Immunohistochemical examination of the mTORC1 pathway in high grade prostatic intraepithelial neoplasia (HGPIN) and prostatic adenocarcinomas (PCa): A tissue microarray study (TMA)
Bibliographic record
Abstract
BACKGROUND: The mammalian target of rapamycin (mTOR) is a serine/threonine protein kinase and a key regulator of protein synthesis and growth and is upregulated in many cancers. mTOR is activated by AKT phosphorylation (p-mTOR). p-mTOR associates with regulatory-associated protein of TOR (RAPTOR), forming the mTORC1 complex. mTORC1 promotes the activation of p70 ribosomal protein s6 kinase 1 (p70(S6K1)) and ribosomal protein s6 (RPS6). Upregulation of this pathway can lead to an aberrant increase in cell growth and metabolism characteristic of malignant transformation. METHODS: This study presents the immunohistochemical (IHC) expression of the mTORC1 pathway in prostate neoplasia. The expression of p-mTOR and RAPTOR and p-p70(S6K1) and p-RPS6 were examined in HGPIN and PCa using tissue microarrays (TMA). Since each case in our TMAs was represented by three tissue cores, we quantified the IHC intratumoral heterogeneity of mTOR expression. This extensive analysis is the first detailed assessment documenting the IHC heterogeneity of mTOR expression in HGPIN and prostate cancer and represents the first IHC description of the mTORC1 pathway in HGPIN and PCa. RESULTS: A Cochran-Armitage analysis demonstrated decreasing p-mTOR activity progressing from PIN through GL6 and GL7 to HG PCa. There was considerable intratumoral IHC heterogeneity within an individual patient. However, a statistically significant correlation was observed between p-mTOR, p-p70(S6K1), and p-RPS6 in each representative core. CONCLUSION: mTOR inhibitors may be an effective treatment for HGPIN and PCa. The extent of mTOR expression in an individual patient would determine the effective use of mTOR inhibitors as a potential therapeutic strategy.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".