Abstract 5815: Both CD4 and CD8 T cells mediate antitumor immunity to prevent development of neoantigen-expressing autochthonous sarcomas
Bibliographic record
Abstract
Sarcoma is a rare, aggressive and highly metastatic disease. The efficacy of current treatment approaches including surgery, chemotherapy and radiation is limited hence the recent focus in novel immunotherapy. However, immunotherapy research for sarcoma is impeded by our limited understanding of the antitumor immune responses, largely due to the lack of faithful mouse models expressing known sarcoma neoantigens. Here, we combined CRISPR/Cas9 and sleeping beauty transposase technology to develop an autochthonous orthotopic murine sarcoma model that allows the tumor to coevolve with the immune system and expresses MHCI (mLama4) and/or MHCII (mItgb1) sarcoma neoantigens. We show that expression of mLama4 and/or mItgb1 neoantigens prevented tumor development in a T-cell dependent manner. Indeed, tumors expressing both neoantigens only developed following depletion of both CD4 and CD8 T cells. Similarly, growth of mItgb1-expressing tumors was observed only in CD4 T cell deficient mice. Tumor-specific T cells were detected, using MHC-mLama4/mItgb1 tetramers, as early as ten days post tumor induction and persisted for more than three months. Both CD4 and CD8 tumor-specific T cells were activated, in cycle, and produced effector cytokines IFNγ and TNFα, suggesting that they both mediate antitumor immunity in part by direct killing of tumor cells. Thus, CD4 and CD8 T cells independently contribute to cancer immunosurveillance leading to clearance of neoantigen-expressing sarcomas. Citation Format: Sabelo Mndeni Lukhele, David G. Kirsch, Jonathon E. Himes. Both CD4 and CD8 T cells mediate antitumor immunity to prevent development of neoantigen-expressing autochthonous sarcomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5815.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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; 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".