Tumor-Targeted Gene Silencing IDO Synergizes PTT-Induced Apoptosis and Enhances Anti-tumor Immunity
Bibliographic record
Abstract
Background: Photothermal therapy (PTT) has been demonstrated as a promising cancer treatment approach, which can be modulated to induce apoptosis instead of necrosis via adjusting irradiation conditions. Recently, an abscopal anti-tumor immunity is highlighted, in which PTT on primary tumor also induced repression of distant tumors. For PTT treating cancers, the mechanism and the role of immunochenck points to enhance anti-tumor immunity is urgently needed to investigate. Methods: We prepared a multi-functional gold nanorod reagent, GMPF-siIDO, that is composed of gold nanorods (GNRs) acting as the nano-platform and photothermal sensitizer, folic acid (FA) as the tumor-targeting moiety, and IDO-specific RNA (siIDO) as an immune-stimulator functionality for inducing anti-tumor immunity. For this study, we adjust the irradiation condition of PTT to induce apoptosis and silence the immunocheck point indoleamine 2,3 dioxygeonase (IDO), silmutaneously. Results: Our studies firstly provide evidences that photothermal effects, killing the tumor cells mainly via inducing apoptosis, can significantly improve antitumor immunity only when IDO was down-regulated in TME through significant increases of localized CD8+ and CD4+ lymphocytes in tumor tissue, downregulation of CD8+ and CD4+ lymphocyte apoptosis, and upregulation of antitumor cytokines, TNF-α and IFN-γ. Conclusion: In this study, we for the first time validated the role of IDO as a negative regulator for both PTT-induced tumor cell apoptosis and anti-tumor immunity; IDO is critical immune checkpoint that impedes the PTT efficient while combination of gene knockdown of IDO in TME enhances anti-tumor efficacy of PTT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".