Pyroptosis Remodeling Tumor Microenvironment to Enhance Pancreatic Cancer Immunotherapy Driven by Membrane Anchoring Photosensitizer
Bibliographic record
Abstract
Abstract Immunotherapy, the most promising strategy of cancer treatment, has achieved promising outcomes, but its clinical efficacy in pancreatic cancer is limited mainly due to the complicated tumor immunosuppressive microenvironment. As a highly inflammatory form of immunogenic cell death (ICD), pyroptosis provides a great opportunity to alleviate immunosuppression and promote systemic immune responses in solid tumors. Herein, membrane‐targeted photosensitizer TBD‐3C with aggregation‐induced emission (AIE) feature to trigger pyroptosis‐aroused cancer immunotherapy via photodynamic therapy (PDT) is applied. The results reveal that pyroptotic cells induced by TBD‐3C could stimulate M1‐polarization of macrophages, cause maturation of dendritic cells (DCs), and activation of CD8 + cytotoxic T‐lymphocytes (CTLs). Pyroptosis‐aroused immunological responses could convert immunosuppressive “cold” tumor microenvironment (TME) to immunogenic “hot” TME, which not only inhibits primary pancreatic cancer growth but also attacks the distant tumor. This work establishes a platform with high biocompatibility for light‐controlled antitumor immunity and solid tumor immunotherapy aroused by cell pyroptosis.
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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".