Anti-tumor immunity in mismatch repair-deficient colorectal cancers requires type I IFN–driven CCL5 and CXCL10
Bibliographic record
Abstract
Colorectal cancers (CRCs) deficient in DNA mismatch repair (dMMR) contain abundant CD8+ tumor-infiltrating lymphocytes (TILs) responding to the abundant neoantigens from their unstable genomes. Priming of such tumor-targeted TILs first requires recruitment of CD8+ T cells into the tumors, implying that this is an essential prerequisite of successful dMMR anti-tumor immunity. We have discovered that selective recruitment and activation of systemic CD8+ T cells into dMMR CRCs strictly depend on overexpression of CCL5 and CXCL10 due to endogenous activation of cGAS/STING and type I IFN signaling by damaged DNA. TIL infiltration into orthotopic dMMR CRCs is neoantigen-independent and followed by induction of a resident memory-like phenotype key to the anti-tumor response. CCL5 and CXCL10 could be up-regulated by common chemotherapies in all CRCs, indicating that facilitating CD8+ T cell recruitment underlies their efficacy. Induction of CCL5 and CXCL10 thus represents a tractable therapeutic strategy to induce TIL recruitment into CRCs, where local priming can be maximized even in neoantigen-poor CRCs.
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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 | 0.001 |
| 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 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".