Local iron homeostasis in the breast ductal carcinoma microenvironment

RESEARCH ARTICLE Open Access Local iron homeostasis in the breast ductal carcinoma microenvironment Oriana Marques 1,2,3,4* , Graça Porto 2,5 , Alexandra Rêma 2 , Fátima Faria 2 , Arnaud Cruz Paula 2,6 , Maria Gomez-Lazaro 4,7 , Paula Silva 4,8,9 , Berta Martins da Silva 1,2 and Carlos Lopes 2,6 Abstract Background: While the deregulation of iron homeostasis in breast epithelial cells is acknowledged, iron-related alterations in stromal inflammatory cells from the tumor microenvironment have not been explored. Methods: Immunohistochemistry for hepcidin, ferroportin 1 (FPN1), transferrin receptor 1 (TFR1) and ferritin (FT) was performed in primary breast tissues and axillary lymph nodes in order to dissect the iron-profiles of epithelial cells, lymphocytes and macrophages. Furthermore, breast carcinoma core biopsies frozen in optimum cutting temperature (OCT) compound were subjected to imaging flow cytometry to confirm FPN1 expression in the cell types previously evaluated and determine its cellular localization. Results: We confirm previous results by showing that breast cancer epithelial cells present an ‘iron-utilization phenotype’with an increased expression of hepcidin and TFR1, and decreased expression of FT. On the other hand, lymphocytes and macrophages infiltrating primary tumors and from metastized lymph nodes display an ‘irondonor’phenotype, with increased expression of FPN1 and FT, concomitant with an activation profile reflected by a higher expression of TFR1 and hepcidin. A higher percentage of breast carcinomas, compared to control mastectomy samples, present iron accumulation in stromal inflammatory cells, suggesting that these cells may constitute an effective tissue iron reservoir. Additionally, not only the deregulated expression of iron-related proteins in epithelial cells, but also on lymphocytes and macrophages, are associated with clinicopathological markers of breast cancer poor prognosis, such as negative hormone receptor status and tumor size. Conclusions: The present results reinforce the importance of analyzing the tumor microenvironment in breast cancer, extending the contribution of immune cells to local iron homeostasis in the tumor microenvironment context. Keywords: Breast cancer, Ferroportin 1, Iron, Stromal inflammatory cells, Tissue microenvironment Background Breast cancer ranks as the most frequent neoplasia and cause of cancer death, in spite of growing advances in early diagnosis and novel therapy regimens [1]. A change in this scenario demands a better understanding of the cellular and molecular processes involved in breast cancer development and progression. As a fundamental element involved in cell metabolism, division and proliferation, iron has been implicated as an important player in cancer development [2]. The argument that iron may promote the development of breast cancer is supported by animal studies consistently demonstrating that iron-rich diets or iron injected subcutaneously favors breast cancer progression at several stages [3–6]. From the cell biology perspective, it is now well accepted that the malignant state in breast epithelial cells is characterized by a deregulation in cellular iron homeostasis, as revealed by differences in the expression of several iron-related proteins relating with markers of poor outcome [7–11]. Particularly, a marked decrease in the levels of the iron exporter ferroportin 1 is observed * Correspondence: [email protected] 1 Laboratory of Immunogenetics –Autoimmunity and Neurosciences, Unit for Multidisciplinary Biomedical Research (UMIB), Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Rua Jorge Viterbo Ferreira 228,Edif 2 Piso 4, P-4050313 Porto, Portugal 2 Pathology and Molecular Immunology Department, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Porto, Portugal Full list of author information is available at the end of the article © 2016 Marques et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Marques et al. BMC Cancer (2016) 16:187 DOI 10.1186/s12885-016-2228-y both in breast cancer tissue and cancer cell lines with a higher malignancy potential, denoting the relative “irondeficient”phenotype compatible with their increased proliferative status [12, 13]. In spite of the known impact of genetic and epigenetic changes of breast epithelial cells in tumor progression, it is acknowledged that these are not sufficient for the acquisition of a fully malignant and invasive potential [14–16]. Stromal inflammatory cells, which are present in the breast tissue even before malignant transformation, may also induce alterations in the breast microenvironment that ultimately can drive tumorigenesis [17, 18]. Pioneering studies by De Sousa and co-workers have shown that lymphocytes and macrophages are capable of synthesizing and secreting ferritin [19, 20]. More recent work by Alkhateeb and coworkers not only confirmed that breast cancerassociated macrophages secrete ferritin, particularly in response to pro-inflammatory cytokines, but also that extracellular ferritin stimulates the proliferation of breast cancer cells [21]. Also, Jezequel and co-workers have described ferritin light-chain expression in tumorassociated macrophages with an M2-like phenotype and validated it as a prognostic biomarker in node-negative breast cancer patients [22]. Of note, in vitro M2 polarized macrophages present an iron-release prone phenotype, with higher transferrin receptor 1 and ferroportin 1 expression than classically activated M1 macrophages, which is thought to contribute to its iron recycling function as scavengers of senescent and apoptotic cells and in tissue remodeling [23, 24]. To our knowledge, the expression of ferroportin 1 in breast cancer tumorassociated lymphocytes and macrophages has never been addressed before. In the present study we analyzed the iron-profiles of epithelial cells, lymphocytes and macrophages in normal human breast and ductal carcinoma samples and assessed their association with clinicopathological markers of cancer progression and behavior. With this approach we reinforce the evidence that favors the contribution of stromal inflammatory cells to breast tumor microenvironment while highlighting the potential role of lymphocytes and macrophages in the regulation of local iron homeostasis. Methods Sample characterization Selected and stored human breast tissue samples referred for histological analysis at the Pathology Service at Centro Hospitalar do Porto (between 2004 and 2009), were re-analyzed. We selected 131 samples corresponding to 58 cases of invasive ductal carcinomas (IDC), 16 cases of ductal carcinomas in situ (DCIS) and 57 samples without evidence of breast disease obtained from breast reduction aesthetic surgery, as controls. Axillary lymph node samples from 14 non-metastized and 12 metastized IDC were randomly selected from the initial cohort and analyzed. In addition, 6 frozen core biopsy samples, collected in 2013, from patients with invasive ductal carcinomas from which written informed consent was obtained, were selected for imaging flow cytometry studies. Pathological and clinical features, including histological diagnosis, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor 2 (HER-2) status and peripheral white blood cell (WBC) count data were available from the interin pathology reports. ER, PR and HER-2 status were assessed by immunohistochemistry, as routinely done in the Pathology Service. HER-2 ambiguous results were confirmed by FISH. Tissue microarray construction Formalin-fixed paraffin-embedded (FFPE) tissue blocks and hematoxylin and eosin (H&E)-stained slides were retrieved from the archive and re-evaluated by an experienced pathologist (CL). Representative areas from normal breast epithelium, ductal carcinoma in situ and invasive ductal carcinoma lesions were selected, marked on the H&E slides and then sampled into the tissue microarray (TMA) collector blocks. Most selected lesions corresponded to “pure”DCIS or IDC lesions, i.e., from samples with the corresponding classification. Whenever possible, non-malignant and DCIS lesions were also selected from invasive ductal carcinoma cases. Two tissue cores from human donor liver samples were also included in each tissue microarray block, as positive controls. A total of 452 FFPE 2 mm breast tissue cores were used for the tissue microarray construction from which 405 were assessable. 