Bibliographic record
Abstract
Epidemiological evidence points towards the role of diets high in red and processed meats in the cancers of many tissue types. The mechanisms by which meat consumption may lead to cancer risk are not well understood. Meat is a complex exposure, i.e. a mixture of various potential carcinogens that may individually or collectively contribute to cancer risk. In these studies we investigated whether carcinogens that accumulate during the process of high temperature cooking of meats, or to due to cooking of meats to high levels of doneness, might increase the risk of prostate and colorectal cancer risk. These carcinogens include heterocyclic amines (HCAs) and polycyclic aromatic hydrocarbons (PAHs). Moreover, diets high in processed meats may contribute to exposure to N-nitroso compounds (NOCs), which can also be formed endogenously when diets are high in red meat intake. To better understand which of these carcinogens might be more likely to explain the observed association between meat and cancer we considered variation in genes that metabolize HCAs, PAHs or N-nitroso compounds (NOCs), and genes that repair DNA damage caused by these exposures, to test for gene-exposure interactions. Given that some of these genes play specific roles in the metabolism of each type of carcinogen, finding of an interaction would help us identify which substrate is more likely to play a role in meat-induced carcinogenesis. Diets high in meat, as well as dairy, are also a rich source of phytanic acid. This branched-fatty acid has also been postulated to play a role in cancer. Therefore, we also investigated whether variants in AMACR, an enzyme that plays a key role in the metabolism of phytanic acid ,may associate with prostate cancer risk. ❧ We tested our hypotheses for prostate cancer using the resources of the California Collaborative Case Control Study of Prostate Cancer that included food frequency questionnaire (FFQ) data for 1,096 controls, 717 localized and 1,140 advanced cases. We conducted analyses for colorectal cancer risk in participants of the Colorectal Family Registry (CFR), an international consortium of six centers from the United States, Canada and Australia.We had food frequency questionnaire data for 3,364 probands, 1,942 familial controls (siblings/ spouse) and 1,620 population based controls. ❧ In the prostate cancer study, pan-fried red meat and white fish were associated with a statistically significant increased risk of advanced prostate cancer. Since pan-frying is associated with the formation of HCAs, but not PAHs or NOCs, we speculate that dietary HCAs may be relevant risk factors of advanced prostate cancer. However estimated levels of total dietary heterocyclic amines using the CHARRED database were not associated with risk of prostate cancer. We observed evidence of modification of the effect of 'estimated mutagenic activity' on advanced prostate cancer risk by a promoter polymorphism in PTGS2, an enzyme that plays a role in activation of both PAHs and HCAs in the prostate as well as in inflammation. We did not find any evidence in support of the hypothesis that phytanic acid may mediate associations between meat products and prostate cancer risk. ❧ In the colorectal study, we did not observe any associations for well done meat types, oven broiled or grilled meat types with colorectal cancer risk. However, of the 6 meat types for which we had pan-frying information, three (beef, spam and sausage) showed a statistically significant increased risk of colorectal cancer. As with the prostate cancer study, estimated levels of heterocyclic amines were not associated with the risk of colorectal cancer. The findings of our studies point towards at least a partial role for meat cooking related exposures and risk of cancers, and have potential implications both in understanding the mechanisms of meat related carcinogenesis and in the public health goal of cancer prevention.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".