1. Reciprocal changes in gene expression profiles of cocultured breast
epithelial cells and primary fibroblasts
Patricia Bortman Rozenchan1
, Dirce Maria Carraro2
, Helena Brentani2
, Louise Danielle de Carvalho Mota2
,
Elen Pereira Bastos1
, Elisa Napolitano e Ferreira2
, Cesar H. Torres2
, Maria Lucia Hirata Katayama1
,
Rosimeire Aparecida Roela1
, Eduardo C. Lyra3
, Fernando Augusto Soares2
, Maria Aparecida Azevedo Koike Folgueira1
,
Jo~ao Carlos Guedes Sampaio Goes3
and Maria Mitzi Brentani1*
1
Disciplina de Oncologia, Departamento de Radiologia, Faculdade de Medicina da Universidade de S~ao Paulo,
Av. Dr. Arnaldo, 455, Sala 4112, S~ao Paulo, SP CEP 01246-903, Brazil
2
Centro de Ensino e Pesquisa, Hospital A.C. Camargo, R. Prof Antoˆnio Prudente, 211, Liberdade,
CEP 01509-900, S~ao Paulo, SP, Brazil
3
Instituto Brasileiro de Controle do Caˆncer, Av. Alcaˆntara Machado 2576, S~ao Paulo, SP CEP 03102-002, Brazil
The importance of epithelial-stroma interaction in normal breast
development and tumor progression has been recognized. To iden-
tify genes that were regulated by these reciprocal interactions, we
cocultured a nonmalignant (MCF10A) and a breast cancer
derived (MDA-MB231) basal cell lines, with fibroblasts isolated
from breast benign-disease adjacent tissues (NAF) or with carci-
noma-associated fibroblasts (CAF), in a transwell system. Gene
expression profiles of each coculture pair were compared with the
correspondent monocultures, using a customized microarray.
Contrariwise to large alterations in epithelial cells genomic pro-
files, fibroblasts were less affected. In MDA-MB231 highly repre-
sented genes downregulated by CAF derived factors coded for
proteins important for the specificity of vectorial transport
between ER and golgi, possibly affecting cell polarity whereas the
response of MCF10A comprised an induction of genes coding for
stress responsive proteins, representing a prosurvival effect. While
NAF downregulated genes encoding proteins associated to glyco-
lipid and fatty acid biosynthesis in MDA-MB231, potentially
affecting membrane biogenesis, in MCF10A, genes critical for
growth control and adhesion were altered. NAFs responded to
coculture with MDA-MB231 by a decrease in the expression of
genes induced by TGFb1 and associated to motility. However,
there was little change in NAFs gene expression profile influenced
by MCF10A. CAFs responded to the presence of both epithelial
cells inducing genes implicated in cell proliferation. Our data
indicate that interactions between breast fibroblasts and basal
epithelial cells resulted in alterations in the genomic profiles of
both cell types which may help to clarify some aspects of this
heterotypic signaling.
' 2009 UICC
Key words: breast cancer; fibroblasts; microenvironment; coculture;
microarray
Important early literature and several recently reviewed studies
have demonstrated that neoplastic transformation and progression
of breast carcinoma cells are influenced by interactions with
neighboring stromal components of which the principal cells are
fibroblasts.1–6
Recent reports demonstrated that breast cancer
derived fibroblasts exhibit biological characteristics distinct from
fibroblasts obtained from nonmalignant breast.7–13
Genetic and
epigenetic alterations were also described in the stromal cells.14–19
Malignant cells interact with the microenvironment by secreting
soluble factors or by cell–cell and cell–matrix contacts. Tumor
cells may release signaling molecules that affect the transcription
of genes in nearby cells and conversely, fibroblasts in the stromal
compartment of malignant breast lesions are also a source
of growth factors, chemokines, proteases and provisional
extracellular matrix molecules, creating a permissive field for the
malignant cells and potentially affecting nontumorigenic epithelial
cells.2,7,20-26
A number of reports have also demonstrated fibroblast effects
on growth differentiation and invasion of normal/malignant breast
epithelial cells.9,27–34
The importance of the functional state of the
stromal cell compartment for the clinical behavior of tumors was
recently reported.35
The microenvironment on which the tumor grows is complex
consisting mainly of tumor epithelial cells and associated
fibroblasts as well as nontransformed epithelial cells and normal
fibroblasts. The exact role of these cell types, interacting with
each other, in the progression of breast cancer has yet to be fully
understood. One approach to study this interaction is to determine
changes in gene expression profiles resulting from combination
between fibroblasts and nonmalignant or malignant breast epithe-
lial cells. Reciprocal inductive interactions on gene expression
have been previously studied in animal breast cancer models36
and analyzed in coculture systems involving melanoma,37
pancre-
atic38
and lung cancer cells39
and recently in mammary cell lines
cocultivated with fibroblasts cell lines of different origins.40
To ask whether soluble factors released by stromal fibroblasts
could regulate gene expression profile of normal or transformed
breast epithelial cells and vice-versa, we performed coculture
assays and analyzed changes in gene profile in both cell types, in
response to 2-way interactions between them. In our experimental
approach, we used a transwell system and cocultivated fibroblasts
derived from breast carcinomas of different patients (CAFs) or
isolated from breast tissues adjacent to breast benign tumors
(NAFs) with either an spontaneously immortalized but noncancer-
ous breast epithelial cell line (MCF10A) or an invasive immortal-
ized breast carcinoma (MDA-MB231), both expressing a basal
signature.41
The gene expression profile of each component of the
different combinations was compared with the respective
monocultures (Fig. 1).
Material and methods
Tissue samples
Malignant and benign breast tissue specimens were obtained
from patients undergoing surgery for breast disease. Carcinoma
samples were obtained from 6 patients clinically staged as IIa, and
benign samples were obtained from 6 patients with a diagnosis of
fibroadenoma (n 5 4) or fibrocystic disease (n 5 2) (hereafter
called normal fibroblasts). None of the patients had received
preoperative chemotherapy. All tissue donors were patients at
Instituto Brasileiro de Controle do Caˆncer, S~ao Paulo, Brazil, a
reference center for cancer treatment. This study was approved by
Additional Supporting Information may be found in the online version
of this article.
Grant sponsor: FAPESP; Grant numbers: 01/13515-1, 05/51593-5, 04/
04607-8; Grant sponsor: CNPQ; Grant number: 47.7538/2003-7.
*Correspondence to: Faculdade de Medicina da USP, Departamento de
Radiologia, Disciplina de Oncologia, Av. Dr. Arnaldo, 455, 4 Andar, Sala
4112, S~ao Paulo, SP, Brazil. Fax: 55-11-3082.6580.
E-mail: mbrentani@lim24.fm.usp.br
Received 13 October 2008; Accepted after revision 2 June 2009
DOI 10.1002/ijc.24646
Published online 15 June 2009 in Wiley InterScience (www.interscience.
wiley.com).
Int. J. Cancer: 125, 2767–2777 (2009)
' 2009 UICC
Publication of the International Union Against Cancer

2. the Institutional Committee and written informed consent was
obtained by all participants. Invasive breast cancer was confirmed
histopathologically. See Table I for patient characteristics.
For validation studies, fresh-frozen human breast tumor samples
were retrieved from the Tumor Tissue Biobank of the Medical and
Research Center - Hospital A. C. Camargo, S~ao Paulo. Sections of
5-lm thick from the fresh-frozen tumor blocks were cut onto glass
slides, stained with hematoxylin and eosin (HE), and reviewed
by a pathologist. The HE-stained sections were used to evaluate
and select appropriate tumor areas corresponding to each histolog-
ical component, only the stromal component of all samples was
collected. Four matched samples were evaluated, consisting of 4
IDC samples and 4 non-neoplastic samples, these samples were
obtained from perilesional mammary specimens from patients
obtained during resection of tumoral lesions. A pathologist sub-
jected all slides representative of IDC to a careful histopathologi-
cal analysis.
Cell lines
The immortalized human breast carcinoma MDA-MB231 and
the spontaneously immortalized but nontumorigenic breast epithe-
lial MCF10A cell line42
were purchased from American Type
Culture Collection (ATCC, Manassas, VA) and maintained as
indicated by the supplier. Briefly, MDA-MB231 cells were culti-
vated with Leibovitz L-15 medium (Gibco, Invitrogen, Carlsbad,
CA) supplemented with 10% FBS (Gibco, Invitrogen). MCF10A
cells were cultivated in DMEM/Ham’s F-12 medium (Gibco,
Invitrogen) supplemented with 100 ng/ml cholera toxin (Calbio-
chem, La Jolla, CA), 0.01 mg/ml insulin (Sigma, Saint Louis,
MO), 500 ng/ml hydrocortisone (Sigma), 20 ng/ml epidermal
growth factor (Sigma) and 5% horse serum (Gibco, Invitrogen).
