Tumor Microenvironment–Derived Proteins Dominate the Plasma Proteome Response During Breast Cancer Induction and Progression

Published OnlineFirst June 8, 2011; DOI: 10.1158/0008-5472.CAN-11-0568

Cancer Integrated Systems and Technologies Research

Tumor Microenvironment–Derived Proteins Dominate the Plasma Proteome Response during Breast Cancer Induction and Progression

Sharon J. Pitteri1, Karen S. Kelly-Spratt2, Kay E. Gurley2, Jacob Kennedy1, Tina Busald Buson1, Alice Chin1, Hong Wang1, Qing Zhang1, Chee-Hong Wong1, Lewis A. Chodosh3, Peter S. Nelson2, Samir M. Hanash1, and Christopher J. Kemp2

Abstract Tumor development relies upon essential contributions from the tumor microenvironment and host immune alterations. These contributions may inform the plasma proteome in a manner that could be exploited for cancer diagnosis and prognosis. In this study, we employed a systems biology approach to characterize the plasma proteome response in the inducible HER2/neu mouse model of breast cancer during tumor induction, progression, and regression. Mass spectrometry data derived from approximately 1.6 million spectra identified protein networks involved in wound healing, microenvironment, and metabolism that coordinately changed during tumor development. The observed alterations developed prior to cancer detection, increased progressively with tumor growth and reverted toward baseline with tumor regression. Gene expression and immu- nohistochemical analyses suggested that the cancer-associated plasma proteome was derived from transcriptional responses in the noncancerous host tissues as well as the developing tumor. The proteomic signature was distinct from a nonspecific response to inflammation. Overall, the developing tumor simultaneously engaged a number of innate physiologic processes, including wound repair, immune response, coagulation and complement cascades, tissue remodeling, and metabolic homeostasis that were all detectable in plasma. Our findings offer an integrated view of tumor development relevant to plasma-based strategies to detect and diagnose cancer. Cancer Res; 71(15); 5090–100. 2011 AACR.

Introduction progenitor cells from the bone marrow to promote angiogenesis and to establish premetastatic niches in distal organs such The tumor microenvironment and host factors play a major as the lung (8–10). To date, these tumor–host interactions role in the establishment, progression, and metastatic dis- have been primarily studied at the cellular and tissue levels, semination of cancer (1). Stromal fibroblasts, myofibroblasts, and it remains unclear up to what extent they contribute to endothelial cells, and immune cells provide growth factors, the changes in the plasma proteome, particularly at early proteases, and angiogenic potential to support tumor growth stages of tumor development. Proteomic advances currently (2, 3). Dendritic cells and recruited T and B cells, regulatory T allow in-depth quantitative profiling of biological fluids, such cells, macrophages, and other myeloid-derived suppressor as plasma spanning of more than 6 logs of protein abundance cells, contribute both positively and negatively to multiple (11, 12). Application of proteomics to mouse models provides stages of tumor progression (4–7). Tumors can also recruit a number of distinct advantages to interrogate the systems biology of cancer (13, 14). We utilized a conditional transgenic neu-induced mouse Authors' Affiliations: 1Division of Public Health Sciences and 2Division of model of mammary cancer to determine the extent and source Human Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington; and 3Department of Cancer Biology, University of Pennsyl- of changes in the plasma proteome at predetermined stages of vania School of Medicine, Philadelphia, Pennsylvania tumor development (15). The neu is an activated rat homo- Note: Supplementary data for this article are available at Cancer Research logue of the human epidermal growth factor receptor 2 Online (http://cancerres.aacrjournals.org/). (ErbB2) gene. ErbB2 is a receptor tyrosine kinase amplified Corresponding Authors: Samir M. Hanash, Fred Hutchinson Cancer and overexpressed in more than 25% of human breast cancers, Research Center, 1100 Fairview Ave., N. Seattle, WA 98109. Phone: and signaling from this oncogene is a central driver in breast 206-667-5703; Fax: 206-667-2537; E-mail: [email protected] or Christopher J. Kemp, Fred Hutchinson Cancer Research Center, cancer development. When induced with doxycycline, bitrans- 1100 Fairview Ave., N. Seattle, WA 98109. Phone: 206-667-4252; genic MMTV-rtTA/TetO-NeuNT mice synchronously develop Fax: 206-667-5815; E-mail: [email protected] invasive mammary carcinomas that recapitulate the morpho- doi: 10.1158/0008-5472.CAN-11-0568 logic, pathologic, and molecular features of ErbB2-positive 2011 American Association for Cancer Research. human breast cancer (16). Doxycycline withdrawal results in

