Multi-omics and network pharmacology reveal the mechanisms of Scutellaria barbata D.Don and Scleromitrion diffusum (Willd.) R.J.Wang against pancreatic cancer

Pancreatic cancer (PC) is a common gastrointestinal malignancy whose initiation and progression may be closely linked to the gut microbiota. Previous research indicates that Scutellaria barbata D. Don and Scleromitrion diffusum (Willd.) R.J. Wang (SB-SD) exhibit diverse biological activities, such as anti-inflammatory, antioxidant, and antitumor effects, though their precise regulatory mechanisms are not fully elucidated. Here, we treated PC cells with SB-SD to assess its impact on cell viability, apoptosis, migration, and cell cycle progression, while Western blotting analyzed the expression of HSP90AA1, MAPK3, p53, CDK1, and p21. We also established a pancreatic cancer xenograft model in nude mice to evaluate the in vivo inhibitory effect of SB-SD on tumor growth. Furthermore, we employed metagenomic sequencing, untargeted metabolomics, and quantitative proteomics to comprehensively profile changes in the gut microbiota, serum metabolites, and differentially expressed proteins, with Western blotting subsequently validating BCKDK, GATM and p53 expression. The results show that SB-SD significantly inhibited PC cell proliferation, promoted apoptosis, and induced S/G2 phase cell cycle arrest, potentially via modulation of the HSP90AA1/MAPK3 signaling pathway. Measurements of tumor volume and weight, complemented by histopathological analysis, confirmed that SB-SD effectively suppressed the growth of PANC-1 xenograft tumors. Integrated multi-omics analyses suggest that the antitumor effects of SB-SD may involve the modulation of key gut microbes like Bacteroides caccae and Lactobacillus, the promotion of choline metabolism, and the regulation of BCKDK and GATM. Together, these findings not only corroborate the direct antitumor activity of SB-SD against pancreatic cancer but also offer novel mechanistic insights by constructing a microbiota-metabolite-protein interaction network.