Selection of established tumour cells through narrow diameter micropores enriches for elevated Ras/Raf/MEK/ERK MAPK signalling and enhanced tumour growth
Bibliographic record
Abstract
As normal cells become cancer cells, and progress towards malignancy, they become progressively softer. Advantages of this change are that tumour cells become more deformable, and better able to move through narrow constraints. We designed a positive selection strategy that enriched for cells which could move through narrow diameter micropores to identify cell phenotypes that enabled constrained migration. Using human MDA MB 231 breast cancer and MDA MB 435 melanoma cancer cells, we found that micropore selection favoured cells with relatively higher Ras/Raf/MEK/ERK mitogen-activated protein kinase (MAPK) signalling, which affected actin cytoskeleton organization, focal adhesion density and cell elasticity. In this follow-up study, we provide further evidence that selection through micropores enriched for cells with altered cell morphology and adhesion. Additional analysis of RNA sequencing data revealed a set of transcripts associated with small cell size that was independent of constrained migration. Gene set enrichment analysis identified the ‘matrisome’ as the most significantly altered gene set linked with small size. When grown as orthotopic xenograft tumours in immunocompromised mice, micropore selected cells grew significantly faster than Parent or Flow-Sorted cells. Using mathematical modelling, we determined that there is an interaction between 1) the cell to gap size ratio; 2) the bending rigidity of the cell, which enable movement through narrow gaps. These results extend our previous conclusion that Ras/Raf/MEK/ERK MAPK signalling has a significant role in regulating cell biomechanics by showing that the selective pressure of movement through narrow gaps also enriches for increased tumour growth in vivo.
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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) | 0.001 | 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".