The luminal mammary epithelial cells, HB4A, were generously
donated by Drs. Michael J. O’Hare and Alan McKay, from Lud-
wig Institute for Cancer Research, London, UK, and maintained
with RPMI 1640 (Gibco, Invitrogen) supplemented with 10%
FBS, 5 lg/ml insulin and 5 lg/ml hydrocortisone and was used as
reference for cDNA microarray assays and validation assays. All
cell lines were maintained at 37°C in a humidified atmosphere
containing 5% CO2. Subconfluent cultures (80–90%) were used in
the experiments.
Primary cell culture
Fibroblasts were obtained from normal adjacent tissue samples
from patients with benign breast diseases (NAF) or with primary
invasive breast cancer tumors (CAF). HE-stained, frozen histo-
logical sections were prepared from each tissue sample to confirm
benignity or malignancy. After adipose tissue removal, tissue was
minced in PBS, washed twice in PBS and in culture medium, and
then chopped into small 1–4 mm3
pieces under sterile conditions.
A total of 15–30 fragments were transferred to a T25 culture flask
and covered with DMEM, 20% FBS, 100 lg/ml ampicillin,
100 lg/ml streptomycin, 2.5 lg/ml Fungizone and maintained at
37°C in a humidified atmosphere containing 5% CO2. Outgrowth
of cells was recorded after 10–20 days and medium was renewed
once or twice a week thereafter. After sufficient outgrowth, the
tissue fragments were removed and the cells were passaged by
mild trypsinization.
Characterization of fibroblasts
Primary cells cultures of breast fibroblast were characterized by
immunofluorescence. Briefly, cells in early passages (passage 3)
were platted in circular slides (U 5 13 mm, Glasscyto, Bioslide
Technology, Walnut, CA) and incubated with human anti-vimen-
tin (clone Vim 3b4), human anti-smooth muscle actin (clone
M0635), human anti-pancytokeratin (clones AE1/AE3) and
human anti-CD31 (clone JC70A), all antibodies from DAKO
Corporation, Carpinteria, CA. In addition, we used anti-fibroblast
activated protein a (FAP-19) antibody, generously donated by
Dr. Lloyd J. Old, for fibroblasts activation characterization. After
that, cells were incubated with the secondary antibody (Alexa
Fluor 488 rabbit or mouse anti-IgG (Invitrogen) diluted in PBS
FIGURE 1 – Schematic representation of cocultures assays. Normal
adjacent tissue from patients with benign breast diseases (NAF, n 5
6) or from primary invasive breast cancer tumors (CAF, n 5 6) and
epithelial cells (MCF10A and MDA-MB231) were cocultured using
transwell tissue-culture inserts with micro porous membrane for 72 hr;
all cocultures and monocultures were exposed to the same conditions;
RNA was extracted and or amplified from each cell type for hybridiza-
tion onto cDNA microarrays, or subjected to RT-PCR.
TABLE I – PATIENT CHARACTERISTICS
Patient # Diagnosis HG ER PR ErbB2
CAF1 IDC III 2 2 1
CAF2 IDC III 1 1 2
CAF3 IDC I 2 1 2
CAF4 ILC II 2 2 2
NAF5 Fibroadenoma
NAF6 Fibroadenoma
NAF7 Fibroadenoma
NAF8 Fibroadenoma
CAF9 IDC II 1 1 2
CAF10 IDC II 1 1 2
NAF11 Fibrocystic disease
NAF12 Fibrocystic disease
IDC, invasive ductal carcinoma; ILC, invasive lobular carcinoma;
HG, histological grade; ER, estrogen receptor; PR, progesterone re-
ceptor; ErbB2, Her2.
2768 ROZENCHAN ET AL.

3. containing 0.005% Evans Blue (Sigma). The cells analysis was
performed using a Zeiss Axioplan microscope (Carl Zeiss; Jena,
Germany) and the mean percentage of smooth muscle actin posi-
tive cells was evaluated using 10 randomically selected areas from
slides and the images (magnification 4003) were processed by the
software Image ProPlus 6.0 (Cybernetics, Silver Spring, MD).
MTT proliferation assay
CAFs (n 5 4) and NAFs (n 5 4) were plated in triplicate in 96-
well plates at a density of 1000 cells/well, and the next day the
media was replaced with 3-(4,5-methylthiazol-2-yl)-2,5-diphenyl-
tetrazolium bromide (MTT) (0.5 mg/ml)-containing media,
incubated at 37°C for 4 hr, to solubilize formazon crystals. We
evaluated the proliferation rate between 0 and 120 hr. Absorbance
was measured at 595 nm in a Bio-Rad plate reader (BioRad,
Hercules, CA) and data analyzed using GraphPad Prism Software,
version 3.0 (GraphPad Software).
Coculture experiments
Seventy-two hours before coculture experiments, all cells were
exposed to the same conditions and distinct culture media were
replaced by DMEM/F12 supplemented with 5% horse serum,
100 ng/mL cholera toxin, 0.01 mg/mL insulin, 500 ng/mL hydro-
cortisone, 20 ng/mL epidermal growth factor and antibiotics.
Cocultures of stromal and epithelial cells were performed using
transwell tissue-culture inserts with a microporous membrane
(Becton Dickinson Labware, Franklin Lakes, NJ). Epithelial cells
were plated (1.3 3 105
cells) onto the bottom of the wells. Stromal
cells were seeded (5.8 3 104
cells) on the permeable membrane of
0.4 lm tissue culture inserts which were then introduced into epi-
thelial cell-containing wells. This proportion of epithelial:stromal
cells was chosen to mimic that observed in the mammary gland
( 70:30). After 72 hr, cells in the inserts or on the bottom of the
wells, as well as monocultures, were washed and harvested, and
the RNA was isolated. A schematic representation of the coculture
experiments can be seen in Figure 1. All experiments were
performed between passage 06–10 and at 70% confluence.
cDNA microarray assembly, hybridization and analysis
A cDNA microarray platform containing 4608 open reading
frame expressed sequence tags (ORESTES) was assembled at the
Ludwig Institute for Cancer Research, S~ao Paulo, Brazil.43
ORESTES privileges the central part of mRNA molecules and
selection of those to be spotted on the slides followed all these
criteria: (i) cDNA clones representing full length genes; (ii) 300
bp and a high-quality sequence (CG content); (iii) 100 bp region
with gene identity 85% as verified on the site http://ncbi.nlm.
nih.gov/Blast and (iv) cDNA clone 30
sequence. cDNA clones
were derived from human breast, colon, stomach, and head and
neck tumors. These sequences could be classified among 505
function categories (biological processes). Another 192 reference
sequences were included as positive and negative controls of
hybridization. Platform characteristics complying with
MIAME format may be verified in the gene expression omnibus
(GEO) data repository, under accession number GPL 1930
(www.ncbi.nlm.nih.gov/projects/geo).
Total RNA from all samples was isolated using TRIZOL
(Invitrogen) reagent according to the manufacturer’s protocol.
RNA quality was verified by agarose gel electrophoresis and
visualization with ethidium bromide. Only RNA samples with a
ratio 1 for 28S/18S ribosomal RNA were further processed. A
2-round RNA amplification and hybridization procedures followed
a previously described protocol.44
Hybridized arrays were scanned on a confocal laser scanner
(Arrayexpress, Packard Bioscience, Wellesley, MA) using identi-
cal photomultiplier voltage (PMT 50) for all slides and data were
recovered with the Quantarray software (Packard Bioscience)
using histogram methods. After image acquisition and quantifica-
tion, saturated spots (signal intensity 63,000) as well as low-
intensity spots were removed from the analysis. Average signal
intensity between technical replicates was determined for each
spotted sequence and a local background subtraction was
performed. Quantified signals were then submitted to log transfor-
mation and Lowess normalization within each array, followed by
global Lowess normalization for all arrays.
The following analysis takes 3 factors into consideration:
(i) whether or not the fibroblast culture was derived from a malig-
nant environment; (ii) which epithelial cell type is involved and (iii)
if cells were exposed to coculture or not. Differentially expressed
genes were assessed by ANOVA (2 3 2). Probe sets with ANOVA
p 0.05 and fold change 2.0 were considered significant. A
Tukey test was done for 2 3 2 comparisons. Hierarchical clustering
analysis based on Euclidian distance and complete linkage was per-
formed using the differentially expressed genes identified through
ANOVA. Reliability of the clustering was assessed by the Boot-
strap technique using the TMEV software. The gene ontology (GO)
analysis was performed using the GO tree machine tool (GOTM)
which identifies categories hyper-represented in our gene lists and
also KEGG pathways. For GO, we used a hyper geometric distribu-
tion with p value 0.01 and for KEGG we also used a hyper
geometric distribution but with p value 0.05.45
Laser capture microdissection
Cells were laser captured using the PixCell II laser capture
microdissection (LCM) system (Arcturus Engineering, Mountain
View, CA). About 4000 cells were captured from 4 to 7 lm frozen
sections, mounted onto glass slides, and stained with 100 lL of
nuclear fast red (C.I.60760; Certistain1
; Merck, Darmstadt,
Germany) for microscopy. Only 1 type of cells was isolated from
each sample group. A representative sample of cells from IDC
depicting the different phases during the microdissection proce-
dure is shown in Supporting Information Figure S1.
