Targeting Glioblastoma Using a Novel Peptide Specific to a Deglycosylated Isoform of Brevican
Bibliographic record
Abstract
Abstract Glioblastoma (GBM) is the most common and deadliest form of brain tumor and remains amongst the most difficult cancers to treat. Brevican (Bcan), a central nervous system (CNS)‐specific extracellular matrix protein, is upregulated in high‐grade glioma cells, including GBM. A Bcan isoform lacking most glycosylation, dg‐Bcan, is found only in GBM tissues. Here, dg‐Bcan is explored as a molecular target for GBM. In this study, a d‐peptide library is screened to identify a small 8‐amino acid dg‐Bcan‐Targeting Peptide (BTP) candidate, called BTP‐7 that binds dg‐Bcan with high affinity and specificity. BTP‐7 is preferentially internalized by dg‐Bcan‐expressing patient‐derived GBM cells. To demonstrate GBM targeting, BTP‐7 is radiolabeled with 18F, a radioisotope of fluorine, and increased radiotracer accumulation is found in intracranial GBM established in mice using positron emission tomography (PET) imaging. dg‐Bcan is an attractive molecular target for GBM, and BTP‐7 represents a promising lead candidate for further development into novel imaging agents and targeted therapeutics.
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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".