Hierarchical Phosphorylation of HOXB13 by mTOR Dictates Its Activity and Oncogenic Function in Prostate Cancer
Bibliographic record
Abstract
Dysregulation of mTOR signaling plays a critical role in promoting prostate cancer growth. HOXB13, a homeodomain transcription factor, is known to influence the androgen response and prostate cancer development. Recently, HOXB13 was found to complex with mTOR on chromatin. However, the functional crosstalk between HOXB13 and mTOR remains elusive. We now report that mTOR directly interacts with and hierarchically phosphorylates HOXB13 at threonine 8 and 41 then serine 31 to promote its interaction with the E3 ligase SKP2 while enhancing its oncogenic properties. Expression of HOXB13 harboring phosphomimetic mutations at the mTOR-targeted sites stimulates prostate cancer cellular growth both in vitro and in murine xenografts. Transcriptional profiling studies revealed a phospho-HOXB13-dependent gene signature capable of robustly discriminating between normal prostate tissues, primary and metastatic prostate cancer samples. This work uncovers a previously unanticipated molecular cascade by which mTOR directly phosphorylates HOXB13 to dictate a specific gene program with oncogenic implications in prostate cancer. IMPLICATIONS: Control of HOXB13 transcriptional activity via its direct phosphorylation by the mTOR kinase is a potential therapeutic avenue for the management of advanced prostate cancer.
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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) | 0.000 | 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 | 0.000 |
| 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".