Recruitment of Immune Effector Cells against Glioblastoma-Multiforme by a MHC-Chlorotoxin Chimeric Protein
Bibliographic record
Abstract
Glioblastoma Multiforme is the most common malignant primary brain tumor, having a mean overall survival <2 years. The lack of an efficient immune response against the tumor have been attributed to its immunosuppressive capabilities and an immunosuppressing local environment. Aim: We set out to design a chimeric molecule that recognizes and binds tissue inducible metalloproteinase known to be induced in GBM cells (MMP-2) on one end. Its other end, the effector domain, mobilizes and recruits cytotoxic T-cells to mount an effective anti-tumor reaction. Methods: The targeting moiety is the small 36-amino acids Chlorotoxin, derived from the venom of the Israeli Yellow scorpion. The effector end is a single chain HLA-A2 (Human leukocyte antigen subtype A2) covalently bound to phosphoprotein-65 derived from the cytomegalovirus, to which most of the human population has developed a specific immune response. Results: The molecular construct was cloned and expressed in E.coli. The protein product was isolated, purified, and then folded in vitro. Various activity assays employed demonstrated retained activity of each domain, including flow-cytometry, intracellular staining, fluorescence immunohistochemistry, radiolabeled toxicity assays etc. Initial in-vivo studies show great promise. Conclusions: We present a proof of concept study for a new immunotherapy approach to battle GBM. A molecular construct which contains a non-antibody compact and highly specific targeting domain, combined with the ability to recruit anti-CMV T-cell lymphocyte population. The recruitment of potent memory CTL’s to the tumor’s milieu may prove resistant to the previously described local immunosuppressive environment brought about by the tumor.
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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) | 0.001 | 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".