PTP1B Deficiency Enables the Ability of a High-Fat Diet to Drive the Invasive Character of PTEN-Deficient Prostate Cancers
Bibliographic record
Abstract
Diet affects the risk and progression of prostate cancer, but the interplay between diet and genetic alterations in this disease is not understood. Here we present genetic evidence in the mouse showing that prostate cancer progression driven by loss of the tumor suppressor Pten is mainly unresponsive to a high-fat diet (HFD), but that coordinate loss of the protein tyrosine phosphatase Ptpn1 (encoding PTP1B) enables a highly invasive disease. Prostate cancer in Pten(-/-)Ptpn1(-/-) mice was characterized by increased cell proliferation and Akt activation, interpreted to reflect a heightened sensitivity to IGF-1 stimulation upon HFD feeding. Prostate-specific overexpression of PTP1B was not sufficient to initiate prostate cancer, arguing that it acted as a diet-dependent modifier of prostate cancer development in Pten(-/-) mice. Our findings offer a preclinical rationale to investigate the anticancer effects of PTP1B inhibitors currently being studied clinically for diabetes treatment as a new modality for management of prostate cancer. Cancer Res; 76(11); 3130-5. ©2016 AACR.
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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 | 0.001 | 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) | 0.003 | 0.001 |
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".