Semaphorin 3C promotes de novo steroidogenesis in prostate cancer cells
Bibliographic record
Abstract
Intratumoral androgen biosynthesis contributes to castration-resistant prostate cancer progression in patients treated with androgen deprivation therapy. The molecular mechanisms by which castration-resistant prostate cancer acquires the capacity for androgen biosynthesis to bypass androgen deprivation therapy are not entirely known. Here, we show that semaphorin 3C, a secreted signaling protein that is highly expressed in castration-resistant prostate cancer, can promote steroidogenesis by altering the expression profile of key steroidogenic enzymes. Semaphorin 3C not only upregulates enzymes required for androgen synthesis from dehydroepiandrosterone or de novo from cholesterol but also simultaneously downregulates enzymes involved in the androgen inactivation pathway. These changes in gene expression correlate with increased production of androgens induced by semaphorin 3C in prostate cancer model cells. Moreover, semaphorin 3C upregulates androgen synthesis in LNCaP cell-derived xenograft tumors, likely contributing to the enhanced in vivo tumor growth rate post castration. Furthermore, semaphorin 3C activates sterol regulatory element-binding protein, a transcription factor that upregulates enzymes involved in the synthesis of cholesterol, a sole precursor for de novo steroidogenesis. The ability of semaphorin 3C to promote intratumoral androgen synthesis may be a key mechanism contributing to the reactivation of the androgen receptor pathway in castration-resistant prostate cancer, conferring continued growth under androgen deprivation therapy. These findings identify semaphorin 3C as a potential therapeutic target for suppressing intratumoral steroidogenesis.
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) | 0.001 | 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".