Diet-Dependent Metabolic Regulation of DNA Double-Strand Break Repair in Cancer: More Choices on the Menu
Bibliographic record
Abstract
Despite several epidemiologic and preclinical studies supporting the role of diet in cancer progression, the complexity of the diet-cancer link makes it challenging to deconvolute the underlying mechanisms, which remain scantly elucidated. This review focuses on genomic instability as one of the cancer hallmarks affected by diet-dependent metabolic alterations. We discuss how altered dietary intake of metabolites of the one-carbon metabolism, including methionine, folate, and vitamins B and C, can impact the methylation processes and thereby tumorigenesis. We present the concept that the protumorigenic effect of certain diets, such as the Western diet, is in part due to a diet-induced erosion of the DNA repair capacity caused by altered epigenetic and epitranscriptomic landscapes, while the protective effect of other dietary patterns, such as the Mediterranean diet, can be partly explained by their ability to sustain a proficient DNA repair. In particular, considering that diet-dependent alterations of the one-carbon metabolism can impact the rate of methylation processes, changes in dietary patterns can affect the activity of writers and erasers of histone and RNA methyl marks and consequently impair their role in ensuring a proficient DNA damage repair.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".