TFPI Alpha and Beta Regulate mRNAs and microRNAs Involved in Cancer Biology and in the Immune System in Breast Cancer Cells

<div><p>Emerging evidence indicate a new role of TFPI in cancer biology. We recently reported that both isoforms of TFPI induced apoptosis and inhibited proliferation of cancer cells. The signaling pathway(s) mediating the effects of TFPI is, however, presently still unclear. Our goal was to further investigate the cellular processes affected by TFPI and to get insight into the molecular mechanisms involved in the effects of TFPI, using a global gene expression study approach. TFPIα or TFPIβ cDNA were transfected into SK-BR-3 breast cancer cells for stable overexpression. Global mRNA and microRNA (miRNA) expressions were measured and functional annotation of the differentially expressed genes and miRNAs according to gene ontology terms was conducted. Selected results were validated using qRT-PCR and Western blot. A total of 242 and 801 mRNA transcripts and 120 and 46 miRNAs were differentially expressed in cells overexpressing TFPIα or TFPIβ, respectively. Overexpression of either isoform significantly affected the expression of genes involved in cell development (apoptosis, cell movement, migration, invasion, colony formation, growth, and adhesion) and immune response. Network analyses revealed biological interactions between these genes and implied that several of the genes may be involved in both processes. The expression profiles also correlated significantly with clinical phenotype and outcome. Functional cluster analyses indicated altered activity of the epidermal growth factor receptor, small GTPases, and the NF-κB and JAK/STAT cascades when TFPI was overexpressed, and increased activity of the transcription factors NF-κB and Elk-1 and phospho-Akt levels was observed. Integrated mRNA-miRNA analyses showed that 19% and 32% of the differentially expressed genes in cells overexpressing TFPIα or TFPIβ, respectively, may have been regulated by miRNAs. Overexpression of TFPI in breast cancer cells affected the expression of mRNAs and miRNAs involved in processes facilitating cancer cell growth and immunologic response, possibly by signal transduction involving the EGFR pathway.</p> </div

Transcription factor activity and phospho-Akt in cells after overexpression of TFPI.

<p>(A) Transcription factor activity was measured using the cignal finder luciferase reporter system. SK-BR-3 cells (3×10⁴) transiently transfected with vectors overexpressing TFPIα (dark gray) or TFPIβ (gray), or with empty vector pTOPO (light gray) as controls were seeded in 96-well arrays 24 hours after transfection. After 48 hours, cells were lysed and the firefly and renilla luciferase intensity determined. The results are presented as mean (n≥8) relative luciferase activity + SEM of three independent experiments. Statistical differences between cells overexpressing TFPI and empty vector control cells were determined using the student's t test (* <i>p</i><.05, ** <i>p</i><.01, *** <i>p</i><.001, ns  =  not significant). (B) Western blot of phospho-Akt in SK-BR-3 cells overexpressing TFPI. Band intensities were measured using ImageJ and the intensities of phospho-Akt were normalized to Akt levels.</p

Validation of microarray and miRNA array expression results.

<p>Selected mRNAs (A and B) and miRNAs (C and D) differentially expressed in SK-BR-3 cells overexpressing TFPIα (A and C) or TFPIβ (B and D) were validated by Taqman single assays and qRT-PCR. Results were normalized against the endogenous controls PMM1 and U6 snRNA and the relative expression calculated using the comparative Ct method. Values are presented as mean (n = 3) fold change (FC) of empty vector pTOPO control + SEM of three biological replicates. White bars indicate array expression values, black bars represent Taqman verification values. Dotted lines indicate FC  = |2|.</p

Venn diagrams of differentially expressed miRNAs after overexpression of TFPIα or TFPIβ.

<p>miRNAs associated with molecular and cellular function (A) and cancer disease (B), as annotated by the Ingenuity Pathway Analysis software.</p

Clinical relevance of gene signatures following overexpression of TFPIα or TFPIβ.

<p>Three publicly available, clinically annotated breast cancer datasets (GSE6532, GSE4922, and GSE7390) were downloaded from the Gene Expression Omnibus (GEO) database at NCBI and merged. Associations between the differentially expressed genes and clinical variables were evaluated using the <i>globaltest</i> package in R.</p

EGFR protein levels detected in the lysate of transfected SK-BR-3 cells by Western blot analysis.

<p>Proteins were separated on a SDS-polyacrylamide gel, transferred to a nitrocellulose membrane and detected using an anti-EGFR antibody. Anti-actin was used as a protein loading control. (A) Western blot of one representative experiment. (B) Quantification of three independent experiments using ImageJ (n = 3+ SEM).</p

Differentially expressed miRNAs with predicted mRNA targets oppositely regulated in both cell lines overexpressing TFPI.

*<p>Fold change.</p

Overexpression of TFPI in breast cancer cells.

<p>Overexpression of TFPIα or TFPIβ in SK-BR-3 breast cancer cells, displayed as a summary of previously reported data <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0047184#pone.0047184-Stavik1" target="_blank">[18]</a>. mRNA levels were quantified using qRT-PCR. Protein levels were measured in cell medium using total TFPI ELISA. Results are presented relatively as mean fold change (FC) of control (n = 3± SD). * Relative increase in TFPI antigen measured in cell medium after PI-PLC treatment.</p

Signal transduction mechanisms affected after overexpression of TFPIα or TFPIβ.

<p>The differentially expressed mRNAs were loaded into eGOn for functional annotation, and the Master-Target test was used to identify significantly over-represented gene ontology categories (by comparing the number of genes associated with a gene ontology category to the total number of genes in the array associated with that category).</p

Syndecan-3 and TFPI Colocalize on the Surface of Endothelial-, Smooth Muscle-, and Cancer Cells

<div><p>Background</p><p>Tissue factor (TF) pathway inhibitor (TFPI) exists in two isoforms; TFPIα and TFPIβ. Both isoforms are cell surface attached mainly through glycosylphosphatidylinositol (GPI) anchors. TFPIα has also been proposed to bind other surface molecules, like glycosaminoglycans (GAGs). Cell surface TFPIβ has been shown to exert higher anticoagulant activity than TFPIα, suggesting alternative functions for TFPIα. Further characterization and search for novel TFPI binding partners is crucial to completely understand the biological functions of cell associated TFPI.</p><p>Methods and Results</p><p>Potential association of TFPI to heparan sulphate (HS) proteoglycans in the syndecan family were evaluated by knock down studies and flow cytometry analysis. Cell surface colocalization was assessed by confocal microscopy, and native PAGE or immunoprecipitation followed by Western blotting was used to test for protein interaction. Heparanase was used to enzymatically degrade cell surface HS GAGs. Anticoagulant potential was evaluated using a factor Xa (FXa) activity assay. Knock down of syndecan-3 in endothelial,- smooth muscle- and breast cancer cells reduced the TFPI surface levels by 20-50%, and an association of TFPIα to syndecan-3 on the cell surface was demonstrated. Western blotting indicated that TFPIα was found in complex with syndecan-3. The TFPI bound to syndecan-3 did not inhibit the FXa generation. Removal of HS GAGs did not release TFPI antigen from the cells.</p><p>Conclusions</p><p>We demonstrated an association between TFPIα and syndecan-3 in vascular cells and in cancer cells, which did not appear to depend on HS GAGs. No anticoagulant activity was detected for the TFPI associated with syndecan-3, which may indicate coagulation independent functions for this cell associated TFPI pool. This will, however, require further investigation.</p></div