5090 Cancer Res; 71(15) August 1, 2011

The Cancer-Associated Plasma Proteome

transgene de-induction and tumor regression, mimicking calculate a P value for the mean case/control ratio of the responses of tumors to targeted therapy. We applied in-depth protein. Second, the probability for the case/control ratio for quantitative proteomic profiling to this model and identified a each MS event was calculated from the distribution of ratios in set of proteins that changed in relative abundance in plasma control/control experiments in which the same sample was during tumor induction, progression, and regression. Data- labeled with heavy and light acrylamide. On the basis of the base mining, cross-referencing proteomic data with transcript control/control experiments, if the P value for each individual profiles, and confirmatory cell-type localization studies event was less than 0.05, the overall protein ratio was con- revealed that tumor cells, the microenvironment, and sys- sidered significant. temic responses contribute to the dynamic changes in the plasma proteome with tumor development and progression. Breast cancer cell line profiling The cell line methods are previously described (24). MCF7, Materials and Methods MDA-MB-231, and SKBR3 cell lines were obtained from American Type Culture Collection (ATCC), cultured for less Tissue collection than 6 months, and were not reauthenticated. Cells were Bitransgenic FVB MMTV-rtTA/TetO-NeuNT "case" and cultured for 7 passages in SILAC DMEM [Invitrogen; dia- monotransgenic FVB TetO-NeuNT "control" mice (15) were lyzed FBS, 13C-lysine; (25)]. After 48 hours, secreted proteins paired at weaning and maintained in the same cage. Doxycy- were obtained from media. For total cell extract, cells were cline (2 mg/mL) was added to drinking water starting at sonicated and centrifuged to remove debris. For cell surface 8 weeks of age. Mice were palpated every other day to detect proteins, cells were biotinylated, extracted, sonicated, and mammary tumor growth. Each pair of case and control mice captured by an avidin column. One milligram of each of was euthanized on the same day by CO2 inhalation and plasma secreted, total cell extract, and cell surface proteins was was collected as described (13). reduced and alkylated with iodoacetamide and fractionated by reversed-phase chromatography. Fractions were digested Plasma proteomic analysis with trypsin and subjected to liquid chromatography/tan- The plasma proteomics workflow has been previously dem mass spectrometry (LC/MS-MS as described above. described (17). In brief, case and control plasma pools (250–315 mL/pool) from 5 to 11 mice were immunodepleted Immunoassays (3 abundant proteins, MS-3; Agilent). Samples were concen- Rules Based Medicine RodentMAP v2.0 Luminex immu- trated and reduced with dithiothreitol. Isotopic intact pro- noassays measured 58 proteins in plasmas. Plasma levels of tein labeling of cysteine residues was done with control insulin-like growth factor–binding protein 5 (Igfbp5), metal- samples receiving 12C-acrylamide (Fluka), and case samples lopeptidase inhibitor-1 (Timp1), lipocalin 2 (Lcn2), galectin- receiving 13C-acrylamide (Cambridge Isotope Laboratories). 1 (Lgals1), and C-C motif chemokine 8 (Ccl8) were mea- Case and control pools were combined for 2-dimensional sured by ELISA (R&D Systems) according to manufacturer's high-performance liquid chromatography (Shimadzu) pro- protocol. tein separation. Anion-exchange chromatography (Poros HQ/10; Applied Biosystems) used an 8-step elution (0– Immunohistochemistry 1,000 mmol/L NaCl). Anion-exchange fractions were sepa- Tissues were processed and stained with calreticulin (Calr; rated by reversed-phase chromatography (Poros R2/10). Abcam), Lgals1 (R&D Systems), lactotransferrin (Ltf; Abgent), Lyophilized fractions were digested with trypsin and 96 S100a9 (NovusBio), Pdz and lim domain protein (Pdlim1; fractions per tumor stage were analyzed by a LTQ-Orbitrap Abcam), smooth muscle actin (SMA; Thermo), Timp1 (Abbio- (Thermo) mass spectrometer and NanoLC-1D (Eksigent). tec), Vasp (Abcam), or Igfbp5 (Santa Cruz) antibodies by using Online reversed-phase peptide separation and tandem mass a standard 3-step technique (26). Collagen staining was done spectrometry (MS-MS) of the 5 most abundant þ2orþ3 using the Sigma Trichrome Kit. The University of Washington ions (m/z 400–1,800) were conducted. Histology Core conducted CD3 and F4/80 staining. Twelve Each tumor stage analysis yielded approximately 4,000,000 tumors were stained. For each antibody all tumors showed spectra, which were searched against the mouse International similar staining patterns. Protein Index (IPI) database (v.3.48) by using X!Tandem with comet scoring (18–21). PeptideProphet and ProteinProphet Results (22) were used for validation and protein inference. Quanti- fication was done by Q3 (23). Identifications with PeptidePro- Histologic evaluation of mammary tumor induction, phet probability greater than 0.2 were submitted to progression, and regression ProteinProphet. Proteins were filtered using greater than Cohorts of MMTV-rtTA/TetO-NeuNT "case" and TetO- 5% error rate. Protein ratios were computed from peptides NeuNT "control" mice were sacrificed at 4 time points during with PeptideProphet probability greater than 0.75. Proteins tumor development (Fig. 1A). After 5 weeks on doxycycline with multiple IPIs and single gene name were combined (log2 and prior to clinically detectable lesions, mammary average of peptides) to give 1 ratio per gene name. duct hyperplasia, intraepithelial neoplasia, and microinvasive For proteins with multiple paired MS events of heavy and carcinoma were apparent (Fig. 1B). By 8 to 12 weeks, 0.5-cm light acrylamide, first, a 2-tailed Student's t test was used to tumors consisted of hyperplastic nodules of intraepithelial

www.aacrjournals.org Cancer Res; 71(15) August 1, 2011 5091

Pitteri et al.

A X Tissue collected

e 1.010 cm Dox withdrawal Start Dox X 0.5 cm X

Tumor size Tumor X X

Preclinical Rapid tumor growth Max Regression Time

B LN

LN LN 12x

Normal Preclinical Mid (0.5 cm) Late (1.0 cm) Regression C

Regression Preclinical Mid (0.5 cm) Late (1.0 cm) )

2 4 4 4 4

0 0 0 0

Case/control (log Case/control –4 –4 –4 –4

Figure 1. Histologic and plasma proteomic analyses of HER2/neu mammary tumor progression. A, samples were collected from litter-matched case and control mice at indicated stages. B, hematoxylin and eosin (H&E) staining of mammary tissue from bitransgenic case mice at the preclinical, 0.5-cm diameter, 1.0-cm diameter tumor stages, and during tumor regression. Top, 26 magnification unless otherwise indicated. Bottom, 130 magnification of boxed sections from the top row. LN, lymph node. Arrows indicate breast epithelial cells within the mammary fat pads of normal and preclinical sections. C, case/ control ratios of all quantified plasma proteins at all 4 tumor stages. Red indicates proteins increased greater than 1.5-fold and green indicates proteins decreased greater than 1.5-fold in plasma from case versus control mice (P < 0.05).

