Gene expression profiling of the tumor microenvironment during breast cancer progression

bcr2222 BCJ Research article Gene expression profiling of the tumor microenvironment during breast cancer progression Ma Xiao-Jun xma@aviaradx.com Dahiya Sonika drsonikadahiya@yahoo.co.in Richardson Elizabeth ERICHARDSON1@PARTNERS.ORG Erlander Mark Mark.Erlander@biotheranostics.com Sgroi C Dennis dsgroi@partners.org

bioTheranostics, Inc., 11025 Roselle Street, Suite 200, San Diego, CA 92121, USA

Molecular Pathology Unit and Center for Cancer Research, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA

Breast Cancer Research 1465-5411 2009 11 1 R7 http://breast-cancer-research.com/content/11/1/R7 See related editorial by Schedin and Borges, http://breast-cancer-research.com/content/11/2/102 19187537 10.1186/bcr2222 3 6 2008 14 7 2008 16 1 2009 2 2 2009 2 2 2009 2009 Ma et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Introduction

The importance of the tumor microenvironment in breast cancer has been increasingly recognized. Critical molecular changes in the tumor stroma accompanying cancer progression, however, remain largely unknown. We conducted a comparative analysis of global gene expression changes in the stromal and epithelial compartments during breast cancer progression from normal to preinvasive to invasive ductal carcinoma.

Methods

We combined laser capture microdissection and gene expression microarrays to analyze 14 patient-matched normal epithelium, normal stroma, tumor epithelium and tumor-associated stroma specimens. Differential gene expression and gene ontology analyses were performed.

Results

Tumor-associated stroma undergoes extensive gene expression changes during cancer progression, to a similar extent as that seen in the malignant epithelium. Highly upregulated genes in the tumor-associated stroma include constituents of the extracellular matrix and matrix metalloproteases, and cell-cycle-related genes. Decreased expression of cytoplasmic ribosomal proteins and increased expression of mitochondrial ribosomal proteins were observed in both the tumor epithelium and the stroma. The transition from preinvasive to invasive growth was accompanied by increased expression of several matrix metalloproteases (MMP2, MMP11 and MMP14). Furthermore, as observed in malignant epithelium, a gene expression signature of histological tumor grade also exists in the stroma, with high-grade tumors associated with increased expression of genes involved in immune response.

Conclusions

Our results suggest that the tumor microenvironment participates in tumorigenesis even before tumor cells invade into stroma, and that it may play important roles in the transition from preinvasive to invasive growth. The immune cells in the tumor stroma may be exploited by the malignant epithelial cells in high-grade tumors for aggressive invasive growth.

Introduction

The tumor microenvironment or the stroma hosting the malignant breast epithelial cells is comprised of multiple cell types, including fibroblasts, myoepithelial cells, endothelial cells and various immune cells 1234. One prevailing view is that tumor-associated stroma is activated by the malignant epithelial cells to foster tumor growth – for example, by secreting growth factors, increasing angiogenesis, and facilitating cell migration, ultimately resulting in metastasis to remote organ sites 3. For example, two chemokines (chemokine (C-X-C motif) ligand (CXCL) 12 and CXCL14) that bind to tumor epithelial cells to promote proliferation, migration and invasion have recently been shown to be overexpressed by the activated tumor fibroblasts and myoepithelial cells 567. Genes involved in tumor-microenvironment interactions may therefore provide novel targets for diagnostic development and therapeutic intervention. Our understanding of the interactions between epithelial and stromal components of breast cancer, however, remains limited at the molecular level. Using the serial analysis of gene expression technique, Allinen and coworkers performed the first systematic profiling of the various stromal cell types isolated via cell-type-specific cell surface markers and magnetic beads 7. They demonstrated gene expression alterations in all cell types within the tumor microenvironment accompanying progression from normal breast tissue to ductal carcinoma in situ (DCIS) to invasive ducal carcinoma (IDC) 8, providing evidence that these cell types all participate in tumorigenesis.

Using laser capture microdissection (LCM), we previously performed gene expression analysis of the epithelial compartment of the malignant lesions during breast cancer progression. We discovered that most of the gene expression changes take place prior to local invasion (even in atypical ductal hyperplasia) and that there are no major changes in gene expression accompanying the in situ to invasive growth transition 9. In the present article we extend this analysis to the tumor stromal microenvironment and demonstrate that, like the tumor epithelium, the tumor stromal microenvironment undergoes extensive gene expression alterations even at the preinvasive stage of DCIS, supporting the view that cell-cell communication via paracrine mechanisms between the two compartments plays an important role in tumor progression.

Materials and methods

Clinical specimen

All breast cancer specimens were fresh-frozen biopsies obtained from the Massachusetts General Hospital between 1998 and 2001. The diagnostic criteria and tumor grading were described previously 9. Patient and tumor characteristics of the 14 tumor specimens in this study are presented in Table 1. Patients were selected in which patient-matched normal and tumor samples were available and the normal breast lobules did not show fibrocystic change. The research was deemed exempt from informed consent as the samples are unidentifiable to the research team. The study was approved by the Massachusetts General Hospital human research committee in accordance with National Institutes of Health human research study guidelines.

Table 1

Patient and tumor characteristics of samples in the study

Patient number

Age (years)

Grade

Estrogen receptor

Progesterone receptor

Her-2

Size

Nodal status

Tumor type

III

Positive

Negative

Ductal

Positive

Negative

N/A

Negative

Ductal

Positive

Negative

2.1

Positive

Ductal

III

Negative

3.7

Negative

Ductal

102

Positive

Negative

5.2

Positive

Ductal

121

Positive

1.5

Positive

Ductal

131

Positive

1.5

Positive

Ductal

133

III

Negative

Positive

1.5

Positive

Ductal

148

Positive

Negative

1.9

Positive

Ductal

153

Positive

N/A

Positive

Ductal

169

Positive

Negative

2.6

Positive

Ductal

178

III

Positive

2.8

Positive

Ductal

179

III

Negative

Positive

1.5

Positive

Ductal

180

Positive

Negative

1.9

Positive

Ductal

ND, not determined; N/A, not available.

Laser capture microdissection, RNA extraction and microarray analysis

Highly enriched populations of patient-matched normal or malignant epithelial cells and of normal stroma or tumor-associated stroma from the different stages of breast cancer progression were procured by LCM using a PixCell IIe system (Molecular Devices, Mountain View, CA, USA) as previously described 9. Enrichment for cells of interest was verified by microscopic examination of the LCM cap after microdissection. The microdissected normal stromal compartment consisted of the intralobular, rather than the extralobular, stromal compartment of normal breast tissue that was a minimum 0.3 cm from any premalignant or malignant lesion (Figure 1). The DCIS-associated stroma (DCIS-S) consisted of a 25 μm rim of cells that surrounded the DCIS; for cases in which synchronous DCIS and IDC were present, the DCIS-S was obtained from areas of DCIS that were at least 0.3 cm from the invasive component. The IDC-associated stroma (IDC-S) consists of stromal cells predominantly within the invasive tumor mass.

Figure 1

Laser capture microdissection experimental design

Laser capture microdissection experimental design. Example of the tumor microenvironment compartments targeted by laser capture microdissection: epithelial (white asterisk) and stromal (black outlined areas with black asterisk) compartments of the normal terminal ductal lobular unit, of ductal carcinoma in situ (DCIS) and of invasive ductal carcinoma (IDC).

Total RNA was isolated from captured cells using the Picopure™ RNA isolation kit (Molecular Devices), amplified by T7 RNA amplification (RiboAmp™; Molecular Devices), labeled and hybridized to the whole genome array U133X3P (3'-biased design) according to the manufacturer's instructions (Affymetrix, Santa Clara, CA, USA). The hybridized microarrays were then washed, stained and scanned as per the manufacturer's protocols (Affymetrix).

