Spatiotemporally sequential delivery of biomimetic liposomes potentiates glioma chemotherapy.

As one of the most challenging cancers, glioma still lacks efficient therapeutic treatment in clinics. The dilemmas of nanodrug-based therapies for glioma are due not only the limited permeability of the blood-brain barrier (BBB) but also the deficiency of targeting tumor lesions. Thus, spatiotemporally sequential delivery of therapeutics from BBB-crossing to glioma accumulation is considered a strategy to obtain better outcomes. Here, we developed a biomimetic chemotherapy nanodrug composed of the hybrid membrane envelope of U87 cell membranes and RAW264.7 cell membranes, and the core of paclitaxel (PTX)-loaded liposome (PTX@C-MMCL). In the research, PTX@C-MMCL showed superior ability to cross the BBB via RAW264.7 cell membranes and accurate targeting to the brain tumor lesions relying on the homotypic targeting capacity of U87 cell membranes. Furthermore, PTX@C-MMCL can maintain a prolonged circulation in vivo. Importantly, PTX@C-MMCL effectively inhibited the development of glioma. Conclusively, our biomimetic nanodrug holds great potential for brain tumor targeting therapy.

Application of indocyanine green-mediated fluorescence molecular imaging technology in liver tumors resection: a systematic review and meta-analysis.

Background: This meta-analysis was dedicated to evaluating the safety and effectiveness of indocyanine green (ICG) -mediated fluorescence molecular imaging (FMI) technology in liver tumors resection. Methods: A literature search of PubMed, Embase databases, Cochrane Library, and Web of Science was performed to identify all clinical controlled studies exploring the effects of fluorescence imaging on liver tumors resection. Quality assessment and data extraction of studies were conducted independently by 3 reviewers. Mean difference (MD) and odds ratio (OR) with 95% confidence interval (CI) were calculated using a fixed-effects or random-effects model. The meta-analysis was performed with RevMan 5.3 software. Results: 14 retrospective cohort studies (RCSs) involving a total of 1227 patients were finally included. The results showed that Fluorescence-assisted liver tumors resection could improve the R0 resection rate (OR = 2.63; 95% CI: 1.46~4.73, p = 0.001), reduce overall complications (OR = 0.66; 95% CI: 0.44~0.97, p = 0.04), biliary fistula (OR = 0.20; 95% CI: 0.05~0.77, p = 0.02), intraoperative blood loss (MD = -70.76, 95% CI: -106.11 to -35.41; p < 0.0001), and shortens hospital stay (MD = -1.41, 95% CI: -1.90 to -0.92; p < 0.00001). There were no significant differences in the incidences of operative time (MD = -8.68, 95% CI: -18.59 to -1.22; p = 0.09), complications of grade III or above (OR = 0.73; 95% CI: 0.43~1.25, p = 0.26), liver failure (OR = 0.86; 95% CI: 0.39~1.89, p = 0.71), and blood transfusion (OR = 0.66; 95% CI: 0.42~1.03, p = 0.07). Conclusion: Current evidence suggests that ICG-mediated FMI technology could enhance the clinical effectiveness of patients with liver tumors resection and is clinically worthy of promotion. Systematic review registration: PROSPERO, identifier CRD42022368387.

Identification of potential biomarkers associated with immune infiltration in papillary renal cell carcinoma.

BACKGROUND: Immunotherapeutic approaches have recently emerged as effective treatment regimens against various types of cancer. However, the immune-mediated mechanisms surrounding papillary renal cell carcinoma (pRCC) remain unclear. This study aimed to investigate the tumor microenvironment (TME) and identify the potential immune-related biomarkers for pRCC. METHODS: The CIBERSORT algorithm was used to calculate the abundance ratio of immune cells in each pRCC samples. Univariate Cox analysis was used to select the prognostic-related tumor-infiltrating immune cells (TIICs). Multivariate Cox regression analysis was performed to develop a signature based on the selected prognostic-related TIICs. Then, these pRCC samples were divided into low- and high-risk groups according to the obtained signature. Analyses using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were performed to investigate the biological function of the DEGs (differentially expressed genes) between the high- and low-risk groups. The hub genes were identified using a weighted gene co-expression network analysis (WGCNA) and a protein-protein interaction (PPI) analysis. The hub genes were subsequently validated by multiple clinical traits and databases. RESULTS: According to our analyses, nine immune cells play a vital role in the TME of pRCC. Our analyses also obtained nine potential immune-related biomarkers for pRCC, including TOP2A, BUB1B, BUB1, TPX2, PBK, CEP55, ASPM, RRM2, and CENPF. CONCLUSION: In this study, our data revealed the crucial TIICs and potential immune-related biomarkers for pRCC and provided compelling insights into the pathogenesis and potential therapeutic targets for pRCC.