neoplasia and areas of adenocarcinoma. By 14 to 16 weeks, Changes in the plasma proteome prior to clinical 1-cm breast tumors were classified as mammary adenocar- evidence of cancer cinomas with areas of local invasion. Neoplastic cells were Plasma samples from preclinical tumor-bearing mice supported by vascular stroma and fibrous connective tissue, yielded 49 proteins with increased and 17 with decreased indicating a desmoplastic reaction. Inflammatory cell infil- concentrations in case compared with control mice (>1.5- trates included lymphocytes, neutrophils, macrophages, fold change, P < 0.05; Fig. 1C and Supplementary Table S1). plasma cells, and mast cells. Doxycycline was withdrawn These proteins were grouped by function, biological process, from mice bearing approximately 1-cm tumors and plasma and cellular localization. Proteins involved in acute-phase samples were taken 3 days later, when tumors had visibly response, immune cell signaling—including cytokines, che- decreased in size. Histologic evaluation showed regressing mokines, and macrophage and neutrophil signaling pro- mammary trees with ductal ectasia, inflammation, and teins—and cytoskeletal and extracellular matrix (ECM) fibrosis. Plasma from case and control mice at each of these functions were increased (Fig. 2). Response to wounding 4 tumor stages was pooled and subjected to differential was the most significant biological process altered in the isotopic labeling, extensive protein fractionation, and LC/ proteome of mice with preclinical neoplasia (Supplementary MS-MS analysis of tryptic digests from individual fractions Fig. S1A). Analysis of the subset of proteins known to be (17). The same plasma pools were analyzed using Rules extracellular identified the acute-phase response and the Based Medicine Luminex/Rules Based Medicine, which mea- coagulation and complement systems as the most signifi- sured 58 proteins representing cytokines, growth factors, cantly altered pathways (Supplementary Figs. S1B and S2). and other signaling proteins. Among the altered plasma proteins with known intracellular

5092 Cancer Res; 71(15) August 1, 2011 Cancer Research

The Cancer-Associated Plasma Proteome

C Cytoskeletal, ECM proteins Figure 2. Wound-healing response components: acute- phase, immune cell, and ECM proteins. Plasma proteins that AB increased in tumor-bearing mice fell into major functional Acute-phase Immune cell response proteins proteins Regression Angiogenesis Acute inflammation Cell lines categories. A, acute-phase Preclinical 0.5 cm 1.0 cm Chronic inflammation response proteins, mainly liver- Timp1** derived. B, proteins from tumor- Papln Mmp9* infiltrating immune cells Vwf* (macrophages and neutrophils). Cnn2 C, proteins involved in cell Vasp Regression Regression Cell lines 1.0 cm Cell lines Chronic inflammation Preclinical 0.5 cm Chronic inflammation Angiogenesis Acute inflammation Angiogenesis Acute inflammation movement and tumor Preclinical 0.5 cm 1.0 cm Pxdn microenvironment, for example, Hp** Ltf Fbln2 cytoskeletal, ECM, and tumor Ambp Mpo* Prg4 Lrg1 Cd40l* stroma proteins. Red indicates Lgals1 Itih4 Ccl8 Adamtsl5 case/control ratios greater than C8g Lcn2 P < Fbln5 1.5 ( 0.05), black indicates no EG214403 S100a9 change between case and control Tpm4 Itih3 S100a8 Col15a1 plasma, and white indicates that Itih1 Ccl12* Tnc the proteins were not measured. C8b Ngp Ltbp2 For the breast cancer cell lines, red Itih2 Retnlg Hspg2 Apob Ccl7* indicates that the protein was Dsg2 Orm3 Ccl9* identified by proteomic profiling Loxl1 F5 Pglyrp1 and white indicates that the Tagln2 Rnase4 Cxcl10* protein was not identified. Unless Cfh Ccl2* Cfl1 otherwise indicated, levels were F11 Cotl1 Flna measured by LC-MS. *, measured Colec11 Treml1 Actb by Luminex/Rules Based Nov Medicine. **, measured by both Ctsd LC-MS and Luminex/Rules Based Zyx Medicine. Pdlim5 Pfn1 Lect1 Coro1a

localization, those involved in glycolysis, fatty acid, and To determine the extent to which protein changes amino acid metabolism predominated (Supplementary detected at this early time point may be specifically Table S2). associated with tumor development, we cross-referenced Of the 49 plasma proteins that increased in relative abun- these data to similar plasma proteomic profiling from dance in mice with preclinical neoplasia, 22 were identified in mouse models of subacute and chronic inflammation proteomic profiling experiments from 3 human breast cancer and angiogenesis (33). Of the 49 proteins with increased cell lines, MCF7, MDA-MB-231, and SKBR3 (Supplementary concentration in plasma from mice with early-stage breast Table S2). SKBR3 cells overexpress ErbB2 and have been cancer, 12 were increased in the plasma of 1 or more of utilized extensively to study ErbB2 signaling (27, 28). Immu- the confounding mouse models (Supplementary Table S2), nohistochemical (IHC) staining of preclinical tumor sections indicating these 12 proteins are not breast cancer specific. showed cytoplasmic and/or nuclear localization in tumor cells Levels of S100a9, Pdlim, Ltf, Calr, and Lgals1 that were for all 5 proteins for which antibodies were available (Fig. 3), detected in primary tumorsbyIHC(Fig.2)werenot suggesting that release from tumor cell turnover could con- increased in the confounder models, thereby increasing tribute to increased plasma levels of these proteins. Calr is a their potential cancer specificity (see Supplementary calcium-binding chaperone protein reported to have prog- Table S2 for additional examples). Interestingly, a greater nostic significance in breast cancer based on tissue expression percentage (50%) of proteins with decreased concentra- (29). Lgals1 is induced by ErbB2 (30), binds to H-ras, and tion in preclinical plasmas were decreased in confounding mediates cell transformation (31). Ltf is an iron-binding condition models, indicating that reduced proteins are less protein that is secreted by breast tissue. Calgranulin B likely to be cancer specific. (S100A9) is a calcium-binding protein present in a wide range Thus, even at a relatively early stage of tumor development, of cells and overexpressed in neutrophils, monocytes, and changes were observed in the plasma proteome reflecting tumor cells (32). The Pdlim1 associates with actin filaments contributions from tumor cells, the microenvironment, and and stress fibers. the host response. Proteins involved in functions relevant to

www.aacrjournals.org Cancer Res; 71(15) August 1, 2011 5093

Pitteri et al.

