Cytosolic DNA composition is determined by genomic instability mechanism and regulates dendritic cell-mediated anti-tumor immunity
Bibliographic record
Abstract
Patients with colorectal cancers (CRCs) that have microsatellite instability (MSI) (MSI CRCs) face a better prognosis than those with the more common chromosomal instability (CIN) subtype (CIN CRCs) due to improved T cell-mediated anti-tumor immune responses. Previous investigations identified the cytosolic DNA (cyDNA) sensor STING as necessary for chemokine-mediated T cell recruitment in MSI CRCs. Here, we find that cyDNA from MSI CRC cells is inherently more capable of inducing STING activation and improves cytotoxic T cell activation by dendritic cells (DCs). Sequencing indicates that MSI cyDNA is enriched in microsatellites, which, upon DC uptake, induce anti-tumor immunity in a manner consistent with clinical MSI CRCs. DNA-damaging therapies also modulate cyDNA stimulation capacity, with radiation inducing larger cyDNA sizes and increased mitochondrial DNA content. Identifying highly stimulatory endogenous cyDNAs such as those in MSI CRCs will allow for optimized development of DNA-based STING agonist therapies to improve the responses of CIN CRCs with CIN to immunotherapies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".