Bojungikki-Tang Augments Pembrolizumab Efficacy in Human PBMC-Injected H460 Tumor-Bearing Mice

Abstract

Bojungikki-Tang (BJIKT) is traditionally used to enhance digestive function and immunity. It has gained attention as a supplement to chemotherapy or targeted therapy owing to its immune-boosting properties. This study aimed to evaluate the synergistic anti-tumor effects of BJIKT in combination with pembrolizumab in a preclinical model. MHC I/II double knockout NSG mice were humanized with peripheral blood mononuclear cells (PBMCs) and injected subcutaneously with H460 lung tumor cells to establish a humanized tumor model. Both agents were administered to evaluate their impact on tumor growth and immune cell behavior. Immunohistochemistry showed decreased exhaustion markers in CD8(+) and CD4(+) T cells within the tumor, indicating enhanced T cell activity. Additionally, RNA sequencing, transcriptome analysis, and quantitative PCR analysis were performed on tumor tissues to investigate the molecular mechanisms underlying the observed effects. The results confirmed that BJIKT improved T cell function and tumor necrosis factor signaling while suppressing transforming growth factor-β signaling. This modulation led to cell cycle arrest and apoptosis. These findings demonstrate that BJIKT, when combined with pembrolizumab, produces significant anti-tumor effects by altering immune pathways and enhancing the anti-tumor immune response. This study provides valuable insights into the role of BJIKT in the tumor microenvironment and its potential to improve therapeutic outcomes.

Keywords: Bojungikki-Tang; anti-tumor; humanized mouse model; immunoregulation; non-small cell lung cancer.

Figure 1

Experimental scheme with a timeline of the mouse experiment. MHC I/II dKO NSG mice humanized with pre-characterized PBMC donors were subcutaneously injected with the human NSCLC cell line H460 (1 × 10⁶ cells). After five days, the mice were segregated into four distinct groups: control, pembrolizumab, BJIKT, and a combination group receiving both BJIKT and pembrolizumab. Treatment consisted of a daily oral administration of 450 mg/kg BJIKT and intraperitoneal injection of 10 mg/kg pembrolizumab every three days.

Figure 2

The combination of BJIKT and pembrolizumab inhibited tumor growth in human PBMC-injected H460 tumor-bearing MHC I/II dKO NSG mice. (A) Tumor volume changes in human PBMC-injected H460 tumor-bearing MHC I/II dKO NSG mice. The tumor sizes were measured twice weekly. (B) Tumor image from each group (n = 5 per group). (C) Tumor weight changes. (D) Representative images of Ki-67 IHC staining and TUNEL staining analysis, and quantitative analysis of both staining (n = 3 per group). Black arrows indicate the marked cells in each image. (E) Body weight changes in human PBMC-injected H460 tumor-bearing MHC I/II dKO NSG mice. Values are presented as the mean ± SD (n = 5 per group). * p < 0.05 compared to the combination group.

Figure 3

The combination of BJIKT and pembrolizumab increased immune cell infiltration in tumors and decreased the exhaustion markers of T cells. (A) IHC staining for CD3, CD4, and CD8 antibodies in tumor tissues. (B) IHC staining using LAG-3, TIGIT, and TIM-3 antibodies in tumor tissues. Black arrows indicate the marked cells in each image. Representative stained sections are shown (scale bar, 50 μm). Values are presented as the mean ± SD (n = 3 per group). * p < 0.05 and ** p < 0.01 compared between each group.

Figure 4

Transcriptome analysis of the combination therapy involving BJIKT and pembrolizumab. (A) A Volcano plot illustrating the variance in gene expression between combination therapy (Comb) involving BJIKT and pembrolizumab (Pemb), in contrast to a single treatment with pembrolizumab. Significantly upregulated and downregulated differentially expressed genes are represented as red and blue dots, respectively. (B–D) GSEA results comparing combination therapy involving BJIKT and pembrolizumab to a single treatment with pembrolizumab. GSEA plots using gene sets associated with (B) the functions of the T cells (“T cell activation”, “T cell differentiation”, and “TCR signaling pathway”); (C) TNF and TGF-β signaling (“TNFR1 signaling pathway”, “TGFBR signaling pathway via SMADS”, and “upregulated genes by TGF-β”); and (D) cell phenotypes (“cell cycle, S phase”, “proliferation”, and “execution phase of apoptosis”). FDR, false discovery rate; NES, normalized enrichment score; Padj, adjusted p-value.

Figure 5

Drug–pathway–gene network analysis for the combination treatment of BJIKT and pembrolizumab. (A) The drug–pathway–gene network was reconstructed through transcriptome data analysis, illustrating the combinatorial effects of BJIKT and pembrolizumab. In this network, each element is distinctly represented: genes are depicted by circles, pathways by squares, and drugs by hexagons. Node color reflects the log₂-transformed fold change (FC) of gene expression levels relative to pembrolizumab monotherapy. The links in the network indicate different types of relationships: an arrow end signifies activating (positive) interactions, a T-shaped end indicates inhibitory (negative) interactions, and a plain line denotes associations. Only significantly changed nodes (|FC| > 1.5, p < 0.05) within the pathway that consistently exhibited the same regulatory pattern as the pathway are shown. (B) Relative mRNA levels of specific genes in activated T cells and H460 cells following treatment with BJIKT. Values are presented as the mean ± SD (n = 3 per group). * p < 0.05, ** p < 0.01, and *** p < 0.001 compared between each group.