Calr Lgals1 Ltf S100a9 Pdlim1

Normal

Preclinical

Figure 3. IHC staining of selected proteins identified in plasma in normal breast and preclinical breast lesions. Calr shows some nuclear staining in normal breast epithelial and strong nuclear and cytoplasmic staining in preclinical tumor cells. Lgals1 shows some nuclear staining in normal and strong nuclear and cytoplasmic staining in preclinical tumor cells. Ltf shows some cytoplasmic staining in normal and strong cytoplasmic staining in tumor cells. Calgranulin B (S100a9) shows some nuclear staining in normal and strong nuclear and cytoplasmic staining in tumor cells. Pdlim1 shows some cytoplasmic staining in normal and strong cytoplasmic staining in the tumor cells. 60 magnification.

wound healing, inflammation, metabolism, and ECM remo- protein abundance associated with cancer can be attributed deling predominated. to metabolic changes, reduced proteasomal components, as well as host responses that are not cancer specific. Plasma proteome changes associated with tumor We next examined the extent and potential contribution of progression altered gene expression in both primary tumor and nontumor To identify plasma protein changes associated with tumor host tissues to changes in the plasma proteome. Gene expres- progression, we profiled the plasma proteome of mice bearing sion profiling was conducted on blood buffy coat, thymus, 0.5- and 1-cm breast tumors. The overall numbers of proteins spleen, liver, and breast tumors from mice with 1-cm tumors, that showed altered plasma levels in case versus control mice using an independent cohort of case and control mice (34). Of progressively increased with tumor growth (Fig. 1C). In mice the 31 proteins that were increased in plasma from tumor- bearing 0.5-cm tumors, 38 proteins showed a significant bearing mice and identified in proteomic profiling of breast increase and 105 a decrease in abundance, whereas in mice cancer cells, 25 (81%) showed a corresponding increase in bearing 1.0-cm tumors, 70 proteins were increased and 114 were decreased (>1.5, P < 0.05; Supplementary Table S2). As in the preclinical samples, proteins that increased in mid- and 5 late-stage tumor-bearing mice included those identified in Lcn2 proteomic profiling of human breast cancer cells, as well as 4 S100a9 Hp S100a8 proteins involved in the acute-phase response, complement, Fbln2 and coagulation cascades, chemokines, macrophage and 3 Ltf Sftpd EG214403 neutrophil signaling, and metabolic proteins (Fig. 2 and 2

Supplementary Fig. S2). A number of cytoskeletal, ECM, ) ratio Ccl8 2 and stroma-associated proteins including Loxl1, Tnc, matrix 1 metalloproteinase (Mmp) 9, Timp1, Dsg2, Fbln2, Col15a1, Pxdn, Prg4, and Vwf increased in their levels. Interestingly, –5 –4 –3 –2 –1 1 2345 only 1 of 30 of these tissue-remodeling proteins was identified as increased in plasma from the confounder mouse models –1

(Fig. 2), suggesting a substantial contribution of the stroma to –2 plasma protein changes associated with tumor development. (log 1.0-cm case/control It is noteworthy that a greater proportion of plasma pro- –3 teins were reduced in abundance, rather than increased in Down in confounder Up in confounder plasma from mice with mid- and advance-stage tumors –4 y = x (Fig. 1C). Decreased proteins that were unique to tumor- –5 bearing mice included metabolic proteins and 10 components 0.5-cm case/control (log2) ratio of the proteasome (Psma1, Psma2, Psma4, Psma7, Psmb1, Psmb10, Psmb6, Psmc5, Psmd4, and Psme1; Supplementary Table S2). Approximately a quarter of the proteins with Figure 4. Correlation of plasma protein abundance between tumor stages. Shown are case/control ratios for plasma proteins that were quantified in reduced levels in mice with clinically apparent breast cancer both 0.5- and 1.0-cm tumor stages. Green and red data points indicate were decreased in plasma from mice with inflammation or proteins identified as increased or decreased in the plasma from the angiogenesis (Fig. 4). These data indicate that decreased confounder models, respectively.

5094 Cancer Res; 71(15) August 1, 2011 Cancer Research

The Cancer-Associated Plasma Proteome

expression in HER2/neu breast tumors as compared with of Timp1 and Vasp that were elevated in plasma and normal breast tissue (Supplementary Fig. S3). Twelve of these expressed in tumor cells. proteins (Flna, Vasp, Cnn2, Coro1a, Cap1, Pxdn, Dsg2, Tpm4, For 14 proteins that were increased in plasma of tumor- Pfn1, Cotl1, Zyx, and Ctsd) are involved in cytoskeletal func- bearing mice and that are known to be involved in myeloid cell tion or ECM remodeling, processes that are necessary for function, we compared the corresponding mRNA expression tumor cell invasion. None of these proteins increased in levels in thymus, spleen, and blood buffy coat fractions that concentration in plasma from the confounder models. The are rich in white blood cells. Of these 14 proteins, 13 had concordance between protein levels in plasma, protein expres- increased levels of mRNA expression levels in 1 or more of sion in breast cancer cells, and mRNA expression in HER2/ these tissues from tumor-bearing versus control mice (Sup- neu-driven tumors for these proteins indicates a contribution plementary Fig. S4). Lcn2, S100a9, S100a8, neutrophilic gran- of tumor cells to their increased levels in plasma. ule protein (Ngp), myeloperoxidase (Mpo), and peptidoglycan To determine the contributions of the tumor microen- recognition protein (Pglyrp1) were the most significantly vironment to increased levels of proteins in plasma, we increased in both plasma and immune cell compartments, used IHC to examine the cellular and stromal landscape of suggesting the increased levels of these proteins in plasma HER2/neu mammary tumors. In addition to tumor cells, reflect an immune cell response to the developing tumor. HER2/neu tumors contained macrophage, neutrophil, and S100a9 and Lcn2 are examples of proteins identified as lymphocyte infiltrates, fibroblasts, extensive collagen increased in both immune cells and tumors. A set of 27 genes deposition, and prominent blood vessels (Fig. 5). Plasma showed significantly increased mRNA expression in the thy- proteins that could be derived from tumor cell interactions mus in case versus control mice (P < 0.05; ref. 34). Proteins with these recruited cell types and the local environment corresponding to 7 of the 27 genes were increased in the are also displayed according to function (immunity, plasma, suggesting a contribution of distal immunologic ECM, cytoskeletal, and angiogenesis). Note the examples tissues to their increased plasma levels.

