A Low Carbohydrate, High Protein Diet Slows Tumor Growth and Prevents Cancer Initiation
Bibliographic record
Abstract
Since cancer cells depend on glucose more than normal cells, we compared the effects of low carbohydrate (CHO) diets to a Western diet on the growth rate of tumors in mice. To avoid caloric restriction-induced effects, we designed the low CHO diets isocaloric with the Western diet by increasing protein rather than fat levels because of the reported tumor-promoting effects of high fat and the immune-stimulating effects of high protein. We found that both murine and human carcinomas grew slower in mice on diets containing low amylose CHO and high protein compared with a Western diet characterized by relatively high CHO and low protein. There was no weight difference between the tumor-bearing mice on the low CHO or Western diets. Additionally, the low CHO-fed mice exhibited lower blood glucose, insulin, and lactate levels. Additive antitumor effects with the low CHO diets were observed with the mTOR inhibitor CCI-779 and especially with the COX-2 inhibitor Celebrex, a potent anti-inflammatory drug. Strikingly, in a genetically engineered mouse model of HER-2/neu-induced mammary cancer, tumor penetrance in mice on a Western diet was nearly 50% by the age of 1 year whereas no tumors were detected in mice on the low CHO diet. This difference was associated with weight gains in mice on the Western diet not observed in mice on the low CHO diet. Moreover, whereas only 1 mouse on the Western diet achieved a normal life span, due to cancer-associated deaths, more than 50% of the mice on the low CHO diet reached or exceeded the normal life span. Taken together, our findings offer a compelling preclinical illustration of the ability of a low CHO diet in not only restricting weight gain but also cancer development and progression.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".