Metagenomic Microbial Signatures for Noninvasive Detection of Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with poor early detection rates owing to the limited sensitivity and specificity of the current biomarker CA19-9. Gut microbiota dysbiosis plays a key role in PDAC pathogenesis. This study aimed to evaluate the noninvasive approach we developed, combining metagenome-derived microbial signatures with CA19-9, to improve PDAC detection. This study included 50 treatment-naïve patients with PDAC and their matched controls. Fecal samples were analyzed using shotgun metagenomic sequencing. Machine learning algorithms were used to develop and validate a diagnostic panel integrating microbial signatures and CA19-9 levels. Subgroup analyses were used to confirm the robustness of the microbial markers. The combined models at both species and genus levels effectively distinguished patients with PDAC from healthy individuals, and their strong diagnostic efficacy and accuracy were demonstrated through rigorous validation. In conclusion, the combination of gut microbiome profiling and CA19-9 improves PDAC detection accuracy compared to the use of CA19-9 alone, showing promise for early and noninvasive diagnosis.