Macrophages Fibroblasts F4/80 α-SMA

T cells B cells Timp1 Immune/cytokine/ CD3 signaling ECM/stromal Ccl8, Cd51, Cd40 Adamts15, Col15a1, ligand, Cotl1, Ip10, Col18a, Ctsb, Dsg2 Tumor cell Fifgr, Fbln2, Fbln5, Lcn2, Lif, Mcp1, Ltf, Hspg2, Lgals1, α Mcp3, Mcp5, Mip1 , Loxl1, Mmp9, Ltbp2, β γ Mip1 , Mip1 , Mip2, Nov, Papln, Prg4, Ngp, Pf4, Pglyrp1, Pxdn, Timp1, Tgln2, Ppbp, Retlg, S100a8, Tnc S100a9

Cytoskeletal trichrome Actb, Cfl1, Cnn2, Coro1a, BV Flna, Myl6, Pfn1, Pdlim1, Pdlim5, Tagln, Tpm4 Tppp3, Vasp, Zyx, Angiogenic Vegf, Vwf, Vcam Vasp

ECM

Figure 5. HER2/neu mammary tumor microenvironment schematic. In addition to the tumor cells, Her2/neu tumors contain cancer-associated macrophages (F4/80), CAFs (a-SMA), lymphocytes (CD3), blood vessels (BV; not shown), and extensive collagen deposition (trichrome). Also shown are IHC results of HER2/neu tumors for Timp1 and Vasp, which were elevated in plasma from tumor-bearing mice. Additional proteins elevated in plasma from tumor-bearing mice are listed according to functional categories (boxes).

www.aacrjournals.org Cancer Res; 71(15) August 1, 2011 5095

Pitteri et al.

Reversion of the plasma proteome toward baseline proteins progressively decreased in their levels during tumor after oncogene de-induction and tumor regression development but rebounded after tumor regression (Fig. 6). To identify plasma protein changes associated with early- These proteins are mainly involved in acute-phase response, stage tumor regression, we quantitated protein changes in and many were also decreased in the confounder inflamma- plasma from mice 3 days after doxycycline withdrawal and tion models. Pathway analysis was used to assess the biolo- oncogene de-induction (Fig. 1). At this time point, only 24 gical processes behind these dynamic changes in the plasma proteins had increased levels and 28 decreased levels in case proteome that accompanied tumor development. Proteins versus control mice (Supplementary Table S2). Many proteins involved in wound healing, the complement pathway, and increased in tumor-bearing mice were undetected or returned metabolism were altered at multiple tumor stages (Supple- to baseline levels after oncogene de-induction. Of the 12 that mentary Fig. S2). remained elevated, 8 were immune cell or acute-phase proteins (Hp, C8g, Ccl8, EG214403, Mpo, Cd40l, Orm3, and Hpx). Confirmation of LC/MS-MS detected changes in protein Changes in acute-phase proteins and complement have also abundance by independent antibody-based methods been observed in plasma from epirubicin/docetaxel-treated Four proteins that span a wide range of concentrations in breast cancer (35). normal plasma and that exhibited altered plasma levels in tumor-bearing mice on the basis of LC/MS-MS analysis were Comparative analysis of the plasma proteome at subjected to validation by ELISAs applied to samples from different tumor stages independent cohorts of mice. Protein concentrations of Comparison of the plasma proteome from mice with 0.5- Igfbp5, Lcn2, Timp1, and Ccl8 were found to progressively and 1.0-cm tumors revealed a significant positive correlation increase during tumor development and return to normal (Pearson correlation coefficient r ¼ 0.67) in relative protein after regression, concordant with MS data (Fig. 7). We also abundance, indicating many of the same proteins are either quantified levels of 37 proteins using bead-based assays reduced or increased at both tumor stages (Fig. 4). Some applied to plasma samples from all 4 tumor stages. Thirteen proteins were quantified at all 4 tumor stages. Papln, Ltf, of these showed increased levels in case versus control mice Igfbp5, S100a8, Lrg1, Pcsk9, and Ccl8 are examples of proteins for at least 1 tumor stage (Supplementary Table S3). These that showed progressive increases in relative abundance included Cd40 ligand, monocyte and macrophage signaling during tumor progression and diminished to near control proteins, and stromal proteins Mmp9, Timp1, and Vwf. Seven levels after tumor regression (Fig. 6). Of these, Ltf and Igfbp5 of these proteins were quantified by LC/MS-MS, and again were expressed in tumor cells as assessed by IHC. A set of there was substantial agreement between the 2 measurement

A 3.5 ) 2 3

2.5 Lrg1 Papln C 2 Ltf Igfbp5 Ltf 1.5 Igfbp5 1 Pcsk9 S100a8 0.5 Ccl8 Case/control ratio (log

0 Preclinical Figure 6. Dynamics of protein al m n o changes with tumor nic .5c cli 0 1.0 cm essi re r establishment, progression, and P Reg regression. A, proteins increased B 1 cm with tumor development and decreased after regression. B,

) 0 2 Klkb1 proteins decreased with tumor –0.2 Bche development and increased after –0.4 Thbs4 regression. C, IHC revealed Ltf –0.6 Gpx3 and Igfbp5 staining in tumor cells. –0.8 Sod3 Regression –1 Tfpi –1.2 F12 –1.4

Case/control ratio (log –1.6

l ica m in cl .5 c e 0 1.0 cm Pr Regression

5096 Cancer Res; 71(15) August 1, 2011 Cancer Research

The Cancer-Associated Plasma Proteome

Control Case A Igfbp5 B Lcn2 300 15,000 * ** *** 200 10,000 * P = 0.44 ng/mLn ng/mL 100 5,000 *** Figure 7. ELISA protein P = 0.054 P measurements in an independent = 0.21 mouse cohort: plasma levels of 0 0 Igfbp5 (A), Lcn2 (B), Timp1 (C), and al m m Ccl8 (D) as determined on 0.5 cm 1.0 cm by ELISA in a set of mouse 0.5 cm 1.0 cm plasmas independent of those Preclinica Preclinical Regressio used for LC/MS-MS experiments. Regression For each time point, n ¼ 6 controls C Timp1 D Ccl8 n ¼ and 6 cases. Statistical 8 1,000 * significance was determined by * *** 2-tailed Student's t test. *** 800 *, P < 0.05; **, P < 0.01; and 6 ***, P < 0.0001. 600 4 P ng/mL ng/mmL 400 * = 0.16 2 *** P = 0.81 200

