Ece Karta et al.
Background Recent evidence suggests a role for the microbiome in pancreatic ductal adenocarcinoma (PDAC) aetiology and progression.
Objective To explore the faecal and salivary microbiota as potential diagnostic biomarkers.
Methods We applied shotgun metagenomic and 16S rRNA amplicon sequencing to samples from a Spanish case–control study (n=136), including 57 cases, 50 controls, and 29 patients with chronic pancreatitis in the discovery phase, and from a German case–control study (n=76), in the validation phase.
Results Faecal metagenomic classifiers performed much better than saliva-based classifiers and identified patients with PDAC with an accuracy of up to 0.84 area under the receiver operating characteristic curve (AUROC) based on a set of 27 microbial species, with consistent accuracy across early and late disease stages. Performance further improved to up to 0.94 AUROC when we combined our microbiome-based predictions with serum levels of carbohydrate antigen (CA) 19–9, the only current non-invasive, Food and Drug Administration approved, low specificity PDAC diagnostic biomarker. Furthermore, a microbiota-based classification model confined to PDAC-enriched species was highly disease-specific when validated against 25 publicly available metagenomic study populations for various health conditions (n=5792). Both microbiome-based models had a high prediction accuracy on a German validation population (n=76). Several faecal PDAC marker species were detectable in pancreatic tumour and non-tumour tissue using 16S rRNA sequencing and fluorescence in situ hybridisation.
Conclusion Taken together, our results indicate that non-invasive, robust and specific faecal microbiota-based screening for the early detection of PDAC is feasible.
Significance of this study
What is already known about this subject?
Pancreatic ductal adenocarcinoma (PDAC) is on the rise worldwide, posing a high disease burden and mortality rate, yet accurate, non-invasive diagnostic options remain unavailable.
Alterations in the oral, faecal and pancreatic microbiome composition have been associated with an increased risk of PDAC.
What are the new findings?
Stool microbiota-based classifiers are described that predict PDAC with high accuracy and specificity, independent of disease stage, with potential as agents for non-invasive diagnostics.
A faecal metagenomic classifier identified PDAC with an accuracy of 0.84 area under the receiver operating characteristic curve (AUROC) in a Spanish cohort, based on 27 species. The accuracy improved to up to 0.94 AUROC when combined with the less specific carbohydrate antigen (CA) 19–9 serum marker.
The classifier was validated in an independent German PDAC cohort (0.83 AUROC), and PDAC disease specificity was confirmed against 25 publicly available metagenomic study populations with various health conditions (n=5792).
The presence of marker taxa enriched in faecal samples (Veillonella, Streptococcus, Akkermansia) and also taxa with differential abundance in healthy and tumour pancreatic tissues (Bacteroides, Lactobacillus, Bifidobacterium) was validated by fluorescence in situ hybridisation.
Significance of this study
How might it impact on clinical practice in the foreseeable future?
Faecal microbiome-based detection of PDAC may provide a non-invasive, cost-effective and robust approach to early PDAC diagnosis.
The presented PDAC-specific microbiome signatures, including links between microbial populations across tissues, provide novel microbiome-related hypotheses regarding disease aetiology, prevention and possible therapeutic intervention.
LEGGI TUTTO http://dx.doi.org/10.1136/gutjnl-2021-326710