Tumour-derived secreted phosphoprotein 1/SPP1 via activation of microglia contributes to the formation of the breast cancer brain metastatic niche

Tumour-derived secreted phosphoprotein 1/SPP1 via activation of microglia contributes to the formation of the breast cancer brain metastatic niche | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Tumour-derived secreted phosphoprotein 1/SPP1 via activation of microglia contributes to the formation of the breast cancer brain metastatic niche Kamil Wojnicki, Katarzyna Poleszak, Agata Kochalska-Les, Adria-Jaume Roura, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5410549/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Brain metastases (BrMets) occur in 20%-40% of patients with breast cancer and contribute significantly to morbidity and/or mortality. BrMets are more common in certain breast cancer subtypes, such as human epidermal growth factor receptor 2–positive breast cancer, which has a higher incidence of BrMets. The molecular mechanisms that drive and permit the progression of metastasis in the brain are poorly understood. Identifying components of the metastatic niches and propensities of primary tumors towards the brain microenvironment are essential to improve our understanding of BrMet development, patient management and outcomes. SPP1, a secreted phosphoglycoprotein 1, is a potent activator of microglia (brain resident myeloid cells) in malignant gliomas. SPP1 is elevated in breast cancer and breast cancer brain metastasis. Exploration of public bulk and scRNAseq datasets shows high SPP1 overexpression in breast malignant cells, as well as in the immune cells in BrMets. We found that breast cancer cells with high expression of SPP1 strongly activate microglia in co-cultures, which in turn increases cancer cell invasion. Blocking SPP1-mediated cancer-microglia communication with the 7aaRGD interfering peptide or shRNA mediated knockdown of SPP1 in cancer cells, abolished microglia-dependent cancer cell invasion. Notably, we found that an antibiotic minocycline efficiently reduces the expression of SPP1 in several breast cancer cell lines, and decreases both the basal and microglia-induced invasion of breast cancer cells. The results highlight the important role of breast cancer-derived SPP1 in shaping the permissive microenvironment of BrMet, and indicate a potential of the 7aaRGD peptide or minocycline to be new therapeutics in breast cancer brain metastasis treatment. breast cancer brain metastasis tumour-microglia communication BrMet niche synthetic peptides minocycline Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Breast cancer is the most commonly diagnosed malignancy in women worldwide and remained the main cause of death, mainly due breast cancer metastasis [ 1 ]. Breast cancer is divided into four molecular subtypes: luminal A, luminal B, HER2-enriched, and triple negative [ 2 ] associated with different patient’s survival [ 3 ] and metastatic abilities. Breast cancer metastases to bones, lungs, liver, brain and in other organs, and brain metastasis (BrMet) account for 15–25% of cases [ 4 , 5 ]. Despite intensive treatment with traditional and stereotactic radiosurgery, molecularly targeted therapies and immunotherapies, median survival of patients with BrMet is 15 months, and it is affected by multiple factors, such as localization of the metastasis, its size and molecular subtype [ 6 ]. This emphasizes the need for a comprehensive understanding of BrMet biology to design more effective therapies. Recent analyses of patient samples have revealed that the composition of the tumor microenvironment (TME) through various mechanisms contributes to disease progression in primary and metastatic brain cancers [ 7 , 8 ]. A comprehensive single-cell transcriptomic analysis of the most frequent BrMets revealed a similarity of the functional cell types and cellular states in various human parenchymal BrMets. Interestingly, they detected metastasis-associated macrophages (MAMs): MAMs:APOE + and MAMs:S100A8 + in BrMets. The MAMs:APOE + population expresses SPP1 [ 8 ] and SPP1 + macrophages have been described as in colorectal cancer as linked to therapy resistance and angiogenesis [ 9 ]. Recent evidence suggests that BrMet-associated macrophages originate both from resident microglia (∼10–50%) and infiltrating monocytes/macrophages (∼25–75%) [ 10 ]. High-dimensional single-cell profiling (CyTOF) indicated the predominance of tissue-invading leukocytes in BrMets when compared to primary glioblastomas and the abundance of subpopulations of monocyte-derived macrophages (MDMs) expressing phagocytosis (CD206, CD209, CD169, and CD163) and immunosuppression markers (PDL-1 and PDL-2) [ 11 ]. The secreted phosphoprotein 1 (SPP1), also known as a osteopontin, is one of the heterogeneously expressed protein among breast cancer cells and cells in the tumour microenvironment (e.g macrophages, stromal cells) [ 12 ]. SPP1 is a secreted glycophosphoprotein with integrin- and CD44-binding domains [ 13 ]. SPP1 undergoes post-translational modifications and proteolytic cleavage by trombin and metaloproteinases, which alter significantly the structure and biological functions of the protein [ 14 ]. SPP1 signalling via integrin receptors leads to activation of many functional pathways, such as cell adhesion, cell migration and tumour metastasis [ 15 , 16 ]. SPP1 after binding to integrins α V β 3 activates FAK, (PI3K)/Akt/mTOR and ERK1/2 signalling pathways, controlling cell migration, extravasation [ 17 ] and pathways supporting tumour cell survival [ 15 , 18 ]. SPP1 expression is elevated in many cancers, associated with their aggressiveness and frequently negatively correlated with survival of cancer patients [ 19 ]. There is a growing evidence suggesting a role of SPP1 in cancer metastasis, as elimination of the SPP1 at the transcriptional, translational or signalling level using RNAi [ 20 – 23 ], aptamers [ 24 ] or monoclonal antibodies [ 25 ] in in vitro and in vivo cancer models efficiently reduced the malignant potential of the cancer cells. However, the expression of SPP1 in BrMets and its specific role in interactions of metastatic cells with brain myeloid cells is largely unexplored. In the present study we determined SPP1 protein expression in breast cancer metastasis in the brain by immunohistochemistry and explored public single-cell RNAseq datasets to identify a cellular source of its expression. We assessed the expression of five SPP1 isoforms in non-transformed breast cells and five breast cancer cell lines. Breast cancer cells induced morphological changes co-cultured microglia indicative of cell activation. Microglia increased the invasion of breast cancer cells in a Matrigel matrix assay. Moreover, we demonstrate the 7aaRGD peptide that blocks SPP1-integrin signalling or knockdown of SPP1 in breast cancer cells diminished both the basal microglia-induced invasion of those cells. We found that a tetracycline, brain penetrant antibiotic minocycline decreased the expression of SPP1 breast cancer cells, which reduced their invasion. Brain metastases remain hard to treat malignancies due to their location in the brain and poor drug penetration into the central nervous system. We propose that blocking the SPP1 expression/activity with the 7aaRGD peptide or minocycline could be a new therapeutic strategy for BrMet patients. Materials and Methods Re-analysis of public scRNA seq datasets Triple-negative breast cancer (TNBC) single-cell RNA sequencing data (scRNAseq) (1500 cells) from six tumours were analysed (accession GSE118389 [ 26 ]) to investigate SPP1 expression in the tumour and its microenvironment with a single cell resolution. The non-normalized data matrix was used as an input to create a Seurat object [ 27 ] and only genes detected in at least 3 cells and cells in which at least 200 features detected were selected for further analysis. A standard quality check pre-processing workflow was performed and unwanted cells were filtered out based on unique counts and mitochondrial counts as previously described [ 28 ]. Data were normalized using a Seurat's LogNormalized method to identify highly variable features throughout the dataset. To equally weight gene expression across cells, a scaling step was performed using the ScaleData method with default parameters. The dimensionality of the dataset was determined using the JackStraw procedure [ 29 ] and the 17 most significant principal components (PCs) were selected for the subsequent analysis. The resulting cells were clustered using the FindNeighbors and FindClusters methods, and the UMAP nonlinear dimensionality reduction technique was applied to visualize and examine the dataset. Once the cell clusters were obtained, markers were identified using the FindMarkers method and a curated cluster evaluation was performed based on the most significant gene markers. With the aim of deciphering the biological significance of the cell cluster with the highest SPP1 expression, Gene Ontology and KEGG analyses were performed using the R package clusterProfiler. Determination of SPP1 expression matched breast cancers and brain metastases GSE14683 dataset containing array expression profiling of matched and unpaired samples of breast cancer and brain metastases was analysed. The normalized gene expression matrix from the study was used as input and SPP1 expression in primary breast cancer and brain metastases was compared using the Student’s t-test method. Cell cultures Breast cancer cells BT-474, MDA-MB-231 (MDA-231) and SKBR3 (ATCC, Manassas, VA, USA) cell lines were cultured in DMEM/F12 GlutaMAX. MCF7 cell line was cultured in DMEM GlutaMAX with insulin (10 µg/mL). BT-549 cell line was cultured in RPMI-1640 supplemented with insulin (10 µg/mL). MCF10a cells was cultured in DMEM/F12 GlutaMAX supplemented with 5% horse bovine serum, insulin (10 µg/mL), ITS (insulin-transferrin-selenium, 10 µg/mL), EGF (human epidermal growth factor, 20 ng/mL), hydrocortisone (500 ng/mL), cholera toxin (100 ng/mL), and ascorbic acid (52 µg/mL). Most cell cultures were supplemented with 10% FBS (or otherwise marked) (Gibco) and antibiotics (100 U/mL penicillin, 100 µg/mL streptomycin) and cultured in a humidified atmosphere of CO 2 /air (5%/95%) at 37°C. Microglial cultures Human SV40 immortalized microglial cells (HMSV40) were cultured in PriCoat T25 flasks in Prigrow III Medium supplemented with 10% FBS (Gibco) supplemented with antibiotics (100 U/mL penicillin, 100 µg/mL streptomycin). Details are listed inin the Suppl. Table S1 . Mouse microglial BV2 cells were cultured in DMEM GlutaMAX™ supplemented with 2% FBS (Gibco). Primary rat microglia cultures were set up from transgenic eGFP-expressing rats Wistar-TgN(CAG-GFP)184Ys, (National Bio Resource Project for the Rat in Japan, Kyoto University) as previously described [ 30 ]. Briefly after dissociation of the cerebral cortices of P0-P2 pups of C57BL/6J mice, the cells were suspended in the medium, counted, checked for viability and seeded at a required density in high-glucose DMEM supplemented with Glutamax, 10% fetal bovine serum (ThermoScientific; CA, USA) and antibiotics. After culturing mixed glial cultures for 8 days cells were subjected to strong shaking at 180 rpm overnight, microglia were collected and cultured in a humidified atmosphere of CO 2 /air (5%/95%) at 37°C. Clinical samples Formalin-fixed paraffin-embedded (FFPE) tissue specimens were provided from the pathology archives of the Department of Pathology, Maria Sklodowska-Curie Memorial Cancer Centre, Institute of Oncology in Warsaw or by the Department of Neurosurgery, Medical University of Warsaw. This retrospective study doesn’t require the Institutional Review Board (IRB) approval. We obtained a statement from the IRB Committee that the study is exempt from the approval and all identifiable information is not included in the manuscript. Altogether, 17 tissue samples from BrMets of breast cancer and 8 from primary breast cancer biopsies were analysed. Immunohistochemistry and immunofluorescence HLA staining was performed on 5-µm paraffin-embedded tissue sections. Sections were deparaffinized by incubation in xylene, followed by ethanol (100, 90, 70%), and rehydrated. Epitopes were retrieved by oven boiling in a pH 6.0 citrate buffer for 35 min. Endogenous peroxidase was blocked in 0.3% H 2 O 2 in 10% methanol for 30 min followed by blocking with 10% horse serum. Sections were incubated overnight at 4°C with the rabbit anti-SPP1 or mouse anti-HLA primary antibody (recognising HLA-DP, -DQ, -DR). Next, sections were washed in PBS, incubated with biotinylated horse immunoglobulin, then with horseradish peroxidase-conjugated avidin for 60 min, and finally with 3,3′-diaminobenzidine (DAB). Sections were counterstained with hematoxylin (Merck), washed, dehydrated and mounted. For immunofluorescence staining, the step of blocking with endogenous peroxidase was omitted and blocking was performed in 3% donkey serum in 0.1% Triton-X100 solution. The sections were incubated with donkey anti-mouse A488 and anti-rabbit A555 for 1 h at room temperature. Subsequently the specimens were counterstained with DAPI (Sigma, 1 µg/mL, PBS), washed and mounted. Reagent specifications, catalogue numbers and concentrations are listed in the Table 1. For immunocytochemistry the MDA-231 cells were seeded onto glass coverslip. After 24 h cells were fixed with 4% paraformaldehyde (PFA) pH 7.2, washed, permeabilised with 0.1% Triton-X100 and blocked in mix of 2% donkey serum and 1.5% FBS, followed by 2 h incubation with rabbit anti-SPP1 and mouse anti-giantin primary antibodies. Cells were then washed in PBS, incubated with donkey anti-rabbit Alexa Fluor A555 and donkey anti-mouse Alexa Fluor A488, counterstained with DAPI (Sigma, 1 µg/mL, PBS) and mounted. Reagent specifications, catalogue numbers and concentrations are listed in the Table 1. Images were taken using either the fluorescence microscope Leica DM4000B or the confocal microscope Zeiss LSM800 Airyscan. Western blotting Western blotting Whole-cell protein extracts were prepared, resolved by electrophoresis and transferred to a nitrocellulose membrane as described [ 31 ]. After blocking with 5% non-fat milk in TBST (Tris-buffered solution pH 7.6, 0.01% Tween-20) the membranes were incubated overnight with primary antibodies: anti-SPP1 and anti-GAPDH diluted in 5% non-fat milk in TBST. The primary antibody reaction was followed by 1 h incubation with horseradish peroxidase-conjugated anti-rabbit IgG or anti-mouse IgG, which were diluted in TBST. Immunocomplexes were detected using an enhanced chemiluminescence detection system (ECL) and Chemidoc (Biorad). Band intensities were measured by a densitometric analysis of immunoblots using the BioRad Image Lab (ver. 5.2) software. Antibody specifications, catalogue numbers, and dilutions are listed in the Table 1. Gene expression and qPCR RNA was isolated using either High Pure RNA Isolation Kit (Roche) or RNeasy Mini Kit (QIAGEN). Quality and quantity were assessed using NanoDrop 2000 Spectrophotometer. Reverse transcription of RNA was performed with SuperScript III Reverse Transcriptase (Invitrogen) on 1 µg of total RNA. Gene expression was determined by quantitative real-time PCR (qPCR) with 50 ng of cDNA in duplicates, using FAST SYBR Green PCR MasterMix (Life Technologies) or TaqMan Fast Universal PCR Master Mix (Applied Biosystems) in 10 µL reaction with a listed set of primers (Table 1). The amplified product was normalized to the endogenous expression of GAPDH and represented as delta Ct values. Matrigel assay for evaluating cancer cell invasion Microglial cells (human HMSV40 or murine BV2) were plated onto 24-well plates at a density of 4 × 10 4 /well. After 24 h, the invasion assay was performed using 6.5 mm Transwell® tissue culture inserts (Corning) coated with the Matrigel™ Matrix (BD Biosciences). Briefly, 50 µL of the Matrigel™ Matrix (1 mg/mL) diluted in fresh DMEM was dried under sterile conditions (37°C) for 6–7 h. The medium in microglial cultures was replaced to a medium with 2% FBS 1 h before seeding 4 × 10 4 /insert of the MDA-231 cells on matrigel-covered membrane on the inserts. The co-cultures were incubated in a 37°C incubator with humidified air containing 5% CO 2 . After 18 h, the cells were fixed in ice-cold methanol and cell nuclei were stained with DAPI (1 µg/mL, Merck). The membranes from Transwell® inserts were cut out and images of the five independent fields (bottom, top, left, right side, and centre) were acquired. Numbers of invading cancer cell nuclei were counted using the ImageJ software. All experiments were performed at least three times, in duplicates. Morphology evaluation in breast cancer-rat primary microglia co-cultures Morphological changes were examined in rat microglia primary cultures co-incubated with breast cancer cells. GFP-expressing rat microglial cells were seeded onto round glass coverslips at a density of 1 × 10 4 /well in a 24-well plate and incubated for 24 h. MDA-231 cells were seeded into the Falcon cell culture inserts with 0.4-µm pores (Falcon) at 6 × 10 4 /insert. After 24 h, the inserts were transferred into the plate with microglial cells and co-cultured for 24 h. Microglial cells were fixed with 4% PFA in PBS, washed and mounted. Next, the images were taken and the average single cell area of rat