPC cell lines are
present in residual cells of prostatectomy specimens trea-
ted with neoadjuvant docetaxel plus androgen depriva-
tion. Our findings may be especially relevant in clinical
practice because most patients receive androgen depriva-
tion prior and concomitantly to the administration of
docetaxel. The observed deregulated pathways may trans-
late common mechanisms of resistance to both therapies.
DU-145 DU-145R
PC-3 PC-3R
D
F
0
1
1.8
2.5
5
10
0
50
100
150
PC-3
PC-3 clon
*
**
*
Docetaxel (nmol/L)
% of Viability
E
CDH1
VIM
ZEB1
Epithelial markers
Mesenchymal marker
Stem cell marker
PC-3 Clon
CD44
C
CD24
CD44
0
1
2
3
DU-145
DU-145R
PC-3
PC3-R
** **
Fold change
Stem cell markers
A
α-Tubulin
VIM
Mesenchymal
markers
ZEB1
DU-145 DU-145R PC-3 PC-3R
Epithelial
markers
DU-145 DU-145R
CDH1
CTNNB1
α-Tubulin
α-Tubulin
PC-3 PC-3R
CD44
ZEB1
CD44+ZEB1
CD44
ZEB1
CD44+ZEB1
CD44
ZEB1
CD44+ZEB1
CD44
ZEB1
CD44+ZEB1
B
CDH1
CDH2
VIM
SNAI2
SNAI1
TWIST
ZEB1
0.0
0.2
0.4
0.6
0.8
1.0
5
10
15
DU-145R
PC3-R
DU-145
PC-3
** **
*
*
*
*
EMT markers
Fold change
(compared with parental cells)
Figure 2. EMT and stem cell
markers in parental and docetaxel-
resistant cell lines. A, Western blot
analysis in DU-145, DU-145R, PC-
3, and PC-3R cell lines of epithelial
markers (CDH1 and CTNNB1) and
mesenchymal markers (VIM and
ZEB1). Tubulin was used as a load
control. B, gene expression of EMT
markers by qRT-PCR in DU-145,
DU-145R, PC-3, and PC-3R cell
lines. Data shown are the
mean SEM of cell lines from
triplicate experiments (,P<0.05;
,P<0.001). C, gene expression of
stem cell markers by qRT-PCR
in DU-145, DU-145R, PC-3, and
PC-3R cell lines. Data, mean
SEM of cell lines from triplicate
experiments (,P<0.001). D,
confocal immunofluorescence of
CD44 (red) and ZEB1 (green) in
DU-145, DU-145R, PC-3, and PC-
3R lines. Colocalization of ZEB1
and CD44 results are in yellow.
Nuclei are stained with 40,6-
diamidino-2-phenylindole (blue). E,
Western blot analysis in parental
PC-3 and a subpopulation of
parental PC-3 cells (clone) sorted
by CD44 marker. Tubulin was used
as a load control. F, viability assay
of PC-3 and PC-3 clone under
docetaxel treatment performed by
the Tripan blue method (,P<0.05).
Marín-Aguilera et al.
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Different neoadjuvant studies have been designed to
identify pathways involved in resistance to androgen
deprivation or chemotherapy in prostate cancer. In one
study of neoadjuvant androgen deprivation, the authors
observed that many androgen-responsive genes, includ-
ing AR and PSA, were not suppressed; this suggests that
suboptimal suppression of tumoral androgen activity
may lead to adaptive cellular changes to allow prostate
cancer cells survival in a low-androgen environment (28).
Another group analyzed prostate tumors removed by
radical prostatectomy after 3 months of androgen depri-
vation. Gene expression analysis revealed that PSA and
other androgen-responsive genes were overexpressed in
tumors from patients who relapsed (29). Our data are in
concordance with these reports. We observed that the
expression of AR and several AR-regulated genes (i.e.,
ZEB1,IL6,TGFBR3,KLF9) increased in treated tumors,
even though serum PSA levels decreased under therapy
in most cases, as we previously reported (17). Moreover,
high levels of AR correlated with high risk of clinical
relapse. These data suggest that persistence of AR signal-
ing may be related to treatment resistance and/or to
eventual disease progression.
