Luminogens with aggregation-induced emission (AIEgens) have been widely applied in the field of photodynamic therapy. Among them, aggregation-induced emission photosensitizers (AIE–PSs) are demonstrated with high capability in fluorescence and photoacoustic bimodal imaging, as well as in fluorescence imaging-guided photodynamic therapy. They not only improve diagnosis accuracy but also provide an efficient theranostic platform to accelerate preclinical translation as well. In this short review, we divide AIE–PSs into three categories. Through the analysis of such classification and construction methods, it will be helpful for scientists to further develop various types of AIE–PSs with superior performance.
We investigated the role of the competing endogenous RNA (ceRNA) network in the development and progression of pancreatic adenocarcinoma (PAAD). We analyzed the expression profiles of PAAD and normal pancreatic tissues from multiple GEO databases and identified 457 differentially expressed circular RNAs (DEcircRNAs), 19 microRNAs (DEmiRNAs) and 1993 mRNAs (DEmRNAs). We constructed a ceRNA network consisting of 4 DEcircRNAs, 3 DEmiRNAs and 149 DEmRNAs that regulates the NF-kappa B, PI3K-Akt, and Wnt signaling pathways. We then identified and validated five hub genes, CXCR4, HIF1A, ZEB1, SDC1 and TWIST1, which are overexpressed in PAAD tissues. The expression of CXCR4, HIF1A, ZEB1, and SDC1 in PAAD was regulated by circ-UBAP2 and hsa-miR-494. The expression of CXCR4 and ZEB1 correlated with the levels of M2 macrophages, T-regulatory cells (Tregs) and exhausted T cells in the PAAD tissues. The expression of CXCR4 and ZEB1 positively correlated with the expression of CTLA-4 and PD-1. This suggests that CXCR4 and ZEB1 proteins inhibit antigen presentation and promote immune escape mechanisms in PAAD cells. In summary, our data suggest that the circUBAP2-mediated ceRNA network modulates PAAD by regulating the infiltration and function of immune cells.
The tumor microenvironment (TME) has attracted attention owing to its essential role in tumor initiation, progression, and metastasis. With the emergence of immunotherapies for various cancers, and their high efficacy, an understanding of the TME in gastric cancer (GC) is critical. The aim of this study was to investigate the effect of various components within the GC TME, and to identify mechanisms that exhibit potential as therapeutic targets. The ESTIMATE algorithm was used to quantify immune and stromal components in GC samples, whose clinicopathological significance and relationship with predicted outcomes were explored. Low tumor mutational burden and high M2 macrophage infiltration, which are considered immune suppressive characteristics and may be responsible for unfavorable prognoses in GC, were observed in the high stromal group (HR = 1.585; 95% CI, 1.112-2.259; P = 0.009). Furthermore, weighted correlation network, differential expression, and univariate Cox analyses were used, along with machine learning methods (LASSO and SVM-RFE), to reveal genome-wide immune phenotypic correlations. Eight stromal-relevant genes cluster (FSTL1, RAB31, FBN1, ANTXR1, LRRC32, CTSK, COL5A2, and ENG) were identified as adverse prognostic factors in GC. Finally, using a combination of TIMER database and single-sample gene set enrichment analyses, we found that the identified genes potentially contribute to macrophage recruitment and polarization of tumor-associated macrophages. These findings provide a different perspective into the immune microenvironment and indicate potential prognostic and therapeutic targets for GC immunotherapies.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.