2 μm-thick TMA sections were cut in a microtome and H&E stained. Histologically, each core was classified by the pathologist without previous knowledge of the type of donor sample. Cores with ‘normal’breast histology retrieved from DCIS or IDC samples were further classified as ‘normal in DCIS’ and ‘normal in IDC’, respectively. Representative areas with malignant lesions from DCIS and IDC were classified as DCIS “pure lesions”or IDC “pure lesions”, respectively. DCIS cores retrieved from IDC samples, without signs of invasion, were classified as DCIS in IDC. The numbers of cores included for each histological type and type of donor sample are summarized in Table 1. Immunohistochemistry Immunohistochemical staining was performed in 2 μmthick TMA sections with the following antibodies: rabbit polyclonal anti-human hepcidin-25 antibody (dilution 1:500, Abcam, Cambridge, UK [25]), rabbit polyclonal anti-human ferroportin 1 antibody (FPN—1:500, Novus Marques et al. BMC Cancer (2016) 16:187 Page 2 of 14 Biologicals Europe, Cambridge, UK [26]), rabbit polyclonal anti-human ferritin antibody (FT—1:1000, SigmaAldrich, MO, USA [27]), mouse monoclonal anti-human CD71 (TFR1 [clone 10 F11]- 1:80, Novocastra, Newcastle, UK [28]), mouse monoclonal anti-human CD68 (clone Kp-1, 1:2000, A. Menarini Diagnostics, CA, USA), mouse monoclonal anti-human CD163 (clone MRQ-26, 1:100, Cell Marque, CA, USA), mouse monoclonal antihuman CD80 (37711, 1:100, R&D Systems, MN, USA), rabbit polyclonal anti-human CD4 (clone H-370, 1:250, Santa Cruz Biotechnology, TX, USA) and mouse monoclonal anti-human CD8 (clone C8/144B, 1:100, Cell Marque, CA, USA). The sections were deparaffinized twice in xylene, rehydrated in decreasing concentrations of ethanol and washed in water. Heat-mediated antigen target retrieval was done with DakoTarget Retrieval Solution (Agilent Technologies, Denmark). Immunohistochemistry was performed according to Novolink Polymer Detection kit procedures (Leica, Biosystems, Cambridge, UK). Enzyme reactivity was visualized using 3,3′-Diaminobenzidine tetrahydrochloride (DAB, SigmaAldrich, MO, USA) and slides were counterstained with Mayers hemalum solution (Merck Millipore, Darmstadt, Germany), dehydrated and mounted with Entellan (Merck Millipore, Darmstadt, Germany). The reaction obtained in all samples was observed in a Leica DM LB microscope. Each antibody optimum dilution was determined in a tissue positive control. Slides with replacement of the primary antibody with an antibody of the same immunoglobulin isotype were integrated in each experiment as negative labeling controls. A section of liver tissue from a HAMP (hepcidin) KO mouse was also included as a hepcidin negative control. Staining criteria Tissue specimens from normal control, DCIS and IDC samples were immunostained for hepcidin, ferroportin (FPN1), transferrin receptor 1 (TFR1) and ferritin (FT) proteins and their cellular localization examined in epithelial cells (Hepcidin, n= 323; FPN1, n= 315; TFR1, n=308; FT, n= 325), lymphocytes (Hepcidin, n=175; FPN1, n= 174; TFR1, n=177; FT, n= 244) and macrophages (Hepcidin, n= 173; FPN1, n= 150; TFR1, n=178; FT, n= 245). A semi-quantitative evaluation method was applied as follows: the score obtained by the percentage of positive cells (0 % = 0 points; 1– 10 % = 1 point:, 11–20 % = 2 points:, 21–35 % = 3 points:, 36–50 % = 4 points: and >50 % = 5 points) was multiplied by the score obtained by the staining intensity (no staining = 0 points, weak staining = 1 point, moderate staining = 2 points and strong staining=3points).Weareawarethatthistypeofscoring results in a higher number of area groups. However, we considered that grouping the area percentages in groups with higher intervals would also introduce high variation inside each group. Cores from the same donor tissue diagnosed with the same histological type were grouped and their mean score calculated. Lymph node iron-related proteins immunoexpression assessment was done in B cell and T cell areas and in macrophages. Scores ranged from 0 to 3, where 0 was considered absence of immunoexpression, 1, low expression, 2, moderate expression, and 