Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with choline degradation
View abstract on PubMed
Summary
This summary is machine-generated.The gut microbiome in colorectal cancer (CRC) patients shows consistently higher richness and specific metabolic pathways compared to healthy individuals. These findings identify reproducible microbiome biomarkers for potential clinical prognostic tests.
Area Of Science
- Microbiome research
- Oncology
- Metagenomics
Background
- The gut microbiome's role in colorectal cancer (CRC) is under investigation, but biomarker replicability across populations remains a challenge.
- Existing studies often lack consistency in identifying reliable microbial signatures for CRC.
Purpose Of The Study
- To perform a meta-analysis of fecal metagenomes to identify reproducible gut microbiome biomarkers for colorectal cancer (CRC).
- To validate predictive microbiome signatures and explore the relationship between microbiome function and CRC.
- To establish a foundation for clinical prognostic tests based on microbiome data.
Main Methods
- Meta-analysis of five public and two new fecal metagenome datasets (total 969 samples), with validation on two additional cohorts.
- Analysis of microbiome functional potential and specific gene abundance (choline trimethylamine-lyase).
- Development and validation of predictive microbiome signatures for CRC detection.
Main Results
- Colorectal cancer (CRC) patients exhibited significantly higher gut microbiome richness compared to controls.
- Specific metabolic pathways (gluconeogenesis, putrefaction, fermentation) were associated with CRC, while others (stachyose, starch degradation) were linked to controls.
- Predictive microbiome signatures achieved high accuracy (average AUC 0.84) in independent validation cohorts.
- The choline trimethylamine-lyase gene was found to be overabundant in CRC patients, indicating a link to choline metabolism.
Conclusions
- Reproducible gut microbiome biomarkers for colorectal cancer (CRC) have been identified through combined analysis of heterogeneous cohorts.
- Accurate disease-predictive models based on microbiome signatures can be developed.
- These findings support the potential for microbiome-based clinical prognostic tests and mechanistic studies in CRC.
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