Data analysis

Raw data from the U133X3P arrays were processed using the Bioconductor rma package with default parameters for background correction, quantile normalization and signal summation 1011. Differential gene expression analyses were performed using linear regression models in the limma package 12. For comparing normal and tumor samples, we used the patient identification as a blocking variable. For tumor grade comparison, we used the tumor stage (in situ or invasive) as the blocking variable. Statistical significance was corrected for multiple testing using the Benjamini-Hochberg procedure 13. All procedures were performed in the R statistical environment 14. For gene ontology analysis, ranked gene lists were first generated according to the moderated t statistics from linear models and then examined for enriched ontology terms using the Gene Set Enrichment Analysis software 15. The data discussed in this publication have been deposited in the NCBI Gene Expression Omnibus 16 and are accessible [GEO:GSE14548] 17.

Quantitative real-time PCR and immunohistochemistry

TaqMan™ real-time PCR was performed on amplified RNA used for microarray analysis as previously described 9. Briefly, amplified RNA was converted to double-stranded cDNA, and the cDNA was quantitated with PicoGreen (Molecular Probes, Eugene, OR, USA) using a spectrofluorometer (Molecular Devices). Each gene was analyzed in triplicate in a 96-well plate using ABI 7900 HT (Applied Biosystems, Foster City, CA., USA).

For each gene, the sequences of the PCR primer pairs and the fluorogenic MGB or TAMRA probe (5' to 3'), respectively, are as follows: ESR1, ATGATCAACTGGGCGAAGA, GGTGGACCTGATCATGGA and VIC-TGCCAGGCTTTGTGGA; RRM2, CCTTTAACCAGCACAGCCAGTT, TTATTTGTTTGTAAAGTGCCAGGTTT and VIC-TGCAGCCTCACTGCTTCAACGCA-TAMRA; gremlin 1 (GREM1), ACGGCAAAGAATTATATAGACTATGAGGTA, TTTTATGAGACTATCAACTCCCCTTTC and VIC-CTTGCTGTGTAGGAGGA; and WNT inhibitory factor 1(WIF1), CACTGTGGTAGTGGCATTTAAACAATA, GCCAATGCAAAAAGTTCATACATT and VIC-TTCTAAACACAATGAAATAGGGA.

Estrogen receptor and progesterone receptor immunohistochemistry staining was performed as previously described, using the rabbit monoclonal antibody (SP1) from Lab Vision (Fremont, CA, USA) for the estrogen receptor (1:50 dilution) and using the mouse monoclonal antibody (PgR 636) from Dako (Carpinteria, CA, USA) for the progesterone receptor (1:50 dilution) 18.

Results

Experimental design

The present study included 14 patients with primary ductal breast cancer (Table 1). These patients were primarily estrogen receptor positive (78.6%), lymph node positive (78.6%), and premenopausal (mean age 41 years). We used LCM to isolate the epithelial and stroma compartments separately from each of the 14 fresh-frozen biopsies. In the epithelial compartment, we captured normal and malignant epithelium from DCIS and/or IDC. In the stromal compartment, we captured normal stroma at least 3 mm from the malignant lesion and the DCIS-S and/or IDC-S whenever possible. An example of the microdissected compartments is shown in Figure 1. As shown in Table 2, in the epithelial compartment four cases had all three stages (normal breast epithelium, DCIS, and IDC) available, five cases had normal breast epithelium and IDC only, and five cases had normal breast epithelium and DCIS only; in the stroma, six cases had all three stages available, five cases had normal stromal compartment and DCIS-S, and three cases had the normal stromal compartment and IDC-S. RNA was isolated from the captured cells and interrogated with the Affymetrix whole-genome array U133X3P.

Table 2

Laser capture microdissection of 14 primary breast cancer patients

Tumor

Stroma

Patient

Normal

In situ

Invasive

Normal

In situ

Invasive

102

121

131

133

148

153

169

178

179

180

x, component captured.

Gene expression changes in the stromal and epithelial compartments during breast cancer progression

We compared the gene expression patterns of the tumor epithelium and stroma at each stage of progression (DCIS or IDC) with their respective normal state using the limma (linear models of microarrays) software package 12. The resulting P values for differential gene expression in each pair-wise comparison were adjusted for multiple testing 13, and the genes with a significant adjusted P value (P <0.05) were extracted.

The DCIS and IDC stages were each associated with thousands of gene expression alterations relative to their respective normal state in both the tumor epithelium and the stroma (Figure 2). Furthermore, within each compartment, the expression patterns of DCIS-associated and IDC-associated genes were highly similar to each other (Figure 3).

Figure 2

Comparative analysis of gene expression changes in tumor and stroma

Comparative analysis of gene expression changes in tumor and stroma. Gene expression changes in normal breast epithelium (N), ductal carcinoma in situ (DCIS), invasive ductal carcinoma (IDC), normal stromal compartment (N-S), ductal carcinoma in situ-associated stroma (DCIS-S) and invasive ductal carcinoma-associated stroma (IDC-S). ↑, upregulated genes; ↓, downregulated genes.

Figure 3

Heatmap of expression patterns of ductal carcinoma in situ-associated and invasive ductal carcinoma-associated genes

Heatmap of expression patterns of ductal carcinoma in situ-associated and invasive ductal carcinoma-associated genes. (a) Heatmap of 849 genes with >3-fold differential expression in either ductal carcinoma in situ (DCIS) versus normal breast or invasive ductal carcinoma (IDC) versus normal breast in the epithelium. (b) Heatmap of 557 genes with >3-fold differential expression in either ductal carcinoma in situ-associated stroma (DCIS-S) versus normal stromal compartment or invasive ductal carcinoma-associated stroma (IDC-S) versus normal stromal compartment. Data shown are log₂(fold change) relative to the average expression in normal controls (normal breast epithelium or normal stromal compartment). In each heatmap, genes (rows) are hierarchically clustered using 1 – Pearson correlation as the distance metric. IS, ductal carcinoma in situ; INV, invasive ductal carcinoma; ISS, ductal carcinoma in situ-associated stroma; INVS, invasive ductal carcinoma-associated stroma.

To gain an overview of the biological processes in which these differentially expressed genes are involved, we performed gene set enrichment analysis 19 using the gene ontology database 20. Table 3 presents the top 20 gene ontology terms significantly enriched within genes upregulated in the invasive stage in the epithelium and the stroma. In the epithelium, the genes were dominated by those associated with the cell cycle (mitosis in particular). In the stroma, the genes prominently featured the components of the extracellular matrix and the matrix metalloproteases responsible for remodeling the extracellular matrix. Additionally, the stromal genes also included those related to the cell cycle, indicating increased proliferation as a common feature in both the tumor epithelium and the stroma.

Table 3

Top 20 gene ontology terms enriched in tumor epithelium and stroma

Name

Size (number of genes)

Normalized enrichment score

False discovery rate q value

Epithelium

SPINDLE

2.33

CHROMOSOME_SEGREGATION

2.15

CELL_CYCLE_PROCESS

180

2.12

MICROTUBULE_CYTOSKELETON_ORGANIZATION_AND_BIOGENESIS

2.11

CHROMOSOME__PERICENTRIC_REGION

2.11

MICROTUBULE_CYTOSKELETON

142

2.11

PROTEASOME_COMPLEX

2.09

1.40 × 10^-4

CONDENSED_CHROMOSOME

2.06

2.48 × 10^-4

M_PHASE

105

2.06

2.20 × 10^-4

NUCLEAR_ENVELOPE

2.05

1.98 × 10^-4

CELL_CYCLE_PHASE

157

2.05

1.80 × 10^-4

M_PHASE_OF_MITOTIC_CELL_CYCLE

2.04

2.49 × 10^-4

CHROMOSOME

115

2.03

2.30 × 10^-4

CYTOSKELETAL_PART

221

2.03

2.14 × 10^-4

MITOSIS

2.02

2.66 × 10^-4

MICROTUBULE

1.99

2.49 × 10^-4

MITOTIC_CELL_CYCLE

139

1.99

2.35 × 10^-4

CELL_CYCLE_CHECKPOINT_GO_0000075

1.98

2.21 × 10^-4

SPINDLE_MICROTUBULE

1.97

2.63 × 10^-4

DNA_REPAIR

120

1.94

6.01 × 10^-4

STRUCTURAL_CONSTITUENT_OF_RIBOSOME

-3.09

Stroma

EXTRACELLULAR_MATRIX_STRUCTURAL_CONSTITUENT

2.12

COLLAGEN

2.07

0.001566

METALLOENDOPEPTIDASE_ACTIVITY

2.06

0.001044

EXTRACELLULAR_MATRIX

1.99

0.001568

PROTEINACEOUS_EXTRACELLULAR_MATRIX

1.97

0.002923

EXTRACELLULAR_MATRIX_PART

1.91

0.007826

SPINDLE

1.89

0.008346

METALLOPEPTIDASE_ACTIVITY

1.82

0.027006

SKELETAL_DEVELOPMENT

1.80

0.032482

STRUCTURAL_CONSTITUENT_OF_RIBOSOME

-3.04

In both compartments, the single gene ontology term STRUCTURAL_CONSTITUENT_OF_RIBOSOME was significantly enriched within the downregulated genes (Table 3). To examine this further, we extracted all ribosomal protein-encoding genes that were differentially expressed between DCIS or IDC versus the normal breast in the epithelium and visualized their expression patterns in both compartments. Interestingly, there was an almost complete bipartite partitioning of these genes (Figure 4): while the downregulated genes were all those encoding for the cytoplasmic ribosomal proteins, the upregulated genes were mostly those encoding for the mitochondrial ribosomal proteins.

