Quantitative Proteomics Reveals That Enzymes of the Ketogenic Pathway Are Associated with Prostate Cancer Progression
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Bibliographic record
Abstract
Prostate cancer is the most common malignancy and the second leading cause of cancer-related deaths in men. One common treatment is androgen-deprivation therapy, which reduces symptoms in most patients. However, over time, patients develop tumors that are androgen-independent and ultimately fatal. The mechanisms that cause this transition remain largely unknown, and as a result, there are no effective treatments against androgen-independent prostate cancer. As a model platform, we used the LNCaP cell line and its androgen-independent derivative, LNCaP-SF. Utilizing stable isotope labeling with amino acids in cell culture coupled to mass spectrometry, we assessed the differential global protein expression of the two cell lines. Our proteomic analysis resulted in the quantification of 3355 proteins. Bioinformatic prioritization resulted in 42 up-regulated and 46 down-regulated proteins in LNCaP-SF cells relative to LNCaP cells. Our top candidate, HMGCS2, an enzyme involved in ketogenesis, was found to be 9-fold elevated in LNCaP-SF cells, based on peptide ratios. After analyzing the remaining enzymes of this pathway (ACAT1, BDH1, HMGCL, and OXCT1), we observed increased expression of these proteins in the LNCaP-SF cells, which was further verified using Western blotting. To determine whether these enzymes were up-regulated in clinical samples, we performed quantitative PCR and immunohistochemistry on human prostate cancer tissues, from which we observed significantly increased transcript and protein levels in high-grade cancer (Gleason grade ≥ 8). In addition, we observed significant elevation of these enzymes in the LuCaP 96AI castration-resistant xenograft. Further assessment of ACAT1 on human castration-resistant metastatic prostate cancer tissues revealed substantially elevated expression of ACAT1 in these specimens. Taken together, our results indicate that enzymes of the ketogenic pathway are up-regulated in high-grade prostate cancer and could serve as potential tissue biomarkers for the diagnosis or prognosis of high-grade disease.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it