CRISPR/Cas9 screening: unraveling cancer immunotherapy’s ‘Rosetta Stone’
Bibliographic record
Abstract
Clustered regularly interspaced palindromic repeats (CRISPR)-based technology, a powerful toolset for the unbiased functional genomic screening of biological processes, has facilitated several scientific breakthroughs in the biomedical field. Cancer immunotherapy has advanced the treatment of numerous malignancies that previously had restricted treatment options or unfavorable outcomes. In the realm of cancer immunotherapy, the application of CRISPR/CRISPR-associated protein 9 (Cas9)-based genetic perturbation screening has enabled the identification of genes, biomarkers, and signaling pathways that govern various cancer immunoreactivities, as well as the development of effective immunotherapeutic targets. In this review, we summarize the advances in CRISPR/Cas9-based screening for cancer immunotherapy and outline the immunotherapeutic targets identified via CRISPR screening based on cancer-type classification.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".