RNA isolation and amplification
LCM captured cells on CapSureTM
HS LCM Caps (Arcturus
Engineering) were resuspended in 10 lL of PicoPure RNA extrac-
tion buffer (Arcturus Engineering). Total RNA was extracted by
using the PicoPureTM
RNA Isolation kit (Arcturus Engineering
#KT0204) and DNase treated using the RNase-Free DNase Set
(Qiagen #79254; Qiagen-Germantown MD), in accordance with
the manufacturer’s instructions.
Samples were processed with the Arcturus Riboamp HSTM
(Arcturus Engineering #KT0505), a T7 RNA polymerase based
technology, following the manufacturer’s recommendations.
Stress treatment
MCF10A cells grown and maintained in DMEM/F12 supple-
mented with 5% horse serum, 100 ng/mL cholera toxin, 0.01
mg/ml insulin, 500 ng/mL hydrocortisone, 20 ng/mL epidermal
growth factor and antibiotics were treated for 24 hr with Thapsi-
gargin (TG) (Sigma-Aldrich, St Louis, MO) dissolved in ethanol at
concentration of 250 nM to induce ER stress by disrupting calcium
homeostasis. The TG concentration of 250 nM was chosen, among
several concentrations (100, 250, 500 and 1000 nM), because
this concentration presented the smallest cytotoxic effect for
MCF10A cells determined using trypan blue dye exclusion. After
treatment total RNA was extracted using Trizol and submitted to
RT-PCR.
Real-time RT-PCR analysis
We evaluated the expression of some genes chosen to be
differently expressed between samples using cDNA microarray
technology by real-time RT-PCR. The genes were randomly
selected, but another criteria used was fold variation 2 and false
discovery ratio 0.05.
Reverse transcription was performed using 2 lg of total RNA, a
random hexamer primer (Invitrogen) and Superscript TM
II
2769COCULTURE INDUCED CHANGES IN EXPRESSION PROFILES

4. Reverse Transcriptase (Invitrogen). Primers were designed for
different exons to avoid amplification of genomic DNA using
Primer 3 software (http://frodo.wi.mit.edu/cgi-bin/primer3/primer3_
www.cgi), and synthesized by IDT (Integrated DNA Technologies,
Coralville, IA).
PCR was performed in a Rotor-gene system (Corbett Research,
Mortlake, Australia). Thermocycling was done in a total volume of
20 lL containing 5 lL of cDNA sample (diluted 1:40), 1.5 mM
MgCl2, 0.2 lM of each primer, 0.1 lL SYBR1
Green I (Sigma;
1:100 working dilution) and Platinum Taq DNA polymerase
(Invitrogen life Tecnologies), reaction buffer, and a deoxyribonucle-
otide triphosphate mixture. Primer sequences and cycling variables
are listed in Table II. PCR were performed in duplicate to all twelve
samples distributed as follow, 08 samples after cDNA microarray
analyses and we have included fibroblasts from 2 patients with duc-
tal invasive carcinomas and from 2 patients with fibrocystic disease
(see Table I). We also obtained 4 matched samples using LCM
from patients diagnosed with invasive ductal carcinoma.
The duplicate average values were used for quantification and
the relative expression of genes of interest was normalized to that
of actin-b, and gene expression in each sample was then compared
with expression in HB4A cells. The comparative CT method
(DDCT) was used for quantification of gene expression and
relative expression was calculated as 22DDCT
.
Results
Characterization of isolated fibroblast population
Isolated breast fibroblast (normal or tumors associated) popula-
tions were characterized by immunofluorescent staining. Both
fibroblast monolayers stained uniformly for vimentin and FAP-19,
but were negative for cytokeratin and CD31, confirming the stro-
mal origin of cells and the absence of contaminating epithelial or
endothelial cells. Approximately 15.5 6 5.6% of the CAFs were
positive for a-SMA, with no differences discerned between CAFs
and NAFs (Supporting Information Figure S2).
Proliferation rate of fibroblasts
To evaluate the proliferation rate of both fibroblasts, cells were
plated on 96 wells plates and treated with sodium tetrazolium
solution as described earlier. Supporting Information Figure S3
shows that both fibroblasts presents similar proliferation curves
(p 5 0.559) after 5 days of evaluation.
Effects of coculture of tumor-associated fibroblasts on the
expression profile of MDA-MB231 and MCF10A
We first analyzed the influence of tumor-associated fibroblasts
from different donors (n 5 4) on the expression profile of the
mammary epithelial cell lines, these analysis were assessed by
ANOVA test (2 3 2). Comparing MCF10A cocultured with CAF,
MCF10A in monoculture, MDA-MB231 cocultured with CAF,
and MDA-MB231 cultured alone, we found 307 genes that were
differentially expressed. Hierarchical clustering of these genes
distinguished two groups: MCF10A and MCF10A cocultured with
CAF clustered together on one branch, and MDA-MB231 and
MDA-MB231 cocultured with CAF clustered together on the
other branch (Fig. 2a).
Applying the Tukey test, 160 genes were differentially
expressed between MDA-MB231 cells cocultured with CAF and
MDA-MB231 monocultures, and 178 genes had their expression
levels altered in MCF10A cocultured with CAF when compared
with MCF10A monocultures. Genes selected by the ANOVA test
were considered differentially expressed when presenting at least
TABLE II – PRIMER SEQUENCES FOR QUANTITATIVE GENE EXPRESSION ANALYSIS
Target Primer Sequence (50
–30
) Product (bp)
Actin b ACTB forward AGAAATCTGGCACCAACC 188
ACTB reverse AGAGGCGTACAGGGATAGCA
A disintegrin and metalloproteinase domain 12 ADAM12 forward AAAAAGGTGTCGGCTTCTCA 112
ADAM12 reverse CCAGAACAACTCGGCTCACT
Arsenate resistance protein ARS2 ARS2 forward TCCATGAGGGACAGGAAGAC 119
ARS2 reverse GAGGCAACAGATGCAGGATT
BMP and activin membrane-bound inhibitor BAMBI forward CTAGAGAAGCAGGCGCTGAG 157
BAMBI reverse ATCGCCACTCCAGCTACATC
S100 calcium binding protein A9 S100A9 forward TCTTTTCGCACCAGCTCTTT 125
S100A9 reverse CAGCTGAGCTTCGAGGAGTT
Cbp/p300-interacting transactivator, with
Glu/Asp-rich carboxy-terminal domain, 2
CITED2 forward ATCCGGCATGTAGTGGTTGT 592
CITED2 reverse GTCCCCTCTATGTGCTGCTG
CCCTC-binding factor (zinc finger protein) CTCF forward TGCACCTGTATTCTGGTCTTCA 157
CTCF reverse TGCCGTAGAAATTGAACCTG
Connective tissue growth factor CTGF forward GTAATGGCAGGCACAGGTCT 211
CTGF reverse CCGTACTCCCAAAATCTCCA
DEAD (Asp-Glu-Ala-Asp) box polypeptide 21 DDX21 forward CCTTCCAGTTCTGGTTGCTC 105
DDX21 reverse TTCCAAAGTGAAGGGAATGG
Dicer 1, ribonuclease type III DICER1 forward CTCTGACCTTCCCGTCGTAA 160
DICER1 reverse CTGGAGACAGTCTGGCAGGT
FOS-like antigen 2 FOSL2 forward GGGAGCTGACAGAGAAGCTG 124
FOSL2 reverse TGAGCCACCAACATGAACTC
Heat shock protein 90kDa beta (Grp94), member 1 HSP90B1 forward AGAAAGAATGCTTCGCCTCA 238
HSP90B1 reverse ACATTCCCTCTCCACACAGG2
Interleukin 1, beta IL1B forward GCTGGAGAGTGTAGATCCCAAA 101
IL1B reverse CAGACTCAAATTCCAGCTTGTT
Lipocalin 2 LCN2 forward TACACTGGTCGATTGGGACA 104
LCN2 reverse CAAGGAGCTGACTTCGGAAC
Procollagen-lysine 1,2-dioxygenase-1 PLOD1 forward GCTCGGATGGAACAGTTGTAG 106
PLOD1 reverse ACCATGATGCCTCCACCTT
Solute carrier family 22, member 18 SLC22A18 forward CCACCACGATGAAGACCAG 130
SLC22A18 reverse GCTGGCTACCTCATGTCCTT
Cycling conditions: initial activation, 95o
C for 5 min; template activation for 40 cycles with denaturation at 95°C for 1 min, primer annealing
at Tm for 1 min, and extension at 72°C for 1 min. Melting curve analysis: after 40 cycles at 72°C for 15 s and increase in temperature up to 99°C
with a heating rate of 1°C/s and continuous fluorescence measurement. All Tms were established at 60°C, except for ARS2, BAMBI and
SLC22A18 primers.
