Literature DB >> 25267635

A 3D matrix platform for the rapid generation of therapeutic anti-human carcinoma monoclonal antibodies.

David T Dudley1, Xiao-Yan Li1, Casey Y Hu1, Celina G Kleer2, Amanda L Willis1, Stephen J Weiss3.   

Abstract

Efforts to develop unbiased screens for identifying novel function-blocking monoclonal antibodies (mAbs) in human carcinomatous states have been hampered by the limited ability to design in vitro models that recapitulate tumor cell behavior in vivo. Given that only invasive carcinoma cells gain permanent access to type I collagen-rich interstitial tissues, an experimental platform was established in which human breast cancer cells were embedded in 3D aldimine cross-linked collagen matrices and used as an immunogen to generate mAb libraries. In turn, cancer-cell-reactive antibodies were screened for their ability to block carcinoma cell proliferation within collagen hydrogels that mimic the in vivo environment. As a proof of principle, a single function-blocking mAb out of 15 identified was selected for further analysis and found to be capable of halting carcinoma cell proliferation, inducing apoptosis, and exerting global changes in gene expression in vitro. The ability of this mAb to block carcinoma cell proliferation and metastatic activity was confirmed in vivo, and the target antigen was identified by mass spectroscopy as the α2 subunit of the α2β1 integrin, one of the major type I collagen-binding receptors in mammalian cells. Validating the ability of the in vitro model to predict patterns of antigen expression in the disease setting, immunohistochemical analyses of tissues from patients with breast cancer verified markedly increased expression of the α2 subunit in vivo. These results not only highlight the utility of this discovery platform for rapidly selecting and characterizing function-blocking, anticancer mAbs in an unbiased fashion, but also identify α2β1 as a potential target in human carcinomatous states.

Entities:  

Keywords:  MDA-MB-231; bone; extracellular matrix; metastasis; mouse model

Mesh:

Substances:

Year:  2014        PMID: 25267635      PMCID: PMC4205646          DOI: 10.1073/pnas.1410996111

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  72 in total

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