The Role of Traditional Chinese Medicine in Cancer Immunotherapy: Current Status and Future Directions.

The tumor microenvironment (TME) plays an important role in the development of tumors. Immunoregulatory cells and cytokines facilitate cancer cells to avoid immune surveillance. Overexpression of immune checkpoint molecules such as CTLA-4 and PD-1/PD-L1 inhibits immune function and enables cancer cells to avoid clearance by the immune system. Thus, minimizing tumor immunosuppression could be an important strategy for cancer therapy. Currently, many immune checkpoint-targeted drugs, such as PD-1/PD-L1 inhibitors, have been approved for marketing and have shown unique advantages in the clinical treatment of cancers. The concept of "strengthening resistance to eliminate pathogenic factors" in traditional Chinese medicine (TCM) is consistent with the immunotherapy of cancer. According to previous studies, the role of TCM in tumor immunotherapy is mainly associated with the positive regulation of natural killer cells, CD8/CD4 T cells, dendritic cells, M2 macrophages, interleukin-2, tumor necrosis factor-[Formula: see text], and IFN-[Formula: see text], as well as with the negative regulation of Tregs, myeloid-derived suppressor cells, cancer-associated fibroblasts, PD-1/PD-L1, transforming growth factor-[Formula: see text], and tumor necrosis factor-[Formula: see text]. This paper summarizes the current research on the effect of TCM targeting the TME, and further introduces the research progress on studying the effects of TCM on immune checkpoints. Modern pharmacological studies have demonstrated that TCM can directly or indirectly affect the TME by inhibiting the overexpression of immune checkpoint molecules and enhancing the efficacy of tumor immunotherapy. TCM with immunomodulatory stimulation could be the key factor to achieve benefits from immunotherapy for patients with non-inflammatory, or "cold", tumors.

Immune checkpoint molecule Tim-3 promotes NKT cell apoptosis and predicts poorer prognosis in Sepsis.

BACKGROUND: Sepsis is a leading cause of death among critically ill patients, which is defined as life-threatening organ dysfunction caused by a deregulated host immune response to infection. Immune checkpoint molecule Tim-3 plays important and complex roles in regulating immune responses and in inducing immune tolerance. Although immune checkpoint blockade would be expected as a promising therapeutic strategy for sepsis, but the underlying mechanism remain unknown, especially under clinical conditions. METHODS: Tim-3 expression and apoptosis in NKT cells were compared in septic patients (27 patients with sepsis and 28 patients with septic shock). Phenotypic and functional characterization of Tim-3+ NKT cells were analysed, and then the relationship between Tim-3 + NKT cells and clinical prognosis were investigated in septic patients. α-lactose (Tim-3/Galectin-9 signalling inhibitor) and Tim-3 mutant mice (targeting mutation of the Tim-3 cytoplasmic domain) were utilized to evaluate the protective effect of Tim-3 signalling blockade following septic challenge. RESULTS: There is a close correlation between Tim-3 expression and the functional status of NKT cells in septic patients, Upregulated Tim-3 expression promoted NKT cell activation and apoptosis during the early stage of sepsis, and it was associated with worse disease severity and poorer prognosis in septic patients. Blockade of the Tim-3/Galectin-9 signal axis using α-lactose inhibited in vitro apoptosis of NKT cells isolated from septic patients. Impaired activity of Tim-3 protected mice following septic challenge. CONCLUSIONS: Overall, these findings demonstrated that immune checkpoint molecule Tim-3 in NKT cells plays a critical role in the immunopathogenesis of septic patients. Blockade of immune checkpoint molecule Tim-3 may be a promising immunomodulatory strategy in future clinical practice for the management of sepsis.

The JAK1/2 inhibitor ruxolitinib downregulates the immune checkpoint protein B7H3 in multiple myeloma.

We hypothesized that ruxolitinib may inhibit the immune checkpoint protein, B7H3; and, thus, investigated its effects on this immune inhibitor using multiple myeloma (MM) cell lines, bone marrow (BM) mononuclear cells from MM patients and human MM LAGλ -1A xenografts. Ruxolitinib reduced B7H3 gene and protein expression and increased IL-2 and CD8 gene expression. These results suggest that ruxolitinib inhibition of B7H3 may restore exhausted T-cell activity in the MM BM tumor microenvironment.

Development of a Non-IgG PD-1/PD-L1 Inhibitor by in Silico Mutagenesis and an In-Cell Protein-Protein Interaction Assay.

Inhibiting the programmed death-1 (PD-1)/programmed death ligand 1 (PD-L1) axis by monoclonal antibodies (mAbs) is a successful cancer immunotherapy. However, mAb-based drugs have various disadvantages including high production costs and large molecular sizes, which motivated us to develop a smaller alternative drug. Since PD-L1 binds PD-1 with moderate affinity, a higher affinity PD-1 variant should serve as a competitive inhibitor of the wild-type PD-1/PD-L1 interaction. In this report, we conducted in silico point mutagenesis of PD-1 to identify potent PD-1 variants with a higher affinity toward PD-L1 and refined the in silico results using a luciferase-based in-cell protein-protein interaction (PPI) assay. As a result, a PD-1 variant was developed that had two mutated amino acids (T76Y, A132V), termed 2-PD-1. 2-PD-1 could bind with PD-L1 at a dissociation constant of 12.74 nM. Moreover, 2-PD-1 successfully inhibited the PD-1/PD-L1 interaction with a half maximal inhibitory concentration of 19.15 nM and reactivated the T cell with a half maximal effective concentration of 136.1 nM. These results show that in silico mutagenesis combined with an in-cell PPI assay verification strategy successfully prepared a non-IgG inhibitor of the PD-1/PD-L1 interaction.

QSP-IO: A Quantitative Systems Pharmacology Toolbox for Mechanistic Multiscale Modeling for Immuno-Oncology Applications.

Immunotherapy has shown great potential in the treatment of cancer; however, only a fraction of patients respond to treatment, and many experience autoimmune-related side effects. The pharmaceutical industry has relied on mathematical models to study the behavior of candidate drugs and more recently, complex, whole-body, quantitative systems pharmacology (QSP) models have become increasingly popular for discovery and development. QSP modeling has the potential to discover novel predictive biomarkers as well as test the efficacy of treatment plans and combination therapies through virtual clinical trials. In this work, we present a QSP modeling platform for immuno-oncology (IO) that incorporates detailed mechanisms for important immune interactions. This modular platform allows for the construction of QSP models of IO with varying degrees of complexity based on the research questions. Finally, we demonstrate the use of the platform through two example applications of immune checkpoint therapy.