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Additional file 1: Figure S1. Extended data for figure 3 and 4. Uncropped Western blot images showing A PDGFR-β and related actin; B cleaved caspase-3 and related actin; C eNOS and VEGF with related actin; D Tie2, ANGPT1 and related actin. Boxed areas correspond to cropped regions shown in figure 3C and 3E. Specific target bands were selected according to the molecular weight reported in antibodies’ datasheets. Table S1: raw RPPA data.

Additional file 1:. Supplementary Methods.

Additional file 1: Supplementary Table 1. List of drugs used for small-molecule kinase inhibitor screening (10 mM in DMSO). Supplementary Table 2. List of antibodies used for Reverse-Phase Protein microArrays (RPPA) analysis. Supplementary Table 3. Patient and GSC line characteristics. Supplementary Table 4. List of genes corresponding to significant antibodies and grouped using the Venn diagram in Fig. 4C. Supplementary Figure S1. A-D. Morphological changes of the four GSC lines used in the study (A, GSC#1; B, GSC#61; C, GSC#83; D, GSC#163) after being induced to transdifferentiate for 2 weeks. Left panel, tumorspheres in stem cell medium; right panel, net-like structures under endothelial conditions (magnification 10X). Supplementary Figure S2. (A) Fluorescent-activated cell sorting dot plots of CD34−/low and CD34high GSC#163 after two weeks of culture in endothelial conditions under hypoxia. Percentage and squares indicate the sorted subpopulations of cells with different CD34-expression levels (left, IgG1 isotype control sample; right, CD34 sample). (B-C) Immunohistochemical analysis of CD34low (B) and CD34high (C) GdEC subcutaneous tumor xenografts based on the expression of the astrocytic marker glial fibrillary acidic protein (GFAP, right panels), showing tumors with different levels of differentiation. (Left panels, haematoxylin and eosin staining; magnification 200X). Supplementary Figure S3. Concentration-response assays on U87MG and all the four glial cell lines derived from the selected GSC lines. Supplementary Figure S4. Cytofluorimetric cell-by-cell analysis of viability in four different GSC lines treated with 10, 100, or 1000 nM elesclomol in the presence or absence of the following cell death inhibitors: z-VAD, necrostatin-1, ferrostatin-1, 3-MA, NAC, and CoQ at the indicated concentrations. Results obtained from four independent experiments are expressed as percentage vs control untreated cells and reported as means ± SD. Supplementary Figure S5. Cytofluorimetric cell-by-cell analysis of cell viability (A), mitochondrial ROS production (B), mitochondrial membrane potential (C), and GSH (D) in four different GSC lines treated with 10, 100, or 1000 nM elesclomol in the presence or absence of the copper chelating agent TTM. Results obtained from four independent experiments are expressed as percentage vs control untreated cells and reported as means ± SD. Supplementary Figure S6. Cytofluorimetric cell-by-cell analysis of cell viability, mitochondrial ROS production, mitochondrial membrane potential, and GSH in HMVECs, used as a control of nontumoral endothelial cell line, treated with 10, 100, or 1000 nM Elesclomol in the presence or absence of the copper chelating agent TTM. Results obtained from four independent experiments are expressed as percentage vs control untreated cells and reported as means ± SD. Supplementary Figure S7. Illustration of the rationale suitable for the choice of rank k, a critical parameter that defines the number of metagenes used to approximate the target matrix (Gaujoux & Seoighe, 2010). A) Measurements are applied to both real data (circles) and randomized data (triangles). The rationale for choosing rank stems on diverse metrics, i) trend of the cophenetic coefficient: Brunet et al. (2004) suggest choosing the smallest value of k for which there is a decrease in the trend of the cophenetic; ii) trend of the dispersion coefficient introduced by Kim & Park. (2007); iii) explained variance by increasing rank; iv) trend of residuals; v) trend of RSS: Hutchins et al. (2008) suggest taking the first rank value for which we have an inflection point. Frigyesi et al. (2008) instead consider the first rank value for which the decrease of the RSS on real data is less than the decrease of the RSS on the random data; vi) silhouette values measured on the matrices of the base, of the coefficients and the consensus matrix; vii) trend of the sparseness introduced by Hoyer (2004). B) Multiple consensus maps corresponding to different value of k. Supplementary Figure S8. Heatmap of the most important antibodies in each of the k = 6 metagenes resulting from the model. Supplementary Figure S9. Principal Component Analysis (PCA) algorithm applied to Elesclomol data, whereby each cell line is considered as a function of the antibodies. A) Scree plot. Given the low amount of variance explained by the variables above the fifth, we considered up to 5 principal components. B) Biplots using cell lines and growth conditions as scores. Ellipses represent the 95% probability of finding sample score values. Supplementary Figure S10. Principal Component Analysis (PCA) biplots of components of the antibodies using (A) Time and (B) treatment, respectively. Ellipses represent the 95% probability of finding sample score values. Supplementary Figure S11. Concent ration-response assays on all the four selected GSC lines for setting the dose of Elesclomol most suitable for the combination with TMZ.

