Elevated expression of CD93 promotes angiogenesis and tumor growth in nasopharyngeal carcinoma.

Biochem Biophys Res Commun

Department of Otorhinolaryngology Head and Neck Surgery, Affiliated Hospital of Nantong University, Nantong, Jiangsu Province, China. Electronic address:

Published: August 2016

CD93, also known as the complement component C1q receptor (C1qRp), has been reported to promote the progression of some cancer types. However, the expression and physiological significance of CD93 in nasopharyngeal carcinoma (NPC) remain largely elusive. In this study, we first examined the expression of CD93 in NPC and experimentally manipulated its expression. We observed that vascular CD93 expression is elevated in NPC and is correlated with T classification, N classification, distant metastasis, clinical stage and poor prognosis (all P < 0.05). In addition, overexpression of CD93 promoted angiogenesis in vitro. What's more, we found that CD93 was highly expressed in NPC tissues and cells, and the regulation of CD93 on cell proliferation was determined by cell counting kit (CCK)-8 assay and cell cycle analyses. Our findings provide unique insight into the pathogenesis of NPC and underscore the need to explore novel therapeutic targets such as CD93 to improve NPC treatment.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.bbrc.2016.05.146DOI Listing

Publication Analysis

Top Keywords

expression cd93
8
nasopharyngeal carcinoma
8
cd93
5
elevated expression
4
cd93 promotes
4
promotes angiogenesis
4
angiogenesis tumor
4
tumor growth
4
growth nasopharyngeal
4
carcinoma cd93
4

Similar Publications

Background: Adaptive cellular therapy (ACT), particularly chimeric antigen receptor (CAR)-T cell therapy, has been successful in the treatment of hemopoietic malignancies. However, poor trafficking of administered effector T cells to the tumor poses a great hurdle for this otherwise powerful therapeutic approach in solid cancers. Our previous study revealed that targeting CD93 normalizes tumor vascular functions to improve immune checkpoint blockade therapy.

View Article and Find Full Text PDF
Article Synopsis
  • Gastric cancer has a poor prognosis and varied cellular characteristics, highlighting the need for a better understanding of its tumor microenvironment and heterogeneity to create effective treatments.
  • Researchers analyzed single-cell RNA sequencing data and used machine learning to identify 18 significant genes related to gastric cancer, with a particular focus on NFKBIE, which showed a strong correlation with patient risk levels.
  • The study suggests NFKBIE could serve as a potential biomarker and therapeutic target, with certain drugs like gemcitabine and chloropyramine possibly being effective against high-risk gastric cancer patients.
View Article and Find Full Text PDF

Avian pathogenic alters complement gene expression in chicken erythrocytes.

Br Poult Sci

January 2025

Department of Preventive Veterinary Medicine, College of Veterinary Medicine, Shanxi Agricultural University, Jinzhong, China.

1. Avian () causes significant losses in livestock by inducing morbidity and mortality. Erythrocytes, the most abundant in blood, possess dual functions of oxygen transportation and immune regulation.

View Article and Find Full Text PDF

Background: Polycystic ovary syndrome (PCOS) is a complex endocrine disorder with various contributing factors. Understanding the molecular mechanisms underlying PCOS is essential for developing effective treatments. This study aimed to identify hub genes and investigate potential molecular mechanisms associated with PCOS through a combination of bioinformatics analysis and Mendelian randomization (MR).

View Article and Find Full Text PDF

This study aimed to investigate the molecular mechanisms of periodontitis and identify key immune-related biomarkers using machine learning and Mendelian randomization (MR). Differentially expressed gene (DEG) analysis was performed on periodontitis datasets GSE16134 and GSE10334 from the Gene Expression Omnibus (GEO) database, followed by weighted gene co-expression network analysis (WGCNA) to identify relevant gene modules. Various machine learning algorithms were utilized to construct predictive models, highlighting core genes, while MR assessed the causal relationships between these genes and periodontitis.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!