“Combi‐targeting” mitozolomide: Conferring novel signaling inhibitory properties to an abandoned DNA alkylating agent in the treatment of advanced prostate cancer
Bibliographic record
Abstract
PURPOSE: At the preclinical stage, mitozolomide (MTZ) showed exciting preclinical activity but failed later in clinical trial due to toxic side effects. We surmised that by targeting MTZ to epidermal growth factor receptor (EGFR), we may not only alter its toxicity profile, but also enhance its potency in EGFR-overexpressing tumors. To test this hypothesis, we designed JDF12, studied its mechanism of action in human prostate cancer (PCa) cells and determined its potency in vivo. EXPERIMENTAL DESIGN: To analyze its mixed EGFR-DNA targeting potential, we performed an enzyme linked immunosorbent assay (ELISA) and western blotting analysis of EGFR phosphorylation in cells stimulated with EGF. DNA damage was analyzed using the comet assay, and apoptosis quantitated by annexin V binding assay. Growth inhibition in vitro was determined by the sulforhodamine B (SRB) assay and in vivo efficacy analyzed in male CD-1 nude mice. RESULTS: The results showed that: Under physiological conditions, JDF12 was hydrolyzed to JDF04R and both agents were capable of inhibiting isolated EGFR tyrosine kinase (TK) and EGFR phosphorylation in EGF-stimulated cells. JDF12 significantly damaged DNA, induced apoptosis in DU145 cells and was up to 2-10-fold more potent than equieffective combinations of MTZ and JDF04R or Iressa in a panel that also included LNCaP and its EGFR and ErbB2 transfectants. In vivo, it induced significant antitumor activity in a DU145 xenograft model. CONCLUSIONS: The results suggest that the superior cytotoxicity of JDF12 when compared with MTZ and JDF04R may be imputed to its potent EGFR-DNA targeting properties and confirm the ability of this novel strategy to confer EGFR targeting properties to a classical alkylator.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".