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Optimized Fc variants and methods for their generation

Active Publication Date: 2006-07-20
XENCOR
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

[0023] It is a further object of the present invention to provide Fc variants that have been screened computationally. A computationally screened Fc variant is one that is predicted by the computational screening calculations described herein as having a sig

Problems solved by technology

Yet another level of complexity is the existence of a number of FcγR polymorphisms in the human proteome.
Despite such widespread use, antibodies are not optimized for clinical use.
Two significant deficiencies of antibodies are their suboptimal anticancer potency and their demanding production requirements.
Despite this arsenal of anti-tumor weapons, the potency of antibodies as anti-cancer agents is unsatisfactory, particularly given their high cost.
In these cases depletion of target cells is undesirable and can be considered a side effect.
Effector function can also be a problem for radiolabeled antibodies, referred to as radioconjugates, and antibodies conjugated to toxins, referred to as immunotoxins.
Antibodies must be expressed in mammalian cells, and the currently marketed antibodies together with other high-demand biotherapeutics consume essentially all of the available manufacturing capacity.
First, it dramatically raises the cost of goods to the producer, a cost that is passed on to the patient.
Second, it hinders industrial production of approved antibody products, limiting availability of high demand therapeutics to patients.
Finally, because clinical trials require large amounts of a protein that is not yet profitable, the insufficient supply impedes progress of the growing antibody pipeline to market.
This may result in reduced or even lack of effector function because, as discussed above, the carbohydrate structure can significantly impact FcγR and complement binding.
A potentially greater problem with nonhuman glycoforms may be immunogenicity; carbohydrates are a key source of antigenicity for the immune system, and the presence of nonhuman glycoforms has a significant chance of eliciting antibodies that neutralize the therapeutic, or worse cause adverse immune reactions.
Thus the efficacy and safety of antibodies produced by transgenic plants and animals remains uncertain.
For complex proteins such as antibodies there are a number of obstacles to bacterial expression, including folding and assembly of these complex molecules, proper disulfide formation, and solubility, stability, and functionality in the absence of glycosylation because proteins expressed in bacteria are not glycosylated.
However the ultimate utility of bacterially expressed antibodies as therapeutics remains hindered by the lack of glycosylation, which results in lack effector function and may result in poor stability and solubility.
This will likely be more problematic for formulation at the high concentrations for the prolonged periods demanded by clinical use.
Yet a substantial obstacle to engineering Fc variants with the desired properties is the difficulty in predicting what amino acid modifications, out of the enormous number of possibilities, will achieve the desired goals, coupled with the inefficient production and screening methods for antibodies.
Indeed one of the principle reasons for the incomplete success of the prior art is that approaches to Fc engineering have thus far involved hit-or-miss methods such as alanine scans or production of glycoforms using different expression strains.

Method used

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  • Optimized Fc variants and methods for their generation
  • Optimized Fc variants and methods for their generation
  • Optimized Fc variants and methods for their generation

Examples

Experimental program
Comparison scheme
Effect test

example 1

Computational Screening and Design of Fc Libraries

[0191] Computational screening calculations were carried out to design optimized Fc variants. Fc variants were computationally screened, constructed, and experimentally investigated over several computation / experimention cycles. For each successive cycle, experimental data provided feedback into the next set of computational screening calculations and library design. All computational screening calculations and library design are presented in Example 1. For each set of calculations, a table is provided that presents the results and provides relevant information and parameters.