2770 ROZENCHAN ET AL.

5. 2-fold difference in signal intensity. A total of 35 upregulated and
55 downregulated genes in MDA-MB231 cocultured with CAF
were selected. In MCF10A cocultured with CAF after a 2-fold
cut-off, we found more genes upregulated (n 5 77) and less genes
downregulated (n 5 21).
Effects of coculture of normal fibroblasts on the expression
profile of MDA-MB231 and MCF10A
In MDA-MB231/NAF versus MDA-MB231 and MCF10A/
NAF versus MCF10A, 248 differentially expressed genes found
by ANOVA (2 3 2) were clustered (Fig. 2b) and sorted into two
branches, one branch with MDA-MB231 alone and after coculture
with NAF (n 5 4), and another branch with MCF10A cells and
MCF10A after coculture with NAF. MDA-MB231/NAF presented
115 genes whose expression levels were altered. After applying
the 2-fold change cut-off, 29 genes were upregulated and 50 were
downregulated. By a similar criterion in the MCF10A/NAF
coculture only 48 upregulated and 33 downregulated genes were
retained, from a total of 161 genes.
Functions regulated by fibroblasts in the epithelial cells
Independently of which fibroblast was used in coculture we
could verify a number of overlapping genes modulated in each
epithelial cell as seen in the Venn diagram (Fig. 3) and Supporting
Information Tables. In MDA-MB231 when these overlapping
genes (n 5 49, 61% downregulated) were sorted by GOTM tool,
(biological process) and genes associated to motility (F11R,
TGFb2, SPINT2, LCN2, CD97, NRP1, p 5 5.89 e24
) were statisti-
cally hyper-represented. MCF10A exposed to NAF or CAF also
revealed shared genes commonly altered relative to control (n 5
40, 27% were downregulated). Neurogenesis (RTN1, MTPN, p 5
8.46 e23
) and hypoxic conditions (AQP3, LDHA, NDRG1,
LOXL3) were also biological process evidenced by GOTM,
whereas just the first group was hyper-represented. Such genes
corresponded to proteins associated to cellular or nuclear-mem-
brane. To select which genes were specifically influenced by each
fibroblast in each epithelial cell, we decided to exclude these
common genes from the next analysis.
After applying GOTM analyses, to the set of genes exclusively
modulated by CAF in MDA-MB231 (n 5 41) those genes
involved in biological processes such as intracellular transport
(KDELR3, TRAPPC1, NAPA, NUP50, TSPO, p 5 3.69 e23
) were
hyper-represented. Using KEGG, MAPK, WNT and Toll like
receptor signaling pathways were hyper-represented in the list of
genes specifically altered by CAFs (PTK2B, MAP2K3, PPM1B,
MYC, CHD8, ILb, p 0.001). We also noted a downregulation of
several genes related to proliferation (MYC, IL1b, PTK2B,
CDCP1) and upregulation of genes associated to cell survival
(DDX21, DICER, EPB41L4A) when compared with MDA-
MB231 monoculture.
Among the genes uniquely modulated by normal fibroblasts in
MDA-MB231 (n 5 30), the major biological process significantly
over represented using GOTM was biopolymer glycosylation
(UGCGL2, GCNT1 and ALG9), (p 5 6.6 e23
). It is interesting to
note that using KEGG pathway the smallest p value encountered
(0.0008) refers to the glycerolipid metabolism pathway. Of partic-
ular interest, among the most highly downregulated genes were
AGTPAT4 and ACSL5, associated to lipid metabolism.
After subtraction of the common effects induced by NAF or
CAF, we noted transcripts (n 5 57) which were specifically
altered in MCF-10A in coculture with CAF compared with mono-
culture conditions. Applying GOTM analysis, over represented
genes could be generally assigned to response to stress (S100A9,
CaLR, B4GALT1, HSP90B1, SPRR3, ERCC5, EGFR, LIG3, p 5
9.43 e23
). An upregulation of several genes associated to cancer
related pathways in the literature (KLK2, EGFR, HSP90B1,
EFNB2, MAPRE-2, CMIP (c-maf), S100A9) was observed. Indeed
for HSP90B1 (GPR94) we have noted an induction of its mRNA
after treatment of MCF10A with thapsigargin (data not shown).
After cocultivation with NAF (n 5 40) most of the genes
specifically differentially expressed in MCF-10A coded for
nuclear proteins and the process of transcription initiation
(DHX35, EIF5B, GTF2E2, MBOAT2, TAF12) was over repre-
sented (p 5 3.42 e23
).
Effects of coculture of MCF10A on the genomic profile
of fibroblasts
Our next step was to evaluate gene expression specifically in
fibroblasts (NAF or CAF) growing in coculture with normal breast
cells (MCF10A) when compared with those from fibroblast mono-
cultures. Cluster analysis indicated that CAF monocultures clus-
tered separately in 1 group whereas normal fibroblasts cocultured
or not and tumoral fibroblasts after coculture with MCF10A were
allocated to the same branch (Fig. 2c). Nevertheless, we have
identified genes that were differentially expressed between pre
and post tumor-associated fibroblasts with MCF10A. Fifty-eight
genes were specifically and significantly differentially expressed
in cocultivated CAFs when compared with CAF monocultures but
considering a 2-fold cut-off, this number decreased to 34 and gene
ontology using GOTM, showed an over representation of genes
involved with regulation of cell cycle (NFYC, CDKN1B, CCT2,
p 5 9.53 e23
), protein amino acid glycosylation (GCNT1 and
ALG8, p 5 4.4 e23
) and MAPKKK cascade such as RGS3
(GTPase which inhibits G-protein mediated signal) and FGFR1
(fibroblast growth factor receptor, p 5 8.34 e23
). There was rela-
tively little change in the gene expression profile of NAF grown
alone or in coculture with MCF10A, just 7 genes were identified
showing a 2-fold change. Of note, however, is the enhanced
expression of CBX2, a chromobox homolog.
Effects of coculture with MDA-MB231 on genomic
profile of fibroblasts
Subsequently, we aimed to identify genes in CAF and NAF that
were affected by coculture with MDA-MB231. Clustering based
on 42 genes differentially expressed in CAFs or NAFs following
coculture with MDA-MB231 does not clearly segregate fibroblasts
into different groups that correlate with particular aspects
(Fig. 2d). Among differentially expressed genes in CAFs (n 5 23),
following the 2-fold cut-off, 4 were over-expressed and 19 were
under-expressed. Ontology analyses identified genes associated to
cell cycle including TACC1 and CDKN1B genes, or to protein
transport (TIMM17A) or classified under the category of integral to
membrane (BAMBI). The influence of MDA-MB231 cells on NAF
resulted in downregulation of 8 of 9 differentially expressed genes
(89%). Genes with decreased expression as determined by gene
ontology analysis were TSPAN5 and PLOD whereas TACC2 was
upregulated. CTGF was the only common modulated gene by
MDA-MB231 cells on both fibroblasts. The category of regulation
of cell control was over represented using GOTM (p 5 9.08 e23
),
and the CTGF gene was included in this biological process.
Quantitative real-time PCR validation
To validate our gene expression data obtained by cDNA micro-
array, we have chosen 15 genes and their expression values were
compared with values obtained by quantitative RT-PCR. Besides
the 4 cases used in the array experiments, we also have included
more 2 cases of CAF and NAF to be cocultured that were not used
in the initial microarray studies.
In MDA-MB231/CAF versus MDA comparison, we selected
the following genes: FOSL2, IL1B, LCN2 and SLC22A18, which
were downregulated in MDA-MB231 after coculture with CAF,
the genes DDX21, DICER and CTCF were upregulated in those
epithelial cells after cocultivation.
Both genes ARS2 and CITED2 were altered in MDA-MB231 af-
ter coculture with NAF cells, being the first one upregulated
whereas the second had its expression levels downregulated.
