Abstract 2515: Tumor presenting cells: a new strategy for cancer immunotherapy
Bibliographic record
Abstract
Abstract Solid tumor cells as other non-immunological cells do not present MHC Class II. The MHC class II is a critical molecule responsible for peptide presentation to T helper cells. The presence of a not-self peptide on a MHC II molecule trigger the production of cytokines responsible for different steps on T cell expansion and maturation. Without the appropriate cytokine stimulation, cytotoxic T cells that identified a not-self peptide associate to a MHC class I molecules, may not proliferate or even be induce to anergy. We hypothesized that lack of anti-tumor immune responses on the majority of cancer patients (too little, too late) is due to a not appropriate MHC II peptide presentation. In our model, solid tumor cells (prostate cancer) are induce to express MHCII on their surface. In this novel approach of Cell Based Cancer Immunotherapy, patient's tumor cells were expanded in tissue culture and treated causing de novo expression of MHC II and activation of the MHC II peptide presentation pathway. Thus, the modified cancer cells are bifunctional, being capable of activating both helper T cells (MHC II) and cytotoxic T cells (MHCI), leading to cytokine production and a surprisingly robust and cancer-specific immune response. The modified solid tumor cell by itself will now behave as an antigen-presenting cell creating a Tumor Presenting Cell (TPC). As previous reported on a Phase IIb clinical trial done in Brazil (FK-Biotec/UFRGS/PUCRS), a population of local advance prostate cancer patients were treated with TPC. The study showed a significant (p = 0,03) increase in number of patients with undetectable levels of PSA (biochemical cure) after 5 years, 85% versus 48% on the control group. Also shown a trend of lowering mortality by prostate cancer, 9% in the threated group versus 19% in the control group. In conclusion, we are describing a novel Cell Based Cancer Immunotherapy that could be apply to several different tumor types. Citation Format: Fernando T. Kreutz. Tumor presenting cells: a new strategy for cancer immunotherapy. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2515. doi:10.1158/1538-7445.AM2015-2515
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".