Published online Aug 15, 2023. doi: 10.4251/wjgo.v15.i8.1424
Peer-review started: March 24, 2023
First decision: May 19, 2023
Revised: May 20, 2023
Accepted: June 19, 2023
Article in press: June 19, 2023
Published online: August 15, 2023
Processing time: 139 Days and 5 Hours
Colorectal cancer (CRC) is a major global health burden, and its incidence and mortality have increased rapidly over the past decades and resulted in massive economic burdens in China.
This case-control study enrolled 54 CRC patients and 51 healthy controls.
This research aimed to explore the characteristics of intestinal flora and its correlation with multi-target stool DNA (MT-sDNA) and tumor markers in CRC patients, and evaluate the diagnostic performance of MT-sDNA and tumor biomarkers combined with microbiota in CRC.
We evaluated the performance of the MT-sDNA test based on a hospital clinical trial. The intestinal microbiota was tested using 16S rRNA gene sequencing. We identified biomarkers of bacteria structure, analyzed the relationship between different tumor markers and the relative abundance of related flora components, and distinguished CRC patients from healthy subjects by the linear discriminant analysis effect size, redundancy analysis, and random forest analysis, respectively.
We found that MT-sDNA was closely associated with Bacteroides. MT-sDNA and carcinoembryonic antigen (CEA) were positively correlated with the existence of Parabacteroides, and alpha-fetoprotein was positively associated with Faecalibacterium and Megamonas. The random forest model results showed that the combination of the six genera, namely, Streptococcus, Escherichia, Chitinophaga, Parasutterella, Lachnospira, and Romboutsia, can distinguish CRC from health controls. The sensitivity and specificity of MT-sDNA combined with the six genera and CEA in the diagnosis of CRC were 98.1% and 92.3%, respectively, and the diagnostic accuracy was 97.1%.
MT-sDNA and tumor markers were positively correlated with intestinal flora. Intestinal flora, MT-sDNA, and tumor markers showed significant sensitivity and specificity for CRC prediction, which could be used as a non-invasive method to improve the diagnostic accuracy.
Our results will optimize the diagnosis of CRC and provide new ideas for translating microbit-based diagnostic strategies into precise diagnosis in the clinic.