A homologous and molecular dual-targeted biomimetic nanocarrier for EGFR-related non-small cell lung cancer therapy.

The abnormal activation of epidermal growth factor receptor (EGFR) drives the development of non-small cell lung cancer (NSCLC). The EGFR-targeting tyrosine kinase inhibitor osimertinib is frequently used to clinically treat NSCLC and exhibits marked efficacy in patients with NSCLC who have an EGFR mutation. However, free osimertinib administration exhibits an inadequate response in vivo, with only ∼3% patients demonstrating a complete clinical response. Consequently, we designed a biomimetic nanoparticle (CMNP@Osi) comprising a polymeric nanoparticle core and tumor cell-derived membrane-coated shell that combines membrane-mediated homologous and molecular targeting for targeted drug delivery, thereby supporting a dual-target strategy for enhancing osimertinib efficacy. After intravenous injection, CMNP@Osi accumulates at tumor sites and displays enhanced uptake into cancer cells based on homologous targeting. Osimertinib is subsequently released into the cytoplasm, where it suppresses the phosphorylation of upstream EGFR and the downstream AKT signaling pathway and inhibits the proliferation of NSCLC cells. Thus, this dual-targeting strategy using a biomimetic nanocarrier can enhance molecular-targeted drug delivery and improve clinical efficacy.

Combining autophagy and immune characterizations to predict prognosis and therapeutic response in lung adenocarcinoma.

Background: Autophagy, a key regulator of programmed cell death, is critical for maintaining the stability of the intracellular environment. Increasing evidence has revealed the clinical importance of interactions between autophagy and immune status in lung adenocarcinoma. The present study evaluated the potential of autophagy-immune-derived biomarkers to predict prognosis and therapeutic response in patients with lung adenocarcinoma. Methods: Patients from the GSE72094 dataset were randomized 7:3 to a training set and an internal validation set. Three independent cohorts, TCGA, GSE31210, and GSE37745, were used for external verification. Unsupervised hierarchical clustering based on autophagy- and immune-associated genes was used to identify autophagy- and immune-associated molecular patterns, respectively. Significantly prognostic autophagy-immune genes were identified by LASSO analysis and by univariate and multivariate Cox regression analyses. Differences in tumor immune microenvironments, functional pathways, and potential therapeutic responses were investigated to differentiate high-risk and low-risk groups. Results: High autophagy status and high immune status were associated with improved overall survival. Autophagy and immune subtypes were merged into a two-dimensional index to characterize the combined prognostic classifier, with 535 genes defined as autophagy-immune-related differentially expressed genes (DEGs). Four genes (C4BPA, CD300LG, CD96, and S100P) were identified to construct an autophagy-immune-related prognostic risk model. Survival and receiver operating characteristic (ROC) curve analyses showed that this model was significantly prognostic of survival. Patterns of autophagy and immune genes differed in low- and high-risk patients. Enrichment of most immune infiltrating cells was greater, and the expression of crucial immune checkpoint molecules was higher, in the low-risk group. TIDE and immunotherapy clinical cohort analysis predicted that the low-risk group had more potential responders to immunotherapy. GO, KEGG, and GSEA function analysis identified immune- and autophagy-related pathways. Autophagy inducers were observed in patients in the low-risk group, whereas the high-risk group was sensitive to autophagy inhibitors. The expression of the four genes was assessed in clinical specimens and cell lines. Conclusions: The autophagy-immune-based gene signature represents a promising tool for risk stratification in patients with lung adenocarcinoma, guiding individualized targeted therapy or immunotherapy.

Antiviral treatment for hepatitis C is associated with a reduced risk of atherosclerotic cardiovascular outcomes: A systematic review and meta-analysis.

Hepatitis C virus infection (HCV) may be associated with a greater risk of cardiovascular disease (CVD), and the evidence for whether antiviral therapy for HCV could reduce the risk of CVD events is inconsistent. The aim of this meta-analysis was to investigate the association between anti-HCV treatment and the risk of CVD. We searched PubMed, EMBASE and Cochrane Library databases from inception to 20 August 2020. The pooled hazard ratio (HR) with 95% confidence interval (CI) of the risk of CVD events [any CVD, coronary artery disease (CAD) and stroke] was calculated using the random-effects model. A total of eleven studies, including 309,470 subjects, were enrolled in this meta-analysis. Among those, four studies reported on any CVD between anti-HCV-treated and anti-HCV-untreated patients, five studies reported on CAD, and five studies reported on stroke. Also, five studies reported on any CVD between patients with sustained virological response (SVR) and without SVR. Overall, antiviral therapy for HCV was associated with a reduced risk of any CVD (HR = 0.64, 95% CI: 0.50-0.83), CAD (HR = 0.73, 95% CI: 0.55-0.96) and stroke (HR = 0.74, 95% CI: 0.64-0.86). Besides, we found that SVR was associated with a significant decrease in any CVD compared with non-SVR (HR = 0.74, 95% CI: 0.60-0.92). In conclusion, this meta-analysis demonstrated that antiviral therapy for HCV was associated with a reduced risk of CVD events. In addition, the risk of CVD events was lower in individuals with SVR compared with those without SVR.