EXTH-103. A prototype mRNA LNP neoantigen vaccine remodels the tumour microenvironment of a syngeneic model of glioblastoma
Bibliographic record
Abstract
Abstract Despite significant advances in understanding the biology of glioblastoma (GBM), the disease remains fatal within 15 months of diagnosis. Emerging immunotherapies including vaccines targeting somatic alterations hold promise but need to address challenges including the highly immunosuppressive GBM tumour microenvironment which causes lymphocyte dysfunction. Here, we evaluated whether an EGFRvIII-targeting mRNA LNP vaccine could favorably reprogram the tumour microenvironment of a syngeneic EGFRvIII-driven GBM mouse model (EGFRvIII-OE/CDKN2A-KO/PTEN-KO) which recapitulates histopathological features of GBM including necrosis, diffuse infiltration, and microvascular proliferation. This syngeneic model is sensitive to but not cured by temozolomide and is resistant to immune checkpoint blockade (anti-PD-1 and anti-CTLA4) therapy, demonstrating responses similar to the human disease. After orthotopic implantation of tumour cells and intramuscular vaccinations (10ug) on days 20, 23, 26, 29, and 32 post-tumour cell implant, tumour was harvested at day 35 for analysis. Spectral flow analyses showed that vaccination remodels the tumour’s CD45 compartment, decreasing myeloid infiltration (*p=0.0365) and increasing T cell infiltration (p=0.1203). Furthermore, activated/antigen-experienced CD8 T cells are more frequent in vaccinated tumours compared to controls. We analyzed cytokines and chemokines in the tumour interstitial fluid of tumours and found an increased in inflammatory cytokines and chemokines related to lymphocyte recruitment and Th1 phenotype polarization and a decrease in immunosuppressive cytokines in vaccinated tumours compared to control. Based on the vaccine-induced shift in the immune phenotype of tumours, we hypothesize the vaccine’s effect was CD8 T cell mediated. Currently, our work is focused on understanding the immune cell subsets responsible for vaccine mediated tumour clearance. Our proof-of-principle work demonstrates that this mRNA LNP neoantigen vaccine powerfully re-shapes the tumour microenvironment towards anti-tumour immunity.
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 | 0.001 |
| 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".