We observed no differences in AR nuclear staining
between treated and nontreated samples. However, cyto-
plasmatic expression was significantly higher in residual
tumor cells after androgen deprivation and docetaxel
exposure. Prior reports have shown that taxanes inhibit
AR nuclear translocation and that patients treated with
taxanes may have lower nuclear expression than treat-
ment-na€
ve patients (30). This was not observed in our
study, likely because our patients were treated with com-
bined therapy. Prior studies have shown that androgen
deprivation increased full-length AR protein levels in
CRPC cells, but decreased its nuclear localization (31).
Other studies have used a similar approach in patients
treated with neoadjuvantchemotherapy alone (32, 33). One
group performed microarray analysis of tumor specimens
from 31 patients treated with docetaxel plus mitoxantrone
(33). The comparison of pre- and posttreatment samples
showed increased expression of cytokines regulated by the
NF-kB pathway. These data are in concordance with our
A
VIM
0
1
2.5
5
10
0
5
10
15 DU-145
DU-145R
PC-3
PC-3R
Docetaxel (nmol/L)
Fold change
SNAI1
0
1
2.5
5
10
0
5
10
15
20 DU-145
DU-145R
PC-3
PC-3R
Fold change
TWIST1
0
1
2.5
5
10
0
1
2
3
4DU-145
DU-145R
PC-3
PC-3R
Docetaxel (n
mol/L
)
Fold change
SNAI2
0
1
2.5
5
10
0
5
10
15 DU-145
DU-145R
PC-3
PC-3R
Fold change
ZEB1
0
1
2.5
5
10
0
10
20
30 DU-145
DU-145R
PC-3
PC-3R
Docetaxel (n
mol/L
)
Docetaxel (nmol/L)
Docetaxel (n
mol/L
)
Docetaxel (nmol/L)
Docetaxel (n
mol/L
)
Docetaxel (n
mol/L
)
Fold change
CDH1
0
1
2.5
5
10
0.000
0.005
0.5
1.0
1.5
2.0
2.5 DU-145
DU-145R
PC-3
PC-3R
Fold change
B
CD24
0
1
2.5
5
10
0
1
2
3DU-145
DU-145R
PC-3
PC-3R
Fold change
CD44
0
1
2.5
5
10
0
2
4
6
8DU-145
DU-145R
PC-3
PC-3R
Fold change
Figure 3. Effect of docetaxel exposure on EMT and stem-like gene expression markers in prostate cancer cell lines. A, EMT markers gene expression in a
docetaxel dose–response manner. B, stem-like cell markers gene expression in a docetaxel dose–response manner. Geometric al symbols represent
significant differences in the corresponding cell line; data from DU-145 0 nmol/L were considered the reference for all the other measures (i.e., fold change,1).
EMT Role in Docetaxel Resistance
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C Lipo si C Lipo si
DU-145 DU-145R
A
C Lipo si C Lipo si
PC-3 PC-3R
C
0
2
3.5
0
50
100
150
PC-3 lip
PC-3 siRNA ZEB1
PC-3R lip
PC-3R siRNA ZEB1
**
**
*
*
*
**
Docetaxel (nmol/L)
Cell viability (%)
0
5
10
0
50
100
150
DU-145 lip
DU-145 siRNA ZEB1
DU-145R lip
DU-145R siRNA ZEB1
*
*
*
*
*
*
*
*
*
**
*
*
Docetaxel (nmol/L)
Cell viability (%)
B
Docetaxel 10 nmol/L Docetaxel 10 nmol/L
DU-145 DU-145R
C Lipo si C Lipo si C Lipo si C Lipo si
CD44
PARP
TUB
Docetaxel 3 nmol/L Docetaxel 3 nmol/L
PC-3 PC-3R
C Lipo si C Lipo si C Lipo si C Lipo si
D
1.0
0.8
0.4
0.6
0.2
0.0
ZEB1 and CD44 Colocalization
No colocalization
Colocalization
Time (mo)
P = 0.371
0 20 40 60 80 100 120
Proportion of radiologic
progression-free survival
ZEB1 and CD44 Colocalization
No colocalization
Colocalization
P = 0.273
1.0
0.8
0.4
0.6
0.2
0.0
0 20 40 60 80 100
Proportion of radiologic
progression-free survival
E
CDH1
ZEB1
TUB
Time (mo)
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results showing an increased expression in treated tumors
of NF-kB subunits and NF-kB–regulated cytokines, such as
IL-6, adding support to a body of evidence on the involve-
ment of this pathway in resistance to chemotherapy in
prostate cancer (11). On the other hand, NF-kB activation
may induce EMT in prostate cancer (34). Although our
study did not investigate the potential causal relationship
between NF-kB activation and EMT, this last phenomenon
was found to be highly relevant in resistance to therapy.
