Novel targets and approaches in advanced prostate cancer
Bibliographic record
Abstract
PURPOSE OF REVIEW: The development of therapeutic resistance is the underlying cause for most cancer deaths. By understanding the molecular basis of resistance to androgen withdrawal and chemotherapy in prostate cancer, the rational design of targeted therapeutics is possible. We review new treatment options for men with advanced prostate cancer. RECENT FINDINGS: Although the taxanes currently represent the most active chemotherapeutic agents and standard of care for first-line treatment of metastatic hormone-refractory prostate cancer, most patients eventually progress because of intrinsic or acquired drug resistance. In recent years, increased knowledge of cancer progression and therapeutic resistance has identified many gene targets that regulate apoptosis, proliferation, and cell signalling. To date, numerous novel compounds have entered clinical trials as either single agents or in combination with cytotoxic chemotherapy. SUMMARY: Even though hormone-refractory prostate cancer is still incurable, it is not untreatable. As cancer cells are proficient at adapting to therapeutic stressors, a combination regimen with drugs that target crucial cellular networks like the apoptotic rheostat may be more promising than treatment with highly selective single-target agents. Recent findings are very hopeful, but challenges remain to demonstrate effective antitumour activity in phase III trials with survival as the principal endpoint.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".