microglia was determined using ImageJ software. Microglia and breast cancer cell co-cultures HMSV40 microglia human cells (2.5x10 6 ) were seeded on 6-well plates and MDA-MB-231 breast cancer cells were seeded on inserts with 0.4-µm pores at density of 2.5x10 6 /insert. After 24 h, the medium was changed to a microglial medium, and these inserts were transferred into the plate with cancer cells for 0.5 h for Western Blotting analysis and 6 h for gene expression analysis. Cell viability The cell viability after minocycline treatment was determined using an MTT metabolism assay. Cells were plated at the following densities: BT-549: 3.5 x 10 4 /well; MCF-10A, NHA: 4.0 x 10 4 /well; MDA-231: 5 x 10 4 /well; MCF-7: 6 x 10 4 /well, and cultured for 24, 48 and 72 h in 24-well plates with the addition of the indicated concentrations of the minocycline dissolved in H 2 O: 10, 25, 50, 100, 500 µM. The MTT stock solution (Merck) was added to each well to a final concentration of 0.5 mg/mL. After 2 h of incubation at 37°C the water-insoluble dark blue formazan crystals were dissolved in DMSO. The optical densities were measured at 570 nm using a scanning multi-well spectrophotometer. All measurements were carried out in triplicate. Cell proliferation The cell proliferation was determined using a Cell Proliferation ELISA, BrdU colorimetric kit (Roche) according to the manufacturer’s instructions. The cells were plated onto 96-well plate at density 6000/well and cultured for 48 h. All experiments were performed at least three times, in six replicates. Development of stably transfected shSPP1 and control cell lines The SPP1 silencing hairpin (shSPP1) was inserted to pSilencer™2.1-U6 hygro vector; a control plasmid carried the neutral shRNA, not recognising any gene in the human cells. The sequence of the sh SPP1 vector was verified by Sanger sequencing. For electroporation MDA-231 cells (4 x 10 5 ) were trypsinised, suspended in antibiotic-free medium, electroporated with shNEG or shSPP1 plasmids using Lonza 4D-Nucleofector, CH-125 program. Transfected cells were seeded and maintained in a medium supplemented with 600 µg/mL hygromycin, changed every 3 days, until death of mock-transfected cells. Stably transfected cells were expanded from individual colonies and SPP1 knockdown was verified by qPCR. Sequences of short hairpin RNA are listed in the. Table 1. Statistical analysis The presented data are representative of at least three independent experiments. Error bars indicate standard deviation (SD) for at least three biological replicates. For comparison of differences between two groups, the t-test or chi-square test were used. We used Mantel-Haenszel Odds Ratio estimator, with repetitions as strata, with confidence interval CI95% obtained based on Robins-Breslow-Greenland estimator of variance [ 32 , 33 ]. For comparison ≥ 3 groups, the one-way ANOVA was used. Statistical analysis was performed using GraphPad Prism (ver. 6.07) software. Results SPP1 is expressed both in malignant and myeloid cells in the brain metastasis of breast cancer We evaluated SPP1 expression levels in primary breast cancer and brain metastases of breast cancer (BrMetBC) in the microarray expression dataset of 29 matched pairs of primary breast cancer with their brain metastases and 22 unmatched brain metastases from breast cancer (GSE14682). SPP1 expression was significantly higher in BrMet than in primary breast cancers (Fig. 1 A). Using immunohistochemistry we investigated the localization of SPP1 protein in patient-derived BrMetBC tissues. Representative images (Fig. 1 B) show the weak presence of SPP1 in the intact brain parenchyma (P1) and abundant staining within the breast metastatic core (P2) or in both compartments (P3). SPP1 staining was strong in the metastatic core in 8 of 17 analysed cases. SPP1 positivity was detected only in the brain parenchyma in 3 cases, only in the metastatic lesions in 3 cases; 3 cases were SPP1 negative (Fig. 1 C). To determine if SPP1 is detected in myeloid cells, we employed the staining with antibody recognising HLA-DP,-DQ,-DR (HLA) antigen (Fig. 1 D) and perform double immunofluorescence staining for HLA-DP,R,Q and SPP1 (Fig. 1 E). HLA belong to the MHC class II cell surface receptors and are expressed on antigen-presenting cells, such as microglia, macrophages and dendritic cells [ 34 ]. Interestingly, the number of immune cells (HLA-positive cells) differs between patients and HLA + cells are highly abundant around tumour core (Fig. 1 D). Co-localisation of HLA and SPP1 staining indicate that some myeloid cells express SPP1 (Fig. 1 E). Using immunohistochemical staining we detected high SPP1 levels in primary breast cancer tissue sections. Positive staining was present exclusively in the cytoplasm of malignant cells in 6 cases (out of 7 tested). The level of SPP1 varied between patients; two representative images of high (BC1) and low (BC2) SPP1 positivity are presented (Fig. 2 A). We used a publicly available single-cell RNA sequencing (scRNAseq) dataset (GSE118389) to profile SPP1 expression in 6 cases of Triple Negative Breast Cancer (TNBC) in the context of tumour and its microenvironment. SPP1 was identified as one of the top 20 genes with differential expression between cells and showed great variation across the dataset (Fig. 2 B). SPP1 was strongly expressed in the clusters 6 and 8, according to differentially expressed genes across clusters (Fig. 2 C). A total of 13 clusters were identified in the dataset. The top significant up-regulated genes in the cluster 6 are show (Fig. 2 D) and the majority of these genes were associated with immune processes. More detailed analysis of annotated clusters showed a significant fraction of SPP1 expressing cells in the cluster 6 (macrophages), while only a few cells within clusters 2 (malignant cells) and 8 (smooth muscle cells) had higher levels of SPP1 . Those clusters were spatially isolated from one another, suggesting that both cell types expressing SPP1 have different gene programs (Fig. 2 E). In each of the clusters, both canonical and manually curated cell type assignments were performed, and macrophages were reported to be the primary component of the tumour microenvironment expressing SPP1 (Fig. 2 E-F). Canonical macrophage marker genes, such as genes coding for scavenger receptor cysteine-rich type 1 protein (CD163) or interleukin 1 beta (IL1B), were highly expressed in the cluster 6. Furthermore, high expression of MATN2 ( encoding Matrilin-2), MYLK (Myosin Light Chain Kinase) or ACTA2 (Actin Alpha 2) in the cluster 8 suggested that SPP1 expression was augmented in smooth muscle cells (SMCs). We performed the Gene Ontology analysis for all differentially expressed genes in the cluster 6 to verify that those cells are macrophages, and found several upregulated genes related to immune signalling pathways (Suppl. Figure 1A), which is typically for myeloid cells. A second pathway enrichment analysis using the Kyoto Encyclopaedia of Genes and Genomes (KEGG) database revealed upregulation of genes related to immune pathways such as phagosome, antigen processing and presentation (Suppl. Figure 1B). Microglia enhance invasion of breast cancer cells Microglia respond to different environmental stimuli with the activation programme which results in changing their morphology from a spindle/ramified to a more amoeboid shape [ 35 ]. To study microglia-breast cancer cell interactions we employed a co-culture system, in which cells are separated by a porous membrane (0.2 µm pores) allowing to exchange only soluble factors. Green fluorescent rat microglial cells were co-cultured with breast cancer cells: MCF7, BT-549 and MDA-231, and after 24 h profound changes in microglial morphology were detected (Fig. 3 A). In the presence of breast cancer cells, microglial cell morphology shifted toward the activated state (characterised by round, amoeboid morphology). Representative image (inset) shows highly flatten, amoeboid microglia co-cultured with MDA-231 cells. We quantified the area of individual microglial cells co-cultured with breast cancer cells. On average a single microglial cell was enlarged 2 times when co-cultured with MCF7, and 2,5 times, when co-cultured with BT-549 or MDA-231 in comparison to the untreated cells (Fig. 3 B). The strongest induction was evoked by the ‘triple negative’ breast cancer cells, therefore we used MDA-231 cells for further experiments in which we determined if murine (BV2) or human (HMSV40) microglia affect the invasion of MDA-231 cells in the Matrigel matrix invasion assay (Fig. 3 C). Matrigel mimics the extracellular matrix (ECM) and cells must actively degrade ECM to appear in the lower compartment. The invasive MDA-231 cells digested the matrigel and crossed the porous membrane. Quantification of nuclei of invading cells shows that in the presence of either BV2 or HMSV40 microglial cells, significantly more MDA-231 cells invaded the matrigel in comparison to control conditions without microglia (Fig. 3 D). Notably, the stronger effect was observed in the presence of human microglia, where the chance of an increased invasion of MDA-231 cells was OR = 13.8 times higher compared to MDA-231 alone, whereas in murine microglia the odds ratio was OR = 7.2. We have recently demonstrated that interactions between glioma and microglia can be prevented with a synthetic peptide RGD, which blocks SPP1-integrin receptor signalling, microglia-dependent invasion and reverses immunosuppression in the glioma microenvironment [ 36 ]. To verify if SPP1 mediates microglia-dependent invasion of breast cancer cells, we used the RGD peptide to block the integrin signalling [ 37 ] and RAE as a control. In the RAE peptide, the RGD motif (arginine-glycine-aspartic acid) is changed to RAE (arginine-alanine-glutamic acid), which blunts its activity. We found that the RGD peptide decreased the basal invasion of MDA-231 cells and strongly reduced microglia-dependent invasion (Fig. 3 E-F). The control RAE peptide did not inhibit cell invasion. SPP1 mediates microglia-dependent breast cancer cell invasion Firstly, we determined expression of SPP1 in a panel of breast cancer cells. In human cells alternative splicing of SPP1 mRNA generates five mRNA variants: SPP1 -a, b, c, 4 and 5. SPP1 -a is a full, canonical form, while SPP1-b (lack exon 5), SPP1-c (deleted exon 4), SPP1-4 (lack exons 4 and 5) and SPP1-5 (contains an additional exon) [ 39 ]. SPP1 -a, b and c isoforms have been thoroughly investigated in terms of specific functions and correlation with different types of cancer [ 38 ] [ 39 ], while functions of SPP1 -4 and 5 are poorly known [ 40 ]. We design primers to determine the mRNA level of particular SPP1 isoforms by RT-qPCR in breast cancer MCF7, BT-474, SKBR3, BT-549 and MDA-231 cells, as well as in the non-cancerous MCF-10a cells (Fig. 4 A). The specific primers for SPP1-a overlap with the SPP1-5 , however the SPP1-5 expression was very low across the cell lines, thus we assume that with SPP1 a primers we can accurately estimate the SPP1 -a expression. qPCR quantification shows that breast cancer cells have variable expression of SPP1 isoforms. The expression of SPP1-a and SPP1-b isoforms was the highest among analysed cell lines. The levels of SPP1-a , SPP1-b and SPP1-4 were significantly higher in BT-549 and MDA-231 in comparison to non-transformed MCF-10a cells (indicated by ‘*’). We did not detect any SPP1 isoforms in BT-474 cells, and SPP1-a isoform was present in SKBR3 cells (not shown). The SPP1-c and SPP1-5 isoforms were not detected in MCF-10a cells. To determine cellular localization of SPP1, we performed immunofluorescence staining for SPP1 and giantin, a marker of the Golgi system, in MDA-231 cells (Fig. 4 B). We showed that SPP1 is localized in the Golgi system, where it may undergo post-translational processing or vesicle packaging for secretion. To evaluate the role of SPP1 in breast cancer cell invasion, we developed MDA-231 cells with shRNA mediated, stably knockdown of SPP1. Knockdown efficacy was verified by RT-qPCR of the SPP1-b mRNA, the most abundant SPP1 mRNA variant in MDA-231, and by Western blotting. The relative expression of SPP1-b in shSPP1 MDA-231 cells was significantly decreased compared to MDA-231 control cells (shNEG) (Fig. 4 C). Moreover, the SPP1 protein level was significantly lower in shSPP1 cells (Fig. 4 D) as shown by Western blotting. The SPP1 knockdown did not affect basal cell proliferation as was shown using a BrdU incorporation assay (Fig. 4 E). The presence of HMSV40 microglia augments breast cancer cell invasion. However, microglia dependent invasion of shSPP1 MDA-231 cells was reduced 6 times in comparison to invasion of shNEG cells in co-cultures (Fig. 4 F). Mechanistically, the exposure of human HMSV40 microglial cells to MDA-231 upregulates the p-STAT3 level (Fig. 4 G-H) and MMP-9 expression (Fig. 4 I) as demonstrated by Western blotting analysis and qPCR, respectively. These results indicate that cancer cell-derived SPP1 mediates microglial-dependent breast cancer invasion. Minocycline decrease the viability and SPP1 level in breast cancer cells. Minocycline (MINO), a second-generation derivative of tetracycline, shows antimicrobial, anti-inflammatory, neuroprotective and anti-tumorigenic effects, being enrolled clinical trials focusing on non-antibiotic properties [ 40 – 42 ]. Treatment with MINO reduced glioma growth in vivo by impairing microglia dependent invasion [ 43 , 44 ]. We found that a systemic MINO treatment decreases Spp1 expression in rat C6 glioma cells and reduces intracranial C6 glioma growth in vivo (unpublished). Therefore, we investigated the effects of MINO on SPP1 expression and communication between breast cancer cells and microglia. Cell viability of MDA-231, BT-549, MCF7 and non-cancerous MCF10a, normal human astrocytes (NHA) and HMSV40 after treatment for 48 h with MINO at different doses was determined by a MTT metabolism assay (Fig. 5 A-B). MINO treatment strongly affected survival of BT-549 and MDA-231 cells (derived from the most aggressive, the ‘triple-negative’ breast cancer subtype) with IC 50 values from 20.6 to 91.4 µM of MINO, respectively. MCF7 cells and non-cancerous MCF10a cells were more resistant to MINO treatment (IC 50 ~ 135 µM). Interestingly, MINO had a minor effect on NHA (Fig. 5 A) and HMSV40 (Fig. 5 B) cells, only at higher concentration > 50 µM. Treatment with MINO strongly reduced expression of SPP1 in MDA-231 cells (Fig. 5 C) and BT-549 (Fig. 5 D) cells, while low expression of SPP1 in MCF7 cells was not affected (Fig. 5 E). We tested effects of MINO on microglia-dependent invasion of MDA-231 cells by applying MINO at non-cytotoxic doses. MINO decreased the basal invasion of MDA-231 cells and had weak effects on HMSV40 microglia-dependent invasion of MDA-231 cells (Fig. 5 F). The results suggest strong effects of MINO at MDA-231 cells but not on communication between breast cancer cells and microglia. Discussion In the CNS, metastatic cancer cells exploit different non-tumor cell types in the microenvironment to form a permissive niche and support their proliferation and survival. Microglia, as the brain resident phagocytic and antigen presenting cells, play a crucial role in immune surveillance and antitumor responses. Single-cell ‘omic’ analyses of BrMet specimens and experimental murine BrMet demonstrated functional and spatial heterogeneity of microglia, and contribution of those cells in metastasis formation in the CNS [ 45 , 46 ]. Here we present the results indicating the augmented expression and role of SPP1 in the breast cancer cell invasion and metastasis. We prose a mechanism through which breast cancer cells “hijack” brain resident myeloid cells (microglia) to create a permissive niche and support tumour invasion. We demonstrate that genetic or pharmacological inhibition of SPP1 signalling with an innovative synthetic peptide 7aaRGD or minocycline can restrict breast cancer growth and dissemination. Using publicly available datasets, we identified SPP1 as a one of the most expressed genes in triple-negative breast cancers. The re-analysis of scRNAseq datasets shows that cells expressing SPP1 are malignant cells, macrophages and smooth muscle cells. SPP1 is expressed in most malignant cancers, and the increased SPP1 level was related to the dismal prognosis for BRCA, CESC, COAD, HNSC, LUAD, and LUSC patients [ 47 ]. SPP1 expressed in malignant cells supports cell proliferation via EGFR-mediated activation [ 48 ]. In smooth muscle cells SPP1 is an inhibitor of calcification [ 49 ]. Immunostaining for SPP1 showed that breast cancer cells produced SPP1 at various levels, and SPP1 expression was higher in breast cancer BrMet. Staining for human leukocyte antigen (with HLA-DP/DR/DQ antibody) is a standard way to visualise myeloid cells in the brain. HLA positivity does not distinguish between various myeloid populations. Immunocytochemistry shows the presence of SPP1 both in malignant cells and HLA-positive cells (microglia/macrophages) in a vast majority of analysed BrMet tissues. To study the role of breast cancer-derived SPP1 in interactions of those cells with microglia, we determined SPP1 expression in cultured breast cancer cells and established a co-culture system for mechanistic studies. Three tested breast cancer cell lines induced morphological changes of rat