The Type III Transforming Growth Factor-β Receptor as a Novel Tumor Suppressor Gene in Prostate Cancer
Bibliographic record
Abstract
The transforming growth factor-beta (TGF-beta) signaling pathway has an important role in regulating normal prostate epithelium, inhibiting proliferation, differentiation, and both androgen deprivation-induced and androgen-independent apoptosis. During prostate cancer formation, most prostate cancer cells become resistant to these homeostatic effects of TGF-beta. Although the loss of expression of either the type I (TbetaRI) or type II (TbetaRII) TGF-beta receptor has been documented in approximately 30% of prostate cancers, most prostate cancers become TGF-beta resistant without mutation or deletion of TbetaRI, TbetaRII, or Smads2, 3, and 4, and thus, the mechanism of resistance remains to be defined. Here, we show that type III TGF-beta receptor (TbetaRIII or betaglycan) expression is decreased or lost in the majority of human prostate cancers as compared with benign prostate tissue at both the mRNA and protein level. Loss of TbetaRIII expression correlates with advancing tumor stage and a higher probability of prostate-specific antigen (PSA) recurrence, suggesting a role in prostate cancer progression. The loss of TbetaRIII expression is mediated by the loss of heterozygosity at the TGFBR3 genomic locus and epigenetic regulation of the TbetaRIII promoter. Functionally, restoring TbetaRIII expression in prostate cancer cells potently decreases cell motility and cell invasion through Matrigel in vitro and prostate tumorigenicity in vivo. Taken together, these studies define the loss of TbetaRIII expression as a common event in human prostate cancer and suggest that this loss is important for prostate cancer progression through effects on cell motility, invasiveness, and tumorigenicity.
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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 | 0.000 | 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 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".