Expression of miR-296-5p as predictive marker for radiotherapy resistance in early-stage laryngeal carcinoma

miR-296-5p表达作为早期喉癌放射治疗耐药性的预测标志物

阅读:1

Abstract

PURPOSE: Definitive radiation therapy is the mainstay of treatment for early stage laryngeal squamous cell carcinoma (LSCC). However, up to 30% of the patients do not respond to radiotherapy. Unfortunately, we are unable to predict which tumors are likely to respond to radiation, and which will be resistant and persist. Therefore, the development of novel markers to predict response to radiotherapy is urgently needed. This study was designed to evaluate the expression pattern of microRNAs (miRNAs) in LSCC in order to identify markers capable of segregating radioresistant and radiosensitive tumors and to investigate the relationship between the expression of these miRNAs and the prognosis of LSCC. METHODS: The expression profile of 667 miRNAs was determined in an initial screening of nine early-stage LSCC samples (5 radioresistant and 4 radiosensitive) using TaqMan Low-Density Array (TLDA). Real-time polymerase chain reactions were performed to validate the expression of selected miRNAs in an expanded LSCC cohort (20 radioresistant and 14 radiosensitive). The miRNA expression level was scored as high or low based on the median of the expression in the LSCC samples. RESULTS: A comprehensive miRNA expression profiling enabled the identification of four miRNAs (miR-296-5p miR-452, miR-183* and miR-200c) differentially expressed in radioresistant LSCC. Moreover, the analysis of additional 34 LSCC samples, confirmed the expression of miR-296-5p as significantly related to radioresistance (p = 0.002) as well as an association of this marker with recurrence (p = 0.025) in early stage laryngeal cancer. CONCLUSIONS: This study indicates that miR-296-5p expression is associated with resistance to radiotherapy and tumor recurrence in early stage LSCC, showing the feasibility of this marker as a novel prognostic factor for this malignance. Furthermore, miR-296-5p expression could be helpful in the identification of tumors resistant to radiotherapy; thus aiding the clinicians in the choice of the best therapeutic scheme to be used in each case.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。