Production and Characterization of a Camelid Single Domain Antibody–Urease Enzyme Conjugate for the Treatment of Cancer
Bibliographic record
Abstract
A novel immunoconjugate (L-DOS47) was developed and characterized as a therapeutic agent for tumors expressing CEACAM6. The single domain antibody AFAIKL2, which targets CEACAM6, was expressed in the Escherichia coli BL21 (DE3) pT7-7 system. High purity urease (HPU) was extracted and purified from Jack bean meal. AFAIKL2 was activated using N-succinimidyl [4-iodoacetyl] aminobenzoate (SIAB) as the cross-linker and then conjugated to urease. The activation and conjugation reactions were controlled by altering pH. Under these conditions, the material ratio achieved conjugation ratios of 8-11 antibodies per urease molecule, the residual free urease content was practically negligible (<2%), and high purity (>95%) L-DOS47 conjugate was produced using only ultradiafiltration to remove unreacted antibody and hydrolyzed cross-linker. L-DOS47 was characterized by a panel of analytical techniques including SEC, IEC, Western blot, ELISA, and LC-MS(E) peptide mapping. As the antibody-urease conjugate ratio increased, a higher binding signal was observed. The specificity and cytotoxicity of L-DOS47 was confirmed by screening in four cell lines (BxPC-3, A549, MCF7, and CEACAM6-transfected H23). BxPC-3, a CEACAM6-expressing cell line was found to be most susceptible to L-DOS47. L-DOS47 is being investigated as a potential therapeutic agent in human phase I clinical studies for nonsmall cell lung cancer.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".