Fundamental control of grade‐specific colorectal cancer morphology by Src regulation of ezrin–centrosome engagement
Bibliographic record
Abstract
The phenotypic spectrum of colorectal cancer (CRC) is remarkably diverse, with seemingly endless variations in cell shape, mitotic figures and multicellular configurations. Despite this morphological complexity, histological grading of collective phenotype patterns provides robust prognostic stratification in CRC. Although mechanistic understanding is incomplete, previous studies have shown that the cortical protein ezrin controls diversification of cell shape, mitotic figure geometry and multicellular architecture, in 3D organotypic CRC cultures. Because ezrin is a substrate of Src tyrosine kinase that is frequently overexpressed in CRC, we investigated Src regulation of ezrin and morphogenic growth in 3D CRC cultures. Here we show that Src perturbations disrupt CRC epithelial spatial organisation. Aberrant Src activity suppresses formation of the cortical ezrin cap that anchors interphase centrosomes. In CRC cells with a normal centrosome number, these events lead to mitotic spindle misorientation, perturbation of cell cleavage, abnormal epithelial stratification, apical membrane misalignment, multilumen formation and evolution of cribriform multicellular morphology, a feature of low-grade cancer. In isogenic CRC cells with centrosome amplification, aberrant Src signalling promotes multipolar mitotic spindle formation, pleomorphism and morphological features of high-grade cancer. Translational studies in archival human CRC revealed associations between Src intensity, multipolar mitotic spindle frequency and high-grade cancer morphology. Collectively, our study reveals Src regulation of CRC morphogenic growth via ezrin-centrosome engagement and uncovers combined perturbations underlying transition to high-grade CRC morphology. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.
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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".