Human Activated T Lymphocytes Modulate IDO Expression in Tumors through Th1/Th2 Balance
Bibliographic record
Abstract
Previous cancer vaccination approaches have shown some efficiency in generating measurable immune responses, but they have rarely led to tumor regression. It is therefore possible that tumors emerge with the capacity to down-regulate immune counterparts, through the local production of immunosuppressive molecules, such as IDO. Although it is known that IDO exerts suppressive effects on T cell functions, the mechanisms of IDO regulation in tumor cells remain to be characterized. Here, we demonstrate that activated T cells can induce functional IDO expression in breast and kidney tumor cell lines, and that this is partly attributable to IFN-gamma. Moreover, we found that IL-13, a Th2 cytokine, has a negative modulatory effect on IDO expression. Furthermore, we report IDO expression in the majority of breast and kidney carcinoma samples, with infiltration of activated Th1-polarized T cells in human tumors. These findings demonstrate complex control of immune activity within tumors. Future immune therapeutic interventions should thus include strategies to counteract these negative 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) | 0.000 | 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) | 0.001 | 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".