Initial Evaluation of Antibody-conjugates Modified with Viral-derived Peptides for Increasing Cellular Accumulation and Improving Tumor Targeting
Bibliographic record
Abstract
Antibody-conjugates (ACs) modified with virus-derived peptides are a potentially powerful class of tumor cell delivery agents for molecular payloads used in cancer treatment and imaging due to increased cellular accumulation over current ACs. During early AC in vitro development, fluorescence techniques and radioimmunoassays are sufficient for determining intracellular localization, accumulation efficiency, and target cell specificity. Currently, there is no consensus on standardized methods for preparing cells for evaluating AC intracellular accumulation and localization. The initial testing of ACs modified with virus-derived peptides is critical especially if several candidates have been constructed. Determining intracellular accumulation by fluorescence can be affected by background signal from ACs at the cell surface and complicate the interpretation of accumulation. For radioimmunoassays, typically treated cells are fractionated and the radioactivity in different cell compartments measured. However, cell lysis varies from cell to cell and often nuclear and cytoplasmic compartments are not adequately isolated. This can produce misleading data on payload delivery properties. The intravenous injection of radiolabeled virus-derived peptide-modified ACs in tumor bearing mice followed by radionuclide imaging is a powerful method for determining tumor targeting and payload delivery properties at the in vivo phase of development. However, this is a relatively recent advancement and few groups have evaluated virus-derived peptide-modified ACs in this manner. We describe the processing of treated cells to more accurately evaluate virus-derived peptide-modified AC accumulation when using confocal microscopy and radioimmunoassays. Specifically, a method for trypsinizing cells to remove cell surface bound ACs. We also provide a method for improving cellular fractionation. Lastly, this protocol provides an in vivo method using positron emission tomography (PET) for evaluating initial tumor targeting properties in tumor-bearing mice. We use the radioisotope 64Cu (t1/2 = 12.7 h) as an example payload in this protocol.
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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 | 0.002 | 0.001 |
| 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".