Additional file 11: Figure S5. ZEB2 expression in TNM stages, correlation with RFS and CMS in stage 2 CRC patients. ZEB2 transcript levels in the indicated number of CRC patients across all TNM stages. One-way ANOVA resulted in non-significant differences between stages. Outliers are depicted as crosses. n = 1079.

Additional file 8: Figure S2. Expression of pCRAF in vivo and in vitro and complementary RPPA data analysis. a Representative confocal microscopy images of PKH26-positive areas (yellow) in xenograft sections immunostained with anti-pCRAF S338 (green) and PROMININ1 (red). Scale bar, 80 μm. b Representative confocal microscopy images of SW480 cells treated for 48 h with 10 μM etoposide or 10 μM irinotecan and stained with anti-pCRAF S338 antibody. Scale bar, 20 μm. c Spatial representation of principal component (PC) analysis computed on a matrix having loading values of the two components, Factor 1 and Factor 2 that discriminates among PKH26+ and PKH26− samples. Results obtained on three PKH26+ versus PKH26− samples, n = 3 pools of 12 tumors each. d Spatial representation of scores of components representing relative RPPA antibodies values (Factor 1 and Factor 2). Results obtained on three PKH26+ versus PKH26− samples, n = 3 pools of 12 tumors each.

Additional file 10: Figure S4. In vivo effects of ZEB2 overexpression in CCSCs. a Volume of xenografts derived from CCSCs transduced with pLenti-GFP (Vector, black line/triangles) or with pLenti-GFP-ZEB2 (ZEB2, red line/squares). Graph shows the mean ± SEM, 6 tumors/group. **P

Additional file 9: Figure S3. Trends of ZEB2 overexpression in cultured cells. a Percentage of GFP positivity in CCSCs (diamonds) or SW480 (circles) cells transduced with empty pLenti-GFP (Vector) or with pLenti-GFP-ZEB2 (ZEB2) as assessed by flow cytometry for 5 weeks following lentiviral transduction and sorting (day 0). Graph shows the mean ± SD of three independent experiments. b Representative confocal image of CCSCs and SW480 cells transduced with GFP-ZEB2 and labeled with anti-Ki67 at day 28 after sorting. Circles indicate rare ZEB2+ cells, which are also Ki67−. Scale bar, 50 μm.

Additional file 4: Figure S1. Chemoresistance and marker expression of PKH26-positive cells. a Representative flow cytometry analysis of SW480 cells stained with PKH26 and treated with 2,5 μM oxaliplatin (OXA) starting from day 11, as described in Fig. 1a. Cell viability plots obtained with 7-AAD staining are shown below PKH26 plots, and the percentage of viable cells is indicated below each plot. b Representative flow cytometry analysis of EpCAM and PKH26 on xenograft-derived CCSCs 3 weeks upon subcutaneous injection of PKH26-stained cells in NSG mice. IgG, isotype control antibody. c Representative flow cytometry analysis of PKH26 and Ki67 in xenograft-derived EpCAM+ CCSCs at 3 weeks of tumor growth. d Representative flow cytometry analysis of PKH26 and PROMININ1 in xenograft-derived EpCAM+ CCSCs at 3 weeks of tumor growth.

