| Literature DB >> 25882816 |
Sébastien Tabariès1,2, Véronique Ouellet3, Brian E Hsu4,5, Matthew G Annis6,7, April A N Rose8,9, Liliane Meunier10, Euridice Carmona11, Christine E Tam12,13, Anne-Marie Mes-Masson14,15, Peter M Siegel16,17,18.
Abstract
INTRODUCTION: Breast cancer cells display preferences for specific metastatic sites including the bone, lung and liver. Metastasis is a complex process that relies, in part, on interactions between disseminated cancer cells and resident/infiltrating stromal cells that constitute the metastatic microenvironment. Distinct immune infiltrates can either impair the metastatic process or conversely, assist in the seeding, colonization and growth of disseminated cancer cells.Entities:
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Year: 2015 PMID: 25882816 PMCID: PMC4413545 DOI: 10.1186/s13058-015-0558-3
Source DB: PubMed Journal: Breast Cancer Res ISSN: 1465-5411 Impact factor: 6.466
Figure 1Gene expression profiling reveals distinct expression patterns associated with different metastatic 4T1 subpopulations. (A) Schematic depicting 4T1-derived breast cancer cell populations isolated from distinct metastatic sites. (B) To identify candidate genes that were differentially expressed among the isolated populations, each group (parental cell line and the explants derived from mammary fat pad (PE), bone, lung and liver metastases) was individually compared to all the other groups. A two-fold change cutoff was determined and 395 differentially expressed genes were selected using a nonparametric test coupled with a 5% false discovery rate. (C) A heatmap displaying the hierarchical clustering of isolated 4T1-derived cell populations using the 395 differentially expressed genes. Red color indicates those genes that are highly expressed and the green color denotes those genes that are underexpressed. The majority of cell populations clustered according to the site from which they were derived.
Differentially affected pathways by Ingenuity Pathway Analysis
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| 4.94E-06 | 7.18E-02 | VCAM1,SDC1,MMP3,MMP10,CLDN7,CCL5,CXCL5,IL18RAP,CXCL10,ITGB2,MMP9,CLDN3,MMP19 |
| Inhibition of matrix metalloproteases | 3.54E-05 | 1.50E-01 | SDC1,MMP3,RECK,MMP10,MMP9,MMP19 |
| MMP19 hepatic fibrosis/hepatic stellate cell activation | 8.91E-05 | 6.45E-02 | 02VCAM1,CTGF,FGFR1,PDGFRA,LBP,CCL5,PDGFC,MMP9,PGF,IL18RAP |
| Regulation of the epithelial-mesenchymal transition pathway | 1.81E-04 | 5.61E-02 | MAP2K6,CDH1,JAG2,WNT10B,ESRP2,FGFR1,PARD6G,JAG1,NOTCH1,MMP9,CLDN3 |
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| 2.09E-04 | 5.76E-02 | CXCL10,ITGB2,VCAM1,MMP3,MMP10,CLDN7,CCL5,CXCL5,MMP9,CLDN3,MMP19 |
| HIF1alpha signaling | 2.68E-04 | 7.14E-02 | MMP3,MMP10,PDGFC,LDHA,MMP9,LDHB,PGF,MMP19 |
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| 3.05E-04 | 1.19E-01 | B2M,PSMB9,HLA-B,PSMB8,TAP1 |
| Bladder cancer signaling | 5.99E-04 | 7.22E-02 | CDH1,MMP3,MMP10,PDGFC,MMP9,PGF,MMP19 |
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| 9.59E-04 | 4.44E-02 | ITGB2,GNB4,CDH1,ANGPT2,VCAM1,CCND2,MYL12B,PDGFC,MMP9,PGF |
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| 1.48E-03 | 4.76E-02 | ITGB2,VCAM1,EDIL3,MMP3,CD44,MMP10,CLDN7,MMP9,CLDN3,MMP19 |
| VDR/RXR activation | 1.63E-03 | 6.82E-02 | CXCL10,SPP1,GADD45A,SEMA3B,VDR,CCL5 |
| Pyruvate fermentation to lactate | 2.53E-03 | 2.22E-01 | LDHA,LDHB |
| ILK signaling | 3.47E-03 | 4.39E-02 | MAP2K6,ITGB2,PARVB,CDH1,VIM,PDGFC,MMP9,DSP,PGF |
| Pathogenesis of multiple sclerosis | 8.71E-03 | 2.00E-01 | CXCL10,CCL5 |
| Sphingosine-1-phosphate signaling | 8.97E-03 | 4.88E-02 | PLCD1,CASP12,CASP1,PDGFRA,CASP4,PDGFC |
| Axonal guidance signaling | 1.04E-02 | 2.90E-02 | WNT10B,BDNF,MMP10,ADAMTS9,PDGFC,SEMA4C,PGF,PLCD1,GNB4,MYL12B,BMP7,SEMA3B,MMP9,SEMA7A |
