Immune checkpoint inhibitors (ICIs) are effective agents for tumor immunotherapy. However, their clinical effectiveness is unsatisfactory due to off-target effects and a suppressive immune microenvironment. This study developed a nanodrug delivery system for bladder cancer (BCa) using PCL-MPEG and PCL-PEG-CHO to synthesize internal hydrophobic and external hydrophilic micelles (PP) that encapsulated water-insoluble astragaloside IV (PPA). The aldehyde group on the surface of PPA reacted with the amino group of aPD-L1, allowing the decoration of this antibody on the surface of the micelles. The resultingPPA@aPD-L1effectively piggybacked astragaloside IV and aPD-L1 antibody. These findings suggest that PPA@aPD-L1 is relatively stable in circulation and efficiently binds to BCa cells with the aid of aPD-L1. Additionally, this strategy prolongs the drug’s retention time in tumors. Compared to PBS, PP, and PPA with PPA + aPD-L1 groups, PPA@aPD-L1significantly prolonged the survival of mice with BCa and reduced tumor volume. Mechanistic studies showed that PPA inhibited the NF-κB and STAT3 signaling pathways in tumor cells. Additionally, PPA@aPD-L1increased IFN-γ and decreased IL-10 expression in bladder tumors, affecting the number and type of intratumorally infiltrating T cells. Our study presents a simple and effective drug delivery system that combines herbal monomers with ICIs. It has demonstrated a potent ability to suppress tumor growth and holds potential for future applications.

Natural killer (NK) cells play essential roles in the tumor development, diagnosis, and prognosis of tumors. In this study, we aimed to establish a reliable signature based on marker genes in NK cells, thus providing a new perspective for assessing immunotherapy and the prognosis of patients with gastric cancer (GC). We analyzed a total of 1560 samples retrieved from the public database. We performed a comprehensive analysis of single-cell RNA-sequencing (scRNA-seq) data of gastric cancer and identified 377 marker genes for NK cells. By performing Cox regression analysis, we established a 12-gene NK cell-associated signature (NKCAS) for the Cancer Genome Atlas (TCGA) cohort, that assigned GC patients into a low-risk group (LRG) or a high-risk group (HRG). In the TCGA cohort, the areas under curve (AUC) value were 0.73, 0.81, and 0.80 at 1, 3, and 5 years. External validation of the predictive ability for the signature was then validated in the Gene Expression Omnibus (GEO) cohorts (GSE84437). The expression levels of signature genes were measured and validated in GC cell lines by real-time PCR. Moreover, NKCAS was identified as an independent prognostic factor by multivariate analysis. We combined this with a variety of clinicopathological characteristics (age, M stage, and tumor grade) to construct a nomogram to predict the survival outcomes of patients. Moreover, the LRG showed higher immune cell infiltration, especially CD8+ T cells and NK cells. The risk score was negatively associated with inflammatory activities. Importantly, analysis of the independent immunotherapy cohort showed that the LRG had a better prognosis and immunotherapy response when compared with the HRG. The identification of NK cell marker genes in this study suggests potential therapeutic targets. Additionally, the developed predictive signatures and nomograms may aid in the clinical management of GC.