摘要
目的通过全基因组寡核苷酸基因芯片构建喉部纯化组织基因表达谱，筛选与喉癌相关的候选靶基因。方法采用R．NA保护技术保护组织标本，激光捕获显微切割纯化分离8例声门型喉癌标本中癌细胞及其相对应的癌旁相对正常的黏膜上皮细胞，结合HGU133．Plus2．0芯片技术，构建16例喉部纯化组织标本全基因组表达谱，筛选出喉癌相关靶基因；选择部分特异性的候选靶基因通过荧光定量PCR在mRNA水平检测基因的表达情况。结果对16例喉部纯化组织基因组表达谱进行统计学处理及聚类分析，筛选出与喉癌发病相关的候选靶基因2351个；假阳性率为0．63％。对特异性候选基因MMP12、KRT16、RARB、PRBImRNA的荧光RT-PCR检测结果与基因表达谱的结果具有一致性。结论利用全基因组基因芯片构建基因表达谱，可准确、高效地筛选出喉癌相关的候选靶基因，为寻找喉癌临床早期诊断的分子标记物及喉癌潜在的药物作用靶分子奠定坚实的理论基础。
Objective To examine the gene expression profile of laryngeal squamous cell carcinoma （LSCC） by combination of laser capture microdissectiou （LCM） and microarray and to identify genetic changes in disease pathogenesis. Methods The study analysed 8 matched pairs of specimens of glottic carcinoma of larynx and histologically normal epithelium tissues adjacent to the carcinoma preserved in the RNAlater reagent. A genome-wide transeriptome analysis was performed by probing 16 eDNA mieroarrays with fluoreseentAabeled amplified RNA derived from laser capture mierodissected cells. Real-time quantitative （RT-PCR） of tissue microarray was used to validate the reliability of cDNA microarrays. Results Significant analysis of microarray（SAM） software and hierarchical cluster analysis of the expressed genes showed that 2351 genes was significantly expressed respectively according to different analysis method （false discover rate =0.63% ）. A selected set of MMP12 ,KRT16, RARB ,PRB1 genes was identified to be consistent with array data by RT-PCR. Conclusions The analysis of gene ontology and pathway distributions futher highlighted genes that may be critically important to laryngeal carcinogenesis. The results strongly suggest that this new approach may facilitate the identification of clinical molecular markers of disease and novel potential therapeutic targets for LSCC.
出处
《中华耳鼻咽喉头颈外科杂志》
CAS
CSCD
北大核心
2008年第9期696-700,共5页
Chinese Journal of Otorhinolaryngology Head and Neck Surgery
基金
国家自然科学基金（30572020）
关键词
喉肿瘤
癌
鳞状细胞
寡核苷酸序列分析
激光捕获显微切割
Laryngeal neoplasms
Carcinoma, squamous cell
Oligonucleotide array sequenceanalysis
Laser capture microdissection