| Atherosclerosis signaling | 1.39E-02 | 4.35E-02 | ITGB2,VCAM1,MMP3,S100A8,PDGFC,MMP9 |
| Sorbitol degradation I | 1.62E-02 | 2.00E-01 | SORD |
| Asparagine biosynthesis I | 1.62E-02 | 1.25E-01 | ASNS |
| Alanine biosynthesis III | 1.62E-02 | 3.33E-01 | NFS1 |
| Colorectal cancer metastasis signaling | 1.73E-02 | 3.36E-02 | GNB4,CDH1,WNT10B,MMP3,MMP10,PDGFC,MMP9,PGF,MMP19 |
| p53 signaling | 1.75E-02 | 4.63E-02 | TP53INP1,CCND2,GADD45A,PLAGL1,SFN |
| Role of IL-17A in psoriasis | 1.81E-02 | 1.43E-01 | S100A8,CXCL5 |
| Chondroitin sulfate degradation (metazoa) | 2.09E-02 | 8.70E-02 | CD44,HEXA |
| Human embryonic stem cell pluripotency | 2.19E-02 | 3.73E-02 | WNT10B,BDNF,FGFR1,PDGFRA,BMP7,PDGFC |
| Notch signaling | 2.33E-02 | 6.98E-02 | JAG2,JAG1,NOTCH1 |
| Dermatan sulfate degradation (metazoa) | 2.38E-02 | 8.70E-02 | CD44,HEXA |
| Thyroid cancer signaling | 2.66E-02 | 6.82E-02 | CXCL10,CDH1,BDNF |
| Alanine degradation III | 3.21E-02 | 1.67E-01 | GPT2 |
| Alanine biosynthesis II | 3.21E-02 | 1.67E-01 | GPT2 |
| Formaldehyde oxidation II (glutathione-dependent) | 3.21E-02 | 1.00E-01 | ESD |
| Glutamine degradation I | 3.21E-02 | 2.00E-01 | GLS2 |
| GADD45 signaling | 4.09E-02 | 8.33E-02 | CCND2,GADD45A |
Figure 24T1-derived breast cancer populations possess distinct and overlapping chemokine profiles. A heatmap representing the secreted levels of 25 chemokines measured using a chemokine array. The chemokines are grouped based on the immune cell types that they are known to recruit (multiple immune cell types, macrophages and/or lymphocytes, T lymphocytes and/or neutrophils, macrophages, T lymphocytes or neutrophils). Red color indicates chemokines that are highly expressed and the blue color denotes chemokines that are underexpressed.
Figure 3T lymphocytes are recruited to liver and lung metastases from breast cancer. Paraffin-embedded sections from primary breast tumors, bone specimens, lung specimens and liver specimens obtained following experimental metastasis assays were subjected to immunohistochemical staining with anti-CD3 antibodies. (A) Representative images from 20X, 40X magnifications for each site are shown. 40X images were taken at the margin of the lesions (40X margin) and in more distal regions (40X adj.). Scale bar represents 40 μm (20X) or 20 μm (40X) and applies to all panels of the same magnification. (B) Positivity of CD3 staining (expressed as a ratio of positive pixels over the total pixels per field) quantified inside lesions (TUMOR), in the adjacent tissue (ADJ) or in control (CTRL) samples without any lesions. Lymphocyte T expression and recruitment is mostly associated with lung or liver metastasis (*: P <0.001).
Figure 4Ly-6G cells are recruited in breast cancer-derived lung and liver metastases. Paraffin-embedded sections from primary breast tumors, bone metastases, lung metastases and liver metastases were obtained following experimental metastasis assays and subjected to immunohistochemical staining with anti-Ly-6G antibodies. (A) Representative images from 20X and 40X magnifications for each metastatic site are shown. 40X images were taken either at the margin of the lesions (40X margin) or in regions distal to the metastatic lesion (40X adj.). (B) Positivity of Ly-6G staining (expressed as a ratio of positive pixels over the total pixels per field) was quantified within the metastatic lesions (TUMOR), in close proximity to the metastatic lesion (PROX ADJ), in the tissue adjacent (ADJ) to the metastases or in control (CTRL) samples without any metastatic lesions. Increased recruitment of Ly-6G+ cells was observed in close proximity to hepatic metastases (*: liver tumor vs. liver adj., P <0.001; liver adj. vs. liver prox. Adj., P <0.001; lung tumor vs. lung adj., P <0.001). Scale bar represents 40 μm (20X) or 20 μm (40X) and applies to all panels of the same magnification.