3, high expression of the correspondent ironrelated protein. Perls’Prussian blue staining Hemosiderin deposits were detected by the routine technique of Prussian blue histochemical staining. Briefly, after deparaffinization and rehydration in the ethanol series, sections were immersed in a mixture of equal volumes of potassium ferrocyanide solution and hydrochloric acid solution, both at 2 %. Counterstaining was achieved with nuclear fast red (Merck Millipore, Darmstadt, Germany). The absence or presence of hemosiderin deposits was evaluated in epithelial and stromal inflammatory cells. Imaging flow cytometry OCT-embedded frozen samples from 6 core biopsies were cut in a cryostat and H&E stained for pathological assessment of malign disease. After thawing, biopsies were gently removed with a scalpel and allowed to mechanically disaggregate with the help of forceps. Cells were resuspended in 2 % BSA (Bovine Serum Albumin, Merck Millipore, Darmstadt, Germany) in PBS, and set for staining in a 96-well standard microplate. A Neubauer counting chamber was used in order to count and stain 1 × 10 6 cells in every assay. After centrifugation at 2000 rpm and resupension in 0.2 % BSA in PBS, cells were incubated with mouse monoclonal anti-human cytokeratin FITC ([clone 1B3] IOTest, Beckman Coulter, Madrid, Spain), mouse monoclonal anti-human CD68 PE-Cy7 ([clone Y1/82A] eBioscience Affymetrix, CA, USA), mouse monoclonal anti-human CD3 PerCP-Cy5.5 ([clone SK7] BD, Madrid, Spain), rabbit polyclonal antihuman FPN PE (Novus Biologicals Europe, Cambridge, Table 1 Number of spots included in TMA receiver blocks Tissue sample Type of core No. of cores in TMA blocks Control Normal Samples Normal 119 DCIS Normal in DCIS 12 DCIS pure lesion 54 IDC Normal in IDC 61 DCIS in IDC 39 IDC pure lesion 120 Abbreviations:TMA Tissue Microarray, DCIS Ductal Carcinoma In Situ,IDC Invasive Ductal Carcinoma Marques et al. BMC Cancer (2016) 16:187 Page 3 of 14 UK), mouse monoclonal anti-human CD20 PE-Cy7 ([clone B9E9] IOTest, Beckman Coulter, Madrid, Spain) and FPN PE (Novus Biologicals Europe, Cambridge, UK) [staining 2]. Cells were washed with 0.2 % BSA in PBS and centrifuged at 2000 rpm prior to fixation with Fixation Medium from Fix & Perm Cell Fixation and Permeabilization Kit (Life Technologies, CA, USA) and then resuspended in 0.2 % BSA in PBS for analysis. Single-stained and unstained cells were used as controls. Data were acquired in an imaging flow cytometer (ImageStream®, Amnis, EDM Millipore, Darmstadt, Germany) using a 488 nm laser. Images and data were acquired using INSPIRE Software v4.0 (Amnis, EDM Millipore, Darmstadt, Germany). Brightfield was detected on channel 1, FITC on channel 2, PE on channel 3, PerCP-Cy5.5 on channel 5 and PE-Cy7 on channel 6. A total of 100 μL was loaded per sample and 8000 events meeting the cell classifier were acquired at a 40× magnification (image pixel 0.5 μm 2 ). Compensation and analysis were performed in IDEAS v6.0.348 software (Amnis, EDM Millipore, Darmstadt, Germany). Data was compensated through a matrix created based on the single-stained cell controls. A hierarchical gating strategy was created in the software in order to identify breast epithelial cells, lymphocytes and macrophages. Briefly, first focused cells were selected (gradient root mean square of the brightfield) followed by gating on single-cells (brightfield area vs aspect ratios). T-Lymphocytes were then selected on an Intensity_CD3 PerCP-Cy5.5 vs Area on Channel 1 plot, B Lymphocytes on an Intensity_CD20 PE-Cy7 vs Area on Channel 1 plot, macrophages on an Intensity_CD68 PECy7 vs Area on Channel 1 plot and finally epithelial cells on an Intensity_cytokeratin FITC vs Area on Channel 1. Gated cells were excluded from further analysis before selecting the next population. FPN1 intensity in the cell membrane and cytoplasm wasmeasuredthroughthe creation of masks defining the total area of the cell and then the correspondent cytoplasm by eroding the cell membrane in channel 1 (cell membrane = total cell—cytoplasm). Laser capture microdissection Six μm-thick sections from the axillary lymph nodes were cut and placed in PALM® 1.0 polyethylene naphthalate (PEN) membrane