microglia in co-cultures which was quantified as the increase of microglial cell area. This type of amoeboid, morphological transformation of microglia is consistent with their pro-tumour activation, which was observed in glioma-microglia co-cultures [ 45 ]. Consistently, the presence of microglial cells (either murine BV2 or human HM SV40 microglial cells) strongly increased invasion of MDA-231 cells, which are cells with the highest expression of SPP1. Blocking SPP1-integrin signalling with the RGD peptide slightly reduced a basal invasion and strongly reduced microglia-induced invasion; the control RAE peptide (the similar sequence with replacement of the RGD motif by the RAE motif). Mechanistically, the exposure of human HMSV40 microglial cells to MDA-231 upregulates the p-STAT3 level and expression of MMP-9 , its transcriptional target in many cells. These results indicate that cancer cell-derived SPP1 mediates microglial-dependent breast cancer invasion likely via pSTAT3-MMP9 axis. Quantitative analysis shows the elevated expression of SPP1-c in breast cancer cell lines in comparison to non-cancerous breast cells. SPP1 is particularly highly expressed in MDA-231 cells (which ER, PR, and E-cadherin negative and expresses the mutated p53). SPP1-c was considered a selective marker in breast cancer [ 50 ] and to lesser extent a favourable predictor to tamoxifen treatment [ 51 ]. Knockdown of SPP1 expression in MDA-231 cells shows that while SPP1 is negligent for a basal cell proliferation, its lack abolishes microglia-dependent invasion. It points to a cancer cell-derived SPP1 as a factor activating microglia which in turn support cancer cell invasion in the brain parenchyma. MINO is a blood-brain barrier penetrating, FDA approved antibiotic with a favourable pharmacokinetics, and has been effective in reducing glioma growth in mice through the attenuation of microglia-dependent invasion and microglial expression of the metalloproteinase MT1-MMP/MMP14 [ 43 , 44 ]. We demonstrate that MINO reduced survival of breast cancer cells, while had no influence on viability of normal human astrocytes or microglial cells (up to 50 µM). MDA-231 and BT-549 cells were the most sensitive. Interestingly, in both MDA-231 and BT-549 cells MINO treatment reduced significantly the SPP1 expression, particularly in MDA-231 cells. Moreover, MINO treatment reduced invasion of MDA-231 cells. The results show that MINO by blocking SPP1 expression in breast cancer cells reduces the microglial support within the tumour niche. These results raise an interesting opportunity of using MINO as a novel therapeutic treatment against breast cancer and its brain metastasis. For patients with brain metastases, the surgery and radiotherapy remain a main therapeutic option, and the further treatment is strictly dependent on the cancer type, size and individual factors. For breast cancer there are many systemic therapies dependent on the hormone and HER2 status, however there is a limited number of treatment recommendations for breast cancer BrMets [ 52 ]. Recent evidence shows that BrMet-associated myeloid cells are derived from resident microglia cells (10–50%) and infiltrated monocytes (25–75%) [ 10 ]. The presence of APOE+, metastasis-associated macrophages expressing SPP1 and SPP1 + tumor associated macrophages have been described in BrMet, and linked to therapy resistance and angiogenesis [ 9 ]. Identifying the contribution of myeloid cells to metastasis in the brain may facilitate developing new therapeutic modalities. The potent anti-invasion effects of the 7aaRGD peptide (RGD) in microglia-MDA-231 cell co-cultures hold a promise of a new treatment option as the efficacy of this peptide in modulation of the tumour microenvironment in intracranial gliomas has been recently demonstrated [ 36 ]. Conclusion SPP1 is highly expressed in BrMets both in malignant and myeloid cells. Its high expression is maintained in breast cancer cells and those cells strongly activate microglia in co-cultures, which in turn increases cancer cell invasion. Blocking SPP1-mediated cancer-microglia communication with the 7aaRGD interfering peptide or shRNA mediated knockdown of SPP1 in cancer cells, abolished microglia-dependent cancer cell invasion. FDA approved drug minocycline efficiently reduces the expression of SPP1 in several breast cancer cells, and decreases both the basal and microglia-induced invasion of breast cancer cells. The results highlight the important role of breast cancer-derived SPP1 in shaping the permissive microenvironment of BrMets, and indicate a potential of the 7aaRGD peptide or minocycline as new therapeutics in breast cancer BrMet treatment. Abbreviations BrMet brain metastasis MINO minocycline MMP9 matrix metalloproteinase 9 SPP1 secreted phopshoprotein 1 Declarations Authors’ contributions Kamil Wojnicki performed most of the experimenst, have analyzed the data and organized all Figures. Katarzyna Poleszak, Agata Kochalska-Les, Kacper Waśniewski, Barbora Vymolova contributed to determination of cell invasion. Adria-Jaume Rouraanalysed scRNAesq data. Ewa Matyja, Tomasz Czernicki, Wiesława Grajkowska provided FFPE section from patients and pathological consultations. Bozena Kaminskaand Kamil Wojnicki have conceived the idea, contributed to data generation and interpretation. Bozena Kaminskaand Kamil Wojnicki have written the first draft. Bozena Kaminskahas designed the study and acquired the required funds. All authors read and approved the final manuscript. Funding Studies were supported by the TRANSCAN-3/1/168/2022 ImmuMet project funded by National Center for Research and Development, Poland. Competing interests The authors declare no competing interests. Acknowledgements We would like to thank Maciej Sobczyński, PhD for help in statistical analysis of the data; Małgorzata Całka-Kresa and Artut Wolny from Laboratory of Imaging Tissue Structure and Function at Nencki Institute of Experimental Biology for their kind assistance. Consent to Publish declaration: not applicable’. Ethics and Consent to Participate declarations : not applicable’. References Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin . American Cancer Society; 2021;71:209–49. Goldhirsch A, Winer EP, Coates AS, Gelber RD, Piccart-Gebhart M, Thürlimann B, et al. Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013. Ann Oncol Off J Eur Soc Med Oncol. 2013;24:2206–23. Fallahpour S, Navaneelan T, De P, Borgo A. Breast cancer survival by molecular subtype: a population-based analysis of cancer registry data. C Open . 2017;5:E734 LP-E739. Weide R, Feiten S, Friesenhahn V, Heymanns J, Kleboth K, Thomalla J, et al. Metastatic breast cancer: prolongation of survival in routine care is restricted to hormone-receptor- and Her2-positive tumors. Springerplus . 2014;3:535. Suh JH, Kotecha R, Chao ST, Ahluwalia MS, Sahgal A, Chang EL. Current approaches to the management of brain metastases. Nat Rev Clin Oncol . 2020;17:279–99. Rostami R, Mittal S, Rostami P. Brain metastasis in breast cancer : a comprehensive literature review. J Neurooncol. Springer US; 2016;127:407–14. Bejarano L, Kauzlaric A, Lamprou E, Lourenco J, Fournier N, Ballabio M, et al. Interrogation of endothelial and mural cells in brain metastasis reveals key immune-regulatory mechanisms. Cancer Cell . Elsevier; 2024;42:378-395.e10. Gonzalez H, Mei W, Robles I, Hagerling C, Allen BM, Hauge Okholm TL, et al. Cellular architecture of human brain metastases. Cell . Elsevier; 2022;185:729-745.e20. Zhang L, Li Z, Skrzypczynska KM, Fang Q, Zhang W, O’Brien SA, et al. Single-Cell Analyses Inform Mechanisms of Myeloid-Targeted Therapies in Colon Cancer. Cell. 2020;181:442-459.e29. Friebel E, Kapolou K, Unger S, Núñez NG, Utz S, Rushing EJ, et al. Single-Cell Mapping of Human Brain Cancer Reveals Tumor-Specific Instruction of Tissue-Invading Leukocytes. Cell. United States; 2020;181:1626-1642.e20. Klemm F, Maas RR, Bowman RL, Kornete M, Soukup K, Nassiri S, et al. Interrogation of the Microenvironmental Landscape in Brain Tumors Reveals Disease-Specific Alterations of Immune Cells. Cell 2020;181:1643-1660.e17. Tuck AB, O’Malley FP, Singhal H, Harris JF, Tonkin KS, Kerkvliet N, et al. Osteopontin expression in a group of lymph node negative breast cancer patients. Int J cancer 1998;79:502–8. Senger DR, Perruzzi CA, Papadopoulos-Sergiou A, Van de Water L. Adhesive properties of osteopontin: regulation by a naturally occurring thrombin-cleavage in close proximity to the GRGDS cell-binding domain. Mol Biol Cell 1994;5:565–74. Christensen B, Nielsen MS, Haselmann KF, Petersen TE, Sørensen ES. Post-translationally modified residues of native human osteopontin are located in clusters: identification of 36 phosphorylation and five O-glycosylation sites and their biological implications. Biochem J . 2005;390:285–92. Zhang H, Guo M, Chen J-H, Wang Z, Du X-F, Liu P-X, et al. Osteopontin knockdown inhibits αv,β3 integrin-induced cell migration and invasion and promotes apoptosis of breast cancer cells by inducing autophagy and inactivating the PI3K/Akt/mTOR pathway. Cell Physiol Biochem Int J Exp Cell Physiol Biochem Pharmacol. Germany; 2014;33:991–1002. Chen Q, Shou P, Zhang L, Xu C, Zheng C, Han Y, et al. An osteopontin-integrin interaction plays a critical role in directing adipogenesis and osteogenesis by mesenchymal stem cells. Stem Cells . 2014;32:327–37. Zou C, Luo Q, Qin J, Shi Y, Yang L, Ju B, et al. Osteopontin promotes mesenchymal stem cell migration and lessens cell stiffness via integrin β1, FAK, and ERK pathways. Cell Biochem Biophys. United States; 2013;65:455–62. Yan W, Qian C, Zhao P, Zhang J, Shi L, Qian J, et al. Expression pattern of osteopontin splice variants and its functions on cell apoptosis and invasion in glioma cells. Neuro Oncol . 2010;12:765–75. Weber GF, Lett GS, Haubein NC. Osteopontin is a marker for cancer aggressiveness and patient survival. Br J Cancer . Nature Publishing Group; 2010;103:861–9. Gardner HA, Berse B, Senger DR. Specific reduction in osteopontin synthesis by antisense RNA inhibits the tumorigenicity of transformed Rat1 fibroblasts. Oncogene. England; 1994;9:2321–6. Rittling SR, Chambers AF. Role of osteopontin in tumour progression. Br J Cancer . Nature Publishing Group; 2004;90:1877–81. Kumar V, Behera R, Lohite K, Karnik S, Kundu GC. p38 kinase is crucial for osteopontin-induced furin expression that supports cervical cancer progression. Cancer Res. United States; 2010;70:10381–91. Syamal D. Bhattacharya, Juline Garrison, Hongtao Guo, Zhiyong Mi, Jovan Markovic, Victoria M. Kim PCK. Micro-RNA-181a regulates osteopontin-dependent metastatic function in hepatocellular cancer cell lines. Surgery. 2010;148. Mi Z, Guo H, Russell MB, Liu Y, Sullenger BA, Kuo PC. RNA aptamer blockade of osteopontin inhibits growth and metastasis of MDA-MB231 breast cancer cells. Mol Ther. 2009;17:153–61. Dai J, Li B, Shi J, Peng L, Zhang D, Qian W, et al. A humanized anti-osteopontin antibody inhibits breast cancer growth and metastasis in vivo. Cancer Immunol Immunother. Germany; 2010;59:355–66. Karaayvaz M, Cristea S, Gillespie SM, Patel AP, Mylvaganam R, Luo CC, et al. Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq. Nat Commun . 2018;9:3588. Stuart T, Butler A, Hoffman P, Hafemeister C, Papalexi E, Mauck WM, et al. Comprehensive Integration of Single-Cell Data. Cell . 2019;177:1888-1902.e21. Ochocka N, Segit P, Walentynowicz KA, Wojnicki K, Cyranowski S, Swatler J, et al. Single-cell RNA sequencing reveals functional heterogeneity of glioma-associated brain macrophages. Nat Commun . 2021;12:1151. Macosko EZ, Basu A, Satija R, Nemesh J, Shekhar K, Goldman M, et al. Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets. Cell . Elsevier; 2015;161:1202–14. Zawadzka M, Kaminska B. A novel mechanism of FK506-mediated neuroprotection: Downregulation of cytokine expression in glial cells. Glia. John Wiley & Sons, Ltd; 2005;49:36–51. Ciechomska IA, Gabrusiewicz K, Szczepankiewicz AA, Kaminska B. Endoplasmic reticulum stress triggers autophagy in malignant glioma cells undergoing cyclosporine A-induced cell death. Oncogene. 2013;32:1518–29. Phillips A, Holland PW. Estimators of the Variance of the Mantel-Haenszel Log-Odds-Ratio Estimate. Biometrics . [Wiley, International Biometric Society]; 1987;43:425–31. Robins J, Breslow N, Greenland S. Estimators of the Mantel-Haenszel variance consistent in both sparse data and large-strata limiting models. Biometrics. United States; 1986;42:311–23. Ulvestad E, Williams K, Bø L, Trapp B, Antel J, Mørk S. HLA class II molecules (HLA-DR, -DP, -DQ) on cells in the human CNS studied in situ and in vitro. Immunology. 1994;82:535–41. Ellert-Miklaszewska A, Dabrowski M, Lipko M, Sliwa M, Maleszewska M, Kaminska B. Molecular definition of the pro-tumorigenic phenotype of glioma-activated microglia. Glia. United States; 2013;61:1178–90. Ellert-Miklaszewska A, Pilanc-Kudlek P, Poleszak K, Roura A-J, Cyranowski S, Ghosh M, et al. Integrin blocking peptide reverses immunosuppression in experimental gliomas and improves anti-PD-1 therapy outcome. bioRxiv. 2024;2024.08.06.606798. Ellert-Miklaszewska A, Wisniewski P, Kijewska M, Gajdanowicz P, Pszczolkowska D, Przanowski P, et al. Tumour-processed osteopontin and lactadherin drive the protumorigenic reprogramming of microglia and glioma progression. Oncogene. 2016;35:6366–77. Briones-Orta MA, Avendaño-Vázquez SE, Aparicio-Bautista DI, Coombes JD, Weber GF, Syn W-K. Osteopontin splice variants and polymorphisms in cancer progression and prognosis. Biochim Biophys acta Rev cancer. Netherlands; 2017;1868:93-108.A. He B, Mirza M, Weber GF. An osteopontin splice variant induces anchorage independence in human breast cancer cells. Oncogene. 2006;25:2192–202. Silva GR, Mattos DS, Bastos ACF, Viana BPPB, Brum MCM, Ferreira LB, et al. Osteopontin-4 and Osteopontin-5 splice variants are expressed in several tumor cell lines. Mol Biol Rep . 2020;47:8339–45. https://clinicaltrials.gov. Matsukawa N, Yasuhara T, Hara K, Xu L, Maki M, Yu G, et al. Therapeutic targets and limits of minocycline neuroprotection in experimental ischemic stroke. BMC Neurosci . 2009;10:126. Markovic DS, Vinnakota K, van Rooijen N, Kiwit J, Synowitz M, Glass R, et al. Minocycline reduces glioma expansion and invasion by attenuating microglial MT1-MMP expression. Brain Behav Immun . 2011;25:624–8. Hu F, Ku M-C, Markovic D, Dzaye O, Lehnardt S, Synowitz M, et al. Glioma-associated microglial MMP9 expression is upregulated by TLR2 signaling and sensitive to minocycline. Int J Cancer . John Wiley & Sons, Ltd; 2014;135:2569–78. You H, Baluszek S, Kaminska B. Immune Microenvironment of Brain Metastases—Are Microglia and Other Brain Macrophages Little Helpers? Front Immunol. 2019;10. You H, Baluszek S, Kaminska B. Supportive roles of brain macrophages in CNS metastases and assessment of new approaches targeting their functions. Theranostics. Australia; 2020;10:2949–64. Chandra Tripathi S, Chakraborty G, Simoes D, Yang Y, Wei T, Bi G, et al. The Significance of Secreted Phosphoprotein 1 in Multiple Human Cancers. 