Bone Marrow-Derived Dendritic Cell Vaccination of Dogs with Naturally Occurring Melanoma by Using Human gp100 Antigen
Bibliographic record
Abstract
Canine malignant melanoma (CMM) is a common and aggressive form of cancer in dogs. Established therapeutic approaches such as surgery, chemotherapy, and radiation therapy (RT) have not proven curative. As a coadjuvant of RT and to enhance the antimelanoma immune response, we characterized dendritic cells (DCs) from the bone marrow (BM) of dogs with CMM, ex vivo, for use in therapeutic vaccines. BM mononuclear cells from 3 dogs with melanoma and from 1 healthy dog were cultured for 12 days in media supplemented with recombinant human granulocyte-macrophage colony stimulating factor, stem cell factor, tumor necrosis factor, and Flt-3 ligand. On day 11, DCs were transduced with an adenovirus vector encoding a xenoantigen, human melanoma antigen gp100. Each dog received 3 subcutaneous vaccinations over a 4-month period. Phenotypic analysis of the expanded DC population demonstrated expression of CD11c/CD18 and major histocompatibility complex class II surface markers, and ultrastructural features characteristic of DCs were observed on electron microscopy. On functional analysis, these DCs were able to stimulate allo-reactivity and capture and express gp100. One dog demonstrated antigen-specific cytotoxic T lymphocyte (CTL) activity in peripheral blood lymphocytes. This dog has displayed no clinical signs, either locally or systemically, of recurrent melanoma 48 months after initial DC injection. However, another dog, which was CTL negative, relapsed 22 months after vaccination. Ex vivo DC expansion is feasible for immunotherapy of spontaneous cancers in outbred dogs.
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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) | 0.001 | 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 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".