Design of a novel multiepitope vaccine against glioblastoma by in silico approaches
Bibliographic record
Abstract
Glioblastoma (GBM) is the most common malignant primary brain tumor, with a median survival rate of less than two years. Currently, there is no cure for GBM, underscoring the urgent need for innovative treatment approaches. Vaccine design emerges as a crucial strategy, offering a safe and effective means for both preventive and therapeutic interventions against GBM. In this study, we targeted four GBM-associated mutated surface proteins-urokinase plasminogen activator surface receptor (PLAUR), integrin beta-3 (ITGB3), and the B-41 alpha chain (HLA-B) and A-24 alpha chain (HLA-A) of the HLA class I histocompatibility antigens-to design a peptide-based vaccine. The vaccine construct includes cytotoxic T lymphocyte (CTL) and T helper cell (Th cell) epitopes, and was meticulously evaluated for antigenicity, allergenicity, and toxicity. The results indicate that the vaccine is antigenic and non-allergenic, making it a promising candidate. Additionally, the physicochemical properties of the vaccine suggest stability and suitability for further development. Immune simulation studies predict a strong immune response upon vaccine administration. Our vaccine shows promise as a potential tool in the fight against GBM, offering new hope for patients facing this devastating disease.
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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 | 0.001 | 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 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".