Figure 4

Heatmap of differential expression of ribosomal protein genes in the malignant epithelium and tumor stroma

Heatmap of differential expression of ribosomal protein genes in the malignant epithelium and tumor stroma. Differential expression of ribosomal protein genes in ductal carcinoma in situ (DCIS), invasive ductal carcinoma (IDC), ductal carcinoma in situ-associated stroma (DCIS-S) and invasive ductal carcinoma-associated stroma (IDC-S). Data shown are log₂(fold change) relative to the average expression level in the normal controls (normal breast epithelium or normal stromal compartment). Expression measurements for multiple probe sets representing the same gene were collapsed to the single representative probe set with the largest differential gene expression. All genes shown were significant at adjusted P < 0.05. IS, ductal carcinoma in situ; INV, invasive ductal carcinoma; ISS, ductal carcinoma in situ-associated stroma; INVS, invasive ductal carcinoma-associated stroma.

In addition to these global patterns, Tables 4 and 5 present the top 50 differentially expressed genes in the epithelium and the stroma, respectively. In these tables, besides the dominant features of cell-cycle-related genes in the epithelium and extracellular matrix genes in the stroma discussed earlier, we note several additional genes important in cell signaling pathways. Two antagonists of WNT receptor signaling, WIF1 and secreted frizzled-related protein 1 (SFRP1), were downregulated in both the tumor epithelium and the stroma. In addition, two members of the transforming growth factor beta superfamily, GREM1 and inhibin beta A (INHBA), showed markedly increased expression specifically in the tumor stroma (Table 5).

Table 4

Top 50 genes differentially expressed in tumor epithelium

Probe set

DICS

IDC

Gene description

g5174662_3p_at

5.3

4.0

S100P – S100 calcium binding protein P

g11993936_3p_s_at

4.5

3.4

CYB561 – cytochrome b-561

g7415720_3p_a_at

4.0

3.0

SCD – stearoyl-CoA desaturase (delta-9-desaturase)

Hs.75319.0.S3_3p_at

3.0

3.8

RRM2 – ribonucleotide reductase M2 polypeptide

Hs.106552.0.S3_3p_s_at

4.2

2.3

CNTNAP2 – contactin associated protein-like 2

g12803628_3p_at

3.7

2.6

HIST1H1C – histone cluster 1, H1c

g5031780_3p_at

4.0

2.3

IFI27 – interferon, alpha-inducible protein 27

Hs.180779.1.S1_3p_at

3.1

3.0

HIST1H2BD – histone cluster 1, H2bd

Hs.184572.0.S2_3p_at

2.7

3.3

CDC2 – cell division cycle 2, G1 to S and G2 to M

Hs.223025.0.S2_3p_a_at

2.6

3.4

RAB31 – RAB31, member RAS oncogene family

g12804874_3p_a_at

2.8

3.1

RRM2 – ribonucleotide reductase M2 polypeptide

Hs.239884.0.S1_3p_x_at

3.5

2.4

HIST1H2BC – histone cluster 1, H2bc

g7661973_3p_at

2.7

3.1

MELK – maternal embryonic leucine zipper kinase

g13259549_3p_at

3.2

2.4

IFI6 – interferon, alpha-inducible protein 6

g4504584_3p_at

3.5

2.0

IFIT1 – interferon-induced protein with tetratricopeptide repeats 1

Hs.155956.0.S1_3p_at

2.6

2.8

NAT1 – N-acetyltransferase 1 (arylamine N-acetyltransferase)

Hs.152677.0.S1_3p_at

3.1

2.3

DHRS2 – dehydrogenase/reductase (SDR family) member 2

Hs.239884.0.S1_3p_at

3.3

2.1

HIST1H2BC – histone cluster 1, H2bc

g5803130_3p_a_at

2.2

3.2

RAB31 – RAB31, member RAS oncogene family

g13699814_3p_s_at

2.7

CYP2B6 – cytochrome P450, family 2, subfamily B, polypeptide 6

g9963780_3p_a_at

2.2

3.2

RAB31 – RAB31, member RAS oncogene family

Hs.72472.0.A1_3p_at

2.3

2.9

g13477106_3p_s_at

3.3

1.8

CEACAM6 – carcinoembryonic antigen-related cell adhesion molecule 6 (nonspecific cross-reacting antigen)

Hs.133342.0.S1_3p_x_at

2.9

2.2

GPC1 – glypican 1

Hs.325335.1.S1_3p_at

2.6

2.5

CAPN13 – calpain 13

Hs.34853.0.S2_3p_at

-3.5

-4.0

ID4 – inhibitor of DNA binding 4, dominant negative helix-loop-helix protein

g3387766_3p_a_at

-3.9

-3.6

GPM6B – glycoprotein M6B

Hs.10587.0.S1_3p_at

-3.2

-4.3

DMN – desmuslin

Hs2.348883.1.S1_3p_s_at

-3.9

-3.6

FOXC1 – forkhead box C1

g4758521_3p_at

-4.9

-2.7

SPARCL1 – SPARC-like 1 (mast9, hevin)

g11037715_3p_x_at

-3.9

-3.7

ROPN1 – ropporin, rhophilin associated protein 1

g4504914_3p_at

-3.9

-3.8

KRT15 – keratin 15

Hs.82101.0.S3_3p_at

-3.7

-4.0

PHLDA1 – pleckstrin homology-like domain, family A, member 1

Hs.149356.0.S1_3p_at

-3.8

-3.9

LOC728264 – hypothetical protein LOC728264

g4506856_3p_s_at

-3.3

-4.6

CX3CL1 – chemokine (C-X3-C motif) ligand 1

g4506516_3p_at

-3.9

-4.1

RGS2 – regulator of G-protein signaling 2, 24 kDa

g7657105_3p_at

-4.2

-4.0

GABRP – gamma-aminobutyric acid (GABA) A receptor, pi

Hs.25956.0.S1_3p_at

-4.1

-4.4

SOSTDC1 – sclerostin domain containing 1

Hs.153961.2.S2_3p_at

-4.6

-3.9

BOC – Boc homolog (mouse)

g11991655_3p_at

-4.5

-4.2

C2orf40 – chromosome 2 open reading frame 40

Hs.288850.0.S1_3p_at

-4.1

-4.7

PHLDA1 – pleckstrin homology-like domain, family A, member 1

g7662650_3p_at

-5.1

-3.7

C13orf15 – chromosome 13 open reading frame 15

g4557694_3p_a_at

-4.5

KIT – v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog

Hs.127428.2.S2_3p_a_at

-4.3

-4.9

HOXA9 – homeobox A9

g6005949_3p_at

-4.4

-4.8

WIF1 – WNT inhibitory factor 1

Hs.34853.0.S3_3p_at

-4.8

-4.5

ID4 – inhibitor of DNA binding 4, dominant negative helix-loop-helix protein

g4559274_3p_a_at

-4.1

-5.3

ELF5 – E74-like factor 5 (ets domain transcription factor)

g8400731_3p_a_at

-4.4

-5.2

SFRP1 – secreted frizzled-related protein 1

g5032314_3p_a_at

-4.9

DMD – dystrophin (muscular dystrophy, Duchenne and Becker types)

g6005714_3p_at

-4.7

-5.6

SLC6A14 – solute carrier family 6 (amino acid transporter), member 14

Ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) data presented as log₂(fold changes) relative to normal epithelium.

