Enhanced anticancer effects of a mixture of low-dose mushrooms and Panax ginseng root extracts in human colorectal cancer cells

The inhibitory effect of TU-100 on hepatic stellate cell activation in the tumor microenvironment

INTRODUCTION

The tumor microenvironment is involved in acquiring tumor malignancies of colorectal liver metastasis (CRLM). We have reported that TU-100 (Daikenchuto) suppresses hepatic stellate cell (HSC) activation in obstructive jaundice. In this study, we report new findings as the direct and indirect inhibitory effects of TU-100 on cancer cell growth through the suppression of HSC activation.

MATERIALS AND METHODS

The HSCs (LX2) were cultured in colon cancer cells (HCT116 and HT29)-conditioned medium (CM) with or without TU-100 treatment (90, 270, 900 μg/ml). Activated HSCs (aHSCs) were detected by α-SMA and IL-6 mRNA expressions and cytokine arrays of HSC's culture supernatants. Cancer cell growth was analyzed for proliferation and migration ability, compared with TU-100 treatment. To investigate the direct anti-tumor effect of TU-100, cancer cells were cultured in the presence of aHSC-CM and TU-100 (90, 270, 900) or aHSC-CM alone, and assessed autophagosomes, conversion to LC3-II protein, and Beclin-1 mRNA expression.

RESULTS

Colon cancer-CM significantly increased α-SMA and IL-6 mRNA expressions of aHSC. α-SMA and IL-6 mRNA expressions of aHSC, and IL-6 secretions from aHSCs were significantly decreased with TU-100 (270, 900) treatment, compared to colon cancer-CM alone. Compared with normal culture medium, aHSC-CM led to a significantly increased cell number and modified HSC-CM (TU-100; 270, 900) significantly suppressed cancer cell growth and migration. TU-100 (900) treatment induced autophagy and significantly promoted the autophagic cell death.

CONCLUSIONS

TU-100 inhibited colon cancer cell malignant potential by both suppressing HSC activation and inducing directly autophagy of cancer cells.

Large-Scale Target Identification of Herbal Medicine Using a Reverse Docking Approach

Herbal medicine has been used to countermine various diseases for centuries. However, most of the therapeutic targets underlying herbal therapy remain unclear, which largely slow down the novel drug discovery process from natural products. In this study, we developed a novel computational pipeline for assisting de novo identification of protein targets for herbal ingredients. The pipeline involves pharmacophore comparison and reverse ligand-protein docking simulation in a high throughput manner. We evaluated the pipeline using three traditional Chinese medicine ingredients such as acteoside, quercetin, and epigallocatechin gallate as examples. A majority of current known targets of these ingredients were successfully identified by the pipeline. Structural comparative analyses confirmed that the predicted ligand-target interactions used the same binding pockets and binding modes as those of known ligand-target interactions. Furthermore, we illustrated the mechanism of actions of the ingredients by constructing the pharmacological networks on the basis of the predicted target profiles. In summary, we proposed an efficient and economic option for large-scale target exploration in the herb study. This pipeline will be particularly valuable in aiding precise drug discovery and drug repurposing from natural products.