Antitumor Efficacy of <i>bcl-2</i> and <i>c-myc</i> Antisense Oligonucleotides in Combination with Cisplatin in Human Melanoma Xenografts: Relevance of the Administration Sequence
Bibliographic record
Abstract
PURPOSE: bcl-2 and c-myc oncogenes are frequently overexpressed in different human tumors, including melanoma. Here, we evaluate the combined efficacy of two antisense oligonucleotides targeting bcl-2 mRNA (ODN bcl-2) and c-myc mRNA (ODN c-myc) in combination with cis-diammine dichloroplatinum (cisplatin, DDP) on three human melanoma lines (LM, NG, and M20). EXPERIMENTAL DESIGN: Two different sequences were designed to treat tumor-bearing mice: in the first one, ODN bcl-2 at a dose of 0.2 mg/day x4, followed by DDP given i.p. at a dose of 3.3 mg/kg/day x3 and ODN c-myc i.v. at 0.5 mg/day x7, whereas the other sequence consisted of ODN c-myc given as first agent followed by DDP and ODN bcl-2 at the same doses. Mice received three complete cycles of treatment in 1-week intervals. RESULTS: The treatment sequence with ODN bcl-2/DDP/ODN c-myc combination completely inhibited growth in NG tumor and induced a 35-day delay in LM tumor growth. In contrast, the M20 tumor growth was unaffected by the combination. A discrete amount of c-Myc and bcl-2 protein expression in both LM and NG tumors was detected, whereas no detectable levels of the two proteins were observed in M20 tumors. Compared with the other combination, the sequence (ODN bcl-2/DDP/ODN c-myc) produced the most effective results, producing a significant decrease in bcl-2 and c-Myc protein expression, which in turn significantly increased the survival of NG- and LM-bearing mice, with 4 mice out of 11 and 1 out of 7 mice being cured, respectively. Finally, this combination increased the apoptotic rate and produced an antiangiogenetic effect. CONCLUSIONS: These results show that an antisense approach to the treatment of melanoma xenografts overexpressing either bcl-2 or c-myc oncogenes represents a successful strategy to improve the response to chemotherapy in melanoma, with particular attention to the treatment sequence.
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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 | 0.001 |
| 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".