Microbiome Profiling from Fecal Immunochemical Test Reveals Microbial Signatures with Potential for Colorectal Cancer Screening

Abstract

Colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer deaths worldwide. Early diagnosis of CRC, which saves lives and enables better outcomes, is generally implemented through a two-step population screening approach based on the use of Fecal Immunochemical Test (FIT) followed by colonoscopy if the test is positive. However, the FIT step has a high false positive rate, and there is a need for new predictive biomarkers to better prioritize cases for colonoscopy. Here we used 16S rRNA metabarcoding from FIT positive samples to uncover microbial taxa, taxon co-occurrence and metabolic features significantly associated with different colonoscopy outcomes, underscoring a predictive potential and revealing changes along the path from healthy tissue to carcinoma. Finally, we used machine learning to develop a two-phase classifier which reduces the current false positive rate while maximizing the inclusion of CRC and clinically relevant samples.

Mucosal Microbiome in Patients with Early Bowel Polyps: Inferences from Short-Read and Long-Read 16S rRNA Sequencing

“…However, this was unlikely, as the top results for a selection of the four most abundant of these reads in the NCBI nucleotide Basic Local Alignment Search Tool (nBLAST) were indeed S. wadsworthensis, with a percent identity ranging from 99.75% to 100% (E value = 0). Previous studies in the literature suggest that S. wadsworthensis tends to be more abundant in IBS [57] stool samples of FOBT+ individuals [58] and in stool samples of individuals with pre-cancerous or CRC lesions [59], which are findings consistent with our long-read data obtained from mucosal specimens. Overall, these results suggest that different species or strains may have different effects on polyp development or may differ in effect depending on their interactions with other bacteria in the environment.…”

Systematic scoping review: Use of the faecal immunochemical test residual buffer to enhance colorectal cancer screening

“…Combined with FIT, this 13‐bacteria panel had an adjusted AUC of 0.641 for AA 31 . Khannous‐Lleiffe et al 32 reported on a two‐phase model including Akkermansia spp., Akkermansia muciniphila , Bacteroides fragilis , Bacteroides plebeius , Negativibacillus spp., Bacteroides coprocola , Bacteroides caccae , Dorea formicigenerans , sex, age, and FIT value. This model had a sensitivity of 100% for CRC and 96% for clinically relevant samples (defined as CRC, carcinomas in situ, high‐risk lesions, or intermediate‐risk lesions).…”

“…In contrast, Zhang et al 31 (in order of level of association) found genus Tyzzerella 4 , genus Rothia , genus Clostridium sensu stricto 1 , genus Streptococcus , and family Streptococcaceae had greater abundance in AA samples ( p < 0.004), with seven other taxa present with greater abundance in AA samples ( p ‐values ranged from p = 0.01052 to p = 0.00375). Khannous‐Lleiffe et al 32 found that 41 total bacterial species with significantly different abundances, including Akkermansia spp. and Akkermansia muciniphila increased in CRC, and Bacteroides fragilis and Bacteroides plebeius decreased in CRC versus controls ( p = 0.0002, p = 0.0002, p = 0.002, p = 0.01, respectively).…”