The Retinoblastoma Tumor Suppressor Protein (pRb)/E2 Promoter Binding Factor 1 (E2F1) Pathway as a Novel Mediator of TGFβ-induced Autophagy
Bibliographic record
Abstract
TGFβ is a multifunctional cytokine that regulates cell proliferation, cell immortalization, and cell death, acting as a key homeostatic mediator in various cell types and tissues. Autophagy is a programmed mechanism that plays a pivotal role in controlling cell fate and, consequently, many physiological and pathological processes, including carcinogenesis. Although autophagy is often considered a pro-survival mechanism that renders cells viable in stressful conditions and thus might promote tumor growth, emerging evidence suggests that autophagy is also a tumor suppressor pathway. The relationship between TGFβ signaling and autophagy is context-dependent and remains unclear. TGFβ-mediated activation of autophagy has recently been suggested to contribute to the growth inhibitory effect of TGFβ in hepatocarcinoma cells. In the present study, we define a novel process of TGFβ-mediated autophagy in cancer cell lines of various origins. We found that autophagosome initiation and maturation by TGFβ is dependent on the retinoblastoma tumor suppressor protein/E2 promoter binding factor (pRb/E2F1) pathway, which we have previously established as a critical signaling axis leading to various TGFβ tumor suppressive effects. We further determined that TGFβ induces pRb/E2F1-dependent transcriptional activation of several autophagy-related genes. Together, our findings reveal that TGFβ induces autophagy through the pRb/E2F1 pathway and transcriptional activation of autophagy-related genes and further highlight the central relevance of the pRb/E2F1 pathway downstream of TGFβ signaling in tumor suppression.
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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) | 0.001 | 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".