Reprogramming of Isocitrate Dehydrogenases Expression and Activity by the Androgen Receptor in Prostate Cancer
Bibliographic record
Abstract
Abstract Mutations of the isocitrate dehydrogenase genes IDH1 and IDH2, key enzymes involved in citrate metabolism, are important oncogenic events in several cancer types, including in 1%–3% of all prostate cancer cases. However, if IDH1 and other IDH isoforms are associated with prostate cancer progression, as well as the regulatory factors controlling their expression and activity, remain mostly unknown. Using publicly available datasets, we showed that prostate cancer harbors the highest IDH1 expression across the human cancer spectrum and that IDH1 expression is altered during prostate cancer progression. We showed that the androgen receptor (AR), a key oncogene in prostate cancer, controls multiple IDH isoforms in both in vitro and in vivo models, predominantly positively regulating IDH1. Chromatin immunoprecipitation experiments confirmed the recruitment of AR at several regulatory regions of IDH1 and enzymatic assays demonstrated that AR significantly induces IDH activity. Genetic blockade of IDH1 significantly impaired prostate cancer cell proliferation, consistent with IDH1 having a key function in these cancer cells. Importantly, knockdown of IDH1 blocked the AR-mediated induction in IDH activity, indicating that AR promotes a mitochondrial to cytoplasmic reprogramming of IDH activity. Overall, our study demonstrates that IDH1 expression is associated with prostate cancer progression, that AR signaling integrates one of the first transcriptional mechanisms shown to regulate IDH1, and that AR reprograms prostate cancer cell metabolism by selectively inducing extra-mitochondrial IDH activity. Implications: The discovery that AR reprograms IDH activity highlights a novel metabolic reprogramming necessary for prostate cancer growth and suggests targeting IDH activity as a new therapeutic approach for prostate cancer treatment.
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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 | 0.001 | 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".