Regulatory T Cells in Ovarian Cancer Are Characterized by a Highly Activated Phenotype Distinct from that in Melanoma
Bibliographic record
Abstract
Abstract Purpose: Regulatory T (Treg) cells expressing the transcription factor FOXP3 are essential for the maintenance of immunologic self-tolerance but play a detrimental role in most cancers due to their ability to suppress antitumor immunity. The phenotype of human circulating Treg cells has been extensively studied, but less is known about tumor-infiltrating Treg cells. We studied the phenotype and function of tumor-infiltrating Treg cells in ovarian cancer and melanoma to identify potential Treg cell–associated molecules that can be targeted by tumor immunotherapies. Experimental Design: The phenotype of intratumoral and circulating Treg cells was analyzed by multicolor flow cytometry, mass cytometry, RNA-seq, and functional assays. Results: Treg cells isolated from ovarian tumors displayed a distinct cell surface phenotype with increased expression of a number of receptors associated with TCR engagement, including PD-1, 4-1BB, and ICOS. Higher PD-1 and 4-1BB expression was associated with increased responsiveness to further TCR stimulation and increased suppressive capacity, respectively. Transcriptomic and mass cytometry analyses revealed the presence of Treg cell subpopulations and further supported a highly activated state specifically in ovarian tumors. In comparison, Treg cells infiltrating melanomas displayed lower FOXP3, PD-1, 4-1BB, and ICOS expression and were less potent suppressors of CD8 T-cell proliferation. Conclusions: The highly activated phenotype of ovarian tumor-infiltrating Treg cells may be a key component of an immunosuppressive tumor microenvironment. Receptors that are expressed by tumor-infiltrating Treg cells could be exploited for the design of novel combination tumor immunotherapies. Clin Cancer Res; 24(22); 5685–96. ©2018 AACR.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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; both teacher heads agree on what is shown here.
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".