Abstract
Background The intestinal flora is correlated with the occurrence of colorectal cancer. We evaluate a new predictive model for non-invasive diagnosis of colorectal cancer based on the intestinal flora to verify the clinical application prospects of the intestinal flora as a new biomarker in non-invasive screening of colorectal cancer. Methods Included subjects from two independent Asian cohorts (cohort I, including 206 colorectal cancer and 112 healthy subjects; cohort II, Including 67 colorectal cancer and 54 healthy subjects). A probe-based duplex quantitative PCR (qPCR) determination was established for the quantitative determination of candidate bacterial markers. Results We screened through the gutMEGA database to identify potential non-invasive biomarkers for colorectal cancer, including Prevotella copri (Pc), Gemella morbillorum (Gm), Parvimonas micra (Pm), Cetobacterium somerae (Cs) and Pasteurella stomatis (Ps). A predictive model with good sensitivity and specificity was established as a new diagnostic tool for colorectal cancer. Under the best cut-off value that maximizes the sum of sensitivity and specificity, Gm and Pm have better specificity and sensitivity than other target bacteria. The combined detection model of five kinds of bacteria showed better diagnostic ability than Gm and Pm alone (AUC=0.861, P<0.0001). These findings were further confirmed in independent cohort II. Particularly, the combination of bacterial markers and FIT improved the diagnostic ability of five-bacteria (sensitivity 67.96%, specificity 89.29%) for patients with colorectal cancer. Conclusion Fecal-based colorectal cancer related bacteria can be used as new non-invasive diagnostic biomarkers of colorectal cancer. Simultaneously the molecular biomarkers in fecal samples are similar to fecal immunochemical test (FIT), have the applicability in combination with other detection methods, which is expected to improve the sensitivity of diagnosis for colorectal cancer and have a promising prospect of clinical application.
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