cGAS-agonistic spherical nucleic acids reprogram the glioblastoma immune microenvironment and promote antitumor immunity
Bibliographic record
Abstract
The cyclic GMP-AMP synthase-Stimulator of Interferon Genes (cGAS–STING) pathway is an important DNA-sensing mechanism that increases T cell trafficking and activation in tumors and reverses the immunosuppressive phenotype of myeloid cells. Therefore, direct STING targeting using synthetic cyclic dinucleotides (CDNs) is an attractive strategy for treating lymphocyte-depleted and myeloid cell–enriched tumors, such as glioblastoma (GBM). However, inadequate bioavailability and poor cellular accumulation limit the clinical development of CDNs, particularly for noninvasive administration strategies. Spherical nucleic acids (SNAs) have emerged as promising modular constructs for creating therapeutic lead compounds for many diseases, including different forms of cancer. Here, we report the development of cGAS-activating SNAs that consist of gold nanoparticle cores functionalized with a shell of densely packed interferon-stimulatory DNA oligonucleotides (ISD 45 -SNAs). These nanostructures bind to cGAS, the sensor of cytosolic dsDNA upstream of STING, promoting the catalytic production of endogenous CDNs and downstream STING activation more potently than clinically tested CDNs. When administered intranasally or intratumorally to poorly immunogenic syngeneic GBM mouse models, ISD 45 -SNAs inhibit tumor growth more effectively than CDNs and promote long-term animal subject survival through specific cGAS–STING pathway activation. ISD 45 -SNAs induce a proinflammatory immune microenvironment enriched with effector T cells and proinflammatory macrophages. When coadministered with immune checkpoint inhibitors (ICI), they abolish GBM tumor development and induce long-term antiglioma immunity. These studies establish ISD 45 -SNAs as an immune-stimulatory modality for triggering innate and adaptive immune responses and increasing ICI efficacy for GBM treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".