Identification and impact of microbiota-derived metabolites in ascites of ovarian and gastrointestinal cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Malignant ascites is a common complication of advanced ovarian cancer (OC) and gastrointestinal cancer (GI), significantly impacting metastasis, quality of life, and survival. Increased intestinal permeability can lead to blood or lymphatic infiltration and microbial translocation from the gastrointestinal or uterine tract. This study aimed to identify microbiota-derived metabolites in ascites from OC (stages II-III and IV) and GI patients, assessing their roles in tumor progression. METHODS: Malignant ascites samples from 18 OC and GI patients were analyzed using a four-dimensional (4D) untargeted metabolomics approach combining reversed-phase (RP) and hydrophilic interaction liquid chromatography (HILIC) with trapped ion mobility spectrometry time-of-flight mass spectrometry (timsTOF-MS). Additonally, a targeted flow cytometry-based cytokine panel was used to screen for inflammatory markers. Non-endogenous, microbiota-derived metabolites were identified through the Human Microbial Metabolome Database (MiMeDB). RESULTS: OC stage IV exhibited metabolic profiles similar to GI cancers, while OC stage II-III differed significantly. Stage IV OC patients exhibited higher levels of 11 typically microbiome-derived metabolites, including 1-methylhistidine, 3-hydroxyanthranilic acid, 4-pyridoxic acid, biliverdin, butyryl-L-carnitine, hydroxypropionic acid, indole, lysophosphatidylinositol 18:1 (LPI 18:1), mevalonic acid, N-acetyl-L-phenylalanine, and nudifloramide, and lower levels of 5 metabolites, including benzyl alcohol, naringenin, o-cresol, octadecanedioic acid, and phenol, compared to stage II-III. Correlation analysis revealed positive associations between IL-10 and metabolites such as glucosamine and LPCs, while MCP-1 positively correlated with benzyl alcohol and phenol. CONCLUSION: 4D metabolomics revealed distinct metabolic signatures in OC and GI ascites, highlighting microbiota-derived metabolites involved in lipid metabolism and inflammation. Metabolites like 3-hydroxyanthranilic acid, indole, and naringenin may serve as markers of disease progression and underscore the microbiota's role in shaping malignant ascites and tumor biology.
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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 it