Figure S1. Additional RPPA endpoints. (PDF 89474 kb)

Table S1. Complete list of antibodies used for RPPA analysis and their main related information. (PDF 26 kb)

Figure S2. Clonogenic Assay. (PDF 440 kb)

Figure S6. (A) Freshly dissociated tissues maintained for one week in serum-free stem cell-isolating medium supplemented with Epidermal Growth Factor (EGF), basic Fibroblast Growth Factor (b-FGF), DMEM (Dulbecco Modified Eagle Medium), or Glutamine and FBS (Fetal Bovine Serum) supplemented medium, and analyzed by cytofluorimetric analysis. CD45 (PE-Cy7), CD146 (PE), CD44 (H450-Pacific Blue) and EpCAM (FITC) antigens were analyzed. TOPRO3 was used for gating vital cells. (B) The histograms report growth rate fold change of cells described in A, 4 and 10 days after sorting. Control represents (red dashed line) value = 1 i.e. reference relative count at sorting and plating day. Mean of three independent experiments is reported. Values are mean ± s.d (C) Colony forming assay of EpCAM+/CD146+/CD44+ and triple negative sorted cells and non-sorted population maintained in culture one week in stem serum free medium (D) Mean colony size of EpCAM+/CD146+/CD44+ and triple negative sorted cells and non-sorted population maintained in culture one week in stem serum free medium. Mean of three independent experiments is reported. Values are mean ± s.d. (PDF 231 kb)

Figure S8. (A) Representative images of Western blot analysis of pAKT S473 and pERK T202/Y204 proteins in clear renal cancer isolated cells (G3 and G4) and commercial lines [primary tumor 786–0 (786) and metastatic Caki-1 (CK1)]. GAPDH expression was used as internal control (B) Anti-mTOR and VEGFR2 protein staining in two representative samples classified by (ISUP) grading as G3 and G4 cases by immunohistochemistry assay. Microscope used Nikon Eclipse 55i, magnification 20X. (C) Representative images of Western blot analysis of pAKT S473 and pERK T202/Y204 proteins in non-sorted stem serum free clear renal cancer enriched cells (Stem Tot.), EpCAM+/CD146+/CD44+ (Stem+) and triple negative (Stem-) sorted cells vs non-sorted clear renal cancer cells maintained in DMEM-FBS condition (DMEM Tot) and evaluated one week after culture. (D) Two-way unsupervised hierarchical clustering of 18 ccRCC samples for the expression of proteins belonging to the angiogenesis pathway. Highlighted in the yellow box are overexpressed protein commonly shared in samples of patients that underwent progression (red arrows). N1 and M1 samples were excluded from the analysis (E) Receiver operating characteristic (ROC) curve showing sensitivity and specificity of HIF-1 alpha and phospho-mTOR (S2448) protein RPPA expressions in predicting progression. The true positive rate (sensitivity) is plotted in function of the false positive rate (100-specificity). The area under the ROC curve (AUC) represents a measure of how well the HIF-1 alpha and phospho-mTOR (S2448) protein RPPA expressions distinguishes progression group from no progression [0.96 (p

Figure S5. Freshly dissociated tissues were maintained three days in serum-free stem cell-isolating medium supplemented with Epidermal Growth Factor (EGF) and basic Fibroblast Growth Factor (b-FGF). On the left a representative image of the sorting of EpCAM+/CD146+/CD44+ populations (EpCAM+/CD146+/CD44+) and triple negative (EpCAM-/CD146-/CD44-) by FACS ARIA cytometer was reported. Images of colonies of both sorted sub-populations were reported on the right. Yellow and pink boxes mirror cytometer density plot. Pink dashed line represents matrigel front of cell invasion. (PDF 179 kb)

Figure S7. (A) Two-way unsupervised hierarchical clustering of RPPA data of 2 G1, 7 G2, 8 G3, and 3 G4 ccRCC populations for the expression of stem cell markers reported as heatmap. (B) mRNA expression of SOX2 gene in G2, G3, and G4 ccRCC samples as assessed by RT-qPCR. Mean of three independent experiments is reported. RRN18S was used as endogenous control. *p