CTGF was downregulated in both CAF and NAF cocultured
with MDA-MB231 as well as, BAMBI and PLOD1 were also
2771COCULTURE INDUCED CHANGES IN EXPRESSION PROFILES

6. FIGURE 2.
2772 ROZENCHAN ET AL.

7. decreased in CAF and NAF respectively after coculture with
MDA-MB231 cells. In addition, ADAM12, HSP90B1 and S100A9
were upregulated in MCF10A after cocultivation with CAF.
For all genes evaluated, we obtained good concordance (86.6%)
between microarray and real-time PCR analysis, except for
FOSL2 and CTCF genes (Fig. 4).
To confirm the altered gene expression in fibroblasts in their
respective tissue samples, we evaluated the 2 genes already vali-
dated by real time in CAF after coculture with MDA-MB231, that
is, BAMBI and CTGF, in stromal tissue obtained from invasive
ductal carcinoma samples and the normal counterpart tissue. For
BAMBI, we have validated both array and real time from coculture
experiments data, for 3 of 4 matched samples. On the other hand,
CTGF presented an over expression in stromal near tumoral tissue
when compared with stromal adjacent peritumoral normal tissue
in all cases analyzed.
Discussion
We used a transwell system allowing diffusible factors
exchange and microarray technology to analyze the gene expres-
sion changes resulting from cocultivation of 2 basal breast carci-
noma cell-lines, MCF10A and MDA-MB231 with mammary
fibroblasts of 2 different origins: from within breast tumors (CAF)
or from breast benign disease (NAF). After pair-wise comparisons
between epithelial cells and fibroblasts, reciprocal inductive inter-
actions were observed but the most consistent gene expression
changes occurred in the epithelial cells, although these changes
were small when compared with the distinct genomic profiles
exhibited by these cells in monoculture.
Each epithelial cell showed overlapped genes in response to
cocultivation with both fibroblast types. As normal fibroblasts
when cultured in vitro should be considered as permanently acti-
vated,26
it is possible that such cells may be competent to exert
similar effects as those described for CAFs.
After removal of genes commonly altered by NAF or CAF,
among the genes exclusively modulated by CAF in MDA-MB231
cells, transport was the most represented, including genes coding
for proteins important for the specificity of vectorial transport
between ER and Golgi or to prevent secretion of ER-resident pro-
teins such as an ER DEL receptor (KDELR3), TRAPPC1, NAPA
or coding for calcium translocation protein (TSPO) that were
downregulated. Decreased expression of those genes may lead to
an altered vesicular addressing of secretory proteins, possibly
affecting polarity and apical-basal organization. Lebret et al.22
suggested that some of the key effects of CAFs on breast epithelial
cells were on motility, cell organization and epithelial mesenchy-
mal transition (EMT) markers expression. Disruption of basal
polarity by inclusion of CAFs in a model of 3-dimensional hetero-
typic culture system was recently described.46
We also noted that some genes associated to proliferation were
selectively downregulated in MDA-MB231 cocultivated with
CAF (MYC, IL1B, RHOV) whereas other specific genes were upre-
gulated including genes that have already been previously
reported as associated to alternative pathways leading to survival
such as DDX21 (dead/H box helicase 21), associated to poor prog-
nosis,47
DICER, an essential component of the RNAi pathway,
required for the maintenance of hypermethylation of selected
epigenetically silenced loci in cancer cells48
and EPB41L4A
(NBL4), an important component of the b-catenin/TCF pathway
probably related to proliferation and cell polarity.49
Approximately 70% of the genes uniquely modulated by normal
fibroblasts in MDA-MB231, were downregulated and this set was
found to contain an over representation of genes involved in gly-
can structure biosynthesis and glycerolipid metabolism. Some of
these genes coded for glycosyl transferases that play important
FIGURE 3 – Venn Diagram with genes differentially expressed
between MDA-MB231/NAF and MDA-MB231/CAF and MCF10A/
NAF and MCF10A/CAF. (a) Thirty genes were exclusively differen-
tially expressed in MDA-MB231/NAF whereas 41 genes were exclu-
sively altered by CAF influence on MDA-MB231 genomic profile.
Common differentially expressed genes (49) represent almost 29% of
the total number of genes. (b) Forty-one genes appeared to be com-
monly differentially expressed when MCF10A was cocultured with ei-
ther NAF or CAF (42%). Forty genes were exclusively modulated by
NAF whereas 57 genes were specifically altered by CAF influence on
MCF10A genomic profile. In parenthesis are the total number of genes
found in each situation regulated at least by 2-fold and p 0.05.
FIGURE 2 – Hierarchical clustering after ANOVA test. Color intensity is scaled within each row so that the highest expression value
corresponds to bright red and the lowest to bright green. The support scale is a guarantee of reliability of dendrograms. (a) Hierarchical cluster-
ing was generated for genes differentially expressed in MCF10A cocultured with CAF, MCF10A alone, MDA-MB231 cocultured with CAF,
and MDA-MB231 monocultures. MCF10A and MCF10A after coculture with CAF clustered on one branch and MDA-MB231 cocultured with
CAF clustered with MDA-MB231 monocultures on another branch. (b) Cluster analysis of differentially expressed genes in MDA-MB231 and
MCF10A after coculture with NAF and both breast epithelial cell lines grown alone. NAF exerted influence on genomic profile of epithelial cells
but this effect could not cluster MCF10A after coculture in the same branch with MDA-MB231 cells. (c) Effects of coculture with MCF10A on
the expression profile of fibroblasts. In the cluster analysis of CAF and NAF in monoculture and after coculture with MCF10A cells, we
observed that the differentially expressed genes allocate the tumoral fibroblasts cocultured with MCF10A in the same branch as normal
fibroblasts cocultured with MCF10A cells. (d) Influence of MDA-MB231 cells on the expression profile of fibroblasts. CAF cocultured with
MDA-MB231 cells clustered on the same branch as NAF. In the figure, we are showing a partial view of the genes differentially expressed, see
Supporting Information Data for the complete list of altered genes.
2773COCULTURE INDUCED CHANGES IN EXPRESSION PROFILES

8. roles in post-translational glycosylation of glycolipids in the ER,
that are one of an ubiquitous membrane component and also
included genes coding for proteins associated to translocation of
misfolded glycoproteins across the ER membrane (UGCGL2,
ALG9 and GCNT1), or proteins interfering with calcium transport
(GPR35) or implicated in ER-stress induced cell death (ERGIC3).
Decreased levels of glycosil transferases may lead to protein
underglycosylation and further degradation in the proteasomes.50
We also noted that the most downregulated gene was ACSL5
coding for an acyl-CoA synthetase that converts fatty acids to
acyl-COA long chain, and another gene with decreased levels was
AGTPAT4 (lysophosphatic acid acyltransferase), indicating a pos-
sible reduction in the fatty acid levels that are essential for breast
cancer survival under stress conditions.51
Especially, the downre-
gulation of CITED-2 (CBP/p300-interacting transactivator with
glutamine acid/aspartic acid-rich C-terminal domain-2) which is
highly expressed in MDA-MB231 is interesting because its down-
regulation attenuated the expression of MMP9 which could affect
tumor cell invasion.52
These findings suggested that exposure of
MDA-MB231 to NAFs resulted mainly in the repression of lypo-
genic enzymes and impaired glycosylation possibly affecting
membrane biogenesis and viability.
Coculture of MCF10A with normal or tumor-associated fibro-
blasts showed both specific and common effects. Particularly,
among the latter, we found that MCF10A gene expression profile
was enriched with many genes that have been associated to
hypoxic conditions such as LOXL3, AQP3, NDRG1, LDHA and
ERRFI1. Although the biological mechanism underlying this cell
type response to both fibroblasts is presently unclear, it could
reflect small variations in oxygen tension caused by cell density
(although it was maintained below 1.38 3 104
cells/cm2
in our
experiments) or result from a specific composition of hypoxia reg-
ulators in MCF10A.53
Genes specifically downregulated in
MCF10A instructed by NAFs encoded several nuclear proteins
implicated in initiation of transcription and translation and RNA
processing functions. In addition, DDIT4 (REDD1) that inhibits
mTOR function to control cell growth and other genes implicated
in adhesion and tight junctions CTNND1 (catenin delta 1),
PCDH1 (cadherin like protein-1), INADL, ITGA5 were upregu-
lated indicating a role of normal fibroblasts in maintaining func-
tions related to differentiation and control of cell proliferation.
