Cell-based cancer gene therapy: breaking tolerance or inducing autoimmunity?
Bibliographic record
Abstract
This review examines the mechanisms involved in anti-tumor immunity and how peptides present in many tumor types (tumor-associated antigens) are recognized by T cells from tumor-bearing cancer patients. Tumor-associated antigens are derived from proteins that are also expressed in normal cells. It is predicted that immune responses to such peptides will be compromised by self-tolerance or that stimulation of effective immune responses will be accompanied by autoimmunity. We also consider that the immunity induced against two autoantigens, which are highly conserved in vertebrates, involve qualitatively different mechanisms, such as the production of antibodies and cell-mediated immune responses. However, both pathways lead to tumor immunity and identical phenotypic manifestations of autoimmunity. Appropriate selection of the optimal tumor antigen is critical for the induction of an anti-tumor immune response. Thus, we stress that the methods for antigen presentation using dendritic cells play a critical role in the development of tumor vaccines, to break immune tolerance and induce a strong immune response against them. The viability and feasibility of expansion of canine dendritic cells from bone marrow and peripheral blood ex vivo for the treatment of spontaneous cancers in dogs is also discussed.
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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 | 0.011 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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; both teacher heads agree on what is shown here.
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".