Table 5

Top 50 genes differentially expressed in tumor-associated stroma

Probe set

DCIS

IDC

Gene description

Hs.179729.0.S1_3p_a_at

6.5

7.0

COL10A1 – collagen, type X, alpha 1(Schmid metaphyseal chondrodysplasia)

Hs.28792.0.S1_3p_at

5.9

6.0

4876385_3p_at

4.9

6.3

COL11A1 – collagen, type XI, alpha 1

g7019348_3p_at

4.9

5.7

GREM1 – gremlin 1, cysteine knot superfamily, homolog (Xenopus laevis)

Hs.179729.1.S1_3p_a_at

4.8

5.5

COL10A1 – collagen, type X, alpha 1(Schmid metaphyseal chondrodysplasia)

Hs.297939.3.S1_3p_at

4.6

5.1

FNDC1 – fibronectin type III domain containing 1

37892_3p_at

4.1

5.6

COL11A1 – collagen, type XI, alpha 1

Hs.41271.0.S1_3p_at

4.7

4.9

COL8A1 – collagen, type VIII, alpha 1

g4502938_3p_s_at

3.8

5.4

COL11A1 – collagen, type XI, alpha 1

g186414_3p_a_at

4.5

4.4

INHBA – inhibin, beta A

g8393842_3p_at

4.4

NOX4 – NADPH oxidase 4

Hs.288467.0.S1_3p_at

3.8

4.8

LRRC15 – leucine rich repeat containing 15

Hs.105700.0.S1_3p_a_at

4.1

4.2

SFRP4 – secreted frizzled-related protein 4

g4481752_3p_at

3.6

4.4

GJB2 – gap junction protein, beta 2, 26 kDa

g8923132_3p_at

3.6

4.3

ASPN – asporin

Hs.287820.2.A1_3p_s_at

3.8

4.1

FN1 – fibronectin 1

g8400733_3p_a_at

3.5

3.9

SFRP4 – secreted frizzled-related protein 4

g10863087_3p_a_at

3.4

3.9

GREM1 – gremlin 1, cysteine knot superfamily, homolog (Xenopus laevis)

g5174662_3p_at

3.4

S100P – S100 calcium binding protein P

Hs.283713.0.A1_3p_at

3.2

3.5

CTHRC1 – collagen triple helix repeat containing 1

g4502844_3p_at

3.1

3.5

CILP – cartilage intermediate layer protein, nucleotide pyrophosphohydrolase

Hs.76722.2.S1_3p_at

2.8

3.7

Hs.70823.0.S3_3p_at

3.3

3.2

SULF1 – sulfatase 1

g4505186_3p_at

3.3

3.0

CXCL9 – chemokine (C-X-C motif) ligand 9

Hs.101302.0.S2_3p_s_at

2.2

3.9

COL12A1 – collagen, type XII, alpha 1

g11415037_3p_at

-3.2

-3.0

SLC22A3 – solute carrier family 22 (extraneuronal monoamine transporter), member 3

Hs.325823.0.A1_3p_at

-2.7

-3.5

CD36 – CD36 molecule (thrombospondin receptor)

g4557418_3p_at

-2.7

-3.6

CD36 – CD36 molecule (thrombospondin receptor)

g4557544_3p_a_at

-2.9

-3.5

EDN3 – endothelin 3

Hs2.147313.1.S1_3p_s_at

-2.9

-3.5

CD300LG – CD300 molecule-like family member g

Hs.106283.4.S1_3p_at

-3.0

-3.4

KLHL13 – kelch-like 13 (Drosophila)

g8400731_3p_a_at

-2.6

-4.0

SFRP1 – secreted frizzled-related protein 1

Hs.250692.0.S4_3p_at

-3.0

-3.7

HLF – hepatic leukemia factor

g4826977_3p_at

-3.3

-3.5

RELN – reelin

Hs.76325.1.A1_3p_x_at

-3.0

-3.9

IGJ – immunoglobulin J polypeptide, linker protein for immunoglobulin alpha and mu polypeptides

Hs.76325.1.A1_3p_at

-3.1

-4.0

IGJ – immunoglobulin J polypeptide, linker protein for immunoglobulin alpha and mu polypeptides

g10835124_3p_a_at

-4.0

-3.1

DCX – doublecortex; lissencephaly, X-linked (doublecortin)

g7657105_3p_at

-3.2

-4.0

GABRP – gamma-aminobutyric acid A receptor, pi

g4506328_3p_at

-3.4

-3.9

PTPRZ1 – protein tyrosine phosphatase, receptor-type, Z polypeptide 1

g4758377_3p_at

-3.9

-3.4

FIGF – c-fos induced growth factor (vascular endothelial growth factor D)

g12707575_3p_at

-3.3

-4.1

OXTR – oxytocin receptor

g13518036_3p_a_at

-2.5

-4.9

MATN2 – matrilin 2

g4559274_3p_a_at

-3.9

-3.6

ELF5 – E74-like factor 5 (ets domain transcription factor)

Hs.10587.0.S1_3p_at

-2.5

-5.1

DMN – desmuslin

Hs.49696.0.A1_3p_at

-3.7

-4.0

SCARA5 – scavenger receptor class A, member 5 (putative)

g4557578_3p_at

-3.4

-4.4

FABP4 – fatty acid binding protein 4, adipocyte

g13186315_3p_a_at

-3.5

-4.3

CAPN6 – calpain 6

g11991655_3p_at

-3.2

-5.3

C2orf40 – chromosome 2 open reading frame 40

g562105_3p_a_at

-4.9

-4.5

DLK1 – delta-like 1 homolog (Drosophila)

g6005949_3p_at

-5.0

-4.8

WIF1 – WNT inhibitory factor 1

Ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) data presented as log₂(fold changes) relative to normal stroma.

Stromal gene expression signature associated with tumor invasion

We next compared the gene expression patterns associated with the DCIS to IDC transition within each compartment. In the tumor epithelium, there were only three genes (POSTN, periostin; SPARC, osteoconectin; SPARCL1, SPARC-like 1) that were significantly upregulated in IDC relative to DCIS. All three genes are known to be specifically expressed in the stroma 212223 and were indeed strongly expressed in the stroma samples in our dataset. Their apparent overexpression in IDC relative to DCIS might therefore be due to contaminating stromal cells in the procured epithelial cell populations in the IDC samples but not in DCIS samples. In the stroma, however, there were more significant changes in comparing IDC-S with DCIS-S, with 76 upregulated genes and 229 downregulated genes (Figure 2). The lack of significant changes in gene expression in the epithelium associated with the DCIS-IDC transition seen here was consistent with that in our previous study 9.

Table 6 presents the top 50 differentially expressed genes between DICS-S and IDC-S (see Additional data file 1). Among genes with increased expression in IDC-S, three matrix metalloproteases (MMP11, MMP2 and MMP14) were notable. In fact, one additional matrix metalloprotease (MMP13) had higher expression in IDC-S than in DCIS-S, with adjusted P = 0.06. These genes have been known to be involved in tumor invasion 3. On the other hand, genes with decreased expression in IDC-S included many genes involved in vasculature development (for example, EMCN, FLT1, KDR, SELE, MYH11, EDNRB and PODXL), a process expected to increase in invasive cancer. This paradoxical result might reflect the decreased vascular density in the leading invasive front where we microdissected the stroma relative to the stroma surrounding DCIS.

Additional file 1

An Excel file containing a table that lists the genes differentially expressed between DCIS-S and IDC-S.

