The Alternative Reading Frame Tumor Suppressor Antagonizes Hypoxia-Induced Cancer Cell Migration via Interaction with the COOH-Terminal Binding Protein Corepressor
Bibliographic record
Abstract
The alternative reading frame (ARF) tumor suppressor exerts both p53-dependent and p53-independent activities critical to the prevention of cancer in mice and humans. Recent evidence from mouse models suggests that when p53 is absent, further loss of ARF can widen the tumor spectrum, and potentiate invasion and metastasis. A major target of the p53-independent activity of ARF is the COOH-terminal binding protein (CtBP) family of metabolically regulated transcriptional corepressors, which are degraded upon acute exposure to the ARF protein. CtBPs are activated under conditions of metabolic stress, such as hypoxia, to repress epithelial and proapoptotic genes, and can mediate hypoxia-induced migration of cancer cells. The possibility that ARF could suppress tumor cell migration as part of its p53-independent activities was thus explored. Small-interfering RNA (siRNA)-mediated knockdown of ARF in human lung carcinoma cells led to increased cell migration, especially during hypoxia, and this effect was blocked by concomitant treatment with CtBP2 siRNA. Introduction of ARF into p53 and ARF-null human colon cancer cells inhibited hypoxia-induced migration. Furthermore, overexpression of CtBP2 in ARF-expressing cells enhanced cell migration, and an ARF mutant defective in CtBP-family binding was impaired in its ability to inhibit cell migration induced by CtBP2. ARF depletion or CtBP2 overexpression was associated with decreased PTEN expression and activation of the phosphatidylinositol 3-kinase pathway, and a phosphatidylinositol 3-kinase inhibitor blocked CtBP2-mediated cell migration. Thus, ARF can suppress cell migration by antagonizing CtBP2 and the phosphatidylinositol 3-kinase pathway, and these data may explain the increased aggressiveness of ARF-null tumors in mouse models.
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 | 0.000 | 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".