Hypoxia enhances cancer cell invasion through relocalization of the proprotein convertase furin from the <i>trans</i>‐golgi network to the cell surface
Bibliographic record
Abstract
Tumor hypoxia is strongly associated with malignant progression such as increased cell invasion and metastasis. Although the invasion-related genes affected by hypoxia have been well described, the contribution of post-transcriptional mechanisms such as protein trafficking and proprotein processing associated with the hypoxic response remains poorly understood. The proprotein convertase furin, the major processing enzyme of the secretory pathway, resides in the trans-Golgi network and most studies support a model where endogenous substrates are processed by furin within this compartment. Here, we report that hypoxia triggered an unexpected relocalization of furin from the trans-Golgi network to endosomomal compartments and the cell surface in cancer cells. Exposing these cells back to normoxic conditions reversed furin redistribution, suggesting that the tumor microenvironment modulates furin trafficking in a highly regulated manner. Assessment of the mechanisms involved revealed that both Rab4GTPase-dependent recycling and interaction of furin with the cytoskeletal anchoring protein, filamin-A, are essential for the cell surface relocalization of furin. Interference with the association of furin with filamin-A, prevented cell surface relocalization of furin and abolished the ability of cancer cells to migrate in response to hypoxia. Our observations support the notion that hypoxia promotes the formation of a peripheral processing compartment where furin translocates for enhanced processing of proproteins involved in tumorigenesis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".