The impact of surgical resection on circulating tumor-reactive cytotoxic T cells for patients with renal tumors.
Bibliographic record
Abstract
725 Background: The impact of surgical resection of renal tumors on peripheral immune related cells is not well characterized, and has potential implications as biomarkers for systemic immune therapy are being developed. We sought to assess the effect of surgical resection on circulating cytotoxic T-cells (CTLs) for patients with renal tumors. Methods: We prospectively enrolled 40 patients undergoing partial, radical, or cytoreductive nephrectomy (PN, RN, CN) for unilateral primary renal tumors between 2016 and 2018. Blood draws were performed pre-op, 1 day post-op, and 3 months post-op. Flow cytometry was performed on peripheral blood mononuclear cells (PBMCs). The % of PBMCs expressing CD11a/CD8 (CTLs) were assessed. The % of CTLs expressing PD-1, Bim (a downstream PD-1 pathway pro-apoptotic mediator), CX3CR1/GZMB (an effector memory T-cell phenotype), and Ki67 (a proliferation marker) were assessed. Median changes in % of CTLs were evaluated with the Wilcoxon signed rank test. Comparisons between aggressive (pT3-4, N1, M1, or aggressive histology (high-grade, coagulative necrosis, sarcomatoid dedifferentiation, or specific RCC-variant histologies)) versus indolent tumors were assessed using the Wilcoxon rank sum test. Results: Twenty, 12, and 8 patients underwent RN, PN, and CN, respectively. Thirty, 7, and 3 patients had clear-cell RCC, non-clear cell RCC, and oncocytoma, respectively. Twenty-three and 17 patients had aggressive and indolent tumors, respectively. While there was no significant change at 1 day, by 3 months there were significantly increased CTLs among PBMCs (+1.3%; p=0.004). There was significant decrease in CX3CR1+GZMB+ CTLs (-2.9%; p<0.001) and significant increase in Bim+ CTLs (+3.0%; p=0.03) at 1 day but not 3 months. Interestingly, Ki67+ CTLs increased at day 1 (+0.6%; p<0.001) but decreased by 3 months (-0.6%; p=0.001). There were no significant changes in PD-1+ CTLs at either time point. There were no significant changes in any CTL characteristics at 1 day or 3 months between aggressive and indolent tumors. Conclusions: These findings characterize changing CTL profiles over time with surgical resection of renal tumors which may help guide biomarker development.
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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 | 0.001 |
| 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".