The Impact of Genetic Variants on <i>PTEN</i> Molecular Functions and Cellular Phenotypes
Bibliographic record
Abstract
Phosphatase and tensin homolog (PTEN) is a tumor suppressor that directly regulates a diverse array of cellular phenotypes, including growth, migration, morphology, and genome stability.How a single protein impacts so many important cellular processes remains a fascinating question.This question has been partially resolved by the characterization of a slew of missense variants that alter or eliminate PTEN's various molecular functions, including its enzymatic activity, subcellular localization, and posttranslational modifications.Here, we review what is known about how PTEN variants impact molecular function and, consequently, cellular phenotype.In particular, we highlight eight informative "sentinel variants" that abrogate distinct molecular functions of PTEN.We consider two published massively parallel assays of variant effect that measured the effect of thousands of PTEN variants on protein abundance and enzymatic activity.Finally, we discuss how characterization of clinically ascertained variants, establishment of clinical sequencing databases, and massively parallel assays of variant effect yield complementary datasets for dissecting PTEN's role in disease.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".