Journal
GUT MICROBES
Volume 13, Issue 1, Pages 1-6Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/19490976.2020.1869505
Keywords
Metagenome; colorectal cancer; single nucleotide variants; gut microbiota; diagnostic markers
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Funding
- Key R&D programs in Hainan [ZDYF2019150, ZDYF2018111]
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This study identified 22 microbial SNV markers for constructing a novel CRC predictive model, which demonstrated high accuracy in both training and validation cohorts. Furthermore, through meta-analysis across 4 metabolic disease cohorts, 3 specific SNVs enriched in CRC patients were found in the genomes of Eubacterium rectale and Faecalibacterium prausnitzii.
Current metagenomic species-based colorectal cancer (CRC) microbial biomarkers may confuse diagnosis because the genetic content of different microbial strains, even those belonging to the same species, may differ from 5% to 30%. Here, a total of 7549 non-redundant single nucleotide variants (SNVs) were annotated in 25 species from 3 CRC cohorts (n = 249). Then, 22 microbial SNV markers that contributed to distinguishing subjects with CRC from healthy subjects were identified by the random forest algorithm to construct a novel CRC predictive model. Excitingly, the predictive model showed high accuracy both in the training (AUC = 75.35%) and validation cohorts (AUC = 73.08%-88.02%). We further explored the specificity of these SNV markers in a broader background by performing a meta-analysis across 4 metabolic disease cohorts. Among these SNV markers, 3 SNVs that were enriched in CRC patients and located in the genomes of Eubacterium rectale and Faecalibacterium prausnitzii were CRC specific (AUC = 72.51%-94.07%).
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