ZIF-8, as an important photoresponsive metal− organic framework (MOF), holds great promise in the field of cancer theranostics owing to its versatile physiochemical properties. However, its photocatalytic anticancer application is still restricted because of the wide bandgap and specific response to ultraviolet light. Herein, we developed lanthanidedoped nanoparticles (LDNPs) coated with Fe/Mn bimetaldoped ZIF-8 (LDNPs@Fe/Mn-ZIF-8) for second near-infrared (NIR-II) imaging-guided synergistic photodynamic/chemodynamic therapy (PDT/CDT). The LDNPs were synthesized by encapsulating an optimal Yb 3+ /Ce 3+ -doped active shell on the NaErF 4 :Tm core to achieve dual-mode red upconversion (UC) and NIR-II downconversion (DC) emission upon NIR laser irradiation. At the optimal doping concentration, the UC and DC NIR-II emission intensities of LDNPs were increased 30.2and 13.2-fold above those of core nanoparticles, which endowed LDNPs@Fe/Mn-ZIF-8 with an outstanding capability to carry out UC-mediated PDT and NIR-II optical imaging. In addition, the dual doping of Fe 2+ /Mn 2+ markedly decreased the bandgap of the ZIF-8 photosensitizer from 5.1 to 1.7 eV, expanding the excitation threshold of ZIF-8 to the visible light region (∼650 nm), which enabled Fe/Mn-ZIF-8 to be efficiently excited by UC photons to achieve photocatalytic-driven PDT. Furthermore, Fe 2+ /Mn 2+ ions could be responsively released in the tumor microenvironment through degradation of Fe/Mn-ZIF-8, thereby producing hydroxyl radicals (•OH) by Fenton/Fenton-like reactions to realize CDT. Meanwhile, the degradation of Fe/Mn-ZIF-8 endowed the nanosystems with tumor self-enhanced NIR-II imaging function, providing precise guidance for CDT/PDT.
Hepatocellular carcinoma (HCC) is one of the most lethal cancers worldwide, which is associated with a variety of risk factors. Cancer stem cells are self-renewal cells, which can promote the occurrence and metastasis of tumors and enhance the drug resistance of tumor treatment. This study aimed to develop a stemness score model to assess the prognosis of hepatocellular carcinoma (HCC) patients for the optimization of treatment. The single-cell sequencing data GSE149614 was downloaded from the GEO database. Then, we compared the gene expression of hepatic stem cells and other hepatocytes in tumor samples to screen differentially expressed genes related to stemness. R package “clusterProfiler” was used to explore the potential function of stemness-related genes. We then constructed a prognostic model using LASSO regression analysis based on the TCGA and GSE14520 cohorts. The associations of stemness score with clinical features, drug sensitivity, gene mutation, and tumor immune microenvironment were further explored. R package “rms” was used to construct the nomogram model. A total of 18 stemness-related genes were enrolled to construct the prognosis model. Kaplan-Meier analysis proved the good performance of the stemness score model at predicting overall survival (OS) of HCC patients. The stemness score was closely associated with clinical features, drug sensitivity, and tumor immune microenvironment of HCC. The infiltration level of CD8+ T cells was lower, and tumor-associated macrophages were higher in patients with high-stemness score, indicating an immunosuppressive microenvironment. Our study established an 18 stemness-related gene model that reliably predicts OS in HCC. The findings may help clarify the biological characteristics and progression of HCC and help the future diagnosis and therapy of HCC.
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