CD8+ T Cells Induce Complete Regression of Advanced Ovarian Cancers by an Interleukin (IL)-2/IL-15–Dependent Mechanism
Bibliographic record
Abstract
PURPOSE: In vitro studies suggest that ovarian cancer evades immune rejection by fostering an immunosuppressive environment within the peritoneum; however, the functional responses of ovarian cancer-specific T cells have not been directly investigated in vivo. Therefore, we developed a new murine model to enable tracking of tumor-specific CD8(+) T-cell responses to advanced ovarian tumors. EXPERIMENTAL DESIGN: The ovarian tumor cell line ID8 was transfected to stably express an epitope-tagged version of HER-2/neu (designated Neu(OT-I/OT-II)). After i.p. injection into C57BL/6 mice, ID8 cells expressing Neu(OT-I/OT-II) gave rise to disseminated serous adenocarcinomas with extensive ascites. CD8(+) T cells expressing a transgenic T-cell receptor specific for the OT-I epitope of Neu(OT-I/OT-II) were adoptively transferred into tumor-bearing mice, and functional responses were monitored. Cytokine signaling requirements were evaluated by comparing the responses of wild-type donor T cells with those with genetic deletion of the interleukin (IL)-2/IL-15 receptor beta subunit (CD122) or the IL-2 receptor alpha subunit (CD25). RESULTS: On adoptive transfer into tumor-bearing hosts, wild-type OT-I T cells underwent a striking proliferative response, reaching peak densities of approximately 40% and approximately 90% of CD8(+) T cells in peripheral blood and ascites, respectively. OT-I cells infiltrated and destroyed tumor tissue, and ascites completely resolved within 10 days. By contrast, CD122(-/-) OT-I cells and CD25(-/-) OT-I cells proliferated in blood but failed to accumulate in ascites or tumor tissue or induce tumor regression. CONCLUSIONS: Contrary to expectation, advanced ovarian cancers can support extraordinary CD8(+) T-cell proliferation and antitumor activity through an IL-2/IL-15-dependent mechanism.
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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".