[0192] Several different structures of Fc bound bound to the extracellular domain of FcγRs served as template structures for the computational screening calculations. Publicly available Fc / FcγR complex structures included pdb accession code 1E4K (Sondermann et al., 2000, Nature 406:267-273.), and pdb accession codes 1IIS and 1IIX (Radaev et al., 2001, J Biol C...

example 2

Experimental Production and Screening of Fc Libraries

[0258] The majority of experimentation on the Fc variants was carried out in the context of the anti-cancer antibody alemtuzumab (Campath®, a registered trademark of Ilex Pharmaceuticals LP). Alemtuzumab binds a short linear epitope within its target antigen CD52 (Hale et al., 1990, Tissue Antigens 35:118-127; Hale, 1995, Immunotechnology 1:175-187). Alemtuzumab has been chosen as the primary engineering template because its efficacy is due in part to its ability to recruit effector cells (Dyer et al., 1989, Blood 73:1431-1439; Friend et al., 1991, Transplant Proc 23:2253-2254; Hale et al., 1998, Blood 92:4581-4590; Glennie et al., 2000, Immunol Today 21:403-410), and because production and use of its antigen in binding assays are relatively straightforward. In order to evaluate the optimized Fc variants of the present invention in the context of other antibodies, select Fc variants were evaluated in the anti-CD20 antibody rituxi...

example 3

Selectively Enhanced Binding to FcγRs

[0264] A number of promising Fc variants with optimized properties were obtained from the FcγRIIIa and FcγRIIb screen. Table 62 provides Fc variants that bind more tightly to FcγRIIIa, and thus are candidates for improving the effector function of antibodies and Fc fusions. These include a number of variants that comprise substitutions at 239, 264, 272, 274, 330, and 332. FIGS. 13a and 13b show AlphaScreen™ binding data for some of these Fc variants. The majority of these Fc variants provide substantially greater FcγRIIIa binding enhancements over S298A / E333A / K334A.

[0265] Select Fc variants were screened in the context of multiple antibodies in order to investigate the breadth of their applicability. AlphaScreen™ data for binding of select Fc variants to human V158 FcγRIIIa in the context of trastuzumab, rituximab, and cetuximab are shown in FIGS. 14a, 14b, 15a, and 15b. Together with the data for alemtuzumab in FIG. 13, the results indicate co...

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Abstract

The present invention relates to optimized Fc variants, methods for their generation, and antibodies and Fc fusions comprising optimized Fc variants.

Description

[0001] This application claims benefit under 35 U.S.C. §199(e) to U.S. Pat. Nos. 10 / 672280, filed Sep. 26, 2003, 10 / 379392, filed Mar. 3, 2003, 60 / 477,839 filed Jun. 12, 2003; 60 / 467,606, filed May 2, 2003; 60 / 414,433 filed Sep. 27, 2002; and 60 / 442,301 filed Jan. 23, 2003, all of which are expressly incorporated by reference in their entirety.FIELD OF THE INVENTION [0002] The present invention relates to novel optimized Fc variants, engineering methods for their generation, and their application, particularly for therapeutic purposes. BACKGROUND OF THE INVENTION [0003] Antibodies are immunological proteins that bind a specific antigen. In most mammals, including humans and mice, antibodies are constructed from paired heavy and light polypeptide chains. Each chain is made up of individual immunoglobulin (Ig) domains, and thus the generic term immunoglobulin is used for such proteins. Each chain is made up of two distinct regions, referred to as the variable and constant regions. The...

Claims

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Application Information

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IPC IPC(8): C07K16/44C07K16/00C07K16/22C07K16/28C07K16/30C07K16/32
CPCA61K2039/505C07K16/00C07K16/22C07K16/283C07K16/2863C07K16/2887C07K16/2893C07K16/2896C07K16/30C07K16/3015C07K16/32C07K2317/71C07K2317/72C07K2317/732C07K2317/734C07K2317/77C07K2317/92C07K2317/52C07K2317/34A61P3/10A61P9/04A61P25/00A61P29/00A61P31/00A61P35/00A61P35/02A61P37/00A61P37/02A61P43/00
Inventor LAZAR, GREGORY ALANCHIRINO, ARTHUR J.DANG, WEIDESJARLAIS, JOHN R.DOBERSTEIN, STEPHEN KOHLHAYES, ROBERT J.KARKI, SHER BAHADURVAFA, OMID
Owner XENCOR
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