Additional file 3: of Circulating healing (CH) cells expressing BST2 are functionally activated by the injury-regulated systemic factor HGFA

Table S2. Fold change values of the 87 characterizing genes derived from SAM analysis for each pairwise class comparison. (XLSX 61 kb

Additional file 5: of Circulating healing (CH) cells expressing BST2 are functionally activated by the injury-regulated systemic factor HGFA

Table S3. RT-PCR array data set for the four considered experimental groups. (XLSX 57 kb

Additional file 1: of Circulating healing (CH) cells expressing BST2 are functionally activated by the injury-regulated systemic factor HGFA

Figure S1. Pairwise class comparisons detecting genes differentially expressed in CH cells. Figure S2. Identification and sorting of BST2pos CH cells. Figure S3. Quantification of BST2pos CH cells migrated toward the injury sites. Figure S4. Specificity of the used anti-RFP antibody. Figure S5. Effects of injury-related signals on BST2pos CH cells motility. (PDF 15587 kb

Additional file 4: of Circulating healing (CH) cells expressing BST2 are functionally activated by the injury-regulated systemic factor HGFA

Unsupervised hierarchical clustering of considered cell populations. (TXT 41 kb

Additional file 2: of Circulating healing (CH) cells expressing BST2 are functionally activated by the injury-regulated systemic factor HGFA

Table S1. Log2 Intensity values of the 87 genes characterizing the CH cells for each considered cell population. (XLSX 69 kb

Additional file 1 of Targeting NOTCH1 in combination with antimetabolite drugs prolongs life span in relapsed pediatric and adult T-acute lymphoblastic leukemia xenografts

Additional file 1: Additional materials and methods. Establishment of T-ALL xenografts and treatments. Sanger sequencing. Reverse transcription-PCR (RT-PCR) and quantitative PCR (qPCR). Western blot analysis. Preparation of RNA libraries and RNA seq. Bioinformatics analysis. T-ALL Patient Derived Xenografts (PDXs) cells in vitro treatments and (half maximal inhibitory concentration) IC50 determination for selected drugs by Caspase-Glo® 3/7 Assay. Statistical analysis. Scientific Image and Illustration software. Additional Tables: Table S1. Characterization of PDXs from T-ALL pediatric and adult relapsed patients. Table S2. Upregulated gene sets in CTRL versus OMP-52M51-treated PDTALL46 cells. Table S3. IC50 determination for selected drugs in T-ALL PDX cells. Table S4. Selected drugs to be combined with anti-NOTCH1 antibody (OMP-52M51). Additional Figures and Legends: Figure S1. NOTCH1 protein and target genes expression in T-ALL PDXs (PDTALL). Figure S2. Anti-NOTCH1 (OMP-52M51) inhibits growth of NOTCH1-driven T-ALL PDXs. Figure S3. RNASeq analysis of OMP-52M51-acute treated PDTALL46 mice. Figure S4. In vitro cell apoptosis determination in T-ALL PDXs cells treated with different drugs alone or in combination with OMP-52M51. Figure S5. In vivo inhibitory effect of OMP-52M51 in combination with COMBO1 and COMBO2 in PDTALL46 model. Figure S6. In vivo inhibitory effect of OMP-52M51 in combination with antimetabolite drugs (COMBO2) in PDTALL39 and PDTALL-AD4 models. Figure S7. Efficacy of Anti-NOTCH1 in combination with antimetabolite drugs in T-ALL PDXs models. Additional References

Additional file 2: of miR-126-3p down-regulation contributes to dabrafenib acquired resistance in melanoma by up-regulating ADAM9 and VEGF-A

Figure S2. Dabrafenib treatment down-regulates ADAM9 expression in A375 and SK-Mel28 cells. Melanoma cells were incubated with 100 nM dabrafenib (+) or with DMSO alone (-) and after 48 h ADAM9 expression was evaluated by immunoblotting. Antibody against β-tubulin was used as a loading control. The results are representative of two independent experiments. (TIF 70 kb

Additional file 3: of miR-126-3p down-regulation contributes to dabrafenib acquired resistance in melanoma by up-regulating ADAM9 and VEGF-A

Figure S3. ADAM9 silencing delays the development of resistance to dabrafenib. a SK-Mel28 cells were seeded into 96-well plates and every eight days transfected with 10 nM siADAM9 or siCTRL and treated with 100 nM dabrafenib (DAB) or DMSO. On day 0 (i.e after the first transfection), 8, 24 and 32, the cells were fixed, stained with crystal violet and photographed before quantitative analysis of proliferation. Images from a representative experiment are shown. b Quantitative analysis of proliferation of cell cultures described in (a). Crystal violet was solubilized and absorbance was read at 595 nm. Each value represents the arithmetic mean of three independent experiments performed with triplicate cultures. Bars, SEM. **P<0.01, siADAM9 vs matched siCTRL; §§P<0.01, siCTRL/DAB/Day 8 vs siCTRL/DMSO/Day 8; ††P<0.01, siADAM9/DAB/Day 8 vs siADAM9/DMSO/Day8; ##P<0.01, siCTRL/DAB/Day 24 vs siCTRL/DAB/Day 8; ¶P<0.05, siCTRL/DAB/Day 32 vs siCTRL/DAB/Day 24. (TIF 354 kb

Additional file 4: of miR-126-3p down-regulation contributes to dabrafenib acquired resistance in melanoma by up-regulating ADAM9 and VEGF-A

Figure S4. Quantification of VEGF-A in serum of melanoma patients treated with BRAFi or BRAFi+MEKi. VEGF-A levels were determined by ELISA in serum samples of 18 responder (a) and 8 non-responder (b) melanoma patients before the start of therapy (T0), after two months of treatment (T2) and at disease progression (TP). One patient among responders (case #11) displayed undetectable VEGF-A serum levels at all time points analyzed and was not included in the figure. Each value represents the arithmetic mean Âą SEM of two independent determinations. (TIF 164 kb

Additional file 1: of miR-126-3p down-regulation contributes to dabrafenib acquired resistance in melanoma by up-regulating ADAM9 and VEGF-A

Figure S1. MMP7 and CXCR4 expression in A375 and SK-Mel28 cell lines and their dabrafenib-resistant sublines. Melanoma cell lysates were analyzed by immunoblotting using antibodies against MMP7 and CXCR4, or against β-tubulin as a loading control. The results are representative of two independent experiments. (TIF 132 kb