Moreover, increased nuclear NF-kB (RELA staining) cor-
related with a shorter time to clinical relapse, confirming
the prognostic value of this pathway activation in prostate
cancer (22).
In the present study, we analyze the transcriptional
profile of residual tumor cells after combined neoadjuvant
androgen deprivation and docetaxel treatment. Because
macrodissected tumor tissues were used for gene expres-
sion studies, our results may translate expression patterns
from both tumor and surrounding nontumor cells. How-
ever, a prior study using the macrodissection strategy
reported only minor interference of nontumor cells with
the overall gene expression profile (35). Moreover, we
considered stroma and benign cells contamination to be
homogeneous in both the treated and nontreated patient
groups. Among the 93 genes analyzed, we observed
differential expression between treated and nontreated
tumors in 63 (67.7%) genes. Of note, the over expression of
the EMT genes correlated with a shorter time to clinical
relapse.
In the EMT process, cells lose epithelial characteristics
and gain mesenchymal properties to increase motility and
invasion, allowing tumor cells to acquire the capacity to
infiltrate surrounding tissues and to metastasize in distant
sites. EMT is typically characterized by the loss of epithe-
lial (i.e., CDH1) and the gain of mesenchymal (i.e., VIM,
CDH2) markers expression (36). Several reports suggest
that AR activation, as well as androgen deprivation ther-
apy, may induce changes characteristic of EMT that may
be involved in prostate cancer progression (37–39). The
expression of the transcription factor ZEB1 may be
induced by dihydrotestosterone and is mediated by two
androgen-response elements (40). Recently, Sun and
colleagues showed that androgen deprivation causes
EMT in animal models and in tumor samples of patients
treated with hormone therapy (41). Moreover, the pres-
ence of AR-truncated isoforms, which are increased in
the castration-resistant progression, regulate the expres-
sion of EMT (42).
On the other hand, there are molecular similarities
between cancer stem-like cells and EMT phenotypic cells.
Moreover, cells with an EMT phenotype induced by
different factors are rich sources for stem-like cancer cells
(14, 27). We observed in the DU-145 in vitro model that
docetaxel-resistant cells expressed high levels of the stem
cell marker CD44 and decreased levels of CD24. More-
over, docetaxel treatment increased CD44 expression in
tumor cells. Likewise, RT-PCR results in tumor samples
showed an increased expression of CD44 and a decreased
expression of CD24 in tumors treated with neoadjuvant
androgen deprivation plus docetaxel. Our results are in
accordance with those of Puhr and colleagues, who
detected an increased CD24
low
–CD44
high
cell population
in docetaxel-resistant prostate cancer models (43). Simi-
larly, Li and colleagues detected CD24
low
–CD44
high
breast
cancer cells that were resistant to neoadjuvant chemo-
therapy (44). In a preclinical study, CD44 and CD147
enhanced metastatic capacity and chemoresistance of
prostate cancer cells, potentially mediated by activation
of the phosphoinositide 3-kinase and mitogen-activated
protein kinase pathways (45).
