Production of afucosylated antibodies in CHO cells by coexpression of an anti‐FUT8 intrabody
Bibliographic record
Abstract
Some effector functions prompted by immunoglobulin G (IgG) antibodies, such as antibody-dependent cell-mediated cytotoxicity (ADCC), strongly depend on the N-glycans linked to asparagine 297 of the Fc region of the protein. A single α-(1,6)-fucosyltransferase (FUT8) is responsible for catalyzing the addition of an α-1,6-linked fucose residue to the first GlcNAc residue of the N-linked glycans. Antibodies missing this core fucose show a significantly enhanced ADCC and increased antitumor activity, which could help reduce therapeutic dose requirement, potentially translating into reduced safety concerns and manufacturing costs. Several approaches have been developed to modify glycans and improve the biological functions of antibodies. Here, we demonstrate that expression of a membrane-associated anti-FUT8 intrabody engineered to reside in the endoplasmic reticulum and Golgi apparatus can efficiently reduce FUT8 activity and therefore the core-fucosylation of the Fc N-glycan of an antibody. IgG1-producing CHO cells expressing the intrabody secrete antibodies with reduced core fucosylation as demonstrated by lectin blot analysis and UPLC-HILIC glycan analysis. Cells engineered to inhibit directly and specifically alpha-(1,6)-fucosyltransferase activity allows for the production of g/L levels of IgGs with strongly enhanced ADCC effector function, for which the level of fucosylation can be selected. The quick and efficient method described here should have broad practical applicability for the development of next-generation therapeutic antibodies with enhanced effector functions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".