Therapeutic integration of c‐myc and bcl‐2 antisense molecules with docetaxel in a preclinical model of hormone‐refractory prostate cancer
Bibliographic record
Abstract
BACKGROUND: The response of hormone-refractory prostate cancer (HRPC) to chemotherapy remains modest, necessitating the search for new forms of treatment to improve the prognosis. Since an increased expression of oncogenes, including c-myc and bcl-2, accompanies the transition to HRPC, we evaluated whether the concomitant downregulation of these oncogenes by antisense strategy sensitized HRPC to chemotherapy. METHODS: PC-3 prostate cancer cells were exposed in vitro to c-myc (INX-6295) and bcl-2 (G3139) antisense oligodeoxynucleotides (ODNs) and docetaxel given alone or in combination. Therapeutic efficacy of the different treatments was also evaluated in xenografts. RESULTS: We show that the triple combination of drugs given in the sequence G3139/docetaxel/INX-6295 was the most active in reducing the survival of PC-3. Likewise, the combination triggered apoptosis in more than 80% of cells. A marked tumor weight inhibition was observed in PC-3 xenografts after G3139/docetaxel/INX-6295 treatment, with a complete tumor regression being noted in half the mice. A 111% overall increase in life survival and a complete cure in two out of eight mice was also reported. This treatment remained effective even when started at a very late stage of tumor growth producing about 80% tumor weight inhibition (TWI), with tumor regression being maintained for 1 month. Finally, the antitumor effect resulted in a significant increase (70%) in mice survival. CONCLUSIONS: These data indicate that the combined targeting of genes involved in uncontrolled proliferation and evasion of apoptosis renders HRPC responsive to chemotherapy making this treatment a promising antineoplastic strategy.
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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 | 0.000 | 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) | 0.001 | 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".