Mechanism of the synergistic enhancement of response to immunotherapy in advanced cholangiocarcinoma based on microbial immunometabolomics.

Abstract

e13651 Background: Intrahepatic cholangiocarcinoma (ICC) is a highly aggressive liver tumor with poor prognosis, and its incidence is gradually increasing worldwide. The gut microbiome is closely related to the host's immune response and may influence tumor progression and treatment response. The composition and function of the microbiome play significant roles in the tumor microenvironment. Previous studies have shown that specific microbial communities are associated with the occurrence and progression of cancer. As an important metabolic product, bile acids are involved in regulating the interactions between the gut microbiome and the host. Alterations in bile acid metabolism may affect the efficacy of immunotherapy. Methods: In this study, we included 78 patients with advanced ICC, collecting fecal and blood samples before immunotherapy. Based on treatment response, patients were divided into a sustained benefit group and a non-sustained benefit group. We applied bioinformatics methods to analyze the significant differences in microbial diversity, community structure, and composition between the two groups using metagenomic sequencing of fecal samples and bile acid metabolism sequencing of blood samples. The results showed that, compared to the non-sustained benefit group, the sustained benefit group had significantly elevated levels of Romboutsia timonensis, Hominilimicola fabiformis, and Alistipes sp. CAG:53, while bacterium P3, Turicibacter sp. TC023, and Prevotella micans were significantly reduced. Additionally, pathway enrichment analysis indicated that the hypoxia-inducible factor 1 (HIF-1) signaling pathway was closely associated with treatment benefit. Results: The study results demonstrated that the bile acid metabolism in the sustained benefit group was significantly better than that in the non-sustained benefit group, specifically showing elevated levels of T-alpha-MCA, TLCA-3S, GCA, TCA, TCDCA, TCDCA-3S, GCDCA-3S, GCA-3S, NorCA, and THCA. These findings not only provide new perspectives for understanding biomarkers in ICC patients undergoing immunotherapy but also offer feasible directions for future research. By jointly analyzing the microbiome and bile acid metabolism, we constructed a predictive model regarding immunotherapy in advanced intrahepatic cholangiocarcinoma, which may provide new tools for clinical practice to improve treatment efficacy and patient survival. Conclusions: Through multi-omics analysis of immunotherapy in advanced intrahepatic cholangiocarcinoma, we constructed a clinical predictive model for predicting the efficacy of immunotherapy.