Intratumoral STING activation causes durable immunogenic tumor eradication in the KP soft tissue sarcoma model
Bibliographic record
Abstract
Introduction: Soft tissue sarcomas (STS) are highly metastatic, connective-tissue lineage solid cancers. Immunologically, sarcomas are frequently characterized by a paucity of tumor infiltrating lymphocytes and an immune suppressive microenvironment. Activation of the STING pathway can induce potent immune-driven anti-tumor responses within immunogenic solid tumors; however, this strategy has not been evaluated in immunologically cold sarcomas. Herein, we assessed the therapeutic response of intratumoral STING activation in an immunologically cold murine model of undifferentiated pleomorphic sarcoma (UPS). Materials and Results: A single intratumoral injection of the murine STING agonist, DMXAA resulted in durable cure in up to 60% of UPS-bearing mice. In mice with synchronous lung metastases, STING activation within hindlimb tumors resulted in 50% cure in both anatomic sites. Surviving mice all rejected UPS re-challenge in the hindlimb and lung. Therapeutic efficacy of STING was inhibited by lymphocyte deficiency but unaffected by macrophage deficiency. Immune phenotyping demonstrated enrichment of lymphocytic responses in tumors at multiple timepoints following treatment. Immune checkpoint blockade enhanced survival following STING activation. Discussion: These data suggest intratumoral activation of the STING pathway elicits local and systemic anti-tumor immune responses in a lymphocyte poor sarcoma model and deserves further evaluation as an adjunctive local and systemic treatment for sarcomas.
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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".