Click here for file

Table 6

Top 50 genes differentially expressed in invasive stroma compared to in situ stroma

Probe set

Log₂ (fold change)

Adjusted P value

Gene description

Hs2.434299.1.S1_3p_at

1.61

8.58 × 10^-3

g13027795_3p_s_at

1.45

1.74 × 10^-2

MMP11 – matrix metallopeptidase 11 (stromelysin 3)

Hs.50081.1.S1_3p_a_at

1.36

5.47 × 10^-3

KIAA1199 – KIAA1199

g11641276_3p_s_at

1.24

3.71 × 10^-2

PDE4DIP – phosphodiesterase 4D interacting protein (myomegalin)

Hs.169517.0.S1_3p_a_at

1.16

5.72 × 10^-3

ALDH1B1 – aldehyde dehydrogenase 1 family, member B1

Hs.98523.0.A1_3p_at

1.13

5.32 × 10^-3

FAT3 – FAT tumor suppressor homolog 3 (Drosophila)

g10938018_3p_at

1.04

1.74 × 10^-2

EPYC – epiphycan

Hs2.350890.1.S1_3p_s_at

1.03

3.72 × 10^-2

GABRB2 – gamma-aminobutyric acid (GABA) A receptor, beta 2

g4507922_3p_at

0.98

1.70 × 10^-2

WISP2 – WNT1 inducible signaling pathway protein 2

g11342665_3p_at

0.98

4.53 × 10^-2

MMP2 – matrix metallopeptidase 2 (gelatinase A, 72kDa gelatinase, 72 kDa type IV collagenase)

g13124890_3p_a_at

0.93

3.28 × 10^-2

GALNT1 – UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylgalactosaminyltransferase 1 (GalNAc-T1)

Hs.98523.0.A1_3p_x_at

0.87

3.15 × 10^-2

FAT3 – FAT tumor suppressor homolog 3 (Drosophila)

Hs.238532.0.A1_3p_at

0.76

3.71 × 10^-2

GALNTL2 – UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylgalactosaminyltransferase-like 2

Hs.42927.0.S1_3p_at

0.75

3.39 × 10^-2

ANTXR1 – anthrax toxin receptor 1

Hs2.359399.1.S1_3p_at

0.74

3.71 × 10^-2

LOC285758 – hypothetical protein LOC285758

Hs.235795.0.A1_3p_at

0.74

1.38 × 10^-2

Hs2.46679.2.S1_3p_s_at

0.66

2.11 × 10^-3

g469044_3p_a_at

0.60

3.22 × 10^-2

CNTN1 – contactin 1

g4758607_3p_at

0.53

1.20 × 10^-2

Hs.288553.0.S1_3p_s_at

0.52

2.82 × 10^-2

200661_3p_at

0.51

4.16 × 10^-2

CTSA – cathepsin A

Hs.2399.1.S1_3p_s_at

0.51

4.48 × 10^-2

MMP14 – matrix metallopeptidase 14 (membrane-inserted)

Hs.98183.0.A1_3p_at

0.48

8.58 × 10^-3

RSPO4 – R-spondin family, member 4

208756_3p_at

0.48

2.28 × 10^-2

EIF3I – eukaryotic translation initiation factor 3, subunit I

Hs.162647.0.S1_3p_at

0.48

2.69 × 10^-2

DKFZP547L112 – hypothetical protein DKFZp547L112

Hs.22968.0.S1_3p_a_at

-2.00

8.37 × 10^-6

FLT1 – fms-related tyrosine kinase 1 (vascular endothelial growth factor/vascular permeability factor receptor)

g11545907_3p_at

-2.03

2.68 × 10^-5

ELTD1 – EGF, latrophilin and seven transmembrane domain containing 1

g5032094_3p_at

-2.03

3.64 × 10^-7

SLCO2A1 – solute carrier organic anion transporter family, member 2A1

Hs.8707.0.S1_3p_at

-2.07

1.29 × 10^-5

HECW2 – HECT, C2 and WW domain containing E3 ubiquitin protein ligase 2

Hs.134970.0.S1_3p_a_at

-2.07

6.66 × 10^-3

KIF26A – kinesin family member 26A

Hs2.420404.1.S1_3p_at

-2.08

7.70 × 10^-6

PELO – pelota homolog (Drosophila)

g4504850_3p_a_at

-2.11

3.62 × 10^-2

KCNK5 – potassium channel, subfamily K, member 5

Hs.288681.0.S1_3p_at

-2.13

4.98 × 10^-4

THSD7A – thrombospondin, type I, domain containing 7A

g4557546_3p_at

-2.15

1.58 × 10^-3

EDNRB – endothelin receptor type B

g11321596_3p_at

-2.19

1.64 × 10^-3

KDR – kinase insert domain receptor (a type III receptor tyrosine kinase)

Hs.124675.0.A1_3p_at

-2.21

2.21 × 10^-4

GIMAP7 – GTPase, IMAP family member 7

Hs.211388.0.S1_3p_at

-2.24

5.72 × 10^-3

RUNDC3B – RUN domain containing 3B

g4885556_3p_at

-2.25

2.13 × 10^-3

PODXL – podocalyxin-like

Hs.26530.0.S2_3p_at

-2.30

1.60 × 10^-3

SDPR – serum deprivation response (phosphatidylserine binding protein)

g13518036_3p_a_at

-2.41

7.19 × 10^-3

MATN2 – matrilin 2

Hs.102415.0.S1_3p_at

-2.43

2.67 × 10^-8

EMCN – endomucin

Hs.61935.0.S1_3p_at

-2.45

2.68 × 10^-5

PCDH17 – protocadherin 17

g8547214_3p_at

-2.46

3.74 × 10^-5

EMCN – endomucin

g4520327_3p_at

-2.48

2.67 × 10^-3

IL33 – interleukin 33

Hs.10587.0.S1_3p_at

-2.66

2.29 × 10^-3

DMN – desmuslin

g3644039_3p_a_at

-2.67

1.43 × 10^-2

TP63 – tumor protein p63

Hs.78344.1.S2_3p_a_at

-2.87

2.13 × 10^-3

MYH11 – myosin, heavy chain 11, smooth muscle

g6580814_3p_s_at

-2.93

8.90 × 10^-5

INMT – indolethylamine N-methyltransferase

Hs.173560.0.S1_3p_at

-2.94

3.58 × 10^-2

ODZ2 – odz, odd Oz/ten-m homolog 2 (Drosophila)

g4506870_3p_at

-3.23

1.80 × 10^-3

SELE – selectin E (endothelial adhesion molecule 1)

Stromal gene expression signature associated with tumor grade

We have previously shown that tumor grade is associated with a strong gene expression signature in malignant breast epithelial cells 9. We therefore examined whether a similar signature also exists in the tumor stroma. Comparing grade I (n = 8) and grade III (n = 7) tumor-associated stroma samples (DCIS-S and IDC-S), we identified 526 upregulated genes and 94 downregulated genes in grade III samples (Figure 5; see also Additional data file 2). The gene set enrichment analysis indicated that the tumor stroma in grade III tumors were associated with a strong immune response signature (interferon signaling, activation of leukocytes and T cells) and with increased mitotic activity (Table 7).

Additional file 2

An Excel file containing a table that lists the genes differentially expressed between grade III and grade I samples.

Click here for file

Table 7

Top 20 gene sets enriched in grade III-associated stroma

Name

Size (number of genes)

Normalized enrichment score

False discovery rate q value

CELLULAR_DEFENSE_RESPONSE

2.31

IMMUNE_RESPONSE

220

2.17

IMMUNE_SYSTEM_PROCESS

312

2.16

T_CELL_ACTIVATION

2.14

LEUKOCYTE_ACTIVATION

2.09

JAK_STAT_CASCADE

2.05

6.82 × 10^-4

LYMPHOCYTE_ACTIVATION

2.05

5.85 × 10^-4

CELL_ACTIVATION

2.04

5.12 × 10^-4

M_PHASE_OF_MITOTIC_CELL_CYCLE

2.04

4.55 × 10^-4

RESPONSE_TO_VIRUS

2.04

5.12 × 10^-4

SPINDLE

2.03

5.60 × 10^-4

MITOSIS

2.02

5.99 × 10^-4

INTERLEUKIN_RECEPTOR_ACTIVITY

2.01

6.33 × 10^-4

POSITIVE_REGULATION_OF_IMMUNE_RESPONSE

2.00

7.35 × 10^-4

REGULATION_OF_IMMUNE_SYSTEM_PROCESS

1.99

7.54 × 10^-4

POSITIVE_REGULATION_OF_IMMUNE_SYSTEM_PROCESS

1.99

7.07 × 10^-4

RESPONSE_TO_BIOTIC_STIMULUS

112

1.99

6.65 × 10^-4

REGULATION_OF_I_KAPPAB_KINASE_NF_KAPPAB_CASCADE

1.99

6.85 × 10^-4

MRNA_PROCESSING_GO_0006397

1.97

0.001135

RESPONSE_TO_OTHER_ORGANISM

1.96

0.001282

Figure 5

Heatmap of gene expression signature correlated with tumor grade in the stroma

Heatmap of gene expression signature correlated with tumor grade in the stroma. Comparison of grade III tumors with grade I tumors identified 526 upregulated genes and 94 downregulated genes in grade III stroma. Data shown are log₂(fold change) relative to the median expression level across all samples. Genes in rows were hierarchically clustered, and samples in columns were arranged by sample type. E, epithelium; S, stroma.

