Quantitative Proteomics Reveals That Enzymes of the Ketogenic Pathway Are Associated with Prostate Cancer Progression
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.
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 | 0.001 | 0.001 |
| 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".