Comprehensive immune profiling of patients (pts) with metastatic urothelial cancer (mUC) or renal cell cancer (mRCC) receiving immune checkpoint inhibitors (CPIs).
Bibliographic record
Abstract
532 Background: CPIs have had a major impact on pts with mUC and mRCC. Only a small subset of pts benefit from CPI, and predictive biomarkers are needed. The role of circulating immune cells is poorly understood, but early changes after CPI exposure may predict response. We aimed to study the changes in circulating immune cell populations of pts receiving CPIs. Methods: Whole blood was collected prior to, and 3 wks after initiation of CPI in CPI-naïve pts with mUC or mRCC. PBMCs were isolated and profiled using mass cytometry (CyTOF) to provide a comprehensive overview of immune cell populations, expression of immune checkpoints, proliferation, and viability. Expression of chemokine receptors and cytokines was measured by flow cytometry. Treatment-emergent changes were correlated with response. Effects of treatment were determined by Wilcoxon signed-rank test; interactions of treatment and other variables like cluster size were determined by repeated measures two-way ANOVA. Any effects described had a significance of p<0.05. Results: Ten pts enrolled in this pilot study (mRCC = 4, mUC = 6) received anti-PDL1 (n=5), anti-PDL1/anti-CTLA4 (n=3), and anti-PDL1/chemotherapy (n=2). Best response was: 1 CR, 3 PR, 2 SD, 4 PD. Treatment induced an increase in dendritic cells (DC) and a decrease in PD1+ CD4+ and CD8+ T-cells. Elevated Ki-67, CTLA-4, LAMP-1, granzyme B and perforin expression in PD1+ cells post CPI suggested re-invigoration of exhausted T-cells. PD1+ T-cells had increased expression of the chemokine receptors CCR4 and CCR5, and decreased expression of CCR7 and CXCR4, irrespective of treatment. Response was associated with fewer CCR4+ CD4+ T cells and fewer PD1+ CD8+ T cells. Conclusions: Deep profiling by CyTOF provides a means of immune monitoring, with potential applications in clinical trials involving CPIs. Immune responses to CPIs are heterogeneous, with pt subgroups segregated by shifts in both T cell and DCs, and patterns of chemokine receptors and cytokines. Therapy reinvigorates exhausted T cells, and may cause these cells to infiltrate tumors or tumor-draining lymph nodes via chemokine receptors.
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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".