2020 Lee SJ, Baek SE, Jang MA, Kim CD. Osteopontin plays a key role in vascular smooth muscle cell proliferation via EGFR-mediated activation of AP-1 and C/EBPβ pathways. Pharmacol Res. Netherlands; 2016;108:1–8. Speer MY, Chien YC, Quan M, Yang HY, Vali H, McKee MD, et al. Smooth muscle cells deficient in osteopontin have enhanced susceptibility to calcification in vitro. Cardiovasc Res. 2005;66:324–33. Mirza M, Shaughnessy E, Hurley JK, Vanpatten KA, Pestano GA, He B, et al. Osteopontin-c is a selective marker of breast cancer. Int J cancer. United States; 2008;122:889–97. Zduniak K, Agrawal A, Agrawal S, Hossain MM, Ziolkowski P, Weber GF. Osteopontin splice variants are differential predictors of breast cancer treatment responses. BMC Cancer. BioMed Central; 2016;16:441. Vogelbaum MA, Brown PD, Messersmith H, Brastianos PK, Burri S, Cahill D, et al. Treatment for Brain Metastases: ASCO-SNO-ASTRO Guideline. J Clin Oncol. Wolters Kluwer; 2021;40:492–516. Tables Table 1. Human microglia culture Reagent Source Human microglia cell line (HMSV40) (# T0251) Applied Biological Materials PriCoat T25 flask (# G299) Applied Biological Materials Prigrow III Medium (# TM003) Applied Biological Materials Antibodies used for stainings Antibody Clone Manufacturer Cat. number Dilution anti-HLA-DP, -DQ, -DR CR3/43 DAKO M0775 1:200 anti-osteopontin - MilliporeSigma HPA027541 IHC: 1:100 IF: 1:100 anti-giantin - Abcam ab37266 1:200 horseradish peroxidase-conjugated horse anti-mouse - Vector BA2000 1:200 horseradish peroxidase-conjugated horse anti-rabbit - Vector BA1100 1:200 donkey anti-rabbit A555 - ThermoFisher A31572 1:1000 donkey anti-mouse A488 - ThermoFisher A21202 1:1000 ExtrAvidin™−Peroxidase - Sigma-Aldrich E2886 1:200 Antibodies used for immunoblotting anti-phospho-STAT3 (Y705) M9C6 Cell signaling 4113 1:1000 anti-STAT3 124H6 Cell signaling 9139 1:1000 horseradish peroxidase-conjugated monoclonal anti-β-actin AC-15 Sigma Aldrich A3854 1:40000 anti-glyceraldehyde-3-phosphate dehydrogenase 6C5 Merck MAB374 1:25000 horseradish peroxidase-conjugated anti-rabbit IgG - Vector PI-1000 1:10000 horseradish peroxidase-conjugated anti-mouse IgG - Vector PI-2000 1:10000 Oligonucleotides Reagent Source human SPP1-b qPCR f- TTGGAAGGGTCTGTGGGGCTAGG, r- CCTCCTAGGCATCACCTGTGCCAT Genomed human SPP1-c qPCR f- GAATTGCAGTGATTTGCTTTTGC, r- AGGACACAGCATTCTGCTTTTC Genomed human SPP1-4 qPCR f- GAATTGCAGTGATTTGCTTTTGC, r- GGAAGGGTCTGCTTTTCCTCA Genomed human SPP1-5 qPCR f- GAATTGCAGTGATTTGCTTTTGC, r- AGGTACATCTTTAGTGCTGCTTTTC Genomed human GAPDH qPCR f- AGGGCTGCTTTTAACTCTGGT, r- CCCCACTTGATTTTGGAGGGA Genomed Human MMP9 qPCR Hs00234579_m1 Applied Biosystems shSPP1: GAT CCC AAG TAA GTC CAA CGA AAT TCA AGA GAT TTC GTT GGA CTT ACT TGG TTT TTG GAA - shNEG: pSilencer 2.1-U6 hygro (# AM5760) ThermoFisher Invasion assay / co-culture Reagent Source 6.5 mm Transwell® with 8.0 µm Pore Polycarbonate Membrane Insert (# 3422) Corning Growth Factor Reduced Matrigel™ Matrix (# 356231) BD Biosciences Falcon cell culture inserts (0.4-µm pores) (# 353095) Falcon Other reagents Reagent Source Cell Proliferation ELISA, BrdU colorimetric kit (# 11647229001) Roche Additional Declarations No competing interests reported. Supplementary Files Supp.S1.tif Supplementary Fig. 1. Gene set enrichment analysis in triple-negative breast cancer cells with high SPP1 expression. (A) Gene Ontology (GO) analysis for cluster 6 shows the top 15 most significant pathways after Benjamini-Hochberg (BH) FDR correction (P < 0.05). (B) Pathway enrichment analysis for cluster 6 using the KEGG database; the top 15 most significant pathways are shown. Supp.S2.jpg Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5410549","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":389384323,"identity":"4afde05d-4d53-4a06-8a2d-7f1cbd66a447","order_by":0,"name":"Kamil Wojnicki","email":"","orcid":"","institution":"Nencki Institute of Experimental Biology of the Polish Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Kamil","middleName":"","lastName":"Wojnicki","suffix":""},{"id":389384324,"identity":"aa3d4426-891b-4c33-8246-293c9cc3a846","order_by":1,"name":"Katarzyna Poleszak","email":"","orcid":"","institution":"Nencki Institute of Experimental Biology of the Polish Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Katarzyna","middleName":"","lastName":"Poleszak","suffix":""},{"id":389384325,"identity":"46dc4f7c-126f-4dce-b314-387a8146cdd2","order_by":2,"name":"Agata Kochalska-Les","email":"","orcid":"","institution":"Nencki Institute of Experimental Biology of the Polish Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Agata","middleName":"","lastName":"Kochalska-Les","suffix":""},{"id":389384326,"identity":"e6273f12-bc23-4595-bfbc-d12c3d724fc8","order_by":3,"name":"Adria-Jaume Roura","email":"","orcid":"","institution":"Nencki Institute of Experimental Biology of the Polish Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Adria-Jaume","middleName":"","lastName":"Roura","suffix":""},{"id":389384327,"identity":"1da92b28-5b64-4bfa-8cd1-9157dee7e0e9","order_by":4,"name":"Ewa Matyja","email":"","orcid":"","institution":"Medical University of Warsaw","correspondingAuthor":false,"prefix":"","firstName":"Ewa","middleName":"","lastName":"Matyja","suffix":""},{"id":389384328,"identity":"7c4beb70-a74e-44cf-bfed-8e5e0ae1430b","order_by":5,"name":"Tomasz Czernicki","email":"","orcid":"","institution":"Medical University of Warsaw","correspondingAuthor":false,"prefix":"","firstName":"Tomasz","middleName":"","lastName":"Czernicki","suffix":""},{"id":389384329,"identity":"11220cb1-e179-43a4-b95f-a2822b2f4438","order_by":6,"name":"Wiesława Grajkowska","email":"","orcid":"","institution":"The Children’s Memorial Health Institute","correspondingAuthor":false,"prefix":"","firstName":"Wiesława","middleName":"","lastName":"Grajkowska","suffix":""},{"id":389384330,"identity":"b5edc676-f96c-44f9-8dd8-ed2b14de7e31","order_by":7,"name":"Kacper Waśniewski","email":"","orcid":"","institution":"Nencki Institute of Experimental Biology of the Polish Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Kacper","middleName":"","lastName":"Waśniewski","suffix":""},{"id":389384331,"identity":"9a3874ce-c615-4436-8834-6f8471a592d2","order_by":8,"name":"Barbora Vymolova","email":"","orcid":"","institution":"Charles University in Prague","correspondingAuthor":false,"prefix":"","firstName":"Barbora","middleName":"","lastName":"Vymolova","suffix":""},{"id":389384332,"identity":"5239d4eb-4d23-4114-b919-c2c1e61f112b","order_by":9,"name":"Bozena Kaminska","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYBACAwY2MMkgwcB8ACwA4ksAsQwRWtgSULTw4NcCVsVjABEgpMWcgS3x042CO/aS7We+Pfi4w86Yj4H54G0ehjs4tVg2sB2WzjF4ljibJ3e74cwzyWZsDGzJ1jwMz3A77AB7A1DL4QQ5htxt0rxtB2zYGHjMpHkYDuPT0vwbqMVejv/NM+m/YC383whoYTsGsoVxtkQOmzRj2wGgw3jY8GqxbGZLswZqSZw545mZZG9bsjEbM5ux5RwD3H4xZ28zvp3z57C9xPnkZxI/2+wM57c3P7zxpuKOHC4tDMzYRQwO4NSBE5ChZRSMglEwCoYrAAAp3UtW/NgNtAAAAABJRU5ErkJggg==","orcid":"","institution":"Nencki Institute of Experimental Biology of the Polish Academy of Sciences","correspondingAuthor":true,"prefix":"","firstName":"Bozena","middleName":"","lastName":"Kaminska","suffix":""}],"badges":[],"createdAt":"2024-11-07 14:08:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5410549/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5410549/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":71787738,"identity":"19c67bea-2e53-4d12-b272-eecb0d8ad9fd","added_by":"auto","created_at":"2024-12-18 15:03:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":736840,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSPP1 is highly abundant in brain metastases from breast cancer (BrMBC).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) \u003cem\u003eSPP1\u003c/em\u003e expression in primary breast cancer and BrMBC from the GSE14682 dataset. (B) Graphical representation of the predominant SPP1 localization in BrMBC tissues. The width of the circle represents a number of patients showing specific localization of SPP1. Representative images of: (C) SPP1 and (D) HLA-DP, -DQ, -DR (HLA) immunostaining in tissue sections from BrMBC patients. (E) Representative confocal images of SPP1 and HLA immunofluorescent staining in BrMBC sections. Myeloid cells (HLA positive cells) expressing SPP1 are marked with yellow arrows. Scale bars: 100 µm.\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-5410549/v1/305cf1a325d814304ef69d75.png"},{"id":71787739,"identity":"51b08ce4-2da0-42fd-acc0-2da4c3a46c26","added_by":"auto","created_at":"2024-12-18 15:03:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1572629,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSPP1 is expressed in different cell populations.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Representative images of SPP1 immunostaining of tissues from breast cancer patients. Scale bar: 100 µm. Breast cancer single cell data were analyzed from the GSE118389 dataset. (B) Plot of highly variable genes shows significant (red dots) features based on dispersion and average gene expression. The top 20 most variable genes across cells are highlighted. (C) Single-cell violin plot shows SPP1 expression distributions across clusters. Each colour represents a different cell cluster and each dot represents a single cell. Only cluster 0 to cluster 10 are shown for simplicity's purposes. (D) Heatmap showing the expression of genes (top 10 markers) from cells in clusters 6 and 8. Rows represent genes and columns represent cells. UMAP dimensionality reduction plot showing clustering of cells: (E) visualization of SPP1 expression (red gradient indicates low or high SPP1 expression), (F) cluster cell type identification based on canonical and curated markers. Cluster annotations: MC malignant cells, BCSCs breast cancer stem cells, MSCs mesenchymal stem cells, SMCs smooth muscle cells, EC epithelial cells, CAF cancer-associated fibroblasts.\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-5410549/v1/d40cf1fdb8c038169b3141c3.png"},{"id":71789467,"identity":"064f9ca9-76cb-4065-807e-2dcc3869e004","added_by":"auto","created_at":"2024-12-18 15:11:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":556363,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMicroglia enhance invasiveness of breast cancer cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Representative images of GFP-expressing primary rat microglia following co-culture with human breast cancer cells: MCF7, BT-549, and MDA-231. Insets show higher magnifications of microglial cells. Scale bars: 50 µm. (B) Morphological changes after co-culture were quantified by measuring the single cell area of rat microglia. (C) Schematic illustration of the matrigel invasion assay. (D) Invasiveness of MDA-231 cells in the absence or presence of the microglial cells. BV2 represents murine microglial cells and HMSV40 represents human immortalized microglial cells. Invasion of MDA-231 cells treated with the RGD peptide (which inhibits the integrin signalling pathway) and the control peptide RAE in the (E) absence or (F) presence of HMSV40. Statistical significance was determined using one-way ANOVA with Dunnett’s post-hoc test (B) or chi-square test (D-F). *p \u0026lt; 0.05, **p \u0026lt; 0.01 and ***p \u0026lt; 0.001; OR stands for odds ratio. OR=7.2 CI95(6.6;7.8), OR=13.8 CI95(11.9;16), OR=1.1 CI95(0.9;1.2), OR=2.6 CI95(2.2;3).\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-5410549/v1/4649209e4472d71e72ceb59e.png"},{"id":71787743,"identity":"05bb3225-8d37-462a-b463-54aeebd3d7ca","added_by":"auto","created_at":"2024-12-18 15:03:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":561598,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSPP1 produced by breast cancer cells is crucial for invasiveness.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Expression of five isoforms of SPP1 in non-cancerous MCF10a cells and breast cancer cells: MCF7, BT549 and MDA-231. The ‘*’ represent comparison to MCF-10a, whereas ‘#’ to MCF7. (B) Immunofluorescent staining shows cellular localization of SPP1 in the area of Golgi apparatus (GIANTIN is used as a marker of Golgi structures). (C) The expression of SPP1-b isoform after SPP1 knockdown using shRNA (shSPP1) in comparison to the negative control in MDA-231 (shNEG). (D) The level of SPP1 protein in shSPP1 and shNEG control cells. GAPDH was used as a protein loading control. (E) shSPP1 and shNEG cell proliferation. (F) Invasion of shSPP1 and shNEG in the absence or presence of HMSV40. The RT-qPCR data are shown as delta Ct values relative to GAPDH expression. (G) Western Blot analysis p-STAT3 and STAT3 levels in human microglia cells (HMSV40) after co-culture with MDA-231 cells. (H) Densitometric analysis of p-STAT3 and STAT3 levels in HMSV40 cells. Fold change was calculated according to control, HMSV40 cells, designated as black line. (I) \u003cem\u003eMMP9\u003c/em\u003eexpression in HMSV40 cells with and without presence of MDA-231 cells. Statistical analysis was performed using two-way ANOVA with Dunnett’s post-hoc test (A), one sample two-tailed t-test (C-E, H-I) or chi-square test (F). *p \u0026lt; 0.05, **p \u0026lt; 0.01 and ***p \u0026lt; 0.001; #p \u0026lt; 0.05 and ##p \u0026lt; 0.01; OR stands for odds ratio. OR=6 CI95(5.1;7.2).\u003c/p\u003e","description":"","filename":"Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-5410549/v1/c44215c4db45ed172db9322d.png"},{"id":71787745,"identity":"36052bdf-82dc-43e0-b81c-2246d96bb144","added_by":"auto","created_at":"2024-12-18 15:03:23","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":196893,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMinocycline reduces the viability and invasiveness of breast cancer cells by\u003c/strong\u003e \u003cstrong\u003edecreasing SPP1 expression.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A,B) Cell viability after minocycline treatment of cancerous cells: MDA-231, BT-549, MCF7, and non-cancerous cells: MCF10A, normal human astrocytes (NHA) and HMSV40. \u003cem\u003eSPP1-b\u003c/em\u003e isoform expression in: (C) MDA-231, (D) BT-549 and (E) MCF7 cells after minocycline treatment. (F) Invasiveness of MDA-231 cells in the absence or presence of HMSV40 microglia after minocycline treatment. The RT-qPCR data are shown as delta Ct values relative to GAPDH expression. Statistical analysis were performed using one sample two-tailed t-test (C-E) or chi-square test (F) *p \u0026lt; 0.05 and **p \u0026lt; 0.01; OR stands for odds ratio. OR=4.6 CI95(3.9;5.5). For the IC\u003csub\u003e50 \u003c/sub\u003edetermination we used ‘Inhibitor vs. normalized response - variable slope’ model in GraphPad Prism software and best fit values were taken.\u003c/p\u003e","description":"","filename":"Fig.5.png","url":"https://assets-eu.researchsquare.com/files/rs-5410549/v1/97a3be9039c503d74b1d1d69.png"},{"id":80428881,"identity":"9d38ea36-0a83-403a-87f2-7e03b6db21f5","added_by":"auto","created_at":"2025-04-12 00:46:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5075260,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5410549/v1/b3704da4-fbb5-4ccd-92fa-83d3e7f322d7.pdf"},{"id":71787742,"identity":"d7e0338f-be42-4482-a36f-55c4a822815e","added_by":"auto","created_at":"2024-12-18 15:03:23","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1113532,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Fig. 1\u003c/strong\u003e. \u003cstrong\u003eGene set enrichment analysis in triple-negative breast cancer cells with high SPP1 expression.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Gene Ontology (GO) analysis for cluster 6 shows the top 15 most significant pathways after Benjamini-Hochberg (BH) FDR correction (P \u0026lt; 0.05). (B) Pathway enrichment analysis for cluster 6 using the KEGG database; the top 15 most significant pathways are shown.\u003c/p\u003e","description":"","filename":"Supp.S1.tif","url":"https://assets-eu.researchsquare.com/files/rs-5410549/v1/93a1cc79151fccb6959f0f80.tif"},{"id":71787741,"identity":"2e5b066b-bb31-41d3-a752-53a95bf45987","added_by":"auto","created_at":"2024-12-18 15:03:23","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":70289,"visible":true,"origin":"","legend":"","description":"","filename":"Supp.S2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5410549/v1/fccff0ef8aa2f60c727bb562.jpg"}],"financialInterests":"No competing interests reported.","formattedTitle":"Tumour-derived secreted phosphoprotein 1/SPP1 via activation of microglia contributes to the formation of the breast cancer brain metastatic niche","fulltext":[{"header":"Background","content":"\u003cp\u003eBreast cancer is the most commonly diagnosed malignancy in women worldwide and remained the main cause of death, mainly due breast cancer metastasis [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Breast cancer is divided into four molecular subtypes: luminal A, luminal B, HER2-enriched, and triple negative [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] associated with different patient\u0026rsquo;s survival [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] and metastatic abilities. Breast cancer metastases to bones, lungs, liver, brain and in other organs, and brain metastasis (BrMet) account for 15\u0026ndash;25% of cases [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Despite intensive treatment with traditional and stereotactic radiosurgery, molecularly targeted therapies and immunotherapies, median survival of patients with BrMet is 15 months, and it is affected by multiple factors, such as localization of the metastasis, its size and molecular subtype [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This emphasizes the need for a comprehensive understanding of BrMet biology to design more effective therapies. Recent analyses of patient samples have revealed that the composition of the tumor microenvironment (TME) through various mechanisms contributes to disease progression in primary and metastatic brain cancers [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. A comprehensive single-cell transcriptomic analysis of the most frequent BrMets revealed a similarity of the functional cell types and cellular states in various human parenchymal BrMets. Interestingly, they detected metastasis-associated macrophages (MAMs): MAMs:APOE\u003csup\u003e+\u003c/sup\u003e and MAMs:S100A8\u003csup\u003e+\u003c/sup\u003e in BrMets. The MAMs:APOE\u003csup\u003e+\u003c/sup\u003e population expresses \u003cem\u003eSPP1\u003c/em\u003e [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and \u003cem\u003eSPP1\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e macrophages have been described as in colorectal cancer as linked to therapy resistance and angiogenesis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Recent evidence suggests that BrMet-associated macrophages originate both from resident microglia (\u0026sim;10\u0026ndash;50%) and infiltrating monocytes/macrophages (\u0026sim;25\u0026ndash;75%) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. High-dimensional single-cell profiling (CyTOF) indicated the predominance of tissue-invading leukocytes in BrMets when compared to primary glioblastomas and the abundance of subpopulations of monocyte-derived macrophages (MDMs) expressing phagocytosis (CD206, CD209, CD169, and CD163) and immunosuppression markers (PDL-1 and PDL-2) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe secreted phosphoprotein 1 (SPP1), also known as a osteopontin, is one of the heterogeneously expressed protein among breast cancer cells and cells in the tumour microenvironment (e.g macrophages, stromal cells) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. SPP1 is a secreted glycophosphoprotein with integrin- and CD44-binding domains [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. SPP1 undergoes post-translational modifications and proteolytic cleavage by trombin and metaloproteinases, which alter significantly the structure and biological functions of the protein [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. SPP1 signalling via integrin receptors leads to activation of many functional pathways, such as cell adhesion, cell migration and tumour metastasis [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. SPP1 after binding to integrins α\u003csub\u003eV\u003c/sub\u003eβ\u003csub\u003e3\u003c/sub\u003e activates FAK, (PI3K)/Akt/mTOR and ERK1/2 signalling pathways, controlling cell migration, extravasation [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and pathways supporting tumour cell survival [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. \u003cem\u003eSPP1\u003c/em\u003e expression is elevated in many cancers, associated with their aggressiveness and frequently negatively correlated with survival of cancer patients [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. There is a growing evidence suggesting a role of SPP1 in cancer metastasis, as elimination of the SPP1 at the transcriptional, translational or signalling level using RNAi [\u003cspan additionalcitationids=\"CR21 CR22\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], aptamers [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] or monoclonal antibodies [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] in \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e cancer models efficiently reduced the malignant potential of the cancer cells. However, the expression of SPP1 in BrMets and its specific role in interactions of metastatic cells with brain myeloid cells is largely unexplored.