Spontaneous Autoimmunity Sufficiently Potent to Induce Diabetes Mellitus Is Insufficient to Protect against Insulinoma
Bibliographic record
Abstract
Intact tolerogenic mechanisms preclude effective immunity against tumors, as most tumor Ags differ little from normal host Ags. In contrast, when tolerance fails, the immune system becomes inappropriately activated against an autoantigen. We postulated that CD8(+) T cells activated during autoimmunity are capable of protecting against tumors that express the targeted autoantigen. To test this hypothesis, double-transgenic 8.3-NOD-RIPTAg mice were developed (where NOD is nonobese diabetic, RIP is rat insulin promoter, and TAg is large T Ag). In this model, individuals with the RIPTAg transgene develop insulinoma; those expressing a transgenic TCR (8.3-TCR) recognizing the islet-specific glucose 6 phosphatase catalytic subunit-related protein (IGRP) harbor a peripheral immune system dominated by diabetogenic CD8(+) T cells. Although tumor emergence was significantly slower in 8.3-NOD-RIPTAg mice compared with NOD-RIPTAg mice, all 8.3-NOD-RIPTAg mice eventually developed insulinoma. Tumor emergence was not secondary to clonal deletion or anergy. Ag loss and MHC down-regulation were not apparent. Endogenous 8.3-TCR CD8(+) T cells were recruited to the tumor site and proliferated upon arrival to the tumor, although they were notably absent from the central parts of more advanced tumors. These results demonstrate that a breakdown of tolerance capable of causing autoimmune disease is insufficient for effective tumor immunity. Alterations in the tumor microenvironment may inhibit efficient and comprehensive delivery of CD8(+) T cells to all regions of the tumor. These data suggest that any immunotherapeutic strategy for cancer must involve enhancement of a proinflammatory tumor microenvironment in addition to inhibition of tolerogenic mechanisms.
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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) | 0.001 | 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 | 0.001 |
| 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 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".