A Single‐Metal‐Doped Nanoplatform for Ferroptosis‐Driven cGAS‐STING Pathway Activation in Hepatocellular Carcinoma Immunotherapy
Bibliographic record
Abstract
Abstract The cGAS‐STING signaling pathway effectively activates antitumor immune responses and holds promise for overcoming drug resistance in hepatocellular carcinoma (HCC) immunotherapy. However, achieving specific activation of this pathway in HCC remains challenging. Here, it is introduced a single‐metal‐doped nanoplatform, ZMRPF, which leverages ferroptosis‐induced mitochondrial DNA (mtDNA) release to stimulate cGAS‐STING‐mediated immune activation. ZMRPF initiates HCC ferroptosis by inducing high levels of lipid reactive oxygen species, leading to mitochondrial stress and the release of endogenous mtDNA. This mtDNA synergistically activates the cGAS‐STING pathway, enhanced by immunoactivating Mn 2 ⁺ ions released from ZMRPF. Concurrently, the tumor antigens released during ferroptosis amplify the activity of antigen‐presenting cells, creating a cascade that links ferroptosis with innate immunity. This cascade drives a robust systemic antitumor immune response, effectively reversing the immunosuppressive microenvironment of HCC. These results demonstrate the ability of ZMRPF to reshape the immune microenvironment of HCC and offer a promising strategy for next‐generation tumor immunotherapy.
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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".