slides (Carl Zeiss MicroImaging GmbH, Germany). Before use, slides were treated with UV irradiation at 320 nm for 30 min as recommended by the manufacturer. Immediately prior to microdissection, slides were deparaffinized, rehydrated and stained with Mayers hemalum solution (Merck Millipore, Darmstadt, Germany). Lymphocyte and macrophage exclusive regions in metastized lymph nodes were selected, cut and catapulted into individual PALM® adhesive cap microcentrifuge tubes (Carl Zeiss MicroImaging GmbH, Germany). Microcentrifuge tubes with the areas of interest were transported on ice and RNA was extracted immediately. RNA extraction and real-time PCR Isolation of total RNA was performed with the Absolutely RNA FFPE kit (Agilent Technologies, California, USA), according to the manufacturers’protocol. Briefly, sections from each archival sample were deparaffinized and incubated overnight with a lysis buffer containing proteinase K and submitted to a series of washes-oncolumn until elution. Immediately after, 50 ng of RNA were reversed transcribed with Maxima First Strand cDNA Synthesis Kit (Thermo Fisher Scientific, MA, USA) in a total volume of 20 μL, according to the manufacturer’s protocol. Evaluation of FPN1 mRNA levels (Hs00221783_m1) was performed in a Rotor-Gene 6000 instrument (Qiagen, CA, USA) with a TaqMan® Probebased gene expression assay (Applied Biosystems, CA, USA). Reactions were carried out in triplicate and gene expression levels calculated relative to GUSB mRNA levels (Hs99999908_m1). Mean relative expression was calculated based on the formula ΔCt = Ct target gene—Ct endogenous control gene and fold change on 2 (ΔCt breast tumor samples –ΔCt normal breast samples) . Statistical analysis Sample distributions were compared using KruskalWallis or Mann-Whitney’s U tests. Pearson’s Chi-Square was used to evaluate the differences between categorical variables. The Spearman’s rank correlation coefficient was used to evaluate the relationship between variables. In figures, experimental errors are shown as one standard error of the mean. Data were analyzed in IBM SPSS Statistics 20.0 software and statistical significance was accepted at p< 0.05. Results Immunolocalization and relative expression of ironrelated proteins in breast tissue Immunolocalization of hepcidin, FPN1, TFR1 and FT was assessed in breast tissue samples of normal controls, DCIS and IDC cases. As seen in the representative images illustrated in Fig. 1, different staining patterns were apparent among sample types and, within samples, among the different cell types. Leukocyte infiltrate was much more pronounced in carcinoma than in normal mastectomy samples. Using the semi-quantitative data (described in Methods) obtained exclusively in representative cores of “pure”lesions, we assessed the expression of hepcidin, FPN1, TFR1 and FT in epithelial cells, lymphocytes and macrophage in normal and cancer (DCIS and IDC) breast tissue. The results are illustrated in Fig. 2. Marques et al. BMC Cancer (2016) 16:187 Page 4 of 14 Hepcidin Hepcidin expression was restricted to the cytoplasm in all cell types detected. Breast cancer epithelial cells (in DCIS and IDC) presented a significantly higher expression of hepcidin than in control normal samples (p< 0.001) (Fig. 2a). The pattern of differential expression was similar for the stromal inflammatory cells analyzed. Breast cancer infiltrating lymphocytes and macrophages also presented significantly higher expression of hepcidin (p=0.002 and p< 0.001, respectively) (Fig. 2b,c). Ferroportin 1 FPN1 expression in breast epithelial cells was mainly observed in the cytoplasm but, in some cases, also in the cell membrane. In lymphocytes and macrophages itcouldonlybedetectedinthecytoplasm.Regarding epithelial cells, no significant differences were observed for FPN1 expression between normal samples, DCIS and IDC (Fig. 2a). However, in breast carcinoma samples, lymphocytes and macrophages expressed significantly higher levels of FPN1 than in normal samples (p= 0.014 and p< 0.001, respectively) (Fig. 2b,c), with FPN1 expression in macrophages being higher in DCIS samples (p<0.01whencompared with IDC samples) (Fig. 2b). Samples with FPN1-expressing