LGN loss randomizes spindle orientation and accelerates tumorigenesis in PTEN-deficient epidermis
Bibliographic record
Abstract
Loss of cell polarity and disruption of tissue organization are key features of tumorigenesis that are intrinsically linked to spindle orientation. Epithelial tumors are often characterized by spindle orientation defects, but how these defects impact tumor formation driven by common oncogenic mutations is not fully understood. Here, we examine the role of spindle orientation in adult epidermis by deleting a key spindle regulator, LGN, in normal tissue and in a PTEN-deficient mouse model. We report that LGN deficiency in PTEN mutant epidermis leads to a threefold increase in the likelihood of developing tumors on the snout, and an over 10-fold increase in tumor burden. In this tissue, loss of LGN alone increases perpendicular and oblique divisions of epidermal basal cells, at the expense of a planar orientation of division. PTEN loss alone does not significantly affect spindle orientation in these cells, but the combined loss of PTEN and LGN fully randomizes basal spindle orientation. A subset of LGN- and PTEN-deficient animals have increased amounts of proliferative spinous cells, which may be associated with tumorigenesis. These results indicate that loss of LGN impacts spindle orientation and accelerates epidermal tumorigenesis in a PTEN-deficient mouse model.
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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 | 0.001 |
| 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".