Background: Targeting tumor microenvironment (TME) may provide therapeutic activity and selectivity in treating cancers. Therefore, an improved understanding of the mechanism by which drug targeting TME would enable more informed and effective treatment measures. Glycyrrhiza uralensis Fisch (GUF, licorice), a widely used herb medicine, has shown promising immunomodulatory activity and anti-tumor activity. However, the molecular mechanism of this biological activity has not been fully elaborated. Methods: Here, potential active compounds and specific targets of licorice that trigger the antitumor immunity were predicted with a systems pharmacology strategy. Flow cytometry technique was used to detect cell cycle profile and CD8⁺ T cell infiltration of licorice treatment. And anti-tumor activity of licorice was evaluated in the C57BL/6 mice. Results: We reported the G0/G1 growth phase cycle arrest of tumor cells induced by licorice is related to the down-regulation of CDK4-Cyclin D1 complex, which subsequently led to an increased protein abundance of PD-L1. Further, in vivo studies demonstrated that mitigating the outgrowth of NSCLC tumor induced by licorice was reliant on increased antigen presentation and improved CD8⁺ T cell infiltration. Conclusions: Briefly, our findings improved the understanding of the anti-tumor effects of licorice with the systems pharmacology strategy, thereby promoting the development of natural products in prevention or treatment of cancers.

In the tumor microenvironment (TME), the activation of programmed death-1 (PD-1)–programmed death ligand-1 (PD-L1) pathway is one of the main signals of immune escape and tumor deterioration. Clinically, the application of monoclonal antibodies slows down the progression of various malignancies and prolongs the survival of patients effectively. However, these treatments result in serious immune-related adverse events (irAEs) owning to systemic immune activation. Therefore, to achieve long-term therapeutic effects and low side effects, it is necessary to find drugs inhibiting the local PD-1/PD-L1 signaling pathway of the TME. Here, we discovered that Platycodon grandiflorum (PG), a medicine and food homology herb, reduced the expression of PD-1 on the surface of CD8⁺ T cells to exert antitumor effects in non-small cell lung cancer (NSCLC). Firstly, by combining systems pharmacology strategies and clinical data analysis, we found that PG has the potential to immunomodulate T cells and suppress tumors. Secondly, in vivo and in vitro experiments have confirmed the antitumor effect of the combination of Platycodin D and Platycodin D3, which is preferred and representative of the compounds. Mechanistically, PG increased the infiltration and killing activity of CD8⁺ T cells, which was related to the decrease of PD-1⁺ CD8⁺ T cells. Furthermore, we confirmed that PG regulated the expression of PD-1 on the surface of CD8⁺ T cells via reducing the secretion of VEGF-A regulated by the level of P-STAT3 in tumor cells. Additionally, PG also positively impacted the biological processes downstream of STAT3. Overall, we demonstrated that PG-mediated downregulation of PD-1 on the surface of CD8⁺ T cells represents a promising strategy to locally enhance T-cell responses and improve antitumor immunity.

Targeting tumor microenvironment (TME), such as immune checkpoint blockade (ICB), has achieved increased overall response rates in many advanced cancers, such as non-small cell lung cancer (NSCLC), however, only in a fraction of patients. To improve the overall and durable response rates, combining other therapeutics, such as natural products, with ICB therapy is under investigation. Unfortunately, due to the lack of systematic methods to characterize the relationship between TME and ICB, development of rational immune-combination therapy is a critical challenge. Here, we proposed a systems pharmacology strategy to identify resistance regulators of PD-1/PD-L1 blockade and develop its combinatorial drug by integrating multidimensional omics and pharmacological methods. First, a high-resolution TME cell atlas was inferred from bulk sequencing data by referring to a high-resolution single-cell data and was used to predict potential resistance regulators of PD-1/PD-L1 blockade through TME stratification analysis. Second, to explore the drug targeting the resistance regulator, we carried out the large-scale target fishing and the network analysis between multi-target drug and the resistance regulator. Finally, we predicted and verified that oxymatrine significantly enhances the infiltration of CD8⁺ T cells into TME and is a powerful combination agent to enhance the therapeutic effect of anti-PD-L1 in a mouse model of lung adenocarcinoma. Overall, the systems pharmacology strategy offers a paradigm to identify combinatorial drugs for ICB therapy with a systems biology perspective of drug-target-pathway-TME phenotype-ICB combination.

Rapid development of high-throughput technologies has permitted the identification of an increasing number of disease-associated genes (DAGs), which are important for understanding disease initiation and developing precision therapeutics. However, DAGs often contain large amounts of redundant or false positive information, leading to difficulties in quantifying and prioritizing potential relationships between these DAGs and human diseases. In this study, a network-oriented gene entropy approach (NOGEA) is proposed for accurately inferring master genes that contribute to specific diseases by quantitatively calculating their perturbation abilities on directed disease-specific gene networks. In addition, we confirmed that the master genes identified by NOGEA have a high reliability for predicting disease-specific initiation events and progression risk. Master genes may also be used to extract the underlying information of different diseases, thus revealing mechanisms of disease comorbidity. More importantly, approved therapeutic targets are topologically localized in a small neighborhood of master genes in the interactome network, which provides a new way for predicting drug-disease associations. Through this method, 11 old drugs were newly identified and predicted to be effective for treating pancreatic cancer and then validated by in vitro experiments. Collectively, the NOGEA was useful for identifying master genes that control disease initiation and co-occurrence, thus providing a valuable strategy for drug efficacy screening and repositioning. NOGEA codes are publicly available at https://github.com/guozihuaa/NOGEA.

Advances in single-cell and spatial technologies have transformed the dissection of cell composition and tissue architecture in complex biological systems. However, identifying rare cells critical to disease pathogenesis and biological processes remains difficult, as their low abundance often masks them among dominant cell populations. We introduce RareQ, a fast and scalable framework for rare cell detection by evaluating cliquishness of each cell’s k -nearest neighborhood using single-cell omics data. Extensive benchmarking on diverse simulated and real datasets demonstrates that RareQ exceeds existing methods in accuracy, sensitivity, and efficiency. RareQ also excels at identifying both modality-specific and shared rare cells. Its versatility across various biological contexts enables the discovery of functionally distinct rare cells with unique molecular signatures in physiological and pathological context. RareQ’s application to spatial transcriptomics data reveals anatomically distinct and clinically relevant rare cell populations. Together, RareQ offers an efficient approach for rare cell discovery, enhancing insights into tissue organization and disease mechanisms.