0 0 0.5 cm 1.0 cm 0.5 cm 1.0 cm Preclinical Preclinical Regression Regression

platforms (Supplementary Fig. S5). Thus, 2 different antibody- We used several methods to ascertain the specificity and based methods confirmed the LC/MS-MS results. Collectively, tissue(s) of origin of the plasma protein signature that these results illuminate the dynamic changes in the plasma occurred in the context of breast tumor development. First, proteome that track tumor evolution. comparisons with mouse models of inflammation and angiogenesis were used to identify those proteins that were Discussion not cancer specific. Approximately 25% of the elevated and 50% of the reduced proteins overlapped between tumor and The cancer-associated plasma proteome is derived confounder plasma proteomes. This indicates that the from the developing tumor, the tumor proteins that decrease in abundance in tumor-bearing mice microenvironment, and host tissues aremorelikelyattributabletoahostresponsethatisnot In this study, we present a dynamic analysis of the plasma specific to cancer. In the future, analysis of other confoun- proteome that accompanies HER2/neu-induced mammary der models such as wound-healing or tissue-specific inflam- tumor establishment, malignant progression, and regression. matory conditions will be useful to further refine the Our findings show that the plasma proteome increasingly cancer-specific signature. Second, we compared plasma deviates from normal as tumors develop and progress. This proteins identified in tumor-bearing mice to proteomic presented as an escalation in the total number of altered and gene expression analyses of human breast cancer cells proteins as well as a progressive increase or decrease in the and HER2/neu-induced breast tumors. Among all the pro- relative abundance of a number of specific proteins with teins that were increased in plasma from tumor-bearing advancing tumor stage. Most of these tumor-associated pro- mice, more than half were identified in the proteomic tein changes rapidly reverted upon oncogene downregulation profiling of human breast cancer cell lines and approxi- and incipient tumor regression. Thus, the plasma proteome mately 80% of this concordant set showed a corresponding responds very early, that is, shortly after tumor induction, increase in gene expression in HER2/neu breast tumors. changes both qualitatively and quantitatively during tumor Third, a subset of those proteins found to be altered in the progression, and rapidly reverts to normal following oncogene plasma of tumor-bearing mice was expressed in tumor cells downregulation and tumor regression. as detected by IHC. These findings point to the tumor itself

www.aacrjournals.org Cancer Res; 71(15) August 1, 2011 5097

Pitteri et al.

as the likely source of a subset of proteins found to be and lipocalin 2, were increased. Many of these proteins altered in plasma. In addition to the secretion of proteins by were elevated even at the earliest tumor stage and progres- tumor cells, tumor cell lysis may also lead to detectable sively increased in abundance with tumor growth. Once levels of cancer-specific proteins in the blood. Finally, recruited to the tumor site, tumor-associated macrophages microarray gene expression analysis of known inflammatory (TAM) secrete Mmp2, Mmp9, TGFb, cathepsins, and other proteins identified a correlation between protein levels in factors that degrade and remodel matrix (36) as well as plasma and gene expression in distal immunologic tissues promote angiogenesis, tumor cell invasion, and metastasis such as thymus and spleen. Collectively, these findings show (37). Our analysis showing elevated plasma levels of Mmp9, that changes in the plasma proteome that arise during Ctsb, and numerous stromal components associated with cancer development derive from multiple sources: nonspe- TAMs extends the reach of this network to the organismal cific systemic reactions, for example, acute-phase proteins level. such as those produced by the liver; other host responses Cancer-associated fibroblasts (CAF) are another signifi- thataremorespecifictobreastcancer,butnotdirectly cant component of the HER2/neu mammary tumor micro- tumor derived, for example, proteins involved in immune environment (Fig. 5). These "activated" fibroblasts express cell recruitment and signaling, and metabolic pathways; smooth muscle actin (38) and support tumor growth, and proteins that originate directly from the tumor and deposit ECM, and promote an inflammatory response by the local microenvironment (Fig. 5). Some proteins are secreting factors such as collagens, tenascin C, Mmps, and expressed in multiple tissues (e.g., S100a9, Lcn2, metabolic, chemokines (2, 3). Tumor cells, in turn, must reorganize and other housekeeping proteins) and unambiguous ascer- cytoskeletal structures, break down the basement mem- tainment of tissue of origin is more difficult. brane, and degrade ECM components to invade, intrava- sate, and metastasize. The levels of many proteins related Plasma proteome dynamics reflect breast cancer to these processes, including ECM, stromal, and cytoske- biology letal proteins, were increased in plasma, particularly from After only 5 weeks of HER2/neu oncogene activity, mice with late-stage tumors. Together this shows that, in extensive neoplastic changes were noted throughout the addition to nonspecific host response proteins and tumor- mammary ductal tree. Although the lesions were clinically derived proteins, alterations in signaling and effector path- undetectable, significant changes in the plasma proteome ways regulating tumor–TAM and tumor–CAF interactions were already apparent, and these reflected acute-phase are prominent features of the cancer-associated plasma responses, macrophage and neutrophil trafficking, ECM proteome. These features bear similarities to a wound remodeling, metabolism, and potentially tumor-derived response (39), which has recently been described to parallel proteins. A significant fraction of these early plasma tumor initiation (40), and indicate the extent to which proteome alterations were not seen in models of inflam- the tumor co-opts these host responses. This establishes mation and so are more likely to be associated with early- the plasma proteome as a sensitive biomonitor of the stage cancer. A number of the candidate tumor-derived ongoing interaction between the developing tumor and proteins, such as Igfbp5, Ltf, Timp1, Lgals1, Mmp9, Vwf, the host. Calr, and Pdlim1, that were increased in preclinical plasma Altered plasma levels of enzymes involved in glucose, lipid, were also seen in tumor sections and/or breast cancer cell and amino acid metabolism were observed at all 3 tumor linesbasedonIHCorgeneexpressionchanges.Asubsetof stages. Liver transcriptional profiling identified altered expres- thesewasconfirmedtobeelevatedinplasmafromother sion of similar metabolic enzymes in case versus control mice cohorts of mice and by independent antibody-based meth- (34), indicating the presence of a tumor triggers systemic ods. Furthermore, the plasma levels of some of these metabolic dysregulation, and this initiates very early during proteins increased with tumor size and rapidly fell after tumor establishment. It will be interesting to determine the oncogene de-induction, indicating they effectively track mechanistic similarities between this response and cachexia, tumor growth. This establishes both the sensitivity of which is an altered systemic metabolic response to the pre- our method to detect tumor-associated proteins very early sence of late-stage cancer (41). intheneoplasticprocessand also the ability to monitor In summary, this study highlights the value of integrating protein levels over the course of tumor development and in-depth proteomic, transcriptomic, and tissue-wide during tumor regression. approaches as a means to illuminate the systems biology Notable histopathologic changes that occurred during of cancer. The identification of plasma protein networks and tumor progression included extensive remodeling of the transcriptional responses in distal normal tissues of tumor- tumor microenvironment, in particular, recruitment of bearing mice indicates the host senses and responds to immune cells, including T and B cells, macrophages, and neoplastic growth to a greater degree than previously appre- neutrophils. This presentation resembles a wound bed and ciated. The developing tumor simultaneously engages a implies that the tumors actively attract these cells from the number of innate physiologic processes including wound circulation. In support of this conclusion, plasma levels of repair, the immune system, the blood coagulation and multiple macrophage signaling proteins, including mono- complement cascades, and metabolic homeostasis. This cyte chemoattractant proteins (Mcps), macrophage inflam- extensive conversation initiates very early, involves many matory proteins (Mip), and other chemokines, calgranulins, cell types and tissues, accurately tracks tumor development

