Sunitinib resistance is, nowadays, the major challenge for advanced renal cell carcinoma patients. Illuminating the potential mechanisms and exploring effective strategies to overcome sunitinib resistance are highly desired. We constructed a reliable gene signature which may function as biomarkers for prediction of sunitinib sensitivity and clinical prognosis. The gene expression profiles were obtained from The Cancer Genome Atlas database. By performing GEO2R analysis, numerous differentially expressed genes (DEGs) were found to be associated with sunitinib resistance. To acquire more precise DEGs, we integrated three different microarray datasets. Functional analysis revealed that these DEGs were mainly involved in Rap1 signaling pathway, p53 signaling pathway and Ras signaling pathway. Then, top five hub genes, BIRC5, CD44, MUC1, TF, CCL5, were identified from protein-protein interaction (PPI) network. Sub-network analysis carried out by MCODE plugin revealed that key DEGs were related with PI3K-Akt signaling pathway, Rap1 signaling pathway and VEGF signaling pathway. Next, we established sunitinib-resistant OS-RC-2 and 786-O cell lines and validated the expression of five hub genes in cell lines. To further evaluate the potentials of five-gene signature for predicting clinical prognosis, we analyzed RCC patients with gene expressions and overall survival information from two independent patient datasets. The Kaplan-Meier estimated the OS of RCC patients in the low- and high-risk groups according to gene expression signature. Multivariate Cox regression analysis indicated that the prognostic power of five-gene signature was independent of clinical features. In conclusion, we developed a five-gene signature which can predict sunitinib sensitivity and OS for advanced RCC patients, providing novel insights into understanding of sunitinib-resistant mechanisms and identification of RCC patients with poor prognosis.
Background:Dendritic cells (DCs) play an important role in host defense against pathogen infection. DC-specific intercellular adhesion molecule-3-grabbing nonintegrin (SIGN) is a group II C-type lectin receptor and specifically expressed on the surface of DCs. This study aimed to determine whether DC-SIGN affects intracellular signaling activation, Th1/Th2 imbalance and aspergillus immune evasion in aspergillus infection, and explore the application of DC-SIGN-modified DCs in immunotherapy.Methods:DCs were first obtained from the mononuclear cells of peripheral blood. The interferon (IFN)-γ and dexamethasone (Dex) were used to stimulate DCs. The expression of DC-SIGN, Th1 and Th2 cytokines, and the capacity of DCs in stimulating T cells proliferation and phagocytosis, and nuclear factor (NF)-κB activation were analyzed. In addition, adenovirus expression vector Ad-DC-SIGN was generated to transfect DCs. Mannan was used to block DC-SIGN signaling for confirming the involvement of DC-SIGN function in Aspergillus fumigatus (Af)-induced DCs maturation. The unpaired, two-tailed Student's t-test was used in the comparisons between two groups.Results:Exogenous IFN-γ could activate Af-induced DCs and promote the Th0 cells toward Th1 profile (interleukin [IL]-12 in IFN-γ/Af group: 50.96 ± 4.38 pg/ml; control/Af group: 29.70 ± 2.00 pg/ml, t = 10.815, P < 0.001). On the other hand, Dex inhibited the secretion of Th2 cytokines (IL-10 in Dex/Af group: 5.27 ± 0.85 pg/ml; control/Af group: 15.14 ± 1.40 pg/ml, t = 14.761, P < 0.001)), and successfully caused immunosuppression. After transfection with Ad-DC-SIGN, DCs have improved phagocytosis (phagocytosis rates in Ad-DC-SIGN group: 74.0% ± 3.4%; control group: 64.7% ± 6.8%, t = 3.104, P = 0.013). There was more Th1 cytokine secreted in the Af-induced DC-SIGN modified DCs (IL-12 in Ad-DC-SIGN/Af group: 471.98 ± 166.31 pg/ml; control/Af group: 33.35 ± 5.98 pg/ml, t = 6.456, P = 0.001), correlated to the enhanced NF-κB activation.Conclusion:Overexpressing DC-SIGN in DCs had a protective function on aspergillosis.
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.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.