Influence of glioma tumour microenvironment on the transport of ANG1005 via low-density lipoprotein receptor-related protein 1
Bibliographic record
Abstract
BACKGROUND: ANG1005 consists of three molecules of paclitaxel conjugated via ester bonds to the 19-amino-acid peptide Angiopep-2. The new chemical agent has been shown to cross the blood-brain barrier (BBB) by receptor-mediated transcytosis via low-density lipoprotein receptor-related protein 1 (LRP1). The experiments here examined the role of LRP1 in the subsequent endocytosis of drug into cancer cells. METHODS: Localisation of ANG1005 and Angiopep-2 was examined by immunohistochemistry and in-vivo near-infrared fluorescence imaging in mice carrying orthotopic glioma tumours. Transport of ANG1005 and Angiopep-2 was examined in U87 glioblastoma cell lines. RESULTS: Systemically administered ANG1005 and Cy5.5Angiopep-2 localised to orthotopic glioma tumours in mice. The glioma transplants correlated with high expression levels of LRP1. Decreasing LRP1 activity, by RNA silencing or LRP1 competitors, decreased uptake of ANG1005 and Angiopep-2 into U87 glioblastoma cells. Conversely, LRP1 expression and endocytosis rates for ANG1005 and Angiopep-2 increased in U87 cells under conditions that mimicked the microenvironment near aggressive tumours, that is, hypoxic and acidic conditions. CONCLUSION: ANG1005 might be a particularly effective chemotherapeutic agent for the wide array of known LRP1-expressing brain and non-brain cancers, in particular those with an aggressive phenotype.
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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".