Tumor affiliated breast fibroblasts in turn, elicited in MCF10A
an over representation of genes coding for stress responsive pro-
teins including upregulation of S100A9 (stress regulated protein
FIGURE 4 – Validation of cDNA microarray data by real-time RT-PCR. cDNAs from breast cell lines (MDA-MB231 and MCF10A) and fibro-
blasts from adjacent fibroadenoma tissues (NAF) or tumor-associated breast (CAF) were used for the RT-PCR reaction. The relative expression
was determined after b-actin normalization; the relative expression determined by RT-PCR was compared with the cDNA microarray ratios for
each of the following comparisons: (a) MDA/CAF versus MDA, (b) MDA/NAF versus MDA, (c) CAF/MDA versus CAF, (d) NAF/MDA
versus NAF and (e) MCF10A/CAF versus MCF10A. The positive and negative values indicated up- and down-expressed genes, respectively.
Dark gray represents array data.
2774 ROZENCHAN ET AL.

9. belonging to the S100 family of small calcium binding protein),54
implicated in breast tumorigenesis in other studies, EGFR that in-
dependent of its kinase activity maintains the basal intracellular
glucose level preventing cell from undergoing autophagic death,55
calcium dependent molecular chaperones such as HSP90B1
(GPR94) that confers resistance to apoptosis and calreticulin with
stabilize protein folding intermediates and SPRR3, a cellular adap-
tator to biochemical stress.56
The induction of several stress re-
sponsive proteins may represent a prosurvival effect following ex-
posure to stress. Several stress proteins have been reported as fre-
quently overexpressed in studies with breast tumors cells.57
Two
of those genes (S100A9 and HSP90B1) were validated in our real-
time experiments and the latter was induced in MCF10A cells af-
ter treatment with Thapsigargin a drug known by its stress effect.
We also noted the upregulation of others genes showing high
magnitude of change including genes involved in breast tumori-
genesis such as KLK2 (kallikrein 2), a predictive marker of breast
cancer,58
ADAM12 that emerges as an important regulator of
breast tumor progression59
and MAPRE-2 which shows homology
to the APC binding EB1 gene and might active b-catenin path-
way.60
Upregulation of CMTM4 (CKLFSF4) that belongs to the
chemokine-like factor gene superfamily and of CMIP (c-maf), a
transcription factor belonging to the AP1 superfamily, are particu-
larly interesting due to recognized function of as chemokines
mediators of tumor-stroma interactions.8,9,61
Although we have not provided complete evidence of the malig-
nant transformation of MCF10A epithelial cells by soluble factors
released by CAFs, the gene pattern observed, suggested that
MCF10A over express some features associated to cancer cells. We
have no clear evidence that exposure to CAFs turns MCF-10A into
a malignant one but we showed that genes coding for several stress
proteins which may increase survival were induced in MCF-10A
triggered by CAFs. All together, these results suggested that normal
cells may acquire some of the characteristics of transformed cells
in the presence of the appropriate environmental stimuli.
One important issue is how normal stromal cells that coexist
with tumor-associated fibroblasts are affected by interactions with
malignant cells. When we focused on the genomic profile of
NAFs after coculture, we observed that they seem to have a mod-
est response to MDA-MB231 and presented a reduced expression
of 3 targets of the TGFb family: CTGF (connective tissue growth
factor), a member of the CCN growth factors family that promotes
fibroblast proliferation and enhanced migratory behavior,62
PLOD2 (procollagen lysine), a profibrotic signaling protein63
and
TPM2 (tropomyosin 2), that is required for TGFb regulation of
stress fibers and motility.64
We also noted the downregulation of
TSPAN5, a transmembrane 4 superfamily member that play a role
in the regulation of mobility. Therefore, we may speculate that
cultured fibroblasts from nonmalignant tumors (NAF) respond to
epithelial malignant cells by decreasing genes associated to motil-
ity and this alteration may serve to immobilize fibroblasts in close
contact with tumor cells, a suggestion previously raised by Ron-
nov-Jensen et al. and Valenti et al.65,66
Downregulation of genes
regulated by TGFb1 has also been observed in normal pulmonary
fibroblasts after coculture with cancer cells.36
In the CAF gene
profile, coculture with MDA-MB231 led to a reduced expression
of TGFb1 3 targets: CTGF, CDKN1B (p27KIP1) which mediates
TGFb1 induced growth arrest and BAMBI, a negative regulator of
feedback loop in TGFb1 signaling,67
suggesting that the response
observed in these cocultures might result from an attenuated
TGFb1 effect. Besides alterations of TGFb1 signaling, it may be
that cultured fibroblasts lack the capacity to transform the latent
form of TGFb1 in the biologically active counterpart as previ-
ously proposed.66
TGFb1 expression was previously reported as
downregulated in breast cancer derived fibroblasts and the authors
suggested that diminished levels of this cytokine may reflect a
stromal mechanism to favor adjacent tumor growth.15
In both
fibroblast types, MDA-MB231 induced an upregulation of genes
coding for members of the TACC family of centrosome and
microtubule interacting proteins that were implicated in fibroblast
transformation68
supporting the notion that both fibroblast types
respond to the presence of cancer cells maintaining a microenvir-
onment favorable for the malignant cells lodging.
Of interest is our observation that the nontumorigenic MCF10A
induces in CAF genes coding for proteins implicated in control-
ling cell growth that may reflect changes in the status of cell pro-
liferation. Gene transcripts altered in CAF included RPS6KA3
(p90 ribosomal S6 Kinase), FGFR1, NRD1 (nardilysin that enhan-
ces shedding of EGF), CDKN1B and NFY. Notably, we also iden-
tified an increased expression of PTGES2, a known inflammatory
gene.69
On the other hand, the gene expression pattern of the
cocultured normal fibroblasts with MCF10A was only modestly
affected and the most upregulated gene was CBX2, a polycomb
homolog, repressor of proto-oncogenes.70
Taken together, our data indicate that the coculture of breast
fibroblasts and normal or invasive breast carcinoma basal cells
exert reciprocal effects on gene expression profile but epithelial
cells seem to be more responsive by altering a larger number of
genes when compared with a more modest effect on the fibro-
blasts. It is possible that the fibroblasts being already activated in
culture are less responsive to factors released by epithelial cells, or
might require direct intercellular communication to be modified
by epithelial cells.
As breast cancer is clinically and molecularly heterogeneous,
we focused on interactions between breast stromal fibroblasts and
well-characterized normal or invasive breast basal cells in this
work. We may expect that coculture with mammary cells of the
luminal type or fibroblasts of different origins results in different
reciprocal gene expression alterations. These results were con-
firmed by RT-PCR with the same patients used in microarray anal-
ysis and also by inclusion of another 2 different donors of each
NAF and CAF. Besides, we evidenced BAMBI, as a good candi-
date for further investigations regarding interactions of malignant
breast epithelial cells with fibroblasts because this gene was also
downregulated in the stromal tissue of 3 patients with invasive
breast carcinoma confirming the previous data of our coculture
model obtained with cDNA microarray and real-time analysis.
Our results should therefore help to better understand some of
the molecular mechanisms involved in the complex heterotypic
signaling between epithelial cells and fibroblasts.
Acknowledgements
The authors thank Dr. W. P. R. Teodoro (Laboratorio de Matriz
Extracelular/Disciplina de Reumatologia) for her assistance with
imunofluorescence assays, Ms. T. L. Lourdes for technical support
and Ms. M. J. Gonc¸alves Benevides for secretary assistance.
References
1. Park CC, Bissell MJ, Barcellos-Hoff MH. The influence of the micro-
environment on the malignant phenotype. Mol Med Today 2000;6:
324–9.
2. Elenbaas B, Weinberg RA. Heterotypic signaling between epithelial
tumor cells and fibroblasts in carcinoma formation. Exp Cell Res
2001;264:169–84.
3. Kunz-Schughart LA, Knuechel R. Tumor-associated fibroblasts
(part I): active stromal participants in tumor development and
progression? Histol Histopathol 2002;17:599–621.
4. Wiseman BS, Werb Z. Stromal effects on mammary gland develop-
ment and breast cancer. Science 2002;296:1046–9.
5. Mueller MM, Fusenig NE. Friends or foes—bipolar effects of the
tumour stroma in cancer. Nat Rev Cancer 2004;4:839–49.
6. Kalluri R, Zeisberg M. Fibroblasts in cancer. Nat Rev Cancer 2006;6:
392–401.
7. Kunz-Schughart LA, Knuechel R. Tumor-associated fibroblasts
(part II): functional impact on tumor tissue. Histol Histopathol 2002;
17:623–37.
2775COCULTURE INDUCED CHANGES IN EXPRESSION PROFILES

10. 8. Allinen M, Beroukhim R, Cai L, Brennan C, Lahti-Domenici J,
Huang H, Porter D, Hu M, Chin L, Richardson A, Schnitt S, Sellers
WR, et al. Molecular characterization of the tumor microenvironment
in breast cancer. Cancer Cell 2004;6:17–32.