\u003c/p\u003e \u003cp\u003eIn the present study we determined SPP1 protein expression in breast cancer metastasis in the brain by immunohistochemistry and explored public single-cell RNAseq datasets to identify a cellular source of its expression. We assessed the expression of five \u003cem\u003eSPP1\u003c/em\u003e isoforms in non-transformed breast cells and five breast cancer cell lines. Breast cancer cells induced morphological changes co-cultured microglia indicative of cell activation. Microglia increased the invasion of breast cancer cells in a Matrigel matrix assay. Moreover, we demonstrate the 7aaRGD peptide that blocks SPP1-integrin signalling or knockdown of SPP1 in breast cancer cells diminished both the basal microglia-induced invasion of those cells. We found that a tetracycline, brain penetrant antibiotic minocycline decreased the expression of \u003cem\u003eSPP1\u003c/em\u003e breast cancer cells, which reduced their invasion. Brain metastases remain hard to treat malignancies due to their location in the brain and poor drug penetration into the central nervous system. We propose that blocking the SPP1 expression/activity with the 7aaRGD peptide or minocycline could be a new therapeutic strategy for BrMet patients.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eRe-analysis of public scRNA seq datasets\u003c/h2\u003e \u003cp\u003eTriple-negative breast cancer (TNBC) single-cell RNA sequencing data (scRNAseq) (1500 cells) from six tumours were analysed (accession GSE118389 [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]) to investigate SPP1 expression in the tumour and its microenvironment with a single cell resolution. The non-normalized data matrix was used as an input to create a Seurat object [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] and only genes detected in at least 3 cells and cells in which at least 200 features detected were selected for further analysis. A standard quality check pre-processing workflow was performed and unwanted cells were filtered out based on unique counts and mitochondrial counts as previously described [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Data were normalized using a Seurat's LogNormalized method to identify highly variable features throughout the dataset. To equally weight gene expression across cells, a scaling step was performed using the ScaleData method with default parameters. The dimensionality of the dataset was determined using the JackStraw procedure [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] and the 17 most significant principal components (PCs) were selected for the subsequent analysis. The resulting cells were clustered using the FindNeighbors and FindClusters methods, and the UMAP nonlinear dimensionality reduction technique was applied to visualize and examine the dataset. Once the cell clusters were obtained, markers were identified using the FindMarkers method and a curated cluster evaluation was performed based on the most significant gene markers. With the aim of deciphering the biological significance of the cell cluster with the highest \u003cem\u003eSPP1\u003c/em\u003e expression, Gene Ontology and KEGG analyses were performed using the R package clusterProfiler.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDetermination of SPP1 expression matched breast cancers and brain metastases\u003c/h3\u003e\n\u003cp\u003eGSE14683 dataset containing array expression profiling of matched and unpaired samples of breast cancer and brain metastases was analysed. The normalized gene expression matrix from the study was used as input and \u003cem\u003eSPP1\u003c/em\u003e expression in primary breast cancer and brain metastases was compared using the Student\u0026rsquo;s t-test method.\u003c/p\u003e\n\u003ch3\u003eCell cultures\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eBreast cancer cells\u003c/h2\u003e \u003cp\u003eBT-474, MDA-MB-231 (MDA-231) and SKBR3 (ATCC, Manassas, VA, USA) cell lines were cultured in DMEM/F12 GlutaMAX. MCF7 cell line was cultured in DMEM GlutaMAX with insulin (10 \u0026micro;g/mL). BT-549 cell line was cultured in RPMI-1640 supplemented with insulin (10 \u0026micro;g/mL). MCF10a cells was cultured in DMEM/F12 GlutaMAX supplemented with 5% horse bovine serum, insulin (10 \u0026micro;g/mL), ITS (insulin-transferrin-selenium, 10 \u0026micro;g/mL), EGF (human epidermal growth factor, 20 ng/mL), hydrocortisone (500 ng/mL), cholera toxin (100 ng/mL), and ascorbic acid (52 \u0026micro;g/mL). Most cell cultures were supplemented with 10% FBS (or otherwise marked) (Gibco) and antibiotics (100 U/mL penicillin, 100 \u0026micro;g/mL streptomycin) and cultured in a humidified atmosphere of CO\u003csub\u003e2\u003c/sub\u003e/air (5%/95%) at 37\u0026deg;C.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMicroglial cultures\u003c/h3\u003e\n\u003cp\u003eHuman SV40 immortalized microglial cells (HMSV40) were cultured in PriCoat T25 flasks in Prigrow III Medium supplemented with 10% FBS (Gibco) supplemented with antibiotics (100 U/mL penicillin, 100 \u0026micro;g/mL streptomycin). Details are listed inin the Suppl. Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. Mouse microglial BV2 cells were cultured in DMEM GlutaMAX\u0026trade; supplemented with 2% FBS (Gibco). Primary rat microglia cultures were set up from transgenic eGFP-expressing rats Wistar-TgN(CAG-GFP)184Ys, (National Bio Resource Project for the Rat in Japan, Kyoto University) as previously described [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Briefly after dissociation of the cerebral cortices of P0-P2 pups of C57BL/6J mice, the cells were suspended in the medium, counted, checked for viability and seeded at a required density in high-glucose DMEM supplemented with Glutamax, 10% fetal bovine serum (ThermoScientific; CA, USA) and antibiotics. After culturing mixed glial cultures for 8 days cells were subjected to strong shaking at 180 rpm overnight, microglia were collected and cultured in a humidified atmosphere of CO\u003csub\u003e2\u003c/sub\u003e/air (5%/95%) at 37\u0026deg;C.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eClinical samples\u003c/h2\u003e \u003cp\u003eFormalin-fixed paraffin-embedded (FFPE) tissue specimens were provided from the pathology archives of the Department of Pathology, Maria Sklodowska-Curie Memorial Cancer Centre, Institute of Oncology in Warsaw or by the Department of Neurosurgery, Medical University of Warsaw. This retrospective study doesn\u0026rsquo;t require the Institutional Review Board (IRB) approval. We obtained a statement from the IRB Committee that the study is exempt from the approval and all identifiable information is not included in the manuscript. Altogether, 17 tissue samples from BrMets of breast cancer and 8 from primary breast cancer biopsies were analysed.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eImmunohistochemistry and immunofluorescence\u003c/h3\u003e\n\u003cp\u003eHLA staining was performed on 5-\u0026micro;m paraffin-embedded tissue sections. Sections were deparaffinized by incubation in xylene, followed by ethanol (100, 90, 70%), and rehydrated. Epitopes were retrieved by oven boiling in a pH 6.0 citrate buffer for 35 min. Endogenous peroxidase was blocked in 0.3% H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e in 10% methanol for 30 min followed by blocking with 10% horse serum. Sections were incubated overnight at 4\u0026deg;C with the rabbit anti-SPP1 or mouse anti-HLA primary antibody (recognising HLA-DP, -DQ, -DR). Next, sections were washed in PBS, incubated with biotinylated horse immunoglobulin, then with horseradish peroxidase-conjugated avidin for 60 min, and finally with 3,3\u0026prime;-diaminobenzidine (DAB). Sections were counterstained with hematoxylin (Merck), washed, dehydrated and mounted.\u003c/p\u003e \u003cp\u003eFor immunofluorescence staining, the step of blocking with endogenous peroxidase was omitted and blocking was performed in 3% donkey serum in 0.1% Triton-X100 solution. The sections were incubated with donkey anti-mouse A488 and anti-rabbit A555 for 1 h at room temperature. Subsequently the specimens were counterstained with DAPI (Sigma, 1 \u0026micro;g/mL, PBS), washed and mounted. Reagent specifications, catalogue numbers and concentrations are listed in the Table\u0026nbsp;1.\u003c/p\u003e \u003cp\u003eFor immunocytochemistry the MDA-231 cells were seeded onto glass coverslip. After 24 h cells were fixed with 4% paraformaldehyde (PFA) pH 7.2, washed, permeabilised with 0.1% Triton-X100 and blocked in mix of 2% donkey serum and 1.5% FBS, followed by 2 h incubation with rabbit anti-SPP1 and mouse anti-giantin primary antibodies. Cells were then washed in PBS, incubated with donkey anti-rabbit Alexa Fluor A555 and donkey anti-mouse Alexa Fluor A488, counterstained with DAPI (Sigma, 1 \u0026micro;g/mL, PBS) and mounted. Reagent specifications, catalogue numbers and concentrations are listed in the Table\u0026nbsp;1.\u003c/p\u003e \u003cp\u003eImages were taken using either the fluorescence microscope Leica DM4000B or the confocal microscope Zeiss LSM800 Airyscan.\u003c/p\u003e\n\u003ch3\u003eWestern blotting\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eWestern blotting\u003c/div\u003e \u003cp\u003eWhole-cell protein extracts were prepared, resolved by electrophoresis and transferred to a nitrocellulose membrane as described [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. After blocking with 5% non-fat milk in TBST (Tris-buffered solution pH 7.6, 0.01% Tween-20) the membranes were incubated overnight with primary antibodies: anti-SPP1 and anti-GAPDH diluted in 5% non-fat milk in TBST. The primary antibody reaction was followed by 1 h incubation with horseradish peroxidase-conjugated anti-rabbit IgG or anti-mouse IgG, which were diluted in TBST. Immunocomplexes were detected using an enhanced chemiluminescence detection system (ECL) and Chemidoc (Biorad). Band intensities were measured by a densitometric analysis of immunoblots using the BioRad Image Lab (ver. 5.2) software. Antibody specifications, catalogue numbers, and dilutions are listed in the Table\u0026nbsp;1.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eGene expression and qPCR\u003c/h2\u003e \u003cp\u003eRNA was isolated using either High Pure RNA Isolation Kit (Roche) or RNeasy Mini Kit (QIAGEN). Quality and quantity were assessed using NanoDrop 2000 Spectrophotometer. Reverse transcription of RNA was performed with SuperScript III Reverse Transcriptase (Invitrogen) on 1 \u0026micro;g of total RNA. Gene expression was determined by quantitative real-time PCR (qPCR) with 50 ng of cDNA in duplicates, using FAST SYBR Green PCR MasterMix (Life Technologies) or TaqMan Fast Universal PCR Master Mix (Applied Biosystems) in 10 \u0026micro;L reaction with a listed set of primers (Table\u0026nbsp;1). The amplified product was normalized to the endogenous expression of \u003cem\u003eGAPDH\u003c/em\u003e and represented as delta Ct values.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMatrigel assay for evaluating cancer cell invasion\u003c/h2\u003e \u003cp\u003eMicroglial cells (human HMSV40 or murine BV2) were plated onto 24-well plates at a density of 4 \u0026times; 10\u003csup\u003e4\u003c/sup\u003e/well. After 24 h, the invasion assay was performed using 6.5 mm Transwell\u0026reg; tissue culture inserts (Corning) coated with the Matrigel\u0026trade; Matrix (BD Biosciences). Briefly, 50 \u0026micro;L of the Matrigel\u0026trade; Matrix (1 mg/mL) diluted in fresh DMEM was dried under sterile conditions (37\u0026deg;C) for 6\u0026ndash;7 h. The medium in microglial cultures was replaced to a medium with 2% FBS 1 h before seeding 4 \u0026times; 10\u003csup\u003e4\u003c/sup\u003e/insert of the MDA-231 cells on matrigel-covered membrane on the inserts. The co-cultures were incubated in a 37\u0026deg;C incubator with humidified air containing 5% CO\u003csub\u003e2\u003c/sub\u003e. After 18 h, the cells were fixed in ice-cold methanol and cell nuclei were stained with DAPI (1 \u0026micro;g/mL, Merck). The membranes from Transwell\u0026reg; inserts were cut out and images of the five independent fields (bottom, top, left, right side, and centre) were acquired. Numbers of invading cancer cell nuclei were counted using the ImageJ software. All experiments were performed at least three times, in duplicates.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eMorphology evaluation in breast cancer-rat primary microglia co-cultures\u003c/h2\u003e \u003cp\u003eMorphological changes were examined in rat microglia primary cultures co-incubated with breast cancer cells. GFP-expressing rat microglial cells were seeded onto round glass coverslips at a density of 1 \u0026times; 10\u003csup\u003e4\u003c/sup\u003e/well in a 24-well plate and incubated for 24 h. MDA-231 cells were seeded into the Falcon cell culture inserts with 0.4-\u0026micro;m pores (Falcon) at 6 \u0026times; 10\u003csup\u003e4\u003c/sup\u003e/insert. After 24 h, the inserts were transferred into the plate with microglial cells and co-cultured for 24 h. Microglial cells were fixed with 4% PFA in PBS, washed and mounted. Next, the images were taken and the average single cell area of rat microglia was determined using ImageJ software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eMicroglia and breast cancer cell co-cultures\u003c/h2\u003e \u003cp\u003eHMSV40 microglia human cells (2.5x10\u003csup\u003e6\u003c/sup\u003e ) were seeded on 6-well plates and MDA-MB-231 breast cancer cells were seeded on inserts with 0.4-\u0026micro;m pores at density of 2.5x10\u003csup\u003e6\u003c/sup\u003e /insert. After 24 h, the medium was changed to a microglial medium, and these inserts were transferred into the plate with cancer cells for 0.5 h for Western Blotting analysis and 6 h for gene expression analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eCell viability\u003c/h2\u003e \u003cp\u003eThe cell viability after minocycline treatment was determined using an MTT metabolism assay. Cells were plated at the following densities: BT-549: 3.5 x 10\u003csup\u003e4\u003c/sup\u003e/well; MCF-10A, NHA: 4.0 x 10\u003csup\u003e4\u003c/sup\u003e/well; MDA-231: 5 x 10\u003csup\u003e4\u003c/sup\u003e/well; MCF-7: 6 x 10\u003csup\u003e4\u003c/sup\u003e/well, and cultured for 24, 48 and 72 h in 24-well plates with the addition of the indicated concentrations of the minocycline dissolved in H\u003csub\u003e2\u003c/sub\u003eO: 10, 25, 50, 100, 500 \u0026micro;M. The MTT stock solution (Merck) was added to each well to a final concentration of 0.5 mg/mL. After 2 h of incubation at 37\u0026deg;C the water-insoluble dark blue formazan crystals were dissolved in DMSO. The optical densities were measured at 570 nm using a scanning multi-well spectrophotometer. All measurements were carried out in triplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eCell proliferation\u003c/h2\u003e \u003cp\u003eThe cell proliferation was determined using a Cell Proliferation ELISA, BrdU colorimetric kit (Roche) according to the manufacturer\u0026rsquo;s instructions. The cells were plated onto 96-well plate at density 6000/well and cultured for 48 h. All experiments were performed at least three times, in six replicates.