Comparative Analysis of Fecal Microbiota in Healthy Controls and Pancreatic Cancer Patients: A Focus on Tumor...

Pancreatic cancer (PC) remains one of the most lethal malignancies worldwide, characterized by late-stage diagnosis and a poor prognosis. This study explores the clinical, biochemical, and gut microbiota differences between PC patients and healthy controls (CTRL), as well as between subgroups of PC patients with pancreatic head cancer (PHC) and pancreatic body-tail cancer (PBTC).

A total of 72 PC patients and 37 CTRL subjects were included, with further stratification of PC patients into 45 PHC and 27 PBTC cases. Clinical and biochemical data were collected. Gut microbiota was analyzed by 16S rRNA gene sequencing. Alpha-diversity indices, Firmicutes/Bacteroidetes ratio and taxonomic composition were evaluated and compared in all the experimental group. Correlation analyses were performed between specific bacterial taxa and biochemical markers and a Random Forest algorithm was applied to identify taxa discriminating PC from CTRL and PHC from PBTC.

Clinical and biochemical data revealed significant heterogeneity between groups, with PHC patients exhibiting higher markers of inflammation and liver dysfunction, while PBTC patients showed relatively preserved physiological status. Gut microbiota analysis revealed significant dysbiosis in PC patients compared to CTRL. Alpha-diversity indices demonstrated reduced species evenness in PC patients, while the Firmicutes/Bacteroidetes ratio was significantly lower. Taxonomic composition analysis indicated enrichment of pro-inflammatory taxa and depletion of beneficial SCFA-producing genera. However, subgroup comparisons revealed distinct microbial profiles, with PHC patients enriched in taxa associated with localized inflammation and PBTCs showing higher levels of anti-inflammatory and SCFA-producing bacteria. A correlation analysis linked specific bacteria to markers of liver dysfunction and systemic inflammation, such as GGT, ALP, and ESR, while SCFA-producing taxa correlated negatively with inflammatory markers. A Random Forest algorithm identified key microbial taxa discriminating PC patients from CTRL and PHC from PBTC.

These findings highlight the interplay between microbiota composition, tumor localization, and systemic inflammation, showing a potential for microbiota-based diagnostics and interventions in PC.