Optimizing Fecal Occult Blood Test (FOBT) Colorectal Cancer Screening Using Gut Bacteriome as a Biomarker.
16S rRNA gene sequencing
Lesion grade
iFOBT screening
Journal
Clinical colorectal cancer
ISSN: 1938-0674
Titre abrégé: Clin Colorectal Cancer
Pays: United States
ID NLM: 101120693
Informations de publication
Date de publication:
13 Oct 2023
13 Oct 2023
Historique:
received:
21
06
2023
revised:
03
10
2023
accepted:
05
10
2023
medline:
19
11
2023
pubmed:
19
11
2023
entrez:
18
11
2023
Statut:
aheadofprint
Résumé
Colorectal cancer (CRC) is a major cause of cancer mortality in the world. One of the most widely used screening tests for CRC is the immunochemical fecal occult blood test (iFOBT), which detects human hemoglobin from patient's stool sample. Although it is highly efficient in detecting blood from patients with gastro-intestinal lesions, such as polyps and cancers, the iFOBT has a high rate of false positive discovery. Recent studies suggested gut bacteria as a promising noninvasive biomarker for improving the diagnosis of CRC. In this study, we examined the composition of gut bacteria using iFOBT leftover from patients undergoing screening test along with a colonoscopy. After collecting data from more than 800 patients, we considered 4 groups for this study. The first and second groups were respectively "healthy" in which the patients had either no blood in their stool or had blood but no lesions. The third and fourth groups of patients had both blood in their stools with precancerous and cancerous lesions and considered either as low-grade and high-grade lesion groups, respectively. An amplification of 16S rRNA (V4 region) gene was performed, followed by sequencing along with various statistical and bioinformatic analysis. We analyzed the composition of the gut bacteriome at phylum, class, genus, and species levels. Although members of the Firmicute phylum increased in the 3 groups compared to healthy patients, the phylum Actinobacteriota was found to decrease. Moreover, Blautia obeum and Anaerostipes hadrus from the phylum Firmicutes were increased and Collinsella aerofaciens from phylum Actinobacteriota was found decreased when healthy group is compared to the patients with high-grade lesions. Finally, among the 5 machine learning algorithms used to perform our analysis, both elastic net (AUC > 0.7) and random forest (AUC > 0.8) performs well in differentiating healthy patients from 3 other patient groups having blood in their stool. Our study integrates the iFOBT screening tool with gut bacterial composition to improve the prediction of CRC lesions.
Sections du résumé
BACKGROUND
BACKGROUND
Colorectal cancer (CRC) is a major cause of cancer mortality in the world. One of the most widely used screening tests for CRC is the immunochemical fecal occult blood test (iFOBT), which detects human hemoglobin from patient's stool sample. Although it is highly efficient in detecting blood from patients with gastro-intestinal lesions, such as polyps and cancers, the iFOBT has a high rate of false positive discovery. Recent studies suggested gut bacteria as a promising noninvasive biomarker for improving the diagnosis of CRC. In this study, we examined the composition of gut bacteria using iFOBT leftover from patients undergoing screening test along with a colonoscopy.
METHODS
METHODS
After collecting data from more than 800 patients, we considered 4 groups for this study. The first and second groups were respectively "healthy" in which the patients had either no blood in their stool or had blood but no lesions. The third and fourth groups of patients had both blood in their stools with precancerous and cancerous lesions and considered either as low-grade and high-grade lesion groups, respectively. An amplification of 16S rRNA (V4 region) gene was performed, followed by sequencing along with various statistical and bioinformatic analysis.
RESULTS
RESULTS
We analyzed the composition of the gut bacteriome at phylum, class, genus, and species levels. Although members of the Firmicute phylum increased in the 3 groups compared to healthy patients, the phylum Actinobacteriota was found to decrease. Moreover, Blautia obeum and Anaerostipes hadrus from the phylum Firmicutes were increased and Collinsella aerofaciens from phylum Actinobacteriota was found decreased when healthy group is compared to the patients with high-grade lesions. Finally, among the 5 machine learning algorithms used to perform our analysis, both elastic net (AUC > 0.7) and random forest (AUC > 0.8) performs well in differentiating healthy patients from 3 other patient groups having blood in their stool.
CONCLUSION
CONCLUSIONS
Our study integrates the iFOBT screening tool with gut bacterial composition to improve the prediction of CRC lesions.
Identifiants
pubmed: 37980216
pii: S1533-0028(23)00091-9
doi: 10.1016/j.clcc.2023.10.004
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
Copyright © 2023 Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Disclosure The authors have stated that they have no conflicts of interest.