Faculty Opinions recommendation of Identification of the PTEN-ARID4B-PI3K pathway reveals the dependency on ARID4B by PTEN-deficient prostate cancer.
Bibliographic record
Abstract
PTEN is frequently mutated in prostate cancer. The tumor suppressor function of PTEN is attributed to its lipid phosphatase activity that counters PI3K action. Here, we report a PTEN-ARID4B-PI3K axis in which PTEN inhibits expression of ARID4B, while ARID4B is a transcriptional activator of the PI3K subunit genes PIK3CA and PIK3R2 that are crucial for activation of the PI3K/AKT pathway. Reciprocal binding of ARID4B and histone H1 to the PIK3CA and PIK3R2 promoters modulates chromatin condensation, suggesting a mechanism by which ARID4B activates these promoters. Functional analyses reveals that ARID4B is required for prostate tumorigenesis when PTEN is deficient. The biological significance is further substantiated by the existence of a PTEN/ARID4B/PIK3CA three-gene signature that improves the predictive power for prostate cancer recurrence in patients. In summary, we identify ARID4B as a master regulator in the PTEN-PI3K pathway, thus providing a potential therapeutic target for prostate cancer carrying PTEN mutations. PMID: 31551414 Funding information This work was supported by: NCI NIH HHS, United States Grant ID: R21 CA187857 NCI NIH HHS, United States Grant ID: R01 CA188471
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.095 | 0.057 |
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".