The developmental path for breast cancer antibody therapeutics follows three stages: (1) discovery of an antibody with high affinity for a given target through screening of murine B-cells or antibody fragments expressed on the surface of non-mammalian cells, (2) development, including engineering for increased affinity and conversion to a human-like IgG antibody, typically in prokaryotic or yeast cells, followed by (3) manufacturing, including expression in FDA-approved mammalian cell lines, purification and formulation. This slow and costly process results in a single monoclonal antibody against a previously known target, in spite of the fact that current research indicates synergistic pools of antibodies can be much more effective. Moreover, many antibodies fail in manufacturing since expression level and stability were not criteria used during the initial selection. In this proposa, these three steps are condensed into a streamlined process using CHO cells, the preferred production host. Novel selection schemes are designed to identify pools of antibodies based on function, induction of apoptosis in cancer cells, as opposed to just affinity. The initial target fr antibody development with this system is HER2, a receptor over-expressed in approximately 20% of breast cancer cases and capable of inducing apoptosis of cancer cells when bound to some therapeutic antibodies. First, a mammalian antigen-binding fragment (Fab) surface display system will be developed to permit cytometric sorting of CHO cells expressing functional anti-HER2 Fab from background cells expressing an irrelevant Fab. Second, mutagenic libraries will be created and screened to identify variants of a low affinity anti-HER2 Fab with increased function and affinity. Flow cytometric sorting will be used to select for high affinity binding to soluble HER2 targets, and, separately, to select Fab molecules that result in downstream anti-cancer effects such as apoptosis and growth factor receptor down-regulation in a breast cancer cell line. Finally, a mouse will be immunized with a breast cancer cell line over-expressing HER2 and EGFR, the murine antibody repertoire recovered and transferred to the Fab display system. The murine- derived Fab sequences will be subjected to error-prone PCR and in vitro somatic hypermutation prior to screening to identify antibodies triggering downstream in vitro anti-cancer effects, providing ample opportunity for discovery of synergistic antibodies. The new antibodies will be transferred to a soluble IgG expression system, biochemically characterized, and tested in vitro for prevention of breast cancer cell line growth. Top performing antibodies will be humanized and tested as both monoclonal and polyclonal therapies in in vitro assays and, ultimately, a murine xenograft model. The technology and techniques developed in this proposal will result in a generalizable method for the discovery of more potent therapeutic antibody mixtures, and the resulting antibody cocktails will offer new options for the treatment of breast cancer.

Public Health Relevance

Therapeutic antibodies have proven to be an effective component of cancer treatment. Unfortunately the antibody development pipeline is slow and typically limited to a single antibody at one time; though we know mixtures of antibodies can be more potent against disease. To address these limitations, an antibody discovery platform will be developed that will result in (1) a widely applicable method for streamlined therapeutic antibody development and (2) pools of new synergistic antibodies that can potentially become powerful breast cancer treatments and elucidate mechanisms of anti-cancer antibodies.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
5F32GM111018-02
Application #
8915978
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Barski, Oleg
Project Start
2014-08-01
Project End
2017-07-31
Budget Start
2015-08-01
Budget End
2016-07-31
Support Year
2
Fiscal Year
2015
Total Cost
Indirect Cost
Name
University of Texas Austin
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
170230239
City
Austin
State
TX
Country
United States
Zip Code
78712
Nguyen, Annalee W; Le, Kevin C; Maynard, Jennifer A (2018) Identification of high affinity HER2 binding antibodies using CHO Fab surface display. Protein Eng Des Sel 31:91-101