Role of The<i>MTHFR</i>Polymorphisms in Cancer Risk Modification and Treatment
Bibliographic record
Abstract
The role of folate, a water-soluble B vitamin, and single nucleotide polymorphisms (SNPs) in the folate metabolic pathway in human health and disease has been rapidly expanding. Recently, functionally significant SNPs in 5,10-methylenetetrahydrofolate reductase (MTHFR), a critical enzyme for intracellular folate homeostasis and metabolism, have been identified and characterized. The MTHFR SNPs are ideal candidates for investigating the role of SNPs in cancer risk modification and treatment because of their well-defined and highly relevant biochemical effects on intracellular folate composition and one-carbon transfer reactions. Indeed, a large body of molecular epidemiologic evidence suggests that the MTHFR 677 variant T allele is associated with cancer risk in a site-specific manner. Furthermore, biologically plausible mechanisms based on the functional consequences of changes in intracellular folate cofactors resulting from the MTHFR 677T variant exist to readily explain cancer risk modification associated with this variant. In addition, a growing body of in vitro and clinical evidence suggests that the MTHFR SNPs may be an important pharmacogenetic determinant of response to and toxicity of 5-fluorouracil (5FU) and methotrexate (MTX)-based cancer and anti-inflammatory chemotherapy. Furthermore, studies suggest that MTHFR inhibition may be a potential target for increasing chemosensitvity of cancer cells to 5FU-based chemotherapy. Because the MTHFR SNPs are prevalent and MTX and 5FU are widely used for the treatment of common cancers and inflammatory conditions, the pharmacogenetic role of the MTHFR SNPs has significant clinical implications. MTHFR SNPs may play an important role in providing rational, effective and safe tailored treatment to patients with cancer and inflammatory disorders requiring 5FU and MTX-based therapy. As such, largescale human studies and in vitro mechanistic studies are warranted to clarify the pharmacogenetic role of the MTHFR SNPs.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".