T-lymphocytes are composed by a combination of CD4 and CD8 cells (Fig. 3). Tissue section staining with CD68 (macrophage lineage marker), CD80 (M1-like) and CD163 (M2-like) led to the observation that while in normal samples the macrophage population comprises a combination of comparable numbers of cells expressing CD80 and CD163, in breast carcinoma samples this population is predominantly composed of CD163positive cells, and thus associated with an M2 (alternative) macrophage polarization phenotype (Fig. 4). Fig. 1 Hepcidin, FPN1, TFR1 and FT expression pattern in breast tissue. Representative images of Hepcidin, FPN1 (Ferroportin 1), TFR1 (Transferrin Receptor 1) and FT (Ferritin) immunostaining in normal breast, DCIS (ductal carcinoma in situ) and IDC (invasive ductal carcinoma). A section of human donor liver is also shown as a positive control. Tissue microarrays containing several samples of breast tissue and human donor liver were constructed, sectioned and subjected to immunohistochemistry, as described in materials and methods (Original magnification × 400). * and †are representative of epithelial cells and leukocyte infiltrate, respectively Marques et al. BMC Cancer (2016) 16:187 Page 5 of 14 Transferrin receptor 1 TFR1 expression was predominantly detected in the cytoplasm of all the cell types analyzed. Nonetheless, in epithelial cells of some breast carcinoma samples a clear membranar staining was also observed. TFR1 expression was significantly higher in epithelial cells, lymphocytes and macrophages from breast carcinoma samples (p< 0.001) in comparison with control normal samples (Fig. 2). Furthermore, TFR1 immunoexpression in infiltrating lymphocytes and macrophages was, as expected, higher in IDC samples (p< 0.01) when compared with DCIS (Fig. 2b,c). Ferritin FT expression was predominantly observed in the cytoplasm of epithelial cells, lymphocytes and macrophages. Fig. 2 Hepcidin/FPN1 and TFR1/FT phenotype dyads in breast tissue. A semi-quantitative method of assessing the immunoexpression in the TMA sections was applied by multiplying the area and intensity staining scores, as described in materials and methods. The scores ranged from 0 to 15. Graphs show Mean ± SEM. Significant differences are shown for comparison with the precedent group *p< 0.05, **p< 0.01, ***p< 0.001, Mann Whitney’s U test; aImmunoexpression score for breast epithelial cells in control normal samples, DCIS (ductal carcinomas in situ) and IDC (invasive ductal carcinomas) for hepcidin (n= 121), FPN1 (Ferroportin 1, n= 113), TFR1 (Transferrin Receptor 1, n= 119) and FT (Ferritin, n= 119); bImmunoexpression score for macrophages in control normal samples, DCIS (ductal carcinomas in situ) and IDC (invasive ductal carcinomas) for Hepcidin (n= 75), FPN1 (Ferroportin 1, n= 62), TFR1 (Transferrin Receptor 1, n= 73) and FT (Ferritin, n= 91); cImmunoexpression score for lymphocytes in control normal samples, DCIS (ductal carcinomas in situ) and IDC (invasive ductal carcinomas) for Hepcidin (n= 77), FPN1 (Ferroportin 1, n= 70), TFR1 (Transferrin Receptor 1, n= 73) and FT (Ferritin, n= 91) Fig. 3 FPN1-expressing leukocytes are composed by a mixture of CD4 and CD8 T-cells. Sections of normal breast tissue, DCIS (ductal carcinoma in situ) and IDC (invasive ductal carcinoma) to reveal the presence of CD4 and CD8 T cells, in FPN1-expressing leukocyte infiltrate. For details see Materials and Methods (Original magnification × 100upper FPN images, ×400CD4 and CD8 images) Marques et al. BMC Cancer (2016) 16:187 Page 6 of 14 Breast cancer epithelial cells presented a significantly lower expression of FT than normal samples (p< 0.001) (Fig. 2a). On the other hand, FT expression in breast cancer infiltrating lymphocytes was significantly higher than in normal samples (p< 0.001) (Fig. 2c). No significant differences were found regarding FT in macrophages, given that its expression was consistently high in all the samples analyzed (Fig. 2b). Nuclear FT staining in epithelial cells was also noted. FT staining was also present in tissue stromal fibers of some IDC cases. In agreement with these results, suggesting an effective iron ‘reservoir’in lymphocytes and macrophages, hemosiderin