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SNP 微阵列在癌前气道病变中染色体不稳定性的全基因组分析中的应用。

Application of SNP microarrays to the genome-wide analysis of chromosomal instability in premalignant airway lesions.

机构信息

University of Colorado, Anschutz Medical Campus, 12700, East 19th Avenue, RC2 9th Floor, Aurora, CO 80045.

出版信息

Cancer Prev Res (Phila). 2014 Feb;7(2):255-65. doi: 10.1158/1940-6207.CAPR-12-0485. Epub 2013 Dec 17.

Abstract

Chromosomal instability is central to the process of carcinogenesis. The genome-wide detection of somatic chromosomal alterations (SCA) in small premalignant lesions remains challenging because sample heterogeneity dilutes the aberrant cell information. To overcome this hurdle, we focused on the B allele frequency data from single-nucleotide polymorphism microarrays (SNP arrays). The difference of allelic fractions between paired tumor and normal samples from the same patient (delta-θ) provides a simple but sensitive detection of SCA in the affected tissue. We applied the delta-θ approach to small, heterogeneous clinical specimens, including endobronchial biopsies and brushings. Regions identified by delta-θ were validated by FISH and quantitative PCR in heterogeneous samples. Distinctive genomic variations were successfully detected across the whole genome in all invasive cancer cases (6 of 6), carcinoma in situ (3 of 3), and high-grade dysplasia (severe or moderate; 3 of 11). Not only well-described SCAs in lung squamous cell carcinoma, but also several novel chromosomal alterations were frequently found across the preinvasive dysplastic cases. Within these novel regions, losses of putative tumor suppressors (RNF20 and SSBP2) and an amplification of RASGRP3 gene with oncogenic activity were observed. Widespread sampling of the airway during bronchoscopy demonstrated that field cancerization reflected by SCAs at multiple sites was detectable. SNP arrays combined with delta-θ analysis can detect SCAs in heterogeneous clinical sample and expand our ability to assess genomic instability in the airway epithelium as a biomarker of lung cancer risk.

摘要

染色体不稳定性是癌症发生过程中的核心。由于样本异质性会稀释异常细胞信息,因此在小的癌前病变中对体细胞染色体改变(SCA)进行全基因组检测仍然具有挑战性。为了克服这一障碍,我们专注于单核苷酸多态性微阵列(SNP 阵列)中的 B 等位基因频率数据。同一患者的配对肿瘤和正常样本之间的等位基因分数差异(δ-θ)为受影响组织中的 SCA 提供了一种简单但敏感的检测方法。我们将 δ-θ 方法应用于小的、异质性的临床标本,包括支气管内活检和刷检。通过 FISH 和定量 PCR 在异质样本中验证了 δ-θ 识别的区域。在所有浸润性癌病例(6/6)、原位癌(3/3)和高级别异型增生(严重或中度;11/11)中,成功地在整个基因组中检测到了独特的基因组变异。不仅在肺鳞状细胞癌中发现了描述明确的 SCA,而且在多个癌前异型增生病例中还经常发现了几个新的染色体改变。在这些新区域中,观察到潜在肿瘤抑制因子(RNF20 和 SSBP2)的缺失和具有致癌活性的 RASGRP3 基因的扩增。支气管镜检查期间对气道的广泛采样表明,多个部位的 SCA 所反映的区域性癌变是可以检测到的。SNP 阵列结合 δ-θ 分析可以检测异质临床样本中的 SCA,并扩展我们评估气道上皮中基因组不稳定性作为肺癌风险生物标志物的能力。

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