Microbiome Analysis of More Than 2,000 NHS Bowel Cancer Screening Programme Samples Shows the Potential to Improve Screening Accuracy

Abstract

To assess the utility of microbiome profiles for national-scale colorectal cancer (CRC) screening, we assessed 2,252 routinely processed NHS Bowel Cancer Screening Programme guaiac faecal occult blood test (gFOBT) samples. We generated four microbiome-based random forest classification models, each showing potential to improve accuracy.Two distinguished either CRC or neoplasm (CRC or adenoma) from gFOBT blood-negative samples (equivalent to firsttier screening). Two distinguished CRC or neoplasm from samples that had tested positive for blood by gFOBT, with participants referred for colonoscopy, but at colonoscopy no-lesion was found (second-tier screening to rule out gFOBT false positives). Each model remained robust to validation and when restricted to fifteen taxa, raising the possibility of an inexpensive qPCR-test. The models performed favourably compared with existing microbiome studies, FIT and Cologuard. These results suggest that microbiome analysis could be integrated into national CRC screening to improve accuracy and reduce the number of unnecessary screening colonoscopies.

The Tissue-Associated Microbiota in Colorectal Cancer: A Systematic Review

“…A large number of studies that address the CRC microbial community composition have used fecal samples, prompted by their potential use as a non-invasive tool for cancer screening and early detection [ 20 , 21 ]. In fact, recent data collected in a national screening program suggest that microbial profiling may improve CRC screening accuracy [ 22 ]. However, while the use of fecal samples for microbiome studies may have advantages due to their ease of collection and non-invasive nature, their composition does not accurately represent the more stable cancer microbiota and the mucosal interactions across the gut [ 23 , 24 ].…”

A systematic review of microbiome-derived biomarkers for early colorectal cancer detection

“…For microbiome-derived biomarkers based on bacteria for the detection of early CRC, 26 articles were found and two articles were found investigating the co-metabolome solely as a biomarker. Seventeen of the studies were conducted in East Asia [ 19 , [27] , [28] , [29] , [30] , [31] , [32] , [33] , [34] , [35] , [36] , [37] , [38] , [39] , [40] , [41] , [42] ], one in South Asia [43] , eight in Europe [44] , [45] , [46] , [47] , [48] , [49] , [50] , [51] and two in North America [ 52 , 53 ]. The number of inclusions of these studies ranged between 2 and 462 for CRC, 18 and 665 for adenoma and/or polyp and 24 and 788 for healthy controls.…”

“…Regarding the stage used in the articles for early CRC detection, five studies were based on stage I or II [ 29 , 30 , 37 , 40 , 50 ] and two used stage 0 [ 19 , 38 ]. The other studies investigated a precursor lesion of CRC, either advanced adenomas or polyps (AP) [ 28 , [31] , [32] , [33] , [34] , [35] , 39 , 41 , [44] , [45] , [46] , [47] , [48] , [49] , [51] , [52] , [53] ]. Only five articles evaluated both precursor lesions of CRC and stages I and II [ 27 , 36 , 38 , 43 , 54 ].…”

“…For the detection of these bacteria, different techniques were used. 11 articles used 16S rRNA gene sequencing [ 28 , [31] , [32] , [33] , 38 , 44 , 46 , 47 , 49 , 52 , 53 ], whereas nine used qPCR [ 27 , 29 , 30 , 37 , [39] , [40] , [41] , 43 , 45 ] and six used metagenomic shotgun sequencing [ 19 , [34] , [35] , [36] , 48 , 50 ]. Universal primers were used in most articles using 16S rRNA gene sequence analysis.…”

“…Statistical approaches for the classification models for the prediction of early CRC were based on different models. Besides simple logistic regression models (LRM) [ 27 , 29 , 30 , 35 , [37] , [38] , [39] , [40] , [41] , 43 , 45 ], a random forest model (RFM) was often used [ 28 , 31 , 34 , 36 , [47] , [48] , [49] , 52 ], followed by LASSO logistic regression models [ 32 , 44 , 50 ] and Bayesian methods [ 33 , 53 ]. Two studies even used two classification models [ 19 , 46 ].…”