Figure S3 (A) RPPA-TCGA elaboration of E-Cadherin and Fibronectin expressions. Data were obtained from macrodissected clear cell renal cancer tissues (GDC-database- https://tcga-data.nci.nih.gov/docs/publications/kirc_2013/ ) and reported for grading, stage and for progression rate by RPPA. (B) mRNA level elaboration of EpCAM, CD146(MCAM) and CD44 antigens. Data were obtained from GSE48550 microarray and were analyzed on different kinds of renal stem cells. (C) TOPRO3 staining for cell viability evaluation of populations maintained for three days (upper panels) and one week (Lower panels) in serum-free stem cell-isolating medium supplemented with Epidermal Growth Factor (EGF), basic Fibroblast Growth Factor (b-FGF), DMEM (Dulbecco Modified Eagle Medium), Glutamine and FBS (Fetal Bovine Serum) supplemented medium and evaluated by cytofluorimetric analysis. Blue and Black areas represent vital and dead cells respectively. (PDF 389 kb)

Table S2. Clinical features of 20 collected ccRCC patients including: 2 G1; 7 G2; 8 G3 and 3 G4 processed by RPPA. (PDF 488 kb)

Figure S10. (A) Kaplan-Meier curve for the Disease Free Survival (DFS) in the engrafted (Engraf) and not engrafted (No Engraf) groups. (B) Histogram showing FACS analysis results of a PDX derived from a G4 metastatic patient with a sarcomatoid phenotype at esordium for the expression of selected markers. (C) Luciferase analysis representative image of G4 ccRCC injected mice (seven mice/group) and after 21Â days of treatment with Sunitinib by IVIS imaging. (D) Histogram showing luciferase photon emission of the vehicle and Sunitinib treated mice at days 0 and 21 of treatment and evaluated by IVIS imaging. (E) Representative Haematoxylin and Eosin staining of tumor sections from treated mice. Microscope used Nikon Eclipse 55i, magnification 10X (upper panel) and 20X (lower panel) (F) Two-way unsupervised hierarchical clustering of 20 samples for the expression of endpoints representing the most common drug targets. Green arrows represent recurrent patients, while the black arrow represents a metastatic (M1) sample at esordium. (PDF 542 kb)

Figure S4. (A) Fresh dissociated tissues maintained for three days in serum-free stem cell-isolating medium supplemented with Epidermal Growth Factor (EGF), basic Fibroblast Growth Factor (b-FGF), DMEM (Dulbecco Modified Eagle Medium), or in Glutamine and FBS (Fetal Bovine Serum) supplemented medium, and analyzed by cytofluorimetric analysis. CD45 (PE-Cy7), CD146(PE), CD44 (H450-Pacific Blue) and EpCAM(FITC) antigens were analyzed. TOPRO3 was used for gating vital cells. (B-C) Images and clonogenic population percentage of cells maintained in both conditions after three days of culture by Colony forming assay. Colonies distinguished on the basis of their shape in the two conditions: spheroidal (blue box) and bidimensional (red box). (D) Percentage of colonies distinguished on the basis of their shape in the two conditions was reported: spheroidal (blue box) and bidimentional (red box) such as in B. (PDF 229 kb)

Table S3. List of total and phosphorylated proteins analyzed by RPPA. In blue, positively expressed proteins. (PDF 87 kb)

Figure S9. Hematoxylin and Eosin staining of PDXs versus parental primary tumor. G4 tumors often retain both epithelial and sarcomatoid phenotypes. Xenografts are frequently representative of most aggressive parental part. Representative images report epithelial and sarcomatoid phenotype belonging to the same patient. Xenograft image mirrors parental tumor aggressive phenotype. (PDF 114 kb)

Figure S1. (A) (PANEL1) Table of 1286 ccRCC patient distribution: 1013 tumor free patients at 36 months from surgery, 130 metastatic (M1) patients at diagnosis time and 143 recurrent patients at 36 months after surgery were reported. (PANEL2) Table of 57 ccRCC cancer patient distribution: 37 tumor free patients at 36 months from surgery, 6 metastatic (M1) patients at diagnosis time and 14 recurrent patients at 36 months from surgery were reported. (B) Representative immunofluorescence of DAPI-stained tumor derived spheroids. (C) Representative image of 7- aminoactinomycin D staining (7AAD) of in vitro isolated populations by flow cytometry. (D) Table reporting distribution of specific antigen expression percentages (%) in all studied ccRCC populations. (E) Representative images of flow cytometry analysis showing the expression of the epithelial and undifferentiated cell markers EpCAM, CD24, CD10, CD90, CD44 and CD146 mesenchymal stem cell markers in ccRCC isolated populations. Background staining was calculated by using appropriate isotype controls. (F) Flow cytometry analysis of cell lines 786–0 and Caki-1 representative of primary and metastatic tumor, respectively. One representative staining of three independent experiments is shown. (PDF 243 kb)

