Methylenetetrahydrofolate reductase polymorphism in advanced colorectal cancer: a novel genomic predictor of clinical response to fluoropyrimidine-based chemotherapy.
Bibliographic record
Abstract
PURPOSE: Fluorouracil (5-FU) is widely used in the treatment of colorectal cancer. Methylenetetrahydrofolate reductase (MTHFR) could play an important role in the action of 5-FU, an inhibitor of thymidylate synthetase, by converting 5,10-methylenetetrahydrofolate, a substrate of thymidylate synthetase, to 5-methyltetrahydrofolate. A polymorphism in MTHFR (677 C-->T; A222V) reduces enzyme activity and presumably increases the level of 5,10-methylenetetrahydrofolate. This increase would be expected to correlate with an improved response to 5-FU. The aim of the present study was to investigate the association between the MTHFR polymorphism and response to 5-FU and other fluoropyrimidines in patients with metastatic colorectal cancer. EXPERIMENTAL DESIGN: Forty-three patients with metastatic colorectal adenocarcinoma were analyzed. All patients were treated with p.o. or i.v. fluoropyrimidine-based chemotherapy. A comprehensive chart examination was performed to determine tumor response rates. Genomic DNA was extracted from blood, and MTHFR genotypes were determined. RESULTS: At least one copy of the mutant valine allele was present in 26 patients (21 heterozygotes and 5 homozygotes). The remaining 17 patients carried only the alanine allele. Exploration of the relationship between MTHFR alleles and response rates revealed a statistically significant difference in the frequency of the valine allele among responders versus nonresponders (P = 0.0351). This observation was associated with an odds ratio of 2.86 (95% confidence interval 1.06-7.73) for a response in individuals with a valine allele. CONCLUSIONS: Our results show a link between the MTHFR polymorphism and tumor response to fluoropyrimidine-based chemotherapy and suggest that MTHFR genotyping may be of predictive benefit in selecting treatment regimens.
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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 | 0.000 | 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".