Coinhibitory Receptor Expression and Immune Checkpoint Blockade: Maintaining a Balance in CD8+ T Cell Responses to Chronic Viral Infections and Cancer
Bibliographic record
Abstract
In cancer and chronic viral infections, T cells are exposed to persistent antigen stimulation. This results in expression of multiple inhibitory receptors also called "immune checkpoints" by T cells. Although these inhibitory receptors under normal conditions maintain self-tolerance and prevent immunopathology, their sustained expression deteriorates T cell function: a phenomenon called exhaustion. Recent advances in cancer immunotherapy involve blockade of cytotoxic T lymphocyte antigen-4 and programmed cell death 1 in order to reverse T cell exhaustion and reinvigorate immunity, which has translated to dramatic clinical remission in many cases of metastatic melanoma and lung cancer. With the paucity of therapeutic vaccines against chronic infections such as HIV, HPV, hepatitis B, and hepatitis C, such adjunct checkpoint blockade strategies are required including the blockade of other inhibitory receptors such as T cell immunoreceptor with immunoglobulin (Ig) and immunoreceptor tyrosine-based inhibitory motif domains, T cell Ig and mucin-domain containing-3, lymphocyte activation gene 3, and V-domain Ig-containing suppressor of T cell activation. The nature of different chronic viral infections and cancers is likely to influence the level, composition, and pattern of inhibitory receptors expressed by responding T cells. This will have implications for checkpoint antibody blockade strategies employed for treating tumors and chronic viral infections. Here, we review recent advances that provide a clearer insight into the role of coinhibitory receptor expression in T cell exhaustion and reveal novel antibody-blockade therapeutic targets for chronic viral infections and cancer. Understanding the mechanism of T cell exhaustion in response to chronic virus infections and cancer as well as the nature of restored T cell responses will contribute to further improvement of immune checkpoint blockade strategies.
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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) | 0.002 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".