In the present work, we identified a population of
prostate cancer cells exhibiting an EMT phenotype that
are primarily resistant to docetaxel. The presence of an
intrinsic resistant cell population was supported by the
isolation of docetaxel-resistant clonal cells in the paren-
tal cell line PC-3, before docetaxel exposure, with a high
expression of CD44 and EMT markers and the loss of
CDH1. ZEB1
þ
/CD44
þ
cells were identified at a very low
frequency in the two parental cell lines, DU-145 and
PC3, before docetaxel exposure but their frequency
massively increased in docetaxel-resistant cells. Simi-
larly, a small percentage of ZEB1
þ
/CD44
þ
cells were
also observed in primary high-risk localized prostate
cancer tumors. ZEB1
þ
/CD44
þ
cells were present only in
tumors that had previously received neoadjuvant
androgen deprivation plus docetaxel (13.6%). Both
in vitro and tumor sample findings support the presence
of primary resistant cells harboring EMT/stem cell–like
characteristics and suggest that the exposure to doce-
taxel may eliminate sensitive cells resulting, however, in
the selective out-growth of this resistant cell population.
In our model, docetaxel also induced EMT changes in
the parental and resistant cell lines. On the basis of our
findings, both mechanisms, the existence of a primary
resistant cell with an EMT phenotype and the induction of
EMT changes induced by docetaxel, are possible. In recent
work on docetaxel-resistant PC-3– and DU-145–derived
cell lines, the authors reported that docetaxel-resistant
cells underwent an EMT transition associated with a
reduction of microRNA (miR)-200c and miR-205, which
Figure 4. Inhibition of ZEB1 in parental and docetaxel-resistant cell lines. ZEB1–CD44 staining in prostate tumor specimens. A, Western blot analysis
of CDH1 and ZEB1 in the four cell lines (DU-145, DU-145R, PC-3, and PC-3R) when ZEB1 was inhibited by siRNA. B, Western blot analysis of CD44
and PARP in the four cell lines (DU-145, DU-145R, PC-3, and PC-3R transfected cells) treated with docetaxel; the band of CD44 in PC-3 and PC-3R
corresponds to the variant CD44v6. C, MTT of ZEB1–siRNA transfected cells. Data, mean SEM of triplicate experiments. ,P<0.05. D, CD44 and ZEB1
immunofluorescence image of a prostate tumor biopsy from a patient treated with neoadjuvant docetaxel and androgen deprivation. E, Kaplan–Meier
according to immunofluorescence intensities of CD44–ZEB1 colocalization and clinical/biochemical relapse of patients treated with neoadjuvant docetaxel
and controls without neoadjuvant treatment. C, nontrasnfected cells; Lipo, control lipofectamine; si, siRNA–ZEB1.
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EMT Role in Docetaxel Resistance
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regulate the epithelial phenotype. Their study also
showed reduced CDH1 expression in tumors after neoad-
juvant chemotherapy (43). Another study showed that
paclitaxel DU-145–resistant cells have greater ZEB1,VIM,
and SNAI1 expression (46).
We tested whether EMT played a causal role in
docetaxel chemoresistance by interfering with the
expression of the transcription factor ZEB1, a key medi-
ator of EMT, in prostate cancer cell lines. We observed
that ZEB1 genetic downmodulation restored CDH1 but
suppressed CD44 expression, which was consistent
with a reversion of EMT and stem-like cell features.
We also observed that ZEB1 inhibition caused prostate
cancer cell mortality independently of docetaxel. This
effect was previously described and is consistent with
the known role of ZEB1 in cell proliferation related,
which is related to the expression of cell cycle inhibitory
cyclin-dependent kinase inhibitors (47). Furthermore,
ZEB1 inhibition restored sensitivity to docetaxel, sup-
porting a mechanistic role of EMT and stem-like cell
phenotype in resistance to therapy. In a previous study
of an adenocarcinoma lung cancer model, inhibition of
ZEB1 significantly enhanced the chemosensitivity of
docetaxel-resistant cells in vitro,andin vivo the ectopic
expression of ZEB1 increased chemoresistance (48).
