Search

Additional file 1: Supplementary Figure S1. EDI3 is highly expressed in ER-HER2+ cells and is regulated by HER2. A (left panel), HER2 mRNA expression measured using qRT-PCR. Quantification of A (right panel), HER2 and B, ER protein expression from immunoblotting as represented in Figure 1D. C, Immunofluorescence staining, and D, metabolite levels by NMR in a panel of breast cancer cell lines representing the different breast cancer subtypes. E, HER2 and EDI3 mRNA, and F, protein expression in HCC1954 cells upon HER2 silencing. G, EDI3 and HER2 mRNA expression and H, EDI3, pHER2, and HER2 protein expression in SKBR3 cells after silencing EDI3 with siRNA. I, EDI3 and HER2 mRNA expression and J, EDI3, pHER2, and HER2 protein expression in HCC1954 cells after silencing EDI3 with siRNA. K, Representative Western blots showing EDI3, pHER2 and HER2 protein expression in HCC1954 cells treated with 0.1 µM or 1.0 µM lapatinib for 24, 48, 72 and 96h, with corresponding quantification of protein levels. Data are mean ± SD or mean ± SE for HER2 protein expression in panel A of at least three independent experiments (*, P

Additional file 3: Supplementary Figure S3. Effect of targeting EDI3 on viability, alone or in combination with lapatinib, in ER-HER2+ and ER+HER2+ breast cancer cell lines. A-B, EDI3 mRNA (left panels) and protein expression (right panels) after silencing EDI3 using siRNA in A, BT474 and B, EFM192A cells. C, Effect of inhibiting HER2 using increasing concentrations of lapatinib on viability in SKBR3, HCC1954, BT474 and EFM192A cells. D-G Influence of silencing EDI3 with siRNA (oligo #2) and inhibiting HER2 with lapatinib (0.01 µM, 0.1 µM and 1 µM), as well as the combined inhibition of both EDI3 and HER2 on viability in D, SKBR3, E, HCC1954, F, BT474 and G, EFM192A cells. H, Effect of inhibiting HER2 using different concentrations of trastuzumab on viability in SKBR3, HCC1954, BT474 and EFM192A cells. I-L Influence of inhibiting EDI3 with siRNA (oligos #1 and #2) and HER2 with trastuzumab (1 µg/ml and 10 µg/ml), as well as the combined inhibition of both EDI3 and HER2 on viability in I, SKBR3, J, HCC1954, K, BT474 and L, EFM192A. Data are mean ± SD (A-C and H) or mean ± SE (D-G and I-L) of at least three independent experiments (*, P

Additional file 2: Supplementary Figure S2. GSK3β and mTOR are key proteins in HER2-mediated upregulation of EDI3. A, Quantification of HER2, EDI3 and p-Akt protein expression after inhibiting PI3K with 5 and 10 µM LY294002 for 3 and 7 days in MCF7-NeuT cells. B, Representative Western blot and HER2, EDI3 and p-PKCα/βII protein expression quantification after inhibiting PLCγ with 1 and 3 µM U73122 for 3 and 7 days in MCF7-NeuT cells. C, Representative Western blot and quantification of HER2, EDI3 and p-ERK1/2 protein expression after inhibiting MEK with 5 and 25 µM PD98059 for 3 and 7 days in MCF7-NeuT cells. D, HER2, EDI3 and p-mTOR protein expression after inhibiting mTORC1 with 1 and 3 µM everolimus for 3 and 7 days in MCF7-NeuT cells. E, HER2, EDI3 and p-mTOR protein expression after inhibiting mTORC1 with 1 and 3 µM everolimus for 1, 2 and 3 days in HCC1954 cells. F, HER2, EDI3 and p-mTOR protein expression after inhibiting mTORC1 with 1 and 3 µM everolimus for 1, 2 and 3 days in SKBR3 cells. G, HER2, EDI3 and β-catenin protein expression after inhibiting GSKβ with 1 and 2.5 µM CHIR-99021 for 3 and 7 days in MCF7/NeuT cells. H, HER2, EDI3 and β-catenin protein expression after inhibiting GSKβ with 1 and 2.5 µM CHIR-99021 for 1, 2 and 3 days in HCC1954 cells. I, HER2, EDI3 and β-catenin protein expression after inhibiting GSKβ with 1 and 2.5 µM CHIR-99021 for 1, 2 and 3 days in SKBR3 cells. Graphs D-I are quantification of Western blots exemplified in Fig. 3C-H, respectively. J, EDI3 mRNA expression after inhibiting c-Myc with 5 and 10 µM 10074-G5, K, NFκB with 5 and 10 µM SC75741, or L, KLF5 with 5 and 10 µM SR18662 for 1, 2 and 3 days in SKBR3 cells. Data are mean ± SD of at least three independent experiments (*, P

Additional file 7: Supplementary Table S2. List of used reagents including A, QuantiTect primer assays, B, siRNA and shRNA oligos, and C, antibodies.

