Endosomal sorting and c-Cbl targeting of paxillin to autophagosomes regulate cell-matrix adhesion turnover in human breast cancer cells
Bibliographic record
Abstract
// Chia-Hao Chang 1, 2 , Krikor Bijian 1, 2 , Dinghong Qiu 1, 2 , Jie Su 1, 2 , Amine Saad 1, 2 , Michael S. Dahabieh 1, 2 , Wilson H. Miller Jr. 1, 2 , Moulay A. Alaoui-Jamali 1, 2 1 Department of Medicine, Lady Davis Institute for Medical Research and Segal Cancer Center, SMBD Jewish General Hospital, Faculty of Medicine, McGill University, Montreal, Canada 2 Department of Oncology, Lady Davis Institute for Medical Research and Segal Cancer Center, SMBD Jewish General Hospital, Faculty of Medicine, McGill University, Montreal, Canada Correspondence to: Moulay A. Alaoui-Jamali, email: moulay.alaoui-jamali@mcgill.ca Keywords: paxillin, focal adhesion dynamics, Rab7-GTPase, c-Cbl, autophagy Received: January 12, 2017 Accepted: March 01, 2017 Published: March 10, 2017 ABSTRACT Post-translational mechanisms regulating cell-matrix adhesion turnover during cell locomotion are not fully elucidated. In this study, we uncovered an essential role of Y118 site-specific tyrosine phosphorylation of paxillin, an adapter protein of focal adhesion complexes, in paxillin recruitment to autophagosomes to trigger turnover of peripheral focal adhesions in human breast cancer cells. We demonstrate that the Rab-7 GTPase is a key upstream regulator of late endosomal sorting of tyrosine118-phosphorylated paxillin, which is subsequently recruited to autophagosomes via the cargo receptor c-Cbl. Essentially, this recruitment involves a direct and selective interaction between Y118-phospho-paxillin, c-Cbl, and LC3 and is independent from c-Cbl E3 ubiquitin ligase activity. Interference with the Rab7-paxillin-autophagy regulatory network using genetic and pharmacological approaches greatly impacted focal adhesion stability, cell locomotion and progression to metastasis using a panel of human breast cancer cells. Together, these results provide novel insights into the requirement of phospho-site specific post-translational mechanism of paxillin for autophagy targeting to regulate cell-matrix adhesion turnover and cell locomotion in breast cancer cells.
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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) | 0.002 | 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".