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eDevelopment of stably transfected shSPP1 and control cell lines\u003c/h2\u003e \u003cp\u003eThe \u003cem\u003eSPP1\u003c/em\u003e silencing hairpin (shSPP1) was inserted to pSilencer\u0026trade;2.1-U6 hygro vector; a control plasmid carried the neutral shRNA, not recognising any gene in the human cells. The sequence of the sh\u003cem\u003eSPP1\u003c/em\u003e vector was verified by Sanger sequencing. For electroporation MDA-231 cells (4 x 10\u003csup\u003e5\u003c/sup\u003e ) were trypsinised, suspended in antibiotic-free medium, electroporated with shNEG or shSPP1 plasmids using Lonza 4D-Nucleofector, CH-125 program. Transfected cells were seeded and maintained in a medium supplemented with 600 \u0026micro;g/mL hygromycin, changed every 3 days, until death of mock-transfected cells. Stably transfected cells were expanded from individual colonies and SPP1 knockdown was verified by qPCR. Sequences of short hairpin RNA are listed in the. Table\u0026nbsp;1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe presented data are representative of at least three independent experiments. Error bars indicate standard deviation (SD) for at least three biological replicates. For comparison of differences between two groups, the t-test or chi-square test were used. We used Mantel-Haenszel Odds Ratio estimator, with repetitions as strata, with confidence interval CI95% obtained based on Robins-Breslow-Greenland estimator of variance [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. For comparison\u0026thinsp;\u0026ge;\u0026thinsp;3 groups, the one-way ANOVA was used. Statistical analysis was performed using GraphPad Prism (ver. 6.07) software.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eSPP1 is expressed both in malignant and myeloid cells in the brain metastasis of breast cancer\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe evaluated \u003cem\u003eSPP1\u003c/em\u003e expression levels in primary breast cancer and brain metastases of breast cancer (BrMetBC) in the microarray expression dataset of 29 matched pairs of primary breast cancer with their brain metastases and 22 unmatched brain metastases from breast cancer (GSE14682). \u003cem\u003eSPP1\u003c/em\u003e expression was significantly higher in BrMet than in primary breast cancers (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Using immunohistochemistry we investigated the localization of SPP1 protein in patient-derived BrMetBC tissues. Representative images (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB) show the weak presence of SPP1 in the intact brain parenchyma (P1) and abundant staining within the breast metastatic core (P2) or in both compartments (P3). SPP1 staining was strong in the metastatic core in 8 of 17 analysed cases. SPP1 positivity was detected only in the brain parenchyma in 3 cases, only in the metastatic lesions in 3 cases; 3 cases were SPP1 negative (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo determine if SPP1 is detected in myeloid cells, we employed the staining with antibody recognising HLA-DP,-DQ,-DR (HLA) antigen (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD) and perform double immunofluorescence staining for HLA-DP,R,Q and SPP1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). HLA belong to the MHC class II cell surface receptors and are expressed on antigen-presenting cells, such as microglia, macrophages and dendritic cells [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Interestingly, the number of immune cells (HLA-positive cells) differs between patients and HLA\u003csup\u003e+\u003c/sup\u003e cells are highly abundant around tumour core (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). Co-localisation of HLA and SPP1 staining indicate that some myeloid cells express SPP1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003eUsing immunohistochemical staining we detected high SPP1 levels in primary breast cancer tissue sections. Positive staining was present exclusively in the cytoplasm of malignant cells in 6 cases (out of 7 tested). The level of SPP1 varied between patients; two representative images of high (BC1) and low (BC2) SPP1 positivity are presented (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). We used a publicly available single-cell RNA sequencing (scRNAseq) dataset (GSE118389) to profile \u003cem\u003eSPP1\u003c/em\u003e expression in 6 cases of Triple Negative Breast Cancer (TNBC) in the context of tumour and its microenvironment. \u003cem\u003eSPP1\u003c/em\u003e was identified as one of the top 20 genes with differential expression between cells and showed great variation across the dataset (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). \u003cem\u003eSPP1\u003c/em\u003e was strongly expressed in the clusters 6 and 8, according to differentially expressed genes across clusters (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). A total of 13 clusters were identified in the dataset. The top significant up-regulated genes in the cluster 6 are show (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD) and the majority of these genes were associated with immune processes. More detailed analysis of annotated clusters showed a significant fraction of \u003cem\u003eSPP1\u003c/em\u003e expressing cells in the cluster 6 (macrophages), while only a few cells within clusters 2 (malignant cells) and 8 (smooth muscle cells) had higher levels of \u003cem\u003eSPP1\u003c/em\u003e. Those clusters were spatially isolated from one another, suggesting that both cell types expressing \u003cem\u003eSPP1\u003c/em\u003e have different gene programs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). In each of the clusters, both canonical and manually curated cell type assignments were performed, and macrophages were reported to be the primary component of the tumour microenvironment expressing \u003cem\u003eSPP1\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE-F). Canonical macrophage marker genes, such as genes coding for scavenger receptor cysteine-rich type 1 protein (CD163) or interleukin 1 beta (IL1B), were highly expressed in the cluster 6. Furthermore, high expression of \u003cem\u003eMATN2 (\u003c/em\u003eencoding Matrilin-2), \u003cem\u003eMYLK\u003c/em\u003e (Myosin Light Chain Kinase) or \u003cem\u003eACTA2\u003c/em\u003e (Actin Alpha 2) in the cluster 8 suggested that \u003cem\u003eSPP1\u003c/em\u003e expression was augmented in smooth muscle cells (SMCs).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe performed the Gene Ontology analysis for all differentially expressed genes in the cluster 6 to verify that those cells are macrophages, and found several upregulated genes related to immune signalling pathways (Suppl. Figure\u0026nbsp;1A), which is typically for myeloid cells. A second pathway enrichment analysis using the Kyoto Encyclopaedia of Genes and Genomes (KEGG) database revealed upregulation of genes related to immune pathways such as phagosome, antigen processing and presentation (Suppl. Figure\u0026nbsp;1B).\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eMicroglia enhance invasion of breast cancer cells\u003c/h2\u003e \u003cp\u003eMicroglia respond to different environmental stimuli with the activation programme which results in changing their morphology from a spindle/ramified to a more amoeboid shape [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. To study microglia-breast cancer cell interactions we employed a co-culture system, in which cells are separated by a porous membrane (0.2 \u0026micro;m pores) allowing to exchange only soluble factors. Green fluorescent rat microglial cells were co-cultured with breast cancer cells: MCF7, BT-549 and MDA-231, and after 24 h profound changes in microglial morphology were detected (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). In the presence of breast cancer cells, microglial cell morphology shifted toward the activated state (characterised by round, amoeboid morphology). Representative image (inset) shows highly flatten, amoeboid microglia co-cultured with MDA-231 cells. We quantified the area of individual microglial cells co-cultured with breast cancer cells. On average a single microglial cell was enlarged 2 times when co-cultured with MCF7, and 2,5 times, when co-cultured with BT-549 or MDA-231 in comparison to the untreated cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe strongest induction was evoked by the \u0026lsquo;triple negative\u0026rsquo; breast cancer cells, therefore we used MDA-231 cells for further experiments in which we determined if murine (BV2) or human (HMSV40) microglia affect the invasion of MDA-231 cells in the Matrigel matrix invasion assay (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Matrigel mimics the extracellular matrix (ECM) and cells must actively degrade ECM to appear in the lower compartment. The invasive MDA-231 cells digested the matrigel and crossed the porous membrane. Quantification of nuclei of invading cells shows that in the presence of either BV2 or HMSV40 microglial cells, significantly more MDA-231 cells invaded the matrigel in comparison to control conditions without microglia (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). Notably, the stronger effect was observed in the presence of human microglia, where the chance of an increased invasion of MDA-231 cells was OR\u0026thinsp;=\u0026thinsp;13.8 times higher compared to MDA-231 alone, whereas in murine microglia the odds ratio was OR\u0026thinsp;=\u0026thinsp;7.2.\u003c/p\u003e \u003cp\u003eWe have recently demonstrated that interactions between glioma and microglia can be prevented with a synthetic peptide RGD, which blocks SPP1-integrin receptor signalling, microglia-dependent invasion and reverses immunosuppression in the glioma microenvironment [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. To verify if SPP1 mediates microglia-dependent invasion of breast cancer cells, we used the RGD peptide to block the integrin signalling [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] and RAE as a control. In the RAE peptide, the RGD motif (arginine-glycine-aspartic acid) is changed to RAE (arginine-alanine-glutamic acid), which blunts its activity. We found that the RGD peptide decreased the basal invasion of MDA-231 cells and strongly reduced microglia-dependent invasion (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE-F). The control RAE peptide did not inhibit cell invasion.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eSPP1 mediates microglia-dependent breast cancer cell invasion\u003c/h2\u003e \u003cp\u003eFirstly, we determined expression of \u003cem\u003eSPP1\u003c/em\u003e in a panel of breast cancer cells. In human cells alternative splicing of \u003cem\u003eSPP1\u003c/em\u003e mRNA generates five mRNA variants: \u003cem\u003eSPP1\u003c/em\u003e-a, b, c, 4 and 5. \u003cem\u003eSPP1\u003c/em\u003e-a is a full, canonical form, while SPP1-b (lack exon 5), SPP1-c (deleted exon 4), SPP1-4 (lack exons 4 and 5) and SPP1-5 (contains an additional exon) [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. \u003cem\u003eSPP1\u003c/em\u003e-a, b and c isoforms have been thoroughly investigated in terms of specific functions and correlation with different types of cancer [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], while functions of \u003cem\u003eSPP1\u003c/em\u003e-4 and 5 are poorly known [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. We design primers to determine the mRNA level of particular \u003cem\u003eSPP1\u003c/em\u003e isoforms by RT-qPCR in breast cancer MCF7, BT-474, SKBR3, BT-549 and MDA-231 cells, as well as in the non-cancerous MCF-10a cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). The specific primers for \u003cem\u003eSPP1-a\u003c/em\u003e overlap with the \u003cem\u003eSPP1-5\u003c/em\u003e, however the \u003cem\u003eSPP1-5\u003c/em\u003e expression was very low across the cell lines, thus we assume that with \u003cem\u003eSPP1\u003c/em\u003ea primers we can accurately estimate the \u003cem\u003eSPP1\u003c/em\u003e-a expression.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eqPCR quantification shows that breast cancer cells have variable expression of \u003cem\u003eSPP1\u003c/em\u003e isoforms. The expression of \u003cem\u003eSPP1-a\u003c/em\u003e and \u003cem\u003eSPP1-b\u003c/em\u003e isoforms was the highest among analysed cell lines. The levels of \u003cem\u003eSPP1-a\u003c/em\u003e, \u003cem\u003eSPP1-b\u003c/em\u003e and \u003cem\u003eSPP1-4\u003c/em\u003e were significantly higher in BT-549 and MDA-231 in comparison to non-transformed MCF-10a cells (indicated by \u0026lsquo;*\u0026rsquo;). We did not detect any \u003cem\u003eSPP1\u003c/em\u003e isoforms in BT-474 cells, and \u003cem\u003eSPP1-a\u003c/em\u003e isoform was present in SKBR3 cells (not shown). The \u003cem\u003eSPP1-c\u003c/em\u003e and \u003cem\u003eSPP1-5\u003c/em\u003e isoforms were not detected in MCF-10a cells.\u003c/p\u003e \u003cp\u003eTo determine cellular localization of SPP1, we performed immunofluorescence staining for SPP1 and giantin, a marker of the Golgi system, in MDA-231 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). We showed that SPP1 is localized in the Golgi system, where it may undergo post-translational processing or vesicle packaging for secretion.\u003c/p\u003e \u003cp\u003eTo evaluate the role of SPP1 in breast cancer cell invasion, we developed MDA-231 cells with shRNA mediated, stably knockdown of SPP1. Knockdown efficacy was verified by RT-qPCR of the \u003cem\u003eSPP1-b\u003c/em\u003e mRNA, the most abundant \u003cem\u003eSPP1\u003c/em\u003e mRNA variant in MDA-231, and by Western blotting. The relative expression of \u003cem\u003eSPP1-b\u003c/em\u003e in shSPP1 MDA-231 cells was significantly decreased compared to MDA-231 control cells (shNEG) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). Moreover, the SPP1 protein level was significantly lower in shSPP1 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD) as shown by Western blotting. The SPP1 knockdown did not affect basal cell proliferation as was shown using a BrdU incorporation assay (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE). The presence of HMSV40 microglia augments breast cancer cell invasion. However, microglia dependent invasion of shSPP1 MDA-231 cells was reduced 6 times in comparison to invasion of shNEG cells in co-cultures (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF). Mechanistically, the exposure of human HMSV40 microglial cells to MDA-231 upregulates the p-STAT3 level (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG-H) and \u003cem\u003eMMP-9\u003c/em\u003e expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eI) as demonstrated by Western blotting analysis and qPCR, respectively. These results indicate that cancer cell-derived SPP1 mediates microglial-dependent breast cancer invasion.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMinocycline decrease the viability and SPP1 level in breast cancer cells.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eMinocycline (MINO), a second-generation derivative of tetracycline, shows antimicrobial, anti-inflammatory, neuroprotective and anti-tumorigenic effects, being enrolled clinical trials focusing on non-antibiotic properties [\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Treatment with MINO reduced glioma growth \u003cem\u003ein vivo\u003c/em\u003e by impairing microglia dependent invasion [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. We found that a systemic MINO treatment decreases \u003cem\u003eSpp1\u003c/em\u003e expression in rat C6 glioma cells and reduces intracranial C6 glioma growth \u003cem\u003ein vivo\u003c/em\u003e (unpublished).\u003c/p\u003e \u003cp\u003eTherefore, we investigated the effects of MINO on \u003cem\u003eSPP1\u003c/em\u003e expression and communication between breast cancer cells and microglia. Cell viability of MDA-231, BT-549, MCF7 and non-cancerous MCF10a, normal human astrocytes (NHA) and HMSV40 after treatment for 48 h with MINO at different doses was determined by a MTT metabolism assay (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-B). MINO treatment strongly affected survival of BT-549 and MDA-231 cells (derived from the most aggressive, the \u0026lsquo;triple-negative\u0026rsquo; breast cancer subtype) with IC\u003csub\u003e50\u003c/sub\u003e values from 20.6 to 91.4 \u0026micro;M of MINO, respectively. MCF7 cells and non-cancerous MCF10a cells were more resistant to MINO treatment (IC\u003csub\u003e50\u003c/sub\u003e\u0026thinsp;~\u0026thinsp;135 \u0026micro;M). Interestingly, MINO had a minor effect on NHA (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA) and HMSV40 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB) cells, only at higher concentration\u0026thinsp;\u0026gt;\u0026thinsp;50 \u0026micro;M. Treatment with MINO strongly reduced expression of \u003cem\u003eSPP1\u003c/em\u003e in MDA-231 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC) and BT-549 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD) cells, while low expression of \u003cem\u003eSPP1\u003c/em\u003e in MCF7 cells was not affected (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe tested effects of MINO on microglia-dependent invasion of MDA-231 cells by applying MINO at non-cytotoxic doses. MINO decreased the basal invasion of MDA-231 cells and had weak effects on HMSV40 microglia-dependent invasion of MDA-231 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF). The results suggest strong effects of MINO at MDA-231 cells but not on communication between breast cancer cells and microglia.