Metastasis‐focused cell‐based SELEX generates aptamers inhibiting cell migration and invasion
Bibliographic record
Abstract
Metastasis, the capacity of tumour cells to disseminate and grow at distant sites, is the main factor in cancer mortality. Compounds inhibiting migration and invasion of cancer cells are promising candidates for anticancer therapy strategies. We have generated nuclease-resistant RNA ligands (aptamers) recognizing highly metastatic cells with high affinity and specificity, and inhibiting their migratory and invasive potentials. Aptamers were generated by a cell-based subtractive SELEX technology using isogenic cell lines with similar tumorigenic potentials but opposite metastatic aggressiveness. Two aptamers, E37 and E10, bound specifically to the metastatically aggressive cell line and altered the phosphorylation of several tyrosine kinases. Fluorescent microscopy showed intracellular uptake of E37, in contrast to membrane binding of E10. Both aptamers inhibited migration of tumour cells in culture (50 and 85% inhibition with respect to control pool for E10 and E37, respectively) while only E10 inhibited cell invasion (-75% with respect to control pool). This proof-of-concept study demonstrates the potential of cell-based SELEX to yield ligands that selectively recognize aggressive metastatic cells and inhibit phenotypes linked to metastatic potential.
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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 | 0.000 | 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".