Killers 2.0: NK cell therapies at the forefront of cancer control
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Natural killer (NK) cells are innate cytotoxic lymphocytes involved in the surveillance and elimination of cancer. As we have learned more and more about the mechanisms NK cells employ to recognize and eliminate tumor cells, and how, in turn, cancer evades NK cell responses, we have gained a clear appreciation that NK cells can be harnessed in cancer immunotherapy. Here, we review the evidence for NK cells' critical role in combating transformed and malignant cells, and how cancer immunotherapies potentiate NK cell responses for therapeutic purposes. We highlight cutting-edge immunotherapeutic strategies in preclinical and clinical development such as adoptive NK cell transfer, chimeric antigen receptor-expressing NK cells (CAR-NKs), bispecific and trispecific killer cell engagers (BiKEs and TriKEs), checkpoint blockade, and oncolytic virotherapy. Further, we describe the challenges that NK cells face (e.g., postsurgical dysfunction) that must be overcome by these therapeutic modalities to achieve cancer clearance.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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 it