9. Orimo A, Gupta PB, Sgroi DC, Arenzana-Seisdedos F, Delaunay T,
Naeem R, Carey VJ, Richardson AL, Weinberg RA. Stromal
fibroblasts present in invasive human breast carcinomas promote
tumor growth and angiogenesis through elevated SDF-1/CXCL12
secretion. Cell 2005;121:335–48.
10. Singer CF, Gschwantler-Kaulich D, Fink-Retter A, Haas C, Hudelist
G, Czerwenka K, Kubista E. Differential gene expression profile in
breast cancer-derived stromal fibroblasts. Breast Cancer Res Treat
2008;110:273–81.
11. Hawsawi NM, Ghebeh H, Hendrayani SF, Tulbah A, Al-Eid M,
Al-Tweigeri T, Ajarim D, Alaiya A, Dermime S, Aboussekhra A.
Breast carcinoma-associated fibroblasts and their counterparts display
neoplastic-specific changes. Cancer Res 2008;68:2717–25.
12. Casey T, Bond J, Tighe S, Hunter T, Lintault L, Patel O, Eneman J,
Crocker A, White J, Tessitore J, Stanley M, Harlow S, et al. Molecu-
lar signatures suggest a major role for stromal cells in development of
invasive breast cancer. Breast Cancer Res Treat 2009;114:47–62.
13. Trimis G, Chatzistamou I, Politi K, Kiaris H, Papavassiliou AG.
Expression of p21waf1/Cip1 in stromal fibroblasts of primary breast
tumors. Hum Mol Genet 2008;17:3596–600.
14. Moinfar F, Man YG, Arnould L, Bratthauer GL, Ratschek M,
Tavassoli FA. Concurrent and independent genetic alterations in the
stromal and epithelial cells of mammary carcinoma: implications for
tumorigenesis. Cancer Res 2000;60:2562–6.
15. Kurose K, Hoshaw-Woodard S, Adeyinka A, Lemeshow S, Watson
PH, Eng C. Genetic model of multi-step breast carcinogenesis involv-
ing the epithelium and stroma: clues to tumour-microenvironment
interactions. Hum Mol Genet 2001;10:1907–13.
16. Kurose K, Gilley K, Matsumoto S, Watson PH, Zhou XP, Eng C.
Frequent somatic mutations in PTEN and TP53 are mutually exclu-
sive in the stroma of breast carcinomas. Nat Genet 2002;32:355–7.
17. Fukino K, Shen L, Matsumoto S, Morrison CD, Mutter GL, Eng C.
Combined total genome loss of heterozygosity scan of breast cancer
stroma and epithelium reveals multiplicity of stromal targets. Cancer
Res 2004;64:7231–6.
18. Hu M, Yao J, Cai L, Bachman KE, van den Bruˆle F, Velculescu V,
Polyak K. Distinct epigenetic changes in the stromal cells of breast
cancers. Nat Genet 2005;37:899–905.
19. Patocs A, Zhang L, Xu Y, Weber F, Caldes T, Mutter GL, Platzer P,
Eng C. Breast-cancer stromal cells with TP53 mutations and nodal
metastases. N Engl J Med 2007;357:2543–51.
20. Bhowmick NA, Neilson EG, Moses HL. Stromal fibroblasts in cancer
initiation and progression. Nature 2004;432:332–7.
21. Kleer CG, Bloushtain-Qimron N, Chen YH, Carrasco D, Hu M, Yao
J, Kraeft SK, Collins LC, Sabel MS, Argani P, Gelman R, Schnitt SJ,
et al. Epithelial and stromal cathepsin K and CXCL14 expression in
breast tumor progression. Clin Cancer Res 2008;14:5357–67.
22. Lebret SC, Newgreen DF, Thompson EW, Ackland ML. Induction of
epithelial to mesenchymal transition in PMC42-LA human breast car-
cinoma cells by carcinoma-associated fibroblast secreted factors.
Breast Cancer Res 2007;9:R19.
23. Holliday DL, Hughes S, Shaw JA, Walker RA, Jones JL. Intrinsic
genetic characteristics determine tumor-modifying capacity of fibro-
blasts: matrix metalloproteinase-3 5A/5A genotype enhances breast
cancer cell invasion. Breast Cancer Res 2007;9:R67.
24. Lin HJ, Zuo T, Lin CH, Kuo CT, Liyanarachchi S, Sun S, Shen R,
Deatherage DE, Potter D, Asamoto L, Lin S, Yan PS, et al. Breast
cancer-associated fibroblasts confer AKT1-mediated epigenetic silenc-
ing of Cystatin M in epithelial cells. Cancer Res 2008;68:10257–66.
25. Studebaker AW, Storci G, Werbeck JL, Sansone P, Sasser AK,
Tavolari S, Huang T, Chan MW, Marini FC, Rosol TJ, Bonafe M,
Hall BM. Fibroblasts isolated from common sites of breast cancer
metastasis enhance cancer cell growth rates and invasiveness in an
interleukin-6-dependent manner. Cancer Res 2008;68:9087–95.
26. Brouty-Boye D, Pottin-Clemenceau C, Doucet C, Jasmin C, Azzarone
B. Chemokines and CD40 expression in human fibroblasts. Eur J
Immunol 2000;30:914–9.
27. van Roozendaal KE, Klijn JG, van Ooijen B, Claassen C, Eggermont
AM, Henzen-Logmans SC, Foekens JA. Differential regulation of
breast tumor cell proliferation by stromal fibroblasts of various breast
tissue sources. Int J Cancer 1996;65:120–5.
28. Dong-Le Bourhis X, Berthois Y, Millot G, Degeorges A, Sylvi M,
Martin PM, Calvo F. Effect of stromal and epithelial cells derived
from normal and tumorous breast tissue on the proliferation of human
breast cancer cell lines in co-culture. Int J Cancer 1997;71:42–8.
29. Shekhar MP, Werdell J, Santner SJ, Pauley RJ, Tait L. Breast stroma
plays a dominant regulatory role in breast epithelial growth and
differentiation: implications for tumor development and progression.
Cancer Res 2001;61:1320–6.
30. Sadlonova A, Novak Z, Johnson MR, Bowe DB, Gault SR, Page GP,
Thottassery JV, Welch DR, Frost AR. Breast fibroblasts modulate
epithelial cell proliferation in three-dimensional in vitro co-culture.
Breast Cancer Res 2005;7:R46–59.
31. Samoszuk M, Tan J, Chorn G. Clonogenic growth of human breast
cancer cells co-cultured in direct contact with serum-activated fibro-
blasts. Breast Cancer Res 2005;7:R274–83.
32. Brouty-Boye D, Mainguene C, Magnien V, Israel L, Beaupain R.
Fibroblast-mediated differentiation in human breast carcinoma cells
(MCF-7) grown as nodules in vitro. Int J Cancer 1994;56:731–5.
33. Sadlonova A, Mukherjee S, Bowe DB, Gault SR, Dumas NA, Van
Tine BA, Frolova N, Page GP, Welch DR, Novak L, Frost AR.
Human breast fibroblasts inhibit growth of the MCF10AT xenograft
model of proliferative breast disease. Am J Pathol 2007;170:1064–76.
34. Karnoub AE, Dash AB, Vo AP, Sullivan A, Brooks MW, Bell GW,
Richardson AL, Polyak K, Tubo R, Weinberg RA. Mesenchymal
stem cells within tumour stroma promote breast cancer metastasis.
Nature 2007;449:557–63.
35. Finak G, Bertos N, Pepin F, Sadekova S, Souleimanova M, Zhao H,
Chen H, Omeroglu G, Meterissian S, Omeroglu A, Hallett M, Park M.
Stromal gene expression predicts clinical outcome in breast cancer.
Nat Med 2008;14:518–27.
36. Montel V, Mose ES, Tarin D. Tumor-stromal interactions reciprocally
modulate gene expression patterns during carcinogenesis and metasta-
sis. Int J Cancer 2006;119:251–63.
37. Gallagher PG, Bao Y, Prorock A, Zigrino P, Nischt R, Politi V,
Mauch C, Dragulev B, Fox JW. Gene expression profiling reveals
cross-talk between melanoma and fibroblasts: implications for host-
tumor interactions in metastasis. Cancer Res 2005;65:4134–46.
38. Sato N, Maehara N, Goggins M. Gene expression profiling of tumor-
stromal interactions between pancreatic cancer cells and stromal fibro-
blasts. Cancer Res 2004;64:6950–56.
39. Fromigue O, Louis K, Dayem M, Milanini J, Pages G, Tartare-Deck-
ert S, Ponzio G, Hofman P, Barbry P, Auberger P, Mari B. Gene
expression profiling of normal human pulmonary fibroblasts following
coculture with non-small-cell lung cancer cells reveals alterations
related to matrix degradation, angiogenesis, cell growth and survival.
