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Development of a CA125-mesothelin cell adhesion assay as a screening tool for biologics discovery.

ABSTRACT: Preventing peritoneal implantation of ovarian carcinoma cells could prolong patient remission and survival. CA125 is expressed on most ovarian cancer cells and was reported to be a ligand of mesothelin, a peritoneal protein. We developed a cell adhesion assay with CA125-expresser ovarian cancer cells and human mesothelin-transfected cells and we confirmed that CA125 and mesothelin mediate cell attachment. We also showed that this assay supplies a high-throughput screening system for reagents able to block CA125/mesothelin-dependent cell attachment with a sensitive quantitative readout. We finally demonstrated that a mesothelin chimeric protein and anti-CA125 antibodies block CA125/mesothelin-dependent cell attachment.

SUBMITTER: Scholler N

PROVIDER: S-EPMC2734268 | biostudies-literature | 2007 Mar

REPOSITORIES: biostudies-literature

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Development of a CA125-mesothelin cell adhesion assay as a screening tool for biologics discovery.

Scholler Nathalie N Garvik Barbara B Hayden-Ledbetter Martha M Kline Toni T Urban Nicole N

Cancer letters 20060504 1

Preventing peritoneal implantation of ovarian carcinoma cells could prolong patient remission and survival. CA125 is expressed on most ovarian cancer cells and was reported to be a ligand of mesothelin, a peritoneal protein. We developed a cell adhesion assay with CA125-expresser ovarian cancer cells and human mesothelin-transfected cells and we confirmed that CA125 and mesothelin mediate cell attachment. We also showed that this assay supplies a high-throughput screening system for reagents abl ...[more]

PMID: 16677756

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Project description:Cigarette smoke (CS) has been reported to affect the adhesion of monocytes to endothelial cells, a critical step in atherogenesis. Using an in vitro adhesion assay together with innovative computational systems biology approaches to analyze omics data, our study aimed at investigating CS-induced mechanisms by which monocyte-endothelial cell adhesion is promoted. Disease-relevant primary human coronary artery endothelial cells (HCAECs) were treated for 4 hours with (1) conditioned media of human monocytic Mono Mac-6 (MM6) cells preincubated with low or high concentrations of aqueous CS extract (sbPBS) from reference cigarette 3R4F for 2 hours (indirect treatment, I), (2) unconditioned media similarly prepared, however without MM6 cells (direct treatment, D), or (3) freshly generated sbPBS (fresh direct treatment, FD). sbPBS promoted MM6 cells-HCAECs adhesion following I and FD, but not D. In I, the effect was mediated at a low concentration through activation of vascular inflammation processes promoted in HCAECs by a paracrine effect of the soluble mediators secreted by sbPBS-treated MM6 cells. Tumor necrosis factor alpha (TNF-alpha major inducer, was actually shed by unstable CS compound-activated TNFalpha-converting enzyme. In FD, the effect was triggered at a high concentration that also induced some toxicity. This effect was mediated through an yet unknown mechanism associated with a stress damage response promoted in HCAECs by unstable CS compounds present in freshly generated sbPBS, which had decayed in D unconditioned media. In conclusion, aqueous CS extract directly and indirectly promotes monocytic cell-endothelial cell adhesion in vitro via distinct concentration-dependent mechanisms. Samples from E-MTAB-3644 dataset correspond to 3R4F sbPBS15 and PBS15 (vehicle control: 15% v/v). In the E-MTAB-3923 dataset, samples correspond to THS2.2 abPBS15, THS2.2 abPBS75 and PBS75 (75% v/v). All THS2.2 abPBS15 from E-MTAB-3923 must be compared with their respective control, PBS15 from E-MTAB-3644; while THS2.2 abPBS75 from E-MTAB-3923 must be compared with their respective control, PBS75 from E-MTAB-3923.

Dataset Information

Development of a CA125-mesothelin cell adhesion assay as a screening tool for biologics discovery.

Publications

Development of a CA125-mesothelin cell adhesion assay as a screening tool for biologics discovery.

Similar Datasets

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