Harada Tomohiko, Chelala Claude, Crnogorac-Jurcevic Tatjana, Lemoine Nicholas R
Centre for Molecular Oncology, Cancer Research UK, Institute of Cancer, Barts and The London School of Medicine and Dentistry, Queen Mary, University of London, London, UK.
Pancreatology. 2009;9(1-2):13-24. doi: 10.1159/000178871. Epub 2008 Dec 12.
BACKGROUND/AIMS: Microarray-based comparative genomic hybridisation (CGH) has allowed high-resolution analysis of DNA copy number alterations across the entire cancer genome. Recent advances in bioinformatics tools enable us to perform a robust and highly sensitive analysis of array CGH data and facilitate the discovery of novel cancer-related genes.
We analysed a total of 29 pancreatic ductal adenocarcinoma (PDAC) samples (6 cell lines and 23 microdissected tissue specimens) using 1-Mb-spaced CGH arrays. The transcript levels of all genes within the identified regions of genetic alterations were then screened using our Pancreatic Expression Database.
In addition to 238 high-level amplifications and 35 homozygous deletions, we identified 315 minimal common regions of 'non-random' genetic alterations (115 gains and 200 losses) which were consistently observed across our tumour samples. The small size of these aberrations (median size of 880 kb) contributed to the reduced number of candidate genes included (on average 12 Ensembl-annotated genes). The database has further specified the genes whose expression levels are consistent with their copy number status. Such genes were UQCRB, SQLE, DDEF1, SLA, ERICH1 and DLC1, indicating that these may be potential target candidates within regions of aberrations.
This study has revealed multiple novel regions that may indicate the locations of oncogenes or tumour suppressor genes in PDAC. Using the database, we provide a list of novel target genes whose altered DNA copy numbers could lead to significant changes in transcript levels in PDAC.
背景/目的：基于微阵列的比较基因组杂交（CGH）技术已能够对整个癌症基因组的DNA拷贝数改变进行高分辨率分析。生物信息学工具的最新进展使我们能够对阵列CGH数据进行强大且高度灵敏的分析，并有助于发现新的癌症相关基因。
我们使用间隔为1兆碱基的CGH阵列分析了总共29个胰腺导管腺癌（PDAC）样本（6个细胞系和23个显微切割组织标本）。然后使用我们的胰腺表达数据库筛选已识别的基因改变区域内所有基因的转录水平。
除了238个高水平扩增和35个纯合缺失外，我们还识别出315个“非随机”基因改变的最小共同区域（115个增益和200个缺失），这些区域在我们所有的肿瘤样本中均一致被观察到。这些畸变的小尺寸（中位数大小为880 kb）导致包含的候选基因数量减少（平均12个经Ensembl注释的基因）。该数据库进一步明确了那些表达水平与其拷贝数状态一致的基因。此类基因有UQCRB、SQLE、DDEF1、SLA、ERICH1和DLC1，这表明这些可能是畸变区域内潜在的候选靶点。
本研究揭示了多个可能指示PDAC中癌基因或肿瘤抑制基因位置的新区域。利用该数据库，我们提供了一份新的靶基因列表，其DNA拷贝数的改变可能导致PDAC转录水平的显著变化。