Oncogene 2003;22:8487–97.
40. Buess M, Nuyten DS, Hastie T, Nielsen T, Pesich R, Brown PO. Char-
acterization of heterotypic interaction effects in vitro to deconvolute
global gene expression profiles in cancer. Genome Biol 2007;8:R191.
41. Charafe-Jauffret E, Ginestier C, Monville F, Finetti P, Adelay¨de J,
Cervera N, Fekairi S, Xerri L, Jacquemier J, Birnbaum D, Bertucci F.
Gene expression profiling of breast cell lines identifies potential new
basal markers. Oncogene 2006;25:2273–84.
42. Soule HD, Maloney TM, Wolman SR, Peterson WD, Jr, Brenz R,
McGrath CM, Russo J, Pauley RJ, Jones RF, Brooks SC. Isolation
and characterization of a spontaneously immortalized human breast
epithelial cell line. MCF-10. Cancer Res 1990;50:6075–86.
43. Brentani RR, Carraro DM, Verjovski-Almeida S, Reis EM, Neves EJ,
de Souza SJ, Carvalho AF, Brentani H, Reis LF. Gene expression
arrays in cancer research: methods and applications. Crit Rev Oncol
Hematol 2005;54:95–105.
44. Folgueira MA, Carraro DM, Brentani H, Patr~ao DF, Barbosa EM,
Netto MM, Caldeira JR, Katayama ML, Soares FA, Oliveira CT,
Reis LF, Kaiano JH, et al. Gene expression profile associated with
response to doxorubicin-based therapy in breast cancer. Clin Cancer
Res 2005;11:7434–43.
45. Zhang B, Schmoyer D, Kirov S, Snoddy J. GOTree Machine
(GOTM): a web-based platform for interpreting sets of interesting
genes using Gene Ontology hierarchies. BMC Bioinformatics
2004;5:16.
46. Holliday DL, Brouilette KT, Markert A, Gordon LA, Jones JL. Novel
multicellular organotypic models of normal and malignant breast:
tools for dissecting the role of the microenvironment in breast cancer
progression. Breast Cancer Res 2009;11:R3.
47. Cimino D, Fuso L, Sfiligoi C, Biglia N, Ponzone R, Maggiorotto F,
Russo G, Cicatiello L, Weisz A, Taverna D, Sismondi P, De Bortoli
M. Identification of new genes associated with breast cancer progres-
sion by gene expression analysis of predefined sets of neoplastic tis-
sues. Int J Cancer 2008;123:1327–38.
48. Chiosea S, Jelezcova E, Chandran U, Acquafondata M, McHale T,
Sobol RW, Dhir R. Up-regulation of dicer, a component of the
MicroRNA machinery, in prostate adenocarcinoma. Am J Pathol
2006;169:1812–20.
49. Ishiguro H, Furukawa Y, Daigo Y, Miyoshi Y, Nagasawa Y,
Nishiwaki T, Kawasoe T, Fujita M, Satoh S, Miwa N, Fujii Y,
Nakamura Y. Isolation and characterization of human NBL4, a gene
involved in the beta-catenin/tcf signaling pathway. Jpn J Cancer Res
2000;91:597–603.
50. Parodi AJ. Role of N-oligosaccharide endoplasmic reticulum process-
ing reactions in glycoprotein folding and degradation. Biochem J
2000;348:1–13.
2776 ROZENCHAN ET AL.

11. 51. Mashima T, Sato S, Sugimoto Y, Tsuruo T, Seimiya H. Promotion of
glioma cell survival by acyl-CoA synthetase 5 under extracellular
acidosis conditions. Oncogene 2009;28:9–19.
52. Chou YT, Yang YC. Post-transcriptional control of Cited2 by trans-
forming growth factor beta. Regulation via Smads and Cited2 coding
region. J Biol Chem 2006;281:18451–62.
53. Chi JT, Wang Z, Nuyten DS, Rodriguez EH, Schaner ME, Salim A,
Wang Y, Kristensen GB, Helland A, Børresen-Dale AL, Giaccia A,
Longaker MT, et al. Gene expression programs in response to
hypoxia: cell type specificity and prognostic significance in human
cancers. PLoS Med 2006;3:e47.
54. Cross SS, Hamdy FC, Deloulme JC, Rehman I. Expression of
S100 proteins in normal human tissues and common cancers using
tissue microarrays: S100A6. S100A8, S100A9 and S100A11 are
all overexpressed in common cancers. Histopathology 2005;46:
256–69.
55. Weihua Z, Tsan R, Huang WC, Wu Q, Chiu CH, Fidler IJ, Hung MC.
Survival of cancer cells is maintained by EGFR independent of its
kinase activity. Cancer Cell 2008;13:385–93.
56. Breckenridge DG, Germain M, Mathai JP, Nguyen M, Shore GC.
Regulation of apoptosis by endoplasmic reticulum pathways.
Oncogene 2003;22:8608–18.
57. Wang J, Hua H, Ran Y, Zhang H, Liu W, Yang Z, Jiang Y. Derlin-1
is overexpressed in human breast carcinoma and protects cancer cells
from endoplasmic reticulum stress-induced apoptosis. Breast Cancer
Res 2008;10:R7.
58. Paliouras M, Borgono C, Diamandis EP. Human tissue kallikreins:
the cancer biomarker family. Cancer Lett 2007;249:61–79.
59. Kveiborg M, Fr€ohlich C, Albrechtsen R, Tischler V, Dietrich N,
Holck P, Kronqvist P, Rank F, Mercurio AM, Wewer UM. A role for
ADAM12 in breast tumor progression and stromal cell apoptosis.
Cancer Res 2005;65:4754–61.
60. Su LK, Qi Y. Characterization of human MAPRE genes and their pro-
teins. Genomics 2001;71:142–9.
61. Eyche`ne A, Rocques N, Pouponnot C. A new MAFia in cancer. Nat
Rev Cancer 2008;8:683–93.
62. Chen PS, Wang MY, Wu SN, Su JL, Hong CC, Chuang SE, Chen
MW, Hua KT, Wu YL, Cha ST, Babu MS, Chen CN, et al. CTGF
enhances the motility of breast cancer cells via an integrin-alphav-
beta3-ERK1/2-dependent S100A4-upregulated pathway. J Cell Sci
2007;120:2053–65.
63. van der Slot AJ, Zuurmond AM, Bardoel AF, Wijmenga C, Pruijs
HE, Sillence DO, Brinckmann J, Abraham DJ, Black CM, Verzijl N,
DeGroot J, Hanemaaijer R, et al. Identification of PLOD2 as telopep-
tide lysyl hydroxylase, an important enzyme in fibrosis. J Biol Chem
2003;278:40967–72.
64. Zheng Q, Safina A, Bakin AV. Role of high-molecular weight tropo-
myosins in TGF-beta-mediated control of cell motility. Int J Cancer
2008;122:78–90.
65. Rønnov-Jessen L, Van Deurs B, Nielsen M, Petersen OW. Identifica-
tion, paracrine generation, and possible function of human breast car-
cinoma myofibroblasts in culture. In Vitro Cell Dev Biol 1992;28:
273–83.
66. Valenti MT, Sartore S, Azzarello G, Balducci E, Amadio M, Sandri
M, Pappagallo GL, Tacchetti G, Bari M, Manconi R, D’Andrea MR,
Silvestri B, et al. Human fibroblasts from normal and malignant
breast tissue grown in vitro show a distinct senescence profile and
telomerase activity. Histochem J 2002;34:403–10.
67. Sekiya T, Oda T, Matsuura K, Akiyama T. Transcriptional regulation
of the TGF-beta pseudoreceptor BAMBI by TGF-beta signaling.
Biochem Biophys Res Commun 2004;320:680–4.
68. Cully M, Shiu J, Piekorz RP, Muller WJ, Done SJ, Mak TW. Trans-
forming acidic coiled coil 1 promotes transformation and mammary
tumorigenesis. Cancer Res 2005;65:10363–70.
69. Larkins TL, Nowell M, Singh S, Sanford GL. Inhibition of cyclooxy-
genase-2 decreases breast cancer cell motility, invasion and matrix
metalloproteinase expression. BMC Cancer 2006;6:181.
70. Satijn DP, Olson DJ, van der Vlag J, Hamer KM, Lambrechts C,
Masselink H, Gunster MJ, Sewalt RG, van Driel R, Otte AP. Interfer-
ence with the expression of a novel human polycomb protein, hPc2,
results in cellular transformation and apoptosis. Mol Cell Biol 1997;
17:6076–86.
2777COCULTURE INDUCED CHANGES IN EXPRESSION PROFILES