MiR-21/miR-375 ratio is an independent prognostic factor in patients with laryngeal squamous cell carcinoma.
Year: 2015
Type: article
Study design: Observational Study
Abstract: We sought to identify microRNAs that exhibit altered expression in laryngeal squamous cell carcinoma (SCC) and to determine whether microRNA expression is predictive of disease. This study was divided into three steps: (1) The expression of six miRNAs, such as up-regulated miR-223, miR-142-3p, miR-21, miR-16, miR-23a and down-regulated miR-375, was evaluated using total RNA isolated from freshly-frozen primary tumors and non-cancerous laryngeal squamous epithelial tissues and analyzed using quantitative real-time polymerase chain reaction (qRT-PCR). (2) We also investigated the mRNA expression levels of processing elements (RNASEN, DGCR8, and DICER1) that participate in miRNA-biogenesis pathway. (3) We analyzed the relationships between the expression levels of these miRNAs and the clinicopathologic parameters of laryngeal SCC patients. In this study, we found that: (1) A marked difference in the microRNA expression pattern was observed between tumors and non-cancerous tissue. With regard to miRNA-processing elements, the expression level of RNASEN was higher in laryngeal SCC than in normal epithelium (P<0.01). (2) The miR-21/miR-375 expression ratio was highly sensitive and specific for disease prediction. Kaplan-Meier analysis revealed a significant association between high expression of miR-21/miR-375 in cancerous tissue and a worse prognosis (p=0.032). (3) Furthermore, the expression ratio of miR-21/mir-375 in patients with stage (III-IV) tumors was significantly higher than that in those with stage (I-II) tumors (p=0.006). These data suggest that the pattern of microRNA expression in primary laryngeal SCC tissues is exhibiting strong predictive potential.
Source: Europe PMC (PubMed Central)
Authors: An Hu, Jing-Juan Huang, Wei-Hua Xu, Xiao-Jie Jin, Ji-Ping Li, Yuan-Jia Tang, Xin-Fang Huang, Hui-Juan Cui, Guang-Bin Sun, Rui-Lin Li, Jun-Li Duan
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2242147159