Opposite Roles of Furin and PC5A in N-Cadherin Processing
Bibliographic record
Abstract
We recently demonstrated that lack of Furin-processing of the N-cadherin precursor (proNCAD) in highly invasive melanoma and brain tumor cells results in the cell-surface expression of a nonadhesive protein favoring cell migration and invasion in vitro. Quantitative polymerase chain reaction analysis of malignant human brain tumor cells revealed that of all proprotein convertases (PCs) only the levels of Furin and PC5A are modulated, being inversely (Furin) or directly (PC5A) correlated with brain tumor invasive capacity. Intriguingly, the N-terminal sequence following the Furin-activated NCAD site (RQKR↓DW(161), mouse nomenclature) reveals a second putative PC-processing site (RIRSDR↓DK(189)) located in the first extracellular domain. Cleavage at this site would abolish the adhesive functions of NCAD because of the loss of the critical Trp(161). This was confirmed upon analysis of the fate of the endogenous prosegment of proNCAD in human malignant glioma cells expressing high levels of Furin and low levels of PC5A (U343) or high levels of PC5A and negligible Furin levels (U251). Cellular analyses revealed that Furin is the best activating convertase releasing an ~17-kDa prosegment, whereas PC5A is the major inactivating enzyme resulting in the secretion of an ~20-kDa product. Like expression of proNCAD at the cell surface, cleavage of the NCAD molecule at RIRSDR↓DK(189) renders the U251 cancer cells less adhesive to one another and more migratory. Our work modifies the present view on posttranslational processing and surface expression of classic cadherins and clarifies how NCAD possesses a range of adhesive potentials and plays a critical role in tumor progression.
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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".