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the CNS, metastatic cancer cells exploit different non-tumor cell types in the microenvironment to form a permissive niche and support their proliferation and survival. Microglia, as the brain resident phagocytic and antigen presenting cells, play a crucial role in immune surveillance and antitumor responses. Single-cell \u0026lsquo;omic\u0026rsquo; analyses of BrMet specimens and experimental murine BrMet demonstrated functional and spatial heterogeneity of microglia, and contribution of those cells in metastasis formation in the CNS [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Here we present the results indicating the augmented expression and role of SPP1 in the breast cancer cell invasion and metastasis. We prose a mechanism through which breast cancer cells \u0026ldquo;hijack\u0026rdquo; brain resident myeloid cells (microglia) to create a permissive niche and support tumour invasion. We demonstrate that genetic or pharmacological inhibition of SPP1 signalling with an innovative synthetic peptide 7aaRGD or minocycline can restrict breast cancer growth and dissemination.\u003c/p\u003e \u003cp\u003eUsing publicly available datasets, we identified \u003cem\u003eSPP1\u003c/em\u003e as a one of the most expressed genes in triple-negative breast cancers. The re-analysis of scRNAseq datasets shows that cells expressing \u003cem\u003eSPP1\u003c/em\u003e are malignant cells, macrophages and smooth muscle cells. \u003cem\u003eSPP1\u003c/em\u003e is expressed in most malignant cancers, and the increased \u003cem\u003eSPP1\u003c/em\u003e level was related to the dismal prognosis for BRCA, CESC, COAD, HNSC, LUAD, and LUSC patients [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. SPP1 expressed in malignant cells supports cell proliferation via EGFR-mediated activation [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. In smooth muscle cells SPP1 is an inhibitor of calcification [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eImmunostaining for SPP1 showed that breast cancer cells produced SPP1 at various levels, and SPP1 expression was higher in breast cancer BrMet. Staining for human leukocyte antigen (with HLA-DP/DR/DQ antibody) is a standard way to visualise myeloid cells in the brain. HLA positivity does not distinguish between various myeloid populations. Immunocytochemistry shows the presence of SPP1 both in malignant cells and HLA-positive cells (microglia/macrophages) in a vast majority of analysed BrMet tissues.\u003c/p\u003e \u003cp\u003eTo study the role of breast cancer-derived SPP1 in interactions of those cells with microglia, we determined SPP1 expression in cultured breast cancer cells and established a co-culture system for mechanistic studies. Three tested breast cancer cell lines induced morphological changes of rat microglia in co-cultures which was quantified as the increase of microglial cell area. This type of amoeboid, morphological transformation of microglia is consistent with their pro-tumour activation, which was observed in glioma-microglia co-cultures [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Consistently, the presence of microglial cells (either murine BV2 or human HM SV40 microglial cells) strongly increased invasion of MDA-231 cells, which are cells with the highest expression of SPP1. Blocking SPP1-integrin signalling with the RGD peptide slightly reduced a basal invasion and strongly reduced microglia-induced invasion; the control RAE peptide (the similar sequence with replacement of the RGD motif by the RAE motif). Mechanistically, the exposure of human HMSV40 microglial cells to MDA-231 upregulates the p-STAT3 level and expression of \u003cem\u003eMMP-9\u003c/em\u003e, its transcriptional target in many cells. These results indicate that cancer cell-derived SPP1 mediates microglial-dependent breast cancer invasion likely via pSTAT3-MMP9 axis.\u003c/p\u003e \u003cp\u003eQuantitative analysis shows the elevated expression of \u003cem\u003eSPP1-c\u003c/em\u003e in breast cancer cell lines in comparison to non-cancerous breast cells. \u003cem\u003eSPP1\u003c/em\u003e is particularly highly expressed in MDA-231 cells (which ER, PR, and E-cadherin negative and expresses the mutated p53). \u003cem\u003eSPP1-c\u003c/em\u003e was considered a selective marker in breast cancer [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] and to lesser extent a favourable predictor to tamoxifen treatment [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Knockdown of SPP1 expression in MDA-231 cells shows that while SPP1 is negligent for a basal cell proliferation, its lack abolishes microglia-dependent invasion. It points to a cancer cell-derived SPP1 as a factor activating microglia which in turn support cancer cell invasion in the brain parenchyma.\u003c/p\u003e \u003cp\u003eMINO is a blood-brain barrier penetrating, FDA approved antibiotic with a favourable pharmacokinetics, and has been effective in reducing glioma growth in mice through the attenuation of microglia-dependent invasion and microglial expression of the metalloproteinase MT1-MMP/MMP14 [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. We demonstrate that MINO reduced survival of breast cancer cells, while had no influence on viability of normal human astrocytes or microglial cells (up to 50 \u0026micro;M). MDA-231 and BT-549 cells were the most sensitive. Interestingly, in both MDA-231 and BT-549 cells MINO treatment reduced significantly the \u003cem\u003eSPP1\u003c/em\u003e expression, particularly in MDA-231 cells. Moreover, MINO treatment reduced invasion of MDA-231 cells. The results show that MINO by blocking \u003cem\u003eSPP1\u003c/em\u003e expression in breast cancer cells reduces the microglial support within the tumour niche. These results raise an interesting opportunity of using MINO as a novel therapeutic treatment against breast cancer and its brain metastasis.\u003c/p\u003e \u003cp\u003eFor patients with brain metastases, the surgery and radiotherapy remain a main therapeutic option, and the further treatment is strictly dependent on the cancer type, size and individual factors. For breast cancer there are many systemic therapies dependent on the hormone and HER2 status, however there is a limited number of treatment recommendations for breast cancer BrMets [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Recent evidence shows that BrMet-associated myeloid cells are derived from resident microglia cells (10\u0026ndash;50%) and infiltrated monocytes (25\u0026ndash;75%) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The presence of APOE+, metastasis-associated macrophages expressing SPP1 and SPP1\u0026thinsp;+\u0026thinsp;tumor associated macrophages have been described in BrMet, and linked to therapy resistance and angiogenesis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Identifying the contribution of myeloid cells to metastasis in the brain may facilitate developing new therapeutic modalities. The potent anti-invasion effects of the 7aaRGD peptide (RGD) in microglia-MDA-231 cell co-cultures hold a promise of a new treatment option as the efficacy of this peptide in modulation of the tumour microenvironment in intracranial gliomas has been recently demonstrated [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eSPP1 is highly expressed in BrMets both in malignant and myeloid cells. Its high expression is maintained in breast cancer cells and those cells strongly activate microglia in co-cultures, which in turn increases cancer cell invasion. Blocking SPP1-mediated cancer-microglia communication with the 7aaRGD interfering peptide or shRNA mediated knockdown of SPP1 in cancer cells, abolished microglia-dependent cancer cell invasion. FDA approved drug minocycline efficiently reduces the expression of \u003cem\u003eSPP1\u003c/em\u003e in several breast cancer cells, and decreases both the basal and microglia-induced invasion of breast cancer cells. The results highlight the important role of breast cancer-derived SPP1 in shaping the permissive microenvironment of BrMets, and indicate a potential of the 7aaRGD peptide or minocycline as new therapeutics in breast cancer BrMet treatment.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBrMet\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebrain metastasis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMINO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eminocycline\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMMP9\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ematrix metalloproteinase 9\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSPP1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003esecreted phopshoprotein 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKamil Wojnicki performed most of the experimenst, have analyzed the data and organized all Figures. Katarzyna Poleszak, Agata Kochalska-Les, Kacper Waśniewski, Barbora Vymolova contributed to determination of cell invasion.\u0026nbsp;Adria-Jaume Rouraanalysed scRNAesq data. Ewa Matyja, Tomasz Czernicki, Wiesława Grajkowska provided FFPE section from patients and pathological consultations. Bozena Kaminskaand Kamil Wojnicki have conceived the idea, contributed to data generation and interpretation. Bozena Kaminskaand Kamil Wojnicki have written the first draft. Bozena Kaminskahas designed the study and acquired the required funds. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudies were supported by the\u0026nbsp;TRANSCAN-3/1/168/2022 ImmuMet project funded by National Center for Research and Development, Poland.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank Maciej Sobczyński, PhD for help in statistical analysis of the data; Małgorzata Całka-Kresa and Artut Wolny from Laboratory of Imaging Tissue Structure and Function at Nencki Institute of Experimental Biology for their kind assistance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish declaration:\u003c/strong\u003e not applicable\u0026rsquo;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics and Consent to Participate declarations\u003c/strong\u003e: not applicable\u0026rsquo;.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin . American Cancer Society; 2021;71:209\u0026ndash;49. \u003c/li\u003e\n\u003cli\u003eGoldhirsch A, Winer EP, Coates AS, Gelber RD, Piccart-Gebhart M, Th\u0026uuml;rlimann B, et al. Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013. Ann Oncol Off J Eur Soc Med Oncol. 2013;24:2206\u0026ndash;23. \u003c/li\u003e\n\u003cli\u003eFallahpour S, Navaneelan T, De P, Borgo A. Breast cancer survival by molecular subtype: a population-based analysis of cancer registry data. C Open . 2017;5:E734 LP-E739. \u003c/li\u003e\n\u003cli\u003eWeide R, Feiten S, Friesenhahn V, Heymanns J, Kleboth K, Thomalla J, et al. Metastatic breast cancer: prolongation of survival in routine care is restricted to hormone-receptor- and Her2-positive tumors. Springerplus . 2014;3:535. \u003c/li\u003e\n\u003cli\u003eSuh JH, Kotecha R, Chao ST, Ahluwalia MS, Sahgal A, Chang EL. Current approaches to the management of brain metastases. Nat Rev Clin Oncol . 2020;17:279\u0026ndash;99. \u003c/li\u003e\n\u003cli\u003eRostami R, Mittal S, Rostami P. Brain metastasis in breast cancer : a comprehensive literature review. J Neurooncol. Springer US; 2016;127:407\u0026ndash;14. \u003c/li\u003e\n\u003cli\u003eBejarano L, Kauzlaric A, Lamprou E, Lourenco J, Fournier N, Ballabio M, et al. Interrogation of endothelial and mural cells in brain metastasis reveals key immune-regulatory mechanisms. Cancer Cell . Elsevier; 2024;42:378-395.e10. \u003c/li\u003e\n\u003cli\u003eGonzalez H, Mei W, Robles I, Hagerling C, Allen BM, Hauge Okholm TL, et al. Cellular architecture of human brain metastases. Cell . Elsevier; 2022;185:729-745.e20. \u003c/li\u003e\n\u003cli\u003eZhang L, Li Z, Skrzypczynska KM, Fang Q, Zhang W, O\u0026rsquo;Brien SA, et al. Single-Cell Analyses Inform Mechanisms of Myeloid-Targeted Therapies in Colon Cancer. Cell. 2020;181:442-459.e29. \u003c/li\u003e\n\u003cli\u003eFriebel E, Kapolou K, Unger S, N\u0026uacute;\u0026ntilde;ez NG, Utz S, Rushing EJ, et al. Single-Cell Mapping of Human Brain Cancer Reveals Tumor-Specific Instruction of Tissue-Invading Leukocytes. Cell. United States; 2020;181:1626-1642.e20. \u003c/li\u003e\n\u003cli\u003eKlemm F, Maas RR, Bowman RL, Kornete M, Soukup K, Nassiri S, et al. Interrogation of the Microenvironmental Landscape in Brain Tumors Reveals Disease-Specific Alterations of Immune Cells. Cell 2020;181:1643-1660.e17. \u003c/li\u003e\n\u003cli\u003eTuck AB, O\u0026rsquo;Malley FP, Singhal H, Harris JF, Tonkin KS, Kerkvliet N, et al. Osteopontin expression in a group of lymph node negative breast cancer patients. Int J cancer 1998;79:502\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eSenger DR, Perruzzi CA, Papadopoulos-Sergiou A, Van de Water L. Adhesive properties of osteopontin: regulation by a naturally occurring thrombin-cleavage in close proximity to the GRGDS cell-binding domain. Mol Biol Cell 1994;5:565\u0026ndash;74. \u003c/li\u003e\n\u003cli\u003eChristensen B, Nielsen MS, Haselmann KF, Petersen TE, S\u0026oslash;rensen ES. Post-translationally modified residues of native human osteopontin are located in clusters: identification of 36 phosphorylation and five O-glycosylation sites and their biological implications. Biochem J . 2005;390:285\u0026ndash;92. \u003c/li\u003e\n\u003cli\u003eZhang H, Guo M, Chen J-H, Wang Z, Du X-F, Liu P-X, et al. Osteopontin knockdown inhibits \u0026alpha;v,\u0026beta;3 integrin-induced cell migration and invasion and promotes apoptosis of breast cancer cells by inducing autophagy and inactivating the PI3K/Akt/mTOR pathway. Cell Physiol Biochem Int J Exp Cell Physiol Biochem Pharmacol. Germany; 2014;33:991\u0026ndash;1002. \u003c/li\u003e\n\u003cli\u003eChen Q, Shou P, Zhang L, Xu C, Zheng C, Han Y, et al. An osteopontin-integrin interaction plays a critical role in directing adipogenesis and osteogenesis by mesenchymal stem cells. Stem Cells . 2014;32:327\u0026ndash;37. \u003c/li\u003e\n\u003cli\u003eZou C, Luo Q, Qin J, Shi Y, Yang L, Ju B, et al. Osteopontin promotes mesenchymal stem cell migration and lessens cell stiffness via integrin \u0026beta;1, FAK, and ERK pathways. Cell Biochem Biophys. United States; 2013;65:455\u0026ndash;62. \u003c/li\u003e\n\u003cli\u003eYan W, Qian C, Zhao P, Zhang J, Shi L, Qian J, et al. Expression pattern of osteopontin splice variants and its functions on cell apoptosis and invasion in glioma cells. Neuro Oncol . 2010;12:765\u0026ndash;75. \u003c/li\u003e\n\u003cli\u003eWeber GF, Lett GS, Haubein NC. Osteopontin is a marker for cancer aggressiveness and patient survival. Br J Cancer . Nature Publishing Group; 2010;103:861\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eGardner HA, Berse B, Senger DR. Specific reduction in osteopontin synthesis by antisense RNA inhibits the tumorigenicity of transformed Rat1 fibroblasts. Oncogene. England; 1994;9:2321\u0026ndash;6. \u003c/li\u003e\n\u003cli\u003eRittling SR, Chambers AF. Role of osteopontin in tumour progression. Br J Cancer . Nature Publishing Group; 2004;90:1877\u0026ndash;81. \u003c/li\u003e\n\u003cli\u003eKumar V, Behera R, Lohite K, Karnik S, Kundu GC. p38 kinase is crucial for osteopontin-induced furin expression that supports cervical cancer progression. Cancer Res. United States; 2010;70:10381\u0026ndash;91. \u003c/li\u003e\n\u003cli\u003eSyamal D. Bhattacharya, Juline Garrison, Hongtao Guo, Zhiyong Mi, Jovan Markovic, Victoria M. Kim PCK. Micro-RNA-181a regulates osteopontin-dependent metastatic function in hepatocellular cancer cell lines. Surgery. 2010;148. \u003c/li\u003e\n\u003cli\u003eMi Z, Guo H, Russell MB, Liu Y, Sullenger BA, Kuo PC. RNA aptamer blockade of osteopontin inhibits growth and metastasis of MDA-MB231 breast cancer cells. Mol Ther. 2009;17:153\u0026ndash;61. \u003c/li\u003e\n\u003cli\u003eDai J, Li B, Shi J, Peng L, Zhang D, Qian W, et al. A humanized anti-osteopontin antibody inhibits breast cancer growth and metastasis in vivo. Cancer Immunol Immunother. Germany; 2010;59:355\u0026ndash;66. \u003c/li\u003e\n\u003cli\u003eKaraayvaz M, Cristea S, Gillespie SM, Patel AP, Mylvaganam R, Luo CC, et al. Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq. Nat Commun . 2018;9:3588. \u003c/li\u003e\n\u003cli\u003eStuart T, Butler A, Hoffman P, Hafemeister C, Papalexi E, Mauck WM, et al. Comprehensive Integration of Single-Cell Data. Cell . 2019;177:1888-1902.e21. \u003c/li\u003e\n\u003cli\u003eOchocka N, Segit P, Walentynowicz KA, Wojnicki K, Cyranowski S, Swatler J, et al. Single-cell RNA sequencing reveals functional heterogeneity of glioma-associated brain macrophages. Nat Commun . 2021;12:1151. \u003c/li\u003e\n\u003cli\u003eMacosko EZ, Basu A, Satija R, Nemesh J, Shekhar K, Goldman M, et al. Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets. Cell . Elsevier; 2015;161:1202\u0026ndash;14. \u003c/li\u003e\n\u003cli\u003eZawadzka M, Kaminska B. A novel mechanism of FK506-mediated neuroprotection: Downregulation of cytokine expression in glial cells. Glia. John Wiley \u0026amp; Sons, Ltd; 2005;49:36\u0026ndash;51. \u003c/li\u003e\n\u003cli\u003eCiechomska IA, Gabrusiewicz K, Szczepankiewicz AA, Kaminska B. Endoplasmic reticulum stress triggers autophagy in malignant glioma cells undergoing cyclosporine A-induced cell death. Oncogene. 