Targeting G Protein–Coupled Receptors in Immuno-Oncological Therapies
Bibliographic record
Abstract
The advent of cancer immunotherapy based on PD-1 and CTLA-4 immune checkpoint blockade (ICB) has revolutionized cancer treatment. However, many cancers do not respond to ICB, highlighting the urgent need for additional approaches to achieve durable cancer remission. The large family of G protein-coupled receptors (GPCRs) is the target of more than 30% of all approved drugs, but GPCRs have been underexploited in cancer immunotherapy. In this review, we discuss the central role of GPCRs in immune cell migration and function and describe how single-cell transcriptomic studies are illuminating the complexity of the human tumor immune GPCRome. These receptors include multiple GPCRs expressed in CD8 T cells that are activated by inflammatory mediators, protons, neurotransmitters, and metabolites that accumulate in the tumor microenvironment, thereby promoting T cell dysfunction. We also discuss new opportunities to target GPCRs as a multimodal approach to enhance the response to ICB for a myriad of human malignancies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".