Validation of selected differentially expressed genes

We next used quantitative real-time PCR to validate selected genes differentially expressed in the various comparisons presented above. Quantitative real-time PCR analysis of the same samples as used in the microarray analysis confirmed the marked downregulation of WIF1 in both neoplastic epithelium and tumor stroma (Figure 6a) and the marked upregulation of GREM1 in both DCIS-associated and IDC-associated stroma (Figure 6b). In addition, two representative genes (ESR1, estrogen receptor alpha; and RRM2, ribonucleotide reductase M2 subunit) differentially expressed in the stroma between grade III and grade I tumors (see Additional data file 2) were also confirmed by quantitative real-time PCR. In both the epithelium and stroma, RRM2, a cell proliferation marker, was more highly expressed in grade III tumors (Figure 6c), whereas ESR1 was more highly expressed in grade I tumors (Figure 6d). Although expression of estrogen receptor alpha is thought to be restricted to the tumor epithelial cells in human breast cancer 24, we confirmed the low but detectable levels of estrogen receptor alpha expression in stromal fibroblasts by immunohistochemical staining (Figure 6e).

Figure 6

Validation of selected genes

Validation of selected genes. (a) to (d) Boxplots of relative gene expression by quantitative real-time PCR in ductal carcinoma in situ (DCIS), invasive ductal carcinoma (IDC), ductal carcinoma in situ-associated stroma (DCIS-S) and invasive ductal carcinoma-associated stroma (IDC-S). (a) and (b) Reference groups were the normal components (N, normal breast epithelium; N-S, normal stromal compartment). (c) and (d) Reference groups were grade I (EI, epithelium; SI, stroma). y axis, cycling threshold values relative to the median value for the entire series. Statistically significant differences by Wilcoxon rank sum test: *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.(e) Immunostaining of an estrogen-receptor-positive breast cancer. Arrows point to positive staining in stromal fibroblasts.

Discussion

Exploratory genome-wide analysis of the tumor microenvironment in breast cancer has been limited to date. Using serial analysis of gene expression coupled with antibody-based ex vivo tissue fractionation, Allinen and colleagues identified a limited set of 417 cell-type-specific genes among the most prominent cell types in breast cancer (epithelial, myoepithelial, and endothelial cells, fibroblasts, and leukocytes) 7. Finak and colleagues more recently obtained gene expression profiles of both epithelial and stromal compartments from the same tumor biopsy via LCM 25. These workers only analyzed the morphologically normal epithelium and normal stroma, however, leaving the gene expression changes in the tumor-activated stroma unexplored. Our work therefore provides the first comprehensive comparative analysis of in vivo gene expression changes in the tumor epithelium and its stromal microenvironment during breast cancer progression from normal to DCIS to IDC.

We observed extensive gene expression changes in the stroma associated with DCIS and IDC, suggesting that tumor-adjacent stroma coevolves with the tumor epithelium, even before tumor invasion occurs. These alterations included many components of the extracellular matrix and the extracellular-matrix-remodeling matrix metalloproteases. Increased mitotic gene expression occurred both in the malignant epithelium and adjacent stroma, which may reflect the often observed desmoplastic reaction around the tumor cells. Expression of cytoplasmic ribosomal proteins was generally decreased in both compartments during cancer progression. While this result may seem paradoxical in that increased protein synthesis is considered a hallmark of cancer, it is supported by several different lines of studies. First, decreased expression of many ribosomal proteins has also been observed in colorectal cancer compared with normal mucosal epithelium 26. Secondly, many ribosomal protein genes have been found to be haploinsufficient tumor suppressors in zebrafish 27. Thirdly, the oncogenic activity of c-Myc is inhibited by the ribosomal protein L11, and inactivation of the L11 gene by small interfering RNA increases c-Myc-induced transcription and cell proliferation 28.

The mechanism by which ribosomal proteins contribute to tumorigenesis is unknown. Decreased expression of ribosomal proteins in cancer may reflect a qualitative change in ribosomal structure, which may allow differential translation of gene products required for rapid tumor growth. Alternatively, it may reflect some unknown nonribosomal functions by these proteins. In contrast to the decreased expression of these cytoplasmic ribosomal protein genes, we observed increased expression of a number of mitochondrial ribosomal protein genes in both the tumor epithelium and the stroma. The human mitochondrial ribosomes are responsible for the production of several key proteins in bioenergetics including subunits of the ATP synthase. Given the importance of mitochondria in cancer 2930, our novel finding suggests that the mitochondrial ribosome may be a potential therapeutic target and thus warrants further study.

The top differentially expressed genes between tumor-associated stroma and the adjacent normal stroma included several signaling molecules known to be important for tumorigenesis. Two antagonists of WNT receptor signaling, WIF1 and SFRP1, were consistently downregulated both in the tumor epithelium and stroma. The WNT signaling pathway plays an important role in development and tissue homeostasis, and its aberrant activation by loss of expression WIF1 or SFRP1 has been shown to be an important early event in breast cancer progression 313233. Two transforming growth factor beta superfamily members (GREM1 and INHBA) are strongly induced in the tumor-associated stroma. GREM1 is a bone morphogenetic protein antagonist, and it is overexpressed in cancer-associated stromal cells in many solid tumors 34. It has been hypothesized that bone morphogenetic proteins and bone morphogenetic protein antagonists may play opposing roles in the maintenance of a niche of self-renewing stem cells, with bone morphogenetic protein antagonists such as GREM1 blocking cell differentiation 34. WNT3A was recently demonstrated in human fibroblasts to markedly increase the expression of GREM2, a close paralog of GREM1 – raising the possibility that the significant downregulation of WNT antagonists (WIF1 and SFRP1) and upregulation of GREM1 in the stroma 35 we observed here may be functionally linked.

INHBA is the gene for the beta A subunit of inhibin and activin, which are pleiotropic growth factors regulating the growth and differentiation of many cell types via autocrine and paracrine mechanisms 36. Although its role in breast cancer remains unclear, circulating levels of INHBA has been shown to be higher in breast cancer patients with bone metastasis 37. These signaling molecules could serve as key messengers between the tumor and its microenvironment, as shown for CXCL12 and CXCL14, which are overexpressed in tumor-associated myoepithelial cells and myofibroblasts 6738. We note that in our dataset, however, CXCL12 and CXCL14 were also expressed in normal stroma. This discrepancy could be due to the fact that Allinen and colleagues used purified stromal cell types 7 and we used the whole stroma compartment in our study.

A watershed event in breast cancer progression is the invasion of tumor cells into the stromal compartment. The only morphological diagnostic criterion distinguishing DCIS from IDC is the association of DCIS with a complete basement membrane. Understanding the molecular events that drive the DCIS-IDC transition has been of great interest. We have previously shown 9, and confirm in the present study, that the malignant epithelium of DCIS and IDC are very similar without significant differences at the transcriptome level. This conclusion is supported by the recent demonstration that MCFDCIS cells, a cell line model for DCIS, make the DCIS-IDC transition spontaneously without further molecular changes in the malignant epithelial cells themselves 39. Instead, this transition is driven by fibroblasts and blocked by myoepithelial cells.

