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一种头颈癌的转录进展模型。

A transcriptional progression model for head and neck cancer.

作者信息

Ha Patrick K, Benoit Nicole E, Yochem Robert, Sciubba James, Zahurak Marianna, Sidransky David, Pevsner Jonathan, Westra William H, Califano Joseph

机构信息

Department of Otolaryngology-Head and Neck Surgery, Head and Neck Cancer Research Division, Johns Hopkins Medical Institutions, Baltimore, Maryland 21287, USA.

出版信息

Clin Cancer Res. 2003 Aug 1;9(8):3058-64.

Abstract

PURPOSE

A genetic progression model for head and neck squamous cell carcinoma (HNSC) has been established and implies the presence of transcriptional dysregulation as a consequence of accumulation of genetic alterations. Although expression array data have been provided for HNSC, the timing of transcriptional dysregulation in the progression from normal mucosa to dyplastic epithelium to invasive HNSC has not been described. Here, we describe a transcriptional progression model of HNSC.

EXPERIMENTAL DESIGN

Expression arrays representing >12,000 genes and expressed sequence tags were used to examine malignant lesions (M), premalignant lesions (PM), distant, histopathologically normal mucosa from patients with premalignant or malignant lesions (MN), and normal mucosa from the upper aerodigestive tract of patients with noncancer diagnoses (N). Significance analysis of microarrays, hierarchical clustering, and principal components analysis was used to identify genes with differential expression patterns.

RESULTS

Using a false discovery rate of <5% for significance analysis of microarray, the M group revealed 965 up-regulated and 1106 down-regulated genes relative to the N group. The PM group demonstrated 108 up-regulated and 226 down-regulated genes relative to the N group, whereas the M group demonstrated only 5 up-regulated and 13 down-regulated genes relative to the PM group. Both hierarchical cluster analysis and principal components analysis revealed a consistent separation between the N, PM, and M groups, with a closer association between the PM and M groups. To provide independent validation of the microarray data, quantitative reverse transcription-PCR was performed for a significantly up-regulated gene, integrin alpha 6, correlating well with microarray data (linear regression analysis, P < 0.0001).

CONCLUSIONS

Similarly to the genetic progression model of HNSC, this transcriptional model shows that the majority of alterations occurs before the development of malignancy and identifies key targets of transcriptional dysregulation during progression from a normal to a premalignant state and from a premalignant to a malignant state.

摘要

目的

已建立头颈部鳞状细胞癌(HNSC)的遗传进展模型,该模型表明由于基因改变的积累会导致转录失调。尽管已提供HNSC的表达阵列数据,但从正常黏膜发展为发育异常上皮再到侵袭性HNSC过程中转录失调的时间尚未明确。在此,我们描述了HNSC的转录进展模型。

实验设计

使用代表超过12,000个基因和表达序列标签的表达阵列,检测恶性病变(M)、癌前病变(PM)、患有癌前或恶性病变患者的远处组织病理学正常黏膜(MN)以及非癌症诊断患者上呼吸消化道的正常黏膜(N)。采用微阵列显著性分析、层次聚类和主成分分析来鉴定具有差异表达模式的基因。

结果

在微阵列显著性分析中,设定错误发现率<5%,M组相对于N组有965个基因上调和1106个基因下调。PM组相对于N组有108个基因上调和226个基因下调,而M组相对于PM组仅有5个基因上调和13个基因下调。层次聚类分析和主成分分析均显示N、PM和M组之间有一致的区分,且PM组和M组之间关联更紧密。为对微阵列数据进行独立验证,对一个显著上调的基因整合素α6进行了定量逆转录PCR,其结果与微阵列数据相关性良好(线性回归分析,P<0.0001)。

结论

与HNSC的遗传进展模型类似,该转录模型表明大多数改变发生在恶性肿瘤发生之前,并确定了从正常状态发展为癌前状态以及从癌前状态发展为恶性状态过程中转录失调的关键靶点。

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