Colorectal cancer diagnostic model utilizing metagenomic and metabolomic data of stool microbial extracellular vesicles

Da Jung Kim, Jinho Yang, Hochan Seo, Won Hee Lee, Dong Ho Lee, Sungmin Kym, Young Soo Park, Jae Gyu Kim, In Jin Jang, Yoon Keun Kim, Joo Youn Cho

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Colorectal cancer (CRC) is the most common type cancers in the world. CRC occurs sporadically in the majority of cases, indicating the predominant cause of the disease are environmental factors. Diet-induced changes in gut-microbiome are recently supposed to contribute on epidemics of CRC. This study was aimed to investigate the association of metagenomics and metabolomics in gut extracellular vesicles (EVs) of CRC and healthy subjects. A total of 40 healthy volunteers and 32 patients with CRC were enrolled in this study. Metagenomic profiling by sequencing 16 S rDNA was performed for assessing microbial codiversity. We explored the small molecule metabolites using gas chromatography-time-of-flight mass spectrometry. In total, stool EVs were prepared from 40 healthy volunteers and 32 patients with CRC. Metagenomic profiling demonstrated that bacterial phyla, particularly of Firmicutes and Proteobacteria, were significantly altered in patients with colorectal cancer. Through metabolomics profiling, we determined seven amino acids, four carboxylic acids, and four fatty acids; including short-chain to long chain fatty acids that altered in the disease group. Binary logistic regression was further tested to evaluate the diagnostic performance. In summary, the present findings suggest that gut flora dysbiosis may result in alternation of amino acid metabolism, which may be correlated with the pathogenesis of CRC.

Original languageEnglish
Article number2860
JournalScientific Reports
Volume10
Issue number1
DOIs
StatePublished - 1 Dec 2020

Fingerprint Dive into the research topics of 'Colorectal cancer diagnostic model utilizing metagenomic and metabolomic data of stool microbial extracellular vesicles'. Together they form a unique fingerprint.

Cite this