Chromosome 9p21.3 Coordinates Cell Intrinsic and Extrinsic Tumor Suppression
Bibliographic record
Abstract
SUMMARY Somatic chromosomal deletions are prevalent in cancer, yet their functional contributions remain ill-defined. Among the most prominent of these events are deletions of chromosome 9p21.3, which disable a cell intrinsic barrier to tumorigenesis by eliminating the CDKN2A/B tumor suppressor genes. However, half of 9p21.3 deletions encompass a cluster of 16 type I interferons (IFNs) whose co-deletions have not been functionally characterized. To dissect how 9p21.3 and other genomic deletions impact cancer, we developed MACHETE (Molecular Alteration of Chromosomes with Engineered Tandem Elements), a genome engineering strategy that enables flexible modeling of megabase-sized deletions. Generation of 9p21.3-syntenic deletions in a mouse model of pancreatic cancer revealed that concomitant loss of Cdkn2a/b and the IFN cluster led to immune evasion and metastasis compared to Cdkn2a/b -only deletions. Mechanistically, IFN co-deletion disrupted type I IFN signaling, altered antigen-presenting cells, and facilitated escape from CD8+ T cell surveillance in a cell extrinsic manner requiring loss of interferon epsilon ( Ifne ). Our results establish co-deletions of the IFN cluster as a pervasive route to tumor immune evasion and metastasis, revealing how deletions can disable physically linked cell intrinsic and extrinsic tumor suppression. Our study establishes a framework to dissect the functions of genomic deletions in cancer and beyond.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".