5098 Cancer Res; 71(15) August 1, 2011 Cancer Research

The Cancer-Associated Plasma Proteome

over time, and mirrors the underlying biology. Further Acknowledgments mining of the cancer-associated plasma proteome and other host tissue responses will likely identify additional regula- The authors thank the Allen Foundation Biomarker Project team, Drs. Aebersold, Anderson, Diamandis, and Smith for advice. tors, mediators, and biomarkers of the evolving tumor, its microenvironment, and the systemic response to cancer. Grant Support Extension of this approach to other models of cancer as well as human studies will establish its utility for early detection, This work was funded by the Paul G. Allen Family Foundation, NCI Mouse diagnosis, and prognosis. Models of Human Cancer Consortium, and Canary Foundation. The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in Disclosure of Potential Conflicts of Interest accordance with 18 U.S.C. Section 1734 solely to indicate this fact. Received February 21, 2011; revised April 27, 2011; accepted May 23, 2011; No potential conflicts of interest were disclosed. published OnlineFirst June 8, 2011.

References 1. Polyak K, Kalluri R. The role of the microenvironment in mammary open-source analytic system for evaluating and publishing proteomic gland development and cancer. Cold Spring Harb Perspect Biol data and high throughput biological experiments. J Proteome Res 2010;2:a003244. 2006;5:112–21. 2. Kalluri R, Zeisberg M. Fibroblasts in cancer. Nat Rev Cancer 19. Craig R, Beavis RC. TANDEM: matching proteins with tandem mass 2006;6:392–401. spectra. Bioinformatics 2004;20:1466–7. 3. Mueller MM, Fusenig NE. Friends or foes—bipolar effects of the 20. MacLean B, Eng JK, Beavis RC, McIntosh M. General framework for tumour stroma in cancer. Nat Rev Cancer 2004;4:839–49. developing and evaluating database scoring algorithms using the 4. Grivennikov SI, Greten FR, Karin M. Immunity, inflammation, and TANDEM search engine. Bioinformatics 2006;22:2830–2. cancer. Cell 2010;140:883–99. 21. Kersey PJ, Duarte J, Williams A, Karavidopoulou Y, Birney E, Apweiler 5. de Visser KE, Eichten A, Coussens LM. Paradoxical roles of the R. The International Protein Index: an integrated database for pro- immune system during cancer development. Nat Rev Cancer teomics experiments. Proteomics 2004;4:1985–8. 2006;6:24–37. 22. Keller A, Nesvizhskii AI, Kolker E, Aebersold R. Empirical statistical 6. Dunn GP, Old LJ, Schreiber RD. The immunobiology of cancer model to estimate the accuracy of peptide identifications made by immunosurveillance and immunoediting. Immunity 2004;21:137–48. MS/MS and database search. Anal Chem 2002;74:5383–92. 7. Mantovani A, Allavena P, Sica A, Balkwill F. Cancer-related inflamma- 23. Faca V, Coram M, Phanstiel D, Glukhova V, Zhang Q, Fitzgibbon M, tion. Nature 2008;454:436–44. et al. Quantitative analysis of acrylamide labeled serum proteins by 8. Hiratsuka S, Watanabe A, Sakurai Y, Akashi-Takamura S, Ishibashi S, LC-MS/MS. J Proteome Res 2006;5:2009–18. Miyake K, et al. The S100A8-serum amyloid A3-TLR4 paracrine 24. Faca VM, Ventura AP, Fitzgibbon MP, Pereira-Faca SR, Pitteri SJ, cascade establishes a pre-metastatic phase. Nat Cell Biol Green AE, et al. Proteomic analysis of ovarian cancer cells reveals 2008;10:1349–55. dynamic processes of protein secretion and shedding of extra-cellular 9. Kaplan RN, Riba RD, Zacharoulis S, Bramley AH, Vincent L, Costa C, domains. PLoS One 2008;3:e2425. et al. VEGFR1-positive haematopoietic bone marrow progenitors 25. Ong SE, Mann M. A practical recipe for stable isotope labeling by initiate the pre-metastatic niche. Nature 2005;438:820–7. amino acids in cell culture (SILAC). Nat Protoc 2006;1:2650–60. 10. Wels J, Kaplan RN, Rafii S, Lyden D. Migratory neighbors and distant 26. Bailey SL, Gurley KE, Hoon-Kim K, Kelly-Spratt KS, Kemp CJ. Tumor invaders: tumor-associated niche cells. Genes Dev 2008;22:559–74. suppression by p53 in the absence of Atm. Mol Cancer Res 11. Faca VM, Song KS, Wang H, Zhang Q, Krasnoselsky AL, Newcomb 2008;6:1185–92. LF, et al. A mouse to human search for plasma proteome changes 27. Le XF, Arachchige-Don AS, Mao W, Horne MC, Bast RC Jr. Roles of associated with pancreatic tumor development. PLoS Med 2008;5: human epidermal growth factor receptor 2, c-jun NH2-terminal kinase, e123. phosphoinositide 3-kinase, and p70 S6 kinase pathways in regulation 12. Hanash SM, Pitteri SJ, Faca VM. Mining the plasma proteome for of cyclin G2 expression in human breast cancer cells. Mol Cancer Ther cancer biomarkers. Nature 2008;452:571–9. 2007;6:2843–57. 13. Kelly-Spratt KS, Kasarda AE, Igra M, Kemp CJ. A mouse model 28. Yang S, Raymond-Stintz MA, Ying W, Zhang J, Lidke DS, Steinberg repository for cancer biomarker discovery. J Proteome Res SL, et al. Mapping ErbB receptors on breast cancer cell membranes 2008;7:3613–8. during signal transduction. J Cell Sci 2007;120:2763–73. 14. Hung KE, Faca V, Song K, Sarracino DA, Richard LG, Krastins B, et al. 29. Lwin ZM, Guo C, Salim A, Yip GW, Chew FT, Nan J, et al. Clinico- Comprehensive proteome analysis of an Apc mouse model uncovers pathological significance of calreticulin in breast invasive ductal proteins associated with intestinal tumorigenesis. Cancer Prev Res carcinoma. Mod Pathol 2010;23:1559–66. (Phila) 2009;2:224–33. 30. Mackay A, Jones C, Dexter T, Silva RL, Bulmer K, Jones A, et al. cDNA 15. Moody SE, Sarkisian CJ, Hahn KT, Gunther EJ, Pickup S, Dugan KD, microarray analysis of genes associated with ERBB2 (HER2/neu) et al. Conditional activation of Neu in the mammary epithelium of overexpression in human mammary luminal epithelial cells. Oncogene transgenic mice results in reversible pulmonary metastasis. Cancer 2003;22:2680–8. Cell 2002;2:451–61. 31. Paz A, Haklai R, Elad-Sfadia G, Ballan E, Kloog Y. Galectin-1 binds 16. Cardiff RD, Anver MR, Gusterson BA, Hennighausen L, Jensen RA, oncogenic H-Ras to mediate Ras membrane anchorage and cell Merino MJ, et al. The mammary pathology of genetically engineered transformation. Oncogene 2001;20:7486–93. mice: the consensus report and recommendations from the Annapolis 32. Gebhardt C, Nemeth J, Angel P, Hess J. S100A8 and S100A9 in meeting. Oncogene 2000;19:968–88. inflammation and cancer. Biochem Pharmacol 2006;72:1622–31. 17. Pitteri SJ, Faca VM, Kelly-Spratt KS, Kasarda AE, Wang H, Zhang Q, 33. Kelly-Spratt KS, Pitteri SJ, Gurley KE, Liggitt D, Chin A, Kennedy J, et al. Plasma proteome profiling of a mouse model of breast cancer et al. Plasma proteome profiles associated with inflammation, angio- identifies a set of up-regulated proteins in common with human breast genesis, and cancer. PLoS One 2011;6:e19721. cancer cells. J Proteome Res 2008;7:1481–9. 34. Schoenherr RM, Kelly-Spratt KS, Lin C, Whiteaker JR, Liu T, Holzman 18. Rauch A, Bellew M, Eng J, Fitzgibbon M, Holzman T, Hussey P, et al. T, et al. Proteome and transcriptome profiles of a Her2/Neu-driven Computational proteomics analysis system (CPAS): an extensible, mouse model of breast cancer. Proteomics Clin Appl 2011;5:179–88.

