Initial gut microbiota composition is a determining factor in the promotion of colorectal cancer by oral iron supplementation: evidence from a murine model
Bibliographic record
Abstract
Abstract Background Colorectal cancer (CRC) development is influenced by both iron and gut microbiota composition. While iron supplementation is routinely used to manage anemia in CRC patients, it may also impact gut microbiota and promote tumorigenesis. In this study, we investigated the impact of initial gut microbiota composition on iron-promoted tumorigenesis. We performed fecal microbiota transplantation (FMT) in Apc Min/ + mice using samples from healthy controls, CRC patients, and mice, followed by exposure to iron sufficient or iron excess diets. Results We found that iron supplementation promoted CRC and resulted in distinct gut microbiota changes in Apc Min/ + mice receiving FMT from CRC patients (FMT-CRC), but not from healthy controls or mice. Oral treatment with identified bacterial strains, namely Faecalibaculum rodentium , Holdemanella biformis , Bifidobacterium pseudolongum , and Alistipes inops, protected FMT-CRC mice against iron-promoted tumorigenesis. Conclusions Our findings suggest that microbiota-targeted interventions may mitigate tumorigenic effects of iron supplementation in anemic patients with CRC. Graphical Abstract
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 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".