Viral subversion of APOBEC3s: Lessons for anti-tumor immunity and tumor immunotherapy
Bibliographic record
Abstract
APOBEC3s (A3) are endogenous DNA-editing enzymes that are expressed in immune cells including T lymphocytes. A3s target and mutate the genomes of retroviruses that infect immune tissues such as the human immunodeficiency virus (HIV). Therefore, A3s were classically defined as host anti-viral innate immune factors. In contrast, we and others showed that A3s can also benefit the virus by mediating escape from adaptive immune recognition and drugs. Crucially, whether A3-mediated mutations help or hinder HIV, is not up to chance. Rather, the virus has evolved multiple mechanisms to actively and maximally subvert A3 activity. More recently, extensive A3 mutational footprints in tumor genomes have been observed in many different cancers. This suggests a role for A3s in cancer initiation and progression. On the other hand, multiple anti-tumor activities of A3s have also come to light, including impact on immune checkpoint molecules and possible generation of tumor neo-antigens. Here, we review the studies that reshaped the view of A3s from anti-viral innate immune agents to host factors exploited by HIV to escape from immune recognition. Viruses and tumors share many attributes, including rapid evolution and adeptness at exploiting mutations. Given this parallel, we then discuss the pro- and anti-tumor roles of A3s, and suggest that lessons learned from studying A3s in the context of anti-viral immunity can be applied to tumor immunotherapy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".