Profilin 1 Potentiates Apoptosis Induced by Staurosporine in Cancer Cells
Bibliographic record
Abstract
The correlation between the loss of Profilin 1 (Pfn1) with tumor progression indicated that Pfn1 is a tumor suppressor in human carcinoma. The molecular mechanisms underlying Pfn1 tumor suppression has yet to be elucidated. In this study, we showed that Pfn1 overexpression sensitizes cancer cells to apoptosis through the typical intrinsic apoptotic pathway. Mechanistically, the increased Pfn1 expression mediated the upregulation of p53R273H, one of the most common tumor-associated hotspot mutations of p53, with transactivation deletion in tumorigenesis and increased localization of p53R273H in cytoplasm. Further studies showed that mutant p53R273H was involved in apoptosis induced by Staurosporine (STS) via transcription-independent mitochondrial functions. We observed (i) the increased cytosolic localization of p53R273H, (ii) the activation of phosphorylation at Ser15, (iii) its mitochondrial localization; Pfn1 acted as a positive regulator of these processes. We also found that Pfn1 interacted with p53R273H and thus facilitated its exertion over the transcription-independent activity in the cytoplasm during drug action. Our results define a new function and mechanism of Pfn1 demonstrating that the combined effect with apoptotic agents led to a synergistic increase in apoptosis. In addition, p53R273H abrogating DNA binding was found to play a major role in the Pfn1- sensitized apoptosis through a transactivation-independent and cytosolic activity.
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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".