Expression and subcellular localization of RAGE in melanoma cells
Bibliographic record
Abstract
The receptor for advanced glycation end products (RAGE) is involved in multiple stages of tumor development and malignization. To gain further knowledge on the RAGE role in tumor progression, we investigated the receptor expression profile and its subcellular localization in melanoma cells at different stages of malignancy. We found that RAGE clustered at membrane ruffles and leading edges, and at sites of cell-to-cell contact in primary melanoma cells (e.g., MelJuSo), in contrast with a more dispersed localization in metastatic cells (e.g., SK-Mel28). RAGE silencing by RNAi selectively inhibited migration of MelJuSo cells, whilst having no influence on SK-Mel28 cell migration, in a "wound healing" assay. Western blot detection of RAGE showed a more complex RAGE oligomerization in MelJuSo cells compared to melanocytes and SK-Mel28 cells. By competing the binding of antibodies with recombinant soluble RAGE, an oligomeric form running at approximately 200 kDa was detected, as it was the monomeric RAGE of 55-60 kDa. SDS-PAGE electrophoresis under reducing versus nonreducing conditions indicated that the oligomer of about 200 kDa is formed by disulfide bonds, but other interactions are likely to be important for RAGE multimerization in melanoma cells. Immunofluorescence microscopy revealed that treatment with two cholesterol-chelating drugs, nystatin and filipin, significantly affected RAGE localization in MelJuSo cells. SK-Mel28 cells showed a reduced RAGE glycosylation and association with cholesterol-rich membranes and also a considerable downregulation of the soluble forms. Our results indicate that RAGE isoform expression and subcellular localization could be important determinants for the regulation of its function 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 | 0.001 |
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".