Fig 1: Capture performance of the antibody-modified silicon surface. a The capture and release device. Rare cells (green) are pre-concentrated on an electrochemically cleavable antibody-modified poorly doped p-type silicon surface from a mixture of cells (left). The pre-concentrated cells can be simultaneously analysed, for example with fluorescence microscopy (middle) before a unique single cell is selected and electrochemically released from the surface (right). b–e Fluorescence micrographs of live MCF-7 cells plated on an oligo(ethylene oxide)-terminated surface (b), an anti-EpCAM-modified surface (c), on a surface with non-specific donkey anti-mouse IgG antibody (d) and HeLa cells on an anti-EpCAM-modified surface (e). Cells were stained with the nuclear dye Hoechst 33342. Scale bar = 200 µm. f–i Fluorescence microscopy images of MCF-7 cells spiked into HeLa cells at 10% (f), 15% (g), 25% (h) and 50% (i) MCF-7 cells of total cells. MCF-7 cells were stained with calcein (green) while HeLa cells were stained with a Hoechst 33342 nuclear stain (magenta). Scale bar = 100 µm. j Quantitation of MCF-7 and HeLa cell densities on the silicon surfaces as a function of their composition in suspension. Error bars represent the margin of error at 95% confidence, n = 6. k–l MCF-7 cells were spiked (1% of total cells) into whole human blood before being captured on an anti-EpCAM-modified electrochemically cleavable silicon surfaces. All mononuclear cells were stained with the Hoechst 33342 nuclear dye (blue) whilst EpCAM-positive MCF-7 cells were also stained with FITC-conjugated anti-EpCAM antibodies (green). Scale bar in k = 100 µm; scale bar in l = 50 µm
Fig 2: A multivariate diagnostic model based on uEVEpCAM-CD9 for PCa. (A) The nomogram was constructed according to the results of multivariate logistic regression. (B) The ROC curve analysis of the multivariable diagnostic model in the training set and validation set. (C) The multivariable diagnostic model was calibrated in the internal validations. (D) The decision curve analysis of the multivariable diagnostic model and uEVEpCAM-CD9. (E) The diagnostic performance of the model, uEVEpCAM-CD9, and PSA in patients with PSA gray zone (4–10 ng/ml) including 23 PCa and 31 BPH. BMI, body mass index; uEVEpCAM-CD9, Log urinary EpCAM-CD9-positive extracellular vesicles concentration (n.u); PV, prostate volume; PSA, prostate-specific antigen; ROC, receiver operating characteristic; AUC, area under the curve.
Fig 3: The scheme of workflow for urinary EpCAM-CD9-positive extracellular vesicle (uEVEpCAM-CD9) detection. (A) EpCAM-CD9-positive EVs diffused in urine are bound with acridinium ester (ACE)-labeled anti-CD9 antibodies and captured by magnetic microbeads labeled anti-EpCAM antibodies. After incubation for 60 min, uEVEpCAM-CD9 binding with magnetic microbeads can be easily isolated under an external magnetic field and quantitatively analyzed by a chemiluminescent immunoassay analyzer to diagnose prostate cancer. (B) TEM images of EVs isolated by ultracentrifugation (white arrow). (C) EVs are characterized by NTA. (D) The expression of CD63, CD9, EpCAM, calnexin, and APO in PC3 cell lysates and the EV fraction from PC3 by WB analysis. (E–G) Flow cytometry assay identified that approximately 80% of EVs released by PC3 carried EpCAM and CD9. EpCAM, epithelial cell adhesion molecule; uEVEpCAM-CD9, urinary EpCAM-CD9-positive extracellular vesicles; EVs, extracellular vesicles; ACE, acridinium ester; TEM, transmission electron microscope; NTA, nanoparticle tracking analysis; WB, western blot.
Fig 4: EVEpCAM-CD9 is ultrasensitively detected by chemiluminescent immunoassay and oversecreted under simulated tumor microenvironment. (A) Groups of PC3 EVs, non-EVs, non-streptavidin-labeled magnetic beads, non-biotin-labeled anti-EpCAM antibodies, and non-ACE-labeled anti-CD9 antibodies were detected by our assay. (B) EVs were penetrated by Triton X-100. (C) A standard curve was for EVs from cell line supernatant quantification using our EV assay. (D) EVs derived from FBS, BPH cell line RWPE-1, and human prostate cancer cell lines PC3 and LNCaP were detected by our EV assay and WB. (E) The changes of EVEpCAM-CD9 secretion index during the growth of PC3 cells. (F) The changes of EVEpCAM-CD9 secretion index when the PC3 cells were cultured under hypoxia. (G) The changes of EVEpCAM-CD9 secretion index when the PC3 cells were cultured under serum starvation. (H) The changes of EVEpCAM-CD9 secreted by PC3 cells with the treatment of 10 and 20 µM GW4869. RCU, relative chemiluminescent unit; EVs, extracellular vesicles; FBS, fetal bovine serum; EVEpCAM-CD9, EpCAM-CD9-positive extracellular vesicles. *P < 0.05,**P < 0.01,****P < 0.0001.
Fig 5: Overexpression of RhoJ promotes GBM progression and angiogenesis in the xenograft mouse model. (A) Representative images of RhoJ expression in the normal brain and grade II to grade IV glioma tissues by IHC staining, obtained at 200× magnification (upper) and 400× magnification (lower). All scale bars, 100 µm. (B) Semi-quantitative analysis results of RhoJ positive cells in different grades of glioma (WHO II-IV) and normal brain tissue samples by immunohistochemical (IHC) staining. (C) Representative tumor xenografts from U87 cells expressing plenti-RhoJ or plenti-con. (D) The xenograft tumor size was measured every 4 days before they were sacrificed. (E) The xenograft tumor weight was measured after sacrifice (mean ± SEM, n = 4). (F) IHC analyses of CD31, RhoJ, meosin and EpCAM in the xenograft tumor. scale bar, 100 µm. (G) Representative images of tumor xenografts for IF analysis of EpCAM and CD31. Scale bar, 100 µm. (F) Quantitative analysis of fluorescence intensity of EpCAM and CD31 in (G). Scale bar, 100 µm. In all images, data are shown as the mean ± SEM. Every experiment was independently repeated 2-3 times. *p<0.05; **p<0.01; ***p<0.001.
Supplier Page from Abcam for Anti-EpCAM antibody [VU-1D9]