aPKC alters TGFβ response in NSCLC cells via both Smad-dependent and Smad-independent pathways
Bibliographic record
Abstract
Transforming growth factor b (TGFb) signaling controls many cellular responses including proliferation, epithelial to mesenchymal transition and apoptosis, through the activation of canonical (Smad) as well as non-canonical (e.g., Par6) pathways. Previous studies from our lab have demonstrated that aPKC inhibition regulates TGFb receptor trafficking and signaling. Here, we report that downstream TGFb-dependent transcriptional responses in aPKC-silenced NSCLC cells were reduced compared with those of control cells, despite a temporal extension of Smad2 phosphorylation. We assessed SARA–Smad2–Smad4 association and observed that knockdown of aPKC increased SARA (also known as ZFYVE9) levels and SARA–Smad2 complex formation, increased cytoplasmic retention of Smad2 and reduced Smad2–Smad4 complex formation, which correlated with reduced Smad2 nuclear translocation. Interestingly, we also detected an increase in p38 MAPK phosphorylation and apoptosis in aPKC-silenced cells, which were found to be TRAF6-dependent. Taken together, our results suggest that aPKC isoforms regulate Smad and non-Smad TGFb pathways and that aPKC inhibition sensitizes NSCLC cells to undergo TGFb dependent apoptosis.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".