Multi-parameter flow cytometry analysis of circulating immune cell populations in recurrent/metastatic adenoid cystic carcinoma
Bibliographic record
Abstract
Background Adenoid cystic carcinoma (ACC) is characterized by high recurrence rates despite surgery and radiotherapy, and anti-PD-1/PD-L1 therapy has limited clinical efficacy in the recurrent/metastatic setting. This study sought to characterise circulating immune cell sub-sets and identify candidate targets for novel immunotherapies in ACC. Methods Blood samples from 22 anti-PD1/PDL1 naive ACC patients, 26 anti-PD1/PDL1 naive head and neck squamous cell carcinoma (SCC) patients and 13 healthy volunteers underwent multi-parameter flow cytometry for comprehensive classification of the immune cell populations, using commercially available validated panels. Results were analysed using FlowJo. Results This study identified significant expansion of CD14hi/CD16+ monocytes compared with healthy volunteers in a sub-population of ACC patients (mean 28%, range 10% to 58%, versus 9% range 1% to 20% p<0.05). This monocyte sub-set was also seen in the comparator group of SCC patients (mean 36%, range 12%-78%.) Expression levels of PDL1 on CD14+ monocytes was greater in ACC monocytes compared to samples from our SCC patient cohort (mean 60% v 32%; p=0.09). Furthermore, 55% of ACC patients had elevated COX-2 expression (greater than 30%), by intracellular fluorescence activated cell sorting in CD14+ monocytes compared with 22% in our SCC group. With regards to T cells, peripheral blood from ACC patients had a decreased CD4+/CD8+ ratio compared to SCC (2.85 vs 5.5.) Furthermore, a significantly higher proportion of CD8+ cells were naïve as defined by CCR7+/CD45RA+ (Mean 38% vs 16% p<0.01). No differences were observed in the proportions of NK T cells, though we did identify a highly significant reduction of TIGIT on them in ACC compared with SCC patients (16% versus 40% of total CD3+ p=<0.001). Conclusions This study provides insights into distinct immune cell subsets in ACC patients. Our findings suggest that novel immunotherapies, including targeting of COX-2, may be have a rationale in ACC. Additionally, TIGIT is associated with exhaustion and so the reduced expression of TIGIT on NK-T cells in ACC may help guide future trial selection.
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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 | 0.001 | 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".