Several reports have provided evidence that EMT is
critical for invasionand migration and is involved in tumor
recurrence, which is believed to be tightly linked to cancer
stem cells. CD44 and VIM expression in primary tumors
has been correlated with adverse prognosis (34, 49). Nota-
bly, the few patients in our series with ZEB1
þ
/CD44
þ
tumor cells in primary tumors showed extremely aggres-
sive clinical behavior.
In summary, we observed a differential expression of
NF-kB, AR, EMT, and stem-like cell markers between
treated and nontreated tumors. Moreover, they were
related to a higher risk of PSA and/or clinical relapse.
Because the neoadjuvant population may be of higher risk
than the surgical patients, we cannot exclude the possi-
bility that the expression of these markers is more related
to the characteristics of the disease than to the therapy.
However, none of the clinical factors (PSA, Gleason,
clinical stage, or the presence of prior neoadjuvant ther-
apy) correlated with clinical outcome in the univariate or
multivariate analysis in our series.
Overall, our findings support a role of EMT in resistance
to prostate cancer therapy and progression. Our clinical
data were generated in the neoadjuvant setting and can-
not be extrapolated to patients with CRPC. However, both
in vitro and clinical results support the investigation of the
role of EMT in resistance to chemotherapy in CRPC.
Moreover, novel strategies to revert or prevent EMT are
warranted to improve the outcome of CRPC or to increase
the probabilities of cure for patients with high-risk pros-
tate cancer.
Disclosure of Potential Conflicts of Interest
M. Donovan is a consultant/advisory board member for Althia. No
potential conflicts of interest were disclosed by the other authors.
Authors' Contributions
Conception and design: M. Marı
´n-Aguilera, J. Codony-Servat, L. Men-
gual, B. Mellado
Development of methodology: M. Marı
´n-Aguilera, J. Codony-Servat,
N. Jim
enez, P. Puig, L. Mengual, M.J. Ribal, B. Mellado
Acquisition of data (provided animals, acquired and managed patients,
provided facilities, etc.): M. Marı
´n-Aguilera, J. Codony-Servat, P.L.
Fern
andez, N. Jim
enez, M. Donovan, R. Bermudo, A. Font, E. Gallardo,
M.J. Ribal, B. Mellado
Analysis and interpretation of data (e.g., statistical analysis, biostatis-
tics, computational analysis): M. Marı
´n-Aguilera, J. Codony-Servat,
O. Reig, J.J. Lozano, P.L. Fern
andez, N. Jim
enez, M. Donovan, L. Mengual,
A. Font, P. Gasc
on, B. Mellado
Writing, review, and/or revision of the manuscript: M. Marı
´n-Aguilera,
J. Codony-Servat,
O. Reig, P.L. Fern
andez, M. Donovan, A. Font, E. Gal-
lardo, P. Gasc
on, B. Mellado
Administrative, technical, or material support (i.e., reporting or orga-
nizing data, constructing databases): M. Marı
´n-Aguilera, J. Codony-
Servat, M.V. Pereira, N. Jim
enez, L. Mengual
Study supervision: M. Marı
´n-Aguilera, J. Codony-Servat, M. Donovan,
A. Alcaraz, B. Mellado
Acknowledgments
The authors thank Instituto de Salud Carlos III and Cellex Foundation
for funding the project. The authors also would like to thank M
onica Marı
´n
and Laura Gelabert for their excellent technical assistance and Elaine Lilly,
for review of the English text.
Grant Support
This work was supported by Cellex Foundation, by the Instituto de
Salud Carlos III—Subdirecci
on General de Evaluaci
on y Fomento de la
Investigaci
on (grants number PI07/0388 and PI12/01226; to B. Mellado),
and by the Ministerio de Economı
´a y competitividad (grant number
SAF2012-40017-C02-02; to P.L. Fern
andez). This study was also cofinanced
by Fondo Europeo de Desarrollo Regional. Uni
on Europea. Una manera de
hacer Europa. M. Marı
´n-Aguilera received a grant from Cellex Foundation.
This work was developed at the Centro Esther Koplowitz, Barcelona,
Spain.
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 September 16, 2013; revised February 13, 2014; accepted March
7, 2014; published OnlineFirst March 21, 2014.
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