Surgical Stress Abrogates Pre-Existing Protective T Cell Mediated Anti-Tumor Immunity Leading to Postoperative Cancer Recurrence
Bibliographic record
Abstract
Anti-tumor CD8+ T cells are a key determinant for overall survival in patients following surgical resection for solid malignancies. Using a mouse model of cancer vaccination (adenovirus expressing melanoma tumor-associated antigen (TAA)-dopachrome tautomerase (AdDCT) and resection resulting in major surgical stress (abdominal nephrectomy), we demonstrate that surgical stress results in a reduction in the number of CD8+ T cell that produce cytokines (IFNγ, TNFα, Granzyme B) in response to TAA. This effect is secondary to both reduced proliferation and impaired T cell function following antigen binding. In a prophylactic model, surgical stress completely abrogates tumor protection conferred by vaccination in the immediate postoperative period. In a clinically relevant surgical resection model, vaccinated mice undergoing a positive margin resection with surgical stress had decreased survival compared to mice with positive margin resection alone. Preoperative immunotherapy with IFNα significantly extends survival in surgically stressed mice. Importantly, myeloid derived suppressor cell (MDSC) population numbers and functional impairment of TAA-specific CD8+ T cell were altered in surgically stressed mice. Our observations suggest that cancer progression may result from surgery-induced suppression of tumor-specific CD8+ T cells. Preoperative immunotherapies aimed at targeting the prometastatic effects of cancer surgery will reduce recurrence and improve survival in cancer surgery patients.
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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) | 0.001 | 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".