Analysis of the PTEN gene mutation in polyposis syndromes and sporadic gastrointestinal tumors in Japanese patients
Bibliographic record
Abstract
PURPOSE: PTEN is a candidate tumor suppressor gene for mutations which are responsible for Cowden disease. Recently, it has been shown that PTEN is mutated in several human neoplasms. To investigate the role of PTEN in tumorigenesis, we screened its mutation in Japanese patients with gastrointestinal polyposis and various sporadic tumors. METHODS: The entire coding region of PTEN was screened by single strand conformational polymorphism or direct sequencing for somatic mutations in 16 gingival papillomas, 4 juvenile polyps, 10 esophageal papillomas, and 20 colorectal cancers and for germline mutations in three patients with Cowden disease (including one with Lhermitte-Duclos disease) and one patient each with juvenile polyposis syndrome, Turcot's syndrome, and Cronkhite-Canada syndrome. RESULTS: Germline mutations were found in all cases of Cowden disease. One mutation was a nonsense mutation at codon 130 (CGA-->TGA), and the other two were splice site mutations at the 5' site of intron 4 and the 3' site of intron 8. We could not detect germline mutations in other patients with gastrointestinal polyposis or somatic mutations in sporadic tumors. CONCLUSIONS: We confirmed previous reports that germline mutations in PTEN are responsible for Cowden disease. However, somatic mutations of PTEN may not play a major role in tumorigenesis, at least in colorectal cancers, esophageal papillomas and gingival papillomas.
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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 | 0.001 | 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".