RasGRPs Are Targets of the Anti-Cancer Agent Ingenol-3-Angelate
Bibliographic record
Abstract
Ingenol-3-angelate (I3A) is a non-tumor promoting phorbol ester-like compound identified in the sap of Euphoria peplus. Similar to tumor promoting phorbol esters, I3A is a diacylglycerol (DAG) analogue that binds with high affinity to the C1 domains of PKCs, recruits PKCs to cellular membranes and promotes enzyme activation. Numerous anti-cancer activities have been attributed to I3A and ascribed to I3A's effects on PKCs. We show here that I3A also binds to and activates members of the RasGRP family of Ras activators leading to robust elevation of Ras-GTP and engagement of the Raf-Mek-Erk kinase cascade. In response to I3A, recombinant proteins consisting of GFP fused separately to full-length RasGRP1 and RasGRP3 were rapidly recruited to cell membranes, consistent with direct binding of the compound to RasGRP's C1 domain. In the case of RasGRP3, IA3 treatment led to positive regulatory phosphorylation on T133 and activation of the candidate regulatory kinase PKCδ. I3A treatment of select B non-Hodgkin's lymphoma cell lines resulted in quantitative and qualitative changes in Bcl-2 family member proteins and induction of apoptosis, as previously demonstrated with the DAG analogue bryostatin 1 and its synthetic analogue pico. Our results offer further insights into the anticancer properties of I3A, support the idea that RasGRPs represent potential cancer therapeutic targets along with PKC, and expand the known range of ligands for RasGRP regulation.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".