detection through Perls staining demonstrated that a significantly higher proportion of carcinoma cases, when compared with control normal samples, present hemosiderin deposits in stromal inflammatory (p= 0.002) and epithelial cells (p= 0.033) (Fig. 5). Comparative expression of iron-related proteins in pure DCIS lesions and DCIS in IDC We demonstrated that the deregulated expression of iron-related proteins in breast cancer is not restricted to the tumor cells, but extends to the lymphocytes and macrophages in the tumor microenvironment. Given the fact that FPN1 expression in macrophages is particularly Fig. 4 FPN1-expressing leukocytes in carcinomas are predominantly M2-like. Sections of normal breast tissue, DCIS (ductal carcinoma in situ) and IDC (invasive ductal carcinoma) to reveal the presence of cells of the macrophage lineage (CD68), and its classical polarization phenotypes, M1like (CD80) and M2-like (CD163), in FPN1-expressing leukocyte infiltrate. For details see Materials and Methods (Original magnification × 100upper CD68 images, ×400squared image series) Fig. 5 Breast cancer tissue presents a higher accumulation of iron than normal breast. aPercentage of normal and breast cancer samples presenting hemosiderin deposits in epithelial and stromal inflammatory cells; b-c Representative images of Perls’iron staining of a normal (b) and DCIS (c) sample, showing pronounced deposition of hemosiderin in stromal inflammatory cells (arrows) and to a lesser extent in ductal epithelial cells (asterisk) (Original magnification × 200, ×400) Marques et al. BMC Cancer (2016) 16:187 Page 7 of 14 high in pre-invasive stages (DCIS), we sought to verify if these iron-related phenotypes were specific of pure DCIS or if they could also be observed in DCIS lesions adjacent to invasive ductal carcinomas (DCIS in IDC). The results are illustrated in Fig. 6. Epithelial cells from DCIS pure lesions or from DCIS in IDC did not exhibit significant differences regarding the expression of the previously assessed iron-related proteins (Fig. 6a). Major differences were found, however, for tumor-associated lymphocytes and macrophages. Lymphocytes had a significantly higher expression of hepcidin (p= 0.030) and TFR1 (p= 0.011) in DCIS in IDC (Fig. 6c), while macrophages from DCIS pure lesions exhibited a higher expression of FPN1 than DCIS in IDC (p=0.036) (Fig. 6b). Imaging flow cytometry In order to confirm the expression of FPN1 in epithelial cells, lymphocytes and macrophages from breast carcinoma samples and further explore its cellular distribution we resourced to imaging flow cytometry to relatively quantify it and determine its localization. For that purpose, we used OCT-frozen tissue from 6 patients with invasive ductal carcinomas, and a panel of antibodies to identify epithelial cells, T and B lymphocytes and macrophages (described in Methods). Furthermore, a mask to identify specifically the cell membrane and cytoplasm was built in IDEAS v6.0.348 software to evaluate FPN1 expression in each cell compartment. The ratio between the median FPN1 intensity in the cytoplasm and membrane was calculated as a putative surrogate for the iron Fig. 6 Hepcidin/FPN1 and TFR1/FT phenotype dyads in ductal carcinoma in situ lesions (DCIS). A semi-quantitative method of assessing the immunoexpression in the TMA sections was applied by multiplying the area and intensity staining scores, as described in materials and methods. The scores ranged from 0 to 15. Graphs show Mean ± SEM. Significant differences are shown for comparison with the precedent group *p< 0.05, **p< 0.01, ***p< 0.001, Mann Whitney’s U test; aImmunoexpression score for breast epithelial cells in DCIS pure lesions and DCIS lesions in IDC for Hepcidin (n= 35), FPN1 (Ferroportin 1, n= 35), TFR1 (Transferrin Receptor 1, n= 32) and FT (Ferritin, n= 36); bImmunoexpression score for macrophages in DCIS pure lesions and DCIS lesions in IDC for Hepcidin (n= 28), FPN1 (Ferroportin 1, n= 27), TFR1 (Transferrin Receptor 1, n= 30) and FT (Ferritin, n= 33); cImmunoexpression score for lymphocytes in DCIS pure lesions and DCIS lesions in IDC for Hepcidin (n= 26), FPN1 (Ferroportin 1, n= 31), TFR1 (Transferrin Receptor 