In the present article we demonstrated that the stromal compartment is associated with a relatively small number of significant changes accompanying the DCIS-IDC transition. In particular, several matrix metalloproteases (MMP2, MMP11 and MMP14) showed significantly increased expression in IDC-associated stroma. MMP14, a membrane-type matrix metalloprotease, can activate MMP2 protease activity, which degrades type IV collagen, the major structural component of the basement membrane 4041. MMP11 has recently been shown to exhibit protease activity towards type VI collagen and to promote tumor progression 42. MMP11 has been shown to be differentially expressed in IDC relative to DCIS in two other studies. Schuetz and colleagues conducted a study similar to ours, using LCM and microarrays to profile the epithelium of patient-matched DCIS and IDC, and found MMP11 to be upregulated in IDC relative to DCIS 43. Their result differs from ours, however, in that we observed upregulation of MMP11 in the IDC-associated stroma but not in the epithelium. A stromal origin of MMP11 expression had been established previously 44. The result by Schuetz and coworkers might be due to contaminating nonepithelial cells in their LCM samples, a possibility acknowledged by these authors 43. In another study, Hannemann and colleagues identified a gene expression signature including MMP11 to be able to distinguish IDC from DCIS 45. Since no microdissection was performed in that study, the gene expression profiles they obtained were from mixtures of tumor epithelium and stroma. Nevertheless, our results together with these other studies support the notion that stroma-produced matrix metalloproteases may be key players driving the DCIS-IDC transition.

Finally, we showed that – like the epithelial compartment 9 – tumor stroma also exhibited a robust gene expression signature correlating with the histological tumor grade. These genes are primarily involved in immune response and cell-cycle progression. The association of an immune response signature with the more aggressive high-grade tumors is seemingly paradoxical. The interactions between tumor cells and the various immune cells are complex, however, ranging from tumor growth-suppressing effects to tumor growth-promoting effects 464748. Perhaps the immune response signature associated with high-grade tumors represents the escape phase 48, when the cancer cells become resistant to immune attack and hijack the abundant cytokines and chemokines made by the immune cells to grow, invade and spread to distant organs.

Conclusions

The present study provides the first comparative analysis of the in situ gene expression profiles of patient-matched normal and neoplastic breast epithelial and stromal compartments of both preinvasive and invasive stages of human breast cancer progression. This study of the breast cancer microenvironment at the transcriptome level and previous studies at the genomic 4950 and epigenetic 5152 levels support the view that the tumor microenvironment is an important co-conspirator rather than a passive bystander during tumorigenesis. Molecular alterations within the stroma offer novel avenues for therapeutic interventions and disease prognosis 53. This gene expression dataset of carefully procured in situ tumor epithelium and stroma should be a timely and valuable addition to the resources for the breast cancer research community.

Abbreviations

CXCL: chemokine (C-X-C motif) ligand; DCIS: ductal carcinoma in situ; DCIS-S: DCIS-associated stroma; GREM1: gremlin 1; IDC: invasive ductal carcinoma; IDC-S: IDC-associated stroma; INHBA: inhibin beta A; LCM: laser capture microdissection; PCR: polymerase chain reaction; SFRP1: secreted frizzled-related protein 1; WIF1: WNT inhibitory factor 1.

Competing interests

XJM and ME are employees of BioTheranostics, Inc. ME, X-JM and DCS are named inventors on a patent application relating to the contents of the manuscript.

Authors' contributions

DCS, XJM and ME conceived of the study, participated in its design and coordination, and helped draft the manuscript. DCS and SD performed microdissection and RNA extraction. XJM and ME performed the microarray experiments and microarray data analysis. ER performed the real-time PCR assays. All authors have read and approved the final manuscript.

Acknowledgements

The present study was supported by NIH RO1-1CA112021-01 (to DCS), the Department of Defense grants W81XWH-04-1-0606 and DAMD170310428 (to DCS), Susan G. Komen Breast Cancer Foundation grant BCTR0402932 (to DCS), and the Avon Foundation (to DCS). The authors thank Erica Chatfield for technical assistance in microdissection and RNA extraction, and they thank Sridhar Ramaswamy and E. Schmidt for helpful discussions and reading of the manuscript.

