Identification of microbial markers across populations in early detection of colorectal cancer

Abstract

Associations between gut microbiota and colorectal cancer (CRC) have been widely investigated. However, the replicable markers for early-stage adenoma diagnosis across multiple populations remain elusive. Here, we perform an integrated analysis on 1056 public fecal samples, to identify adenoma-associated microbial markers for early detection of CRC. After adjusting for potential confounders, Random Forest classifiers are constructed with 11 markers to discriminate adenoma from control (area under the ROC curve (AUC) = 0.80), and 26 markers to discriminate adenoma from CRC (AUC = 0.89), respectively. Moreover, we validate the classifiers in two independent cohorts achieving AUCs of 0.78 and 0.84, respectively. Functional analysis reveals that the altered microbiome is characterized with increased ADP-l-glycero-beta-d-manno-heptose biosynthesis in adenoma and elevated menaquinone-10 biosynthesis in CRC. These findings are validated in a newly-collected cohort of 43 samples using quantitative real-time PCR. This work proves the validity of adenoma-specific markers across multi-populations, which would contribute to the early diagnosis and treatment of CRC.

Microbiota and Colorectal Cancer: From Gut to Bedside

“…Moreover, changes in the diversity of bacterial communities in the gut is a common event in colorectal tumours. Specific bacteria, such as Fusobacterium nucleatum and several microbial metabolites have been associated with the onset and progression of this disease ( Yachida et al, 2019 ; Castellarin et al, 2012 ; Kostic et al, 2012 ; Wu et al, 2021 ; Feng et al, 2015 ). Using faecal samples from a large cohort of CRC patients in different stages of disease progression Yachida et al (2019) conducted the largest metagenomics ( n = 616) and metabolomics ( n = 406) analysis on human CRC to date ( Yachida et al, 2019 ).…”

“…The decrease in lactic acid-producing commensals caused by dysbiosis, could lead to progression of early to advanced disease stages ( Feng et al, 2015 ). More recently, bacterial communities were also shown to vary their composition during CRC progression ( Wu et al, 2021 ). By comparing the microbiome in stool samples from 306 adenoma patients, 217 CRC subjects and 252 healthy controls, the authors identified 43 bacteria species with distinguishable differential abundances between controls and patients with adenoma.…”

“…By comparing the microbiome in stool samples from 306 adenoma patients, 217 CRC subjects and 252 healthy controls, the authors identified 43 bacteria species with distinguishable differential abundances between controls and patients with adenoma. Similarly, 114 differentially abundant bacteria were detected between adenoma and cancer ( Wu et al, 2021 ). Of note, Fusobacterium nucleatum was enriched in cancer samples compared to adenoma further confirming previous findings ( Yachida et al, 2019 ).…”

“…The combined data from the aforementioned studies together with the decrease in the costs of sequencing technologies over time, suggests the possibility of using the gut bacteria for diagnostic assessment of disease. In fact, the idea of using bacteria as a non-invasive way to predict disease has been explored in several recent studies and the results seem indeed promising ( Liang et al, 2020 ; Poore et al, 2020 ; Wu et al, 2021 ). Remarkably, by combining the data of the differentially enriched bacteria in different stages of disease together with patient data (such as age, gender and BMI) the authors could successfully distinguish adenoma from healthy control subjects (AUC 0.8) and adenoma from cancer samples (AUC 0.89) ( Wu et al, 2021 ).…”

“…In fact, the idea of using bacteria as a non-invasive way to predict disease has been explored in several recent studies and the results seem indeed promising ( Liang et al, 2020 ; Poore et al, 2020 ; Wu et al, 2021 ). Remarkably, by combining the data of the differentially enriched bacteria in different stages of disease together with patient data (such as age, gender and BMI) the authors could successfully distinguish adenoma from healthy control subjects (AUC 0.8) and adenoma from cancer samples (AUC 0.89) ( Wu et al, 2021 ). Concomitantly, metagenomic analysis of the faecal microbiome of a large cohort of normal controls, adenoma and carcinoma samples allowed the identification of a bacterial gene marker ( m3 ) from a Lachnoclostridium sp .…”