Towards canine immunotherapy models: Monoclonal antibodies with redox regulated epitopes targeting TIM3 attenuate Galectin-9 binding
Bibliographic record
Abstract
The TIM3 receptor acts as an immune checkpoint protein. Canine cancers exhibit higher pan-cancer penetrance of TIM3 compared to PD1, highlighting the potential of TIM3 as a compelling target in comparative immuno-oncology. We have used a highly diverse naïve canine scFv phage library to isolate antibodies to canine TIM3. Alternating rounds of biopanning were performed using either Fc or GST tagged canine TIM3 synthesized in mammalian cells. scFv sequences were identified using colony screening and next generation deep sequencing (NGS). The NGS protocol identified lower abundant frequency clones, demonstrating the enhanced depth of repertoire discovery possible using sequence-tag based tracing. Three representative scFv were expressed as mouse-canine chimeric scFv-Fc fusions or as full-length chimeric IgG. These antibodies all bound to the TIM3 receptor using either ELISA or immunoblotting. All the antibodies displayed sensitivity to reducing agents, which indicates the existence of disulfide-stabilized conformational epitopes. Epitope mapping using pepscan libraries suggested that the antibodies recognize a shared structural motif within the IgV domain of TIM3, within β-sheets fixed by disulfide bonds which would form the conformational epitope. Such conformational epitopes might be functional because they overlap with ligand-binding interfaces. Consistent with this, the antibodies attenuated TIM3 binding to Galectin-9. These data affirm that naïve canine scFv antibody libraries can yield self-antigen reactive antibodies to immune blockade receptor antigens. The data also emphasize the value in using native, folded, mammalian expressed receptor antigens to increase the probability of acquiring conformationally sensitive antibodies with potential therapeutic applications in veterinary and human medicine.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".