Objective and aims: Osteopontin (OPN), an oxidant stress sensitive cytokine, plays a central role in liver fibrosis. While OPN expression can be reduced by small interfering RNA (siRNA), the challenge to deliver siRNA safely and effectively into liver remains unresolved. Exosomes are promising natural nanocarriers for drug delivery that are able to enter cells with different biological barriers efficiently. In this study, we used exosomes as a delivery vehicle to target OPN in liver fibrosis.Methods: Exosomes selectively home to fibrotic liver according to small animal imaging system. Electroporation technique was used to engineer exosomes to carry siRNA targeting OPN (ExosiRNA−OPN). Primary hepatic stellate cells (HSCs) were isolated and treated with ExosiRNA−OPN to assess the effect on activated HSCs (aHSCs). Immunofluorescence for α−SMA, an aHSCs marker, and sirius red staining were performed to assess ECM deposition. Finally, plasma OPN from patients with liver fibrosis was identified by ELISA assay.Results: Exosome-mediated siRNA delivery systems show high uptake and low toxicity. Besides, ExosiRNA−OPN suppressed HSCs activation and ECM deposition and more efficiently improved liver function when compared to naked siRNA-OPN. Moreover, ExosiRNA−OPN was assumed inhibiting TGF-β1 signaling activation, along with other fibrotic-related genes based on a GEO datasheet of liver fibrosis samples for correlation analyzes. ExosiRNA−OPN inhibited TGF-β1 signaling by decreasing high-mobility group box-1 (HMGB1). Plasma proteins from chronic HBV-induced fibrosis patients were identified that patients with high OPN expression correlates with more advanced fibrosis progression.Discussion: This study shows that exosome-mediated siRNA-OPN delivery may be an effective option for the treatment of liver fibrosis.

Purpose. Head and neck squamous cell carcinoma (HNSCC) exhibits a high mortality and morbidity rate, and its treatment is facing clinical challenges. Cuproptosis, a copper-dependent cell death process, can help derive new forms of cancer therapies. However, the potential of cuproptosis-related genes (CRGs) as novel biomarkers for risk prediction, screening, and prognosis remains to be further explained in HNSCC. Methods. We built a prognostic multigene signature with CRGs, which is associated with the tumor immune microenvironment (TME) by gene set enrichment analysis (GSEA), in the TCGA cohort. Furthermore, we systematically correlated risk signature with immunological characteristics in TME including tumor-infiltrating immune cells (TIICs), immune checkpoints, T cell inflamed score, and cancer immunity cycles. We also thoroughly investigated the biological functions of cuproptosis-associated lncRNAs and its immunological characteristics. Results. CRGs-related prognostic model showed good prediction performance. A higher risk score was associated with a poorer overall survival (OS) than those with low-risk scores, according to the results of the survival analysis ( p < 0.0001 ). The risk score was significantly related to the variable clinicopathological factors. Samples with high-risk scores had lower levels of CD8+ T cells infiltration. Immune therapy might be effective for the low-risk subtype of HNSCC patients ( p < 0.05 ). Moreover, 11 differentially expressed lncRNAs as the independent prognostic factor could also predict TME in an accurate manner. Conclusion. Our study identified and validated novel cuproptosis-related biomarkers for HNSCC prognosis and screening, which offer better insights into developing accurate, reliable, and novel cancer therapies in the era of precision medicine.

Although the advancement of radiotherapy significantly improves the survival of nasopharyngeal cancer (NPC), radioresistance associated with recurrence and poor outcomes still remains a daunting challenge in the clinical scenario. Currently, effective biomarkers and convenient detection methods for predicting radioresistance have not been well established. Here, the surface-enhanced Raman spectroscopy combined with proteomics is used to firstly profile the characteristic spectral patterns of exosomes secreted from self-established NPC radioresistance cells, and reveals specific variations of proteins expression during radioresistance formation, including collagen alpha-2 (I) chain (COL1A2) that is associated with a favorable prognosis in NPC and is negatively associated with DNA repair scores and DNA repair-related genes via bioinformatic analysis. Furthermore, deep learning model-based diagnostic model is generated to accurately identify the exosomes from radioresistance group. This work demonstrates the promising potential of exosomes as a novel biomarker for predicting the radioresistance and develops a rapid and sensitive liquid biopsy method that will provide a personalized and precise strategy for clinical NPC treatment.