1, n= 30) and FT (Ferritin, n= 33) Marques et al. BMC Cancer (2016) 16:187 Page 8 of 14 export capacity of the cell. Representative images are shown in Fig. 7 and the results are summarized in Table 2. FPN1 expression could be detected by Imaging Flow Cytometry in epithelial cells, T lymphocytes, B lymphocytes and macrophages. Macrophages in breast cancer tissue presented the highest median fluorescence intensity of the cell types considered, as a confirmation of the results presented in Fig. 2b. The ratio between the median FPN1 intensity in the cytoplasm and membrane allowed us to notice that FPN1 expression was higher in the cytoplasm of all the cell types considered, when compared with the membrane. Lymph nodes Considering that the expression of iron-related proteins in lymphocytes and macrophages varied in different tumor microenvironments, we extended the observation to metastized and non-metastized lymph nodes from the original cohort of patients, whose primary tumors had been previously analyzed. Hepcidin, FPN1, TFR1 and FT immunoexpression were assessed in 14 non-metastized and 12 metastized lymph-nodes (Fig. 8) and semiquantitatively scored (Table 3). Hepcidin immunoexpression in lymph nodes was mostly restricted to macrophages and scarcely observed in lymphocytes. Metastized lymph nodes, however, presented a significantly higher immunoexpression of hepcidin in lymphocytes (B cell areas: p= 0.005; T cell areas: p= 0.018), than in non-metastized lymph-nodes. FPN1 was uniformly expressed in all the cell types. In lymph nodes with sinus histiocytosis, lymphocytes and macrophages had a tendency to lower FPN1 expression. Remarkably, lymphocytes in metastized lymph nodes expressed 1.80-fold more FPN1 than in non-metastized ones, particularly in areas adjacent to the metastasis (p= 0.002). Expression assessment at the mRNA level confirmed a 1.48-fold increase in FPN1 expression in leukocyte areas of metastized lymph nodes, comparing with non-metastized lymph nodes (p=0.057). TFR1 was mostly expressed in macrophages and germinal center cells, particularly in non-metastized lymph nodes (p= 0.026). TFR1 was seldom expressed in T-cell areas, with no significant differences observed between metastized and non-metastized lymph nodes. While the immunoexpression pattern of FT was similar to FPN1, a significantly higher expression of FT was observed for lymphocytes (p< 0.001), noted particularly near metastasis areas. Clinicopathological data The expression of iron-related proteins was finally correlated with clinicobiological markers of breast cancer behavior, specifically hormone receptor and HER2 status. Results of mean FPN1 expression values in epithelial cells and macrophages in DCIS and IDC lesions are shown in Table 4 in relation to the ER, PR and HER2 status. FPN1 expression in IDC lesions was significantly higher in ER negative (p= 0.018) and in HER2 positive cases (p= 0.001) in epithelial cells, whereas in DCIS lesions FPN1 expression was only associated with negative ER status in macrophages (p= 0.033). No associations were found between FPN1 expression and PR status. Regarding TFR1 expression, a significantly higher expression was seen in macrophages of negative PR DCIS cases (n= 15; p= 0.039) and in lymphocytes and macrophages of HER2 positive IDC cases (Ly: n= 79; p= 0.028; M0: n= 79; p= 0.003). A higher expression of FT in lymphocytes was observed in negative PR DCIS cases (n = 15; p= 0.029). All other comparisons were not statistically significant. We next analyzed the expression of these iron-related proteins in relation to local and metastatic tumor growth in invasive tumors (Table 5). Tumor size was positively correlated with TFR1 expression in all the cell types considered (EC: p= 0.027; r= 0.226; Ly: p= 0.041; r= 0.235; M0: p= 0.017; r= 0.274). Fig. 7 Representative images of the FPN1 analysis by Imaging Flow Cytometry in breast cancer core biopsies. Epithelial cells (EC) are stained by an anti-cytokeratin (CK) FITC. T lymphocytes (T Ly) were identifiable by CD3 PerCP-Cy5.5, B lymphocytes (B Ly) by CD20 PE-Cy7 and macrophages (M0) by CD68 PE-Cy7 (Original magnification × 400) Marques et al. BMC Cancer (2016) 16:187 Page 9 of 14