Additional file 6: Supplementary Table S1. EDI3 (GPCPD1) expression in human breast cancer tissue was evaluated in publicly available Affymetrix HG U133 Plus 2.0 gene expression microarray dataset that were downloaded from the Gene Expression Omnibus webportal (GEO) together with available clinicopathological data.

Additional file 8: Supplementary Table S3. Association of EDI3 expression for the three probesets on the Affymetrix HG U133 Plus 2.0 array and available clinicopathological parameters shown for A, the six datasets combined, as well as separately for B, GSE16446, C, GSE19615, D, GSE28844, E, GSE32646, F, GSE6532, and G, GSE9195. P value from the Mann Whitney or Kruskal-Wallis U test.

Additional file 5: Supplemental Figure S5. Inducibly silencing EDI3 inhibits colony formation and cell viability. A, Representative images (top) and corresponding quantification (bottom) of colony number (left) and size (right) formed by HCC1954 shNEG and HCC1954 shEDI3 (oligos shEDI3 #1, #2, #3) cells treated with 0 or 0.1 µg/ml doxycycline. B, Viability (RFU) after treating HCC1954 shNEG and HCC1954 shEDI3 (oligos shEDI3 #1, #2) with 0.1 or 1 µg/ml doxycycline. All in vitro data are mean ± SD of three independent experiments. (*, P < 0.05; **, P < 0.01; ***, P < 0.001). RFU, relative fluorescence units.

Additional file 4: Supplementary Figure S4. Inhibiting EDI3 with dipyridamole, alone or in combination with HER2-targeting therapy, in ER-HER2+ tumors in mice. A-D EDI3 activity in percent after treatment with dipyridamole at different concentrations in A, HCC1954 B, SKBR3, C, BT474 and D, EFM192 cells. E, Cell viability in percent of vehicle control after treatment with different concentrations of dipyridamole in SKBR3, HCC1954, BT474 and EFM192A cells (upper panel) and EC50-values with corresponding 95% confidence intervals (CI) (lower panel). F, Concentration of dipyridamole in plasma after a single oral dose of 120 mg/kg dipyridamole in mice over time. G, Mouse weight (grams) after treatment with dipyridamole, lapatinib and the combination for up to 4 weeks. H, Images of CD1 nude mice with tumors encircled, after 4-week treatment of vehicle, dipyridamole, lapatinib and the combination of both. I, Plasma and tumor concentrations (µM) of dipyridamole (upper panel) and lapatinib (lower panel) after treatment with each compound alone or in combination (D+L). Data (A-E) are mean ± SD of three independent experiments; mean ± SD of three CD1 mice (F); mean ± SD 5 to 6 mice (G); and representative images of 4 mice per condition H. D+L (combined dipyridamole and lapatinib treatment); BQL (below quantification limit); EC50 (half maximal effective concentration).

Repeated administration of hepatotoxicants is usually accompanied by liver fibrosis. However, the difference in response as a result of repeated exposures of acetaminophen (APAP) compared to a single dose is not well-studied. Therefore, in the current study, the liver response after a second dose of APAP was investigated. Adult fasted Balb/C mice were exposed to two toxic doses of 300 mg/kg APAP, which were administered 72 h apart from each other. Subsequently, blood and liver from the treated mice were collected 24 h and 72 h after both APAP administrations. Liver transaminase, i.e. alanine amino transferase (ALT) and aspartate amino transferase (AST) levels revealed that the fulminant liver damage was reduced after the second APAP administration compared to that observed at the same time point after the first treatment. These results correlated with the necrotic areas as indicated by histological analyses. Surprisingly, Picro Sirius Red (PSR) staining showed that the accumulation of extracellular matrix after the second dose coincides with the upregulation of some fibrogenic signatures, e.g., alpha smooth muscle actin. Non-targeted liver tissue metabolic profiling indicates that most alterations occur 24 h after the first dose of APAP. However, the levels of most metabolites recover to basal values over time. This organ adaptation process is also confirmed by the upregulation of antioxidative systems like e.g. superoxide dismutase and catalase. From the results, it can be concluded that there is a different response of the liver to APAP toxic doses, if the liver has already been exposed to APAP. A necroinflammatory process followed by a liver regeneration was observed after the first APAP exposure. However, fibrogenesis through the accumulation of extracellular matrix is observed after a second challenge. Therefore, further studies are required to mechanistically understand the so called “liver memory”., EXCLI Journal;Vol. 18 2019