Putting tumours in context Bissell MJ Radisky D Nat Rev Cancer 2001 1 46 54 11900251 The inflammatory tumor microenvironment and its impact on cancer development de Visser KE Coussens LM Contrib Microbiol 2006 13 118 137 16627962 The microenvironment of the tumour-host interface Liotta LA Kohn EC Nature 2001 411 375 379 11357145 The fibroblastic coconspirator in cancer progression Egeblad M Littlepage LE Werb Z Cold Spring Harb Symp Quant Biol 2005 70 383 388 2580828 16869775 Involvement of chemokine receptors in breast cancer metastasis Muller A Homey B Soto H Ge N Catron D Buchanan ME McClanahan T Murphy E Yuan W Wagner SN Barrera JL Mohar A Verastegui E Zlotnik A Nature 2001 410 50 56 11242036 Stromal fibroblasts present in invasive human breast carcinomas promote tumor growth and angiogenesis through elevated SDF-1/CXCL12 secretion Orimo A Gupta PB Sgroi DC Arenzana-Seisdedos F Delaunay T Naeem R Carey VJ Richardson AL Weinberg RA Cell 2005 121 335 348 15882617 Molecular characterization of the tumor microenvironment in breast cancer 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 Polyak K Cancer Cell 2004 6 17 32 15261139 Histological and biological evolution of human premalignant breast disease Allred DC Mohsin SK Fuqua SA Endocr Relat Cancer 2001 8 47 61 11350726 Gene expression profiles of human breast cancer progression Ma XJ Salunga R Tuggle JT Gaudet J Enright E McQuary P Payette T Pistone M Stecker K Zhang BM Zhou YX Varnholt H Smith B Gadd M Chatfield E Kessler J Baer TM Erlander MG Sgroi DC Proc Natl Acad Sci USA 2003 100 5974 5979 156311 12714683 Bioconductor: open software development for computational biology and bioinformatics Gentleman RC Carey VJ Bates DM Bolstad B Dettling M Dudoit S Ellis B Gautier L Ge Y Gentry J Hornik K Hothorn T Huber W Iacus S Irizarry R Leisch F Li C Maechler M Rossini AJ Sawitzki G Smith C Smyth G Tierney L Yang JY Zhang J Genome Biol 2004 5 R80 545600 15461798 A comparison of normalization methods for high density oligonucleotide array data based on variance and bias Bolstad BM Irizarry RA Astrand M Speed TP Bioinformatics 2003 19 185 193 12538238 limmaGUI: a graphical user interface for linear modeling of microarray data Wettenhall JM Smyth GK Bioinformatics 2004 20 3705 3706 15297296 Controlling the false discovery rate: a practical and powerful approach to multiple testing Benjamin RS Hochberg Y J R Stat Soc Ser B 1995 57 289 300 R Project for Statistical Computing http://www.r-project.org GSEA-P: a desktop application for Gene Set Enrichment Analysis Subramanian A Kuehn H Gould J Tamayo P Mesirov JP Bioinformatics 2007 23 3251 3253 17644558 Gene Expression Omnibus: NCBI gene expression and hybridization array data repository Edgar R Domrachev M Lash AE Nucleic Acids Res 2002 30 207 210 99122 11752295 Gene Expression Omnibus http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE14548 A two-gene expression ratio predicts clinical outcome in breast cancer patients treated with tamoxifen Ma XJ Wang Z Ryan PD Isakoff SJ Barmettler A Fuller A Muir B Mohapatra G Salunga R Tuggle JT Tran Y Tran D Tassin A Amon P Wang W Enright E Stecker K Estepa-Sabal E Smith B Younger J Balis U Michaelson J Bhan A Habin K Baer TM Brugge J Haber DA Erlander MG Sgroi DC Cancer Cell 2004 5 607 616 15193263 Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles Subramanian A Tamayo P Mootha VK Mukherjee S Ebert BL Gillette MA Paulovich A Pomeroy SL Golub TR Lander ES Mesirov JP Proc Natl Acad Sci USA 2005 102 15545 15550 1239896 16199517 Gene ontology: tool for the unification of biology. The Gene Ontology Consortium Ashburner M Ball CA Blake JA Botstein D Butler H Cherry JM Davis AP Dolinski K Dwight SS Eppig JT Harris MA Hill DP Issel-Tarver L Kasarskis A Lewis S Matese JC Richardson JE Ringwald M Rubin GM Sherlock G Nat Genet 2000 25 25 29 10802651 Periostin, secreted from stromal cells, has biphasic effect on cell migration and correlates with the epithelial to mesenchymal transition of human pancreatic cancer cells Kanno A Satoh K Masamune A Hirota M Kimura K Umino J Hamada S Satoh A Egawa S Motoi F Unno M Shimosegawa T Int J Cancer 2008 122 2707 2718 18381746 Periostin, a member of a novel family of vitamin K-dependent proteins, is expressed by mesenchymal stromal cells Coutu DL Wu JH Monette A Rivard GE Blostein MD Galipeau J J Biol Chem 2008 283 17991 18001 18450759 SPARC and tumor growth: where the seed meets the soil? Framson PE Sage EH J Cell Biochem 2004 92 679 690 15211566 Estrogen receptors and proliferation markers in primary and recurrent breast cancer Jensen EV Cheng G Palmieri C Saji S Makela S Van Noorden S Wahlstrom T Warner M Coombes RC Gustafsson JA Proc Natl Acad Sci USA 2001 98 15197 15202 65006 11734621 Gene expression signatures of morphologically normal breast tissue identify basal-like tumors Finak G Sadekova S Pepin F Hallett M Meterissian S Halwani F Khetani K Souleimanova M Zabolotny B Omeroglu A Park M Breast Cancer Res 2006 8 R58 1779486 17054791 Differential expression of ribosomal proteins in human normal and neoplastic colorectum Kasai H Nadano D Hidaka E Higuchi K Kawakubo M Sato TA Nakayama J J Histochem Cytochem 2003 51 567 574 12704204 Many ribosomal protein genes are cancer genes in zebrafish Amsterdam A Sadler KC Lai K Farrington S Bronson RT Lees JA Hopkins N PLoS Biol 2004 2 E139 406397 15138505 Inhibition of c-Myc activity by ribosomal protein L11 Dai MS Arnold H Sun XX Sears R Lu H EMBO J 2007 26 3332 3345 1933407 17599065 Mitochondrial defects in cancer Carew JS Huang P Mol Cancer 2002 1 9 149412 12513701 Targeting mitochondria in the treatment of human cancer: a coordinated attack against cancer cell energy metabolism and signalling Hagland H Nikolaisen J Hodneland LI Gjertsen BT Bruserud O Tronstad KJ Expert Opin Ther Targets 2007 11 1055 1069 17665978 WNT pathway and mammary carcinogenesis: loss of expression of candidate tumor suppressor gene SFRP1 in most invasive carcinomas except of the medullary type Ugolini F Charafe-Jauffret E Bardou VJ Geneix J Adelaide J Labat-Moleur F Penault-Llorca F Longy M Jacquemier J Birnbaum D Pebusque MJ Oncogene 2001 20 5810 5817 11593386 WIF1, a component of the Wnt pathway, is down-regulated in prostate, breast, lung, and bladder cancer Wissmann C Wild PJ Kaiser S Roepcke S Stoehr R Woenckhaus M Kristiansen G Hsieh JC Hofstaedter F Hartmann A Knuechel R Rosenthal A Pilarsky C J Pathol 2003 201 204 212 14517837 Loss of SFRP1 is associated with breast cancer progression and poor prognosis in early stage tumors Klopocki E Kristiansen G Wild PJ Klaman I Castanos-Velez E Singer G Stohr R Simon R Sauter G Leibiger H Essers L Weber B Hermann K Rosenthal A Hartmann A Dahl E Int J Oncol 2004 25 641 649 15289865 Bone morphogenetic protein antagonist gremlin 1 is widely expressed by cancer-associated stromal cells and can promote tumor cell proliferation Sneddon JB Zhen HH Montgomery K Rijn van de M Tward AD West R Gladstone H Chang HY Morganroth GS Oro AE Brown PO Proc Natl Acad Sci USA 2006 103 14842 14847 1578503 17003113 Transcriptional program induced by Wnt protein in human fibroblasts suggests mechanisms for cell cooperativity in defining tissue microenvironments Klapholz-Brown Z Walmsley GG Nusse YM Nusse R Brown PO PLoS ONE 2007 2 e945 1976560 17895986 Activin, inhibin and the human breast Reis FM Luisi S Carneiro MM Cobellis L Federico M Camargos AF Petraglia F Mol Cell Endocrinol 2004 225 77 82 15451571 Inhibin/activin subunits (inhibin-alpha, -betaA and -betaB) are differentially expressed in human breast cancer and their metastasis Mylonas I Jeschke U Shabani N Kuhn C Friese K Gerber B Oncol Rep 2005 13 81 88 15583806 CXCR4: a key receptor in the crosstalk between tumor cells and their microenvironment Burger JA Kipps TJ Blood 2006 107 1761 1767 16269611 Regulation of in situ to invasive breast carcinoma transition Hu M Yao J Carroll DK Weremowicz S Chen H Carrasco D Richardson A Violette S Nikolskaya T Nikolsky Y Bauerlein EL Hahn WC Gelman RS Allred C Bissell MJ Schnitt S Polyak K Cancer Cell 2008 13 394 406 18455123 Molecular signature of MT1-MMP: transactivation of the downstream universal gene network in cancer Rozanov DV Savinov AY Williams R Liu K Golubkov VS Krajewski S Strongin AY Cancer Res 2008 68 4086 4096 18519667 New functions for the matrix metalloproteinases in cancer progression Egeblad M Werb Z Nat Rev Cancer 2002 2 161 174 11990853 Matrix metalloproteinase-11/stromelysin-3 exhibits collagenolytic function against collagen VI under normal and malignant conditions Motrescu ER Blaise S Etique N Messaddeq N Chenard MP Stoll I Tomasetto C Rio MC Oncogene 2008 27 6347 55 18622425 Progression-specific genes identified by expression profiling of matched ductal carcinomas in situ and invasive breast tumors, combining laser capture microdissection and oligonucleotide microarray analysis Schuetz CS Bonin M Clare SE Nieselt K Sotlar K Walter M Fehm T Solomayer E Riess O Wallwiener D Kurek R Neubauer HJ Cancer Res 2006 66 5278 5286 16707453 A novel metalloproteinase gene specifically expressed in stromal cells of breast carcinomas Basset P Bellocq JP Wolf C Stoll I Hutin P Limacher JM Podhajcer OL Chenard MP Rio MC Chambon P Nature 1990 348 699 704 1701851 Classification of ductal carcinoma in situ by gene expression profiling Hannemann J Velds A Halfwerk JB Kreike B Peterse JL Vijver van de MJ Breast Cancer Res 2006 8 R61 1779498 17069663 Paradoxical roles of the immune system during cancer development de Visser KE Eichten A Coussens LM Nat Rev Cancer 2006 6 24 37 16397525 The IKK-related kinases: from innate immunity to oncogenesis Clement JF Meloche S Servant MJ Cell Res 2008 18 889 899 19160540 Tumor microenvironments, the immune system and cancer survival Strausberg RL Genome Biol 2005 6 211 1088935 15774034 Combined total genome loss of heterozygosity scan of breast cancer stroma and epithelium reveals multiplicity of stromal targets Fukino K Shen L Matsumoto S Morrison CD Mutter GL Eng C Cancer Res 2004 64 7231 7236 15492239 Breast-cancer stromal cells with TP53 mutations and nodal metastases Patocs A Zhang L Xu Y Weber F Caldes T Mutter GL Platzer P Eng C N Engl J Med 2007 357 2543 2551 18094375 Breast cancer DNA methylation profiles in cancer cells and tumor stroma: association with HER-2/neu status in primary breast cancer Fiegl H Millinger S Goebel G Muller-Holzner E Marth C Laird PW Widschwendter M Cancer Res 2006 66 29 33 16397211 Distinct epigenetic changes in the stromal cells of breast cancers Hu M Yao J Cai L Bachman KE Brule van den F Velculescu V Polyak K Nat Genet 2005 37 899 905 16007089 Stromal gene expression predicts clinical outcome in breast cancer Finak G Bertos N Pepin F Sadekova S Souleimanova M Zhao H Chen H Omeroglu G Meterissian S Omeroglu A Hallett M Park M Nat Med 2008 14 518 527 18438415