The identification of cancer‐associated long noncoding RNA (lncRNA) is critical for us to understand cancer pathogenesis and development. The aim of this study was to evaluate the expression profile of the lncRNA SPRY4‐IT1 in cervical cancer and to identify its clinical significance in cancer progression. The expression levels of SPRY4‐IT1 in cervical cancer tissues were measured by quantitative real‐time PCR, and its correlation with overall survival of cervical cancer patients was analyzed statistically. Our results showed that the expression levels of SPRY4‐IT1 were higher in cervical cancer tissues than in adjacent normal tissues. Patients with higher SPRY4‐IT1 expression had advanced clinical characteristics and a shorter overall survival time than those with lower SPRY4‐IT1 expression. Moreover, multivariate analysis showed that relative SPRY4‐IT1 expression was an independent predictor of overall survival in patients with cervical cancer. In addition, the model we have established shows a good prediction of the probability of 5‐year overall survival of patients according to the c‐index and calibration curve. Collectively, our data suggest that lncRNA SPRY4‐IT1 may be a novel molecule involved in cervical cancer progression, which may be of use as both a potential predictor and therapeutic target.
PurposeExosomes are key mediators of cellular communication by transporting molecules, including long noncoding RNAs (lncRNAs), and have been regarded as promising non-invasive biomarkers. This study aimed to evaluate the expression pattern and clinical significance of serum exosomal lncRNA antisense hypoxia inducible factor (aHIF) in epithelial ovarian cancer (EOC).Patients and methodsSixty-two EOC patients in Obstetrics and Gynecology Hospital of Fudan University were enrolled. The expression levels of aHIF in tissues and serum exosomes were examined by RT-qPCR. The origin of serum exosomal aHIF was explored in vitro and in vivo. Univariate and multivariate Cox regression analyses were used to evaluate the prognostic factors of EOC. A prognostic predictive nomogram was formulated in R software.ResultsWe isolated exosomes, identified exosomal aHIF in the serum of EOC patients. The expression of serum exosomal aHIF was higher in EOC patients and was correlated with the aHIF level in EOC tissues. In vitro and in vivo, the results indicated that serum exosomal aHIF was derived from tumor cells. Kaplan-Meier survival analysis demonstrated that EOC patients with higher serum exosomal aHIF expression had poorer overall survival. Cox multivariate regression model revealed that FIGO stage, residual tumor size, and serum exosomal aHIF level were independent prognostic factors of EOC. Based on the prognostic value of serum exosomal aHIF, we established a nomogram model that showed a good predictive ability for EOC patients.ConclusionSerum exosomal aHIF is overexpressed in EOC and can serve as a noninvasive predictive biomarker for unfavorable prognosis.
Nanoparticles of noble metals dispersed on solid support have been extensively utilized for catalyzing chemical reactions for energy conversion, environmental remediation, and chemical industry for their remarkable catalytic performance. [1][2][3][4] To maneuver the catalytic performance of these materials, tremendous efforts have been focused on the control of metal nanoparticles, including size and shape, [5][6][7] composition, [8] and chemical ordering. [9] At the meantime, the influence of the support on catalytic properties maximizing the number of active sites accessible for reaction have been well recognized. For example, the size distribution [10] and structural stability [11] of metal nanoparticles could be adjusted via the selection of the support. Furthermore, encapsulation of the metals by support species under high temperature treatment are widely observed, which finally results in the establishment of the classical strong metal-support interaction (SMSI). [12] However, the physicochemical interaction between metal and support cannotThe catalytic properties of nanometals are strongly dependent on their electronic states which, are influenced by the interaction with the supports. However, a precise manipulation of the electronic interaction is lacking, and the nature of the interaction is still ambiguous. Herein, using Au/ZnFe x Co 2−x O 4 (x = 0-2) as a model system with continuously tuned Fermi levels of supports, the electronic structure of the Au catalyst can be precisely controlled by changing the Fermi level of the support, which arises from the charge redistribution between the two phases. A higher Fermi level of ZnFe 2 O 4 support makes nano-Au negatively charged and thus facilitates the oxidation of CO, and in contrast, a lower Fermi level of ZnCo 2 O 4 support makes nano-Au positively charged and is preferential to the oxidation of benzyl alcohol. This work represents a solid step towards exploration of advanced catalysts with deliberate design of electronic structure and catalytic properties.
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