Missense Polymorphisms in the Adenomatous Polyposis Coli Gene and Colorectal Cancer Risk
Bibliographic record
Abstract
PURPOSE: Whereas truncating germline mutations of the adenomatous polyposis coli (APC) gene give rise to familial adenomatous polyposis, missense polymorphisms of APC may confer a weaker risk for colorectal cancer. METHODS: We sequenced the entire open reading frame of the APC gene and tested for two common MYH mutations in a population-based series of patients with colorectal cancer and 5 to 99 adenomas. Missense adenomatous polyposis coli alterations identified in this colorectal cancer multiple-polyp population were analyzed in a population-based series of patients with colorectal cancer and healthy control subjects. RESULTS: Germline APC or mutY human homologue (MYH) alterations were identified in 16 of 39 colorectal cancer-multiple polyp patients. Four missense APC gene alterations (S130G, E1317Q, D1822V, G2502S) were observed in 13 individuals and 3 additional patients carried presumed pathogenic (APC Y94X, biallelic MYH Y165C and heterozygous MYH G382D) mutations. When independently assessed in 971 patients with colorectal cancer and 954 healthy control subjects, none of the identified missense APC alterations conferred a significantly increased risk for colorectal cancer, odds ratio (95 percent confidence intervals): S130G = 3.1 (0.29-32.25), E1317Q = 1.08 (0.59-2.74), G2502S = 1 (0.65-1.63), D1822V (heterozygous) = 0.79 (0.64-0.98), D1822V (homozygous) = 0.82 (0.63-1.27). CONCLUSIONS: Germline missense APC alterations observed in 33 percent of patients with multiple colorectal neoplasms seemed to play a limited role in colorectal cancer risk when independently assessed by a population-based, case-control analysis.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".