Fig 1: CAFs promote MCA formation. (A) EpCAM+ tumor cells were isolated from the ascitic fluid by flow cytometric cell sorting. (B) Identification of primary CAFs isolated from omentum with metastasis; spindle-shaped, vimentin-positive, cytokeratin 8-negative and a-SMA-positive characterization. Scale bars, 50 µm. (C) Western blot analysis of a-SMA expression in primary CAFs; passage 1-3. (D) Representative images of MCA formation assays. SKOV3 and primary tumor cells isolated from patient #6 were cultured alone or co-cultured with CAFs in suspension. Scale bars, 100 µm. (E) Histograms show the MCA counts from the MCA formation assays. (F) Histograms show MCA size in the MCA formation assays. *P<0.05 and **P<0.01. (G) The dynamic process of tumor cell-CAF MCA formation. CAFs and SKOV3 cells were labeled with FM4-64 (red) and GFP (green), respectively. Black arrows indicate the filopodia of CAFs. Scale bars, 50 µm. CAFs, cancer-associated fibroblasts; MCA, multicellular aggregate; a-SMA, a-smooth muscle actin.
Fig 2: Signaling cascade induced by activated PROCR in NPC. a Ca2+ flux dynamics labeled by fluo-4 in PROCR overexpression or knockout cells. Living cells were observed right after the dye supplementation. The corresponding right panels show the statistical analysis of fluorescence intensity. b, c Western blotting analysis of lipid metabolism related genes expression and stem cell markers expression in vector or PROCR overexpressing cells with different drugs treatment. 8-Bromo-cAMP, PKA agonist; H 89 2HCl, PKA antagonist; PDTC, NF?B inhibitor. d ELISA detection of the cellular cAMP content in PROCR overexpressing cells. e Sphere forming assay of the sorted CD45-EPCAM+PROCR+ cells treated with different drugs. f, g The cell content of triglycerides and cholesterol in PROCR overexpressing cells treated with different drugs. h ChIP-PCR detection of the direct transcriptional regulation of NF?B on FASN or PTGS2 expression. i Subcutaneous xenograft tumor volume of PROCR overexpressing cells treated with different drugs; n = 5 for each group. All mice received APC activation. j Percentages of GFP+ cells from xenograft tumor nodules in the lungs of mice treated with different drugs. The drugs were administered every week; ns Not significant, *P < 0.05, ***P < 0.001
Fig 3: Identification of an NPC cell group with stem cell-like properties. a Flow cytometry analysis of CD45-EPCAM+PROCR+ cells in different patients with NPC. b Correlation analysis of the amount of CD45-EPCAM+PROCR+ cells with the matching TNM stages of the patients (n = 51). c Sphere formation assay of the sorted cells from NPC biopsy samples. All the sorted cells were gated from the CD45- population. *P < 0.05. d Immunofluorescence staining of CD31 and PROCR in sectioned paraffin embedded NPC biopsy samples. e Summary of the xenograft results showing the number of sorted cells transplanted into the mice, and their corresponding engraftment efficiency. The successfully engrafted tumor was regarded as the ones with both osteolytic lesion and lung nodules in mice. All of the successfully engrafted specimens from different patients were pooled together. The CSC frequency is estimated to be 1/17152 according to Extreme Limiting Dilution Analysis (ELDA) with 0.95 confidence interval. f CT scanning of the mice femurs. The image shows the three-dimensional volume reconstruction of leg bones of a representative recipient mouse. The arrowheads label the osteolytic lesions resulting from tumor metastasis. g Lung metastases of the recipient mouse. The arrowheads mark the nodules in the lung, after incubating in the Bousin solution. h HE staining and KI67 expression of xenograft tumors in mouse lungs sections. The right panels show the red box regions at a higher magnification
Fig 4: rVAR2- and EpCAM-based CTC isolation and enumeration in cancer patients. a Number of CTCs isolated from 5mL pancreatic (n = 9), hepatocellular (n = 4), and prostate (n = 25) cancer patient-derived blood using rVAR2-coated beads. CTCs were enumerated by immunofluorescence stainings and defined as CK+ CD45- DAPI+. b Representative confocal microscopy image of a circulating tumor cell isolated with rVAR2 from blood derived from one of the pancreatic cancer patients (patient 4, Table 3). Isolated cells were stained with anti-cytokeratin FITC antibody (green), anti-CD45 PE antibody (red), and DAPI (blue). Scale bar, 10 µm. c Number of CK+ CD45- DAPI+ CTCs isolated using rVAR2 or anti-EpCAM antibody-coated beads from 5mL blood from 15 of the stage II–III prostate cancer (PCa) patients (P < 0.02, Wilcoxon test for paired data). d Number of CK+ CD45- DAPI+ CTCs isolated using rVAR2 or anti-EpCAM antibody-coated beads from 5mL blood from six of the stage III–IV pancreatic ductal adenocarcinoma (PDAC) patients. e Box-Whiskers plot showing post-isolation characterization of CK+ CD45- DAPI+ CTCs using EpCAM or rVAR2 stain on CTCs isolated using rVAR2 (n = 7) or anti-EpCAM antibody-coated (n = 7) beads, respectively. The median is presented as the center line, whiskers as min to max values, and the 25th to 75th percentiles define the box. f Number of PBMCs contaminating the isolated CTCs from patient-matched blood samples using rVAR2 or anti-EpCAM antibody-coated beads. PBMC levels were estimated by immunofluorescence stainings and defined as CK-, CD45+, DAPI+ stained cells (P < 0.0001, Wilcoxon test for paired data) (n = 23).
Fig 5: rVAR2-capture of CTCs from prostate cancer patients. a Number of CK+ CD45- DAPI+ CTCs isolated from 7.5 mL blood from four prostate cancer patients using rVAR2 or anti-EpCAM antibody-coated beads or the CellSearch® CTC platform. b CTC enumeration using rVAR2-coated beads on blood samples from prostate cancer patients with different disease stages (n = 25) as well as from healthy controls (n = 16) and patients with non-malignant diseases (n = 12). (P = 0.0001 for association between disease severity and CTC number, Kruskal–Wallis test). UTI: urinary tract infection, BPH: benign prostatic hyperplasia
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