Synthetic Glycosylated Ether Glycerolipids as Anticancer Agents
Bibliographic record
Abstract
Glycosylated antitumor ether lipids (GAELs) are a class of synthetic antitumor ether lipids (AELs) with a sugar moiety in place of the phosphocholine found in the prototypical AEL, edelfosine. This chapter reviews the development of GAELs as antitumor agents. Studies on structure–activity relationships, mechanism of induction of cell death, metabolism, selectivity against cancer cells, toxicity, hemolysis and thrombogenic effects are discussed. The requirements for significant cytotoxic activity include a glycerol moiety, a cationic sugar other than mannose and an O- or C-glycosidic bond with either α- or β-configuration. Compounds with S- and N-glycosidic linkages are not very active. The most active GAEL to date, 1-O-hexadecyl-2-O-methyl-3-O-(2′-amino-2′-deoxy-α-d-galactopyranosyl)-sn-glycerol, displays greater in vitro activity than edelfosine, the AEL “gold standard”. The unique properties of GAELs as antitumor agents include their apoptotic-independent mechanism of inducing cell death and the ability to kill cancer stem cells. These characteristics of GAELs offer the potential for their development into chemotherapeutic agents to prevent the recurrence of tumors as well as for treatment against drug-resistant cancers.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".