Figure 5Depletion of Gr-1 (Ly-6C/Ly-6G) cells differentially affects the establishment and growth of bone, lung and liver metastases. (A) Schematic depicting the experimental protocol for depletion of Gr-1+ cells. (B) The degree of osteolytic bone destruction in the hindlimbs of mice treated with anti-Gr1 and isotype control antibodies was quantified by in vivo micro-computed. tomography (μCT) imaging. Bone volume of defined regions of the proximal tibia is shown following cardiac injection of 593 bone-aggressive cells. No difference was observed when comparing bone volumes between the two populations. Representative images of bone reconstructions are shown. (C) Quantification of the tumor burden (tumor area/tissue area) within the lung following tail vein injection of 526 lung-aggressive cells. No statistical difference in lung metastatic burden was observed when the isotype control cohort was compared with Gr-1+-depleted cohort. (D) Quantification of the tumor burden (tumor area/tissue area) within the cardiac liver lobe following splenic injection of 2776 liver-aggressive cells. Statistically significant decreases in liver-metastatic burden were observed when the isotype control cohort was compared with the Gr-1-depleted cohort (P = 0.012). Hematoxylin and eosin (H&E) images of the lung or cardiac liver lobe are shown for mice injected with each of the indicated cell populations and treated with isotype control or anti-Gr1 antibodies. Dotted lines circumscribe breast cancer metastatic lesions within the liver. Scale bar represents 2 mm and applies to all panels. IP: intraperitoneal injection; ns: not statistically significant.
Figure 6Ly-6G cell depletion decreases the establishment and growth of liver metastases. (A) Schematic depicting the experimental protocol for depletion of Ly-6G+ cells. (B) Paraffin-embedded liver sections were obtained following completion of the experimental metastasis assays and subjected to immunohistochemical staining with anti-Ly-6G antibodies. Statistically significant decreases in Ly-6G+ cells that infiltrate the liver were observed when the neutrophil-depleted cohort was compared with the isotype control cohort (P = 0.045). Representative images of Ly-6G-stained liver sections from each cohort. (C) Quantification of the tumor burden (tumor area/tissue area) within the cardiac liver lobe following splenic injection of 2776 liver-aggressive cells. Statistically significant decreases in liver-metastatic burden were observed when the isotype control cohort was compared with the neutrophil-depleted cohort (P = 0.031). Representative images of hematoxylin and eosin (H&E)-stained liver sections exhibiting the liver-metastatic burden in each cohort. Dotted lines circumscribe breast cancer metastatic lesions within the liver. Scale bar represents 2 mm and applies to all panels. IP: intraperitoneal injection.
Figure 7Neutrophils are recruited to early lesions and are maintained at the margin of liver metastases over time. Paraffin-embedded sections from liver metastases were collected at early (1.5 week) or late (3 weeks) time points following experimental metastasis assays and subjected to immunohistofluorescence staining with anti-S100a8 (red) or anti-neutrophil elastase (NE) (green) antibodies. The number of S100a8-positive cells (A) or NE-positive cells (B) per field was quantified. (C) Positivity of neutrophil staining (expressed as a percentage of S100a8 and NE double-positive cells over the total number of S100a8-positive cells) was quantified within each region of interest. While the number of s100a8- and NE-positive cells increased during tumor progression (s100a8 distal early vs. distal late, P <0.001; NE distal early vs. distal late, P = 0.021; s100a8 tumor early vs. tumor late, P <0.001; NE tumor early vs. tumor late, P <0.001), a decrease in the proportion of neutrophils comprising the s100a8+ infiltrate was routinely observed in the tumor or the distal region as tumor progressed (distal early vs. distal late, P = 0.019; tumor early vs. tumor late, P = 0.006). In contrast, no changes were observed in the margin of the lesions.
Figure 8N2-polarized neutrophils are recruited to the invasive front of liver metastases over time. (A) Schematic depicting the experimental protocol to isolate neutrophils from metastasis-bearing livers. (B) Quantitative real-time PCR analysis was performed for IFN-β, CCL3 and TNF-α as markers for anti-tumorigenic (N1)-polarized neutrophils, normalized to total Gapdh levels, in neutrophils isolated from early (7 days) or late (14 days) time points post splenic injection with the 2776 liver-aggressive cell line. The data is depicted as fold expression relative to early time point and is representative of four independent experiments performed in triplicate. (C) Quantitative real-time PCR analysis was performed for MMP9, CCL5 and Arginase 1 as markers for pro-tumorigenic (N2)-polarized neutrophils, normalized to total Gapdh levels, in neutrophils isolated from early or late time points post splenic injection with the 2776 liver-aggressive cell line. The data is depicted as fold expression relative to early time point and is representative of four independent experiments performed in triplicate.
N2-polarized neutrophils are recruited at the invasive front of breast liver metastases over time
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| Distal | 60.84 | +/− 9.39 | |
| Invasive front | 90.19 | +/− 6.04 | <0.00001 |
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| Distal | 79.58 | +/− 5.93 | |
| Invasive front | 94.92 | +/− 3.56 | <0.0001 |
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| Distal | 88.21 | +/− 3.53 | |
| Invasive front | 93.63 | +/− 2.80 | 0.003 |
aOCT-embedded sections from liver metastases were collected either 7 days (D7) or 14 days (D14) following splenic injection of breast cancer cells and subjected to immunohistofluorescence staining with anti-Ly-6G (cyan), MMP9 (red) or Cd11b (green) antibodies. The percentage of pro-tumorigenic (N2)-polarized neutrophils (Cd11b+/Ly-6G+/MMP9+) out of the total number of neutrophils (Cd11b+/Ly-6G+) was assessed either at the invasive front of the metastatic lesions or in regions distal to the metastases (distal). Representative images can be found in Additional files 3 and 4.