The Microbial Bile Acid Metabolite 3-Oxo-LCA Inhibits Colorectal Cancer Progression
Bibliographic record
Abstract
Bile acids (BA) not only influence the gut microbiome composition but are also metabolized by gut bacteria to form various microbial BAs. Among these, 3-oxo-lithocholic acid (3-oxo-LCA) and isoallo-LCA have been reported to modulate host immunity, suppress intestinal pathogens, and provide antiaging benefits, suggesting that they could also affect intestinal epithelial cells and colorectal cancer progression. To investigate the impact of 3-oxo-LCA on intestinal tumorigenesis, we evaluated its activity in vitro on mouse and human colorectal cancer cell lines, as well as primary mouse intestinal organoids and patient-derived colorectal cancer organoids, and in vivo using a genetically engineered mouse model, cell line-derived syngeneic and xenograft tumors, and patient-derived xenografts. 3-Oxo-LCA functioned as a potent FXR agonist that restored FXR signaling both in vitro and in vivo. Activation of FXR signaling reduced the growth of colorectal cancer cell lines and suppressed the proliferation of intestinal stem cells in both mouse organoids and patient-derived colorectal cancer organoids. In the APCMin/+ genetically engineered mouse model, 3-oxo-LCA reduced BA levels, enhanced gut barrier function, decreased tumor burden, and suppressed tumor initiation. Furthermore, 3-oxo-LCA significantly inhibited tumor progression in syngeneic and xenograft mouse models and promoted apoptosis within the tumors. Together, these results underscore the function of 3-oxo-LCA as an FXR agonist with the ability to inhibit colorectal cancer tumorigenesis and progression by modulating epithelial cell growth and death. SIGNIFICANCE: The microbial bile acid 3-oxo-LCA activates FXR signaling in intestinal epithelial cells that inhibits cancer stem cell proliferation and induces apoptosis, highlighting the potential of 3-oxo-LCA for treating intestinal tumorigenesis.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".