Targeted siRNA Silencing of Indoleamine 2, 3-Dioxygenase in Antigen-presenting Cells Using Mannose-conjugated Liposomes
Bibliographic record
Abstract
Indoleamine 2, 3-dioxygenase (IDO) expression in dendritic cells (DCs) leads to the inhibition of T-cell activation, induction of T-cell apoptosis, and promotion of T-cell differentiation into regulatory T cells. All of these could promote tumor escapement of the host's immune surveillance system. We hypothesized that DC-targeted gene silencing of IDO would enhance antitumor immunity and thus restrain tumor growth. Mannose receptors are highly expressed in antigen-presenting cells (APCs) including DCs. In this study, we developed a novel APC-targeted small interfering RNA delivery system using mannosed liposomes (Man-lipo) with encapsulated IDO small interfering RNA (Man-lipo-siIDO), which preferentially knocked down IDO expression in draining lymph node and spleen of melanoma-bearing mice. Mice treated with Man-lipo-siIDO displayed a delayed time of onset of implanted murine melanomas, increased survival time, reduced tumor size, and increased reactivity of T cells from spleen and lymph nodes against melanoma antigens. The enhanced antitumor immunity may be linked to inhibition of apoptosis in CD8 and CD4 T cells as well as Treg cells in spleen and lymph nodes. This study is the first to demonstrate that Man-lipo-siIDO can preferentially targets APCs and efficiently silence IDO expression in vitro and in vivo; events expected to enhance antitumor immune reactions against melanoma xenografts. This study supports the hypothesis that Man-lipo-siIDO may possess the potential for development as an immune-targeting therapeutic anticancer agent.
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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) | 0.000 | 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 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".