Figure S2. (A) Hematoxylin and Eosin (H&E) and CD31 staining of formalin-fixed and paraffin- embedded (FPPE) of primary tumors. Three patients for each grading were analyzed. A representative image for samples is reported. (B) RPPA-TCGA elaboration of CD31 expression. Data were obtained from macrodissected clear cell renal cancer tissues (GDC-database- https://tcga-data.nci.nih.gov/docs/publications/kirc_2013/ ) and reported for grading, stage and for progression rate by RPPA. (C) Representative images of flow cytometry analysis showing the expression of the endothelial CD31, VE-Cadherin (VE-Cadh) and putative stem cell markers (CD133, CD105) in ccRCC isolated populations. The analysis was combined with CD44 expression. Background staining was calculated by using appropriate isotype controls. (PDF 402 kb)

Malignant hemopoietic cells are often characterized by ineffective death pathways, resulting in enhanced resistance to apoptosis and ultimately in the survival/expansion of the abnormal clone. Mechanistic studies have been undertaken to identify the aberrant signal transduction pathway and to develop small-molecule inhibitors targeting deregulated modules. Regulators of apoptotic pathways play a key role in the control of erythroid cell expansion; in particularl Bcl-XL is essential for erythroid cell development and, together with Bcl-2, it protects erythroblast survival from cytotoxic stimuli. Previous studies on erythroid cells derived from polycythemia vera (PV) patients have revealed an increased expression of Bcl-XL associated with cell survival in the absence of erythropoietin. The discovery of the JAK2V617F mutation in the vast majority of PV patients and its association with an increased resistance to apoptosis induced by death receptors prompted us to investigate the correlation between JAK2V617F and the expression of anti-apoptotic Bcl-2 family members and to explore the activity of a Bcl-2 inhibitor on PV erythroid cells. ABT-737 is a synthetic small-molecule inhibitor that binds with high affinity to Bcl-2 and Bcl-XL, poorly to Mcl-1, promoting apoptosis as single agent in malignant hemopoietic cells. In this study we analyzed pure populations of primary erythroid precursors obtained from CD34+ cells of healthy donors and PV patients to investigate the expression of Bcl-2, Bcl-XL and Mcl-1. We found that the expression of Bcl-XL and Bcl-2 was increased in PV patients compared to controls, while Mcl-1 levels did not significantly differ. Then we analyzed Bcl-2 and Bcl-XL expression in erythroblasts derived from PV patients clustered on the basis of a different JAK2V617F allele burden. We found that on average the expression of both Bcl-2 and Bcl-XL was comparable to controls in PV erythroblasts with low/null mutation rates while both proteins were significantly (P< 0.001 and P

Fenretinide is a synthetic retinoid characterized by anticancer activity in preclinical models and favorable toxicological profile, but also by a low bioavailability that hindered its clinical efficacy in former clinical trials. We developed a new formulation of fenretinide complexed with 2-hydroxypropyl-beta-cyclodextrin (nanofenretinide) characterized by an increased bioavailability and therapeutic efficacy. Nanofenretinide was active in cell lines derived from multiple solid tumors, in primary spheroid cultures and in xenografts of lung and colorectal cancer, where it inhibited tumor growth independently from the mutational status of tumor cells. A global profiling of pathways activated by nanofenretinide was performed by reverse-phase proteomic arrays and lipid analysis, revealing widespread repression of the mTOR pathway, activation of apoptotic, autophagic and DNA damage signals and massive production of dihydroceramide, a bioactive lipid with pleiotropic effects on several biological processes. In cells that survived nanofenretinide treatment there was a decrease of factors involved in cell cycle progression and an increase in the levels of p16 and phosphorylated p38 MAPK with consequent block in G0 and early G1. The capacity of nanofenretinide to induce cancer cell death and quiescence, together with its elevated bioavailability and broad antitumor activity indicate its potential use in cancer treatment and chemoprevention.