2013;32:1518\u0026ndash;29. \u003c/li\u003e\n\u003cli\u003ePhillips A, Holland PW. Estimators of the Variance of the Mantel-Haenszel Log-Odds-Ratio Estimate. Biometrics . [Wiley, International Biometric Society]; 1987;43:425\u0026ndash;31. \u003c/li\u003e\n\u003cli\u003eRobins J, Breslow N, Greenland S. Estimators of the Mantel-Haenszel variance consistent in both sparse data and large-strata limiting models. Biometrics. United States; 1986;42:311\u0026ndash;23. \u003c/li\u003e\n\u003cli\u003eUlvestad E, Williams K, B\u0026oslash; L, Trapp B, Antel J, M\u0026oslash;rk S. HLA class II molecules (HLA-DR, -DP, -DQ) on cells in the human CNS studied in situ and in vitro. Immunology. 1994;82:535\u0026ndash;41. \u003c/li\u003e\n\u003cli\u003eEllert-Miklaszewska A, Dabrowski M, Lipko M, Sliwa M, Maleszewska M, Kaminska B. Molecular definition of the pro-tumorigenic phenotype of glioma-activated microglia. Glia. United States; 2013;61:1178\u0026ndash;90. \u003c/li\u003e\n\u003cli\u003eEllert-Miklaszewska A, Pilanc-Kudlek P, Poleszak K, Roura A-J, Cyranowski S, Ghosh M, et al. Integrin blocking peptide reverses immunosuppression in experimental gliomas and improves anti-PD-1 therapy outcome. bioRxiv. 2024;2024.08.06.606798. \u003c/li\u003e\n\u003cli\u003eEllert-Miklaszewska A, Wisniewski P, Kijewska M, Gajdanowicz P, Pszczolkowska D, Przanowski P, et al. Tumour-processed osteopontin and lactadherin drive the protumorigenic reprogramming of microglia and glioma progression. Oncogene. 2016;35:6366\u0026ndash;77. \u003c/li\u003e\n\u003cli\u003eBriones-Orta MA, Avenda\u0026ntilde;o-V\u0026aacute;zquez SE, Aparicio-Bautista DI, Coombes JD, Weber GF, Syn W-K. Osteopontin splice variants and polymorphisms in cancer progression and prognosis. Biochim Biophys acta Rev cancer. Netherlands; 2017;1868:93-108.A. \u003c/li\u003e\n\u003cli\u003eHe B, Mirza M, Weber GF. An osteopontin splice variant induces anchorage independence in human breast cancer cells. Oncogene. 2006;25:2192\u0026ndash;202. \u003c/li\u003e\n\u003cli\u003eSilva GR, Mattos DS, Bastos ACF, Viana BPPB, Brum MCM, Ferreira LB, et al. Osteopontin-4 and Osteopontin-5 splice variants are expressed in several tumor cell lines. Mol Biol Rep . 2020;47:8339\u0026ndash;45. \u003c/li\u003e\n\u003cli\u003ehttps://clinicaltrials.gov. \u003c/li\u003e\n\u003cli\u003eMatsukawa N, Yasuhara T, Hara K, Xu L, Maki M, Yu G, et al. Therapeutic targets and limits of minocycline neuroprotection in experimental ischemic stroke. BMC Neurosci . 2009;10:126. \u003c/li\u003e\n\u003cli\u003eMarkovic DS, Vinnakota K, van Rooijen N, Kiwit J, Synowitz M, Glass R, et al. Minocycline reduces glioma expansion and invasion by attenuating microglial MT1-MMP expression. Brain Behav Immun . 2011;25:624\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eHu F, Ku M-C, Markovic D, Dzaye O, Lehnardt S, Synowitz M, et al. Glioma-associated microglial MMP9 expression is upregulated by TLR2 signaling and sensitive to minocycline. Int J Cancer . John Wiley \u0026amp; Sons, Ltd; 2014;135:2569\u0026ndash;78. \u003c/li\u003e\n\u003cli\u003eYou H, Baluszek S, Kaminska B. Immune Microenvironment of Brain Metastases\u0026mdash;Are Microglia and Other Brain Macrophages Little Helpers? Front Immunol. 2019;10. \u003c/li\u003e\n\u003cli\u003eYou H, Baluszek S, Kaminska B. Supportive roles of brain macrophages in CNS metastases and assessment of new approaches targeting their functions. Theranostics. Australia; 2020;10:2949\u0026ndash;64. \u003c/li\u003e\n\u003cli\u003eChandra Tripathi S, Chakraborty G, Simoes D, Yang Y, Wei T, Bi G, et al. The Significance of Secreted Phosphoprotein 1 in Multiple Human Cancers. 2020\u003c/li\u003e\n\u003cli\u003eLee SJ, Baek SE, Jang MA, Kim CD. Osteopontin plays a key role in vascular smooth muscle cell proliferation via EGFR-mediated activation of AP-1 and C/EBP\u0026beta; pathways. Pharmacol Res. Netherlands; 2016;108:1\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eSpeer MY, Chien YC, Quan M, Yang HY, Vali H, McKee MD, et al. Smooth muscle cells deficient in osteopontin have enhanced susceptibility to calcification in vitro. Cardiovasc Res. 2005;66:324\u0026ndash;33. \u003c/li\u003e\n\u003cli\u003eMirza M, Shaughnessy E, Hurley JK, Vanpatten KA, Pestano GA, He B, et al. Osteopontin-c is a selective marker of breast cancer. Int J cancer. United States; 2008;122:889\u0026ndash;97. \u003c/li\u003e\n\u003cli\u003eZduniak K, Agrawal A, Agrawal S, Hossain MM, Ziolkowski P, Weber GF. Osteopontin splice variants are differential predictors of breast cancer treatment responses. BMC Cancer. BioMed Central; 2016;16:441.\u003c/li\u003e\n\u003cli\u003eVogelbaum MA, Brown PD, Messersmith H, Brastianos PK, Burri S, Cahill D, et al. Treatment for Brain Metastases: ASCO-SNO-ASTRO Guideline. J Clin Oncol. Wolters Kluwer; 2021;40:492\u0026ndash;516. \u003cstrong\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"604\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHuman microglia culture\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 406px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReagent\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSource\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 406px;\"\u003e\n \u003cp\u003eHuman microglia cell line (HMSV40) (# T0251)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003eApplied Biological Materials\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 406px;\"\u003e\n \u003cp\u003ePriCoat T25 flask (# G299)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003eApplied Biological Materials\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 406px;\"\u003e\n \u003cp\u003ePrigrow III Medium (# TM003)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003eApplied Biological Materials\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAntibodies used for stainings\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 233px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAntibody\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClone\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eManufacturer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCat. number\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDilution\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003eanti-HLA-DP, -DQ, -DR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eCR3/43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003eDAKO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eM0775\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1:200\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003eanti-osteopontin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003eMilliporeSigma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eHPA027541\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eIHC: 1:100\u003c/p\u003e\n \u003cp\u003eIF: \u0026nbsp; \u0026nbsp;1:100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003eanti-giantin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003eAbcam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eab37266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1:200\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003ehorseradish peroxidase-conjugated\u0026nbsp;horse anti-mouse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eVector\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 94px;\"\u003e\n \u003cp\u003eBA2000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e1:200\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003ehorseradish peroxidase-conjugated\u0026nbsp;horse anti-rabbit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eVector\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 94px;\"\u003e\n \u003cp\u003eBA1100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e1:200\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003edonkey anti-rabbit A555\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003eThermoFisher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eA31572\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1:1000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003edonkey anti-mouse A488\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003eThermoFisher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eA21202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1:1000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003eExtrAvidin\u0026trade;\u0026minus;Peroxidase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003eSigma-Aldrich\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eE2886\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1:200\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAntibodies used for immunoblotting\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003eanti-phospho-STAT3 (Y705)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eM9C6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003eCell signaling\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e4113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1:1000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003eanti-STAT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e124H6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003eCell signaling\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e9139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1:1000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003ehorseradish peroxidase-conjugated monoclonal anti-\u0026beta;-actin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eAC-15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eSigma Aldrich\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 94px;\"\u003e\n \u003cp\u003eA3854\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e1:40000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003eanti-glyceraldehyde-3-phosphate dehydrogenase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e6C5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eMerck\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 94px;\"\u003e\n \u003cp\u003eMAB374\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e1:25000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003ehorseradish peroxidase-conjugated anti-rabbit IgG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eVector\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 94px;\"\u003e\n \u003cp\u003ePI-1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e1:10000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003ehorseradish peroxidase-conjugated anti-mouse IgG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eVector\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 94px;\"\u003e\n \u003cp\u003ePI-2000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e1:10000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOligonucleotides\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 501px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReagent\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSource\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 501px;\"\u003e\n \u003cp\u003ehuman \u003cem\u003eSPP1-b\u0026nbsp;\u003c/em\u003eqPCR\u003c/p\u003e\n \u003cp\u003ef- TTGGAAGGGTCTGTGGGGCTAGG, r- CCTCCTAGGCATCACCTGTGCCAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eGenomed\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 501px;\"\u003e\n \u003cp\u003ehuman \u003cem\u003eSPP1-c\u0026nbsp;\u003c/em\u003eqPCR\u003c/p\u003e\n \u003cp\u003ef- GAATTGCAGTGATTTGCTTTTGC, r- AGGACACAGCATTCTGCTTTTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eGenomed\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 501px;\"\u003e\n \u003cp\u003ehuman \u003cem\u003eSPP1-4\u0026nbsp;\u003c/em\u003eqPCR\u003c/p\u003e\n \u003cp\u003ef- GAATTGCAGTGATTTGCTTTTGC, r- GGAAGGGTCTGCTTTTCCTCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eGenomed\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 501px;\"\u003e\n \u003cp\u003ehuman \u003cem\u003eSPP1-5\u0026nbsp;\u003c/em\u003eqPCR\u003c/p\u003e\n \u003cp\u003ef- GAATTGCAGTGATTTGCTTTTGC, r- AGGTACATCTTTAGTGCTGCTTTTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eGenomed\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 501px;\"\u003e\n \u003cp\u003ehuman \u003cem\u003eGAPDH\u0026nbsp;\u003c/em\u003eqPCR\u003c/p\u003e\n \u003cp\u003ef- AGGGCTGCTTTTAACTCTGGT, r- CCCCACTTGATTTTGGAGGGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eGenomed\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 501px;\"\u003e\n \u003cp\u003eHuman MMP9 qPCR\u003c/p\u003e\n \u003cp\u003eHs00234579_m1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eApplied Biosystems\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 501px;\"\u003e\n \u003cp\u003eshSPP1:\u003c/p\u003e\n \u003cp\u003eGAT CCC AAG TAA GTC CAA CGA AAT TCA AGA GAT TTC GTT GGA CTT ACT TGG TTT TTG GAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 501px;\"\u003e\n \u003cp\u003eshNEG: \u0026nbsp;pSilencer 2.1-U6 hygro (# AM5760)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eThermoFisher\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInvasion assay / co-culture\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 501px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReagent\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSource\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 501px;\"\u003e\n \u003cp\u003e6.5 mm Transwell\u0026reg; with 8.0 \u0026micro;m Pore Polycarbonate Membrane Insert (#\u0026nbsp;3422)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eCorning\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 501px;\"\u003e\n \u003cp\u003eGrowth Factor Reduced Matrigel\u0026trade; Matrix (# 356231)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eBD Biosciences\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 501px;\"\u003e\n \u003cp\u003eFalcon cell culture inserts (0.4-\u0026micro;m pores)\u0026nbsp;(# 353095)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eFalcon\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther reagents\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 500px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReagent\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSource\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 500px;\"\u003e\n \u003cp\u003eCell Proliferation ELISA, BrdU colorimetric kit (# 11647229001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eRoche\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 233px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"breast cancer brain metastasis, tumour-microglia communication, BrMet niche, synthetic peptides, minocycline","lastPublishedDoi":"10.21203/rs.3.rs-5410549/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5410549/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBrain metastases (BrMets) occur in 20%-40% of patients with breast cancer and contribute significantly to morbidity and/or mortality. BrMets are more common in certain breast cancer subtypes, such as human epidermal growth factor receptor 2\u0026ndash;positive breast cancer, which has a higher incidence of BrMets. The molecular mechanisms that drive and permit the progression of metastasis in the brain are poorly understood. Identifying components of the metastatic niches and propensities of primary tumors towards the brain microenvironment are essential to improve our understanding of BrMet development, patient management and outcomes. SPP1, a secreted phosphoglycoprotein 1, is a potent activator of microglia (brain resident myeloid cells) in malignant gliomas. SPP1 is elevated in breast cancer and breast cancer brain metastasis. Exploration of public bulk and scRNAseq datasets shows high \u003cem\u003eSPP1\u003c/em\u003e overexpression in breast malignant cells, as well as in the immune cells in BrMets. We found that breast cancer cells with high expression of \u003cem\u003eSPP1\u003c/em\u003e strongly activate microglia in co-cultures, which in turn increases cancer cell invasion. Blocking SPP1-mediated cancer-microglia communication with the 7aaRGD interfering peptide or shRNA mediated knockdown of SPP1 in cancer cells, abolished microglia-dependent cancer cell invasion. Notably, we found that an antibiotic minocycline efficiently reduces the expression of \u003cem\u003eSPP1\u003c/em\u003e in several breast cancer cell lines, and decreases both the basal and microglia-induced invasion of breast cancer cells. The results highlight the important role of breast cancer-derived SPP1 in shaping the permissive microenvironment of BrMet, and indicate a potential of the 7aaRGD peptide or minocycline to be new therapeutics in breast cancer brain metastasis treatment.\u003c/p\u003e","manuscriptTitle":"Tumour-derived secreted phosphoprotein 1/SPP1 via activation of microglia contributes to the formation of the breast cancer brain metastatic niche","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-18 15:03:18","doi":"10.21203/rs.3.rs-5410549/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5eff71e6-719e-48a0-a313-c4829f0574d7","owner":[],"postedDate":"December 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-12T00:38:14+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-18 15:03:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5410549","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5410549","identity":"rs-5410549","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}