Qin Huang formula enhances the effect of Adriamycin in B-cell lymphoma via increasing tumor infiltrating lymphocytes by targeting toll-like receptor signaling pathway

Figures

• 

  Fig. 1. Active ingredients and core targets screening. A. The volcano plot displayed the significance and the fold change of differentially expressed genes acquired from the GEO database; The red ones represented up-regulated DEGs (log2(fold change) > 1), while the green ones represented down-regulated DEGs (log2(fold change) < − 1). B. The Venn diagram demonstrates the overlapping of network pharmacology-based targets of QHF components (red color) and transcriptionally dysregulated genes of B-cell lymphoma (turquoise color). C. The Protein-Protein-Interaction (PPI) network of the core genes. D. The core targets and their node degrees. E. The herb-target chord chart displays the relationship of the most involved targets and herbs. F. The drug-disease-target network indicated the relationship between the drugs, compounds, and targets. The pink triangles of the left peripheral circle represented the compounds of QHF, while the four orange octagons represented the four herbs of QHF. The blue arrows of the right peripheral circle represented the core targets of B cell lymphoma

• 

  Fig. 2. Predicted mechanisms of QHF in treating B cell lymphoma. A. The dot plot of GO functional enrichment of QHF. B. The dot plot of KEGG pathway enrichment analysis of QHF. C. The KEGG pathway diagram of Toll-like receptor signaling pathway [49–51]. It shows that QHF could target AKT, NF-κB, p38, ERK, and JNK to activate PI3K/Akt signaling pathway, MAPK, and NF-κB signaling pathways. D. Representative images of molecular docking show that the active components of QHF bind to TLR2, ERK, JNK, and AKT primarily with hydrogen bonds

• 

  Fig. 3. QHF + ADM significantly inhibits the growth of A20 in the tumor-bearing mice model. A. Scheme of the animal experiment protocol. B. Photographs of all the tumor blocks collected from the Control group (n = 5), ADM group (n = 6), and QHF + ADM group (n = 5). C. Tumor volume of the tumor blocks collected from mice on day 12. It showed that QHF + ADM group (n = 5) significantly lowered tumor volume when compared with the control group (n = 5, p < 0.05). But there is no significance between the ADM group (n = 6, p > 0.05) and the control group (n = 5, p > 0.05). D. The tumor volume changes with time of the three groups. The tumor growth of the QHF + ADM group (n = 5) was the slowest of the three groups, followed by the ADM group (n = 5). E. Tumor growth inhibition rate (TGI, %) of the treatment groups. It showed that QHF + ADM (n = 5) could significantly inhibit tumor growth in an A20 murine model (vs. ADM (n = 5), p < 0.01). Data are presented as the mean ± standard errors, *p < 0.05

• 

  Fig. 4. QHF + ADM recruited CD4+ and CD8+ T cells in the A20 tumor sites. A. Representative images of IHC staining for CD4+ T cell among the three groups (200×). B. Bar plot of the positive cell rate of CD4+ T cells of the control group (n = 3), ADM group (n = 3), and QHF + ADM group (n = 3). C. Representative images of IHC staining for CD8+ T cells among the three groups (200×). D. Bar plot of the positive cell rate of CD8+ T cells of the control group (n = 3), ADM group (n = 3), and QHF + ADM group (n = 3). E. Bar plot of TGF-β, IFN-γ, CXCL10, and IL-6 levels based on ELISA of the control group (n = 3), ADM group (n = 3), and QHF + ADM group (n = 3).F. 18F FDG PET-CT scan of the ADM group (n = 1), and QHF + ADM group (n = 1). G. Expression of TLR2, p38 MAPK, and β-actin by western blot. Data are presented as the mean ± standard errors, *p < 0.05; **p < 0.01