HOXB13 Induces Growth Suppression of Prostate Cancer Cells as a Repressor of Hormone-Activated Androgen Receptor Signaling
Bibliographic record
Abstract
Androgen receptor (AR) signals play a decisive role in regulating the growth and differentiation of both normal and cancerous prostate cells by triggering the regulation of target genes, in a process in which AR cofactors have critical functions. Because of the highly prostate-specific expression pattern of HOXB13, we studied the role of this homeodomain protein in prostate cells. Expression of HOXB13 was limited to AR-expressing prostate cells. Reporter transcription assay demonstrated that HOXB13 significantly suppressed hormone-mediated AR activity in a dose-responsive manner, and suppression was specific to AR with which HOXB13 physically interacts. Overexpression of HOXB13 further down-regulated the androgen-stimulated expression of prostate-specific antigen, and suppression of endogenous HOXB13 stimulated transactivation of AR. Functionally, HOXB13 suppressed growth of LNCaP prostate cancer cells, which could be counteracted by additional hormone-activated AR. On the other hand, the growth-suppressive function of HOXB13 in AR-negative CV-1 cells was not affected by AR. These results suggest that HOXB13 functions as an AR repressor to modulate the complex AR signaling and subsequent growth regulation of prostate cancer cells. In addition to the loss of HOXB13 expression, maintaining AR may be an important step for prostate cancer cells to tolerate the suppressor function of HOXB13. Altogether, our data present a novel mechanism for the HOXB13-mediated repression of AR signaling, which can be interpreted to a growth-suppressive event.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".