Additional file 1 of Gut microbiota and metabolites signatures of clinical response in anti-PD-1/PD-L1 based immunotherapy of biliary tract cancer
Creators: name: Zhu, Chengpei
name: Wang, Yunchao
name: Zhu, Ruijuan
name: Wang, Shanshan
name: Xue, Jingnan
name: Zhang, Dongya
name: Lan, Zhou
name: Zhang, Chenchen
name: Liang, Yajun
name: Zhang, Nan
name: Xun, Ziyu
name: Zhang, Longhao
name: Ning, Cong
name: Yang, Xu
name: Chao, Jiashuo
name: Long, Junyu
name: Yang, Xiaobo
name: Wang, Hanping
name: Sang, Xinting
name: Jiang, Xianzhi
name: Zhao, Haitao
Publisher: name: figshare
Year: 2024
Subjects: subject: Biochemistry
subject: Medicine
subject: Microbiology
subject: FOS: Biological sciences
subject: Cell Biology
subject: Biotechnology
subject: Chemical Sciences not elsewhere classified
subject: Ecology
subject: Immunology
subject: FOS: Clinical medicine
subject: Cancer
subject: Computational Biology

description: Supplementary Table S1. Types of therapeutic regimen of the study population with 88 biliary tract cancer patients Supplementary Table S2. The influence of clinical factors to gut microbiota by PERMANOVA based on species Supplementary Table S3. Gut microbiome composition at the phylum level in the DCB and NDB group Supplementary Table S4. Gut microbiome composition at the species level in the DCB and NDB group Supplementary Table S5. Gut microbiome composition at the genus level in the DCB and NDB group Supplementary Table S6. Gut microbiome composition at the class level in the DCB and NDB group Supplementary Table S7. Gut microbiome composition at the order level in the DCB and NDB group Supplementary Table S8. Gut microbiome composition at the family level in the DCB and NDB group Supplementary Table S9. Summary of 24 significantly differential metabolites Supplementary Table S10. Dynamic microbial composition in the DCB and NDB group at the species level Supplementary Table S11. Dynamic microbial composition in the DCB and NDB group at the phylum level Supplementary Table S12. Quantity summary of differential enriched metabolites from Point 1 to Point 6 Supplementary Table S13. 20 survival associated differential taxa Supplementary Table S14. Clinical characteristics of the study population in train and test sets. Supplementary Table S15. The performances of all prediction models by Random Forest Analysis. Supplementary Table S16. Differential kegg pathways for metagenomic sequencing Supplementary Table S17. Differential metacyc pathways for metagenomic sequencing Supplementary Table S18. Enrichment metabolic pathways for differential metabolite annotation Supplementary Table S19. The contribution of different clinical factors to the analysis of CCA based on species Supplementary Table S20. The contribution of different clinical factors to the analysis of CCA based on 20 survival differential taxa Supplementary Fig. S1 Study workflow Supplementary fig. S2 The alpha diversity and beta diversity between DCB and NDB group based on species. (A) Alpha diversity. (B)Principal coordinate analysis (PCoA) of beta diversity measurements by Bray-Curtis distances. ANOSIM, R = 0.04, P = 0.025. (C)Beta diversity. Supplementary fig. S3 gut microbiome composition in the DCB and NDB group (A)Venn diagram of common and unique species. (B)Gut microbiome composition at the phylum level. (C)Bacteroidetes/Firmicutes ratio (B/F). (D)Gut microbiome composition at the species level. The inner circle shows the species belonging to NDB, and the outer circle shows the species belonging to DCB. (E)The composition of the top 20 species of each baseline sample. Gut microbiome composition at the genus (F), class (G), order (H), and family (I) level. Supplementary fig. S4 significantly different abundant taxa in the DCB group and NDB (A)All enriched taxa in DCB or NDB group. (B)Relative expression abundances in the DCB and NDB group based on species. Supplementary fig. S5 Differential metabolites for group DCB vs. NDB (A)Score scatter plot of PCA. (B)Score scatter plot of OPLS-DA model. (C)Permutation test of OPLS-DA model. (D)OPLS-DA S-plot. (E)Heatmap of hierarchical clustering analysis. (F)Radar chart analysis. (G)VIP scores. (H)Violin Plot of differential metabolites. (I)Z-score of differential metabolites. Supplementary Fig. S6 Dynamic point analysis in DCB and NDB groups. (A)Dynamic microbial composition at the species level. (B) Dynamic point alpha diversity based on species_shannon. (C) Dynamic point beta diversity based on species_Bray-Curtis distances. (D) Differential taxa and metabolites from Point 1 to Point 6. Blue font represents differential taxa, and red represents differential metabolites. Supplementary fig. S7 functional annotation of metagenomic and metabolomics (A)Significantly different KO genes in the DCB and NDB group. The alpha diversity and beta diversity between DCB and NDB group based on Kegg pathway (B), ko gene (C), and metabolic pathway (D). Supplementary fig. S8 correlations between microbes and metabolites (A) Cooccurrence network of enrichment metabolic pathways by LC-MS/MS analysis. (B) KO00260 pathway co-plotted the differential KO gene and metabolites. Red indicates that the DCB group is significantly higher than the NDB group; green indicates that it is significantly lower in the DCB group than in the NDB group; pink indicates that it was higher in the DCB group than in the NDB group but not significant; bright green indicates that the DCB group is lower than the NDB group but not significant. (C)Correlations analysis of all differential species and differential metabolites. Supplementary fig. S9 gut microbiome distribution was affected by clinical factors Canonical correspondence analysis (CCA) with permutation test showed the clinical factors associated with the distribution of patients with BTC, the different species enriched in the DCB and NDB group, and contribution of different clinical factors to CCA for all differential taxa (A) and survival differential taxa (B). *P &lt; 0.05. Supplementary fig. S10 Correlations of clinical factors with differential metabolites and survival associated differentially taxa (Spearman’s rank correlation with two-tailed P values). *P &lt; 0.05; **P &lt; 0.01; ***P &lt; 0.001. Supplementary Fig. S11 Comparison of intergroup differences between cholangiocarcinoma and gallbladder cancer. (A-B)Principal Coordinate analysis (PCoA) based on Bray-Curtis distances between cholangiocarcinoma (CCA) and gallbladder cancer (GBC) groups. (C) Comparison of PCoA between the four groups (CCA_DCB, CCA_NDB, GBC_DCB, and GBC_NDB). Supplementary Fig. S12 The differences between the DCB and NDB groups based on gut fungi. (A) alpha diversity. (B) Beta diversity. (C) Significantly different fungi. (D) Association analysis of differential fungi with differential bacteria and metabolites.