www.aacrjournals.org Cancer Res; 71(15) August 1, 2011 5099

Pitteri et al.

35. Michlmayr A, Bachleitner-Hofmann T, Baumann S, Marchetti-Desch- stromal myofibroblasts of normal and malignant human breast tissue. mann M, Rech-Weichselbraun I, Burghuber C, et al. Modulation of Proc Natl Acad Sci U S A 1993;90:999–1003. plasma complement by the initial dose of epirubicin/docetaxel therapy 39. Troester MA, Lee MH, Carter M, Fan C, Cowan DW, Perez ER, et al. in breast cancer and its predictive value. Br J Cancer 2010;103: Activation of host wound responses in breast cancer microenviron- 1201–8. ment. Clin Cancer Res 2009;15:7020–8. 36. Kessenbrock K, Plaks V, Werb Z. Matrix metalloproteinases: regula- 40. Feng Y, Santoriello C, Mione M, Hurlstone A, Martin P. Live imaging of tors of the tumor microenvironment. Cell 2010;141:52–67. innate immune cell sensing of transformed cells in zebrafish larvae: 37. Qian BZ, Pollard JW. Macrophage diversity enhances tumor progres- parallels between tumor initiation and wound inflammation. PLoS Biol sion and metastasis. Cell 2010;141:39–51. 2010;8:e1000562. 38. Lazard D, Sastre X, Frid MG, Glukhova MA, Thiery JP, Koteliansky VE. 41. Tayek JA. A review of cancer cachexia and abnormal glucose meta- Expression of smooth muscle-specific proteins in myoepithelium and bolism in humans with cancer. J Am Coll Nutr 1992;11:445–56.

5100 Cancer Res; 71(15) August 1, 2011 Cancer Research

Tumor Microenvironment−Derived Proteins Dominate the Plasma Proteome Response during Breast Cancer Induction and Progression

Sharon J. Pitteri, Karen S. Kelly-Spratt, Kay E. Gurley, et al.

Cancer Res 2011;71:5090-5100. Published OnlineFirst June 8, 2011.

Updated version Access the most recent version of this article at: doi:10.1158/0008-5472.CAN-11-0568

Supplementary Access the most recent supplemental material at: Material http://cancerres.aacrjournals.org/content/suppl/2011/06/08/0008-5472.CAN-11-0568.DC1

Cited articles This article cites 41 articles, 8 of which you can access for free at: http://cancerres.aacrjournals.org/content/71/15/5090.full#ref-list-1

Citing articles This article has been cited by 3 HighWire-hosted articles. Access the articles at: http://cancerres.aacrjournals.org/content/71/15/5090.full#related-urls

E-mail alerts Sign up to receive free email-alerts related to this article or journal.

Reprints and To order reprints of this article or to subscribe to the journal, contact the AACR Publications Department at Subscriptions [email protected].

Permissions To request permission to re-use all or part of this article, use this link http://cancerres.aacrjournals.org/content/71/15/5090. Click on "Request Permissions" which will take you to the Copyright Clearance Center's (CCC) Rightslink site.