Frequent Inactivation of PTEN by Promoter Hypermethylation in Microsatellite Instability-High Sporadic Colorectal Cancers
Bibliographic record
Abstract
Loss of PTEN tumor suppressor function is observed in tumors of breast, prostate, thyroid, and endometrial origin. Allelic losses in the proximity of the PTEN locus (10q23) also occur in sporadic colorectal cancers (CRCs), but biallelic inactivation of this site has not been frequently demonstrated. We hypothesized that alternative mechanisms of PTEN allelic inactivation, such as promoter hypermethylation, might be operative in CRC and that PTEN inactivation may be related to recognized forms of genomic instability. We characterized a cohort of 273 sporadic CRCs by determining their microsatellite instability (MSI) status. Of these, 146 cancers were examined for PTEN promoter methylation by methylation-specific PCR. Mutations at the poly(A)6 repeat sequences in PTEN exons 7 and 8 and deletions at the 10q23 locus were also identified using microsatellite analysis. The presence of PTEN protein was determined by immunostaining, and the results were correlated with the promoter methylation status. We observed that PTEN promoter hypermethylation was a frequent occurrence in MSI-high (MSI-H) tumors (19.1% of MSI-H versus 2.2% of MSI-low/microsatellite stable tumors; P = 0.002). A PTEN mutation or a deletion event was present in 60% of the tumors with promoter region hypermethylation. Hypermethylation of the PTEN promoter correlated significantly with either decreased or complete loss of PTEN protein expression (P = 0.004). This is the first demonstration of PTEN inactivation as a result of promoter hypermethylation in MSI-H sporadic CRCs. These data suggest that this silencing mechanism plays a major role in PTEN inactivation and, in colon cancer, may be more important than either allelic losses or inactivating mutations. The significant correlation of PTEN hypermethylation with MSI-H tumors further suggests that PTEN is an additional important "target" of methylation along with the hMLH1 gene in the evolution of MSI-H CRCs and also confers the "second hit" in the biallelic inactivation mechanism for some proportion of tumors.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".