Associations of Ki-<i>ras</i> Proto-oncogene Mutation and p53 Gene Overexpression in Sporadic Colorectal Adenomas with Demographic and Clinicopathologic Characteristics
Bibliographic record
Abstract
In colorectal tumorigenesis, Ki-ras proto-oncogene mutation often occurs early in the adenoma-adenocarcinoma sequence, whereas mutation of the p53 gene is associated with late progression to carcinoma. We evaluated the relationship of demographic and clinicopathologic characteristics to Ki-ras mutation and p53 gene product overexpression in 1,093 baseline sporadic colorectal adenomas from 926 individuals enrolled in a phase III recurrence prevention trial. Ki-ras mutation was found in 14.7% of individuals and p53 overexpression was found in 7.0% of those tested. Multivariate analysis found older age, rectal location, and villous histology to be independently associated with Ki-ras mutation. Individuals with an advanced adenoma (>or=1 cm or high-grade dysplasia or villous histology) had a 4-fold higher likelihood of Ki-ras mutation [odds ratios (OR), 3.96; 95% confidence intervals (CI), 2.54-6.18]. Ki-ras mutations in codon 12 and of the G-to-A transition type were more frequent in older individuals, whereas G-to-T transversion was more frequent in rectal adenomas than in the colon. Multivariate analysis showed that previous history of a polyp (P = 0.03) was inversely associated with p53 overexpression. Large adenoma size (>or=1 cm), high-grade dysplasia, and villous histology were independently associated with p53 overexpression, with the strongest association for advanced adenomas (OR, 7.20; 95% CI, 3.01-17.22). Individuals with a Ki-ras mutated adenoma were more likely to overexpress p53 (OR, 2.46; 95% CI, 1.36-4.46), and 94.8% of adenomas with both alterations were classified as advanced (P
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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 | 0.003 |
| 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 | 0.000 | 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".