Representational Oligonucleotide Microarray Analysis (ROMA) array for Copy Number Variation Detection.. Homo sapiens

The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to identify genes critical to the development and progression of cancer. We provide a bioinformatic analysis of copy number variation and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We individually examined the copy number variation and DNA methylation for 44 primary ovarian cancer samples and 7 ovarian normal samples using our MOMA-ROMA technology and Affymetrix expression data as well as 379 tumor samples analyzed by The Cancer Genome Atlas. We have identified 346 genes with significant deletions or amplifications among the tumor samples. Utilizing associated gene expression data we predict 156 genes with significantly altered copy number and correlated changes in expression. We identify changes in DNA methylation and expression for all amplified and deleted genes. We predicted 615 potential oncogenes and tumor suppressors candidates by integrating these multiple genomic and epigenetic data types. This ROMA experiment was performed on Ovarian Tumor samples using the same platform as previously reported by Navin, N. et. al. Genome Res. 2010 Jan;20(1):68-80 (PMID: 19903760). Analysis of the array data was performed as previously reported in Chen, S. et. al. Cancer Biol Ther. 2008 Nov;7(11):1793-802. (PMID: 18836286 ). Overall design: The genomic DNA from each tumor was labeled with Cy5 and hybridized to an 85K Bgl2 ROMA Microarray. A normal reference male fibroblast was labeled with Cy3 as a control. The value data repesents a log ratio. (As previously reported Chen, S. et. al. Cancer Biol Ther. 2008 Nov;7(11):1793-802. PMID: 18836286 ).

从原发性肿瘤细胞中鉴定遗传与表观遗传改变，已成为筛选癌症发生发展关键调控基因的常规研究手段。本数据集提供了覆盖卵巢癌细胞遗传全景的拷贝数变异（copy number variation）与DNA甲基化的生物信息学分析。
我们采用MOMA-ROMA技术与Affymetrix表达谱数据，对44例原发性卵巢癌样本及7例卵巢正常样本的拷贝数变异与DNA甲基化水平分别进行了检测；同时纳入379例经癌症基因组图谱（The Cancer Genome Atlas, TCGA）分析的肿瘤样本。
本研究在肿瘤样本中鉴定出346个存在显著缺失或扩增的基因。结合关联基因表达谱数据，我们预测得到156个拷贝数发生显著改变且伴随表达水平相关变化的基因。我们还对所有扩增与缺失基因的DNA甲基化及表达改变情况进行了系统鉴定。通过整合多组基因组与表观基因组数据类型，我们共预测出615个潜在致癌基因与抑癌基因候选靶点。
本次ROMA实验采用与Navin N.等发表于*Genome Res.* 2010 Jan;20(1):68-80（PMID: 19903760）中一致的实验平台，在卵巢肿瘤样本中完成。阵列数据分析方法参照Chen S.等发表于*Cancer Biol Ther.* 2008 Nov;7(11):1793-802（PMID: 18836286）的研究方案进行。
整体实验设计：将每例肿瘤的基因组DNA用Cy5标记，与85K Bgl2 ROMA微阵列进行杂交；以Cy3标记的正常男性成纤维细胞作为对照样本。数据值以对数比值（log ratio）形式呈现（参照Chen S.等发表于*Cancer Biol Ther.* 2008 Nov;7(11):1793-802，PMID: 18836286的报道）。