Co‐targeting driver pathways in prostate cancer: two birds with one stone
Bibliographic record
Abstract
Abstract Co‐targeting strategies strive to improve cancer outcomes by combining therapies under contextualized genetic and environmental conditions that selectively target exploitable alterations in tumor cells. Adaptive survival pathways triggered by inhibition of driver genes in the androgen receptor (AR) or PI3K/AKT pathways are of great interest, since they are among the most frequently altered in castrate‐resistant prostate cancer (CRPC). Unfortunately, negative feedback loops exist between the AR and PI3K/AKT pathways such that targeting AR leads to activation of PI3K/AKT signaling, while PI3K/AKT pathway inhibition leads to increased AR transcriptional activity. Hence, targeting both pathways provides an opportunity for conditional lethality and a high therapeutic index. In this issue of EMBO Molecular Medicine , Yan et al (2018) present an elegant study showing that histone deacetylase 3 (HDAC3) acts as a common upstream activator of both AR and AKT signaling pathways, and use HDAC3 inhibitors as a monotherapy to co‐target two major pathways driving CRPC growth.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.014 | 0.023 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".